diff --git "a/citations.jsonl" "b/citations.jsonl"
deleted file mode 100644--- "a/citations.jsonl"
+++ /dev/null
@@ -1,7877 +0,0 @@
-{"year":"2016","title":"A Case Study of Complex Graph Analysis in Distributed Memory: Implementation and Optimization","authors":["GM Slota, S Rajamanickam, K Madduri"],"snippet":"... Focusing on one of the largest publicly-available hyperlink graphs (the 2012 Web Data Commons graph1, which was in- turn extracted from the open Common Crawl web corpus2), we develop parallel ... 1http://webdatacommons.org/hyperlinkgraph/ 2http://commoncrawl.org ...","url":["http://www.personal.psu.edu/users/g/m/gms5016/pub/Dist-IPDPS16.pdf"]}
-{"year":"2016","title":"A Convolutional Encoder Model for Neural Machine Translation","authors":["J Gehring, M Auli, D Grangier, YN Dauphin - arXiv preprint arXiv:1611.02344, 2016"],"snippet":"... WMT'15 English-German. We use all available parallel training data, namely Europarl v7, Common Crawl and News Commentary v10 and apply the standard Moses tokenization to obtain 3.9M sentence pairs (Koehn et al., 2007). We report results on newstest2015. ...","url":["https://arxiv.org/pdf/1611.02344"]}
-{"year":"2016","title":"A Deep Fusion Model for Domain Adaptation in Phrase-based MT","authors":["N Durrani, S Joty, A Abdelali, H Sajjad"],"snippet":"... test-13 993 18K 17K test-13 1169 26K 28K Table 1: Statistics of the English-German and Arabic-English training corpora in terms of Sentences and Tokens (represented in millions). ep = Europarl, cc = Common Crawl, un = United Nations ...","url":["https://www.aclweb.org/anthology/C/C16/C16-1299.pdf"]}
-{"year":"2016","title":"A Large DataBase of Hypernymy Relations Extracted from the Web","authors":["J Seitner, C Bizer, K Eckert, S Faralli, R Meusel… - … of the 10th edition of the …, 2016"],"snippet":"... 3http://webdatacommons.org/framework/ 4http://commoncrawl.org ... The corpus is provided by the Common Crawl Foundation on AWS S3 as free download.6 The extraction of ... isadb/) and can be used to repeat the tuple extraction for different or newer Common Crawl releases. ...","url":["http://webdatacommons.org/isadb/lrec2016.pdf"]}
-{"year":"2016","title":"A Maturity Model for Public Administration as Open Translation Data Providers","authors":["N Bel, ML Forcada, A Gómez-Pérez - arXiv preprint arXiv:1607.01990, 2016"],"snippet":"... There are techniques to mitigate the need of large quantities of parallel text, but most often at the expense of resulting translation quality. As a reference of the magnitude we can take as a standard corpus the Common Crawl corpus (Smith et al. ...","url":["http://arxiv.org/pdf/1607.01990"]}
-{"year":"2016","title":"A Neural Architecture Mimicking Humans End-to-End for Natural Language Inference","authors":["B Paria, KM Annervaz, A Dukkipati, A Chatterjee… - arXiv preprint arXiv: …, 2016"],"snippet":"... We used batch normalization [Ioffe and Szegedy, 2015] while training. The various model parameters used are mentioned in Table I. We experimented with both GloVe vectors trained1 on Common Crawl dataset as well as Word2Vec vector trained2 on Google news dataset. ...","url":["https://arxiv.org/pdf/1611.04741"]}
-{"year":"2016","title":"A practical guide to big data research in psychology.","authors":["EE Chen, SP Wojcik - Psychological Methods, 2016"],"snippet":"... as well as general collections, such as Amazon Web Services' Public Data Sets repository (AWS, nd, http://aws.amazon.com/public-data-sets/) which includes the 1000 Genomes Project, with full genomic sequences for 1,700 individuals, and the Common Crawl Corpus, with ...","url":["http://psycnet.apa.org/journals/met/21/4/458/"]}
-{"year":"2016","title":"A semantic based Web page classification strategy using multi-layered domain ontology","authors":["AI Saleh, MF Al Rahmawy, AE Abulwafa - World Wide Web, 2016"],"snippet":"Page 1. A semantic based Web page classification strategy using multi-layered domain ontology Ahmed I. Saleh1 & Mohammed F. Al Rahmawy2 & Arwa E. Abulwafa1 Received: 3 February 2016 /Revised: 13 August 2016 /Accepted ...","url":["http://link.springer.com/article/10.1007/s11280-016-0415-z"]}
-{"year":"2016","title":"A Story of Discrimination and Unfairness","authors":["A Caliskan-Islam, J Bryson, A Narayanan"],"snippet":"... power has led to high quality language models such as word2vec [7] and GloVe [8]. These language models, which consist of up to half a million unique words, are trained on billions of documents from sources such as Wikipedia, CommonCrawl, GoogleNews, and Twitter. ...","url":["https://www.securityweek2016.tu-darmstadt.de/fileadmin/user_upload/Group_securityweek2016/pets2016/9_a_story.pdf"]}
-{"year":"2016","title":"A Way out of the Odyssey: Analyzing and Combining Recent Insights for LSTMs","authors":["S Longpre, S Pradhan, C Xiong, R Socher - arXiv preprint arXiv:1611.05104, 2016"],"snippet":"... All models in this paper used publicly available 300 dimensional word vectors, pre-trained using Glove on 840 million tokens of Common Crawl Data (Pennington et al., 2014), and both the word vectors and the subsequent weight matrices were trained using Adam with a ...","url":["https://arxiv.org/pdf/1611.05104"]}
-{"year":"2016","title":"A Web Application to Search a Large Repository of Taxonomic Relations from the Web","authors":["S Faralli, C Bizer, K Eckert, R Meusel, SP Ponzetto"],"snippet":"... 1 https://commoncrawl.org 2 http://webdatacommons.org/framework/ 3 https://www.mongodb. com ... of the two noun phrases involved in the isa relations into pre-modifiers, head and post-modifiers [6], as well as the frequency of occurrence of the relation in the Common Crawl...","url":["http://ceur-ws.org/Vol-1690/paper58.pdf"]}
-{"year":"2016","title":"Abu-MaTran at WMT 2016 Translation Task: Deep Learning, Morphological Segmentation and Tuning on Character Sequences","authors":["VM Sánchez-Cartagena, A Toral - Proceedings of the First Conference on Machine …, 2016"],"snippet":"... 362 Page 2. Corpus Sentences (k) Words (M) Europarl v8 2 121 39.5 Common Crawl 113 995 2 416.7 News Crawl 2014–15 6 741 83.1 Table 1: Finnish monolingual data, after preprocessing, used to train the LMs of our SMT submission. ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2322.pdf"]}
-{"year":"2016","title":"Action Classification via Concepts and Attributes","authors":["A Rosenfeld, S Ullman - arXiv preprint arXiv:1605.07824, 2016"],"snippet":"... To assign GloVe [19] vectors to object names or attributes, we use the pre-trained model on the Common-Crawl (42B) corpus, which contains a vocabulary of 1.9M words. We break up phrases into their words and assign to them their mean GloVe vector. ...","url":["http://arxiv.org/pdf/1605.07824"]}
-{"year":"2016","title":"Active Content-Based Crowdsourcing Task Selection","authors":["P Bansal, C Eickhoff, T Hofmann"],"snippet":"... Pennington et. al. [28] showed distributed text representations to capture more semantic information when the models are trained on Wikipedia text, as opposed to other large corpora such as the Common Crawl. This is attributed ...","url":["https://www.researchgate.net/profile/Piyush_Bansal4/publication/305442609_Active_Content-Based_Crowdsourcing_Task_Selection/links/578f416d08ae81b44671ad85.pdf"]}
-{"year":"2016","title":"Adverse Drug Reaction Classification With Deep Neural Networks","authors":["T Huynh, Y He, A Willis, S Rüger"],"snippet":"... 4http://commoncrawl.org/ 5Source code is available at https://github.com/trunghlt/ AdverseDrugReaction 879 Page 4. max pooling feedforward layer convolutional layer (a) Convolutional Neural Network (CNN) (b) Recurrent Convolutional Neural Network (RCNN) ...","url":["http://www.aclweb.org/anthology/C/C16/C16-1084.pdf"]}
-{"year":"2016","title":"All Your Data Are Belong to us. European Perspectives on Privacy Issues in 'Free'Online Machine Translation Services","authors":["P Kamocki, J O'Regan, M Stauch - Privacy and Identity Management. Time for a …, 2016"],"snippet":"... http://​www.​cnet.​com/​news/​google-translate-now-serves-200-million-people-daily/​. Accessed 23 Oct 2014. Smith, JR, Saint-Amand, H., Plamada, M., Koehn, P., Callison-Burch, C., Lopez, A.: Dirt cheap web-scale parallel text from the Common Crawl...","url":["http://link.springer.com/chapter/10.1007/978-3-319-41763-9_18"]}
-{"year":"2016","title":"An Analysis of Real-World XML Queries","authors":["P Hlísta, I Holubová - OTM Confederated International Conferences\" On the …, 2016"],"snippet":"... crawler. Or, there is another option – Common Crawl [1], an open repository of web crawled data that is universally accessible and analyzable, containing petabytes of data collected over the last 7 years. ... 3.1 Common Crawl. We ...","url":["http://link.springer.com/chapter/10.1007/978-3-319-48472-3_36"]}
-{"year":"2016","title":"An Attentive Neural Architecture for Fine-grained Entity Type Classification","authors":["S Shimaoka, P Stenetorp, K Inui, S Riedel - arXiv preprint arXiv:1604.05525, 2016"],"snippet":"... appearing in the training set. Specifically, we used the freely available 300 dimensional cased word embeddings trained on 840 billion to- kens from the Common Crawl supplied by Pennington et al. (2014). As embeddings ...","url":["http://arxiv.org/pdf/1604.05525"]}
-{"year":"2016","title":"Analysing Structured Scholarly Data Embedded in Web Pages","authors":["P Sahoo, U Gadiraju, R Yu, S Saha, S Dietze"],"snippet":"... the following section. 2.2 Methodology and Dataset For our investigation, we use the Web Data Commons (WDC) dataset, being the largest available corpus of markup, extracted from the Common Crawl. Of the crawled web ...","url":["http://cs.unibo.it/save-sd/2016/papers/pdf/sahoo-savesd2016.pdf"]}
-{"year":"2016","title":"ArabicWeb16: A New Crawl for Today's Arabic Web","authors":["R Suwaileh, M Kutlu, N Fathima, T Elsayed, M Lease"],"snippet":"... English content dominates the crawl [12]. While Common Crawl could be mined to identify and ex- tract a useful Arabic subset akin to ArClueWeb09, this would address only recency, not coverage. To address the above concerns ...","url":["http://www.ischool.utexas.edu/~ml/papers/sigir16-arabicweb.pdf"]}
-{"year":"2016","title":"Ask Your Neurons: A Deep Learning Approach to Visual Question Answering","authors":["M Malinowski, M Rohrbach, M Fritz - arXiv preprint arXiv:1605.02697, 2016"],"snippet":"Page 1. Noname manuscript Ask Your Neurons: A Deep Learning Approach to Visual Question Answering Mateusz Malinowski · Marcus Rohrbach · Mario Fritz Abstract We address a question answering task on realworld images that is set up as a Visual Turing Test. ...","url":["http://arxiv.org/pdf/1605.02697"]}
-{"year":"2016","title":"Automated Generation of Multilingual Clusters for the Evaluation of Distributed Representations","authors":["P Blair, Y Merhav, J Barry - arXiv preprint arXiv:1611.01547, 2016"],"snippet":"... (2013a), the 840-billion token Common Crawl corpus-trained GloVe model released by Pennington et al. (2014), and the English, Spanish, German, Japanese, and Chinese MultiCCA vectors5 from Ammar et al. ... Outliers OOV GloVe Common Crawl 75.53 38.57 5 6.33 5.70 ...","url":["https://arxiv.org/pdf/1611.01547"]}
-{"year":"2016","title":"Automated Haiku Generation based on Word Vector Models","authors":["AF Aji"],"snippet":"... and Page 28. 16 Chapter 3. Design Common Crawl data. Those data also come with various vector dimension size from 50-D to 300-D. Those pre-trained word vectors are used directly for this project as they take considerably ...","url":["http://project-archive.inf.ed.ac.uk/msc/20150275/msc_proj.pdf"]}
-{"year":"2016","title":"Automatic Construction of Morphologically Motivated Translation Models for Highly Inflected, Low-Resource Languages","authors":["J Hewitt, M Post, D Yarowsky - AMTA 2016, Vol., 2016"],"snippet":"... sentences of Europarl (Koehn, 2005), SETIMES3 (Tyers and Alperen, 2010), extracted from OPUS (Tiedemann, 2009), or Common Crawl (Bojar et al ... Turkish, we train models on 29000 sentences of biblical data with 1000 and 20000 sentences of CommonCrawl and SETIMES ...","url":["https://www.researchgate.net/profile/John_Ortega3/publication/309765044_Fuzzy-match_repair_using_black-box_machine_translation_systems_what_can_be_expected/links/5822496f08ae7ea5be6af317.pdf#page=183"]}
-{"year":"2016","title":"B1A3D2 LUC@ WMT 2016: a Bilingual1 Document2 Alignment3 Platform Based on Lucene","authors":["L Jakubina, P Langlais"],"snippet":"... 2013. Dirt cheap web-scale parallel text from the common crawl. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pages 1374–1383. Jakob Uszkoreit, Jay M. Ponte, Ashok C. Popat, and Moshe Dubiner. 2010. ...","url":["http://www-etud.iro.umontreal.ca/~jakubinl/publication/badluc_jaklan_wmt16_stbad.pdf"]}
-{"year":"2016","title":"Big Data Facilitation and Management","authors":["J Fagerli"],"snippet":"Page 1. Faculty of Science and Technology Department of Computer Science Big Data Facilitation and Management A requirements analysis and initial evaluation of a big biological data processing service — Jarl Fagerli INF ...","url":["http://bdps.cs.uit.no/papers/capstone-jarl.pdf"]}
-{"year":"2016","title":"Bootstrap, Review, Decode: Using Out-of-Domain Textual Data to Improve Image Captioning","authors":["W Chen, A Lucchi, T Hofmann - arXiv preprint arXiv:1611.05321, 2016"],"snippet":"... We report the performance of our model and competing methods in terms of six standard metrics used for image captioning as described in [4]. During the bootstrap learning phase, we use both the 20082010 News-CommonCrawl and Europarl corpus 2 as out- of-domain ...","url":["https://arxiv.org/pdf/1611.05321"]}
-{"year":"2016","title":"bot. zen@ EVALITA 2016-A minimally-deep learning PoS-tagger (trained for Italian Tweets)","authors":["EW Stemle"],"snippet":"... The data was only distributed to the task participants. 4.1.4 C4Corpus (w2v) c4corpus8 is a full documents Italian Web corpus that has been extracted from CommonCrawl, the largest publicly available general Web crawl to date. ...","url":["http://ceur-ws.org/Vol-1749/paper_020.pdf"]}
-{"year":"2016","title":"Building mutually beneficial relationships between question retrieval and answer ranking to improve performance of community question answering","authors":["M Lan, G Wu, C Xiao, Y Wu, J Wu - Neural Networks (IJCNN), 2016 International Joint …, 2016"],"snippet":"... The first is the 300-dimensional version of word2vec [23] vectors, which is trained on part of Google News dataset (about 100 billion words). The second is 300-dimensional Glove vectors [24] which is trained on 840 billion tokens of Common Crawl data. ...","url":["http://ieeexplore.ieee.org/abstract/document/7727286/"]}
-{"year":"2016","title":"C4Corpus: Multilingual Web-size corpus with free license","authors":["I Habernal, O Zayed, I Gurevych"],"snippet":"... documents. Our project is entitled C4Corpus, an abbreviation of Creative Commons from Common Crawl Corpus and is hosted under the DKPro umbrella4 at https:// github.com/dkpro/dkpro-c4corpus under ASL 2.0 license. ...","url":["https://www.ukp.tu-darmstadt.de/fileadmin/user_upload/Group_UKP/publikationen/2016/lrec2016-c4corpus-camera-ready.pdf"]}
-{"year":"2016","title":"Capturing Pragmatic Knowledge in Article Usage Prediction using LSTMs","authors":["J Kabbara, Y Feng, JCK Cheung"],"snippet":"... GloVe: The embedding is initialized by the global vectors Pennington et al. (2014) that are trained on the Common Crawl corpus (840 billion tokens). Both word2vec and GloVe word embeddings consist of 300 dimensions. ...","url":["https://www.aclweb.org/anthology/C/C16/C16-1247.pdf"]}
-{"year":"2016","title":"Character-level and Multi-channel Convolutional Neural Networks for Large-scale Authorship Attribution","authors":["S Ruder, P Ghaffari, JG Breslin - arXiv preprint arXiv:1609.06686, 2016"],"snippet":"... σ: Standard deviation of document number. d: Median document size (tokens). All word embedding channels are initialized with 300-dimensional GloVe vectors (Pennington et al., 2014) trained on 840B tokens of the Common Crawl corpus11. ...","url":["http://arxiv.org/pdf/1609.06686"]}
-{"year":"2016","title":"Citation Classification for Behavioral Analysis of a Scientific Field","authors":["D Jurgens, S Kumar, R Hoover, D McFarland… - arXiv preprint arXiv: …, 2016"],"snippet":"... The classifier is implemented using SciKit (Pedregosa et al., 2011) and syntactic processing was done using CoreNLP (Manning et al., 2014). Selectional preferences used pretrained 300-dimensional vectors from the 840B token Common Crawl (Pennington et al., 2014). ...","url":["http://arxiv.org/pdf/1609.00435"]}
-{"year":"2016","title":"CNRC at SemEval-2016 Task 1: Experiments in crosslingual semantic textual similarity","authors":["C Lo, C Goutte, M Simard - Proceedings of SemEval, 2016"],"snippet":"... The system was 3We use the glm function in R. 669 Page 3. trained using standard resources – Europarl, Common Crawl (CC) and News & Commentary (NC) – totaling approximately 110M words in each language. Phrase ...","url":["http://anthology.aclweb.org/S/S16/S16-1102.pdf"]}
-{"year":"2016","title":"Commonsense Knowledge Base Completion","authors":["X Li, A Taheri, L Tu, K Gimpel"],"snippet":"... We use the GloVe (Pennington et al., 2014) embeddings trained on 840 billion tokens of Common Crawl web text and the PARAGRAM-SimLex embeddings of Wieting et al. (2015), which were tuned to have strong performance on the SimLex-999 task (Hill et al., 2015). ...","url":["http://ttic.uchicago.edu/~kgimpel/papers/li+etal.acl16.pdf"]}
-{"year":"2016","title":"Comparing Topic Coverage in Breadth-First and Depth-First Crawls Using Anchor Texts","authors":["AP de Vries - Research and Advanced Technology for Digital …, 2016","T Samar, MC Traub, J van Ossenbruggen, AP de Vries - International Conference on …, 2016"],"snippet":"... nl domain, with the goal to crawl websites as completes as possible. The second crawl was collected by the Common Crawl foundation using a breadth-first strategy on the entire Web, this strategy focuses on discovering as many links as possible. ...","url":["http://books.google.de/books?hl=en&lr=lang_en&id=VmTUDAAAQBAJ&oi=fnd&pg=PA133&dq=%22common+crawl%22&ots=STVgD4vke3&sig=Gr5Q94wWtvFSfT_EYf1cQGP-Mrg","http://link.springer.com/chapter/10.1007/978-3-319-43997-6_11"]}
-{"year":"2016","title":"COMPARISON OF DISTRIBUTIONAL SEMANTIC MODELS FOR RECOGNIZING TEXTUAL ENTAILMENT.","authors":["Y WIBISONO, DWIH WIDYANTORO… - Journal of Theoretical & …, 2016"],"snippet":"... To our knowledge, this paper is the first study of various DSM on RTE. We found that DSM improves entailment accuracy, with the best DSM is GloVe trained with 42 billion tokens taken from Common Crawl corpus. ... Glove_42B Common Crawl 42 billion tokens ...","url":["http://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=19928645&AN=120026939&h=neaFgJXHcv5SjyzIFWIJp046Uq5Cr3qfiPCmXc4DYTEi9kN6SN9YQqm1CUdjmDg%2BwZzzXWI6ftJLniJiB6Go1g%3D%3D&crl=c"]}
-{"year":"2016","title":"ConceptNet 5.5: An Open Multilingual Graph of General Knowledge","authors":["R Speer, J Chin, C Havasi - arXiv preprint arXiv:1612.03975, 2016"],"snippet":"... 2013), and the GloVe 1.2 embeddings trained on 840 billion words of the Common Crawl (Pennington, Socher, and Manning 2014). These matrices are downloadable, and we will be using them both as a point of comparison and as inputs to an ensemble. ...","url":["https://arxiv.org/pdf/1612.03975"]}
-{"year":"2016","title":"Content Selection through Paraphrase Detection: Capturing different Semantic Realisations of the Same Idea","authors":["E Lloret, C Gardent - WebNLG 2016, 2016"],"snippet":"... either sentences or pred-arg structures, GLoVe pre-trained WE vectors (Pennington et al., 2014) were used, specifically the ones derived from Wikipedia 2014+ Gi- gaword 5 corpora, containing around 6 billion to- kens; and the ones derived from a Common Crawl, with 840 ...","url":["https://webnlg2016.sciencesconf.org/data/pages/book.pdf#page=33"]}
-{"year":"2016","title":"Corporate Smart Content Evaluation","authors":["R Schäfermeier, AA Todor, A La Fleur, A Hasan… - 2016"],"snippet":"Page 1. Fraunhofer FOKUS FRAUNHOFER INSTITUTE FOR OPEN COMMUNICATION SYSTEMS FOKUS STUDY – CORPORATE SMART CONTENT EVALUATION Page 2. Page 3. STUDY – CORPORATE SMART CONTENT EVALUATION ...","url":["http://www.diss.fu-berlin.de/docs/servlets/MCRFileNodeServlet/FUDOCS_derivate_000000006523/CSCStudie2016.pdf"]}
-{"year":"2016","title":"Crawl and crowd to bring machine translation to under-resourced languages","authors":["A Toral, M Esplá-Gomis, F Klubička, N Ljubešić… - Language Resources and …"],"snippet":"... Wikipedia. The CommonCrawl project 5 should be mentioned here as it allows researchers to traverse a frequently updated crawl of the whole web in search of specific data, and therefore bypass the data collection process. ...","url":["http://link.springer.com/article/10.1007/s10579-016-9363-6"]}
-{"year":"2016","title":"Cross Site Product Page Classification with Supervised Machine Learning","authors":["J HUSS"],"snippet":"... An other data set used often is Common Crawl [1], which is a possible source that contain product specification pages. The data of Common Crawl is not complete with HTML-source code and it was collected in 2013, which creates many dead links. ...","url":["http://www.nada.kth.se/~ann/exjobb/jakob_huss.pdf"]}
-{"year":"2016","title":"CSA++: Fast Pattern Search for Large Alphabets","authors":["S Gog, A Moffat, M Petri - arXiv preprint arXiv:1605.05404, 2016"],"snippet":"... The latter were extracted from a sentence-parsed prefix of the German and Spanish sections of the CommonCrawl5. The four 200 ... translation process described by Shareghi et al., corresponding to 40,000 sentences randomly selected from the German part of Common Crawl...","url":["http://arxiv.org/pdf/1605.05404"]}
-{"year":"2016","title":"CUNI-LMU Submissions in WMT2016: Chimera Constrained and Beaten","authors":["A Tamchyna, R Sudarikov, O Bojar, A Fraser - Proceedings of the First Conference on …, 2016"],"snippet":"... tag). Our input is factored and contains the form, lemma, morphological tag, 1http://commoncrawl.org/ 387 Page 4. lemma ... 2015. The second LM only uses 4-grams but additionally contains the full Common Crawl corpus. We ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2325.pdf"]}
-{"year":"2016","title":"D6. 3: Improved Corpus-based Approaches","authors":["CP Escartin, LS Torres, CO UoW, AZ UMA, S Pal - 2016"],"snippet":"... Based on this system and the data retrieved from Common Crawl, several websites were identified as possible candidates for crawling. ... 8http://commoncrawl.org/ 9For a description of this tool, see Section 3.1.2 in this Deliverable. 6 Page 9. ...","url":["http://expert-itn.eu/sites/default/files/outputs/expert_d6.3_20160921_improved_corpus-based_approaches.pdf"]}
-{"year":"2016","title":"Data Selection for IT Texts using Paragraph Vector","authors":["MS Duma, W Menzel - Proceedings of the First Conference on Machine …, 2016"],"snippet":"... models/doc2vec.html 3http://commoncrawl.org/ 4https://github.com/melix/jlangdetect 5-gram LMs using the SRILM toolkit (Stolcke, 2002) with Kneser-Ney discounting (Kneser and Ney, 1995) on the target side of the Commoncrawl and IT corpora. ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2331.pdf"]}
-{"year":"2016","title":"David W. Embley, Mukkai S. Krishnamoorthy, George Nagy &","authors":["S Seth"],"snippet":"... tabulated data on the web even before Big Data became a byword [1]. Assuming “that an average table contains on average 50 facts it is possible to extract more than 600 billion facts taking into account only the 12 billion sample tables found in the Common Crawl” [2]. Tables ...","url":["https://www.ecse.rpi.edu/~nagy/PDF_chrono/2016_Converting%20Web%20Tables,IJDAR,%2010.1007_s10032-016-0259-1.pdf"]}
-{"year":"2016","title":"Deep Recurrent Models with Fast-Forward Connections for Neural Machine Translatin","authors":["J Zhou, Y Cao, X Wang, P Li, W Xu - arXiv preprint arXiv:1606.04199, 2016"],"snippet":"... 4.1 Data sets For both tasks, we use the full WMT'14 parallel corpus as our training data. The detailed data sets are listed below: • English-to-French: Europarl v7, Common Crawl, UN, News Commentary, Gigaword • English-to-German: Europarl v7, Common</","url":["http://arxiv.org/pdf/1606.04199"]}
-{"year":"2016","title":"Deeper Machine Translation and Evaluation for German","authors":["E Avramidis, V Macketanz, A Burchardt, J Helcl… - 2nd Deep Machine …, 2016"],"snippet":"... corpus entries words Chromium browser 6.3 K 55.1 K Drupal 4.7 K 57.4 K Libreoffice help 46.8 K 1.1 M Libreoffice UI 35.6 K 143.7 K Ubuntu Saucy 182.9 K 1.6 M Europarl (mono) 2.2 M 54.0 M News (mono) 89M 1.7 B Commoncrawl (parallel) 2.4 M 53.6 M Europarl (parallel ...","url":["http://www.aclweb.org/anthology/W/W16/W16-64.pdf#page=35"]}
-{"year":"2016","title":"DeepNNNER: Applying BLSTM-CNNs and Extended Lexicons to Named Entity Recognition in Tweets","authors":["F Dugas, E Nichols - WNUT 2016, 2016"],"snippet":"... 850M words) 50 130K 51.43% 75.31% 84.63% 82.18% GloVe 6B Gigaword5+ Wikipedia (6B words) 50 400k 54.22% 82.71% 86.02% 84.17% GloVe 27B Twitter microposts (27B words) 50 1.2 M 57.47% 90.47% 83.67% 97.66% GloVe 42B Common Crawl (42B words) 300 1.9 ...","url":["http://www.aclweb.org/anthology/W/W16/W16-39.pdf#page=190"]}
-{"year":"2016","title":"Detecting Opinion Polarities using Kernel Methods","authors":["R Kaljahi, J Foster - PEOPLES 2016, 2016"],"snippet":"... 0.7, 0.8, 0.9}. The pre-trained word vectors used are the publicly available ones trained using GloVe (Pennington et al., 2014) trained on 42B-token corpus of Common Crawl (1.9 M vocabulary) with 300 dimensions. 4 4.1 Word ...","url":["http://www.aclweb.org/anthology/W/W16/W16-43.pdf#page=74"]}
-{"year":"2016","title":"DEVELOPMENT AND APPLICATION OF A STAGE-GATE PROCESS TO REDUCE THE UNERLYING RISKS OF IT SERVICE PROJECTS","authors":["E JEONG, SR JEONG, MS RAO, VV KUMAR… - Journal of Theoretical and …, 2016"],"snippet":"... RTE. To our knowledge, this paper is the first study of various DSM on RTE. We found that DSM improves entailment accuracy, with the best DSM is GloVe trained with 42 billion tokens taken from Common Crawl corpus. We ...","url":["http://jatit.org/volumes/ninetythree2.php"]}
-{"year":"2016","title":"DFKI's system for WMT16 IT-domain task, including analysis of systematic errors","authors":["E Avramidis, A Burchardt, V Macketanz, A Srivastava - Proceedings of the First …, 2016"],"snippet":"... Europarl (mono) 2.2M 54.0M News (mono) 89M 1.7B Commoncrawl (parallel) 2.4M 53.6M Europarl (parallel) 1.9M 50.1M MultiUN (parallel) 167.6K 5.8M News Crawl (parallel) 201.3K 5.1M Table 1: Size of corpora used for SMT. ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2329.pdf"]}
-{"year":"2016","title":"Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network","authors":["H Khanpour, N Guntakandla, R Nielsen"],"snippet":"... Word2vec embeddings were learned from Google News (Mikolov et al., 2013), and separately, from Wikipedia1. The Glove embeddings were pretrained on the 840 billion token Common Crawl corpus. ... Word2vec GoogleNews 300 71.32 Glove CommonCrawl 75 69.28 ...","url":["http://www.aclweb.org/anthology/C/C16/C16-1189.pdf"]}
-{"year":"2016","title":"Discontinuous Verb Phrases in Parsing and Machine Translation of English and German","authors":["S Loaiciga Sanchez, K Gulordava - 2016","S Loáiciga, K Gulordava"],"snippet":"... all 2https://translate.google.com/ 2841 Page 5. monolingual data (Heafield et al., 2013). Approximately 4.5 million sentences were used for training, combining Europarlv7, CommonCrawl and News data. Optimization weights ...","url":["http://archive-ouverte.unige.ch/unige:84454/ATTACHMENT01","http://www.lrec-conf.org/proceedings/lrec2016/pdf/628_Paper.pdf"]}
-{"year":"2016","title":"Discovering Disease-associated Drugs Using Web Crawl Data","authors":["H Kim, S Park - 2016"],"snippet":"... System Online) database is used for the biomedical literature. 81.7GB sized text data of Common Crawl which Amazon Web Services hosts is used for the web crawl data. Gene symbol, Disease name and Drug name which ...","url":["http://delab.yonsei.ac.kr/files/paper/Kim_ACMSAC2016_CR.PDF"]}
-{"year":"2016","title":"Discriminating between similar languages and arabic dialect identification: A report on the third dsl shared task","authors":["S Malmasi, M Zampieri, N Ljubešic, P Nakov, A Ali… - Proceedings of the 3rd …, 2016"],"snippet":"... PITEOG used their own custom web-based corpus, with no further details provided. • SUKI created an additional dataset using web pages in the Common Crawl corpus. 5 Results for Subtask 2: Arabic Dialect Identification ...","url":["https://pdfs.semanticscholar.org/7478/2d315d5cd472bef874ffbca589cc2285a99f.pdf"]}
-{"year":"2016","title":"Distributed Graph Storage And Querying System","authors":["J Balaji - 2016"],"snippet":"... generation and consumption of such interrelated data. The number of Facebook users grew from 500 million in 2010 to 1.5 billion in 2014 [1]. The Common Crawl web corpora [2] covered for 2012 contains 3.5 billion web pages and 128 billion hyperlinks between these ...","url":["http://scholarworks.gsu.edu/cgi/viewcontent.cgi?article=1112&context=cs_diss"]}
-{"year":"2016","title":"Distributed Platforms and Cloud Services: Enabling Machine Learning for Big Data","authors":["D Pop, G Iuhasz, D Petcu - Data Science and Big Data Computing, 2016"],"snippet":"... Data sets are growing faster, being common now to reach numbers of 100 TB or more. The Sloan Digital Sky Survey occupies 5 TB of storage, the Common Crawl Web corpus is 81 TB in size, and the 1000 Genomes Project requires 200 TB of space, just to name a few. ...","url":["http://link.springer.com/chapter/10.1007/978-3-319-31861-5_7"]}
-{"year":"2016","title":"DRAFT: Interoperation Among Web Archiving Technologies","authors":["DSH Rosenthal, N Taylor, J Bailey - 2016"],"snippet":"... WET (WARC Encapsulated Text, or Parsed Text), specified by Common Crawl and Internet Archive respectively, to represent only the text extracted from Web resources. 3 Page 4. ... [12] Common CrawlCommon Crawl. https:// commoncrawl.org/.","url":["http://www.lockss.org/tmp/Interoperation2016.pdf"]}
-{"year":"2016","title":"Dual Learning for Machine Translation","authors":["Y Xia, D He, T Qin, L Wang, N Yu, TY Liu, WY Ma - arXiv preprint arXiv:1611.00179, 2016"],"snippet":"... In detail, we used the same bilingual corpora from WMT'14 as used in [1, 6], which contains 12M sentence pairs extracting from five datasets: Europarl v7, Common Crawl corpus, UN corpus, News Commentary, and 109French-English corpus. ...","url":["https://arxiv.org/pdf/1611.00179"]}
-{"year":"2016","title":"Dynamic Coattention Networks For Question Answering","authors":["C Xiong, V Zhong, R Socher - arXiv preprint arXiv:1611.01604, 2016"],"snippet":"... We use as GloVe word vectors pretrained on the 840B Common Crawl corpus (Pennington et al., 2014). We limit the vocabulary to words that are present in the Common Crawl corpus and set embeddings for out-of-vocabulary words to zero. ...","url":["https://arxiv.org/pdf/1611.01604"]}
-{"year":"2016","title":"Edinburgh's Statistical Machine Translation Systems for WMT16","authors":["P Williams, R Sennrich, M Nadejde, M Huck, B Haddow… - Proceedings of the First …, 2016"],"snippet":"... Our final system used two different countbased 5-gram language models (one trained on all data, including the WMT16 Romanian CommonCrawl corpus, without pruning, and one trained on news2015 monolingual only), a neural language model trained on news2015 ...","url":["http://www.statmt.org/wmt16/pdf/W16-2327.pdf"]}
-{"year":"2016","title":"Efficient construction of metadata-enhanced web corpora","authors":["A Barbaresi - ACL 2016, 2016"],"snippet":"... 3.3 Extraction I designed a text extraction targeting specifically WordPress pages, which is transferable to a whole range of self-hosted websites using WordPress, al- lowing to reach various blogger profiles thanks 8http://commoncrawl. org 9https://github. ...","url":["http://iiegn.eu/assets/outputs/WAC-X:2016.pdf#page=17"]}
-{"year":"2016","title":"Efficient Data Selection for Bilingual Terminology Extraction from Comparable Corpora","authors":["A Hazem, E Morin"],"snippet":"... We used the FrenchEnglish aligned version at OPUS provided by JRC (Tiedemann, 2012). Common crawl corpus (CC) is a petabytes of data collected over 7 years of web crawling set of raw web page data and text extracts5. ...","url":["http://www.aclweb.org/anthology/C/C16/C16-1321.pdf"]}
-{"year":"2016","title":"Electronic Commerce Meets the Semantic Web","authors":["J Jovanovic, E Bagheri - IT Professional, 2016"],"snippet":"... The latest Common Crawl corpus (Winter 2014; http://commoncrawl.org) consists of 2.01 billion HTML pages collected from more than 15.68 million pay-level domains (PLDs). An analysis of this corpus shows that 30 percent ...","url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7535074"]}
-{"year":"2016","title":"Embedded Sensors System Applied to Wearable Motion Analysis in Sports","authors":["A Valade, A Costes, A Bouillod, M Mangin, P Acco… - 2016"],"snippet":"... the general aspect is good: the mean error is 2.5 degrees and the standard deviation is of 6 degrees. In a second time, we tested the system behaviour on a common crawl swimming movement to ensure the functionality on complex actions. 5.2.2 Tests on Sportsmen ...","url":["https://www.researchgate.net/profile/Anthony_Bouillod/publication/301721501_Embedded_Sensors_System_Applied_to_Wearable_Motion_Analysis_in_Sports/links/572dc45708aee022975a5858.pdf"]}
-{"year":"2016","title":"Enabling Network Security Through Active DNS Datasets","authors":["A Kountouras, P Kintis, C Lever, Y Chen, Y Nadji… - Research in Attacks, …, 2016","Y Nadji, D Dagon, M Antonakakis, R Joffe - … in Attacks, Intrusions, and Defenses: 19th …, 2016"],"snippet":"... These include but are not limited to Public Blacklists, the Alexa list, the Common Crawl project, and various Top Level Domain (TLD) zone files. More specifically, we are using the zone files that are published daily by the administrators of the zones for com, net, biz and org. ...","url":["http://www.cc.gatech.edu/~ynadji3/docs/pubs/activedns.pdf"]}
-{"year":"2016","title":"Engineering a Distributed Full-Text Index","authors":["J Fischer, F Kurpicz, P Sanders - arXiv preprint arXiv:1610.03332, 2016"],"snippet":"... For our experiments we use the common crawl corpus as input.1 It provides world wide web crawl data and contains raw content, text only and metadata of the crawled websites from about 1.23 billion web pages. In total the corpus has a size of 541 TB (as of 27.07.2016). ...","url":["https://arxiv.org/pdf/1610.03332"]}
-{"year":"2016","title":"Engineering top-k document retrieval systems based on succinct data structures","authors":["S Gog, P Sanders"],"snippet":"... relevant documents to a given query”. For large sets of documents, eg web crawls like gov2, clueweb, or CommonCrawl, time-efficient solutions rely on precomputed index data structures. For collections of natural language ...","url":["https://formal.iti.kit.edu/teaching/projektgruppe/themen/WiSe1617/sanders16.pdf"]}
-{"year":"2016","title":"Enriching Product Ads with Metadata from HTML Annotations","authors":["P Ristoski, P Mika - The Semantic Web. Latest Advances and New …, 2016"],"snippet":"... Offers - WDC Microdata Dataset: The latest extraction of WebDataCommons includes over 5 billion entities marked up by one of the three main HTML markup languages (ie, Microdata, Microformats and RDFa) and has been retrieved from the CommonCrawl 2014 corpus 5 ...","url":["http://link.springer.com/chapter/10.1007/978-3-319-34129-3_10"]}
-{"year":"2016","title":"Examining the Relationship between Preordering and Word Order Freedom in Machine Translation","authors":["J Daiber, M Stanojevic, W Aziz, K Sima'an"],"snippet":"Page 1. Examining the Relationship between Preordering and Word Order Freedom in Machine Translation Joachim Daiber Miloš Stanojevic Wilker Aziz Khalil Sima'an Institute for Logic, Language and Computation (ILLC) University of Amsterdam {initial.last}@uva.nl Abstract ...","url":["http://jodaiber.github.io/doc/wmt2016.pdf"]}
-{"year":"2016","title":"Explorations in Identifying and Summarizing Subjective Content in Text","authors":["P Kumar, V Venugopal"],"snippet":"... puted word embeddings using pre-trained word vectors from GloVe [14] (300-dimensional vectors trained on the 840B token CommonCrawl dataset) to encode our input tokens for both the opinion identification and the opinion summarization task. ...","url":["http://cs224d.stanford.edu/reports/poorna.pdf"]}
-{"year":"2016","title":"Exploring Corpora","authors":["C Barrière - Natural Language Understanding in a Semantic Web …, 2016"],"snippet":"Page 1. Chapter 5 Exploring Corpora In previous chapters, we have worked with very small corpora. Some were even constructed manually to specifically illustrate a particular point, and they have generally contained ten to twenty sentences each. ...","url":["http://link.springer.com/chapter/10.1007/978-3-319-41337-2_5"]}
-{"year":"2016","title":"Exploring the Application Potential of Relational Web Tables","authors":["C Bizer"],"snippet":"... crawls. This situation has changed in 2012 with the University of Mannheim [7] and in 2014 with the Dresden University of Technology [3] starting to extract web table corpora from the CommonCrawl, a large public web corpus. ...","url":["http://ceur-ws.org/Vol-1670/paper-07.pdf"]}
-{"year":"2016","title":"Fast Connected Components Computation in Large Graphs by Vertex Pruning","authors":["A Lulli, E Carlini, P Dazzi, C Lucchese, L Ricci"],"snippet":"... Consider, for instance, the Web graph (Common Crawl provides 3.5 billion pages with 128 billion hyperlinks[1]), the Linked Open Data datasets (the LOD2 project indexes for 5.7 billion triples/edges [2]) or the Facebook and Twitter social networks (respectively 1.35 billion and ...","url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7515231"]}
-{"year":"2016","title":"Fast Gated Neural Domain Adaptation: Language Model as a Case Study","authors":["J Zhang, X Wu, A Way, Q Liu"],"snippet":"... The glove 6b model is trained on Wikipedia data and the English Gigaword Fifth Edition corpus;7 the glove 42b model is trained on the Common Crawl data; and the glove 840b model is trained on the the Common Crawl and additional web data. ...","url":["http://www.computing.dcu.ie/~away/PUBS/2016/Fast_Gated_Neural_Domain_Adaptation.pdf"]}
-{"year":"2016","title":"Fast, Small and Exact: Infinite-order Language Modelling with Compressed Suffix Trees","authors":["E Shareghi, M Petri, G Haffari, T Cohn - arXiv preprint arXiv:1608.04465, 2016"],"snippet":"Page 1. Fast, Small and Exact: Infinite-order Language Modelling with Compressed Suffix Trees Ehsan Shareghi,♭ Matthias Petri,♮ Gholamreza Haffari♭ and Trevor Cohn♮ ♭ Faculty of Information Technology, Monash University ...","url":["http://arxiv.org/pdf/1608.04465"]}
-{"year":"2016","title":"FBK HLT-MT Participation in the 1st Translation Memory Cleaning Shared Task","authors":["D Ataman, MJ Sabet, M Turchi, M Negri"],"snippet":"... The English-German corpus was formed using KDE4, GNOME, OpenOffice, PHP, Ubuntu, Tatoeba (Tiedemann, 2012), Europarl v.7 (Koehn, 2005), CommonCrawl (WMT 2013) (Bojar et al., 2013), News Commentary v.11 (WMT 2015) (Bojar et al., 2015), MultiUN (Eisele and ...","url":["http://rgcl.wlv.ac.uk/wp-content/uploads/2016/05/fbkhltmt-workingnote.pdf"]}
-{"year":"2016","title":"Findings of the 2016 Conference on Machine Translation (WMT16)","authors":["O Bojar, R Chatterjee, C Federmann, Y Graham…"],"snippet":"... Some training corpora were identical from last year (Europarl3, United Nations, French-English 109 corpus, Common Crawl, Russian-English parallel data provided by Yandex, Wikipedia Headlines provided by CMU) and ... Monolingual data sets from CommonCrawl (Buck et al ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2301.pdf","https://cris.fbk.eu/bitstream/11582/307240/1/W16-2301.pdf"]}
-{"year":"2016","title":"Findings of the WMT 2016 Bilingual Document Alignment Shared Task","authors":["C Buck, P Koehn - Proceedings of the First Conference on Machine …, 2016"],"snippet":"... Espl`a-Gomis, 2009). 8NLP4TM 2016: Shared task http://rgcl.wlv.ac.uk/nlp4tm2016/ shared-task/ 9http://commoncrawl.org/ 10https://sourceforge.net/p/bitextor/wiki/Home/ 555 Page 3. 3 Training and Test Data We made available ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2347.pdf"]}
-{"year":"2016","title":"Finki at SemEval-2016 Task 4: Deep Learning Architecture for Twitter Sentiment Analysis","authors":["D Stojanovski, G Strezoski, G Madjarov, I Dimitrovski - Proceedings of SemEval, 2016"],"snippet":"... Our system finki, employs both convolutional and gated recurrent neural networks to obtain a more diverse tweet representation. The network is trained on top of GloVe word embeddings pre-trained on the Common Crawl dataset. ... 154 Page 2. Crawl dataset. ...","url":["http://m-mitchell.com/NAACL-2016/SemEval/pdf/SemEval23.pdf"]}
-{"year":"2016","title":"Gathering Alternative Surface Forms for DBpedia Entities","authors":["V Bryl, C Bizer, H Paulheim"],"snippet":"... Surface forms have been extracted in a number of works from Wikipedia labels, redirects, disambiguations and anchor texts of internal Wikipedia links, which we complement with anchor texts of external Wikipedia links from the Common Crawl web corpus. ...","url":["http://ceur-ws.org/Vol-1581/paper2.pdf"]}
-{"year":"2016","title":"Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation","authors":["Y Wu, M Schuster, Z Chen, QV Le, M Norouzi… - arXiv preprint arXiv: …, 2016"],"snippet":"Page 1. Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi yonghui,schuster,zhifengc,qvl,mnorouzi@google.com ...","url":["http://arxiv.org/pdf/1609.08144"]}
-{"year":"2016","title":"Grammatical Error Correction: Machine Translation and Classifiers","authors":["A Rozovskaya, D Roth - Urbana"],"snippet":"... Many teams also used native English datasets. The most common ones are the Web1T corpus (Brants and Franz, 2006), the CommonCrawl dataset, which is similar to Web1T, and the English Wikipedia. Several teams used off-the-shelf spellcheckers. ...","url":["http://cogcomp.cs.illinois.edu/papers/RozovskayaRo16.pdf"]}
-{"year":"2016","title":"Guided Alignment Training for Topic-Aware Neural Machine Translation","authors":["W Chen, E Matusov, S Khadivi, JT Peter - arXiv preprint arXiv:1607.01628, 2016"],"snippet":"... We first trained a baseline NMT model on English-French WMT data (common-crawl, Europarl v7, and news commentary corpora) for two epochs to get the best result on a development set, and then continued training the same model on the in-domain training set for a few ...","url":["http://arxiv.org/pdf/1607.01628"]}
-{"year":"2016","title":"Guided Neural Machine Translation","authors":["F Stahlberg"],"snippet":"Page 1. Guided Neural Machine Translation Felix Stahlberg Department of Engineering University of Cambridge This first year report is submitted as part of the degree of Doctor of Philosophy Queens' College August 2016 Page 2. Page 3. Declaration ...","url":["http://xilef-software.e8u.de/sites/default/files/store/firstyear/firstyear-sgnmt.pdf"]}
-{"year":"2016","title":"HeLI, a Word-Based Backoff Method for Language Identification","authors":["T Jauhiainen, K Lindén, H Jauhiainen - Proceedings of the VarDial Workshop, 2016"],"snippet":"... We collected from the Common Crawl 3 corpus all the web pages from the respective domains as in Table 2. When language models were created directly from the pages, the accuracy on the DSL development corpus was 49.86%, which was much ... 3http://commoncrawl.org/ ...","url":["http://web.science.mq.edu.au/~smalmasi/vardial3/pdf/VarDial320.pdf"]}
-{"year":"2016","title":"Hybrid Morphological Segmentation for Phrase-Based Machine Translation","authors":["SA Grönroos, S Virpioja, M Kurimo - Proceedings of the First Conference on Machine …, 2016"],"snippet":"... Due to TheanoLM limitations, only the Europarl and News data (but not Common Crawl) were used for training. ... As monolingual data, we used the Finnish side of Europarl-v8, news.2014.fi.shuffled.v2, news.2015.fi.shuffled and Common Crawl...","url":["http://www.aclweb.org/anthology/W/W16/W16-2312.pdf"]}
-{"year":"2016","title":"IIT Bombay's English-Indonesian submission at WAT: Integrating Neural Language Models with SMT","authors":["SSAKP Bhattacharyya - WAT 2016, 2016"],"snippet":"... Since Commoncrawl provides raw data by web scraping, the Indonesian data obtained was cleaned for noisy sentences and then tokenized and truecased for training the language model. ... statmt. org/europarl/ 6 http://commoncrawl. org/ 70 Page 85. ...","url":["http://www.aclweb.org/anthology/W/W16/W16-46.pdf#page=82"]}
-{"year":"2016","title":"Impact of Data Placement on Resilience in Large-Scale Object Storage Systems","authors":["P Carns, K Harms, J Jenkins, M Mubarak, R Ross…"],"snippet":"... Figure 2 compares the distribution of file sizes across three different example data populations.1 The first two (the contents of the 1000 Genomes [19] catalog of gene sequencing data and the Common Crawl Corpus [20] catalog of web crawler data) are available as Amazon ...","url":["http://storageconference.us/2016/Papers/ImpactOfDataPlacement.pdf"]}
-{"year":"2016","title":"Improving Translation Selection with Supersenses","authors":["H Tang, D Xiong, OL de Lacalle, E Agirre"],"snippet":"... We set the Gaussian prior to 1 to avoid overfitting. 4There are 12 subcorpora: commoncrawl, europarl, kde4, news2007, news2008, news2009, news2010, news2011, news2012, newscommentary, openoffice, un 5http://homepages.inf.ed.ac.uk/lzhang10/maxenttoolkit.html ...","url":["http://www.aclweb.org/anthology/C/C16/C16-1293.pdf"]}
-{"year":"2016","title":"INSIGHT-1 at SemEval-2016 Task 5: Deep Learning for Multilingual Aspect-based Sentiment Analysis","authors":["S Ruder12, P Ghaffari, JG Breslin - Proceedings of SemEval, 2016"],"snippet":"... respective task. English word embeddings are initialized with 300-dimensional GloVe vectors (Pennington et al., 2014) trained on 840B tokens of the Common Crawl corpus for the unconstrained submission. Word embeddings ...","url":["http://www.aclweb.org/anthology/S/S16/S16-1053.pdf"]}
-{"year":"2016","title":"Is an Image Worth More than a Thousand Words? On the Fine-Grain Semantic Differences between Visual and Linguistic Representations","authors":["G Collell, MF Moens"],"snippet":"... 3.2 Word Embeddings We employ 300-dimensional GloVe vectors (Pennington et al., 2014) pre-trained in the largest available corpus (840B tokens and a 2.2M words vocabulary from Common Crawl corpus) from the author's website1. ...","url":["http://www.aclweb.org/anthology/C/C16/C16-1264.pdf"]}
-{"year":"2016","title":"JU-USAAR: A Domain Adaptive MT System","authors":["K Pahari, A Kuila, S Pal, SK Naskar, S Bandyopadhyay… - Proceedings of the First …, 2016"],"snippet":"... In this task, the information technology (IT) do- main English–German parallel corpus released in the WMT-2016 IT-domain shared task serves as the in-domain data and the Europarl, News and Common Crawl English–German parallel corpus released in the Translation Task ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2333.pdf"]}
-{"year":"2016","title":"Language Models with GloVe Word Embeddings","authors":["V Makarenkov, B Shapira, L Rokach - arXiv preprint arXiv:1610.03759, 2016"],"snippet":"... Despite the huge size of the Common Crawl corpus, some words may not exist with the embeddings, so we set these words to random vectors, and use the same embeddings consistently if we encounter the same unseen word again in the text. ...","url":["https://arxiv.org/pdf/1610.03759"]}
-{"year":"2016","title":"Language Semantic Embeddings in Deep Visual Representation","authors":["Y Chen - 2016"],"snippet":"... As for the final system (shown in Figure 1.1), word representation is learned based on pre-trained GloVe model with Common Crawl data [5]. 2. Examine how to learn visual representation from weakly supervised dataset (Pixabay is the image data source) with ConvNets. ...","url":["http://www.nada.kth.se/~ann/exjobb/yanbei_chen.pdf"]}
-{"year":"2016","title":"Large-scale evaluation of splicing localization algorithms for web images","authors":["M Zampoglou, S Papadopoulos, Y Kompatsiaris - Multimedia Tools and Applications, 2016"],"snippet":"... In reality, especially for the Web-based forensics case, despite the recent proliferation of PNG files, JPEG remains the norm: it is indicative that among the contents of the Common Crawl corpus,2 87 % of identifiable image suffixes correspond to JPEG (.jpg, .jpeg). ...","url":["http://link.springer.com/article/10.1007/s11042-016-3795-2"]}
-{"year":"2016","title":"Latent Space Inference of Internet-Scale Networks","authors":["Q Ho, J Yin, EP Xing - Journal of Machine Learning Research, 2016"],"snippet":"Page 1. Journal of Machine Learning Research 17 (2016) 1-41 Submitted 4/15; Published 4/16 Latent Space Inference of Internet-Scale Networks Qirong Ho∗ hoqirong@gmail.com Institute for Infocomm Research A*STAR Singapore 138632 Junming Yin∗ ...","url":["http://www.jmlr.org/papers/volume17/15-142/15-142.pdf"]}
-{"year":"2016","title":"Learning to recognise named entities in tweets by exploiting weakly labelled data","authors":["KJ Espinosa, R Batista-Navarro, S Ananiadou - WNUT 2016, 2016"],"snippet":"... Pre-trained Word Embeddings Description Text Type Twitter 2B tweets, 27B tokens, 1.2 M vo- cabulary words, uncased, 100 di- mensions Tweets Common Crawl 840B tokens, 2.2 M vocabulary words, cased, 300 dimensions Web Pages Wikipedia 2014+ Gigaword 5 6B tokens ...","url":["http://www.aclweb.org/anthology/W/W16/W16-39.pdf#page=165"]}
-{"year":"2016","title":"Learning to refine text based recommendations","authors":["Y Gu, T Lei, R Barzilay, T Jaakkola"],"snippet":"... Word Vectors: For the ingredient/product prediction task, we used the GloVe pre-trained vectors (Common Crawl, 42 billion tokens, 300dimensional) (Pennington et al., 2014). The word vectors for the AskUbuntu vectors are pre-trained using the AskUbuntu and Wikipedia ...","url":["https://people.csail.mit.edu/taolei/papers/emnlp16_recommendation.pdf"]}
-{"year":"2016","title":"Learning to translate from graded and negative relevance information","authors":["L Jehl, S Riezler"],"snippet":"Page 1. Learning to translate from graded and negative relevance information Laura Jehl Computational Linguistics Heidelberg University 69120 Heidelberg, Germany jehl@cl.uni-heidelberg.de Stefan Riezler Computational ...","url":["https://pdfs.semanticscholar.org/79ee/9b20f0776affab912a3528d604e152cc1217.pdf"]}
-{"year":"2016","title":"Lexical Coherence Graph Modeling Using Word Embeddings","authors":["M Mesgar, M Strube - Proceedings of NAACL-HLT, 2016"],"snippet":"... 1971). We use a pretrained model of GloVe for word embeddings. This model is trained on Common Crawl with 840B tokens, 2.2M vocabulary. We represent each word by a vector with length 300 (Pennington et al., 2014). For ...","url":["http://www.aclweb.org/anthology/N/N16/N16-1167.pdf"]}
-{"year":"2016","title":"LIMSI@ WMT'16: Machine translation of news","authors":["A Allauzen, L Aufrant, F Burlot, E Knyazeva… - Proc. of the ACL 2016 First …, 2016"],"snippet":"... Having noticed many sentence alignment errors and out-of-domain parts in the Russian common-crawl parallel corpus, we have used a bilingual sentence aligner3 and proceeded to a domain adaptation filtering using the same procedure as for monolingual data (see ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2304.pdf"]}
-{"year":"2016","title":"Log-linear Combinations of Monolingual and Bilingual Neural Machine Translation Models for Automatic Post-Editing","authors":["M Junczys-Dowmunt, R Grundkiewicz - arXiv preprint arXiv:1605.04800, 2016"],"snippet":"... 4. The German monolingual common crawl corpus — a very large resource of raw German text from the Common Crawl project — admissible for the WMT-16 news translation and IT translation tasks. 3.2 Preand post-processing ...","url":["http://arxiv.org/pdf/1605.04800"]}
-{"year":"2016","title":"Lurking Malice in the Cloud: Understanding and Detecting Cloud Repository as a Malicious Service","authors":["X Liao, S Alrwais, K Yuan, L Xing, XF Wang, S Hao… - Proceedings of the 2016 …, 2016"],"snippet":"... Running the scanner over all the data collected by the Common Crawl [?], which indexed five billion web pages, for those associated with all major cloud storage providers (including Amazon S3, Cloudfront, Google Drive, etc.), we found around 1 million sites utilizing 6,885 ...","url":["http://dl.acm.org/citation.cfm?id=2978349"]}
-{"year":"2016","title":"Machine Translation Quality and Post-Editor Productivity","authors":["M Sanchez-Torron, P Koehn - AMTA 2016, Vol., 2016"],"snippet":"... corresponding Spanish human reference translations. We trained nine MT systems with training data from the European Parliament proceedings, News Commentary, Common Crawl, and United Nations. The systems are phrase ...","url":["https://www.researchgate.net/profile/John_Ortega3/publication/309765044_Fuzzy-match_repair_using_black-box_machine_translation_systems_what_can_be_expected/links/5822496f08ae7ea5be6af317.pdf#page=22"]}
-{"year":"2016","title":"Machine Translation Through Learning From a Communication Game","authors":["D He, Y Xia, T Qin, L Wang, N Yu, T Liu, WY Ma - Advances In Neural Information …, 2016"],"snippet":"... In detail, we used the same bilingual corpora from WMT'14 as used in [1, 5], which contains 12M sentence pairs extracting from five datasets: Europarl v7, Common Crawl corpus, UN corpus, News Commentary, and 109French-English corpus. ...","url":["http://papers.nips.cc/paper/6468-machine-translation-through-learning-from-a-communication-game.pdf"]}
-{"year":"2016","title":"Measuring semantic similarity of words using concept networks","authors":["G Recski, E Iklódi, K Pajkossy, A Kornai"],"snippet":"... We extend this set of models with GloVe vectors4 (Pennington et al., 2014), trained on 840 billion tokens of Common Crawl data5, and the two word embeddings mentioned in Section 1 that have recently been evaluated on the SimLex dataset: the 500-dimension SP model6 ...","url":["http://www.kornai.com/Papers/wordsim.pdf"]}
-{"year":"2016","title":"Models and Inference for Prefix-Constrained Machine Translation","authors":["J Wuebker, S Green, J DeNero, S Hasan, MT Luong"],"snippet":"... The English-French bilingual training data consists of 4.9M sentence pairs from the Common Crawl and Europarl corpora from WMT 2015 (Bo- jar et al., 2015). The LM was estimated from the target side of the bitext. For English-German we run large-scale experiments. ...","url":["http://nlp.stanford.edu/pubs/wuebker2016acl_prefix.pdf"]}
-{"year":"2016","title":"Multi-cultural Wikipedia mining of geopolitics interactions leveraging reduced Google matrix analysis","authors":["KM Frahm, SE Zant, K Jaffrès-Runser… - arXiv preprint arXiv: …, 2016"],"snippet":"... At present directed networks of real systems can be very large (about 4.2 million articles for the English Wikipedia edition in 2013 [13] or 3.5 billion web pages for a publicly ac- cessible web crawl that was gathered by the Common Crawl Foundation in 2012 [18]). ...","url":["https://arxiv.org/pdf/1612.07920"]}
-{"year":"2016","title":"Multi-Perspective Context Matching for Machine Comprehension","authors":["Z Wang, H Mi, W Hamza, R Florian - arXiv preprint arXiv:1612.04211, 2016"],"snippet":"... jpurkar et al., 2016). To initialize the word embeddings in the word representation layer, we use the 300-dimensional GloVe word vectors pre-trained from the 840B Common Crawl corpus (Pennington et al., 2014). For the out ...","url":["https://arxiv.org/pdf/1612.04211"]}
-{"year":"2016","title":"N-gram language models for massively parallel devices","authors":["N Bogoychev, A Lopez"],"snippet":"... benchmark task computes perplexity on data ex- tracted from the Common Crawl dataset used for the 2013 Workshop on Machine Translation, which ... statmt.org/moses/RELEASE-3.0/models/ fr- en/lm/europarl.lm.1 7http://www.statmt.org/wmt13/training-parallelcommoncrawl.tgz ...","url":["http://homepages.inf.ed.ac.uk/s1031254/publications/n-gram-language.pdf"]}
-{"year":"2016","title":"Neural Architectures for Fine-grained Entity Type Classification","authors":["S Shimaoka, P Stenetorp, K Inui, S Riedel - arXiv preprint arXiv:1606.01341, 2016"],"snippet":"... Rocktäschel et al., 2015). For this purpose, we used the freely available 300-dimensional cased word embeddings trained on 840 billion tokens from the Common Crawl supplied by Pennington et al. (2014). For words not present ...","url":["http://arxiv.org/pdf/1606.01341"]}
-{"year":"2016","title":"Neural Interactive Translation Prediction","authors":["R Knowles, P Koehn - AMTA 2016, Vol., 2016"],"snippet":"... The data consists of a 115 million word parallel corpus (Europarl, News Commentary, CommonCrawl), 3http://www. statmt. ... and about 75 billion words of additional English monolingual data (LDC Gigaword, monolingual news, monolingual CommonCrawl). ...","url":["https://www.researchgate.net/profile/John_Ortega3/publication/309765044_Fuzzy-match_repair_using_black-box_machine_translation_systems_what_can_be_expected/links/5822496f08ae7ea5be6af317.pdf#page=113"]}
-{"year":"2016","title":"Neural Machine Translation with Pivot Languages","authors":["Y Cheng, Y Liu, Q Yang, M Sun, W Xu - arXiv preprint arXiv:1611.04928, 2016"],"snippet":"... We use the statistical significance test with paired bootstrap resampling [Koehn, 2004]. Table 1 shows the Spanish-English and English-French corpora from WMT which include Common Crawl, News Commentary, Europarl v7 and UN. ...","url":["https://arxiv.org/pdf/1611.04928"]}
-{"year":"2016","title":"Neural Machine Translation with Recurrent Attention Modeling","authors":["Z Yang, Z Hu, Y Deng, C Dyer, A Smola - arXiv preprint arXiv:1607.05108, 2016"],"snippet":"... 3 Experiments & Results 3.1 Data sets We experiment with two data sets: WMT EnglishGerman and NIST Chinese-English. • English-German The German-English data set contains Europarl, Common Crawl and News Commentary corpus. ...","url":["http://arxiv.org/pdf/1607.05108"]}
-{"year":"2016","title":"Neural Network-based Word Alignment through Score Aggregation","authors":["J Legrand, M Auli, R Collobert - arXiv preprint arXiv:1606.09560, 2016"],"snippet":"... For LSE, we set r = 1 in (4). We initialize the word embeddings with a simple PCA computed over the matrix of word co- occurrence counts (Lebret and Collobert, 2014). The co-occurrence counts were computed over the common crawl corpus provided by WMT16. ...","url":["http://arxiv.org/pdf/1606.09560"]}
-{"year":"2016","title":"Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision","authors":["C Liang, J Berant, Q Le, KD Forbus, N Lao - arXiv preprint arXiv:1611.00020, 2016"],"snippet":"... All the weight matrices are initialized with a uniform distribution in [− √ 3 d , √ 3 d] where d is the input dimension. For pretrained word embeddings, we used the 300 dimension GloVe word embeddings trained on 840B common crawl corpus [? ]. ...","url":["https://arxiv.org/pdf/1611.00020"]}
-{"year":"2016","title":"NewsQA: A Machine Comprehension Dataset","authors":["A Trischler, T Wang, X Yuan, J Harris, A Sordoni… - arXiv preprint arXiv: …, 2016"],"snippet":"... Both mLSTM and BARB are implemented with the Keras framework (Chollet, 2015) using the Theano (Bergstra et al., 2010) backend. Word embeddings are initialized using GloVe vectors (Pennington et al., 2014) pre-trained on the 840-billion Common Crawl corpus. ...","url":["https://arxiv.org/pdf/1611.09830"]}
-{"year":"2016","title":"Normalized Log-Linear Interpolation of Backoff Language Models is Efficient","authors":["K Heafield, C Geigle, S Massung, L Schwartz - Urbana"],"snippet":"Page 1. Normalized Log-Linear Interpolation of Backoff Language Models is Efficient Kenneth Heafield University of Edinburgh 10 Crichton Street Edinburgh EH8 9AB United Kingdom kheafiel@inf.ed.ac.uk Chase Geigle Sean ...","url":["https://kheafield.com/professional/edinburgh/interpolate_paper.pdf"]}
-{"year":"2016","title":"NRC Russian-English Machine Translation System for WMT 2016","authors":["C Lo, C Cherry, G Foster, D Stewart, R Islam… - Proceedings of the First …, 2016"],"snippet":"... They include the CommonCrawl corpus, the NewsCommentary v11 corpus, the Yandex corpus and the Wikipedia headlines corpus. ... Due to resource limits, we have not used the newly re- leased 3 billion sentence CommonCrawl monolingual English corpus. ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2317.pdf"]}
-{"year":"2016","title":"of Deliverable: Multimedia Linking and Mining","authors":["K Andreadou, S Papadopoulos, M Zampoglou… - 2016"],"snippet":"Page 1. D3.2 – Multimedia Linking and Mining Version: v1.4 – Final, Date: 02/03/2016 PROJECT TITLE: REVEAL CONTRACT NO. FP7-610928 PROJECT COORDINATOR: INTRASOFT INTERNATIONAL SA WWW.REVEALPROJECT.EU PAGE 1 OF 139 REVEAL FP7-610928 ...","url":["http://revealproject.eu/wp-content/uploads/D3.2Multimedia-Linking-and-Mining.pdf"]}
-{"year":"2016","title":"On Approximately Searching for Similar Word Embeddings","authors":["K Sugawara, H Kobayashi, M Iwasaki"],"snippet":"... GV 300-dimensional embeddings (Pennington et al., 2014a) learned by the global vectors for word representation (GloVe) model (Pennington et al., 2014b) using Common Crawl corpora, which contain about 2 million words and 42 billion tokens. ...","url":["http://www.aclweb.org/anthology/P/P16/P16-1214.pdf"]}
-{"year":"2016","title":"On Bias-free Crawling and Representative Web Corpora","authors":["R Schäfer, H Allee - ACL 2016, 2016"],"snippet":"... Language Resources and Evaluation. Online first: DOI 10.1007/s10579-016-9359-2. Roland Schäfer. 2016b. CommonCOW: Massively huge web corpora from CommonCrawl data and a method to distribute them freely under restrictive EU copyright laws. ...","url":["http://iiegn.eu/assets/outputs/WAC-X:2016.pdf#page=81"]}
-{"year":"2016","title":"On the Ubiquity of Web Tracking: Insights from a Billion-Page Web Crawl","authors":["S Schelter, J Kunegis - arXiv preprint arXiv:1607.07403, 2016"],"snippet":"... We extract third-party embeddings from more than 3.5 billion web pages of the CommonCrawl 2012 corpus, and aggregate those to a dataset containing more than 140 million third-party embeddings in over 41 million domains. ...","url":["http://arxiv.org/pdf/1607.07403"]}
-{"year":"2016","title":"Online tracking: A 1-million-site measurement and analysis","authors":["S Englehardt, A Narayanan - 2016"],"snippet":"... AdFisher builds on similar technologies as OpenWPM (Selenium, xvfb), but is not intended for tracking measurements. Common Crawl4 uses an Apache Nutch based crawler. The Common Crawl dataset is the largest publicly available web crawl5, with billions of page visits. ...","url":["http://senglehardt.com/papers/ccs16_online_tracking.pdf"]}
-{"year":"2016","title":"Optimizing Interactive Development of Data-Intensive Applications","authors":["M Interlandi, SD Tetali, MA Gulzar, J Noor, T Condie… - Proceedings of the Seventh …, 2016"],"snippet":"... 1. 311 service requests dataset. https://data.cityofnewyork.us/Social-Services/311-ServiceRequests-from-2010-to-Present/erm2-nwe9. 2. Common crawl dataset. http://commoncrawl.org. 3. Hadoop. http://hadoop.apache.org. 4. Spark. http://spark.apache.org. 5. WikiReverse. ...","url":["http://dl.acm.org/citation.cfm?id=2987565"]}
-{"year":"2016","title":"Paragraph Vector for Data Selection in Statistical Machine Translation","authors":["MS Duma, W Menzel"],"snippet":"... As general domain data we chose the Commoncrawl corpus1 as it is a relatively large corpus and contains crawled data from a variety of domains as well as texts having different discourse types 1http://commoncrawl.org/ (including spoken discourse). ...","url":["https://www.linguistics.rub.de/konvens16/pub/11_konvensproc.pdf"]}
-{"year":"2016","title":"Parallel Graph Processing on Modern Multi-Core Servers: New Findings and Remaining Challenges","authors":["A Eisenman, L Cherkasova, G Magalhaes, Q Cai…"],"snippet":"Page 1. Parallel Graph Processing on Modern Multi-Core Servers: New Findings and Remaining Challenges Assaf Eisenman1,2, Ludmila Cherkasova2, Guilherme Magalhaes3, Qiong Cai2, Sachin Katti1 1Stanford University ...","url":["http://www.labs.hpe.com/people/lucy_cherkasova/papers/main-mascots16.pdf"]}
-{"year":"2016","title":"ParFDA for Instance Selection for Statistical Machine Translation","authors":["E Biçici - Proceedings of the First Conference on Machine …, 2016"],"snippet":"... Compared with last year, this year we do not use Common Crawl parallel corpus except for en-ru. We use Common Crawl monolingual corpus fi, ro, and tr datasets and we extended the LM corpora with previous years' corpora. ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2306.pdf"]}
-{"year":"2016","title":"Partitioning Trillion-edge Graphs in Minutes","authors":["GM Slota, S Rajamanickam, K Devine, K Madduri - arXiv preprint arXiv:1610.07220, 2016"],"snippet":"Page 1. Partitioning Trillion-edge Graphs in Minutes George M. Slota Computer Science Department Rensselaer Polytechnic Institute Troy, NY slotag@rpi.edu Sivasankaran Rajamanickam & Karen Devine Scalable Algorithms ...","url":["https://arxiv.org/pdf/1610.07220"]}
-{"year":"2016","title":"Performance Optimization Techniques and Tools for Distributed Graph Processing","authors":["V Kalavri - 2016"],"snippet":"Page 1. Performance Optimization Techniques and Tools for Distributed Graph Processing VASILIKI KALAVRI School of Information and Communication Technology KTH Royal Institute of Technology Stockholm, Sweden 2016 ...","url":["http://www.diva-portal.org/smash/get/diva2:968786/FULLTEXT02"]}
-{"year":"2016","title":"Phishing Classification using Lexical and Statistical Frequencies of URLs","authors":["S Villegas, AC Bahnsen, J Vargas"],"snippet":"... We used a sample of 1.2 million phishing URLs extracted from Phishtank and 1.2 million ham URLs from the CommonCrawl corpus to train the model. Classification based on URLs facilitates a defense against all phishing attacks due to the feature they all share, a URL. ...","url":["http://albahnsen.com/files/Phishing%20Classification%20using%20Lexical%20and%20Statistical%20Frequencies%20of%20URLs.pdf"]}
-{"year":"2016","title":"Phrase-based Machine Translation is State-of-the-Art for Automatic Grammatical Error Correction","authors":["M Junczys-Dowmunt, R Grundkiewicz - arXiv preprint arXiv:1605.06353, 2016"],"snippet":"... Their method relies on a character-level encoder-decoder recurrent neural network with an attention mechanism. They use data from the public Lang-8 corpus and combine their model with an n-gram language model trained on web-scale Common Crawl data. ...","url":["http://arxiv.org/pdf/1605.06353"]}
-{"year":"2016","title":"Phrase-Based SMT for Finnish with More Data, Better Models and Alternative Alignment and Translation Tools","authors":["J Tiedemann, F Cap, J Kanerva, F Ginter, S Stymne… - Proceedings of the First …, 2016"],"snippet":"... The English language model based on the provided Common Crawl data is limited to trigrams. ... The data is obtained from a large-scale Internet crawl, seeded from all Finnish pages in CommonCrawl.3 However, actual CommonCrawl data is only a small fraction of the total ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2326.pdf"]}
-{"year":"2016","title":"PJAIT Systems for the WMT 2016","authors":["K Wołk, K Marasek - Proceedings of the First Conference on Machine …, 2016"],"snippet":"... “BASE” in the tables represents the baseline SMT system. “EXT” indicates results for the baseline system, using the baseline settings but extended with additional permissible data (limited to parallel Europarl v7, Common Crawl, ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2328.pdf"]}
-{"year":"2016","title":"Porting an Open Information Extraction System from English to German","authors":["T Falke, G Stanovsky, I Gurevych, I Dagan"],"snippet":"... For this purpose, we created a new dataset consisting of 300 German sentences, randomly sampled from three sources of different genres: news articles from TIGER (Brants et al., 2004), German web pages from CommonCrawl (Habernal et al., 2016) and featured Wikipedia ...","url":["https://www.ukp.tu-darmstadt.de/fileadmin/user_upload/Group_UKP/publikationen/2016/EMNLP_2016_PropsDE_cr.pdf"]}
-{"year":"2016","title":"Practical Variable Length Gap Pattern Matching","authors":["J Bader, S Gog, M Petri - Experimental Algorithms, 2016"],"snippet":"... implemented on top of SDSL [7] data structures. We use three datasets from different application domains: The CC data set is a \\(371 \\,\\mathrm{GiB}\\) prefix of a recent \\(145 \\,\\mathrm{TiB}\\) web crawl from commoncrawl.​org. ...","url":["http://link.springer.com/chapter/10.1007/978-3-319-38851-9_1"]}
-{"year":"2016","title":"Pre-Translation for Neural Machine Translation","authors":["J Niehues, E Cho, TL Ha, A Waibel - arXiv preprint arXiv:1610.05243, 2016"],"snippet":"... The systems were trained on all parallel data available for the WMT 20161. The news commentary corpus, the European parliament proceedings and the common crawl corpus sum up to 3.7M sentences and around 90M words. ...","url":["https://arxiv.org/pdf/1610.05243"]}
-{"year":"2016","title":"Predicting Motivations of Actions by Leveraging Text","authors":["C Vondrick, D Oktay, H Pirsiavash, A Torralba - … of the IEEE Conference on Computer …, 2016"],"snippet":"... In ECCV. 2012. [5] C. Buck, K. Heafield, and B. van Ooyen. N-gram counts and language models from the common crawl. LREC, 2014. [6] X. Chen, A. Shrivastava, and A. Gupta. Neil: Extracting visual knowledge from web data. In ICCV, 2013. 3004 Page 9. ...","url":["http://www.cv-foundation.org/openaccess/content_cvpr_2016/html/Vondrick_Predicting_Motivations_of_CVPR_2016_paper.html"]}
-{"year":"2016","title":"Privacy issues in online machine translation services–European perspective","authors":["P Kamocki, J O'Regan - 2016"],"snippet":"... 1/11/2014. Retrieved from http://itre.cis.upenn.edu/~myl/languagelog/archives/005 492.html Smith, JR et al. (2013). Dirt cheap web-scale parallel text from the Common Crawl. In Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics. ...","url":["https://ids-pub.bsz-bw.de/files/5043/Kamocki-ORegan_Privacy_issues_in_online_machine_translation_2016.pdf"]}
-{"year":"2016","title":"Query Answering to IQ Test Questions Using Word Embedding","authors":["M Frąckowiak, J Dutkiewicz, C Jędrzejek, M Retinger… - Multimedia and Network …, 2017"],"snippet":"... The pre-trained model based on Google News [16]. Embedding vector size 300, the negative sampling count as 3. 8. Glove Small. Pre-trained model based on Glove approach [20] using common crawl data, accessible on [15]. Embedding vector size 300. 9. Glove Large. ...","url":["http://link.springer.com/chapter/10.1007/978-3-319-43982-2_25"]}
-{"year":"2016","title":"Query Expansion with Locally-Trained Word Embeddings","authors":["F Diaz, B Mitra, N Craswell - arXiv preprint arXiv:1605.07891, 2016"],"snippet":"... the entire corpus. Instead of training a global embedding on the large web collection, we use a GloVe embedding trained on Common Crawl data.4 We train local embeddings using one of three retrieval sources. First, we consider ...","url":["http://arxiv.org/pdf/1605.07891"]}
-{"year":"2016","title":"Real-Time Presentation Tracking Using Semantic Keyword Spotting","authors":["R Asadi, HJ Fell, T Bickmore, H Trinh"],"snippet":"... gathered from a large corpus. We use a pre-trained vector representation with 1.9 million uncased words and vectors with 300 elements. It was trained using 42 billion tokens of web data from Common Crawl. We will use both the ...","url":["http://relationalagents.com/publications/Interspeech2016.pdf"]}
-{"year":"2016","title":"Recurrent versus Recursive Approaches Towards Compositionality in Semantic Vector Spaces","authors":["A Nayebi, H Blundell"],"snippet":"... 0.01, and 1They were in fact trained on 840 billion tokens of Common Crawl data, as in http://nlp.stanford.edu/ projects/glove/. Adagrad (with the default learning rate of 0.01) as our optimizer, with a minibatch size of 300. Addi ...","url":["http://web.stanford.edu/~anayebi/projects/CS_224U_Final_Project_Writeup.pdf"]}
-{"year":"2016","title":"Relatedness","authors":["C Barrière - Natural Language Understanding in a Semantic Web …, 2016"],"snippet":"... GloVe has some datasets trained on Wikipedia 2014 + Gigaword 5 (large news corpus) for a total of 6 billion tokens, covering a 400K vocabulary. It has other datasets based on an even larger corpus, the Common Crawl. To ...","url":["http://link.springer.com/chapter/10.1007/978-3-319-41337-2_10"]}
-{"year":"2016","title":"Reordering space design in statistical machine translation","authors":["N Pécheux, A Allauzen, J Niehues, F Yvon - Language Resources and Evaluation"],"snippet":"... in (Allauzen et al. 2013), and, for English-Czech, the Europarl and CommonCrawl parallel WMT'12 corpora. For each task, a 4-gram language model is estimated using the target side of the training data. We use Ncode with ...","url":["http://link.springer.com/article/10.1007/s10579-016-9353-8"]}
-{"year":"2016","title":"Richer Interpolative Smoothing Based on Modified Kneser-Ney Language Modeling","authors":["E Shareghi, T Cohn, G Haffari"],"snippet":"... Interdependency of m, data size, and discounts To explore the correlation between these factors we selected the German and investigated this correlation on two different training data sizes: Europarl (61M words), and CommonCrawl 2014 (984M words). ...","url":["http://people.eng.unimelb.edu.au/tcohn/papers/shareghi16emnlp.pdf"]}
-{"year":"2016","title":"Scaling Up Word Clustering","authors":["J Dehdari, L Tan, J van Genabith"],"snippet":"... The parallel data comes from the WMT-2015 Common Crawl Corpus, News Commentary, Yandex 1M Corpus, and the Wiki Headlines Corpus.7 The monolingual data consists of 2007– 2014 News Commentary and News Crawl articles. ...","url":["http://anthology.aclweb.org/N/N16/N16-3009.pdf"]}
-{"year":"2016","title":"Selecting Domain-Specific Concepts for Question Generation With Lightly-Supervised Methods","authors":["Y Jin, PTV Le"],"snippet":"... 3 Datasets We make use of two datasets obtained from the In- ternet. One is 200k company profiles from CrunchBase. Another is 57k common crawl business news articles. We refer to these two corpora as “Company Profile Corpus” and “News Corpus”. ...","url":["https://www.researchgate.net/profile/Yiping_Jin2/publication/304751113_Selecting_Domain-Specific_Concepts_for_Question_Generation_With_Lightly-Supervised_Methods/links/57cfc28208ae057987ac127c.pdf"]}
-{"year":"2016","title":"Semantic Snippets via Query-Biased Ranking of Linked Data Entities","authors":["M Alsarem - 2016"],"snippet":"Page 1. Semantic Snippets via Query-Biased Ranking of Linked Data Entities Mazen Alsarem To cite this version: Mazen Alsarem. Semantic Snippets via Query-Biased Ranking of Linked Data Entities. In- formation Retrieval [cs.IR]. ...","url":["https://hal.archives-ouvertes.fr/tel-01327769/document"]}
-{"year":"2016","title":"Semantic word embedding neural network language models for automatic speech recognition","authors":["K Audhkhasi, A Sethy, B Ramabhadran - 2016 IEEE International Conference on …, 2016"],"snippet":"... The Gigaword corpus was a suitable choice because of its focus on news domain data in- stead of generic data sets such as Wikipedia or Common Crawl. We used a symmetric window size of 10 words for constructing the word co-occurrence matrix. ...","url":["http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=7472828"]}
-{"year":"2016","title":"Semantics derived automatically from language corpora necessarily contain human biases","authors":["A Caliskan-Islam, JJ Bryson, A Narayanan - arXiv preprint arXiv:1608.07187, 2016"],"snippet":"... Page 9. GloVe authors provide trained embeddings, which is a “Common Crawl” corpus obtained from a large-scale crawl of the web, containing 840 billion tokens (roughly, words). Tokens in this corpus are case-sensitive and ...","url":["http://arxiv.org/pdf/1608.07187"]}
-{"year":"2016","title":"Session: P44-Corpus Creation and Querying (1)","authors":["MK Bingel, P Banski, A Witt, C Data, F Lefevre, M Diab…"],"snippet":"... 960 Roland Schäfer CommonCOW: Massively Huge Web Corpora from CommonCrawl Data and a Method to Distribute them Freely under Restrictive EU Copyright Laws 990 Ioannis Manousos Katakis, Georgios Petasis and Vangelis Karkaletsis ...","url":["https://pdfs.semanticscholar.org/f62d/6d9b67532ccd66915481b7cb4047ba03a1f2.pdf"]}
-{"year":"2016","title":"Shared Task on Quality Assessment for Text Simplification","authors":["S Štajner, M Popovic, H Saggion, L Specia, M Fishel - Training"],"snippet":"... The parameters for the ensemble were obtained using particle swarm optimisation under multiple cross-validation scenarios. 2. Treelstm – The metric uses GloVe word vectors8 trained on the Common Crawl corpus and dependency parse trees. ...","url":["https://www.researchgate.net/profile/Maja_Popovic7/publication/301229567_Shared_Task_on_Quality_Assessment_for_Text_Simplification/links/570e179e08ae3199889d4eb5.pdf"]}
-{"year":"2016","title":"Sheffield Systems for the English-Romanian Translation Task","authors":["F Blain, X Song, L Specia"],"snippet":"... For the two last, we use subsets of both the News Commentary (93%) and the Common Crawl (13%), selected using XenC- v2.12 (Rousseau, 2013) in mode 23 with the parallel corpora (Europarl7, SETimes2) as in-domain data. ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2307.pdf"]}
-{"year":"2016","title":"SoK: Applying Machine Learning in Security-A Survey","authors":["H Jiang, J Nagra, P Ahammad - arXiv preprint arXiv:1611.03186, 2016"],"snippet":"Page 1. SoK: Applying Machine Learning in Security - A Survey Heju Jiang* , Jasvir Nagra, Parvez Ahammad ∗ Instart Logic, Inc. {hjiang, jnagra, pahammad }@instartlogic.com ABSTRACT The idea of applying machine learning ...","url":["https://arxiv.org/pdf/1611.03186"]}
-{"year":"2016","title":"Source Sentence Simplification for Statistical Machine Translation","authors":["E Hasler, A de Gispert, F Stahlberg, A Waite, B Byrne - Computer Speech & Language, 2016"],"snippet":"... translation lattices. We trained an English-German system on the WMT 2015 training data (Bojar et al., 2015) comprising 4.2M parallel sentences from the Europarl, News Commentary v10 and Commoncrawl corpora. We word ...","url":["http://www.sciencedirect.com/science/article/pii/S0885230816301711"]}
-{"year":"2016","title":"Syntactically Guided Neural Machine Translation","authors":["F Stahlberg, E Hasler, A Waite, B Byrne - arXiv preprint arXiv:1605.04569, 2016"],"snippet":"... The En-De training set includes Europarl v7, Common Crawl, and News Commentary v10. Sentence pairs with sentences longer than 80 words or length ratios exceeding 2.4:1 were deleted, as were Common Crawl sentences from other languages (Shuyo, 2010). ...","url":["http://arxiv.org/pdf/1605.04569"]}
-{"year":"2016","title":"SYSTEMS AND METHODS FOR SPEECH TRANSCRIPTION","authors":["A Hannun, C Case, J Casper, B Catanzaro, G Diamos… - US Patent 20,160,171,974, 2016"],"snippet":"... the decoding. The language model was trained on 220 million phrases of the Common Crawl (available at commoncrawl.org), selected such that at least 95% of the characters of each phrase were in the alphabet. Only the most ...","url":["http://www.freepatentsonline.com/y2016/0171974.html"]}
-{"year":"2016","title":"TAIPAN: Automatic Property Mapping for Tabular Data","authors":["I Ermilov, ACN Ngomo"],"snippet":"... RAM. Gold Standard We aimed to use T2D entity-level Gold Standard (T2D), a reference dataset which consists of 1 748 tables and reflects the actual distribution of the data in the Common Crawl,5 to evaluate our algorithms. ...","url":["http://svn.aksw.org/papers/2016/EKAW_Taipan/public.pdf"]}
-{"year":"2016","title":"Target-Side Context for Discriminative Models in Statistical Machine Translation","authors":["A Tamchyna, A Fraser, O Bojar, M Junczys-Dowmunt - arXiv preprint arXiv: …, 2016"],"snippet":"... Our English-German system is trained on the data available for the WMT14 translation task: Europarl (Koehn, 2005) and the Common Crawl corpus,3 roughly 4.3 million sentence pairs altogether. We tune the system on the WMT13 test set and we test on the WMT14 set. ...","url":["http://arxiv.org/pdf/1607.01149"]}
-{"year":"2016","title":"TAXI at SemEval-2016 Task 13: a Taxonomy Induction Method based on Lexico-Syntactic Patterns, Substrings and Focused Crawling","authors":["A Panchenko, S Faralli, E Ruppert, S Remus, H Naets…"],"snippet":"... 59G 59.2 – – – CommonCrawl 168000.0 ‡ – – – FocusedCrawl Food 22.8 7.9 3.4 3.6 ... WebISA. In addition to PattaMaika and PatternSim, we used a publicly available database of English hypernym relations extracted from the CommonCrawl corpus (Seitner et al., 2016). ...","url":["http://web.informatik.uni-mannheim.de/ponzetto/pubs/panchenko16.pdf"]}
-{"year":"2016","title":"Temporal Attention-Gated Model for Robust Sequence Classification","authors":["W Pei, T Baltrušaitis, DMJ Tax, LP Morency - arXiv preprint arXiv:1612.00385, 2016"],"snippet":"... 4.2.2 Experimental Setup We utilize 300-d Glove word vectors pretrained over the Common Crawl [27] as the features for each word of the sentences. Our model is well suitable to perform sentiment analysis using sentence-level labels. ...","url":["https://arxiv.org/pdf/1612.00385"]}
-{"year":"2016","title":"The 2016 KIT IWSLT Speech-to-Text Systems for English and German","authors":["TS Nguyen, M Müller, M Sperber, T Zenkel, K Kilgour…"],"snippet":"... Page 4. Text corpus # Words TED 3.6m Fisher 10.4m Switchboard 1.4m TEDLIUM dataselection 155m News + News-commentary + -crawl 4,478m Commoncrawl 185m GIGA 2323m Table 3: English language modeling data. Text corpus # Words ...","url":["http://workshop2016.iwslt.org/downloads/IWSLT_2016_paper_24.pdf"]}
-{"year":"2016","title":"The AFRL-MITLL WMT16 News-Translation Task Systems","authors":["J Gwinnup, T Anderson, G Erdmann, K Young, M Kazi… - Proceedings of the First …, 2016"],"snippet":"... to build a monolithic language model from the following sources: Yandex4, Commoncrawl (Smith et al., 2013), LDC Gigaword English v5 (Parker et al., 2011) and News Commentary. Submission system 1 included the data selected from the large Commoncrawl corpus as ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2313.pdf"]}
-{"year":"2016","title":"The CogALex-V Shared Task on the Corpus-Based Identification of Semantic Relations","authors":["E Santus, A Gladkova, S Evert, A Lenci - COLING 2016, 2016"],"snippet":"... Team Method (s) Corpus size Corpus GHHH Word analogies, linear regression and multi-task CNN 100B 6B 840B Google News (pre-trained word2vec embeddings, 300 dim.); Wikipedia+ Gigaword 5 (pre-trained GloVe embeddings, 300 dim.), Common Crawl (pre-trained ...","url":["https://sites.google.com/site/cogalex2016/home/accepted-papers/CogALex-V_Proceedings.pdf#page=83"]}
-{"year":"2016","title":"The Edinburgh/LMU Hierarchical Machine Translation System for WMT 2016","authors":["M Huck, A Fraser, B Haddow - Proc. of the ACL 2016 First Conf. on Machine …, 2016"],"snippet":"... CommonCrawl LM training data in background LM ... Utilizing a larger amount of target-side monolingual resources by appending the CommonCrawl corpus to the background LM's training data is very beneficial and increases the BLEU scores by around one point. ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2315.pdf"]}
-{"year":"2016","title":"The Edit Distance Transducer in Action: The University of Cambridge English-German System at WMT16","authors":["F Stahlberg, E Hasler, B Byrne - arXiv preprint arXiv:1606.04963, 2016","FSEHB Byrne"],"snippet":"This paper presents the University of Cambridge submission to WMT16. Motivated by the complementary nature of syntactical machine translation and neural machine translation (NMT), we exploit the synergies of Hiero and NMT in different …","url":["http://arxiv.org/pdf/1606.04963","https://ar5iv.labs.arxiv.org/html/1606.04963"]}
-{"year":"2016","title":"The ILSP/ARC submission to the WMT 2016 Bilingual Document Alignment Shared Task","authors":["V Papavassiliou, P Prokopidis, S Piperidis - Proceedings of the First Conference on …, 2016"],"snippet":"... 1http://commoncrawl.org/ 2http://nlp.ilsp.gr/redmine/ilsp-fc/ 3Including modules for metadata extraction, language identification, boilerplate removal, document clean-up, text classification and sentence alignment 733 ... Dirt cheap web-scale parallel text from the common crawl...","url":["http://www.aclweb.org/anthology/W/W16/W16-2375.pdf"]}
-{"year":"2016","title":"The JHU Machine Translation Systems for WMT 2016","authors":["S Ding, K Duh, H Khayrallah, P Koehn, M Post - … of the First Conference on Machine …, 2016"],"snippet":"... In addition, we included a large language model based on the CommonCrawl monolingual data ... of the language model trained on the monomlingual corpora extracted from Common Crawl... year, large corpora of monolingual data were extracted from Common Crawl (Buck et ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2310.pdf"]}
-{"year":"2016","title":"The Karlsruhe Institute of Technology Systems for the News Translation Task in WMT 2016","authors":["TL Ha, E Cho, J Niehues, M Mediani, M Sperber… - Proceedings of the First …, 2016"],"snippet":"... To im- prove the quality of the Common Crawl corpus be- ing used in training, we filtered out noisy sentence pairs using an SVM classifier as described in (Me- diani et al., 2011). All of our translation systems are basically phrase-based. ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2314.pdf"]}
-{"year":"2016","title":"The NTNU-YZU System in the AESW Shared Task: Automated Evalua-tion of Scientific Writing Using a Convolutional Neural Network","authors":["LH Lee, BL Lin, LC Yu, YH Tseng"],"snippet":"... For the GloVe representation, we adopted 4 different datasets for training the vectors including one from Wikipedia 2014 and Gigaword 5 (400K vo- cabulary), two common crawl datasets (uncased 1.9M vocabulary, and cased 2.2M vocabulary) and one Twitter dataset (1.2M ...","url":["http://anthology.aclweb.org/W/W16/W16-0513.pdf"]}
-{"year":"2016","title":"The RWTH Aachen Machine Translation System for IWSLT 2016","authors":["JT Peter, A Guta, N Rossenbach, M Graça, H Ney"],"snippet":"... ich war fünf Mal dort oben . . Figure 1: An example of multiple phrasal segmentations taken from the common crawl corpus. The JTR sequence is indicated by blue arcs. The distinct phrasal segmentations are shown in red and shaded green colour. log-linear framework. ...","url":["http://workshop2016.iwslt.org/downloads/IWSLT_2016_paper_23.pdf"]}
-{"year":"2016","title":"Topics of Controversy: An Empirical Analysis of Web Censorship Lists","authors":["Z Weinberg, M Sharif, J Szurdi, N Christin - Proceedings on Privacy Enhancing …, 2017"],"snippet":"... Common Crawl Finally, this is the closest available ap- proximation to an unbiased sample of the entire Web. The Common Crawl Foundation continuously operates a large-scale Web crawl and publishes the results [27]. Each crawl contains at least a billion pages. ...","url":["https://www.andrew.cmu.edu/user/nicolasc/publications/Weinberg-PETS17.pdf"]}
-{"year":"2016","title":"Toward Multilingual Neural Machine Translation with Universal Encoder and Decoder","authors":["TL Ha, J Niehues, A Waibel - arXiv preprint arXiv:1611.04798, 2016"],"snippet":"... translation and the web-crawled parallel data (CommonCrawl). ... network. We mix the TED parallel corpus and the substantial monolingual corpus (EPPS+NC+ CommonCrawl) and train a mix-source NMT system from those data. ...","url":["https://arxiv.org/pdf/1611.04798"]}
-{"year":"2016","title":"Towards a Complete View of the Certificate Ecosystem","authors":["B VanderSloot, J Amann, M Bernhard, Z Durumeric… - 2016"],"snippet":"... In 36th IEEE Symposium on Security and Privacy, May 2015. [5] Certificate Transparency: Extended validation in Chrome. https://www.certificate-transparency.org/ev-ct-plan. [6] Common Crawl. https://commoncrawl.org/. [7] The DROWN attack. https://drownattack.com/. ...","url":["https://jhalderm.com/pub/papers/https-perspectives-imc16.pdf"]}
-{"year":"2016","title":"Towards More Accurate Statistical Profiling of Deployed schema. org Microdata","authors":["R Meusel, D Ritze, H Paulheim - Journal of Data and Information Quality (JDIQ), 2016"],"snippet":"... Springer International Publishing. 44. Alex Stolz and Martin Hepp. 2015. Towards crawling the web for structured data: Pitfalls of common crawl for e-commerce. In Proceedings of the 6th International Workshop on Consuming Linked Data (COLD ISWC'15). ...","url":["http://dl.acm.org/citation.cfm?id=2992788"]}
-{"year":"2016","title":"Translation of Unknown Words in Low Resource Languages","authors":["B Gujral, H Khayrallah, P Koehn"],"snippet":"... worthy trade-off. Word Embedding: For this technique, we collect Hindi monolingual data from Wikipedia dump (Al-Rfou et al., 2013) and Commoncrawl (Buck et al., 2014),2 with a total of about 29 million tokens. For Uzbek, the ...","url":["https://pdfs.semanticscholar.org/f130/2e20b4dabb48b8442f857426c28b205287f1.pdf"]}
-{"year":"2016","title":"TripleSent: a triple store of events associated with their prototypical sentiment","authors":["V Hoste, E Lefever, S van der Waart van Gulik… - eKNOW 2016: The Eighth …, 2016"],"snippet":"... These events will be obtained by extracting patterns for highly explicit sentiment expressions (eg, “I hate” or “I love”) or from large web data crawls (eg, commoncrawl.org), which will subsequently be syntactically and semantically parsed to extract events and sentiment triples. ...","url":["https://biblio.ugent.be/publication/8071695/file/8071708"]}
-{"year":"2016","title":"Undercounting File Downloads from Institutional Repositories","authors":["P OBrien, K Arlitsch, L Sterman, J Mixter, J Wheeler… - Journal of Library …, 2016"],"snippet":"Page 1. © Patrick OBrien, Kenning Arlitsch, Leila Sterman, Jeff Mixter, Jonathan Wheeler, and Susan Borda Address correspondence to Patrick OBrien, Semantic Web Research Director, Montana State University, PO Box 173320, Bozeman, MT 59717-3320, USA. ...","url":["http://scholarworks.montana.edu/xmlui/bitstream/handle/1/9943/IR-Undercounting-preprint_2016-07.pdf?sequence=3&isAllowed=y"]}
-{"year":"2016","title":"User Modeling in Language Learning with Macaronic Texts","authors":["A Renduchintala, R Knowles, P Koehn, J Eisner - Proceedings of ACL, 2016"],"snippet":"... We translated each German sentence using the Moses Statistical Machine Translation (SMT) toolkit (Koehn et al., 2007). The SMT system was trained on the German-English Commoncrawl parallel text used in WMT 2015 (Bojar et al., 2015). ...","url":["https://www.cs.jhu.edu/~jason/papers/renduchintala+al.acl16-macmodel.pdf"]}
-{"year":"2016","title":"Using Feedforward and Recurrent Neural Networks to Predict a Blogger's Age","authors":["T Moon, E Liu"],"snippet":"... The embedding matrix L ∈ RV ×d is initialized for d = 300 with GloVe word vectors trained on the Common Crawl data set [9]. If a token does not correspond to any pre-trained word vector, a random word vector is generated with Xavier initialization [2]. The unembedded vector ...","url":["http://cs224d.stanford.edu/reports/tym1.pdf"]}
-{"year":"2016","title":"Vive la petite différence! Exploiting small differences for gender attribution of short texts","authors":["F Gralinski, R Jaworski, Ł Borchmann, P Wierzchon"],"snippet":"... The procedure of preparing the HSSS corpus was to take Common Crawl-based Web corpus1 of Polish [4] and grep for lines ... Classification with Deep Learning (2015) 4. Buck, C., Heafield, K., van Ooyen, B.: N-gram counts and language models from the common crawl...","url":["http://www.staff.amu.edu.pl/~rjawor/tsd-article.pdf"]}
-{"year":"2016","title":"Vive la Petite Différence!","authors":["F Graliński, R Jaworski, Ł Borchmann, P Wierzchoń - International Conference on …, 2016"],"snippet":"... The research was conducted on the publicly available corpus called “He Said She Said”, consisting of a large number of short texts from the Polish version of Common Crawl... Keywords. Gender attribution Text classification Corpus Common Crawl Research reproducibility. ...","url":["http://link.springer.com/chapter/10.1007/978-3-319-45510-5_7"]}
-{"year":"2016","title":"VoldemortKG: Mapping schema. org and Web Entities to Linked Open Data","authors":["A Tonon, V Felder, DE Difallah, P Cudré-Mauroux"],"snippet":"... that apply to the Common Crawl corpus.12 4 The VoldemortKG Knowledge Graph To demonstrate the potential of the dataset we release, we built a proof of concept knowledge graph called VoldemortKG. VoldemortKG integrates schema.org 12 http://commoncrawl.org/terms ...","url":["http://daplab.ch/wp-content/uploads/2016/08/voldemort.pdf"]}
-{"year":"2016","title":"What does the Web remember of its deleted past? An archival reconstruction of the former Yugoslav top-level domain","authors":["A Ben-David - New Media & Society, 2016"],"snippet":"... The completeness of the reconstruction effort could have been aided by consulting other large repositories of temporal Web data, such as Common Crawl, or by simply contacting the Internet Archive and requesting for all domains in the .yu domain. ...","url":["http://nms.sagepub.com/content/early/2016/04/27/1461444816643790.abstract"]}
-{"year":"2016","title":"What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation","authors":["F Hirschmann, J Nam, J Fürnkranz"],"snippet":"... 5.1 Dataset & Preprocessing Our models were trained on the data provided by the 2014 Workshop on Machine Translation (WMT). Specifically, we used the Europarl v7, Common Crawl, and News Commentary corpora. Our ...","url":["http://www.aclweb.org/anthology/C/C16/C16-1301.pdf"]}
-{"year":"2016","title":"WHAT: A Big Data Approach for Accounting of Modern Web Services","authors":["M Trevisan, I Drago, M Mellia, HH Song, M Baldi - 2016"],"snippet":"... [5] D. Plonka and P. Barford, “Flexible Traffic and Host Profiling via DNS Rendezvous,” in Proc. of the SATIN, 2011, pp. 1–8. [6] “Common Crawl,” http://commoncrawl.org/. [7] A. Finamore et al., “Experiences of Internet Traffic Monitoring with Tstat,” IEEE Netw., vol. 25, no. 3, pp. ...","url":["http://www.tlc-networks.polito.it/mellia/papers/BMLIT_web_meter.pdf"]}
-{"year":"2016","title":"Which argument is more convincing? Analyzing and predicting convincingness of Web arguments using bidirectional LSTM","authors":["I Habernal, I Gurevych"],"snippet":"... Memory (BLSTM) neural network for end-to-end processing.9 The input layer relies on pre-trained word embeddings, in particular GloVe (Pennington et al., 2014) trained on 840B tokens from Common Crawl;10 the embedding weights are further updated during training. ...","url":["https://www.informatik.tu-darmstadt.de/fileadmin/user_upload/Group_UKP/publikationen/2016/acl2016-convincing-arguments-camera-ready.pdf"]}
-{"year":"2016","title":"Wikipedia mining of hidden links between political leaders","authors":["KM Frahm, K Jaffrès-Runser, DL Shepelyansky - arXiv preprint arXiv:1609.01948, 2016"],"snippet":"... At present directed networks of real systems can be very large (about 4.2 million articles for the English Wikipedia edition in 2013 [10] or 3.5 billion web pages for a publicly accessible web crawl that was gathered by the Common Crawl Foundation in 2012 [28]). ...","url":["http://arxiv.org/pdf/1609.01948"]}
-{"year":"2016","title":"WOLVESAAR at SemEval-2016 Task 1: Replicating the Success of Monolingual Word Alignment and Neural Embeddings for Semantic Textual Similarity","authors":["H Bechara, R Gupta, L Tan, C Orasan, R Mitkov… - Proceedings of SemEval, 2016"],"snippet":"... 2We use the 300 dimensions vectors from the GloVe model trained on the Commoncrawl Corpus with 840B tokens, 2.2M vocabulary. distributions p and pθ using regularised KullbackLeibler (KL) divergence. J(θ) = 1 n n ∑ i=1KL(p(i)∣ ∣ ∣ ∣ p (i) θ ) + λ2||θ||2 2 (8) ...","url":["http://www.anthology.aclweb.org/S/S16/S16-1096.pdf"]}
-{"year":"2016","title":"Word Representation on Small Background Texts","authors":["L Li, Z Jiang, Y Liu, D Huang - Chinese National Conference on Social Media …, 2016"],"snippet":"... For example, Pennington et al. (2014) used Wikipedia, Gigaword 5 and Common Crawl to learn word representations, each of which contained billions of tokens. There was not always a monotonic increase in performance as the amount of background texts increased. ...","url":["http://link.springer.com/chapter/10.1007/978-981-10-2993-6_12"]}
-{"year":"2016","title":"Word2Vec vs DBnary: Augmenting METEOR using Vector Representations or Lexical Resources?","authors":["C Servan, A Berard, Z Elloumi, H Blanchon, L Besacier - arXiv preprint arXiv: …, 2016","C Servan, A Bérard, Z Elloumi, H Blanchon, L Besacier"],"snippet":"... German–English Europarl V7 + news commentary V10 2.1 M 57.2 M 59.7 M Russian–English Common Crawl + news commentary V10 + Yandex 2.0 M 47.2 M 50.3 M Table 2: Bilingual corpora used to train the word embeddings for each language pair. ...","url":["http://www.aclweb.org/anthology/C/C16/C16-1110.pdf","https://arxiv.org/pdf/1610.01291"]}
-{"year":"2016","title":"Yandex School of Data Analysis approach to English-Turkish translation at WMT16 News Translation Task","authors":["A Dvorkovich, S Gubanov, I Galinskaya - Proceedings of the First Conference on …, 2016"],"snippet":"... 2.7 Data For training translation model, language models, and NMT reranker, we used only the provided constrained data (SETIMES 2 parallel TurkishEnglish corpus, and monolingual Turkish and En- glish Common Crawl corpora). ...","url":["http://www.aclweb.org/anthology/W/W16/W16-2311.pdf"]}
-{"year":"2017","title":"$ k $-Nearest Neighbor Augmented Neural Networks for Text Classification","authors":["Z Wang, W Hamza, L Song - arXiv preprint arXiv:1708.07863, 2017"],"snippet":"... Table 1 shows the statistics of all the datasets. Experiment Settings We initialize word embeddings with the 300-dimensional GloVe word vectors pre-trained from the 840B Common Crawl corpus (Pennington, Socher, and Manning, 2014). ...","url":["https://arxiv.org/pdf/1708.07863"]}
-{"year":"2017","title":"A Context-Aware Recurrent Encoder for Neural Machine Translation","authors":["B Zhang, D Xiong, J Su, H Duan - IEEE/ACM Transactions on Audio, Speech, and …, 2017"],"snippet":"Page 1. 2329-9290 (c) 2017 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This ...","url":["http://ieeexplore.ieee.org/abstract/document/8031316/"]}
-{"year":"2017","title":"A Continuously Growing Dataset of Sentential Paraphrases","authors":["W Lan, S Qiu, H He, W Xu"],"snippet":"... We used 300-dimensional word vectors trained on Common Crawl and Twitter, summed the vectors for each sentence, and computed the cosine similarity. WMF/OrMF Weighted Matrix Factorization (WMF) (Guo and Diab, 2012) is an unsupervised latent space model. ...","url":["https://pdfs.semanticscholar.org/dfd2/bc4a55bfe59554ec1d5086e5c0f5a503c8a8.pdf"]}
-{"year":"2017","title":"A Framework for Enriching Lexical Semantic Resources with Distributional Semantics","authors":["C Biemann, S Faralli, A Panchenko, SP Ponzetto - arXiv preprint arXiv:1712.08819, 2017"],"snippet":"… This makes our approach highly scalable: in recent experiments we have been accordingly able to apply our method at web scale on the CommonCrawl6, the largest existing public repository of web content … 6 https://commoncrawl.org Page 15 …","url":["https://arxiv.org/pdf/1712.08819"]}
-{"year":"2017","title":"A Hybrid Framework for Text Modeling with Convolutional RNN","authors":["C Wang, F Jiang, H Yang - Proceedings of the 23rd ACM SIGKDD International …, 2017"],"snippet":"Page 1. A Hybrid Framework for Text Modeling with Convolutional RNN Chenglong Wang, Feijun Jiang, Hongxia Yang Alibaba Group 969 West Wenyi Road Hangzhou, China 310000 {chenglong.cl,feijun.jiang ,yang.yhx}@alibaba-inc.com ...","url":["http://dl.acm.org/citation.cfm?id=3098140"]}
-{"year":"2017","title":"A Large Self-Annotated Corpus for Sarcasm","authors":["M Khodak, N Saunshi, K Vodrahalli - arXiv preprint arXiv:1704.05579, 2017"],"snippet":"... simple low-dimensional document representation. For word vectors we use normalized 300-dimensional GloVe representations trained on the Common Crawl corpus (Pennington et al., 2014). Since we are establishing baselines ...","url":["https://arxiv.org/pdf/1704.05579"]}
-{"year":"2017","title":"A Lightweight Front-end Tool for Interactive Entity Population","authors":["H Oiwa, Y Suhara, J Komiya, A Lopatenko - arXiv preprint arXiv:1708.00481, 2017"],"snippet":"... We prepared models trained based on the CommonCrawl corpus and the Twitter corpus1. Note that the specification of the expansion algorithm is not limited to the algorithm described in this paper, as LUWAK considers the Expansion API as an external function. ...","url":["https://arxiv.org/pdf/1708.00481"]}
-{"year":"2017","title":"A Memory-Augmented Neural Model for Automated Grading","authors":["S Zhao, Y Zhang, X Xiong, A Botelho, N Heffernan - 2017"],"snippet":"... networks. We used the publicly available pre-trained Glove word embeddings [23], which was trained on 42 billion tokens of web data, from Common Crawl (http://commoncrawl.org/). The dimension of each word vector is 300. ...","url":["https://siyuanzhao.github.io/pdf/L_S_2017.pdf"]}
-{"year":"2017","title":"A Nested Attention Neural Hybrid Model for Grammatical Error Correction","authors":["J Ji, Q Wang, K Toutanova, Y Gong, S Truong, J Gao - arXiv preprint arXiv: …, 2017"],"snippet":"Page 1. A Nested Attention Neural Hybrid Model for Grammatical Error Correction Jianshu Ji†, Qinlong Wang†, Kristina Toutanova‡∗, Yongen Gong†, Steven Truong†, Jianfeng Gao§ †Microsoft AI & Research ‡Google Research ...","url":["https://arxiv.org/pdf/1707.02026"]}
-{"year":"2017","title":"A Neural Approach to Source Dependency-Based Context Model for Statistical Machine Translation","authors":["K Chen, T Zhao, M Yang, L Liu, A Tamura, R Wang… - IEEE/ACM Transactions on …, 2017"],"snippet":"Page 1. 2329-9290 (c) 2017 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["http://ieeexplore.ieee.org/abstract/document/8105847/"]}
-{"year":"2017","title":"A Neural Chatbot with Personality","authors":["H Nguyen, D Morales, T Chin"],"snippet":"... We also experiment with initializing embeddings for en- coder vocabulary and decoder vocabulary using GLoVe 300d Common Crawl [8]. To ensure that our model was implemented correctly, we trained it on a subset of data (3,000 pairs) and saw that the loss converged to 0 ...","url":["http://web.stanford.edu/class/cs224n/reports/2761115.pdf"]}
-{"year":"2017","title":"A Query Log Analysis of Dataset Search","authors":["E Kacprzak, LM Koesten, LD Ibánez, E Simperl… - … 2017, Rome, Italy, June 5-8, …, 2017"],"snippet":"... Cafarella estimates more than one billion sources of data on the web as of February 2011, counting structured data extracted from Web pages [3]; and The Web Data Commons project recently extracted 233 million data tables from the Common Crawl [12]. ...","url":["http://books.google.de/books?hl=en&lr=lang_en&id=kiYmDwAAQBAJ&oi=fnd&pg=PA429&dq=commoncrawl&ots=a4pucnNpg8&sig=rhbU3CaLPahnItWRuhUlAHj8J9E"]}
-{"year":"2017","title":"A Semi-supervised Framework for Image Captioning","authors":["W Chen, A Lucchi, T Hofmann"],"snippet":"... we use both the 2008-2010 News-CommonCrawl and Eu- roparl corpus 3 as out-of-domain training data. Combined, these two datasets contain ∼ 3M sentences, from which we removed sentences shorter than 7 words or longer than 30 words. ...","url":["https://pdfs.semanticscholar.org/4fa6/a688f350831503d158f8f618c58d1e06bc5d.pdf"]}
-{"year":"2017","title":"A Shared Task on Bandit Learning for Machine Translation","authors":["A Sokolov, J Kreutzer, K Sunderland, P Danchenko"],"snippet":"... Data. For training initial or seed MT systems (the input to Algorithm 1), out-of-domain parallel data was restricted to DE-EN parts of Europarl v7, NewsCommentary v12, CommonCrawl and Rapid data from the WMT 2017 News Translation (constrained) task4. Furthermore ...","url":["http://www.cl.uni-heidelberg.de/~riezler/publications/papers/WMT2017.pdf"]}
-{"year":"2017","title":"A simple sequence attention model for machine comprehension","authors":["M Hasegawa"],"snippet":"... The data was tokenized with a basic tokenizer and the Stanford GloVe [1] was used as trained word embeddings. To ensure a larger coverage among the extracted tokens the larger ”Common Crawl” with 840B tokens, 2.2M vocab and 300d vectors embeddings were used. ...","url":["https://web.stanford.edu/class/cs224n/reports/2761077.pdf"]}
-{"year":"2017","title":"A Survey of Domain Adaptation for Statistical Machine Translation","authors":["H Cuong, K Sima'an"],"snippet":"... Surprisingly, degradation of translation quality is observed even when we train an MT system on large heterogeneous corpora (eg EuroParl, Common Crawl Corpus, UN Corpus, News Commentary) (Shah et al, 2012; Carpuat et al, 2014; Cuong et al, 2016). ...","url":["https://staff.fnwi.uva.nl/c.hoang/mt20172.pdf"]}
-{"year":"2017","title":"A Teacher-Student Framework for Zero-Resource Neural Machine Translation","authors":["Y Chen, Y Liu, Y Cheng, VOK Li"],"snippet":"... For the WMT corpus, we evaluate our approach on a Spanish-French (Es-Fr) translation task with a zero-resource setting. We combine the following corpora to form the Es-En and En-Fr parallel corpora: Common Crawl, News Commentary, Europarl v7 and UN. ...","url":["http://nlp.csai.tsinghua.edu.cn/~ly/papers/acl2017_cy.pdf"]}
-{"year":"2017","title":"A Unified Query-based Generative Model for Question Generation and Question Answering","authors":["L Song, Z Wang, W Hamza - arXiv preprint arXiv:1709.01058, 2017"],"snippet":"... The encoder and decoder share the same pre-trained word embeddings, which are the 300-dimensional GolVe (Pennington, Socher, and Manning, 2014) word vectors pre-trained from the 840B common crawl corpus, and the embeddings are not updated during training. ...","url":["https://arxiv.org/pdf/1709.01058"]}
-{"year":"2017","title":"A Web Corpus for eCare: Collection, Annotation and Learning-Preliminary Results-DRAFT: 20 March 2017","authors":["M Santini, M Alirezai, M Nyström, A Jönsson"],"snippet":"... web, neither within the ”web as a corpus” experience, nor within the ”wacky” initiative, nor with Common Crawl corpus7. 5 See https://en.wikipedia.org/wiki/Fair_use 6 See https://www.jisc.ac. uk/guides/text-and-data-mining-copyright-exception 7 See http://commoncrawl.org/the ...","url":["https://www.researchgate.net/profile/Marina_Santini/publication/315390867_A_Web_Corpus_for_eCare_Collection_Annotation_and_Learning_-_Preliminary_Results_-/links/58cfb829458515b6ed8c1527/A-Web-Corpus-for-eCare-Collection-Annotation-and-Learning-Preliminary-Results.pdf"]}
-{"year":"2017","title":"A Web Corpus for eCare: Collection, Lay Annotation and Learning-First Results","authors":["M Santini, A Jönsson, M Nyström, M Alirezai"],"snippet":"... from the web, neither within the \"web as a corpus\" experience, nor within the \"wacky\" initiative, nor with Common Crawl corpus9. ... for human language technology: introducing an LRE special section\" Lang Resources & Evaluation 2017 51 9See http://commoncrawl.org/the ...","url":["https://www.researchgate.net/profile/Marina_Santini/publication/318379265_A_Web_Corpus_for_eCare_Collection_Lay_Annotation_and_Learning_-First_Results-/links/596650de0f7e9b80917fea3e/A-Web-Corpus-for-eCare-Collection-Lay-Annotation-and-Learning-First-Results.pdf"]}
-{"year":"2017","title":"A Web Page Distillation Strategy for Efficient Focused Crawling Based on Optimized Naïve Bayes (ONB) Classifier","authors":["AI Saleh, AE Abulwafa, MF Al Rahmawy - Applied Soft Computing, 2017"],"snippet":"The target of a focused crawler (FC) is to retrieve pages related to a specific domain of interest (DOI). However, FCs may be hasted if bad links were injected.","url":["http://www.sciencedirect.com/science/article/pii/S1568494616306536"]}
-{"year":"2017","title":"Abstract Meaning Representation Parsing using LSTM Recurrent Neural Networks","authors":["M Hutchinson","W Foland, JH Martin - Proceedings of the 55th Annual Meeting of the …, 2017"],"snippet":"... The use of distributed word representations generated from large text corpora is pervasive in modern NLP. We start with 300 dimension GloVe representations (Pennington et al., 2014) trained on the 840 billion word common crawl (Smith et al., 2013). ...","url":["http://www.aclweb.org/anthology/P17-1043","https://zdoc.pub/abstract-meaning-representation-parsing-using-lstm-recurrent.html"]}
-{"year":"2017","title":"Accelerating Innovation Through Analogy Mining","authors":["T Hope, J Chan, A Kittur, D Shahaf - arXiv preprint arXiv:1706.05585, 2017"],"snippet":"... In more formal terms, let wi = (w1 i ,w2 i ,...,wT i) be the sequence of GloVe [27] word vectors (pre-trained on Common Crawl web data), representing (x1 i ,x2 i ,...,xT i ). We select all xi word vectors for which ˜p j ik = 1(˜m j ik = 1) for some k, and concatenate them into one ...","url":["https://arxiv.org/pdf/1706.05585"]}
-{"year":"2017","title":"Accurate Sentence Matching with Hybrid Siamese Networks","authors":["M Nicosia, A Moschitti - Proceedings of the 2017 ACM on Conference on …, 2017"],"snippet":"… Their training split contains 384,348 pairs, and the balanced development and test sets contain 10,000 pairs each. The embeddings are a subset of the 300-dimensional GloVe word vectors pretrained on the Common Crawl corpus, 3 covering the Quora dataset vocabulary …","url":["http://dl.acm.org/citation.cfm?id=3133156"]}
-{"year":"2017","title":"Acquiring Common Sense Spatial Knowledge through Implicit Spatial Templates","authors":["G Collell, L Van Gool, MF Moens - arXiv preprint arXiv:1711.06821, 2017"],"snippet":"… 4.5 Word embeddings We use 300-dimensional GloVe word embeddings (Pennington, Socher, and Manning 2014) pre-trained on the Common Crawl corpus (consisting of 840B-tokens), which we obtain from the authors' website.8 …","url":["https://arxiv.org/pdf/1711.06821"]}
-{"year":"2017","title":"Adaptation and Combination of NMT Systems: The KIT Translation Systems for IWSLT 2016","authors":["E Cho, J Niehues, TL Ha, M Sperber, M Mediani… - Proceedings of the 13th …, 2016"],"snippet":"... to 1.0. We use a beam search for decoding, with the beam size of 12. The baseline systems were trained on the WMT parallel data. For both languages, this consists of the EPPS, NC, CommonCrawl corpus. In addition, we ...","url":["http://workshop2016.iwslt.org/downloads/IWSLT_2016_paper_17.pdf"]}
-{"year":"2017","title":"Adapting Sequence Models for Sentence Correction","authors":["A Schmaltz, Y Kim, AM Rush, SM Shieber - arXiv preprint arXiv:1707.09067, 2017"],"snippet":"... provided access to SRILM (Stolcke, 2002) for running Junczys-Dowmunt and Grundkiewicz (2016) 7We found that including the features and data associated with the large language models of Junczys-Dowmunt and Grundkiewicz (2016), created from Common Crawl text ...","url":["https://arxiv.org/pdf/1707.09067"]}
-{"year":"2017","title":"Adversarial Training for Cross-Domain Universal Dependency Parsing","authors":["M Sato, H Manabe, H Noji, Y Matsumoto"],"snippet":"... initialized POS tag embeddings. For the model 2The pre-trained word embeddings are provided by the CoNLL 2017 Shared Task organizers. These are trained with CommonCrawl and Wikipedia. with adversarial training, we ...","url":["http://universaldependencies.org/conll17/proceedings/pdf/K17-3007.pdf"]}
-{"year":"2017","title":"Agree to Disagree: Improving Disagreement Detection with Dual GRUs","authors":["S Hiray, V Duppada"],"snippet":"... NLP tasks [24] [25]. For this task of (dis)agreement classification, we use GloVe embeddings of 300 dimensions trained on Common Crawl with 840 billion tokens, 2.2 million vocabulary. Page 3. 4.2. Lexicons We used affect, sentiment ...","url":["https://www.deepaffects.com/s/agree-to-disagree.pdf"]}
-{"year":"2017","title":"All-but-the-Top: Simple and Effective Postprocessing for Word Representations","authors":["J Mu, S Bhat, P Viswanath - arXiv preprint arXiv:1702.01417, 2017"],"snippet":"... We test our observations on various word representations: four publicly available word representations (WORD2VEC1 (Mikolov et al., 2013) trained using Google News, GLOVE2 (Pennington et al., 2014) trained using Common Crawl, RAND-WALK (Arora et al., 2016 ...","url":["https://arxiv.org/pdf/1702.01417"]}
-{"year":"2017","title":"An Empirical Analysis of NMT-Derived Interlingual Embeddings and their Use in Parallel Sentence Identification","authors":["C España-Bonet, ÁC Varga, A Barrón-Cedeño… - arXiv preprint arXiv: …, 2017","J van Genabith, A Barron-Cedeno, C España-Bonet…"],"snippet":"... context vectors. The parallel corpus includes data from United Na- tions (Rafalovitch and Dale, 2009), Common Crawl2, News Commentary3 and IWSLT4. We train system S1-w after cleaning and tokenising the texts. We ...","url":["https://arxiv.org/pdf/1704.05415","https://deepai.org/publication/an-empirical-analysis-of-nmt-derived-interlingual-embeddings-and-their-use-in-parallel-sentence-identification"]}
-{"year":"2017","title":"An End-to-End Neural Architecture for Reading Comprehension","authors":["M Burkle, M Camacho, N Danyliw"],"snippet":"... referencing a fixed sized vocabulary using GloVe word embeddings from the Wikipedia 6B word dataset or the CommonCrawl 840B word ... Wikipedia corpus of ∼6 billion words, we moved to the 300-dimensional word embeddings trained on the Common Crawl vocabulary of ...","url":["http://web.stanford.edu/class/cs224n/reports/2761845.pdf"]}
-{"year":"2017","title":"An In-Depth Experimental Comparison of RNTNs and CNNs for Sentence Modeling","authors":["Z Ahmadi, M Skowron, A Stier, S Kramer"],"snippet":"... On other datasets, we use the model trained on the web data from Common Crawl which contains a case-sensitive vocabulary of size 2.2 million. Experiments show that RNTNs work best when the word vector dimension is set between 25 and 35 [11]. ...","url":["http://www.ofai.at/~marcin.skowron/papers/DS2017.pdf"]}
-{"year":"2017","title":"An overview of Lithuanian Internet media n-gram corpus","authors":["I Bumbuliene, L Boizou, J Mandravickaite, T Krilavicius - 2017"],"snippet":"... 19(1), pp. 61-93, 2013. [2] C. Buck, K. Heafield, B. Van Ooyen, “N-gram counts and language models from the common crawl,” in LREC, vol. 2. Citeseer, p. 4, 2014. [3] A. Pauls, D. Klein, “Faster and smaller n-gram language models,” in Proc. ...","url":["http://ceur-ws.org/Vol-1853/p05.pdf"]}
-{"year":"2017","title":"Analogy Mining for Specific Design Needs","authors":["K Gilon, FY Ng, J Chan, HL Assaf, A Kittur, D Shahaf - arXiv preprint arXiv …, 2017"],"snippet":"… We use Glove pre-trained on the Common Crawl dataset (840B tokens, 300d vectors)1. We then normalize each document vector, and calculate cosine similarity (which is the same as Euclidean distance in this case) between the resulting vectors for each seed and all other …","url":["https://arxiv.org/pdf/1712.06880"]}
-{"year":"2017","title":"Analysing and Improving embedded Markup of Learning Resources on the Web","authors":["S Dietze, D Taibi, R Yu, P Barker, M d'Aquin - 2017"],"snippet":"... 6 http://commoncrawl.org/ 7 http://grouper.ieee.org/groups/ltsc/wg12/20020612-Final-LOMDraft.html 8 https://www.imsglobal.org ... The Web Data Commons [1], a recent initiative investigating the Common Crawl, ie a Web crawl of approximately 2 billion HTML pages from over ...","url":["https://www.researchgate.net/profile/Stefan_Dietze/publication/313964715_Analysing_and_Improving_embedded_Markup_of_Learning_Resources_on_the_Web/links/58b05d1545851503be97ddfc/Analysing-and-Improving-embedded-Markup-of-Learning-Resources-on-the-Web.pdf"]}
-{"year":"2017","title":"Analysis of semantic URLs to support automated linking of structured data on the web","authors":["S Lynden - Proceedings of the 7th International Conference on …, 2017"],"snippet":"... The Web Data Commons [13] effort to study the evolution of structured data on the web analyse the Common Crawl Web Corpus annually, most recently finding that about 38% of web pages contain some form of structured data. ...","url":["http://dl.acm.org/citation.cfm?id=3102265"]}
-{"year":"2017","title":"Analyzing Movie Reviews Sentiment","authors":["D Sarkar, R Bali, T Sharma - Practical Machine Learning with Python, 2018"],"snippet":"In this chapter, we continue with our focus on case-study oriented chapters, where we will focus on specific real-world problems and scenarios and how we can use Machine Learning to solve them. We wil.","url":["https://link.springer.com/chapter/10.1007/978-1-4842-3207-1_7"]}
-{"year":"2017","title":"Analyzing Neural MT Search and Model Performance","authors":["J Niehues, E Cho, TL Ha, A Waibel - ACL 2017, 2017"],"snippet":"... For the single models, we apply the early stopping based on the validation score. The baseline system is trained on the WMT parallel data, namely EPPS, NC, CommonCrawl and TED corpus. As validation data we used the newstest13 set from IWSLT evaluation campaign. ...","url":["http://www.aclweb.org/anthology/W/W17/W17-32.pdf#page=23"]}
-{"year":"2017","title":"Analyzing the compositional properties of word embeddings","authors":["T Scheepers, E Gavves, E Kanoulas"],"snippet":"... 3For GloVe we used the representations from the Common Crawl which has 840B tokens and a vocabulary of 2.2M. ... trained on used news data, where fastText and GloVe use more definitional data, Wikipedia and Common Crawl respectively. ...","url":["https://thijs.ai/papers/scheepers-gavves-kanoulas-analyzing-compositional-properties.pdf"]}
-{"year":"2017","title":"Any-gram Kernels for Sentence Classification: A Sentiment Analysis Case Study","authors":["R Kaljahi, J Foster - arXiv preprint arXiv:1712.07004, 2017"],"snippet":"… We use cosine similarity for word embedding similarities and the GloVe (Pennington et al., 2014) Common Crawl (1.9M vocabulary) word embeddings with a dimensionality of 300.6 … (2014). The GloVe Common Crawl vectors, however, performed better. Page 7 …","url":["https://arxiv.org/pdf/1712.07004"]}
-{"year":"2017","title":"AraVec: A set of Arabic Word Embedding Models for use in Arabic NLP","authors":["AB Soliman, K Eissa, SR El-Beltagy - Linguistics, 2017"],"snippet":"... Here it is important to note that the Common Crawl project does not provide any technique for identifying or selecting the language of web pages to ... 5 http://www.internetworldstats.com/stats19. htm 6 http://www.internetworldstats.com/stats5.htm 7 http://commoncrawl.org 8 https ...","url":["https://www.researchgate.net/profile/Samhaa_El-Beltagy2/publication/319880027_AraVec_A_set_of_Arabic_Word_Embedding_Models_for_use_in_Arabic_NLP/links/59bfef730f7e9b48a29ba3a8/AraVec-A-set-of-Arabic-Word-Embedding-Models-for-use-in-Arabic-NLP.pdf"]}
-{"year":"2017","title":"Architecting for Performance Clarity in Data Analytics Frameworks","authors":["K Ousterhout - 2017"],"snippet":"Page 1. Architecting for Performance Clarity in Data Analytics Frameworks Kay Ousterhout Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2017-158 http://www2 ...","url":["https://www2.eecs.berkeley.edu/Pubs/TechRpts/2017/EECS-2017-158.pdf"]}
-{"year":"2017","title":"Archival Crawlers and JavaScript: Discover More Stuff but Crawl More Slowly","authors":["JF Brunelle, MC Weigle, ML Nelson - Digital Libraries (JCDL), 2017 ACM/IEEE Joint …, 2017"],"snippet":"... If our method was applied to the July 2015 Common Crawl dataset, a web-scale archival crawler will discover an additional 7.17 PB (5.12 times more) of information per year. This illustrates the significant increase in resources necessary for more thorough archival crawls. ...","url":["http://ieeexplore.ieee.org/abstract/document/7991554/"]}
-{"year":"2017","title":"Are distributional representations ready for the real world? Evaluating word vectors for grounded perceptual meaning","authors":["L Lucy, J Gauthier - arXiv preprint arXiv:1705.11168, 2017"],"snippet":"... attributive features. Collell and Moens (2016) find that word representations fail to pre- # word tokens # word types GloVe (Common Crawl) 840B 2.2M GloVe (Wiki+Gigaword) 6B 400K word2vec 100B 3M Table 1: Statistics ...","url":["https://arxiv.org/pdf/1705.11168"]}
-{"year":"2017","title":"Assessing Convincingness of Arguments in Online Debates with Limited Number of Features","authors":["LA Chalaguine, C Schulz"],"snippet":"... 6http://nlp.stanford.edu/projects/glove/ 7http://commoncrawl.org/ 8because including stems, lemmas or both had no impact on the results we included stems only in our “top feature set” because they are less expensive to compute 80 Page 7. ture resulted in 66% in our case. ...","url":["https://www.aclweb.org/anthology/E/E17/E17-4008.pdf"]}
-{"year":"2017","title":"ATOL: A Framework for Automated Analysis and Categorization of the Darkweb Ecosystem","authors":["SGPPV Yegneswaran, KNA Das - 2017"],"snippet":"... 2016), and an open repository of (non-onion) Web crawling data, called Common Crawl (Common Crawl Foundation 2016). Using these data sources as starting points, we developed tools to acquire additional onion addresses both from the onion Web and the open Web. ...","url":["http://www.csl.sri.com/users/shalini/atol_aics17_cameraready.pdf"]}
-{"year":"2017","title":"Attention-based Dialog Embedding for Dialog Breakdown Detection","authors":["C Park, K Kim, S Kim"],"snippet":"… sentence. We used GloVe vectors of dimension 100 trained by the Twitter data. We used one from Twitter data rather than Common Crawl data be- cause it is more closely related to the general chat domain of our task. After …","url":["http://workshop.colips.org/dstc6/papers/track3_paper14_park.pdf"]}
-{"year":"2017","title":"Attributes2Classname: A discriminative model for attribute-based unsupervised zero-shot learning","authors":["B Demirel, RG Cinbis, NI Cinbis - arXiv preprint arXiv:1705.01734, 2017"],"snippet":"... For each class and attribute name, we generate a 300-dimensional word embedding vector using GloVe [26] based on Common Crawl Data2 ... 2http://commoncrawl.org/the-data/ 3http://nlp.stanford. edu/projects/glove/ 4We will release our code and models upon publication. ...","url":["https://arxiv.org/pdf/1705.01734"]}
-{"year":"2017","title":"Automated Categorization of Onion Sites for Analyzing the Darkweb Ecosystem","authors":["S Ghosh, A Das, P Porras, V Yegneswaran, A Gehani - 2017"],"snippet":"... Our sources of seed data include various published onion datasets( [32], [5], [25], [22]), .onion references from a large collection of recursive DNS resolvers [17], and an open repository of (non-onion) web crawling data, called Common Crawl [11]. ...","url":["http://www.csl.sri.com/users/gehani/papers/KDD-2017.Onions.pdf"]}
-{"year":"2017","title":"Automatic Learning Content Sequence via Linked Open Data","authors":["R Manrique"],"snippet":"... in [14, 13]. We also plan to use a recent release dataset [5] that contains all embedded Learning Resource Metadata Initiative (LRMI)4 markup statements extracted from the Common Crawl releases 2013-2015. Each entity description ...","url":["https://iswc2017.ai.wu.ac.at/wp-content/uploads/papers/DC/paper_19.pdf"]}
-{"year":"2017","title":"Automatic Threshold Detection for Data Selection in Machine Translation","authors":["MS Duma, W Menzel - WMT 2017, 2017"],"snippet":"... The in-domain corpora were made available by the competition and the general domain corpora we have chosen to select data from are the Wikipedia corpora (Wolk and Marasek, 2014) and the Commoncrawl corpora1. Experiments 1http://commoncrawl. org/ 483 Page 508. ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=507"]}
-{"year":"2017","title":"Better Text Understanding Through Image-To-Text Transfer","authors":["K Kurach, S Gelly, M Jastrzebski, P Haeusser… - arXiv preprint arXiv: …, 2017"],"snippet":"... We used word embeddings obtained from three methods: • Glove: embeddings proposed in [20], trained on a Common Crawl dataset with 840 billion tokens. • M-Skip-Gram: embeddings proposed in [12], trained on Wikipedia and a set of images from ImageNet. ...","url":["https://arxiv.org/pdf/1705.08386"]}
-{"year":"2017","title":"Biasing Attention-Based Recurrent Neural Networks Using External Alignment Information","authors":["T Alkhouli, H Ney"],"snippet":"... (1). We use the full bilingual data of the English→Romanian task. For the German→English task, we choose the common crawl, news commentary and European parliament bilingual data. ... This is to remove noisy sentence pairs that are frequent in the common crawl corpus. ...","url":["https://www-i6.informatik.rwth-aachen.de/publications/download/1036/Alkhouli-WMT%202017-2017.pdf"]}
-{"year":"2017","title":"Big Data","authors":["R Womack"],"snippet":"Page 1. Topics in Data Science / Өгөгдлийн шинжлэх ухаан Rutgers University has made this article freely available. Please share how this access benefits you. Your story matters. [https://rucore.libraries.rutgers.edu/rutgers-lib/52378/story/] …","url":["https://rucore.libraries.rutgers.edu/rutgers-lib/52378/PDF/1/play/"]}
-{"year":"2017","title":"Big Data: A Very Short Introduction","authors":["DE Holmes - 2017"]}
-{"year":"2017","title":"Bilateral Multi-Perspective Matching for Natural Language Sentences","authors":["Z Wang, W Hamza, R Florian - arXiv preprint arXiv:1702.03814, 2017"],"snippet":"... 4.5. 4.1 Experiment Settings We initialize the word embeddings in the word representation layer with the 300-dimensional GloVe word vectors pretrained from the 840B Common Crawl corpus [Pennington et al., 2014]. For ...","url":["https://arxiv.org/pdf/1702.03814"]}
-{"year":"2017","title":"Bilingual Word Embeddings for Bilingual Terminology Extraction from Specialized Comparable Corpora","authors":["A Hazem, E Morin - Proceedings of the Eighth International Joint …, 2017"],"snippet":"… and economic commentary crawled from the web (NC), Europarl corpus is a parallel corpus extracted from the proceedings of the European Parliament (EP7), JRC acquis corpus is a collection of legislative European Union documents (JRC) and Common Crawl corpus (CC …","url":["http://www.aclweb.org/anthology/I17-1069"]}
-{"year":"2017","title":"BLEU2VEC: the Painfully Familiar Metric on Continuous Vector Space Steroids","authors":["A Tättar, M Fishel - WMT 2017, 2017"],"snippet":"... modifications. data from the WMT'2017 news translation shared task: we took a random 50 million sentences from the News Crawl corpora for each language (ex- cept Chinese, where we used a portion of Common Crawl). While ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=643"]}
-{"year":"2017","title":"Bloom Filters for ReduceBy, GroupBy and Join in Thrill","authors":["A Noe, DIDMT Bingmann - 2017"],"snippet":"Page 1. Master thesis Bloom Filters for ReduceBy, GroupBy and Join in Thrill Alexander Noe Date: 12. January 2017 Supervisors: Prof. Dr. Peter Sanders Dipl. Inform. Dipl. Math. Timo Bingmann Institute of Theoretical Informatics, Algorithmics Department of Informatics ...","url":["https://pdfs.semanticscholar.org/bf34/8f2819a740ba3a473314b4eab616c421c9e1.pdf"]}
-{"year":"2017","title":"Bootstrapping Chatbots for Novel Domains","authors":["P Babkin, MFM Chowdhury, A Gliozzo, M Hirzel… - Workshop at NIPS on …, 2017"],"snippet":"… between the corresponding dense vectors. We used 300-dimensional vectors pre-trained with the GloVe algorithm [19] on the Common Crawl corpus that come with the gensim Python library [20]. By applying this model, for …","url":["https://www.researchgate.net/profile/Avraham_Shinnar/publication/321664993_Bootstrapping_Chatbots_for_Novel_Domains/links/5a29ff24a6fdccfbbf81994a/Bootstrapping-Chatbots-for-Novel-Domains.pdf"]}
-{"year":"2017","title":"Building a Web-Scale Dependency-Parsed Corpus from CommonCrawl","authors":["A Panchenko, E Ruppert, S Faralli, SP Ponzetto… - arXiv preprint arXiv: …, 2017"],"snippet":"Abstract: We present DepCC, the largest to date linguistically analyzed corpus in English including 365 million documents, composed of 252 billion tokens and 7.5 billion of named entity occurrences in 14.3 billion sentences from a web-scale crawl of the CommonCrawl","url":["https://arxiv.org/pdf/1710.01779"]}
-{"year":"2017","title":"Building Lexical Vector Representations from Concept Definitions","authors":["DS Carvalho, M Le Nguyen"],"snippet":"... This parameter was adjusted using the training set for MEN, or inside each CV fold for the rest. • Both Word2Vec and GloVe were used with pre-trained, 300-dimensional models: 100 billion words GoogleNews corpus and Common Crawl 42 billion token corpus respectively. ...","url":["http://www.aclweb.org/anthology/E/E17/E17-1085.pdf"]}
-{"year":"2017","title":"Byte-based Neural Machine Translation","authors":["MR Costa-jussà, C Escolano, JAR Fonollosa - Proceedings of the First Workshop on …, 2017"],"snippet":"... English. For the three language pairs, we used all data parallel data provided in the evaluation. For German-English, we used: europarl v.7, news commentary v.12, common crawl and rapid corpus of EU press re- leases. For ...","url":["http://www.aclweb.org/anthology/W17-4123"]}
-{"year":"2017","title":"Can word vectors help corpus linguists?","authors":["G Desagulier - 2017"],"snippet":"… If we follow the distributional hypothesis, this means that the words have similar meanings. The quality of the vector representation is a function of the number 2It is sampled from a matrix of vectors obtained with GloVe (see below) on the basis of the Common Crawl dataset. 6 …","url":["https://halshs.archives-ouvertes.fr/halshs-01657591/document"]}
-{"year":"2017","title":"Characterisation of mental health conditions in social media using Informed Deep Learning","authors":["G Gkotsis, A Oellrich, S Velupillai, M Liakata… - Scientific Reports, 2017"],"snippet":"... We considered pre-trained word vectors as input to the classifiers (eg using Glove's Common Crawl containing 840 Billion tokens 17 ), but the results did not improve. We attribute this to the size of our dataset which is adequate for representing the language within the corpus. ...","url":["http://www.nature.com/srep/2017/170322/srep45141/full/srep45141.html"]}
-{"year":"2017","title":"Classification of keywords","authors":["I Prémont-schwarz, A Thakur, M Tober - US Patent 9,798,820, 2017"],"snippet":"… The resource contents module 320 may automatically acquire a plurality of resources. The resources may, for example, be Wikipedia articles and be acquired from Wikipedia.org, or an open repository of web crawl data such as CommonCrawl.org …","url":["http://www.freepatentsonline.com/9798820.html"]}
-{"year":"2017","title":"Classification of search queries","authors":["A Thakur, M Tober - US Patent 9,767,182, 2017"],"snippet":"... The resource contents module 320 may automatically acquire a plurality of resources. The resources may, for example, be Wikipedia articles and be acquired from Wikipedia.org, or an open repository of web crawl data such as CommonCrawl.org. ...","url":["http://www.freepatentsonline.com/9767182.html"]}
-{"year":"2017","title":"Classifier Stacking for Native Language Identification","authors":["W Li, L Zou - Bronze Sponsors, 2017"],"snippet":"... Word embeddings We use the Common Crawl (42B tokens, 1.9 M vocab, uncased, 300d vectors) in GloVe (global vectors for word representation)(Pennington et al., 2014) to produce feature vectors for each essay, with the help of Gensim (ˇRehurek and Sojka, 2010). ...","url":["http://www.aclweb.org/anthology/W/W17/W17-50.pdf#page=410"]}
-{"year":"2017","title":"Classifying Phishing URLs Using Recurrent Neural Networks","authors":["AC Bahnsen, EC Bohorquez, S Villegas, J Vargas…"],"snippet":"... Sections 1PhishTank (https://www.phishtank.com/) 2Common Crawl (http://commoncrawl.org/) 978-1-5386-2701-3/17/$31.00 c 2017 IEEE Page 2. ... Half of them legitimate and half of them phishing. The legitimate URLs came from Common Crawl, a corpus of web crawl data. ...","url":["http://albahnsen.com/files/Classifying%20Phishing%20URLs%20Using%20Recurrent%20Neural%20Networks_cameraready.pdf"]}
-{"year":"2017","title":"Cloud Computing Infrastructure for Data Intensive Applications","authors":["Y Demchenko, F Turkmen, C de Laat, CH Hsu… - Big Data Analytics for …, 2017"],"snippet":"This chapter describes the general architecture and functional components of the cloud-based big data infrastructure (BDI). The chapter starts with the analysis.","url":["https://www.sciencedirect.com/science/article/pii/B9780128093931000027"]}
-{"year":"2017","title":"Coattention-Based Neural Network for Question Answering","authors":["J Andress, C Zanoci"],"snippet":"... We then proceed by embedding each word using the GloVe word vectors pretrained on the 840B Common Crawl corpus [6]. We found that switching from the default 100dimensional GloVe vectors to the larger 300-dimensional representation improved the performance ...","url":["https://web.stanford.edu/class/cs224n/reports/2762015.pdf"]}
-{"year":"2017","title":"Common Crawl Mining","authors":["T Dean, A Pasha, B Clarke, CJ Butenhoff - 2017"],"snippet":"The main goal behind the Common Crawl Mining system is to improve Eastman Chemical Company's ability to use timely knowledge of public concerns to inform key business decisions. It provides information to Eastman Chemical Company that is valuable for","url":["https://vtechworks.lib.vt.edu/bitstream/handle/10919/77629/ccm_source_code.zip?sequence=5&isAllowed=y"]}
-{"year":"2017","title":"Common Crawled Web Corpora: Constructing corpora from large amounts of web data","authors":["KB Kristoffersen - 2017"],"snippet":"… Additionally, by using data provided by the Common Crawl Foundation, I develop a new very large English corpus with more than 135 billion tokens … 3 Exploring the Common Crawl 27 3.1 The data . . . . . 27 3.1.1 A note on scale …","url":["https://www.duo.uio.no/bitstream/handle/10852/57836/Kristoffersen_MSc2.pdf?sequence=5"]}
-{"year":"2017","title":"Composition of Compound Nouns Using Distributional Semantics","authors":["K Yee, J Kalita"],"snippet":"... word2vec 300 3,000,000 100.00 bn Google News GloVe 300 400,000 42.00 bn Common Crawl HPCA 200 178,080 1.65 bn enWiki+Reuters +WSJ CW 50 130,000 0.85 bn enWiki+Reuters RCV1 word2vec 500 30,025 100 mn BNC word2vec 500 19,679 120 mn esWiki ...","url":["http://www.cs.uccs.edu/~jkalita/papers/2016/KyraYeeICON2016.pdf"]}
-{"year":"2017","title":"Compressed Nonparametric Language Modelling","authors":["E Shareghi, G Haffari, T Cohn"],"snippet":"Page 1. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17) 2701 Compressed Nonparametric Language Modelling Ehsan Shareghi,♣ Gholamreza Haffari,♣ Trevor Cohn♠ ♣ Faculty ...","url":["http://static.ijcai.org/proceedings-2017/0376.pdf"]}
-{"year":"2017","title":"COMPRESSING WORD EMBEDDINGS VIA DEEP COMPOSITIONAL CODE LEARNING","authors":["R Shu, H Nakayama - arXiv preprint arXiv:1711.01068, 2017","RSH Nakayama"],"snippet":"… purpose. We lowercase and tokenize all texts with the nltk package. We choose the 300-dimensional uncased GloVe word vectors (trained on 42B tokens of Common Crawl data) as our baseline embeddings. The vocabulary …","url":["https://arxiv.org/pdf/1711.01068","https://pdfs.semanticscholar.org/1713/d05f9d5861cac4d5ec73151667cb03a42bfc.pdf"]}
-{"year":"2017","title":"Compression with the tudocomp Framework","authors":["P Dinklage, J Fischer, D Köppl, M Löbel, K Sadakane - arXiv preprint arXiv: …, 2017"],"snippet":"Page 1. Compression with the tudocomp Framework Patrick Dinklage1, Johannes Fischer1, Dominik Köppl1, Marvin Löbel1, and Kunihiko Sadakane2 1 Department of Computer Science, TU Dortmund, Germany, pdinklag@gmail ...","url":["https://arxiv.org/pdf/1702.07577"]}
-{"year":"2017","title":"Concept/Theme Roll-Up","authors":["T Sahay, R Tadishetti, A Mehta, S Jadon - 2017"],"snippet":"... representation. For word embeddings, we used GloVe trained on a common crawl corpus, containing 1900000 words in its vocabulary. ... phrases. For words, the weights were initialized with GloVe embeddings trained on the common-crawl corpus. ...","url":["https://people.cs.umass.edu/~tsahay/lexalytics_report.pdf"]}
-{"year":"2017","title":"ConceptNet at SemEval-2017 Task 2: Extending Word Embeddings with Multilingual Relational Knowledge","authors":["R Speer, J Lowry-Duda - arXiv preprint arXiv:1704.03560, 2017"],"snippet":"... The first source is the word2vec Google News embeddings2, and the second is the GloVe 1.2 embeddings that were trained on 840 billion tokens of the Common Crawl3. Because the input embeddings are only in En- glish, the vectors in other languages depended en- tirely on ...","url":["https://arxiv.org/pdf/1704.03560"]}
-{"year":"2017","title":"CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies","authors":["D Zeman, M Popel, M Straka, J Hajic, J Nivre, F Ginter… - Proceedings of the CoNLL …, 2017"],"snippet":"... Page 3. Raw texts The supporting raw data was gathered from CommonCrawl, which is a publicly available web crawl created and maintained by the non-profit CommonCrawl foundation.2 The data is publicly available in the Amazon cloud both as raw HTML and as plain text. ...","url":["http://www.aclweb.org/anthology/K17-3001"]}
-{"year":"2017","title":"Connecting the Dots: Towards Human-Level Grammatical Error Correction","authors":["S Chollampatt, HT Ng - Bronze Sponsors, 2017"],"snippet":"... Moreover, Junczys-Dowmunt and Grundkiewicz (2016) trained a web-scale language model (LM) using large corpora from the Common Crawl data (Buck et al., 2014). ... 2014. N-gram counts and language models from the Common Crawl...","url":["http://www.aclweb.org/anthology/W/W17/W17-50.pdf#page=347"]}
-{"year":"2017","title":"Constructing and Evaluating a Novel Crowdsourcing-based Paraphrased Opinion Spam Dataset","authors":["S Kim, S Lee, D Park, J Kang - Proceedings of the 26th International Conference on …, 2017"],"snippet":"... the past and future context of an input are captured (Figure 3). We initialized the input word representations of our LSTM model using publicly available 300dimensional GloVe10 vectors (Pennington et al., 2014), which are trained on 840 billion tokens of Common Crawl data. ...","url":["http://dl.acm.org/citation.cfm?id=3052607"]}
-{"year":"2017","title":"Context Similarity for Retrieval-Based Imputation","authors":["A Ahmadov, M Thiele, W Lehner, R Wrembel"],"snippet":"... an accurate imputation. We use Dresden Web Table Corpus (DWTC) which is comprised of more than 125 million web tables extracted from the Common Crawl as our knowledge source. The comprehensive experimental ...","url":["http://asonamdata.com/ASONAM2017_Proceedings/papers/165_1017_135.pdf"]}
-{"year":"2017","title":"CONTEXT-AWARE CLUSTERING USING GLOVE AND K-MEANS","authors":["P Juneja, H Jain, T Deshmukh, S Somani, BK Tripathy"],"snippet":"... Gigaword5 + Page 7. International Journal of Software Engineering & Applications (IJSEA), Vol.8, No.4, July 2017 27 Wikipedia2014 which has 6 billion tokens, and on 42 billion tokens of web data, from Common Crawl. For ...","url":["https://www.researchgate.net/profile/BK_Tripathy/publication/318815506_Context_Aware_Clustering_Using_Glove_and_K-Means/links/598037d2458515687b4f9dfd/Context-Aware-Clustering-Using-Glove-and-K-Means.pdf"]}
-{"year":"2017","title":"Continuous Learning from Human Post-Edits for Neural Machine Translation","authors":["M Turchi, M Negri, MA Farajian, M Federico - The Prague Bulletin of Mathematical …, 2017"],"snippet":"... For training the En_De NMT system, we merged the Europarl v7 (Koehn, 2005) and Common Crawl datasets released for the translation task at the 2016 Workshop on Statistical Machine Translation (WMT'16 (Bojar, 2016)) and random sampled 3.5 million sentence pairs. ...","url":["https://www.degruyter.com/downloadpdf/j/pralin.2017.108.issue-1/pralin-2017-0023/pralin-2017-0023.xml"]}
-{"year":"2017","title":"Convolutional Encoding in Bidirectional Attention Flow for Question Answering","authors":["DR Miller"],"snippet":"... Language Processing (EMNLP), pp. 1532–1543, 2014. [9] “Common Crawl.” https://commoncrawl.org/. [10] RK Srivastava, K. Greff, and J. Schmidhuber, “Highway networks,” arXiv preprint arXiv:1505.00387, 2015. [11] P. Rajpurkar, J ...","url":["http://web.stanford.edu/class/cs224n/reports/2762032.pdf"]}
-{"year":"2017","title":"Cost Weighting for Neural Machine Translation Domain Adaptation","authors":["B Chen, C Cherry, G Foster, S Larkin - ACL 2017, 2017"],"snippet":"... which contains 3003 sentence pairs. The training data contain 12 million sentence pairs, composed of various sub-domains, such as news commentary, Europarl, UN, common crawl web data, etc. In the corpus weighting adaptation ...","url":["http://www.aclweb.org/anthology/W/W17/W17-32.pdf#page=52"]}
-{"year":"2017","title":"Counterfactual Learning for Machine Translation: Degeneracies and Solutions","authors":["C Lawrence, P Gajane, S Riezler - arXiv preprint arXiv:1711.08621, 2017"],"snippet":"… signal. Experiments are conducted on two language pairs. The first is German-to-English and its baseline system is trained on the concatenation of the Europarl corpus, the Common Crawl corpus and the News corpus. The …","url":["https://arxiv.org/pdf/1711.08621"]}
-{"year":"2017","title":"Counterfactual learning from bandit feedback under deterministic logging: A case study in statistical machine translation","authors":["C Lawrence, A Sokolov, S Riezler - arXiv preprint arXiv:1707.09118, 2017"],"snippet":"... We conduct two SMT tasks with hypergraph re-decoding: The first is German-to-English and is trained using a concatenation of the Europarl corpus (Koehn, 2005), the Common Crawl corpus3 and the News Commentary corpus (Koehn and Schroeder, 2007). ...","url":["https://arxiv.org/pdf/1707.09118"]}
-{"year":"2017","title":"Critical review of various near-duplicate detection methods in web crawl and their prospective application in drug discovery","authors":["L Pamulaparty, CVG Rao, MS Rao - International Journal of Biomedical Engineering …, 2017"],"snippet":"... Smith, JR, Saint-Amand, H., Plamada, M. and Lopez, A. (2013) 'Dirt cheap web-scale parallel text from the common crawl', Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013), Association for Computational Linguistics, Sofia ...","url":["http://www.inderscienceonline.com/doi/abs/10.1504/IJBET.2017.087723"]}
-{"year":"2017","title":"CS 224N Assignment 4: Question Answering on SQuAD","authors":["RA Ozturk, HA Inan, K Garbe"],"snippet":"... Fixing this problem partly by using all of the 400k words resulted in increased performance naturally, but there is still a performance gap between our dev performance and test performance. We should also note that 1 uses the Common Crawl dataset (2.2m words). ...","url":["https://web.stanford.edu/class/cs224n/reports/2761126.pdf"]}
-{"year":"2017","title":"CS224N Project: Natural Language Inference for Quora Dataset","authors":["KHK Yoo, MM Almajid, ZY Wong"],"snippet":"... Most of the results were obtained using the smaller vocabulary of 6 billion tokens obtained from Wikipedia and Gigaword 5, while there exists a Common Crawl version which has 840B tokens with an embedding size of 300. ...","url":["https://web.stanford.edu/class/cs224n/reports/2755939.pdf"]}
-{"year":"2017","title":"CUNI System for the WMT17 Multimodal Translation Task","authors":["J Helcl, J Libovický - arXiv preprint arXiv:1707.04550, 2017"],"snippet":"... By scoring the German part of several parallel corpora (EU Bookshop (Skadinš et al., 2014), News Commentary (Tiedemann, 2012) and CommonCrawl (Smith et al., 2013)), we were only able to retrieve a few hundreds of in-domain sentences. ...","url":["https://arxiv.org/pdf/1707.04550"]}
-{"year":"2017","title":"D1. 1: Report on Building Translation Systems for Public Health Domain","authors":["O Bojar, B Haddow, D Marecek, R Sudarikov… - 2017"],"snippet":"Page 1. This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 644402. D1.1: Report on Building Translation Systems for Public Health Domain ...","url":["http://www.himl.eu/files/D1.1-report-on-building-translation-systems.pdf"]}
-{"year":"2017","title":"Data Integration for Open Data on the Web","authors":["S Neumaier, A Polleres, S Steyskal, J Umbrich"],"snippet":"... However, some Web crawls have been made openly available, such as the Common Crawl corpus which contains “petabytes of data collected over the last 7 years”10. ... 10http://commoncrawl.org/, last accessed 30/03/2017 Page 5. Table 1: Top-10 portals, ordered by datasets. ...","url":["https://aic.ai.wu.ac.at/~polleres/publications/neum-etal-RW2017.pdf"]}
-{"year":"2017","title":"Data Selection Strategies for Multi-Domain Sentiment Analysis","authors":["S Ruder, P Ghaffari, JG Breslin - arXiv preprint arXiv:1702.02426, 2017"],"snippet":"... a linear SVM classifier (Blitzer et al., 2006). We use GloVe vectors (Pennington et al., 2014) pre-trained on 42B tokens of the Common Crawl corpus7 for our word embeddings. For the auto-encoder representations, we use a ...","url":["https://arxiv.org/pdf/1702.02426"]}
-{"year":"2017","title":"DCN+: Mixed Objective and Deep Residual Coattention for Question Answering","authors":["C Xiong, V Zhong, R Socher - arXiv preprint arXiv:1711.00106, 2017"],"snippet":"... Manning et al., 2014). For word embeddings, we use GloVe embeddings pretrained on the 840B Common Crawl corpus (Pennington et al., 2014) as well as character ngram embeddings by Hashimoto et al. (2017). In addition, we ...","url":["https://arxiv.org/pdf/1711.00106"]}
-{"year":"2017","title":"Deep Almond: A Deep Learning-based Virtual Assistant","authors":["GCR Ramesh"],"snippet":"... Preprocessing was implemented in Java using CoreNLP [22]. We use the pretrained GloVe [23] vectors of size 300 trained on Common Crawl as our word vectors, and we do not train the word vectors. 5.1 Model Validation & Tuning ...","url":["https://web.stanford.edu/class/cs224n/reports/2748325.pdf"]}
-{"year":"2017","title":"Deep Learning for User Comment Moderation","authors":["J Pavlopoulos, P Malakasiotis, I Androutsopoulos - arXiv preprint arXiv:1705.09993, 2017"],"snippet":"... 11See https://nlp.stanford.edu/projects/ glove/. We use 'Common Crawl' (840B tokens). 12For Gazzetta, words encountered only once in the training set (G-TRAIN-L or G-TRAIN-S) are also treated as OOV. ta : accept threshold tr : reject threshold 0.0 1.0 reject gray accept ...","url":["https://arxiv.org/pdf/1705.09993"]}
-{"year":"2017","title":"Deep Neural Machine Translation with Linear Associative Unit","authors":["M Wang, Z Lu, J Zhou, Q Liu - arXiv preprint arXiv:1705.00861, 2017","MWZLJ Zhou, Q Liu"],"snippet":"... translation are presented in Table 2. We compare our NMT systems with various other systems including the winning system in WMT14 (Buck et al., 2014), a phrase-based system whose language models were trained on a huge monolingual text, the Common Crawl corpus. ...","url":["http://www.aclweb.org/anthology/P/P17/P17-1013.pdf","https://arxiv.org/pdf/1705.00861"]}
-{"year":"2017","title":"Deeper Attention to Abusive User Content Moderation","authors":["J Pavlopoulos, P Malakasiotis, I Androutsopoulos - 2017"],"snippet":"... (2017a). 14We implemented the methods of this sub-section using Keras (keras.io) and TensorFlow (tensorflow.org). 15See https://nlp.stanford.edu/projects/ glove/. We use 'Common Crawl' (840B tokens). Page 6. ta : accept threshold tr : reject threshold 0.0 1.0 reject gray accept ...","url":["http://nlp.cs.aueb.gr/pubs/emnlp2017.pdf"]}
-{"year":"2017","title":"DeepSpace: Mood-Based Image Texture Generation for Virtual Reality from Music","authors":["M Sra, P Vijayaraghavan, O Rudovic, P Maes, D Roy - Computer Vision and Pattern …, 2017"],"snippet":"... task. We use the GloVe model trained on a common crawl dataset7 for the representation for words in the descriptive labels and mood. ... This approach of tractably modeling a joint distribution of 7http://commoncrawl.org/the-data/ pixels ...","url":["http://ieeexplore.ieee.org/abstract/document/8015017/"]}
-{"year":"2017","title":"Denoising Clinical Notes for Medical Literature Retrieval with Convolutional Neural Model","authors":["L Soldaini, A Yates, N Goharian - 2017"],"snippet":"... Two source of evidence were used to obtain, for each term qi , its word embedding xi : GloVe vectors [10] pre-trained on the common crawl corpus4 and SkipGram vectors pre-trained on PubMed5. We found that concatenating domain-speci c with domain-agnostic embeddings ...","url":["http://ir.cs.georgetown.edu/downloads/cikm17-cds-notes.pdf"]}
-{"year":"2017","title":"Deriving Neural Architectures from Sequence and Graph Kernels","authors":["T Lei, W Jin, R Barzilay, T Jaakkola - arXiv preprint arXiv:1705.09037, 2017"],"snippet":"Page 1. Deriving Neural Architectures from Sequence and Graph Kernels Tao Lei* 1 Wengong Jin* 1 Regina Barzilay 1 Tommi Jaakkola 1 Abstract The design of neural architectures for structured objects is typically guided by experimental in- sights rather than a formal process. ...","url":["https://arxiv.org/pdf/1705.09037"]}
-{"year":"2017","title":"Determining Entailment of Questions in the Quora Dataset","authors":["A Tung, E Xu"],"snippet":"... We used the 840B common crawl GloVe pretrained embeddings https://nlp.stanford.edu/projects/ glove/, the starter code from CS224N http://web.stanford.edu/class/cs224n/, and tuned the hyper-parameters on these various models to achieve the optimal accuracy. ...","url":["https://web.stanford.edu/class/cs224n/reports/2748301.pdf"]}
-{"year":"2017","title":"Distance-Aware Selective Online Query Processing Over Large Distributed Graphs","authors":["X Zhang, L Chen - Data Science and Engineering"],"url":["http://link.springer.com/article/10.1007/s41019-016-0023-z"]}
-{"year":"2017","title":"Distinguishing “good” from “bad” Arguments in Online Debates & Feature Analysis using Feed-Forward Neural Networks","authors":["LA Chalaguine"],"snippet":"Page 1. Imperial College London Department of Computing Distinguishing “good” from “bad” Arguments in Online Debates & Feature Analysis using Feed-Forward Neural Networks Lisa Andreevna Chalaguine Supervisor: Claudia Schulz ...","url":["https://pdfs.semanticscholar.org/526f/468ebe630e10221dc77f21ce65aba72e0021.pdf"]}
-{"year":"2017","title":"Distributed Algorithms on Exact Personalized PageRank","authors":["T Guo, X Cao, G Cong, J Lu, X Lin"],"snippet":"Page 1. Distributed Algorithms on Exact Personalized PageRank Tao Guo1 Xin Cao2 Gao Cong1 Jiaheng Lu3 Xuemin Lin2 1 School of Computer Science and Engineering, Nanyang Technological University, Singapore 2 School ...","url":["https://www.cs.helsinki.fi/u/jilu/documents/SIGMOD2017.pdf"]}
-{"year":"2017","title":"Distributed Computing in Social Media Analytics","authors":["M Riemer - Distributed Computing in Big Data Analytics, 2017"],"snippet":"... For example, [16] the current state of the art Twitter sentiment analysis technique leverages knowledge from a Common Crawl of the internet, Movie Reviews, Emoticons, and a human defined rule logic model to drastically improve the performance of its recurrent neural network ...","url":["https://link.springer.com/chapter/10.1007/978-3-319-59834-5_8"]}
-{"year":"2017","title":"Document Context Neural Machine Translation with Memory Networks","authors":["S Maruf, G Haffari - arXiv preprint arXiv:1711.03688, 2017"],"snippet":"Page 1. Document Context Neural Machine Translation with Memory Networks Sameen Maruf and Gholamreza Haffari Faculty of Information Technology, Monash University, VIC, Australia {firstname.lastname}@monash.edu.au Abstract …","url":["https://arxiv.org/pdf/1711.03688"]}
-{"year":"2017","title":"Domain Adaptation for Multilingual Neural Machine Translation","authors":["AC Varga - 2017"],"snippet":"Page 1. Universität des Saarlandes Universidad del Pa´ıs Vasco/Euskal Herriko Unibertsitatea Domain Adaptation for Multilingual Neural Machine Translation Master's Thesis submitted in fulfillment of the degree requirements of the ...","url":["https://www.clubs-project.eu/assets/publications/other/MSc_thesis_AdamVarga.pdf"]}
-{"year":"2017","title":"Don't Let One Rotten Apple Spoil the Whole Barrel: Towards Automated Detection of Shadowed Domains","authors":["D Liu, Z Li, K Du, H Wang, B Liu, H Duan - 2017"],"snippet":"Page 1. Don't Let One Rotten Apple Spoil the Whole Barrel: Towards Automated Detection of Shadowed Domains Daiping Liu University of Delaware dpliu@udel.edu Zhou Li ACM Member lzcarl@gmail.com Kun Du Tsinghua University dk15@tsinghua.edu.cn ...","url":["https://www.eecis.udel.edu/~dpliu/papers/ccs17.pdf"]}
-{"year":"2017","title":"Doubly-Attentive Decoder for Multi-modal Neural Machine Translation","authors":["I Calixto, Q Liu, N Campbell - arXiv preprint arXiv:1702.01287, 2017"],"snippet":"... M sentence pairs (Bojar et al., 2015). These include the Eu- roparl v7 (Koehn, 2005), News Commentary and Common Crawl corpora, which are concatenated and used for pre-training. We use the scripts in the Moses SMT ...","url":["https://arxiv.org/pdf/1702.01287"]}
-{"year":"2017","title":"Dynamic Coattention Networks for Reading Comprehension","authors":["H Tepanyan"],"snippet":"... using linear decoder. We use this final version with Common Crawl 840B glove vector embeddings from [2] to achieve the final scores of F1 = 58.2% and EM = 44.5% scores on the dev set. 1 Model 1. Simple Baseline Below we ...","url":["http://web.stanford.edu/class/cs224n/reports/2743745.pdf"]}
-{"year":"2017","title":"Dynamic Coattention with Sentence Information","authors":["A Ruch"],"snippet":"... choice for document length. Embeddings: We used the GloVe word embeddings for the Common Crawl 840B dataset and explored initializing the embeddings of unseen words to zero or to a random vector. Intuitively using a ...","url":["https://pdfs.semanticscholar.org/eef0/e42394c625772f5b220797661aba893012f4.pdf"]}
-{"year":"2017","title":"Dynamic Data Selection for Neural Machine Translation","authors":["M van der Wees, A Bisazza, C Monz - arXiv preprint arXiv:1708.00712, 2017"],"snippet":"... The WMT training corpus contains Commoncrawl, Europarl, and News Commentary but no in-domain news data. ... We train our systems on a mixture of domains, comprising Commoncrawl, Europarl, News Commentary, EMEA, Movies, and TED. ...","url":["https://arxiv.org/pdf/1708.00712"]}
-{"year":"2017","title":"Dynamic Space Efficient Hashing","authors":["T Maier, P Sanders - arXiv preprint arXiv:1705.00997, 2017"],"snippet":"Page 1. Dynamic Space Efficient Hashing Tobias Maier and Peter Sanders Karlsruhe Institute of Technology, Karlsruhe, Germany {t.maier,sanders}@kit.edu Abstract We consider space efficient hash tables that can grow and ...","url":["https://arxiv.org/pdf/1705.00997"]}
-{"year":"2017","title":"Effect of Data Imbalance on Unsupervised Domain Adaptation of Part-of-Speech Tagging and Pivot Selection Strategies","authors":["X Cui, F Coenen, D Bollegala - Journal of Machine Learning Research, 2017"],"snippet":"... (2016) to train the final adaptive classifier f only by projected features to reduce the dimensionality, where θx ∈ Rh. We use d = 300 dimensional GloVe (Pennington et al., 2014) embeddings (trained using 42B tokens from the Common Crawl) as word representations. ...","url":["https://cgi.csc.liv.ac.uk/~frans/PostScriptFiles/lidta2017.pdf"]}
-{"year":"2017","title":"Energy-Efficient Data Transfer Algorithms for HTTP-Based Services","authors":["T Kosar, I Alan - arXiv preprint arXiv:1707.05730, 2017"],"snippet":"... Three different representative datasets were used during experiments in order to capture the throughput and power consumption differences based on the dataset type: (i) the HTML dataset is a set of raw HTML files from the Common Crawl project [3]; (ii) the image dataset is a ...","url":["https://arxiv.org/pdf/1707.05730"]}
-{"year":"2017","title":"Entity linking across vision and language","authors":["AN Venkitasubramanian, T Tuytelaars, MF Moens - Multimedia Tools and …, 2017"],"snippet":"... 5.2 Using a hypernym database The second approach for detecting relevant mentions uses the WebIsADb database [40] containing more than 400 million hypernymy relations extracted from the CommonCrawl web corpus. ...","url":["http://link.springer.com/article/10.1007/s11042-017-4732-8"]}
-{"year":"2017","title":"Estimating Missing Temporal Meta-Information using Knowledge-Based-Trust","authors":["Y Oulabi, C Bizer"],"snippet":"... We acquired data from the sources either by manually written crawlers and extractors, or through data dumps. 5.2 Web Table Corpus For our experiments we use the Web Data Commons Web Table Corpus from 20153, which was extracted from the July 2015 Common Crawl...","url":["https://pdfs.semanticscholar.org/9016/87f0f79efd175d6c3b9efba4e254e4bc410a.pdf"]}
-{"year":"2017","title":"Evaluating Story Generation Systems Using Automated Linguistic Analyses","authors":["M Roemmele, AS Gordon, R Swanson"],"snippet":"... We specifically used the GloVe embedding vectors [45] trained on the Common Crawl corpus8. We computed the mean cosine similarity of the vectors for all pairs of content words between a generated sentence and its context (Metric 11). ...","url":["http://people.ict.usc.edu/~roemmele/publications/fiction_generation.pdf"]}
-{"year":"2017","title":"Evaluating vector-space models of analogy","authors":["D Chen, JC Peterson, TL Griffiths - arXiv preprint arXiv:1705.04416, 2017"],"snippet":"... We used the 300-dimensional word2vec vectors trained on the Google News corpus that were provided by Google (Mikolov et al., 2013), and the 300-dimensional GloVe vectors trained on a Common Crawl web crawl corpus that were provided by Pennington et al. (2014). ...","url":["https://arxiv.org/pdf/1705.04416"]}
-{"year":"2017","title":"Evaluation of a Feedback Algorithm inspired by Quantum Detection for Dynamic Search Tasks","authors":["E Di Buccio, M Melucci"],"snippet":"... Polar Domain and the Ebola Do- main. Each dataset is formatted using the Common Crawl Architecture schema from the DARPA MEMEX project, and stored as sequences of CBOR objects. The Ebola dataset refers to the outbreak ...","url":["http://trec.nist.gov/pubs/trec25/papers/UPD_IA-DD.pdf"]}
-{"year":"2017","title":"Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events","authors":["PK Choubey, R Huang - arXiv preprint arXiv:1707.07344, 2017"],"snippet":"Page 1. Event Coreference Resolution by Iteratively Unfolding Inter-dependencies among Events Prafulla Kumar Choubey and Ruihong Huang Department of Computer Science and Engineering Texas A&M University (prafulla.choubey, huangrh)@tamu.edu Abstract ...","url":["https://arxiv.org/pdf/1707.07344"]}
-{"year":"2017","title":"Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis","authors":["R Cotterell, A Poliak, B Van Durme, J Eisner"],"snippet":"... distributional information. The embeddings, trained on extremely large text corpora, eg, Wikipedia and the Common Crawl, are claimed to encode semantic knowledge extracted from large text corpora. While numerous models ...","url":["https://ryancotterell.github.io/papers/cotterell+alb.eacl17.pdf"]}
-{"year":"2017","title":"Exploiting Embedding in Content-Based Recommender systems","authors":["Y Huang - 2016"],"snippet":"Page 1. Multimedia Computing Group Exploiting Embedding in Content-Based Recommender Systems Yanbo Huang Master of Science Thesis Page 2. Page 3. Exploiting Embedding in Content-Based Recommender Systems Master of Science Thesis ...","url":["http://repository.tudelft.nl/islandora/object/uuid:cbec7bdd-4bab-4132-93cd-359587b9bf46/datastream/OBJ/view"]}
-{"year":"2017","title":"Exploring Neural Transducers for End-to-End Speech Recognition","authors":["E Battenberg, J Chen, R Child, A Coates, Y Gaur, Y Li… - arXiv preprint arXiv: …, 2017"],"snippet":"... available for this benchmark from the Kaldi receipe [20]. The language model used by all models in Table 3 is built from a sample of the common crawl dataset [26]. Model specification. All models in Tables 1 and 3 are tuned ...","url":["https://arxiv.org/pdf/1707.07413"]}
-{"year":"2017","title":"Extending the Scope of Co-occurrence Embedding","authors":["J Mi, Y Wang, J Zhu"],"snippet":"... Therefore, it is highly likely that our model ignores the n-grams with strong emotion, simply because they rarely occur in the training data. We expect a boost in the classification accuracy if we could train our model on a more comprehensive dataset, say, common crawl...","url":["https://web.stanford.edu/class/cs224n/reports/2758144.pdf"]}
-{"year":"2017","title":"Extracting Conceptual Relationships and Inducing Concept Lattices from Unstructured Text","authors":["VS Anoop, S Asharaf - Journal of Intelligent Systems"],"snippet":"AbstractConcept and relationship extraction from unstructured text data plays a key role in meaning aware computing paradigms, which make computers intelligent by helping them learn, interpret, and synthesis information. These concepts and relationships leverage knowledge ...","url":["https://www.degruyter.com/view/j/jisys.ahead-of-print/jisys-2017-0225/jisys-2017-0225.xml"]}
-{"year":"2017","title":"Extracting Parallel Paragraphs from Common Crawl","authors":["J Kúdela, I Holubová, O Bojar - The Prague Bulletin of Mathematical Linguistics, 2017"],"snippet":"Abstract Most of the current methods for mining parallel texts from the web assume that web pages of web sites share same structure across languages. We believe that there still exists a non-negligible amount of parallel data spread across sources not satisfying this","url":["https://www.degruyter.com/downloadpdf/j/pralin.2017.107.issue-1/pralin-2017-0003/pralin-2017-0003.xml"]}
-{"year":"2017","title":"Extracting Visual Knowledge from the Web with Multimodal Learning","authors":["D Gong, DZ Wang"],"snippet":"... 5.1 Dataset We evaluate our approach based on a collection of web pages and images derived from the Common Crawl dataset [Smith et al., 2013] that is publicly available on Amazon S3. The entire Common Crawl dataset ...","url":["http://static.ijcai.org/proceedings-2017/0238.pdf"]}
-{"year":"2017","title":"Fast Construction of Compressed Web Graphs","authors":["J Broß, S Gog, M Hauck, M Paradies - … on String Processing and Information Retrieval, 2017"],"snippet":"... Table 1). For experiments on a very large graph, we added a web graph originating from the CommonCrawl project. Table 1. ... Graphs are stored as set of adjacency lists. Each list entry occupies 4 bytes (8 bytes in case of CommonCrawl). ...","url":["https://link.springer.com/chapter/10.1007/978-3-319-67428-5_11"]}
-{"year":"2017","title":"FBK's Participation to the English-to-German News Translation Task of WMT 2017","authors":["MA Di Gangi, N Bertoldi, M Federico - WMT 2017, 2017"],"snippet":"... Number of training sentences. original cleaned commoncrawl 2399123 2228833 europarl-v7 1920209 1719859 news-comm-v12 270769 255944 rapid2016 1329041 1277997 both English and German. We also filtered out ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=295"]}
-{"year":"2017","title":"FilteredWeb: A Framework for the Automated Search-Based Discovery of Blocked URLs","authors":["A Darer, O Farnan, J Wright - arXiv preprint arXiv:1704.07185, 2017"],"snippet":"... Web search is a large and complicated business; most engines do not simply rank pages based on hyperlinks, but rather current trends and activity. One alternative to Bing is Common Crawl – an open data project that scrapes the web for pages. ...","url":["https://arxiv.org/pdf/1704.07185"]}
-{"year":"2017","title":"Findings of the 2017 conference on machine translation (wmt17)","authors":["O Bojar, R Chatterjee, C Federmann, Y Graham… - WMT 2017, 2017"],"snippet":"... Some training corpora were identical from last year (Europarl4, Common Crawl, SETIMES2, Russian-English parallel data provided by Yandex, Wikipedia Headlines provided by CMU) and some were updated (United Nations, CzEng v1. ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=193"]}
-{"year":"2017","title":"Findings of the WMT 2017 Biomedical Translation Shared Task","authors":["A Jimeno Yepes, A Neveol, M Neves, K Verspoor…","AJ Yepes, A Névéol, M Neves, HPIU Potsdam… - WMT 2017, 2017"],"snippet":"... used. Tuning of the SMT systems was performed with MERT. Commoncrawl and Wikipedia were used as general domain data for all language pairs ex- cept for EN/PT, where no Commoncrawl data was provided by WMT. As ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=258","https://www.research.ed.ac.uk/portal/files/40797681/123_1.pdf"]}
-{"year":"2017","title":"From Segmentation to Analyses: A Probabilistic Model for Unsupervised Morphology Induction","authors":["T Bergmanis, S Goldwater"],"snippet":"... by our system and the MorphoChains baseline, we used word2vec (Mikolov et al., 2013) to train a Continuous Bag of Words model on a sub-sample of the Common Crawl (CC) corpus6 for ... 6Common Crawl http://commoncrawl.org 7Morpho Challenge 2010: http://research.ics. ...","url":["http://homepages.inf.ed.ac.uk/sgwater/papers/eacl17-morphAnalyses.pdf"]}
-{"year":"2017","title":"Game, Set, Match-LSTM: Question Answering on SQUaD","authors":["I Torres, E Ehizokhale"],"snippet":"... The official test dataset is not publically available. It's kept by the authors of SQuAD to make model evaluation fair. We use GloVE word vectors trained on the 840B Common Crawl corpus. We limit the max context paragraph length to 300 and the max question length to 30. ...","url":["https://web.stanford.edu/class/cs224n/reports/2761956.pdf"]}
-{"year":"2017","title":"Geographical Evaluation of Word Embeddings","authors":["M Konkol, T Brychcín, M Nykl, T Hercig - Proceedings of the Eighth International Joint …, 2017"],"snippet":"… We use two models provided by the authors of the model trained on Wikipedia and News Crawl (LexVec - w + nc), and Common Crawl (LexVec - cc). MetaEmbeddings is an ensemble method that combines several embeddings (Yin and Schütze, 2016) …","url":["http://www.aclweb.org/anthology/I17-1023"]}
-{"year":"2017","title":"Global-Context Neural Machine Translation through Target-Side Attentive Residual Connections","authors":["L Miculicich, N Pappas, D Ram, A Popescu-Belis - arXiv preprint arXiv:1709.04849, 2017"],"snippet":"... Finally, we use the complete English- to-German set from WMT 2016 (Bojar and others 2016)3 which includes Europarl v7, Common Crawl, and News Commentary v11 with a total of ca. 4.5 million sentence pairs. ... N-gram counts and language models from the common crawl...","url":["https://arxiv.org/pdf/1709.04849"]}
-{"year":"2017","title":"Globally Normalized Reader","authors":["J Raiman, J Miller - Proceedings of the 2017 Conference on Empirical …, 2017"],"snippet":"... tion. The hidden dimension of all recurrent layers is 200. We use the 300 dimensional 8.4B token Common Crawl GloVe vectors (Pennington et al., 2014). Words missing from the Common Crawl vocabulary are set to zero. In ...","url":["http://www.aclweb.org/anthology/D17-1112"]}
-{"year":"2017","title":"Googleology as smart lexicography: Big messy data for better regional labels","authors":["S Dollinger - Dictionaries: Journal of the Dictionary Society of North …, 2016"],"snippet":"... help. Other services have other problems. Commoncrawl.org is one of the longest-running such projects and [End Page 72] offers big data for free. Accessing its data, however, requires serious programming expertise. Other ...","url":["https://muse.jhu.edu/article/645766/summary"]}
-{"year":"2017","title":"Grammatical error correction in non-native English","authors":["Z Yuan - 2017"],"snippet":"Page 1. Technical Report Number 904 Computer Laboratory UCAM-CL-TR-904 ISSN 1476-2986 Grammatical error correction in non-native English Zheng Yuan March 2017 15 JJ Thomson Avenue Cambridge CB3 0FD United Kingdom phone +44 1223 763500 ...","url":["http://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-904.pdf"]}
-{"year":"2017","title":"Handling Homographs in Neural Machine Translation","authors":["F Liu, H Lu, G Neubig - arXiv preprint arXiv:1708.06510, 2017"],"snippet":"... side. For German and French, we use a combination of Europarl v7, Common Crawl, and News Commentary as training set. For development set, newstest2013 is used for German and newstest2012 is used for French. For ...","url":["https://arxiv.org/pdf/1708.06510"]}
-{"year":"2017","title":"HCTI at SemEval-2017 Task 1: Use convolutional neural network to evaluate Semantic Textual Similarity","authors":["S Yang"],"snippet":"... 1) All punctuations are removed. 2) All words are lower-cased. 3) All sentences are tokenized by Natural Language Toolkit (NLTK) (Bird et al., 2009). 4) All words are replaced by pre-trained GloVe word vectors (Common Crawl, 840B tokens) (Pennington et al., 2014). ...","url":["http://nlp.arizona.edu/SemEval-2017/pdf/SemEval016.pdf"]}
-{"year":"2017","title":"Hungarian Layer: Logics Empowered Neural Architecture","authors":["H Xiao, L Meng - arXiv preprint arXiv:1712.02555, 2017"],"snippet":"… for illustration. 4.1. Experimental Setting We initialize the word embedding with 300-dimensional GloVe (Pennington et al., 2014) word vectors pre-trained in the 840B Common Crawl corpus (Pennington et al., 2014). For the …","url":["https://arxiv.org/pdf/1712.02555"]}
-{"year":"2017","title":"Hunter MT: A Course for Young Researchers in WMT17","authors":["J Xu, YZ Kuang, S Baijoo, H Lee, U Shahzad, M Ahmed… - WMT 2017, 2017"],"snippet":"... ing and tuning, including Europarl v7, News Commentary v12, Rapid Corpus of EU press releases, and parts of the Common Crawl corpus ... Rapid News Test 2016 2 German-English News 33.61 News Test 2016 3 English-Czech News 13.59 Europarl, CommonCrawl, News' 12 ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=446"]}
-{"year":"2017","title":"IIIT-H at IJCNLP-2017 Task 4: Customer Feedback Analysis using Machine Learning and Neural Network Approaches","authors":["P Danda, P Mishra, S Kanneganti, S Lanka - … of the IJCNLP 2017, Shared Tasks, 2017"],"snippet":"… We used glove pre-trained embeddings1 (Pennington et al., 2014) for English while for the rest 1we used Common Crawl corpus with 840B tokens, 2.2M vocab, case-sensitive, 300-dimensional vectors available on https://nlp.stanford.edu/projects/glove/ 155 Page 2 …","url":["http://www.aclweb.org/anthology/I17-4026"]}
-{"year":"2017","title":"IITP at EmoInt-2017: Measuring Intensity of Emotions using Sentence Embeddings and Optimized Features","authors":["MS Akhtar, P Sawant, A Ekbal, J Pawar… - EMNLP 2017, 2017"],"snippet":"... For this task, we use GloVe (Pennington et al., 2014) pre-trained word embedding trained on common crawl corpus. ... The choice of common crawl word embeddings for Twitter datasets is because of the normalization steps (Section 2.1). ...","url":["http://www.aclweb.org/anthology/W/W17/W17-52.pdf#page=228"]}
-{"year":"2017","title":"IITP at SemEval-2017 Task 5: An Ensemble of Deep Learning and Feature Based Models for Financial Sentiment Analysis","authors":["D Ghosal, S Bhatnagar, MS Akhtar, A Ekbal…"],"snippet":"... billion and 400 million tweets respectively. For news headline we used GloVe common crawl model trained on 802 billion words and Word2Vec Google News model (Mikolov et al., 2013). We experimented with 200, 300 and ...","url":["https://www.aclweb.org/anthology/S/S17/S17-2154.pdf"]}
-{"year":"2017","title":"Implementation and Analysis of Match-LSTM for SQuAD","authors":["M Graczyk"],"snippet":"... We used the Common Crawl 840B Glove vectors with 300 dimensions as our input embedding, and like the paper we did not train these vectors. Finally, we used softsign instead of tanh for a substantial improvement in training performance with no obvious change in metrics. ...","url":["https://web.stanford.edu/class/cs224n/reports/2761882.pdf"]}
-{"year":"2017","title":"Implementation and Improvement of Match-LSTM in Question-Answering System","authors":["Y Zhang, H Peng"],"snippet":"... To initialize the word vector embeddings, we used the GloVe word embeddings of dimensionality o = 300 and vocabulary size of 2.2M that have been pre-trained on Common Crawl. We did not train the word embeddings, since our dataset is not very large. ...","url":["https://web.stanford.edu/class/cs224n/reports/2748656.pdf"]}
-{"year":"2017","title":"Improving Machine Translation Quality Estimation with Neural Network Features","authors":["Z Chen, Y Tan, C Zhang, Q Xiang, L Zhang, M Li… - WMT 2017, 2017"],"snippet":"... To train the word embedding and the RNNLM, the source side and the target side of the bilingual parallel corpus for the translation task, publicly re- leased by the WMT evaluation campaign, are used; they include Europarl v7, Common Crawl corpus, News Commentary v8 and ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=575"]}
-{"year":"2017","title":"Improving the Compositionality of Word Embeddings","authors":["MJ Scheepers - 2017"],"snippet":"… 2Real, natural and imaginary numbers are represented in computers as floating point numbers [49], which are not always exact but more often really close estimations of these numbers. 3The Common Crawl dataset can be found at: http://commoncrawl.org. Page 10. 4 …","url":["https://thijs.ai/papers/scheepers-msc-thesis-2017-improving-compositionality-word-embeddings.pdf"]}
-{"year":"2017","title":"Induction of Latent Domains in Heterogeneous Corpora: A Case Study of Word Alignment","authors":["H Cuong, K Sima'an"],"snippet":"... resulting SMT systems. Going beyond the findings, we surmise that virtually any large corpus (eg Europarl, Hansards, Common Crawl) harbors an arbitrary diversity of hidden domains, unknown in advance. We address the ...","url":["https://staff.fnwi.uva.nl/c.hoang/mt20171.pdf"]}
-{"year":"2017","title":"Inductive Representation Learning on Large Graphs","authors":["WL Hamilton, R Ying, J Leskovec - arXiv preprint arXiv:1706.02216, 2017"],"snippet":"... For features, we use off-the-shelf 300-dimensional GloVe CommonCrawl word vectors [25]; for each post, we concatenated (i) the average embedding of the post title, (ii) the average embedding of all the post's comments (iii) the post's score, and (iv) the number of comments ...","url":["https://arxiv.org/pdf/1706.02216"]}
-{"year":"2017","title":"Information Extraction meets the Semantic Web: A Survey","authors":["JL Martinez-Rodriguez, A Hogan, I Lopez-Arevalo"],"snippet":"… Web [234]. Mika referred to this as the semantic gap [193], whereby the demand for structured data on the Web outstrips its supply. For example, in analysis of the 2013 Common Crawl dataset, Meusel et al. [189] found that …","url":["http://www.semantic-web-journal.net/system/files/swj1744.pdf"]}
-{"year":"2017","title":"Integrating Knowledge from Latent and Explicit Features for Triple Scoring","authors":["LW Chen, B Mangipudi, J Bandlamudi, R Sehgal…"],"snippet":"... ford NLP Group. We use word embeddings of size 300 dimensions, which were pre-trained on the Common Crawl corpus 2. We integrate the learned vector representations of GloVe for nationality and profession. In a nutshell ...","url":["http://www.uni-weimar.de/medien/webis/events/wsdm-cup-17/wsdmcup17-papers-final/wsdmcup17-triple-scoring/chen17-notebook.pdf"]}
-{"year":"2017","title":"Interstitial Content Detection","authors":["E Lucas - arXiv preprint arXiv:1708.04879, 2017"],"snippet":"... 'http://servo.org'. [7] I. Kreymer. Announcing the common crawl index, April 2015. 'http://commoncrawl. org/2015/04/announcing-the-common-crawl-index/'. [8] S. Rasheed, A. Naeem, and O. Ishaq. Automated number plate recognition using hough lines and template ...","url":["https://arxiv.org/pdf/1708.04879"]}
-{"year":"2017","title":"ISSUES IN HUMAN AND AUTOMATIC TRANSLATION QUALITY ASSESSMENT","authors":["S Doherty"],"snippet":"... 2013; Bojar et al. 2014). These campaigns typically involve the provision of existing corpora (eg Europarl, News Commentary, Common Crawl, Gigaword, Wiki Headlines, and the UN Corpus) as well as WMT-commissioned translations with Page 6. 6 ...","url":["https://www.researchgate.net/profile/Stephen_Doherty3/publication/314261771_Issues_in_human_and_automatic_translation_quality_assessment/links/58bea025458515dcd28defdd/Issues-in-human-and-automatic-translation-quality-assessment.pdf"]}
-{"year":"2017","title":"Iterative Attention Network for Question Answering","authors":["T Henighan"],"snippet":"... 3.6 future studies In this work only the 100-dimensional GloVe vectors trained on 6 billion tokens was used. It may be useful to try the 300-dimensional vectors trained over a 840 billion common-crawl corpus, which 6 Page 7. ...","url":["http://www.tomhenighan.com/pdfs/iterative-attention-network.pdf"]}
-{"year":"2017","title":"Joint Learning of Structural and Textual Features for Web Scale Event Extraction","authors":["J Wiedmann - 2017"],"snippet":"... In a second expansion step, this seed data set is further extended automatically by identifying single event pages in the Common Crawl, a repository of crawled web data, based on Microdata annotations and the annotations derived from the seed data. ...","url":["http://www.cs.ox.ac.uk/files/8846/aaai17-wiedmann-eventextraction.pdf"]}
-{"year":"2017","title":"Joint Training for Pivot-based Neural Machine Translation","authors":["Y Cheng, Q Yang, Y Liu, M Sun, W Xu"],"snippet":"... sets. The evaluation metric is case-insensitive BLEU [Papineni et al., 2002] as calculated by the multi-bleu.perl script. The WMT corpus is composed of the Common Crawl, News Commentary, Europarl v7 and UN corpora. The ...","url":["http://nlp.csai.tsinghua.edu.cn/~ly/papers/ijcai2017_cy.pdf"]}
-{"year":"2017","title":"Killing Two Birds with One Stone: Malicious Domain Detection with High Accuracy and Coverage","authors":["I Khalil, B Guan, M Nabeel, T Yu - arXiv preprint arXiv:1711.00300, 2017"],"snippet":"Page 1. Killing Two Birds with One Stone: Malicious Domain Detection with High Accuracy and Coverage Issa Khalil, Bei Guan, Mohamed Nabeel, Ting Yu Qatar Computing Research Institute {ikhalil,bguan,mnabeel,tyu}@hbku.edu.qa ...","url":["https://arxiv.org/pdf/1711.00300"]}
-{"year":"2017","title":"LDOW2017: 10th Workshop on Linked Data on the Web","authors":["J Lehmann, S Auer, S Capadisli, K Janowicz, C Bizer… - Proceedings of the 26th …, 2017"],"snippet":"... Wikidata, a collaborative knowledge-base designed to complement Wikipedia; LinkedGeoData, providing a structureddata export from OpenStreetMap; and Web Data Commons, collecting embedded meta-data extracted from billions of webpages found in the Common Crawl ...","url":["http://aidanhogan.com/docs/ldow2017.pdf"]}
-{"year":"2017","title":"Learned in Translation: Contextualized Word Vectors","authors":["B McCann, J Bradbury, C Xiong, R Socher - arXiv preprint arXiv:1708.00107, 2017"],"snippet":"... When training an MT-LSTM, we used fixed 300-dimensional word vectors. We used the CommonCrawl-840B GloVe model for English word vectors, which were completely fixed during training, so that the MT-LSTM had to learn how to use the pretrained vectors for translation. ...","url":["https://arxiv.org/pdf/1708.00107"]}
-{"year":"2017","title":"Learning bilingual word embeddings with (almost) no bilingual data","authors":["MAGLE Agirre"],"snippet":"... and Italian. Given that Finnish is not in- cluded in this collection, we used the 2.8 billion word Common Crawl corpus provided at WMT 20164 instead, which we tokenized using the Stanford Tokenizer (Manning et al., 2014). In ...","url":["http://www.aclweb.org/anthology/P/P17/P17-1042.pdf"]}
-{"year":"2017","title":"Learning Paraphrastic Sentence Embeddings from Back-Translated Bitext","authors":["J Wieting, J Mallinson, K Gimpel - arXiv preprint arXiv:1706.01847, 2017"],"snippet":"... EN, FR→EN, and DE→EN, respectively). The training data included: Eu- roparl v7 (Koehn, 2005), the Common Crawl corpus, the UN corpus (Eisele and Chen, 2010), News Commentary v10, the 109 French-English corpus, ...","url":["https://arxiv.org/pdf/1706.01847"]}
-{"year":"2017","title":"Learning to Predict: A Fast Re-constructive Method to Generate Multimodal Embeddings","authors":["G Collell, T Zhang, MF Moens - arXiv preprint arXiv:1703.08737, 2017"],"snippet":"... 4 Experimental setup 4.1 Word embeddings We use 300-dimensional GloVe1 vectors [19] pre-trained on the Common Crawl corpus consisting of 840B tokens and a 2.2M words vocabulary. 4.2 Visual data and features We use ImageNet [17] as our source of labeled images. ...","url":["https://arxiv.org/pdf/1703.08737"]}
-{"year":"2017","title":"Learning to select data for transfer learning with Bayesian Optimization","authors":["S Ruder, B Plank - arXiv preprint arXiv:1707.05246, 2017"],"snippet":"... We train an LDA model (Blei et al., 2003) with 50 topics and 10 iterations for topic distribution-based representations and use GloVe embeddings (Pennington et al., 2014) trained on 42B tokens of Common Crawl data6 for word embedding-based representations. ...","url":["https://arxiv.org/pdf/1707.05246"]}
-{"year":"2017","title":"Length, Interchangeability, and External Knowledge: Observations from Predicting Argument Convincingness","authors":["P Potash, R Bhattacharya, A Rumshisky"],"snippet":"... and create the appropriate representation. For the embedding representation, we use GloVe (Pennington et al., 2014) 300 dimensions learned from the Common Crawl corpus with 840 billion tokens. Our Wikipedia data is from ...","url":["https://pdfs.semanticscholar.org/9785/f21ac0b33689dc3ae711a94383eda01785e9.pdf"]}
-{"year":"2017","title":"Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search","authors":["C Hokamp, Q Liu - arXiv preprint arXiv:1704.07138, 2017"],"snippet":"Page 1. Lexically Constrained Decoding for Sequence Generation Using Grid Beam Search Chris Hokamp ADAPT Centre Dublin City University chris.hokamp@computing.dcu.ie Qun Liu ADAPT Centre Dublin City University qun.liu@dcu.ie Abstract ...","url":["https://arxiv.org/pdf/1704.07138"]}
-{"year":"2017","title":"LIG-CRIStAL Submission for the WMT 2017 Automatic Post-Editing Task","authors":["A Berard, L Besacier, O Pietquin - Proceedings of the Second Conference on …, 2017"],"snippet":"... To mitigate this, we decided to limit our use of external data to monolingual English (commoncrawl). ... PE side Similarly to Junczys-Dowmunt and Grundkiewicz (2016) we first performed a coarse filtering of well-formed sentences of commoncrawl...","url":["http://www.aclweb.org/anthology/W17-4772"]}
-{"year":"2017","title":"LIG-CRIStAL System for the WMT17 Automatic Post-Editing Task","authors":["A Berard, O Pietquin, L Besacier - arXiv preprint arXiv:1707.05118, 2017"],"snippet":"... To mitigate this, we decided to limit our use of external data to monolingual English (commoncrawl). ... PE side Similarly to Junczys-Dowmunt and Grundkiewicz (2016) we first performed a coarse filtering of well-formed sentences of commoncrawl...","url":["https://arxiv.org/pdf/1707.05118"]}
-{"year":"2017","title":"LIMSI submission for WMT'17 shared task on bandit learning","authors":["G Wisniewski - WMT 2017, 2017"],"snippet":"... At the end, our monolingual corpus contain 193292548 sentences. The translation model is estimated from the CommonCrawl, NewsCo, Europarl and Rapid corpora, resulting in a parallel corpus made of 5919142 sentences. ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=698"]}
-{"year":"2017","title":"Linked Data is People: Building a Knowledge Graph to Reshape the Library Staff Directory","authors":["JA Clark, SWH Young"],"snippet":"... RDFa and JSON-LD are two other syntax encodings that enable structured data in HTML pages. In their analysis of structured data in the Common Crawl dataset, Bizer et al. (2013) note that the growth of machine-readable descriptions of web content continues to grow. ...","url":["http://journal.code4lib.org/articles/12320"]}
-{"year":"2017","title":"LMU Munich's Neural Machine Translation Systems for News Articles and Health Information Texts","authors":["M Huck, F Braune, A Fraser"],"snippet":"... 1. Adding the News Commentary (NC) and Common Crawl (CC) parallel training data as provided for WMT17 by the organizers of the news translation shared task. We initialize the optimization on the larger corpus with the Europarl-trained baseline model. ...","url":["http://www.cis.uni-muenchen.de/~fraser/pubs/huck_wmt2017_system.pdf"]}
-{"year":"2017","title":"Lump at SemEval-2017 Task 1: Towards an Interlingua Semantic Similarity","authors":["C España-Bonet, A Barrón-Cedeño - Proceedings of the 11th International Workshop …, 2017"],"snippet":"... 2http://commoncrawl.org/ 3http://www.casmacat.eu/corpus/ news-commentary.html 4https://sites.google.com/site/ iwsltevaluation2016/mt-track/ 5We built a version of the lemma translator with an extra language: Babel synsets (cf. ...","url":["http://www.aclweb.org/anthology/S17-2019"]}
-{"year":"2017","title":"Machine Comprehension Using Multi-Perspective Context Matching and Co-Attention","authors":["A Bajenov, T Gupta"],"snippet":"... Embedding Layer Trainable or fixed embeddings Dropout post-embedding layer Gigaword (6B) or Common Crawl (840B) corpus Architecture Choices Number of layers Type of Layers Representation Sizes embedding size (100-300) lstm units (100-200) perspective units ...","url":["http://web.stanford.edu/class/cs224n/reports/2758309.pdf"]}
-{"year":"2017","title":"Machine Comprehension with MMLSTM and Clustering","authors":["T Romero, Z Barnes, F Cipollone"],"snippet":"... 1.2 Data Our model is trained on the SQuAD dataset [1]. We split the SQuAD dataset up into 82k training questions, 5k validation questions, and 10k dev questions. The set of test questions is withheld. We use 300d Common Crawl GloVe [2] vectors for our word embeddings. ...","url":["https://web.stanford.edu/class/cs224n/reports/2761209.pdf"]}
-{"year":"2017","title":"Machine Question and Answering","authors":["J Chang, M Jiang, D Le"],"snippet":"... 5 Page 6. were also initialized with 300-dimensional GloVe word vectors from the 840B Common Crawl corpus (Pennington et al., 2014). The above plots illustrate the cross entropy loss (left) and F1 score (right) vs epoch and clearly show overfitting. ...","url":["https://web.stanford.edu/class/cs224n/reports/2761996.pdf"]}
-{"year":"2017","title":"Machine Translation Evaluation with Neural Networks","authors":["F Guzmán, S Joty, L Màrquez, P Nakov - Computer Speech & Language, 2016"],"snippet":"We present a framework for machine translation evaluation using neural networks in a pairwise setting, where the goal is to select the better translation from a.","url":["http://www.sciencedirect.com/science/article/pii/S0885230816301693"]}
-{"year":"2017","title":"Machine Translation: Phrase-Based, Rule-Based and Neural Approaches with Linguistic Evaluation","authors":["V Macketanz, E Avramidis, A Burchardt, J Helcl… - Cybernetics and Information …, 2017"],"snippet":"... difference). The generic parallel training data (Europarl [18], News Commentary, MultiUN [19], Commoncrawl [20]) are augmented with domain-specific data from the IT domain (Libreoffice, Ubuntu, Chromium Browser [21]). ...","url":["https://www.degruyter.com/downloadpdf/j/cait.2017.17.issue-2/cait-2017-0014/cait-2017-0014.xml"]}
-{"year":"2017","title":"Massive Exploration of Neural Machine Translation Architectures","authors":["D Britz, A Goldie, T Luong, Q Le - arXiv preprint arXiv:1703.03906, 2017"],"snippet":"... 3 Experimental Setup 3.1 Datasets and Preprocessing We run all experiments on the WMT'15 English→German task consisting of 4.5M sentence pairs, obtained by combining the Europarl v7, News Commentary v10, and Common Crawl corpora. ...","url":["https://arxiv.org/pdf/1703.03906"]}
-{"year":"2017","title":"Matching Web Tables To DBpedia-A Feature Utility Study","authors":["D Ritze, C Bizer - context, 2017"],"snippet":"... 215 Page 7. has been extracted from the CommonCrawl web corpus3. ... 3http://commoncrawl org/ Table 3 shows the results of the correlation analysis for the property and instance similarity matrices regarding precision, eg PPstdev, and recall, eg RPstdev. ...","url":["https://openproceedings.org/2017/conf/edbt/paper-148.pdf"]}
-{"year":"2017","title":"Methods of sentence extraction, abstraction and ordering for automatic text summarization","authors":["MT Nayeem - 2017"],"snippet":"Page 1. METHODS OF SENTENCE EXTRACTION, ABSTRACTION AND ORDERING FOR AUTOMATIC TEXT SUMMARIZATION MIR TAFSEER NAYEEM Bachelor of Science, Islamic University of Technology, 2011 A Thesis …","url":["https://www.uleth.ca/dspace/bitstream/handle/10133/4993/NAYEEM_MIR_TAFSEER_MSC_2017.pdf?sequence=1"]}
-{"year":"2017","title":"Modeling Target-Side Inflection in Neural Machine Translation","authors":["A Tamchyna, MWD Marco, A Fraser - arXiv preprint arXiv:1707.06012, 2017"],"snippet":"Page 1. Modeling Target-Side Inflection in Neural Machine Translation Aleš Tamchyna1,2 and Marion Weller-Di Marco1,3 and Alexander Fraser1 1LMU Munich, 2Memsource, 3University of Stuttgart ales.tamchyna@memsource ...","url":["https://arxiv.org/pdf/1707.06012"]}
-{"year":"2017","title":"Modeling the Dynamic Framing of Controversial Topics in Online Communities","authors":["J Mendelsohn"],"snippet":"... After preprocessing, each post is a bag-of-words of variable length: p (n) ij = [w1,w2, ..., wl]. Each word in a post is represented by its 300-dimensional GloVe vector, trained on Common Crawl data (CITE GLOVE). Posts are then represented as the average of each word's vector. ...","url":["http://web.stanford.edu/class/cs224n/reports/2761128.pdf"]}
-{"year":"2017","title":"Monotasks: Architecting for Performance Clarity in Data Analytics Frameworks","authors":["K Ousterhout, C Canel, S Ratnasamy, S Shenker - 2017"],"snippet":"Page 1. Monotasks: Architecting for Performance Clarity in Data Analytics Frameworks Kay Ousterhout UC Berkeley Christopher Canel⇤ Carnegie Mellon University Sylvia Ratnasamy UC Berkeley Scott Shenker UC Berkeley, ICSI ...","url":["http://kayousterhout.org/publications/sosp17-final183.pdf"]}
-{"year":"2017","title":"Multi-channel Encoder for Neural Machine Translation","authors":["H Xiong, Z He, X Hu, H Wu - arXiv preprint arXiv:1712.02109, 2017"],"snippet":"… WMT'14 English-French. We use the full WMT' 14 parallel corpus as our training data. The detailed data sets are Europarl v7, Common Crawl, UN, News Commentary, Gi- gaword. In total, it includes 36 million sentence pairs …","url":["https://arxiv.org/pdf/1712.02109"]}
-{"year":"2017","title":"Multi-Domain Neural Machine Translation through Unsupervised Adaptation","authors":["MA Farajian, M Turchi, M Negri, M Federico"],"snippet":"... PHP, Ubuntu, and translated UN documents (UN-TM).2 Since the size of these corpora is relatively small for training robust MT systems, in particular NMT solutions, we added the News Commentary data from WMT'133(WMT nc), as well as the CommonCrawl (CommonC.) and ...","url":["https://hermessvn.fbk.eu/svn/hermes/open/federico/papers/Amin_et.al-wmt2017.pdf"]}
-{"year":"2017","title":"Multimodal Learning for Web Information Extraction","authors":["D Gong, DZ Wang, Y Peng - ACM International Conference​​ on​​ Multimedia, 2017"],"snippet":"… Collecting image corpus. The image corpus is not included in the Common Crawl data [25] where we derived text corpus … 5.1.2 Corpus. We derive our text and image corpus based on the Common Crawl dataset [25] that is publicly available on Amazon S3 …","url":["https://pdfs.semanticscholar.org/d2a5/815007832255a033759d25d771157ae9be16.pdf"]}
-{"year":"2017","title":"Multimodal sentiment analysis with word-level fusion and reinforcement learning","authors":["M Chen, S Wang, PP Liang, T Baltrušaitis, A Zadeh… - Proceedings of the 19th …, 2017"],"snippet":"… For text inputs, we use pre-trained word embeddings (glove.840B.300d) [19] to convert the transcripts of videos in the CMU-MOSI dataset into word vectors. This is a 300 dimensional word embedding trained on 840 billion tokens from the common crawl dataset …","url":["http://dl.acm.org/citation.cfm?id=3136755.3136801"]}
-{"year":"2017","title":"Multiple Turn Comprehension for the Bi-Directional Attention Flow Model","authors":["T Liu"],"snippet":"... The word embedding layer converts each word in the context and question into a dense vector word representation. We use the pre-trained GloVe (Pennington et al., 2014) vectors for this layer, in particular the Common Crawl 840B tokens, 300d vectors. ...","url":["http://web.stanford.edu/class/cs224n/reports/2761890.pdf"]}
-{"year":"2017","title":"Named Entity Recognition in Twitter using Images and Text","authors":["D Esteves, R Peres, J Lehmann, G Napolitano"],"snippet":"... A disadvantage when using web search engines is that they are not open and free. This can be circumvented by indexing and searching on other large sources of information, such as Common Crawl and Flickr11. ... 11 http://commoncrawl.org/ and https://www.flickr.com/ Page 7. 7 ...","url":["https://www.researchgate.net/profile/Diego_Esteves/publication/317721565_Named_Entity_Recognition_in_Twitter_using_Images_and_Text/links/594a85dda6fdcc89090cb5f5/Named-Entity-Recognition-in-Twitter-using-Images-and-Text.pdf"]}
-{"year":"2017","title":"Native Language Identification from i-vectors and Speech Transcriptions","authors":["B Ulmer, A Zhao, N Walsh"],"snippet":"... word (Pennington et al., 2014). The GloVe embeddings of words came from the Common Crawl 42B to- kens collection, and the 300 dimensional embeddings were used (Pennington et al., 2014). If no corresponding GloVe ...","url":["http://web.stanford.edu/class/cs224s/reports/Ben_Ulmer.pdf"]}
-{"year":"2017","title":"Natural Language Question-Answering using Deep Learning","authors":["B Liu, F Lyu, R Roy"],"snippet":"... We experimented with both fixed 193 CommonCrawl.840B.300d pretrained word vectors and GLoVE.6B.100d pretrained word 194 vectors (Pennington, Socher, & Manning, 2015) 195 We enforce a fixed question length of 22 words, and fixed context length of 300 words. ...","url":["https://pdfs.semanticscholar.org/505a/ed7c751eb57bf5e59ab1cedc49448376b7d5.pdf"]}
-{"year":"2017","title":"Neural Lie Detection with the CSC Deceptive Speech Dataset","authors":["S Desai, M Siegelman, Z Maurer"],"snippet":"... Each acoustic feature frame was 34 dimensional and each speaker-dependent frame was 68 dimensional. Lexical features were encoded using GloVe Wikipedia and CommonCrawl 100-dimensional embeddings[9] based on the transcripts provided with the dataset. ...","url":["http://web.stanford.edu/class/cs224s/reports/Shloka_Desai.pdf"]}
-{"year":"2017","title":"Neural Machine Translation Leveraging Phrase-based Models in a Hybrid Search","authors":["L Dahlmann, E Matusov, P Petrushkov, S Khadivi - arXiv preprint arXiv:1708.03271, 2017"],"snippet":"... For development and test sets, two reference translations are used. The German→English system is trained on parallel corpora provided for the constrained WMT 2017 evaluation (Europarl, Common Crawl, and others). We ...","url":["https://arxiv.org/pdf/1708.03271"]}
-{"year":"2017","title":"Neural Machine Translation Training in a Multi-Domain Scenario","authors":["H Sajjad, N Durrani, F Dalvi, Y Belinkov, S Vogel - arXiv preprint arXiv:1708.08712, 2017","HSNDF Dalvi, Y Belinkov, S Vogel"],"snippet":"... For German-English, we use the Europarl (EP), and the Common Crawl (CC) corpora made available for the 1st Conference on Statistical Machine Translation2 as out- of-domain corpus. ... EP = Europarl, CC = Common Crawl, UN = United Nations. ...","url":["https://arxiv.org/pdf/1708.08712","https://www.researchgate.net/profile/Nadir_Durrani/publication/319349687_Neural_Machine_Translation_Training_in_a_Multi-Domain_Scenario/links/59d0f2a3aca2721f43673f75/Neural-Machine-Translation-Training-in-a-Multi-Domain-Scenario.pdf"]}
-{"year":"2017","title":"Neural Machine Translation with LSTM's","authors":["J Dhaliwal"],"snippet":"... 3. dev08 11 - old dev dat from 2008 to 2011 (0.3M) 4. crawl - data from common crawl (90M) 5. ccb2 - 109 parallel corpus (81M) ... 3. dev08 11 - old dev dat from 2008 to 2011 (0.3M) 4. crawl - data from common crawl (90M) 5. ccb2 pc30109 parallel corpus (81M) ...","url":["https://people.umass.edu/~jdhaliwal/files/s2s.pdf"]}
-{"year":"2017","title":"Neural Networks and Spelling Features for Native Language Identification","authors":["J Bjerva, G Grigonyte, R Ostling, B Plank - Bronze Sponsors, 2017"],"snippet":"... PoS tags are represented by 64-dimensional embeddings, initialised randomly; word tokens by 300-dimensional embeddings, initialised with GloVe (Pennington et al., 2014) em- beddings trained on 840 billion words of English web data from the Common Crawl project. ...","url":["http://www.aclweb.org/anthology/W/W17/W17-50.pdf#page=255"]}
-{"year":"2017","title":"Neural vs. Phrase-Based Machine Translation in a Multi-Domain Scenario","authors":["MA Farajian, M Turchi, M Negri, N Bertoldi, M Federico - EACL 2017, 2017"],"snippet":"... K PHP 38.4 K 259.0 K 9.7 K Ubuntu 9.0 K 47.7 K 8.6 K UN-TM 40.3 K 913.8 K 12.5 K CommonCrawl 2.6 M ... in particular NMT solutions, we used CommonCrawl and Europarl corpora as out-domain data in addition to the above-mentioned domain-specific corpora, resulting in ...","url":["http://www.aclweb.org/anthology/E/E17/E17-2.pdf#page=312"]}
-{"year":"2017","title":"New Word Pair Level Embeddings to Improve Word Pair Similarity","authors":["A Shaukat, N Khan"],"snippet":"... Many previous approaches present embeddings for individual words [14, 15, 16, 27] using their distributional semantics (Common Crawl corpus1) and structured knowledge from ConceptNet and PPDB [31]. ... Figure 1 shows 1 http://commoncrawl.org/ ...","url":["http://faculty.pucit.edu.pk/nazarkhan/work/wps/wpe_icdar_wml17.pdf"]}
-{"year":"2017","title":"NEWSQA: AMachine COMPREHENSION DATASET","authors":["A Trischler, T Wang, X Yuan, J Harris, A Sordoni…"],"snippet":"... Both mLSTM and BARB are implemented with the Keras framework (Chollet, 2015) using the Theano (Bergstra et al., 2010) backend. Word embeddings are initialized using GloVe vectors (Pennington et al., 2014) pre-trained on the 840-billion Common Crawl corpus. ...","url":["https://www.openreview.net/pdf?id=ry3iBFqgl"]}
-{"year":"2017","title":"NoSQL Web Crawler Application","authors":["GC Deka - Advances in Computers, 2017"],"snippet":"With the advent of Web technology, the Web is full of unstructured data called Big Data. However, these data are not easy to collect, access, and process at lar.","url":["http://www.sciencedirect.com/science/article/pii/S0065245817300323"]}
-{"year":"2017","title":"Novel Ranking-Based Lexical Similarity Measure for Word Embedding","authors":["J Dutkiewicz, C Jędrzejek - arXiv preprint arXiv:1712.08439, 2017"],"snippet":"… 4.1 Experimental setup We use the unmodified vector space model trained on 840 billion words from Common Crawl data with the GloVe algorithm introduced in Pennington et al. (2014). The model consists of 2.2 million unique vectors; Each vector consists of 300 components …","url":["https://arxiv.org/pdf/1712.08439"]}
-{"year":"2017","title":"NRC Machine Translation System for WMT 2017","authors":["C Lo, S Larkin, B Chen, D Stewart, C Cherry, R Kuhn… - WMT 2017, 2017"],"snippet":"... 2 Russian-English news translation We used all the Russian-English parallel corpora available for the constrained news translation task. They include the CommonCrawl corpus, the NewsCommentary v12 corpus, the Yandex corpus and the Wikipedia headlines corpus. ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=354"]}
-{"year":"2017","title":"On the Effective Use of Pretraining for Natural Language Inference","authors":["I Cases, MT Luong, C Potts - arXiv preprint arXiv:1710.02076, 2017"],"snippet":"... a 1We used the publicly released embeddings, trained with Common Crawl 840B tokens for GloVe (http:// nlp.stanford.edu/projects/glove/) and Google News 42B for word2vec https://code.google.com/ archive/p/word2vec/. Although ...","url":["https://arxiv.org/pdf/1710.02076"]}
-{"year":"2017","title":"Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks","authors":["N Reimers, I Gurevych - arXiv preprint arXiv:1707.06799, 2017","NRI Gurevych"],"snippet":"... (2014) trained either on Wikipedia 2014 + Gigaword 5 (about 6 billion tokens) or on Common Crawl (about 840 billion tokens), and the Komninos and Manandhar (2016) embeddings11 trained on the Wikipedia August 2015 dump (about 2 billion tokens). ...","url":["https://arxiv.org/pdf/1707.06799","https://www.arxiv-vanity.com/papers/1707.06799v2/"]}
-{"year":"2017","title":"Parallel Training Data Selection for Conversational Machine Translation","authors":["X Niu, M Carpuat"],"snippet":"... Corpus # Sentences # Words (en/fr) OpenSubtitles 33.5 M 284.0 M / 268.3 M MultiUN 13.2 M 367.1 M / 432.3 M Common Crawl 3.2 M 81.1 M / 91.3 M Europarl v7 2.0 M 55.7 M / 61.9 M Wikipedia 396 k 9.7 M / 8.7 M TED corpus 207 k 4.5 M / 4.8 M News Commentary v10 199 k ...","url":["https://pdfs.semanticscholar.org/fdf6/ae86229f51893dd6e33579511489af4a5eb7.pdf"]}
-{"year":"2017","title":"Passfault: an Open Source Tool for Measuring Password Complexity and Strength","authors":["BA Rodrigues, JRB Paiva, VM Gomes, C Morris…"],"snippet":"... Wikipedia: The full text of Wikipedia in 2015. • Reddit: The corpus of Reddit comments through May 2015. • CCrawl: Text extracted from the Common Crawl and language-detected with cld2. Page 6. ACKNOWLEDGMENTS ...","url":["https://www.owasp.org/images/1/13/Artigo-Passfault.pdf"]}
-{"year":"2017","title":"Predictor-Estimator using Multilevel Task Learning with Stack Propagation for Neural Quality Estimation","authors":["H Kim, JH Lee, SH Na - WMT 2017, 2017"],"snippet":"... allel corpora including the Europarl corpus, common crawl corpus, news commentary, rapid corpus of EU press releases for the WMT17 translation task3, and src-pe (source sentences-their target post-editions) pairs for the WMT17 QE task. ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=586"]}
-{"year":"2017","title":"Predictor-Estimator: Neural Quality Estimation Based on Target Word Prediction for Machine Translation","authors":["H Kim, HY Jung, H Kwon, JH Lee, SH Na - ACM Transactions on Asian and Low- …, 2017"],"snippet":"... For training the word predictor, two parallel datasets of different sizes were used: a small dataset consisting of only the Europarl corpus (Koehn 2005) and a large dataset consisting of the Europarl corpus, common crawl corpus, and news commentary, which were provided for ...","url":["http://dl.acm.org/citation.cfm?id=3109480"]}
-{"year":"2017","title":"Probabilistic Relation Induction in Vector Space Embeddings","authors":["Z Bouraoui, S Jameel, S Schockaert - arXiv preprint arXiv:1708.06266, 2017"],"snippet":"... data set1 (SG-GN). We also use two embeddings that have been learned with GloVe, one from the same Wikipedia dump (GloVe-Wiki) and one from the 840B words Common Crawl data set2 (GloVe-CC). For relations with at ...","url":["https://arxiv.org/pdf/1708.06266"]}
-{"year":"2017","title":"Proposal for Automatic Extraction of Taxonomic Relations in Domain Corpus","authors":["HRL Chavez, MT Vidal - Advances in Pattern Recognition"],"snippet":"… His methodology is based on two sources of evidence, substring matches and Hearts patterns. They analyze all Wikipedia in search of the Hearts patterns and extract those relationships and make use of another corpus like GigaWord, ukWac and CommonCrawl. 30 …","url":["http://www.rcs.cic.ipn.mx/rcs/2017_133/Proposal%20for%20Automatic%20Extraction%20of%20Taxonomic%20Relations%20in%20Domain%20Corpus.pdf"]}
-{"year":"2017","title":"ProvDS: Uncertain Provenance Management over Incomplete Linked Data Streams","authors":["Q Liu"],"snippet":"... These datasets will be used to evaluate our provenance computation over incomplete Linked Data Streams techniques. • The Web Data Commons project5 extracts structured data from the Common Crawl, the largest web corpus available to the public. ...","url":["https://iswc2017.semanticweb.org/wp-content/uploads/papers/DC/paper_2.pdf"]}
-{"year":"2017","title":"Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations","authors":["J Wieting, K Gimpel - arXiv preprint arXiv:1711.05732, 2017"],"snippet":"… The model was trained on this data along with data from some smaller Czech sources ( 160k from common-crawl, 650k from Europarlm and 190k from News) … We compare with Eu- roparl, Common-crawl, and News for Czech …","url":["https://arxiv.org/pdf/1711.05732"]}
-{"year":"2017","title":"Quantext: Analysing student responses to short-answer questions","authors":["J McDonald, ACM Moskal"],"snippet":"… 1 Similarity is calculated from a word2vec model of word embeddings using the GloVe algorithm (Pennington, Socher & Manning, 2014) and is pre-trained on the Common Crawl Corpus (Spiegler, 2013) … 1532-1543 Spiegler, S (2013) Statistics of the Common Crawl Corpus …","url":["https://www.researchgate.net/profile/Adon_Moskal/publication/321266093_Quantext_Analysing_student_responses_to_short-answer_questions/links/5a179890a6fdcc50ade61806/Quantext-Analysing-student-responses-to-short-answer-questions.pdf"]}
-{"year":"2017","title":"Question Answering on SQuAD","authors":["C Yang, H Ishfaq"],"snippet":"... Then we use word embeddings from GloVe[6] to map words into embedding vectors. To decrease the out of vocabulary (OOV) error, we use the Common Crawl 840B 300d GloVe vectors. Words not found in GloVe are initialized randomly. ...","url":["https://web.stanford.edu/class/cs224n/reports/2749099.pdf"]}
-{"year":"2017","title":"Question Answering on the SQuAD Dataset","authors":["DH Park, V Lakshman"],"snippet":"... Initially, we used 100-dimensional word embeddings pretrained on the Wikipedia corpus to train our model before fine-tuning our system by switching to 300-dimensional GloVe vectors trained on the Common Crawl corpus. ...","url":["https://web.stanford.edu/class/cs224n/reports/2761899.pdf"]}
-{"year":"2017","title":"Question Answering with Multi-Perspective Context Matching","authors":["J Asperger"],"snippet":"... The word-level embeddings were taken from GloVe vectors that were pre-trained on the 840-billion-word Common Crawl Corpus. ... For my word representations, I used 300-dimensional GloVe vectors trained on the 840 billion word Common Crawl Corpus. ...","url":["https://pdfs.semanticscholar.org/599f/376502c61550fdd37011e0cb7157d281b493.pdf"]}
-{"year":"2017","title":"Reading Comprehension on the SQuAD Dataset","authors":["FNU Budianto"],"snippet":"... The Glove version used is the Common Crawl (840B tokens, 2.2M vocab, cased, 300d vectors). Figure 1: Histogram of context length, question length, and answer length in the training set. 2 Page 3. ... I use the Glove840B300d Common Crawl for the word embedding layer. ...","url":["https://web.stanford.edu/class/cs224n/reports/2762006.pdf"]}
-{"year":"2017","title":"Recurrent neural networks with specialized word embeddings for health-domain named-entity recognition","authors":["IJ Unanue, EZ Borzeshi, M Piccardi - arXiv preprint arXiv:1706.09569, 2017"],"snippet":"... Therefore, the training of the word embeddings only requires large, general-purpose text corpora such as Wikipedia (400K unique words) or Common Crawl (2.2M unique words), without the need for any manual annotation. ...","url":["https://arxiv.org/pdf/1706.09569"]}
-{"year":"2017","title":"Regularizing neural networks by penalizing confident output distributions","authors":["G Pereyra, G Tucker, J Chorowski, Ł Kaiser, G Hinton - arXiv preprint arXiv: …, 2017"],"snippet":"... 535–541. ACM, 2006. Christian Buck, Kenneth Heafield, and Bas Van Ooyen. N-gram counts and language models from the common crawl. In LREC, volume 2, pp. 4. Citeseer, 2014. 8 Page 9. Under review as a conference paper at ICLR 2017 ...","url":["https://arxiv.org/pdf/1701.06548"]}
-{"year":"2017","title":"Reinvestigating the Classification Approach to the Article and Preposition Error Correction","authors":["R Grundkiewicz, M Junczys-Dowmunt"],"snippet":"... Other than that, default options were used. We learnt word vectors from 75 millions of English sentences extracted from Common Crawl data4. ... 3 https://code.google.com/p/word2vec/ 4 https://commoncrawl.org/ 5 http://www.comp.nus.edu.sg/~nlp/conll14st.html Page 6. ...","url":["http://www.research.ed.ac.uk/portal/files/40342436/ltc_073_grundkiewicz_2.pdf"]}
-{"year":"2017","title":"Report on the 2nd Workshop on Managing the Evolution and Preservation of the Data Web (MEPDaW 2016)","authors":["J Debattista, JD Fernández, J Umbrich"],"snippet":"... 1Slides of the talk: https://aic.ai.wu.ac.at/ polleres/presentations/20160530Keynote-MEPDaW2016. pdf 2http://commoncrawl.org/ 3http://internetmemory.org/ 4https://archive.org/index.php 5http://swse.deri.org/dyldo/ ACM SIGIR Forum 84 Vol. 50 No. 2 December 2016 Page 4. ...","url":["https://pdfs.semanticscholar.org/c1eb/93952ed5cc4bda08bdd75bed84332656d864.pdf"]}
-{"year":"2017","title":"Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging","authors":["N Reimers, I Gurevych - arXiv preprint arXiv:1707.09861, 2017"],"snippet":"... (2014) trained either on Wikipedia 2014 + Gigaword 5 (GloVe1 with 100 dimensions and GloVe2 with 300 dimensions) or on Common Crawl (GloVe3), and the Komninos and Manandhar (2016) embeddings (Komn.)10. We also evaluate the approach of Bojanowski et al. ...","url":["https://arxiv.org/pdf/1707.09861"]}
-{"year":"2017","title":"Representation Stability as a Regularizer for Improved Text Analytics Transfer Learning","authors":["M Riemer, E Khabiri, R Goodwin - arXiv preprint arXiv:1704.03617, 2017"],"snippet":"... Our GRU model was fed a sequence of fixed 300 dimensional Glove vectors (Pennington et al., 2014), representing words based on analysis of 840 billion words from a common crawl of the internet, as the input xt for all tasks. ...","url":["https://arxiv.org/pdf/1704.03617"]}
-{"year":"2017","title":"Representing Sentences as Low-Rank Subspaces","authors":["J Mu, S Bhat, P Viswanath - arXiv preprint arXiv:1704.05358, 2017"],"snippet":"... Due to the widespread use of word2vec and GloVe, we use their publicly available word representations – word2vec(Mikolov et al., 2013) trained us- ing Google News1 and GloVe (Pennington et al., 2014) trained using Common Crawl2 – to test our observations. ...","url":["https://arxiv.org/pdf/1704.05358"]}
-{"year":"2017","title":"Retrieval, Crawling and Fusion of Entity-centric Data on the Web","authors":["S Dietze"],"snippet":"... Page 8. linked data world. However, the question to what extent this is due to the se- lective content of the Common Crawl or representative for schema.org adoption on the Web in general requires additional investigations. (a ...","url":["https://www.researchgate.net/profile/Stefan_Dietze/publication/312490472_Retrieval_Crawling_and_Fusion_of_Entity-centric_Data_on_the_Web/links/587e683808aed3826af45f18.pdf"]}
-{"year":"2017","title":"Rule-based spreadsheet data transformation from arbitrary to relational tables","authors":["AO Shigarov, AA Mikhailov - Information Systems, 2017"],"snippet":"... These include about 50% of tables presented in 0.4M spreadsheets of ClueWeb09 Crawl 1 [5] and 147M (61%) of 233M web tables extracted from Common Crawl 2 [3]. They lack explicit semantics required for computer programs to interpret their layout and content. ...","url":["http://www.sciencedirect.com/science/article/pii/S0306437917304301"]}
-{"year":"2017","title":"S3C: An Architecture for Space-Efficient Semantic Search over Encrypted Data in the Cloud","authors":["J Woodworth, MA Salehi, V Raghavan"],"snippet":"... To evaluate our system under Big data scale datasets, we utilized a second dataset, the Common Crawl Corpus from AWS, a web crawl composed of over five billion web pages We evaluated our system against the RFC using three types of metrics: Performance, Overhead ...","url":["http://hpcclab.org/paperPdf/bigdata16/bigdata16.pdf"]}
-{"year":"2017","title":"Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ","authors":["JS Kessler - arXiv preprint arXiv:1703.00565, 2017"],"snippet":"Page 1. Scattertext: a Browser-Based Tool for Visualizing how Corpora Differ Jason S. Kessler CDK Global jason.kessler@gmail.com Abstract Scattertext is an open source tool for visualizing linguistic variation between document categories in a language-independent way. ...","url":["https://arxiv.org/pdf/1703.00565"]}
-{"year":"2017","title":"Scientific Literature Text Mining and the Case for Open Access","authors":["G Sarma"],"snippet":"… science and society of scientific literature text mining. We need a scientific analogue to CommonCrawl, an open respository of scientific articles for use in exploratory data analysis. Ironically, this argument is not new, and indeed …","url":["https://www.tjoe.org/pub/scientific-literature-text-mining-and-the-case-for-open-access"]}
-{"year":"2017","title":"Secure Semantic Search Over Encrypted Big Data in the Cloud","authors":["JW Woodworth - 2017"],"snippet":"Page 1. Secure Semantic Search Over Encrypted Big Data in the Cloud A Dissertation Presented to the Graduate Faculty of the University of Louisiana at Lafayette In Partial Fulfillment of the Requirements for the Degree Master's of Science Jason W. Woodworth Spring 2017 ...","url":["http://hpcclab.org/theses/jasonwoodworth17.pdf"]}
-{"year":"2017","title":"SEF@ UHH at SemEval-2017 Task 1: Unsupervised knowledge-free semantic textual similarity via paragraph vector","authors":["MS Duma, W Menzel - Proceedings of SemEval-2017. http://www. aclweb. org/ …, 2017"],"snippet":"... Track / Corpora AR-AR AR-EN ES-ES ES-EN EN-EN TR-EN Commoncrawl - - 1.84M - 2.39M - Wikipedia 151K 151K - 1.81M - 160K TED 152K 152K - 157K - 137K MultiUN 1M 1M - - - - EUBookshop - - - - - 23K SETIMES - - - - - 207K Tatoeba - - - - - 156K SNLI* - 150K - 150K ...","url":["https://www.aclweb.org/anthology/S/S17/S17-2024.pdf"]}
-{"year":"2017","title":"Selective Decoding for Cross-lingual Open Information Extraction","authors":["S Zhang, K Duh, B Van Durme"],"snippet":"... The word embedding size is 300 for input tokens on both the encoder side and the decoder side. We use open-source GloVe vectors (Pennington et al., 2014) trained on Common Crawl 840B with 300 dimensions6 to initialize the word embeddings on the decoder side. ...","url":["https://www.cs.jhu.edu/~s.zhang/assets/pdf/selective-decoding.pdf"]}
-{"year":"2017","title":"Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints","authors":["N Mrkšić, I Vulić, DÓ Séaghdha, I Leviant, R Reichart… - arXiv preprint arXiv: …, 2017"],"snippet":"... The first four languages are those of the Multilingual SimLex-999 dataset. For the four SimLex languages, we employ four well-known, high-quality word vector collections: a) The Common Crawl GloVe English vectors from Pennington et al. ...","url":["https://arxiv.org/pdf/1706.00374"]}
-{"year":"2017","title":"Semantic vector evaluation and human performance on a new vocabulary MCQ test","authors":["JP Levy, JA Bullinaria, S McCormick"],"snippet":"... The 42B and 840B vectors were generated from 42 billion and 840 billion word corpora derived from Common Crawl archives (obtained by an automated process of systematically browsing the web). All the GloVe vectors used here have 300 dimensions. ...","url":["https://pdfs.semanticscholar.org/6506/d7783d2297f70c15a8caa07f022c36dfb168.pdf"]}
-{"year":"2017","title":"Semantic-based Analysis of Javadoc Comments","authors":["A Blasi, K Kuznetsov, A Goffi, SD Castellanos, A Gorla…"],"snippet":"... In our preliminary tests we found that the publicly available pre-trained word vectors of the GloVe model based on Common Crawl dataset2 already produce good results, as they identify relations such as: “if vertex exists” ; graph.containsVertex(v) and “if the graph contains the ...","url":["http://sattose.wdfiles.com/local--files/2017:schedule/SATToSE_2017_paper_24.pdf"]}
-{"year":"2017","title":"Semantics derived automatically from language corpora contain human-like biases","authors":["A Caliskan, JJ Bryson, A Narayanan - Science, 2017"],"snippet":"... We used the largest of the four corpora provided—the “Common Crawl” corpus obtained from a large-scale crawl of the Internet, containing 840 billion tokens (roughly, words). Tokens in this corpus are case sensitive, resulting in 2.2 million different ones. ...","url":["http://science.sciencemag.org/content/356/6334/183.abstract"]}
-{"year":"2017","title":"Semeval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation","authors":["D Cer, M Diab, E Agirre, I Lopez-Gazpio, L Specia - Proceedings of the 11th …, 2017"],"snippet":"Page 1. Proceedings of the 11th International Workshop on Semantic Evaluations (SemEval-2017), pages 1–14, Vancouver, Canada, August 3 - 4, 2017. cO2017 Association for Computational Linguistics SemEval-2017 Task ...","url":["http://nlp.arizona.edu/SemEval-2017/pdf/SemEval001.pdf"]}
-{"year":"2017","title":"Sentence Embedding for Neural Machine Translation Domain Adaptation","authors":["R Wang, A Finch, M Utiyama, E Sumita"],"snippet":"... Out- of-domain corpora contained Common Crawl, Europarl v7, News Commentary v10 and United Nation (UN) EN-FR parallel corpora.4 • NIST 2006 Chinese (ZH) to English corpus 5 was used as the in-domain training corpus, following the settings of (Wang et al., 2014). ...","url":["https://www.aclweb.org/anthology/P/P17/P17-2089.pdf"]}
-{"year":"2017","title":"SentiHeros at SemEval-2017 Task 5: An application of Sentiment Analysis on Financial Tweets","authors":["N Tabari, A Seyeditabari, W Zadrozny"],"snippet":"... In two separate experiments, we used vectors based on the Common Crawl (840B tokens, 2.2M vo- cab, cased, 300 dimensions), and the pre-trained word vectors for Twitter (2B tweets, 27B tokens, 1.2M vocab, 200 dimensions). ...","url":["http://nlp.arizona.edu/SemEval-2017/pdf/SemEval146.pdf"]}
-{"year":"2017","title":"Shallow reading with Deep Learning: Predicting popularity of online content using only its title","authors":["K Marasek, P law Rokita","W Stokowiec, T Trzcinski, K Wolk, K Marasek, P Rokita - arXiv preprint arXiv: …, 2017"],"snippet":"... As a text embedding in our experiments, we use publicly available GloVe word vectors [12] pre-trained on two datasets: Wikipedia 2014 with Gigaword5 (W+G5) and Common Crawl (CC)7. Since their output dimensionality can be modified, we show the results for varying ...","url":["http://ii.pw.edu.pl/~ttrzcins/papers/ISMIS_2017_paper_57.pdf","https://arxiv.org/pdf/1707.06806"]}
-{"year":"2017","title":"Simple Dynamic Coattention Networks","authors":["W Wu"],"snippet":"... unk〉. This affected the accuracy of predicted answers, as seen from Table 3. To reduced the number of unknown words, the Common Crawl GloVe vectors, which has a larger vocabulary, should be used instead. Document ...","url":["https://pdfs.semanticscholar.org/6a79/6c1c9c30913cb24d64939f90dcb06fa82be7.pdf"]}
-{"year":"2017","title":"Six Challenges for Neural Machine Translation","authors":["P Koehn, R Knowles - arXiv preprint arXiv:1706.03872, 2017"],"snippet":"... BLEU scores of 34.5 on the WMT 2016 news test set (for the NMT model, this reflects the BLEU score re- sulting from translation with a beam size of 1). We use a single corpus for computing our lexical frequency counts (a concatenation of Common Crawl, Europarl, and News ...","url":["https://arxiv.org/pdf/1706.03872"]}
-{"year":"2017","title":"Sockeye: A Toolkit for Neural Machine Translation","authors":["F Hieber, T Domhan, M Denkowski, D Vilar, A Sokolov… - arXiv preprint arXiv …, 2017"],"snippet":"… 9 Page 10. EN→DE LV→EN Dataset Sentences Tokens Types Sentences Tokens Types Europarl v7/v8 1,905,421 91,658,252 862,710 637,687 27,256,803 437,914 Common Crawl 2,394,616 97,473,856 3,655,645 - - - News Comm. v12 270,088 11,990,594 460,220 …","url":["https://arxiv.org/pdf/1712.05690"]}
-{"year":"2017","title":"Specialising Word Vectors for Lexical Entailment","authors":["I Vulić, N Mrkšić - arXiv preprint arXiv:1710.06371, 2017"],"snippet":"... experiment with a variety of well-known, publicly available English word vectors: 1) Skip-Gram with Negative Sampling (SGNS) (Mikolov et al., 2013) trained on the Polyglot Wikipedia (Al-Rfou et al., 2013) by Levy and Goldberg (2014); 2) GLOVE Common Crawl (Pennington et ...","url":["https://arxiv.org/pdf/1710.06371"]}
-{"year":"2017","title":"SpreadCluster: Recovering Versioned Spreadsheets through Similarity-Based Clustering","authors":["L Xu, W Dou, C Gao, J Wang, J Wei, H Zhong, T Huang"],"snippet":"Page 1. SpreadCluster: Recovering Versioned Spreadsheets through Similarity-Based Clustering Liang Xu1,2, Wensheng Dou1*, Chushu Gao1, Jie Wang1,2, Jun Wei1,2, Hua Zhong1, Tao Huang1 1State Key Laboratory of ...","url":["http://www.tcse.cn/~wsdou/papers/2017-msr-spreadcluster.pdf"]}
-{"year":"2017","title":"SQuAD Question Answering using Multi-Perspective Matching","authors":["Z Maurer, S Desai, S Usmani"],"snippet":"... in some cases. In terms of future work to improve on our models, we can use 840B Common Crawl GloVe word vectors rather than the Glove word vectors pretrained on Wikipedia 2014 and Gigaword5. Given additional computational ...","url":["https://pdfs.semanticscholar.org/3b1a/a646bdc6daab268f6763b829686b00263333.pdf"]}
-{"year":"2017","title":"Story Cloze Ending Selection Baselines and Data Examination","authors":["M Armstrong","T Mihaylov, A Frank - arXiv preprint arXiv:1703.04330, 2017"],"snippet":"Our contribution is that we set a new baseline for the task, showing that a simple linear model based on distributed representations and semantic similarity features achieves state-of-the-art results. We also evaluate the ability of different embedding …","url":["https://arxiv.org/pdf/1703.04330","https://zdoc.pub/story-cloze-ending-selection-baselines-and-data-examination.html"]}
-{"year":"2017","title":"Stronger Baselines for Trustable Results in Neural Machine Translation","authors":["M Denkowski, G Neubig - arXiv preprint arXiv:1706.09733, 2017"],"snippet":"... Scenario Size (sent) Sources WMT German-English 4,562,102 Europarl, Common Crawl, news commentary WMT English-Finnish 2,079,842 Europarl, Wikipedia titles WMT Romanian-English 612,422 Europarl, SETimes IWSLT English-French 220,400 TED talks IWSLT Czech ...","url":["https://arxiv.org/pdf/1706.09733"]}
-{"year":"2017","title":"Structured Attention Networks","authors":["Y Kim, C Denton, L Hoang, AM Rush - arXiv preprint arXiv:1702.00887, 2017"],"snippet":"Page 1. Under review as a conference paper at ICLR 2017 STRUCTURED ATTENTION NETWORKS Yoon Kim∗ Carl Denton∗ Luong Hoang Alexander M. Rush {yoonkim@seas,carldenton@college,lhoang@g,srush@seas ...","url":["https://arxiv.org/pdf/1702.00887"]}
-{"year":"2017","title":"Supervised Learning of Universal Sentence Representations from Natural Language Inference Data","authors":["A Conneau, D Kiela, H Schwenk, L Barrault, A Bordes - arXiv preprint arXiv: …, 2017"],"snippet":"... 512 hidden units. We use opensource GloVe vectors trained on Common Crawl 840B2 with 300 dimensions as fixed word embeddings and initialize other word vectors to random values sampled from U(-0.1,0.1). Input sen ...","url":["https://arxiv.org/pdf/1705.02364"]}
-{"year":"2017","title":"SVD-Softmax: Fast Softmax Approximation on Large Vocabulary Neural Networks","authors":["K Shim, M Lee, I Choi, Y Boo, W Sung - Advances in Neural Information Processing …, 2017"],"snippet":"… 5, pp. 79–86. [29] Common Crawl Foundation, “Common crawl,” http://commoncrawl.org, 2016, Accessed: 2017-04-11. [30] Jorg Tiedemann, “Parallel data, tools and interfaces in OPUS,” in LREC, 2012, vol. 2012, pp. 2214–2218. 10 Page 11 …","url":["http://papers.nips.cc/paper/7130-svd-softmax-fast-softmax-approximation-on-large-vocabulary-neural-networks.pdf"]}
-{"year":"2017","title":"SwissLink: High-Precision, Context-Free Entity Linking Exploiting Unambiguous Labels","authors":["R Prokofyev, M Luggen, DE Difallah, P Cudré-Mauroux - 2017"],"snippet":"… In order to understand how annotations are used on the Web, we crawled all entity links found on two large datasets, by processing the CommonCrawl 3 and the Wikipedia dumps 4. The output of our processing is a list of all words and phrases that were used as anchors in …","url":["https://exascale.info/assets/pdf/swisslink-semantics2017.pdf"]}
-{"year":"2017","title":"Syntax-Directed Attention for Neural Machine Translation","authors":["K Chen, R Wang, M Utiyama, E Sumita, T Zhao - arXiv preprint arXiv:1711.04231, 2017"],"snippet":"… 4.1 Data sets The proposed methods were evaluated on two data sets. • For English (EN) to German (DE) translation task, 4.43 million bilingual sentence pairs of the WMT'14 data set was used as the training data, including Common Crawl, News Commentary and Europarl v7 …","url":["https://arxiv.org/pdf/1711.04231"]}
-{"year":"2017","title":"SYSTRAN Purely Neural MT Engines for WMT2017","authors":["Y Deng, J Kim, G Klein, C Kobus, N Segal, C Servan… - WMT 2017, 2017"],"snippet":"... 3.1 Corpora We used the parallel corpora made available for the shared task: Europarl v7, Common Crawl corpus, News Commentary v12 and Rapid corpus of EU press releases. Both English and German texts were preprocessed with standard tokenisation tools. ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=289"]}
-{"year":"2017","title":"Table Identification and Reconstruction in Spreadsheets","authors":["E Koci, M Thiele, O Romero, W Lehner - International Conference on Advanced …, 2017"],"snippet":"... This corpus is of a particular interest, since it provides access to real-world business spreadsheets used in industry. The third corpus is FUSE [3] that contains 249, 376 unique spreadsheets, extracted from Common Crawl 6 . ...","url":["http://link.springer.com/chapter/10.1007/978-3-319-59536-8_33"]}
-{"year":"2017","title":"Tagging Patient Notes With ICD-9 Codes","authors":["S Ayyar"],"snippet":"... For every word we obtained pretrained word vectors from Glove (Common Crawl 840 billion tokens, 2.2 million vocab of dimension size 300)[7]. Since our text consists of translated text from clinical notes, there are several misrepresentations or errors in spellings of words ...","url":["https://web.stanford.edu/class/cs224n/reports/2744196.pdf"]}
-{"year":"2017","title":"Taking into account Inter-sentence Similarity for Update Summarization","authors":["G de Chalendar, O Ferret - Proceedings of the Eighth International Joint …, 2017"],"snippet":"… MCL-GLOVE-ICSISumm. In this run, we used 2.2 million word vectors (300 dimensions) trained with GloVe (Pennington et al., 2014) on the 840 billion tokens from the Common Crawl repository. • MCL-ConceptNet-ICSISumm …","url":["http://www.aclweb.org/anthology/I17-2035"]}
-{"year":"2017","title":"Taxonomy Induction using Hypernym Subsequences","authors":["A Gupta, R Lebret, H Harkous, K Aberer - arXiv preprint arXiv:1704.07626, 2017"],"snippet":"... A prominent ex- ample of such a resource is WebIsA [Seitner et al., 2016], a collection of more than 400 million hypernymy relations for English, extracted from the CommonCrawl web corpus using lexico-syntactic patterns. However ...","url":["https://arxiv.org/pdf/1704.07626"]}
-{"year":"2017","title":"TGIF-QA: Toward Spatio-Temporal Reasoning in Visual Question Answering","authors":["Y Jang, Y Song, Y Yu, Y Kim, G Kim - arXiv preprint arXiv:1704.04497, 2017"],"snippet":"... We then generate multiple choice options for each QA pair, selecting four phrases from our dataset. Specifically, we represent all verbs in our dictionary as a 300D vector using the GloVe word embedding [26] pretrained on the Common Crawl dataset. ...","url":["https://arxiv.org/pdf/1704.04497"]}
-{"year":"2017","title":"The AFRL-MITLL WMT17 Systems: Old, New, Borrowed, BLEU","authors":["J Gwinnup, T Anderson, G Erdmann, K Young, M Kazi… - WMT 2017, 2017"],"snippet":"... 2.1 Data Used We utilized all available data sources provided for the language pairs we participated in, including the Commoncrawl (Smith et ... For Russian we conducted monolingual selection from provided Common Crawl, to match test sets from 2012-2016 (15K lines total). ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=327"]}
-{"year":"2017","title":"The Effect of Translationese on Tuning for Statistical Machine Translation","authors":["S Stymne"],"snippet":"... For training we used Europarl and News commentary, provided by WMT, with a total of over 2M segments for German and French and .77M for Czech. For English→German we used additional data: bilingual Common Crawl (1.5M) and monolingual News (83M). ...","url":["http://www.ep.liu.se/ecp/131/030/ecp17131030.pdf"]}
-{"year":"2017","title":"The Helsinki Neural Machine Translation System","authors":["R Östling, Y Scherrer, J Tiedemann, G Tang… - arXiv preprint arXiv: …, 2017"],"snippet":"... Another common outcome in SMT is the strong impact of language models. We can confirm this once again. Adding a second language model trained on common-crawl data (CC) has a strong influence on translation quality as we can see by the BLEU scores in Table 5. ...","url":["https://arxiv.org/pdf/1708.05942"]}
-{"year":"2017","title":"The HIT-SCIR System for End-to-End Parsing of Universal Dependencies","authors":["W Che, J Guo, Y Wang, B Zheng, H Zhao, Y Liu… - CoNLL 2017, 2017"],"snippet":"... 4.1. 2 Data and Tools We use the provided 100-dimensional multilingual word embeddings5 in our tokenization, POS tagging and parsing models, and use the Wikipedia and CommonCrawl data for training Brown clusters. The number of clusters is set to 256. ...","url":["https://www.aclweb.org/anthology/K/K17/K17-3.pdf#page=64"]}
-{"year":"2017","title":"The Karlsruhe Institute of Technology Systems for the News Translation Task in WMT 2017","authors":["NQ Pham, J Niehues, TL Ha, E Cho, M Sperber… - WMT 2017, 2017"],"snippet":"... 2.1 German↔ English As parallel data for our German↔ English systems, we used Europarl v7 (EPPS), News Commentary v12 (NC), Rapid corpus of EU press releases, Common Crawl corpus, and simulated data. Except ...","url":["http://www.aclweb.org/anthology/W/W17/W17-47.pdf#page=390"]}
-{"year":"2017","title":"The RWTH Aachen University English-German and German-English Machine Translation System for WMT 2017","authors":["JT Peter, A Guta, T Alkhouli, P Bahar, J Rosendahl…"],"snippet":"... Both models are trained on all monolingual corpora, except the commoncrawl corpus, and the target side of the bilingual data (Section 4.2), which sums up to 365.44M sentences and 7230.15M running words, respectively. ...","url":["https://www-i6.informatik.rwth-aachen.de/publications/download/1048/PeterJan-ThorstenGutaAndreasAlkhouliTamerBaharParniaRosendahlJanRossenbachNickGra%E7aMiguelNeyHermann--TheRWTHAachenUniversityEnglish-GermanGerman-EnglishMachineTranslationSystemforWMT2017--2017.pdf"]}
-{"year":"2017","title":"The TALP-UPC Neural Machine Translation System for German/Finnish-English Using the Inverse Direction Model in Rescoring","authors":["C Escolano, MR Costa-jussà, JAR Fonollosa - … of the Second Conference on Machine …, 2017"],"snippet":"... 4.1 Data and Preprocess For the three language pairs that we experimented with, we used all data parallel data available in the evaluation1. For German-English, we used: europarl v.7, news commentary v.12, common crawl and rapid corpus of EU press releases. ...","url":["http://www.aclweb.org/anthology/W17-4725"]}
-{"year":"2017","title":"The UMD Machine Translation Systems at IWSLT 2016: English-to-French Translation of Speech Transcripts","authors":["X Niu, M Carpuat - Proceedings of the ninth International Workshop on …, 2016"],"snippet":"... Corpus # Sentences # Words (en/fr) OpenSubtitles 33.5 M 284.0 M / 268.3 M MultiUN 13.2 M 367.1 M / 432.3 M Common Crawl 3.2 M 81.1 M / 91.3 M Europarl v7 2.0 M 55.7 M / 61.9 M Wikipedia 396 k 9.7 M / 8.7 M TED corpus 207 k 4.5 M / 4.8 M News Commentary v10 199 k ...","url":["http://workshop2016.iwslt.org/downloads/IWSLT_2016_paper_26.pdf"]}
-{"year":"2017","title":"The UMD Neural Machine Translation Systems [at WMT17 Bandit Learning Task","authors":["A Sharaf, S Feng, K Nguyen, K Brantley, H Daumé III - arXiv preprint arXiv: …, 2017"],"snippet":"... sider 40k sentences). Using this monolingual data, we use data selection on a large corpus of parallel out-of-domain data (Europarl, NewsCommentary, CommonCrawl, Rapid) to seed an initial translation model. Overall, the ...","url":["https://arxiv.org/pdf/1708.01318"]}
-{"year":"2017","title":"The University of Edinburgh's Neural MT Systems for WMT17","authors":["R Sennrich, A Birch, A Currey, U Germann, B Haddow… - arXiv preprint arXiv: …, 2017"],"snippet":"... the whole of CzEng 1.6pre (Bojar et al., 2016), plus the latest WMT releases of Europarl, News-commentary and CommonCrawl... We use the following resources from the WMT parallel data: News Commentary v12, Common Crawl, Yandex Corpus and UN Parallel Corpus V1.0 ...","url":["https://arxiv.org/pdf/1708.00726"]}
-{"year":"2017","title":"The University of Edinburgh's systems submission to the MT task at IWSLT","authors":["M Junczys-Dowmunt, A Birch - Proceedings of the ninth International Workshop on …, 2016"],"snippet":"... Commoncrawl [3] 2.3M 3.2M Europarl v7 [4] 1.9M 2.0M Giga Fr-En [3] – 22.5M News Commentary v11 [3] 0.2M 0.2M Opensubtitles 2016 [5] 13.4M 33.5M ... [7] C. Buck, K. Heafield, and B. van Ooyen, “N-gram counts and language models from the common crawl,” in Proceedings ...","url":["http://workshop2016.iwslt.org/downloads/IWSLT_2016_paper_27.pdf"]}
-{"year":"2017","title":"The Web Data Commons Structured Data Extraction","authors":["A Primpeli, R Meusel, C Bizer, H Stuckenschmidt - 2017"],"snippet":"... for the year 2016. The Web Data Commons project extracts structured data from the web corpus provided by Common Crawl, the largest public web corpus, and offers the extracted data for public download. In order to process ...","url":["http://archiv.ub.uni-heidelberg.de/volltextserver/22891/"]}
-{"year":"2017","title":"To Parse or Not to Parse: An Experimental Comparison of RNTNs and CNNs for Sentiment Analysis","authors":["Z Ahmadi, A Stier, M Skowron, S Kramer"],"snippet":"... On other datasets, we use the model trained on the web data from Common Crawl which contains a case-sensitive vocabulary of size 2.2 million. In all the experiments, the size of the word vector, the minibatch and the epochs were set to 25, 20 and 100, respectively. ...","url":["http://ceur-ws.org/Vol-1874/paper_1.pdf"]}
-{"year":"2017","title":"TO THE METHODOLOGY OF CORPUS CONSTRUCTION FOR MACHINE LEARNING:“TAIGA” SYNTAX TREE CORPUS AND PARSER","authors":["TO Shavrina, O Shapovalova - КОРПУСНАЯ ЛИНГВИСТИКА–2017"],"snippet":"… For Russian language, large collections of web corpora are assembled—projects like RuTenTen and Aranea Russicum, which are not available for downloading, unlike resources based on Common Crawl, but all these corpora are crawled from an unbalanced set of links and …","url":["https://dspace.spbu.ru/bitstream/11701/8786/1/%D0%9A%D0%BE%D1%80%D0%BF%D1%83%D1%81%D0%BD%D0%B0%D1%8F%20%D0%BB%D0%B8%D0%BD%D0%B3%D0%B2%D0%B8%D1%81%D1%82%D0%B8%D0%BA%D0%B0-2017%20%28%D1%82%D1%80%D1%83%D0%B4%D1%8B%20%D0%BC%D0%B5%D0%B6%D0%B4.%20%D0%BA%D0%BE%D0%BD%D1%84%D0%B5%D1%80.%29.pdf#page=78"]}
-{"year":"2017","title":"Topics in Data Science/Өгөгдлийн шинжлэх ухаан","authors":["R Womack - 2017"],"snippet":"Page 1. Topics in Data Science / Өгөгдлийн шинжлэх ухаан Rutgers University has made this article freely available. Please share how this access benefits you. Your story matters. [https://rucore.libraries.rutgers.edu/rutgers-lib/52378/story/] …","url":["https://rucore.libraries.rutgers.edu/rutgers-lib/52378/PDF/1/"]}
-{"year":"2017","title":"Toward intrusion detection using belief decision trees for big data","authors":["I Boukhris, Z Elouedi, M Ajabi - Knowledge and Information Systems, 2017"],"snippet":"Page 1. Knowl Inf Syst DOI 10.1007/s10115-017-1034-4 REGULAR PAPER Toward intrusion detection using belief decision trees for big data Imen Boukhris1 · Zied Elouedi1 · Mariem Ajabi1 Received: 3 December 2015 / Accepted ...","url":["http://link.springer.com/article/10.1007/s10115-017-1034-4"]}
-{"year":"2017","title":"Towards Accurate Duplicate Bug Retrieval Using Deep Learning Techniques","authors":["J Deshmukh, S Podder, S Sengupta, N Dubash - Software Maintenance and …, 2017"],"snippet":"… Each word in the dictionary was then mapped to its corresponding embedding. We experimented with both GloVe vectors trained3 on Common Crawl dataset as well as Word2Vec vectors trained4 on Google news dataset. We …","url":["http://ieeexplore.ieee.org/abstract/document/8094414/"]}
-{"year":"2017","title":"Towards Automatic Identification of Fake News: Headline-Article Stance Detection with LSTM Attention Models","authors":["S Chopra, S Jain, JM Sholar - 2017"],"snippet":"... 3 Page 4. of Wikipedia and Common Crawl. We further created a randomly initialized UNK vector of zeros, for words that were not found in the GloVe set. 5.4 LSTM Attention Architectures 5.4.1 Conditionally Encoded (CE) LSTMs ...","url":["https://pdfs.semanticscholar.org/eecc/5781c826a0af8229b8a24a6fca3d3e48b0fa.pdf"]}
-{"year":"2017","title":"Towards Automatically Evaluating Security Risks and Providing Cyber Intelligence","authors":["X Liao - 2017"],"snippet":"Page 1. TOWARDS AUTOMATICALLY EVALUATING SECURITY RISKS AND PROVIDING CYBER INTELLIGENCE A Thesis Presented to The Academic Faculty by Xiaojing Liao In Partial Fulfillment of the Requirements for ...","url":["https://smartech.gatech.edu/bitstream/handle/1853/58679/LIAO-DISSERTATION-2017.pdf?sequence=1&isAllowed=y"]}
-{"year":"2017","title":"Towards Document-Level Neural Machine Translation","authors":["L Miculicich Werlen - 2017"],"snippet":"Page 1. TROPE R HCRAESE R PAID I TOWARDS DOCUMENT-LEVEL NEURAL MACHINE TRANSLATION Lesly Miculicich Werlen Idiap-RR-25-2017 SEPTEMBER 2017 Centre du Parc, Rue Marconi 19, PO Box 592, CH ...","url":["https://infoscience.epfl.ch/record/231129/files/MiculicichWerlen_Idiap-RR-25-2017.pdf"]}
-{"year":"2017","title":"Towards Semantic Query Segmentation","authors":["A Kale, T Taula, S Hewavitharana, A Srivastava - arXiv preprint arXiv:1707.07835, 2017"],"snippet":"... estimators. This process was repeated with pretrained GloVe vectors on common crawl [14] and facebook fasttext [2] pretrained model over Wikipedia corpus with 2.5M word vocabulary. 2 shows the experiment results. We ...","url":["https://arxiv.org/pdf/1707.07835"]}
-{"year":"2017","title":"Towards the ImageNet-CNN of NLP: Pretraining Sentence Encoders with Machine Translation","authors":["B McCann, J Bradbury, C Xiong, R Socher - Advances in Neural Information …, 2017"],"snippet":"… When training an MT-LSTM, we used fixed 300-dimensional word vectors. We used the CommonCrawl-840B GloVe model for English word vectors, which were completely fixed during training, so that the MT-LSTM had to learn how to use the pretrained vectors for translation …","url":["http://papers.nips.cc/paper/7209-towards-the-imagenet-cnn-of-nlp-pretraining-sentence-encoders-with-machine-translation.pdf"]}
-{"year":"2017","title":"TraininG towards a society of data-saVvy inforMation prOfessionals to enable open leadership INnovation","authors":["T Blume, F Böschen, L Galke, A Saleh, A Scherp - 2017"],"snippet":"Page 1. Deliverable 3.1: Technologies for MOVING data processing and visualisation v1.0 Till Blume, Falk Böschen, Lukas Galke, Ahmed Saleh, Ansgar Scherp, Matthias Schulte-Althoff/ZBW Chrysa Collyda, Vasileios Mezaris, Alexandros Pournaras, Christos Tzelepis/CERTH ...","url":["http://moving-project.eu/wp-content/uploads/2017/04/moving_d3.1_v1.0.pdf"]}
-{"year":"2017","title":"Translation Quality and Productivity: A Study on Rich Morphology Languages","authors":["L Specia, K Harris, F Blain, A Burchardt, V Macketanz…"],"snippet":"... This process resulted in: • EN–DE: Over 20 million generic and in-domain sentence pairs obtained by merging the datasets available in the OPUS (Tiedemann, 2012), TAUS, WMT and JRC 3 repositories (eg Europarl, CDEP, CommonCrawl, etc.); ...","url":["https://fredblain.org/papers/pdf/specia_et_al_2017_translation_quality_and_productivity.pdf"]}
-{"year":"2017","title":"Translation Quality Estimation Using only bilingual Corpora","authors":["L Liu, A Fujita, M Utiyama, A Finch, E Sumita - IEEE/ACM Transactions on Audio, …, 2017"],"snippet":"... languages. As the bilingual corpora for conducting M2LE training, we employed Europarl and Common Crawl provided by WMT13 for the WMT15 and WMT14 tasks and a Japanese–Chinese bilingual corpus [9] for the JA2ZH task. ...","url":["http://ieeexplore.ieee.org/abstract/document/7949019/"]}
-{"year":"2017","title":"TSP: Learning Task-Specific Pivots for Unsupervised Domain Adaptation","authors":["X Cui, F Coenen, D Bollegala"],"snippet":"... We use the publicly available D = 300 dimensional GloVe4 (trained using 42B tokens from the Common Crawl) and CBOW5 (trained using 100B tokens from Google News) embeddings as the word representations required by TSP. ...","url":["https://cgi.csc.liv.ac.uk/~danushka/papers/Xia_ECML_2017.pdf"]}
-{"year":"2017","title":"Two-Stage Synthesis Networks for Transfer Learning in Machine Comprehension","authors":["D Golub, PS Huang, X He, L Deng - arXiv preprint arXiv:1706.09789, 2017"],"snippet":"... We initialize word-embeddings for the BIDAF model, answer synthesis module, and question synthesis module with 300-dimensional-GloVe vectors (Pennington et al., 2014) trained on the 840B Common Crawl corpus. We set all embeddings of unknown word tokens to zero. ...","url":["https://arxiv.org/pdf/1706.09789"]}
-{"year":"2017","title":"Two-Step MT: Predicting Target Morphology","authors":["F Burlot, E Knyazeva, T Lavergne, F Yvon - 2016"],"snippet":"... from TED training set Full TED set (117k) + QED (242k) + europarl (885k) + news-commentary (1M) Monolingual data (various subsets ranging from 5M to 200M): Target side of the biggest parallel corpus Czeng-1.6-pre subtitles news corpora (WMT'16) common-crawl (WMT'16 ...","url":["http://workshop2016.iwslt.org/downloads/IWSLT16_Burlot.pdf"]}
-{"year":"2017","title":"Unbounded cache model for online language modeling with open vocabulary","authors":["E Grave, M Cisse, A Joulin - arXiv preprint arXiv:1711.02604, 2017"],"snippet":"... In the following, we refer to this dataset as commentary. • Common Crawl is a text dataset collected from diverse web sources. The dataset is shuffled at the sentence level. ... [9] C. Buck, K. Heafield, and B. van Ooyen. N-gram counts and language models from the common crawl...","url":["https://arxiv.org/pdf/1711.02604"]}
-{"year":"2017","title":"Understanding and Predicting the Usefulness of Yelp Reviews","authors":["DZ Liu"],"snippet":"... I concatenate output from both RNNs to make the final prediction. (figure 1) [1] https://www.yelp. com/dataset_challenge [2] Common Crawl (42B tokens, 1.9M vocab, uncased, 300d vectors): glove.42B.300d.zip from http://nlp.stanford.edu/projects/glove/ Page 4. ...","url":["https://web.stanford.edu/class/cs224n/reports/2760995.pdf"]}
-{"year":"2017","title":"Understanding Regional Context of World Wide Web using Common Crawl Corpus","authors":["MA Mehmood, HM Shafiq, A Waheed"],"snippet":"Abstract—The World Wide Web has emerged as the most important and essential tool for the society. Today, people heavily rely on rich resources available in the web for communication, business, maps, and social networking etc. In addition, people seek web","url":["https://www.researchgate.net/profile/Amir_Mehmood/publication/321489200_Understanding_Regional_Context_of_World_Wide_Web_using_Common_Crawl_Corpus/links/5a251abaaca2727dd87e780a/Understanding-Regional-Context-of-World-Wide-Web-using-Common-Crawl-Corpus.pdf"]}
-{"year":"2017","title":"Understanding Spreadsheet Evolution in Practice","authors":["L Xu - Software Maintenance and Evolution (ICSME), 2017 …, 2017"],"snippet":"… IEEE International Conference on Software Engineering (ICSE), 2015, pp. 7– 16. [28] “Common crawl data on AWS.” [Online]. Available: http://aws.amazon.com/datasets/ 41740. [29] C. Chambers, M. Erwig, and M. Luckey, “SheetDiff …","url":["http://ieeexplore.ieee.org/abstract/document/8094479/"]}
-{"year":"2017","title":"Unsupervised Neural Machine Translation","authors":["M Artetxe, G Labaka, E Agirre, K Cho - arXiv preprint arXiv:1710.11041, 2017"],"snippet":"... For that purpose, we used the combination of all parallel corpora provided at WMT 2014, which comprise Europarl, Common Crawl and News Commentary for both language pairs plus the UN and the Gigaword corpus for FrenchEnglish. ...","url":["https://arxiv.org/pdf/1710.11041"]}
-{"year":"2017","title":"Using Distributional Semantics for Automatic Taxonomy Induction","authors":["B Zafar, M Cochez, U Qamar"],"snippet":"... system. They used general and domain specific corpora such as GigaWord, ukWac etc. and the common crawl to extract lexico-syntactic patterns. Additionally, they applied pruning methods to refine the generated taxonomy. ...","url":["http://users.jyu.fi/~miselico/papers/distributional-semantics-taxonomy.pdf"]}
-{"year":"2017","title":"Using images to improve machine-translating e-commerce product listings","authors":["I Calixto, D Stein, E Matusov, P Lohar, S Castilho… - EACL 2017, 2017"],"snippet":"... Table 2 we show the number of running words as well as the perplexity scores obtained with LMs trained on three sets of different German corpora: the Multi30k, eBay's in-domain data and a concatenation of the WMT 20152 Europarl (Koehn, 2005), Common Crawl and News ...","url":["https://www.aclweb.org/anthology/E/E17/E17-2.pdf#page=669"]}
-{"year":"2017","title":"Using Recurrent Neural Network to Predict The Usefulness of Yelp Reviews","authors":["DZ Liu, G Singh"],"snippet":"... The frequency of alternation is a hyper-parameter Figure 2: MTL RNN structure with detailed input and output description [2] Common Crawl (42B tokens, 1.9M vocab, uncased, 300d vectors): glove.42B.300d.zip from http://nlp.stanford.edu/projects/glove/ Page 4. ...","url":["https://web.stanford.edu/class/cs221/2017/restricted/p-final/dzliu/final.pdf"]}
-{"year":"2017","title":"UWat-Emote at EmoInt-2017: Emotion Intensity Detection using Affect Clues, Sentiment Polarity and Word Embeddings","authors":["V John, O Vechtomova - EMNLP 2017, 2017"],"snippet":"... GloVe Model-Tweets (GV-T), Wikipedia + Gigaword (GV-WG), Common Crawl 42B tokens (GV-CC1), Common Crawl 840B tokens (GV-CC2): GloVe is similar to Word2Vec, in that it obtains dense vector representations of words. ...","url":["http://www.aclweb.org/anthology/W/W17/W17-52.pdf#page=265"]}
-{"year":"2017","title":"Variable length word encodings for neural translation models","authors":["J Gao"],"snippet":"Page 1. Variable length word encodings for neural translation models Jiameng Gao Department of Engineering University of Cambridge This dissertation is submitted for the degree of Master of Philosophy Peterhouse August 11, 2016 Page 2. Page 3. Page 4. Page 5. ...","url":["http://www.mlsalt.eng.cam.ac.uk/foswiki/pub/Main/CurrentMPhils/Jiameng_Gao_8224881_assignsubmission_file_J_Gao_MPhil_dissertation.pdf"]}
-{"year":"2017","title":"VecShare: A Framework for Sharing Word Representation Vectors","authors":["J Fernandez, Z Yu, D Downey"],"snippet":"... we utilize three sets of GloVe embeddings (Pennington et al., 2014): wik+, 100-dimensional embeddings trained on six billion tokens of Wikipedia and the Gigaword corpus; web, 300-dimensional embeddings trained on 42 billion tokens of the Common Crawl Web dataset ...","url":["http://www.cs.northwestern.edu/~ddowney/publications/vecshare_fernandez_2017.pdf"]}
-{"year":"2017","title":"Vector Space Representations in Information Retrieval","authors":["V Novotný"],"snippet":"Page 1. Masaryk University Faculty of Informatics Vector Space Representations in Information Retrieval Master's Thesis Vít Novotný Brno, Fall 2017 Page 2. Page 3. Masaryk University Faculty of Informatics Vector Space Representations in Information Retrieval Master's Thesis …","url":["https://is.muni.cz/th/409729/fi_m/main.pdf"]}
-{"year":"2017","title":"Visual Exploration of High-Dimensional Spaces Through Identification, Summarization, and Interpretation of Two-Dimensional Projections","authors":["S Liu - 2017"],"snippet":"Visual Exploration of High-Dimensional Spaces Through Identification, Summarization, and Interpretation of Two-Dimensional Projections. Abstract. With the ever-increasing amount of available computing resources and sensing ...","url":["http://search.proquest.com/openview/521292ce267e4e2b78aa24b8452c5a8d/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2017","title":"Visually Grounded Word Embeddings and Richer Visual Features for Improving Multimodal Neural Machine Translation","authors":["JB Delbrouck, S Dupont, O Seddati - arXiv preprint arXiv:1707.01009, 2017"],"snippet":"... to. As previously mentioned, the textual representation lwi is obtained with the word embeddings algorithm Glove. We use the pre-trained model on the Common Crawl corpus consisting of 840B tokens and a 2.2M words. The ...","url":["https://arxiv.org/pdf/1707.01009"]}
-{"year":"2017","title":"Web-scale profiling of semantic annotations in HTML pages","authors":["R Meusel - 2017"],"snippet":"... In 2012, the Common Crawl Foundation (CC)8 started to continuously release crawled web corpora of a decent size and made them publicly available. Each of the corpora contains several tera-bytes of compressed HTML pages. ...","url":["https://ub-madoc.bib.uni-mannheim.de/41884/1/thesis_final_rm_20170322-1.pdf"]}
-{"year":"2017","title":"Web-Scale Web Table to Knowledge Base Matching","authors":["D Ritze - 2017"],"snippet":"… 43 4.2.1 Common Crawl … Page 20. 12 CHAPTER 1. INTRODUCTION 1.4 Published Work Parts of the work presented in this thesis have been published previously: • The extraction of the WDC Web Table Corpus from the Common Crawl …","url":["https://ub-madoc.bib.uni-mannheim.de/43123/1/thesis.pdf"]}
-{"year":"2017","title":"What's good for the goose is good for the GANder","authors":["C Hung, B Corcoran"],"snippet":"... To reduce the percentage of un- known words, we additionally brought down the size of our vocabulary to contain only the 10k most commonly used words in the training set; and used GloVe vectors (Pennington et al., 2014), pretrained on Common Crawl (having around 42B ...","url":["https://web.stanford.edu/class/cs224n/reports/2761035.pdf"]}
-{"year":"2017","title":"Word Embeddings for Practical Information Retrieval","authors":["L Galke, A Saleh, A Scherp - INFORMATIK 2017, 2017"],"snippet":"... 2 zbw.eu/stw 3 A dataset of crawled web data from https://commoncrawl.org/ Word Embeddings for Similarity Scoring in Practical Information Retrieval 2161 Page 8. i “proceedings” — 2017/8/24 — 12:20 — page 2162 — #2162 i i i ...","url":["https://dl.gi.de/bitstream/handle/20.500.12116/3987/B29-2.pdf?sequence=1"]}
-{"year":"2017","title":"Word Embeddings Quantify 100 Years of Gender and Ethnic Stereotypes","authors":["N Garg, L Schiebinger, D Jurafsky, J Zou - arXiv preprint arXiv:1711.08412, 2017"],"snippet":"… nearly identical correlation. We further validate this association using different embeddings trained on Wikipedia and Common Crawl texts instead of Google News; see Appendix Section B.1 for details. Google News embedding …","url":["https://arxiv.org/pdf/1711.08412"]}
-{"year":"2017","title":"Word Re-Embedding via Manifold Dimensionality Retention","authors":["S Hasan, E Curry - Proceedings of the 2017 Conference on Empirical …, 2017"],"snippet":"... Original Embedding Spaces. The original word embeddings used are pre-trained GloVe models: Wikipedia 2014 + Gigaword 5 (6B tokens, 400K vocab, 50d, 100d, 200d, & 300d vectors), and Common Crawl (42B tokens, 1.9M vocab, 300d vectors) (Pennington et al., 2014b). ...","url":["http://www.aclweb.org/anthology/D17-1033"]}
-{"year":"2017","title":"Word vectors, reuse, and replicability: Towards a community repository of large-text resources","authors":["M Fares, A Kutuzov, S Oepen, E Velldal"],"snippet":"... Moreover, with an ac- curacy of 83.08 for the semantic analogies, the GloVe model trained on the lemmatized version of Wikipedia outperforms the GloVe model trained on 42 billion tokens of web data from the Common Crawl reported in (Pennington et al., 2014), which at an ...","url":["http://www.ep.liu.se/ecp/131/037/ecp17131037.pdf"]}
-{"year":"2018","title":"“I think it might help if we multiply, and not add”: Detecting Indirectness in Conversation","authors":["P Goel, Y Matsuyama, M Madaio, J Cassell"],"snippet":"… We tried various available pre-trained models like Twitter word2vec [14] trained on 400 million Twitter tweets, GloVe representations [34] trained on Wikipedia articles (called GloVe wiki) and web content crawled via …","url":["http://articulab.hcii.cs.cmu.edu/wordpress/wp-content/uploads/2018/04/Goel-IWSDS2018_camera-ready_13Mar.pdf"]}
-{"year":"2018","title":"A Bi-Encoder LSTM Model for Learning Unstructured Dialogs","authors":["D Shekhar - 2018"],"snippet":"Page 1. University of Denver Digital Commons @ DU Electronic Theses and Dissertations Graduate Studies 8-1-2018 A Bi-Encoder LSTM Model for Learning Unstructured Dialogs Diwanshu Shekhar University of Denver Follow …","url":["https://digitalcommons.du.edu/cgi/viewcontent.cgi?article=2508&context=etd"]}
-{"year":"2018","title":"A Bidirectional LSTM-CRF Network with Subword Representations, Character Convolutions and Morphosyntactic Features for Named Entity Recognition in Polish","authors":["M Piotrowski, W Janowski, P Pezik - Proceedings ofthePolEval2018Workshop"],"snippet":"… Chiu and Nichols 2015, Ma and Hovy 2016). Secondly, the input token sequences are matched against 300-dimensional FastText subword embeddings vectors derived from a Common Crawl dump of Polish texts (Grave et al …","url":["http://poleval.pl/files/poleval2018.pdf#page=93"]}
-{"year":"2018","title":"A Case Study of Closed-Domain Response Suggestion with Limited Training Data","authors":["L Galke, G Gerstenkorn, A Scherp"],"snippet":"… and return the known answer to this context. To compute the word vector centroids, we use German fastText [16] word vectors trained on CommonCrawl and Wikipedia6 [17]. For the experiment on English utterances, we use …","url":["http://www.lpag.de/p/response_suggestion.pdf"]}
-{"year":"2018","title":"A Cognitive Assistant for Risk Identification and Modeling","authors":["D Subramanian, D Bhattachrajya, RR Torrado…"],"snippet":"… politics/government or alternative ways to describe the same risk. Specifically, we use Glove [17] trained on a Common Crawl corpus that has 1.9 million vocabulary words embedded in a 300-dimensional vector space. Table II …","url":["http://ieeexplore.ieee.org/iel7/8241556/8257893/08258091.pdf"]}
-{"year":"2018","title":"A Comparative Analysis of Content-based Geolocation in Blogs and Tweets","authors":["K Pappas, M Azab, R Mihalcea - arXiv preprint arXiv:1811.07497, 2018"],"snippet":"… Page 13. We also experiment with a word embedding representation, where we use word vectors obtained with GloVe [47] trained on a Common Crawl and a Twitter dataset respectively, which are added up and averaged to create a word …","url":["https://arxiv.org/pdf/1811.07497"]}
-{"year":"2018","title":"A Comparative Study of Embedding Models in Predicting the Compositionality of Multiword Expressions","authors":["N Nandakumar, B Salehi, T Baldwin - Australasian Language Technology Association …"],"snippet":"… The two character-level embedding models we experiment with are fastText (Bojanowski et al., 2017) and ELMo (Peters et al., 2018), as detailed below. fastText We used the 300-dimensional model pre-trained on Common Crawl and Wikipedia us- ing CBOW …","url":["http://alta2018.alta.asn.au/alta2018-draft-proceedings.pdf#page=81"]}
-{"year":"2018","title":"A Comparison of Machine Translation Paradigms for Use in Black-Box Fuzzy-Match Repair","authors":["R Knowles, JE Ortega, P Koehn"],"snippet":"… We report scores with a beam size of 12. 4.3 Phrase-Based SMT (Moses) We use Moses (Koehn et al., 2007) to train our phrasebased statistical MT (SMT) system using the same parallel text as the NMT model, with the addition of Common Crawl,10 for phrase extraction …","url":["https://www.researchgate.net/profile/John_Ortega3/publication/324007613_A_Comparison_of_Machine_Translation_Paradigms_for_Use_in_Black-Box_Fuzzy-Match_Repair/links/5ab8cd010f7e9b68ef51fa23/A-Comparison-of-Machine-Translation-Paradigms-for-Use-in-Black-Box-Fuzzy-Match-Repair.pdf"]}
-{"year":"2018","title":"A Comprehensive Course on Big Data for Undergraduate Students","authors":["JA Shamsi, SZ ul Hassan, N Bawany, N Shoaib"],"snippet":"… ' TABLE V PROJECTS S. No Project Title Big Data Analytics 1 Performance Analysis on EspnCricinfo data 2 YouTube Data Analysis Using Hadoop 3 Analysis of emails in Amazon Common Crawl Dataset using MapReduce …","url":["https://grid.cs.gsu.edu/~tcpp/curriculum/sites/default/files/paper%201_0.pdf"]}
-{"year":"2018","title":"A course on big data analytics","authors":["J Eckroth - Journal of Parallel and Distributed Computing, 2018"],"snippet":"This report details a course on big data analytics designed for undergraduate junior and senior computer science students. The course is heavily focused on proj.","url":["https://www.sciencedirect.com/science/article/pii/S0743731518300972"]}
-{"year":"2018","title":"A database of German definitory contexts from selected web sources.","authors":["A Barbaresi, L Lemnitzer, A Geyken - LREC, 2018"],"snippet":"… specific datasets, eg instructional texts compiled for teaching purposes (Borg, 2009); large encyclopedic re- sources such as Wikipedia (Kovár et al., 2016); or generalpurpose web corpora (Navigli et al., 2010); unfiltered …","url":["https://hal.archives-ouvertes.fr/hal-01798704/document"]}
-{"year":"2018","title":"A Dataset and Reranking Method for Multimodal MT of User-Generated Image Captions","authors":["S Schamoni, J Hitschler, S Riezler"],"snippet":"… pairs: French-English We trained our French-English translation system on data made available for the WMT 2015 translation shared task.7 We used the Europarl, News Commentary and Common Crawl data for training. Russian …","url":["http://www.cl.uni-heidelberg.de/statnlpgroup/papers/AMTA2018a.pdf"]}
-{"year":"2018","title":"A Dataset for Web-scale Knowledge Base Population","authors":["M Glass, A Gliozzo"],"snippet":"… Obtain the list of WARC paths from the Common Crawl website – Download the WARC files hosted … 8 http://commoncrawl.org 9 https://github.com/optimaize/language-detector Page 10. 4.2 DBpedia DBpedia [1] is a mature knowledge base built from the infoboxes of Wikipedia …","url":["https://2018.eswc-conferences.org/wp-content/uploads/2018/02/ESWC2018_paper_173.pdf"]}
-{"year":"2018","title":"A Deep Learning Approach for Extracting Attributes of ABAC Policies","authors":["M Alohaly, H Takabi, E Blanco - Proceedings of the 23nd ACM on Symposium on …, 2018"],"snippet":"… IBM 2004. Course Registration Requirements. (2004). 3. 2017. Common Crawl. (September 2017). http://commoncrawl.org/. 4. Ryma Abassi, Michael Rusinowitch, Florent Jacquemard, and Sihem Guemara El Fatmi. 2010. XML …","url":["https://dl.acm.org/citation.cfm?id=3205984"]}
-{"year":"2018","title":"A Deep Learning Architecture for De-identification of Patient Notes: Implementation and Evaluation","authors":["K Khin, P Burckhardt, R Padman - arXiv preprint arXiv:1810.01570, 2018"],"snippet":"… embeddings. The traditional word embeddings use the latest GloVe 3 [13] pre-trained word vectors that were trained on the Common Crawl with about 840 billion tokens. For every token input, ti,j,k, the GloVe 6 Page 7. system …","url":["https://arxiv.org/pdf/1810.01570"]}
-{"year":"2018","title":"A Discriminative Latent-Variable Model for Bilingual Lexicon Induction","authors":["S Ruder, R Cotterell, Y Kementchedjhieva, A Søgaard - arXiv preprint arXiv …, 2018"],"snippet":"Page 1. A Discriminative Latent-Variable Model for Bilingual Lexicon Induction Sebastian Ruder @,H∗ Ryan Cotterell S,P∗ Yova Kementchedjhieva Z Anders Søgaard Z @ Insight Research Centre, National University of Ireland …","url":["https://arxiv.org/pdf/1808.09334"]}
-{"year":"2018","title":"A Document Descriptor using Covariance of Word Vectors","authors":["M Torki"],"snippet":"… We tested the available different dimensionality 100, 200 and 300. We also used the 300 dimensions GloVe model that used commoncrawl with 42 Billion tokens We call the last one Lrg. This model provides word vectors of 300 dimensions for each word …","url":["https://www.researchgate.net/profile/Marwan_Torki/publication/325678643_A_Document_Descriptor_using_Covariance_of_Word_Vectors/links/5b1d9b5345851587f29f58a2/A-Document-Descriptor-using-Covariance-of-Word-Vectors.pdf"]}
-{"year":"2018","title":"A Domain is only as Good as its Buddies: Detecting Stealthy Malicious Domains via Graph Inference","authors":["IM Khalil, B Guan, M Nabeel, T Yu - 2018"],"snippet":"… Thales scans DNS using a set of seed domain list compiled from multiple sources, including public blacklists (eg [19, 40, 47]), the Alexa list [13], the Common Crawl dataset [3], the domain feed from an undisclosed security","url":["https://www.researchgate.net/profile/Issa_Khalil/publication/323393061_A_Domain_is_only_as_Good_as_its_Buddies_Detecting_Stealthy_Malicious_Domains_via_Graph_Inference/links/5a93a507a6fdccecff05aa6f/A-Domain-is-only-as-Good-as-its-Buddies-Detecting-Stealthy-Malicious-Domains-via-Graph-Inference.pdf"]}
-{"year":"2018","title":"A flexible space-time tradeoff on hybrid index with bicriteria optimization","authors":["X Song, Y Yang, Y Jiang - Tsinghua Science and Technology, 2019"],"snippet":"… sorting. Page 3. 108 Tsinghua Science and Technology, February 2019, 24(1): 106–122 (4) We execute a detailed experimental evaluation on two realistic datasets, GOV2 and Common Crawl, with AOL query log. Analysis shows …","url":["https://ieeexplore.ieee.org/iel7/5971803/8526498/08526502.pdf"]}
-{"year":"2018","title":"A Framework to Discover Significant Product Aspects from E-commerce Product Reviews","authors":["S Indrakanti, G Singh - 2018"],"snippet":"… ranking. 3.4.3 Synonym-based Clustering. We use 300-dimensional word embeddings for one million vocabulary entries trained on the Common Crawl corpus using the GloVe algorithm [18] to compute word similarities. Synonym …","url":["https://sigir-ecom.github.io/ecom18Papers/paper19.pdf"]}
-{"year":"2018","title":"A Genetic Algorithm for Combining Visual and Textual Embeddings Evaluated on Attribute Recognition","authors":["R Li, G Collell, MF Moens"],"snippet":"… Following Collell and Moens (2016), we employ 300dimensional GloVe vectors (Pennington et al., 2014) trained on the largest available corpus (840B tokens and a 2.2M words vocabulary from Common Crawl corpus) …","url":["http://ceur-ws.org/Vol-2226/paper7.pdf"]}
-{"year":"2018","title":"A Geo-Tagging Framework for Address Extraction from Web Pages","authors":["J Efremova, I Endres, I Vidas, O Melnik - Industrial Conference on Data Mining, 2018"],"snippet":"… Common Crawl is a public corpus, mostly stored on Amazon Web Services 3 . A subset of the CommonCrawl dataset has schema information in the microdata format with manual annotation of the main content such as …","url":["https://link.springer.com/chapter/10.1007/978-3-319-95786-9_22"]}
-{"year":"2018","title":"A Graph-to-Sequence Model for AMR-to-Text Generation","authors":["L Song, Y Zhang, Z Wang, D Gildea - arXiv preprint arXiv:1805.02473, 2018"],"snippet":"… 5.2 Settings We extract a vocabulary from the training set, which is shared by both the encoder and the de- coder. The word embeddings are initialized from Glove pretrained word embeddings (Pennington et al., 2014) on …","url":["https://arxiv.org/pdf/1805.02473"]}
-{"year":"2018","title":"A Helping Hand: Transfer Learning for Deep Sentiment Analysis","authors":["X Dong, G Melo - Proceedings of the 56th Annual Meeting of the …, 2018"],"snippet":"… en es de ru α 0.0004 0.0008 0.003 0.003 cs it ja α 0.003 0.003 0.003 Common Crawl data1, while for other languages, we rely on the Facebook fastText Wikipedia em- beddings (Bojanowski et al., 2016) as input representations. All of these are 300-dimensional …","url":["http://www.aclweb.org/anthology/P18-1235"]}
-{"year":"2018","title":"A Hybrid Deep Learning System for Machine Comprehension","authors":["G Wu"],"snippet":"… and therefore can suffer from the out-of-vocabulary words. Thus, I used glove840B300d Common Crawl as the word embedding database during my training. e Apply dropout and regularization: dropout and regularization help …","url":["http://web.stanford.edu/class/cs224n/reports/6879317.pdf"]}
-{"year":"2018","title":"A Machine Learning Approach to Correlate Emotional Intelligence and Happiness Based on Twitter Data","authors":["SS Shravani, NK Jha, R Guha - 2018"],"snippet":"… The corpus in this case was the common crawl dataset [Mikolov, 2017] and the word vectors were obtained using fast text algorithm of Facebook AI research (FAIR) which gave us around 2 million word vectors. The data set …","url":["http://hci2018.bcs.org/prelim_proceedings/papers/Work-in-Progress%20Track/BHCI-2018_paper_115.pdf"]}
-{"year":"2018","title":"A Multi-layer LSTM-based Approach for Robot Command Interaction Modeling","authors":["M Mensio, E Bastianelli, I Tiddi, G Rizzo - arXiv preprint arXiv:1811.05242, 2018"],"snippet":"… for word representation,” in Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP), 2014, pp. 1532–1543. [23] (2012) Common crawl. [Online]. Available: http://commoncrawl.org/","url":["https://arxiv.org/pdf/1811.05242"]}
-{"year":"2018","title":"A Multi-task Ensemble Framework for Emotion, Sentiment and Intensity Prediction","authors":["MS Akhtar, D Ghosal, A Ekbal, P Bhattacharyya - arXiv preprint arXiv:1808.01216, 2018"],"snippet":"… Figure 1: Proposed Multi-task framework. 3.1 Deep Learning Models We employ the architecture of Figure 1a to train and tune all the deep learning models using pretrained GloVe (common crawl 840 billion) word embeddings (Pennington et al., 2014) …","url":["https://arxiv.org/pdf/1808.01216"]}
-{"year":"2018","title":"A Multilayer Convolutional Encoder-Decoder Neural Network for Grammatical Error Correction","authors":["S Chollampatt, HT Ng - arXiv preprint arXiv:1801.08831, 2018"],"snippet":"… Grundkiewicz 2016) employs a word-level SMT approach with task-specific features and a web-scale LM trained on the Common Crawl corpus … all subsidiary models that make use of additional English corpora such as the word-class LM and the web-scale Common Crawl LM …","url":["https://arxiv.org/pdf/1801.08831"]}
-{"year":"2018","title":"A Multimodal Assessment Framework for Integrating Student Writing and Drawing in Elementary Science Learning","authors":["PAM Smith, S Leeman-Munk, A Shelton, BW Mott… - IEEE Transactions on …, 2018"],"snippet":"Page 1. 1939-1382 (c) 2018 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["http://ieeexplore.ieee.org/abstract/document/8274912/"]}
-{"year":"2018","title":"A novel approach for phishing emails real time classifica-tion using k-means algorithm","authors":["V Mhaske-Dhamdhere, S Vanjale - International Journal of Engineering & …, 2017"],"snippet":"… to get to the two techniques utilizes RF (Random Forest) and LSTM (a long/here and now memory mastermind on datasets phish tank and Common Crawl, which gives result as precision rate of 93.5% and 98.7% .RF and LSTM utilizes 14 highlights of lexical and quantifiable …","url":["https://forum.sciencepubco.com/index.php/ijet/article/download/9018/3069"]}
-{"year":"2018","title":"A novel approach for phishing emails real time classification using k-means algorithm","authors":["V Mhaske-Dhamdhere, S Vanjale - International Journal of Engineering & …, 2018"],"snippet":"… to get to the two techniques utilizes RF (Random Forest) and LSTM (a long/here and now memory mastermind on datasets phish tank and Common Crawl, which gives result as precision rate of 93.5% and 98.7% .RF and …","url":["http://bvucoepune.edu.in/wp-content/uploads/2018/BVUCOEP-DATA/Research_Publications/2017_18/168.pdf"]}
-{"year":"2018","title":"A Pragmatic Guide to Geoparsing Evaluation","authors":["M Gritta, MT Pilehvar, N Collier - arXiv preprint arXiv:1810.12368, 2018"],"snippet":"… It 11 https://cloud.google.com/natural-language/ 12 https://spacy.io/usage/linguistic-features 13 https://github.com/jiesutd/NCRFpp 14 Common Crawl 42B - https://nlp.stanford.edu/ projects/glove/ Page 17. A Pragmatic Guide to Geoparsing Evaluation 17 …","url":["https://arxiv.org/pdf/1810.12368"]}
-{"year":"2018","title":"A QUANTITATIVE ANALYSIS OF THE USE OF MICRODATA FOR SEMANTIC ANNOTATIONS ON EDUCATIONAL RESOURCES","authors":["R NAVARRETE, S LUJÁN-MORA - Journal of Web Engineering, 2018"],"snippet":"… This quantitative analysis was conducted on datasets extracted from the Common Crawl Corpus [17], as it is the largest corpus of web crawl … The CCF periodically releases the web corpus results from each crawling process for public use. This is the Common Crawl Corpus …","url":["http://www.rintonpress.com/xjwe17/jwe-17-12/045-072.pdf"]}
-{"year":"2018","title":"A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings","authors":["M Artetxe, G Labaka, E Agirre - arXiv preprint arXiv:1805.06297, 2018"],"snippet":"… EnglishSpanish. More concretely, the dataset consists of 300-dimensional CBOW embeddings trained on WacKy crawling corpora (English, Italian, German), Common Crawl (Finnish) and WMT News Crawl (Spanish). The …","url":["https://arxiv.org/pdf/1805.06297"]}
-{"year":"2018","title":"A Simple Machine Learning Method for Commonsense Reasoning? A Short Commentary on Trinh & Le (2018)","authors":["WS Saba - arXiv preprint arXiv:1810.00521, 2018"],"snippet":"… the suitcase”. T&L then compute, against the backdrop of training on a large corpus (trained on the language model LM-1-Billion, CommonCrawl, and SQuAD), the probabilities of s1 and s2 appearing in a large corpus. The …","url":["https://arxiv.org/pdf/1810.00521"]}
-{"year":"2018","title":"A Simple Method for Commonsense Reasoning","authors":["TH Trinh, QV Le - arXiv preprint arXiv:1806.02847, 2018"],"snippet":"… We train an array of large RNN language models that operate at word or character level on LM-1-Billion, CommonCrawl, SQuAD, Gutenberg Books, and a customized corpus for this task and show that diversity of training …","url":["https://arxiv.org/pdf/1806.02847"]}
-{"year":"2018","title":"A Social Robot System for Modeling Children's Word Pronunciation: Socially Interactive Agents Track","authors":["S Spaulding, H Chen, S Ali, M Kulinski, C Breazeal - Proceedings of the 17th …, 2018"],"snippet":"… 3) The semantic distance between two words is the cosine distance between their word-embedding vector representation. We used word-embedding vectors from the pre-trained Common Crawl GloVe vectors [27], included with the SpaCy Python package …","url":["https://dl.acm.org/citation.cfm?id=3237946"]}
-{"year":"2018","title":"A survey on optimal utilization of preemptible VM instances in cloud computing","authors":["AK Mishra, BK Umrao, DK Yadav - The Journal of Supercomputing, 2018"],"snippet":"Page 1. The Journal of Supercomputing https://doi.org/10.1007/s11227-018-2509-0 A survey on optimal utilization of preemptible VM instances in cloud computing Ashish Kumar Mishra1 · Brajesh Kumar Umrao1 · Dharmendra K. Yadav1 …","url":["https://link.springer.com/article/10.1007/s11227-018-2509-0"]}
-{"year":"2018","title":"A Transfer Learning Based Hierarchical Attention Neural Network for Sentiment Classification","authors":["Z Qu, Y Wang, X Wang, S Zheng - International Conference on Data Mining and Big …, 2018"],"snippet":"… The large one consists of 209772 sentences pairs. While training the LSTM encoder, we obtain the fixed English word vectors using the CommonCrawl-840B GloVe model. The size of hidden units is 300 in the LSTM. We use SGD for training …","url":["https://link.springer.com/chapter/10.1007/978-3-319-93803-5_36"]}
-{"year":"2018","title":"A Vector Worth a Thousand Counts-A Temporal Semantic Similarity Approach to Patent Impact Prediction","authors":["DS Hain, R Jurowetzki, T Buchmann, P Wolf - 2018"],"snippet":"… task convolutional neural network model trained on OntoNotes, with GloVe vectors (685k unique vectors with 300 dimensions) trained on Common Crawl. Given a patent abstract, spaCy predicts the meaning of each term in the document …","url":["http://conference.druid.dk/acc_papers/tgct2l45t4lahofdzb2w9uvbpan4hq.pdf"]}
-{"year":"2018","title":"Absolute Orientation for Word Embedding Alignment","authors":["S Dev, S Hassan, JM Phillips - arXiv preprint arXiv:1806.01330, 2018"],"snippet":"… For instance, some groups have built word vector embeddings for enormous datasets (eg, GloVe embedding using 840 billion tokens from Common Crawl, or the word2vec embedding using 100 billion tokens of Google News), which …","url":["https://arxiv.org/pdf/1806.01330"]}
-{"year":"2018","title":"Abstractive Summarization of Reddit Posts with Multi-level Memory Networks","authors":["B Kim, H Kim, G Kim - arXiv preprint arXiv:1811.00783, 2018"],"snippet":"… 4.1 Text Embedding Online posts include lots of morphologically similar words, which should be closely embedded. Thus, we use the fastText (Bojanowski et al., 2016) trained on the Common Crawl corpus, to initialize the word embedding matrix Wemb …","url":["https://arxiv.org/pdf/1811.00783"]}
-{"year":"2018","title":"Abstractive Summarization Using Attentive Neural Techniques","authors":["J Krantz, J Kalita - arXiv preprint arXiv:1810.08838, 2018"],"snippet":"… Page 5. similarity sub-score uses GloVe embeddings2 pretrained on Common Crawl while the dissimilarity sub-score uses Word2Vec3 trained on the Google News dataset. Using different word embeddings provides …","url":["https://arxiv.org/pdf/1810.08838"]}
-{"year":"2018","title":"Accurate semantic textual similarity for cleaning noisy parallel corpora using semantic machine translation evaluation metric: The NRC supervised submissions to the …","authors":["C Lo, M Simard, D Stewart, S Larkin, C Goutte, P Littell - Proceedings of the Third …, 2018"],"snippet":"… 2011, 2012; Bojar et al., 2013) as the basis of our development set, as we believe that all the test sets in the previous years are clean and highly parallel, as opposed to the “clean” training data where glitches may occur (especially …","url":["http://www.aclweb.org/anthology/W18-6481"]}
-{"year":"2018","title":"Achieving Human Parity on Automatic Chinese to English News Translation","authors":["H Hassan, A Aue, C Chen, V Chowdhary, J Clark… - arXiv preprint arXiv …, 2018"],"snippet":"Page 1. Achieving Human Parity on Automatic Chinese to English News Translation Hany Hassan∗, Anthony Aue, Chang Chen, Vishal Chowdhary, Jonathan Clark, Christian Federmann, Xuedong Huang, Marcin Junczys-Dowmunt …","url":["https://arxiv.org/pdf/1803.05567"]}
-{"year":"2018","title":"Adapted TextRank for Term Extraction: A Generic Method of Improving Automatic Term Extraction Algorithms","authors":["Z Zhang, J Petrak, D Maynard"],"snippet":"… cosine similarity function between two vectors. For the word embeddings, we use the GloVe embeddings pre-trained on the general-purpose Common Crawl data2, but others could be investigated. For multi-word expressions, we …","url":["https://www.researchgate.net/profile/Ziqi_Zhang7/publication/326904600_A_Generic_Method_of_Improving_Automatic_Term_Extraction_Algorithms/links/5b6b3b73a6fdcc87df6da54b/A-Generic-Method-of-Improving-Automatic-Term-Extraction-Algorithms.pdf"]}
-{"year":"2018","title":"Adaptive Semi-supervised Learning for Cross-domain Sentiment Classification","authors":["R He, WS Lee, HT Ng, D Dahlmeier - arXiv preprint arXiv:1809.00530, 2018"],"snippet":"… 4.4 Training Details and Hyper-parameters We initialize word embeddings using the 300dimension GloVe vectors supplied by Pennington et al., (2014), which were trained on 840 billion tokens from the Common Crawl. For …","url":["https://arxiv.org/pdf/1809.00530"]}
-{"year":"2018","title":"Addressing Age-Related Bias in Sentiment Analysis","authors":["M Díaz, I Johnson, A Lazar, AM Piper, D Gergle - 2018"],"snippet":"… 400K words, uncased WG-6B-100D WG-6B-200D WG-6B-300D CC-42B-300D Common Crawl of the Internet 1.9M works, uncased CC-840B-300D 2.2M words, cased TW-27B-25D 2 billion Twitter tweets 1.2M words, uncased TW-27B-50D TW-27B-100D TW-27B-200D …","url":["http://www-users.cs.umn.edu/~joh12041/Publications/AgeBiasSentimentAnalysis_CHI18.pdf"]}
-{"year":"2018","title":"Advances in Pre-Training Distributed Word Representations","authors":["T Mikolov, E Grave, P Bojanowski, C Puhrsch, A Joulin - arXiv preprint arXiv …, 2017"],"snippet":"… problems. Training such models on massive data sources, like Common Crawl, can be cumbersome and many NLP practitioners prefer to use publicly available pre-trained word vectors over training the models by themselves …","url":["https://arxiv.org/pdf/1712.09405"]}
-{"year":"2018","title":"Adversarial Example Generation with Syntactically Controlled Paraphrase Networks","authors":["M Iyyer, J Wieting, K Gimpel, L Zettlemoyer - arXiv preprint arXiv:1804.06059, 2018"],"snippet":"… The pretrained Czech-English model used for translation came from the Nematus NMT system (Sennrich et al., 2017). The training data of this system includes four sources: Common Crawl, CzEng 1.6, Europarl, and News Commentary …","url":["https://arxiv.org/pdf/1804.06059"]}
-{"year":"2018","title":"Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization","authors":["EM Ponti, I Vulić, G Glavaš, N Mrkšić, A Korhonen - arXiv preprint arXiv:1809.04163, 2018"],"snippet":"… Polyglot Wikipedia (Al-Rfou et al., 2013) using Skip-Gram with Negative Sampling (SGNS) (Mikolov et al., 2013) by Levy and Goldberg (2014) with bag-of- words contexts (window size is 2). 2) GLOVE-CC are GloVe vectors …","url":["https://arxiv.org/pdf/1809.04163"]}
-{"year":"2018","title":"Aggression Identification Using Deep Learning and Data Augmentation","authors":["J Risch, R Krestel"],"snippet":"… More specifically, we use the common crawl embeddings5 for the English tasks and the Hindi Wikipedia embeddings6 for the Hindi tasks (Grave et al., 2018). In comparison to other embedding methods, fastText embeddings …","url":["https://hpi.de/fileadmin/user_upload/fachgebiete/naumann/publications/2018/Aggression_Identification_Using_Deep_Learning_and_Data_Augmentation.pdf"]}
-{"year":"2018","title":"Aggressive Language Identification Using Word Embeddings and Sentiment Features","authors":["C Orasan - Proceedings of the First Workshop on Trolling …, 2018"],"snippet":"… representation of words. For the experiments presented in this paper, we used the pretrained word vectors obtained from the Common Crawl corpus containing 840 billion tokens and 2.2 million vocabulary entries. Each word …","url":["http://www.aclweb.org/anthology/W18-4414"]}
-{"year":"2018","title":"Ain't Nobody Got Time For Coding: Structure-Aware Program Synthesis From Natural Language","authors":["J Bednarek, K Piaskowski, K Krawiec - arXiv preprint arXiv:1810.09717, 2018"],"snippet":"… Given that, we rely on a pretrained GloVe embedding, more specifically the Common Crawl, which has been trained on generic NL on 42B tokens by Pennington et al. (2014), has vocabulary size of 1.9M tokens, and embeds the words in a 300dimensional space …","url":["https://arxiv.org/pdf/1810.09717"]}
-{"year":"2018","title":"Alibaba's Neural Machine Translation Systems for WMT18","authors":["Y Deng, S Cheng, J Lu, K Song, J Wang, S Wu, L Yao… - Proceedings of the Third …, 2018"],"snippet":"… For English ↔ Russian, we use the following resources from the WMT parallel data: News Commentary v13, CommonCrawl, ParaCrawl corpus … For EN → TR, about 6 million sentences are selected from the newscrawl2016, 2017 …","url":["http://www.aclweb.org/anthology/W18-6408"]}
-{"year":"2018","title":"ALOD2Vec Matcher⋆","authors":["J Portisch, H Paulheim"],"snippet":"… like DBpedia [3] – but in- stead on the whole Web: The data set consists of hypernymy relations extracted from the Common Crawl1, a … 1 see http://commoncrawl.org/ 2 see http://webisa.webdatacommons.org/concept …","url":["http://dit.unitn.it/~pavel/om2018/papers/oaei18_paper3.pdf"]}
-{"year":"2018","title":"Amortized Context Vector Inference for Sequence-to-Sequence Networks","authors":["S Chatzis, A Charalampous, K Tolias, SA Vassou - arXiv preprint arXiv:1805.09039, 2018"],"snippet":"Page 1. Amortized Context Vector Inference for Sequence-to-Sequence Networks Sotirios Chatzis Cyprus University of Technology sotirios. chatzis@cut.ac.cy Aristotelis Charalampous Cyprus University of …","url":["https://arxiv.org/pdf/1805.09039"]}
-{"year":"2018","title":"AmritaNLP at SemEval-2018 Task 10: Capturing discriminative attributes using convolution neural network over global vector representation.","authors":["V Vinayan, KP Soman - Proceedings of The 12th International Workshop on …, 2018"],"snippet":"… ding (Pennington et al., 2014) of various dimensions are considered, which is learned over public data, available under the PDDL.2 (100, 300 di- mension word representation, embedded over 6B, 840B sizes common crawl corpus are considered) …","url":["http://www.aclweb.org/anthology/S18-1166"]}
-{"year":"2018","title":"An Adaption of BIOASQ Question Answering dataset for Machine Reading systems by Manual Annotations of Answer Spans.","authors":["S Kamath, B Grau, Y Ma - Proceedings of the 6th BioASQ Workshop A challenge …, 2018"],"snippet":"… Several embedding spaces were tested as input vectors (Kamath et al., 2017) and the best performing ones which were the Glove embeddings trained on common crawl data with 840B tokens, were chosen as input to the system …","url":["http://www.aclweb.org/anthology/W18-5309"]}
-{"year":"2018","title":"An Analysis of Hierarchical Text Classification Using Word Embeddings","authors":["RA Stein, PA Jaques, JF Valiati - Information Sciences, 2018"],"snippet":"Skip to main content …","url":["https://www.sciencedirect.com/science/article/pii/S0020025518306935"]}
-{"year":"2018","title":"An Encoder-decoder Approach to Predicting Causal Relations in Stories","authors":["M Roemmele, AS Gordon"],"snippet":"… First, we encoded the words in each in- put segment as the sum of their GloVe embeddings3 (Pennington et al., 2014), which represent words according to a global log-bilinear regression model trained on word co-occurrence counts in the Common Crawl corpus …","url":["http://people.ict.usc.edu/~gordon/publications/NAACL-WS18A.PDF"]}
-{"year":"2018","title":"An Experimental Analysis of Multi-Perspective Convolutional Neural Networks","authors":["Z Tu - 2018"],"snippet":"… nity to use. Popular pre-trained word vectors include word2vec trained on Google News, GloVe [31] trained on Common Crawl/Wikipedia/Twitter, and fastText [19] trained on Common Crawl/Wikipedia. Whereas word2vec captures …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/13297/Tu_Zhucheng.pdf?sequence=1"]}
-{"year":"2018","title":"An Unsupervised Approach to Relatedness Analysis of Legal Language","authors":["Y Wang - 2018"],"snippet":"Page 1. An Unsupervised Approach to Relatedness Analysis of Legal Language by Ying Wang A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master of Applied …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/13847/Wang_Ying.pdf?sequence=3&isAllowed=y"]}
-{"year":"2018","title":"Analysis of DNS in cybersecurity","authors":["P Hudák"],"snippet":"Page 1. Masarykova univerzita Fakulta informatiky Analysis of DNS in cybersecurity Master's thesis Patrik Hudák Brno, 2017 Page 2. Page 3. Declaration Hereby I declare, that this paper is my original authorial work, which I have worked out by my own …","url":["https://is.muni.cz/th/byrdn/Thesis.pdf"]}
-{"year":"2018","title":"Analysis of parallel iterative graph applications on shared memory systems","authors":["F Atik - 2018"],"snippet":"Page 1. ANALYSIS OF PARALLEL ITERATIVE GRAPH APPLICATIONS ON SHARED MEMORY SYSTEMS a thesis submitted to the graduate school of engineering and science of bilkent university in partial fulfillment of the requirements for the degree of master of science in …","url":["http://repository.bilkent.edu.tr/bitstream/handle/11693/35746/10178583.pdf?sequence=1"]}
-{"year":"2018","title":"Analysis of Short Text Classification strategies using Out of-domain Vocabularies","authors":["D Roa - 2018"],"snippet":"Page 1. IN DEGREE PROJECT INFORMATION AND COMMUNICATION TECHNOLOGY, SECOND CYCLE, 30 CREDITS , STOCKHOLM SWEDEN 2018 Analysis of Short Text Classification strategies using Out- of-domain Vocabularies DIEGO ROA …","url":["http://www.diva-portal.org/smash/get/diva2:1259356/FULLTEXT01.pdf"]}
-{"year":"2018","title":"Analysis of the Web Graph Aggregated by Host and Pay-Level Domain","authors":["A Funel - arXiv preprint arXiv:1802.05435, 2018"],"snippet":"… The web graph datasets, publicly available, have been released by the Common Crawl Foundation 1 and are based on a web crawl performed during the period May-June-July 2017 … 1http://commoncrawl.org … [7] from a crawl, provided by the Common Crawl Foundation, gath …","url":["https://arxiv.org/pdf/1802.05435"]}
-{"year":"2018","title":"Analyzing conversations to automatically identify action items","authors":["R Raanani, R Levy, MY Breakstone, D Facher - US Patent App. 15/854,642, 2018"],"snippet":"… At the same time, natural language processing (NLP) approaches to both topic modeling and world-knowledge modeling, have become much more efficient due to the availability of large, freely accessible natural language corpora (eg, CommonCrawl), as well as freely …","url":["https://patents.google.com/patent/US20180122383A1/en"]}
-{"year":"2018","title":"ANALYZING CONVERSATIONS TO AUTOMATICALLY IDENTIFY CUSTOMER PAIN POINTS","authors":["R Raanani, R Levy, MY Breakstone, D Facher - US Patent App. 15/902,808, 2018"],"snippet":"… At the same time, natural language processing (NLP) approaches to both topic modeling and world-knowledge modeling, have become much more efficient due to the availability of large, freely accessible natural language corpora (eg, CommonCrawl), as well as freely …","url":["http://www.freepatentsonline.com/y2018/0181561.html"]}
-{"year":"2018","title":"Analyzing conversations to automatically identify deals at risk","authors":["R Raanani, R Levy, D Facher, MY Breakstone - US Patent App. 15/835,807, 2018"],"snippet":"… language processing (NLP) approaches to both topic modeling and i Insidesales.com “Market size 2013” study world-knowledge modeling, have become much more efficient due to the availability of large, freely accessible …","url":["https://patents.google.com/patent/US20180096271A1/en"]}
-{"year":"2018","title":"ANALYZING CONVERSATIONS TO AUTOMATICALLY IDENTIFY PRODUCT FEATURE REQUESTS","authors":["R Raanani, R Levy, MY Beakstone, D Facher - US Patent App. 15/902,751, 2018"],"snippet":"… At the same time, natural language processing (NLP) approaches to both topic modeling and world-knowledge modeling, have become much more efficient due to the availability of large, freely accessible natural language corpora (eg, CommonCrawl), as well as freely …","url":["http://www.freepatentsonline.com/y2018/0183930.html"]}
-{"year":"2018","title":"Analyzing conversations to automatically identify product features that resonate with customers","authors":["R Raanani, R Levy, MY Breakstone, D Facher - US Patent App. 15/937,494, 2018"],"snippet":"… At the same time, natural language processing (NLP) approaches to both topic modeling and world-knowledge modeling, have become much more efficient due to the availability of large, freely accessible natural language corpora (eg, CommonCrawl), as well as freely …","url":["https://patents.google.com/patent/US20180218733A1/en"]}
-{"year":"2018","title":"Analyzing Uncertainty in Neural Machine Translation","authors":["M Ott, M Auli, D Granger, MA Ranzato - arXiv preprint arXiv:1803.00047, 2018"],"snippet":"Page 1. Analyzing Uncertainty in Neural Machine Translation Myle Ott Michael Auli David Granger Marc'Aurelio Ranzato Facebook AI Research Abstract Machine translation is a popular test bed for research in neural sequence …","url":["https://arxiv.org/pdf/1803.00047"]}
-{"year":"2018","title":"Answering Factoid Questions with Recurrent Neural Networks","authors":["M Kim, K Paeng"],"snippet":"… one. The embedding matrix is initialized with 300-dimensional GloVe embeddings pre-trained on the 840B Common Crawl corpus [9]. We use case-sensitive embeddings, which results in ~140k usable GloVe embeddings …","url":["http://cs.umd.edu/~miyyer/data/answering-factoid-questions.pdf"]}
-{"year":"2018","title":"Approaching Nested Named Entity Recognition with Parallel LSTM-CRFs","authors":["Ł Borchmann, A Gretkowski, F Gralinski - Proceedings ofthePolEval2018Workshop, 2018"],"snippet":"… 2014) were trained on a very large, freely available7 Common Crawl-based Web corpus of Polish (Buck et al. 2014) … N-gram Counts and Language Models from the Common Crawl.[in:] Proceedings of the Language Resources …","url":["http://poleval.pl/files/poleval2018.pdf#page=63"]}
-{"year":"2018","title":"Approaching Neural Grammatical Error Correction as a Low-Resource Machine Translation Task","authors":["M Junczys-Dowmunt, R Grundkiewicz, S Guha… - arXiv preprint arXiv …, 2018"],"snippet":"… Current state-of-the-art GEC systems based on SMT, however, all include large-scale in- domain language models either following the steps outlined in Junczys-Dowmunt and Grundkiewicz (2016) or directly re-using their …","url":["https://arxiv.org/pdf/1804.05940"]}
-{"year":"2018","title":"Approaching the largest 'API': extracting information from the Internet with Python","authors":["JE Germann"],"snippet":"… For every patron their dataset. For every dataset its patron. Bibliography. Common Crawl: Get Started[Internet]. [accessed 2017 Dec. 1] Available from http://commoncrawl.org/the-data/getstarted/. Imperva Incapsula's Bot Traffic Report [Internet]. [accessed 2017 Dec …","url":["http://journal.code4lib.org/articles/13197"]}
-{"year":"2018","title":"Arabic Sentences Classification via Deep Learning","authors":["D Sagheer, F Sukkar"],"snippet":"… The research [21] presents AraVec Arabic word2vec models for the Arabic language using three different dataset resources: Wikipedia, Twitter and Common Crawl webpages crawl data, the models are built in the same strategies in Mikilov word2vec, skip-gram and CBOW …","url":["https://www.researchgate.net/profile/Dania_Sagheer/publication/326429992_Arabic_Sentences_Classification_via_Deep_Learning/links/5b5b5ecfa6fdccf0b2fa820a/Arabic-Sentences-Classification-via-Deep-Learning.pdf"]}
-{"year":"2018","title":"Are Automatic Metrics Robust and Reliable in Specific Machine Translation Tasks?","authors":["M Chinea-Rios, A Peris, F Casacuberta"],"snippet":"… 5 Experimental setup Our experimental framework related a domain adaptation task, in the English to Spanish language direction. In our setup, we trained a PB-SMT and a NMT system on the same data, from a general corpus extracted from websites (Common Crawl) …","url":["https://www.researchgate.net/profile/Alvaro_Peris/publication/325059351_Are_Automatic_Metrics_Robust_and_Reliable_in_Specific_Machine_Translation_Tasks/links/5af4002e4585157136c96459/Are-Automatic-Metrics-Robust-and-Reliable-in-Specific-Machine-Translation-Tasks.pdf"]}
-{"year":"2018","title":"Are we experiencing the Golden Age of Automatic Post-Editing?","authors":["M Junczys-Dowmunt - Proceedings of the AMTA 2018 Workshop on …, 2018"],"snippet":"… EN-DE bilingual data from the WMT-16 shared tasks on IT and news translation. ▶ German monolingual Common Crawl (CC) corpus. Proceedings for AMTA 2018 Workshop: Translation Quality Estimation …","url":["http://www.aclweb.org/anthology/W18-2105"]}
-{"year":"2018","title":"ArgumenText: Searching for Arguments in Heterogeneous Sources","authors":["C Stab, J Daxenberger, C Stahlhut, T Miller, B Schiller… - Proceedings of the 2018 …, 2018"],"snippet":"… 3.1 Data As our objective is to search for arguments in any text domain, we build upon the English part of CommonCrawl,1 the largest Web corpus available to date. Before further processing, we followed 1http://commoncrawl.org/ Habernal et al …","url":["http://www.aclweb.org/anthology/N18-5005"]}
-{"year":"2018","title":"Arretium or Arezzo? A Neural Approach to the Identification of Place Names in Historical Texts","authors":["R Sprugnoli"],"snippet":"… summarised below: • dropout: 0.25, 0.25 • classifier: CRF • LSTM-Size: 100 • optimizer: NADAM • word embeddings: GloVe Common Crawl 840B • character … namely: (i) GloVe embeddings, trained on a corpus of 840 billion …","url":["http://ceur-ws.org/Vol-2253/paper26.pdf"]}
-{"year":"2018","title":"Associative Multichannel Autoencoder for Multimodal Word Representation","authors":["S Wang, J Zhang, C Zong - Proceedings of the 2018 Conference on Empirical …, 2018"],"snippet":"… representations. 4 Experimental Setup 4.1 Datasets Textual vectors. We use 300-dimensional GloVe vectors1 which are trained on the Common Crawl corpus consisting of 840B tokens and a vocabulary of 2.2M words2. Visual vectors. Our …","url":["http://www.aclweb.org/anthology/D18-1011"]}
-{"year":"2018","title":"AttnConvnet at SemEval-2018 Task 1: Attention-based Convolutional Neural Networks for Multi-label Emotion Classification","authors":["Y Kim, H Lee, K Jung - arXiv preprint arXiv:1804.00831, 2018"],"snippet":"… dataset. Among those well-known word embeddings such as Word2Vec( Mikolov et al., 2013), GloVe(Pennington et al., 2014), fastText(Piotr et al., 2016), we adopt 300-dimension GloVe vectors for English ,which is trained …","url":["https://arxiv.org/pdf/1804.00831"]}
-{"year":"2018","title":"Automated Detection of Adverse Drug Reactions in the Biomedical Literature Using Convolutional Neural Networks and Biomedical Word Embeddings","authors":["DS Miranda - arXiv preprint arXiv:1804.09148, 2018"],"snippet":"… 5.1 Embeddings GloVe 840B As in Huynh's work (Huynh et al., 2016), we use pre-trained word embeddings. Huynh focused mainly on the general purpose GloVe Common Crawl 840B, 300 dimensional word embeddings (Pennington et al., 2014). Pyysalo's Embeddings …","url":["https://arxiv.org/pdf/1804.09148"]}
-{"year":"2018","title":"Automated discovery of privacy violations on the web","authors":["ST Englehardt - 2018"],"snippet":"Page 1. Automated discovery of privacy violations on the web Steven Tyler Englehardt A Dissertation Presented to the Faculty of Princeton University in Candidacy for the Degree of Doctor of Philosophy Recommended for …","url":["https://senglehardt.com/papers/princeton_phd_dissertation_englehardt.pdf"]}
-{"year":"2018","title":"Automatic generation of playlists from conversations","authors":["R Raanani, R Levy, MY Breadstone - US Patent App. 15/793,691, 2018"],"snippet":"… At the same time, natural language processing (NLP) approaches to both topic modeling and world-knowledge modeling, have become much more efficient due to the availability of large, freely accessible natural language corpora (eg, CommonCrawl), as well as freely …","url":["https://patents.google.com/patent/US20180046710A1/en"]}
-{"year":"2018","title":"Automatic Neural Question Generation using Community-based Question Answering Systems","authors":["T Baghaee - 2017"],"snippet":"Page 1. AUTOMATIC NEURAL QUESTION GENERATION USING COMMUNITYBASED QUESTION ANSWERING SYSTEMS TINA BAGHAEE Bachelor of Science, Shahid Beheshti University, 2011 A Thesis Submitted to the …","url":["https://www.uleth.ca/dspace/bitstream/handle/10133/5004/Baghaee_Tina_MSC_2017.pdf?sequence=1&isAllowed=y"]}
-{"year":"2018","title":"AUTOMATIC PATTERN RECOGNITION IN CONVERSATIONS","authors":["R Raanani, R Levy, D Facher, MY Breakstone - US Patent App. 15/817,490, 2018"],"snippet":"… language processing (NLP) approaches to both topic modeling and world-knowledge modeling, have become much more efficient due to the i Insidesales.com “Market size 2013” study availability of large, freely …","url":["http://www.freepatentsonline.com/y2018/0077286.html"]}
-{"year":"2018","title":"Automatic Post-Editing of Machine Translation: A Neural Programmer-Interpreter Approach","authors":["TT Vu, G Haffari - Proceedings of the 2018 Conference on Empirical …, 2018"],"snippet":"… Interestingly, training MT+AG and MT+AG+LM models on 23K data lead to better TER/BLEU than those trained on 500K+12K. This implies the importance of in-domain training data, as the synthetic corpus is created …","url":["http://www.aclweb.org/anthology/D18-1341"]}
-{"year":"2018","title":"Automatic Question Tagging with Deep Neural Networks","authors":["B Sun, Y Zhu, Y Xiao, R Xiao, YG Wei - IEEE Transactions on Learning Technologies, 2018"],"snippet":"… Word2vec [41] trained on a large corpus. Some pre-trained word vectors are available, such as GloVe Common Crawl vectors1 and word2vec vectors2, which is trained on Google News. The word vectors can be divided into …","url":["http://ieeexplore.ieee.org/abstract/document/8295250/"]}
-{"year":"2018","title":"Automatically Categorizing Software Technologies","authors":["M Nassif, C Treude, M Robillard - IEEE Transactions on Software Engineering, 2018","S Khan, WH Butt - 2022 2nd International Conference on Digital Futures …, 2022"],"snippet":"… All these approaches work by mining large text corpora. Among the latest such techniques is the WebIsA Database [32] from the Web Data Commons project, which extracts hypernyms from CommonCrawl,1 a corpus of over …","url":["https://ieeexplore.ieee.org/abstract/document/8359344/","https://ieeexplore.ieee.org/abstract/document/9787457/"]}
-{"year":"2018","title":"Based Speech Recognition with Gated ConvNets","authors":["V Liptchinsky, G Synnaeve, R Collobert - arXiv preprint arXiv:1712.09444, 2017"],"snippet":"… Extra Resources Panayotov et al. (2015) HMM+DNN+pNorm phone fMLLR phone lexicon Amodei et al. (2016) 2D-CNN+RNN letter none 11.9Kh train set, Common Crawl LM Peddinti et al. (2015b) HMM+CNN phone iVectors phone lexicon Povey et al …","url":["https://arxiv.org/pdf/1712.09444"]}
-{"year":"2018","title":"Belittling the Source: Trustworthiness Indicators to Obfuscate Fake News on the Web","authors":["D Esteves, AJ Reddy, P Chawla, J Lehmann - arXiv preprint arXiv:1809.00494, 2018"],"snippet":"… Social Tags: returns the frequency of social tags in wb: R ⋃ i=1 ϕ(i, wb) 11. OpenSources: returns the open-source classification (x) for a given website: x = { 1, if w ∈ O 0, if w ∈ O 12. PageRankCC: PageRank information …","url":["https://arxiv.org/pdf/1809.00494"]}
-{"year":"2018","title":"Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine Translation","authors":["X Niu, W Xu, M Carpuat - arXiv preprint arXiv:1811.01116, 2018"],"snippet":"… data for Swahili↔English (SW↔EN), Tagalog↔English (TL↔EN) and Somali↔English (SO↔EN) contains a mixture of domains such as news and weblogs and is collected from the IARPA MATERIAL program2, the Global …","url":["https://arxiv.org/pdf/1811.01116"]}
-{"year":"2018","title":"Bi-Directional Neural Machine Translation with Synthetic Parallel Data","authors":["X Niu, M Denkowski, M Carpuat - arXiv preprint arXiv:1805.11213, 2018"],"snippet":"… Page 3. Type Dataset # Sentences High-resource: German↔English Training Common Crawl + Europarl v7 + News Comm. v12 … 2.2). We use the training data as in-domain and either Common Crawl or ICWSM as out-of-domain …","url":["https://arxiv.org/pdf/1805.11213"]}
-{"year":"2018","title":"Big Data Integration for Product Specifications","authors":["L Barbosa, V Crescenzi, XL Dong, P Merialdo, F Piai… - Data Engineering, 2018"],"snippet":"… Only 20% of our sources contained fewer pages than the same sources in Common Crawl, and a very small fraction of the pages in these sources were product pages: on a sample set of 12 websites where Common Crawl …","url":["http://sites.computer.org/debull/A18june/A18JUN-CD.pdf#page=73"]}
-{"year":"2018","title":"Big Open Research Data","authors":["A PRIMPELI"],"snippet":"… Outline ▪ Requirements of a data scientist ▪ Open access datasets ▪ DBpedia ▪ Common Crawl ▪ The Web Data Commons project ▪ Why should we share data? ▪ How should we share data? 26/10/2017 … 5 Page 6. Common Crawl …","url":["https://pdfs.semanticscholar.org/presentation/a576/94b9a19b82cc219ae01004e5c30cbeea916e.pdf"]}
-{"year":"2018","title":"Bigrams and BiLSTMs Two neural networks for sequential metaphor detection","authors":["Y Bizzoni, M Ghanimifard - NAACL HLT 2018, 2018"],"snippet":"… GloVe embeddings on British National Corpus (Consortium et al., 2007) from which the VUAMC corpus was sampled, and compared it with both pre-trained Word2Vec em- beddings on Google News corpus and standard …","url":["http://www.cl.cam.ac.uk/~es407/papers/Fig-Lang2018-proceedings.pdf#page=103"]}
-{"year":"2018","title":"Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition","authors":["GI Winata, CS Wu, A Madotto, P Fung - arXiv preprint arXiv:1805.12061, 2018"],"snippet":"… We use 300-dimensional English (Mikolov et al., 2018) and Spanish (Grave et al., 2018) FastText pre-trained word vectors which comprise two million words vocabulary each and they are trained using Common Crawl and Wikipedia …","url":["https://arxiv.org/pdf/1805.12061"]}
-{"year":"2018","title":"Biomedical Domain-Oriented Word Embeddings via Small Background Texts for Biomedical Text Mining Tasks","authors":["L Li, J Wan, D Huang - National CCF Conference on Natural Language …, 2017"],"snippet":"… For example, Pennington et al. used Wikipedia, Giga word 5 and Common Crawl to learn word embeddings, each of which contained billions of tokens [15]. However, there is not always a monotonic increase in performance as the amount of background texts increase …","url":["https://link.springer.com/chapter/10.1007/978-3-319-73618-1_46"]}
-{"year":"2018","title":"BlogSet-BR: A Brazilian Portuguese Blog Corpus","authors":["H Santos, V Woloszyn, R Vieira - … of the Eleventh International Conference on …, 2018"],"snippet":"… For instance, the Common Crawl project maintains an open repository of web crawl data that can be accessed and analyzed by any research group2. This corpus has been used to build language models (Roziewski …","url":["http://www.aclweb.org/anthology/L18-1105"]}
-{"year":"2018","title":"BomJi at SemEval-2018 Task 10: Combining Vector-, Pattern-and Graph-based Information to Identify Discriminative Attributes","authors":["E Santus, C Biemann, E Chersoni"],"snippet":"… 2The pre-trained vectors are available, respectively, at https://code.google.com/archive/ p/ word2vec/ (Google News, 300 dimensions) and at https://nlp.stanford.edu/projects/ glove/ (Common Crawl, 840B tokens, 300 dimensions) …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2018-santusetal-semeval-bomji.pdf"]}
-{"year":"2018","title":"Bootstrapping Multilingual Intent Models via Machine Translation for Dialog Automation","authors":["N Ruiz, S Bangalore, J Chen - arXiv preprint arXiv:1805.04453, 2018"],"snippet":"… The NMT models were trained with parallel English-Spanish data from Europarl v7, CommonCrawl, and WMT News Commentary v8 from the WMT 2013 evaluation campaign (Bojar et al., 2013), as well as the TED talks from IWSLT 2014 (Cettolo et al., 2014) …","url":["https://arxiv.org/pdf/1805.04453"]}
-{"year":"2018","title":"Bringing Order to Neural Word Embeddings with Embeddings Augmented by Random Permutations (EARP)","authors":["A Sharp","T Cohen, D Widdows - Proceedings of the 22nd Conference on Computational …, 2018"],"snippet":"Page 1. Proceedings of the 22nd Conference on Computational Natural Language Learning (CoNLL 2018), pages 465–475 Brussels, Belgium, October 31 - November 1, 2018. c 2018 Association for Computational Linguistics 465 …","url":["http://www.aclweb.org/anthology/K18-1045","https://zdoc.pub/bringing-order-to-neural-word-embeddings-with-embeddings-aug.html"]}
-{"year":"2018","title":"Bringing replication and reproduction together with generalisability in NLP: Three reproduction studies for Target Dependent Sentiment Analysis","authors":["A Moore, P Rayson - arXiv preprint arXiv:1806.05219, 2018"],"snippet":"… We found the best word vectors from SSWE and the common crawl 42B 300 dimension Glove vectors by five fold stratified cross validation for the NP methods and the highest accuracy on the validation set for the LSTM methods …","url":["https://arxiv.org/pdf/1806.05219"]}
-{"year":"2018","title":"C) uestion Answering System with Deep Learning","authors":["JSRMI Schoenhals"],"snippet":"… The dataset contains more than 100k question-answer pairs on more than 500 articles, and it is split into 90k/10k train/dev question-context tuples with hidden test set. 3.2 Word Embeddings We use pre-trained GLoVe embeddings from the 840B Common Crawl corpus …","url":["http://web.stanford.edu/class/cs224n/reports/6908933.pdf"]}
-{"year":"2018","title":"CAESAR: Context Awareness Enabled Summary-Attentive Reader","authors":["LH Chen, K Tripathi - arXiv preprint arXiv:1803.01335, 2018"],"snippet":"… Aftering experimenting with hyperparameters and various preprocessing settings, we settle on the following experiment details which gave the optimal result. We apply pretrained GloVe word embeddings trained on common","url":["https://arxiv.org/pdf/1803.01335"]}
-{"year":"2018","title":"Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering","authors":["T Mihaylov, P Clark, T Khot, A Sabharwal"],"snippet":"… 11For all experiments we use d = 300 GloVe (Pennington et al., 2014) embeddings pre-trained on 840B tokens from Common Crawl (https://nlp.stanford.edu/projects/glove/). Page 7. Question Science Fact Common Knowledge (Type) Reasoning Challenge …","url":["http://ai2-website.s3.amazonaws.com/publications/Mihaylov-OpenBookQA-emnlp2018.pdf"]}
-{"year":"2018","title":"Can Common Crawl reliably track persistent identifier (PID) use over time?","authors":["HS Thompson, J Tong - arXiv preprint arXiv:1802.01424, 2018"],"snippet":"Abstract: We report here on the results of two studies using two and four monthly web crawls respectively from the Common Crawl (CC) initiative between 2014 and 2017, whose initial goal was to provide empirical evidence for the changing patterns of use of so-called","url":["https://arxiv.org/pdf/1802.01424"]}
-{"year":"2018","title":"Can Network Embedding of Distributional Thesaurus be Combined with Word Vectors for Better Representation?","authors":["A Jana, P Goyal - arXiv preprint arXiv:1802.06196, 2018"],"snippet":"… representation. For that purpose, we directly use very wellknown GloVe 1.2 embeddings (Pennington et al., 2014) trained on 840 billion words of the common crawl dataset having vector dimension of 300. As an instance …","url":["https://arxiv.org/pdf/1802.06196"]}
-{"year":"2018","title":"Card-660: A Reliable Evaluation Framework for Rare Word Representation Models","authors":["MT Pilehvar, D Kartsaklis, V Prokhorov, N Collier - Proceedings of the 2018 …, 2018"],"snippet":"… Glove Wikipedia-Gigaword (300d) 400K 7% 55% 12% 74% 34.9 15.1 34.4 15.7 Glove Common Crawl - uncased (300d) 1.9M 1% 36% 1% 50% 36.5 29.2 37.7 27.6 Glove Common Crawl - cased (300d) 2.2M 1% 29% 2% 44% 44.0 33.0 45.1 27.3 …","url":["http://www.aclweb.org/anthology/D18-1169"]}
-{"year":"2018","title":"Card-660: Cambridge Rare Word Dataset-a Reliable Benchmark for Infrequent Word Representation Models","authors":["MT Pilehvar, D Kartsaklis, V Prokhorov, N Collier - arXiv preprint arXiv:1808.09308, 2018"],"snippet":"… Glove Wikipedia-Gigaword (300d) 400K 7% 55% 12% 74% 34.9 15.1 34.4 15.7 Glove Common Crawl - uncased (300d) 1.9M 1% 36% 1% 50% 36.5 29.2 37.7 27.6 Glove Common Crawl - cased (300d) 2.2M 1% 29% 2% 44% 44.0 33.0 45.1 27.3 …","url":["https://arxiv.org/pdf/1808.09308"]}
-{"year":"2018","title":"Categorization of Comparative Sentences for Argument Mining","authors":["M Franzek, A Panchenko, C Biemann - arXiv preprint arXiv:1809.06152, 2018"],"snippet":"… The re- maining objects were combined to pairs. For each object type as given by the Wikipedia List page or the seed word, all possible combinations were created. We drew sentences from the publicly available CommonCrawl3 index of Panchenko et al …","url":["https://arxiv.org/pdf/1809.06152"]}
-{"year":"2018","title":"CERES: Distantly Supervised Relation Extraction from the Semi-Structured Web","authors":["C Lockard, XL Dong, A Einolghozati, P Shiralkar - arXiv preprint arXiv:1804.04635, 2018"],"snippet":"Page 1. CERES: Distantly Supervised Relation Extraction from the Semi-Structured Web Colin Lockard ∗ University of Washington lockardc@cs.washington.edu Xin Luna Dong Amazon lunadong@amazon.com Arash Einolghozati ∗ Facebook arashe@fb.com …","url":["https://arxiv.org/pdf/1804.04635"]}
-{"year":"2018","title":"Character-based Neural Networks for Sentence Pair Modeling","authors":["W Lan, W Xu - arXiv preprint arXiv:1805.08297, 2018"],"snippet":"… word vectors (Pennington et al., 2014), trained on 27 billion words from Twitter (vocabulary size of 1.2 milion words) for social media datasets, and 300dimensional GloVe vectors, trained on 840 billion words (vocabulary …","url":["https://arxiv.org/pdf/1805.08297"]}
-{"year":"2018","title":"Character-Level Feature Extraction with Densely Connected Networks","authors":["C Lee, YB Kim, D Lee, HS Lim - arXiv preprint arXiv:1806.09089, 2018"],"snippet":"… Our model uses the GloVe (Pennington et al., 2014) 300-dimensional vectors trained on the Common Crawl corpus with 42B tokens as word level features, as this resulted in the best performance in preliminary experiments …","url":["https://arxiv.org/pdf/1806.09089"]}
-{"year":"2018","title":"Characterising dataset search—An analysis of search logs and data requests","authors":["E Kacprzak, L Koesten, LD Ibáñez, T Blount… - Journal of Web Semantics, 2018"],"snippet":"… In 2015 the Web Data Commons project extracted 233 million data tables from the Common Crawl [3]. The ability to generate business value from data analytics offers competitive advantage in virtually every industry worldwide …","url":["https://www.sciencedirect.com/science/article/pii/S1570826818300556"]}
-{"year":"2018","title":"CIKM AnalytiCup 2017 Lazada Product Title Quality Challenge An Ensemble of Deep and Shallow Learning to predict the Quality of Product Titles","authors":["K Singh, V Sunder - arXiv preprint arXiv:1804.01000, 2018"],"snippet":"… calculate semantic similarity based features. For each pair of words in a title, we calculate the cosine distance between vectors of words generated from Common crawl google glove [Pennington et al. 2014]. Further, we normalize …","url":["https://arxiv.org/pdf/1804.01000"]}
-{"year":"2018","title":"ClaiRE at SemEval-2018 Task 7-Extended Version","authors":["L Hettinger, A Dallmann, A Zehe, T Niebler, A Hotho"],"url":["https://www.arxiv-vanity.com/papers/1804.05825/"]}
-{"year":"2018","title":"ClaiRE at SemEval-2018 Task 7: Classification of Relations using Embeddings","authors":["L Hettinger, A Dallmann, A Zehe, T Niebler, A Hotho - Proceedings of The 12th …, 2018"],"snippet":"… As a baseline, we employ a publicly available set of 300-dimensional word embeddings trained with GloVe (Pennington et al., 2014) on the Common Crawl data4 (CC) … 4http://commoncrawl.org/ 5https://arxiv.org 6https://arxiv.org/help/bulk_data …","url":["http://www.aclweb.org/anthology/S18-1134"]}
-{"year":"2018","title":"Classifying Occupations According to Their Skill Requirements in Job Advertisements","authors":["J Djumalieva, A Lima, C Sleeman - 2018"],"snippet":"… There are publicly available pre-trained word embeddings models. We use a GloVe model, which contains a vocabulary of 2.2 million words and was trained using word to word co-occurrences in a Common Crawl corpus (Pennington, Socher, and Manning, 2014) …","url":["https://www.escoe.ac.uk/wp-content/uploads/2018/03/ESCoE-DP-2018-04.pdf"]}
-{"year":"2018","title":"Cloud repository as a malicious service: challenge, identification and implication","authors":["X Liao, S Alrwais, K Yuan, L Xing, XF Wang, S Hao… - Cybersecurity, 2018"],"snippet":"… Running the scanner over all the data collected by the Common Crawl (Crawl 2015), which indexed five billion web pages, for those associated with all major cloud storage providers (including Amazon S3, Cloudfront, Google …","url":["https://link.springer.com/article/10.1186/s42400-018-0015-6"]}
-{"year":"2018","title":"Clustering-Oriented Representation Learning with Attractive-Repulsive Loss","authors":["K Kenyon-Dean, A Cianflone, L Page-Caccia… - arXiv preprint arXiv …, 2018"],"snippet":"… Each sample contains the news article's title concatenated with its description. As input to our models, we use the 300-dimensional 840B Common Crawl pretrained Glove word embeddings (Pennington, Socher, and Manning 2014) provided by Stanford6 …","url":["https://arxiv.org/pdf/1812.07627"]}
-{"year":"2018","title":"Code-Switched Named Entity Recognition with Embedding Attention","authors":["C Wang, K Cho, D Kiela - Proceedings of the Third Workshop on Computational …, 2018"],"snippet":"… We use high-quality FastText embeddings trained on Common Crawl (Grave et al., 2018; Mikolov et al., 2018) and employ shortcut-stacked sentence encoders (Nie and Bansal, 2017) to obtain deep token-level representations to feed into the CRF …","url":["http://www.aclweb.org/anthology/W18-3221"]}
-{"year":"2018","title":"Collaborative Context-Aware Visual Question Answering","authors":["AS Toor - 2018"],"snippet":"Page 1. COLLABORATIVE CONTEXT-AWARE VISUAL QUESTION ANSWERING by Andeep Singh Toor A Dissertation Submitted to the Graduate Faculty of George Mason University In Partial fulfillment of The Requirements …","url":["http://search.proquest.com/openview/d4ca94e1edcc41c3401b171ab495c21c/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2018","title":"Combination of Statistical and Neural Machine Translation for Myanmar–English","authors":["B Marie, A Fujita, E Sumita"],"snippet":"… For English, we used the monolingual corpora provided by the WMT18 shared News Translation Task. As for Myanmar, we experimented with two monolingual corpora: Myanmar Wikipedia and Myanmar CommonCrawl … The CommonCrawl cor …","url":["http://benjaminmarie.com/pdf/WAT_2018_paper_7.pdf"]}
-{"year":"2018","title":"Combining Convolution and Recursive Neural Networks for Sentiment Analysis","authors":["VD Van, T Thai, MQ Nghiem - Proceedings of the Eighth International Symposium on …, 2017"],"snippet":"… movie reviews. These words might not appear or not have good vector representations in the pre-trained Glove Common Crawl. 153 Page 4. SoICT '17, December 7–8, 2017, Nha Trang City, Viet Nam V. Van et al. Additionally …","url":["https://dl.acm.org/citation.cfm?id=3155158"]}
-{"year":"2018","title":"Combining Shallow and Deep Learning for Aggressive Text Detection","authors":["V Golem, M Karan, J Šnajder - Proceedings of the First Workshop on Trolling …, 2018"],"snippet":"… Inputs to both models were GloVe (Pennington et al., 2014) 300-dimensional word embeddings trained on 840 billion tokens from the Common Crawl or 200-dimensional word embeddings trained on 20 billion tweets.5 Since …","url":["http://www.aclweb.org/anthology/W18-4422"]}
-{"year":"2018","title":"Compact inverted index storage using general‐purpose compression libraries","authors":["M Petri, A Moffat - Software: Practice and Experience"],"snippet":"… We also develop (and make freely available) a new IR test collection based on the News sub-collection of the Common Crawl.6 The News sub-collection provides daily crawls of news websites in many languages. We refer to this collection as CC-NEWS-URL …","url":["http://onlinelibrary.wiley.com/doi/10.1002/spe.2556/full"]}
-{"year":"2018","title":"Comparative Argument Mining","authors":["M Franzek"],"snippet":"… First, does a sentence compare two known objects? And secondly, if it does, is the first-mentioned object better or worse than the second-mentioned, according to the sentence context? The data set was created with data from …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2018-ma-mirco-franzek.pdf"]}
-{"year":"2018","title":"Comparing Distributional and Frame Semantic Properties of Words","authors":["T Kleinbauer, TA Trost"],"snippet":"… G50 50 96.3% 6G Wikipedia & G100 100 96.3% Gigaword 5 G200 200 96.3% G300 300 96.3% G42 300 98.9% 42G Common Crawl G840 300 99.3% 840G Common Crawl GT25 25 90.2% 27G Twitter GT50 50 90.2% GT100 100 90.2% GT200 200 90.2 …","url":["https://www.oeaw.ac.at/fileadmin/subsites/academiaecorpora/PDF/konvens18_08.pdf"]}
-{"year":"2018","title":"Comparing Open Source Search Engine Functionality, Efficiency and Effectiveness with Respect to Digital Forensic Search","authors":["J Hansen, K Porter, A Shalaginov, K Franke - NISK 2018, 2018"],"snippet":"… Malware ISCXAB Malware DAROA98/99 Network DARPA2000 Network MAWILab Network KDD Cup99 Network UNSW-NB15 Network NSA-CDX Network ADFA Network Name Catagory Kyoto data Network crawdad Network …","url":["http://nikt2018.ifi.uio.no/images/NISK2018_preproceedings.pdf#page=117"]}
-{"year":"2018","title":"Comparing Theories of Speaker Choice Using a Model of Classifier Production in Mandarin Chinese","authors":["M Zhan, R Levy - Proceedings of the 2018 Conference of the North …, 2018"],"snippet":"Page 1. Proceedings of NAACL-HLT 2018, pages 1997–2005 New Orleans, Louisiana, June 1 - 6, 2018. c 2018 Association for Computational Linguistics Comparing Theories of Speaker Choice Using a Model of Classifier Production in Mandarin Chinese …","url":["http://www.aclweb.org/anthology/N18-1181"]}
-{"year":"2018","title":"Comparison of Paragram and Glove Results for Similarity Benchmarks","authors":["PM Skłodowskiej-Curie - Multimedia and Network Information Systems, 2019"],"snippet":"… The TOEFL test set was introduced in [13]; the ESL test set was introduced in [28]. 4.1 Experimental Setup We use the unmodified vector space model trained on 840 billion words from Common Crawl data with the GloVe algorithm introduced in [21] …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=cf5sDwAAQBAJ&oi=fnd&pg=PA236&dq=commoncrawl&ots=Zl8zpSyQVF&sig=p1R4RPXAKZFFv4LxOE09nc5dejg"]}
-{"year":"2018","title":"Comparison of Word Embeddings and Sentence Encodings as Generalized Representations for Crisis Tweet Classification Tasks","authors":["H Li, X Li, D Caragea, C Caragea"],"snippet":"… the other parameters. • SIF: denotes the SIF approach, which is considered to be a baseline for sentence embeddings. The original paper used GloVe embeddings pre-trained on the Common Crawl data. However, we used …","url":["https://www.cs.uic.edu/~cornelia/papers/iscram_asian18.pdf"]}
-{"year":"2018","title":"Compositional Source Word Representations for Neural Machine Translation","authors":["D Ataman, MA Di Gangi, M Federico - 2018"],"snippet":"… For training the Czech–English and German– English NMT models, we use the available data sets from the WMT2 (Bojar et al., 2017) shared task on machine translation of news, which consist of Europarl (Koehn, 2005), Commoncrawl …","url":["http://rua.ua.es/dspace/bitstream/10045/76018/1/EAMT2018-Proceedings_05.pdf"]}
-{"year":"2018","title":"Concatenated $ p $-mean Word Embeddings as Universal Cross-Lingual Sentence Representations","authors":["A Rücklé, S Eger, M Peyrard, I Gurevych - arXiv preprint arXiv:1803.01400, 2018"],"snippet":"… Word embeddings We use four diverse, po- tentially complementary types of word embeddings as basis for our sentence representation techniques: GloVe embeddings (GV) (Pennington et al., 2014) trained on Common Crawl;","url":["https://arxiv.org/pdf/1803.01400"]}
-{"year":"2018","title":"Content Extraction and Lexical Analysis from Customer-Agent Interactions","authors":["S Nisioi, A Bucur, LP Dinu - Proceedings of the 2018 EMNLP Workshop W-NUT …, 2018"],"snippet":"… Somewhat surprising is the fact that a big majority of words from the Common Crawl vocabulary (approx … Furthermore, both the lexicons used in questions and answers present little overlap with Common Crawl, and in accordance …","url":["http://www.aclweb.org/anthology/W18-6118"]}
-{"year":"2018","title":"Context and Copying in Neural Machine Translation","authors":["R Knowles, P Koehn - Proceedings of the 2018 Conference on Empirical …, 2018"],"snippet":"… are trained using the Marian toolkit (Junczys-Dowmunt et al., 2018).2 We use the WMT parallel text3 (Europarl, News Commentary, and CommonCrawl) along with … We consider both the full training data (including backtranslations …","url":["http://www.aclweb.org/anthology/D18-1339"]}
-{"year":"2018","title":"Context and Embeddings in Language Modelling–an Exploration","authors":["M Nitsche, M Tropmann-Frick - 2018"],"snippet":"… alone. GloVe typically performs better than Word2Vec skip-gram, especially when the vocabulary is large. GloVe is also available on different corpora such as Twitter, Common Crawl or Wikipedia. 2.2 Bag of Tricks - fastText …","url":["http://ceur-ws.org/Vol-2277/paper24.pdf"]}
-{"year":"2018","title":"Context is Everything: Finding Meaning Statistically in Semantic Spaces","authors":["E Zelikman - arXiv preprint arXiv:1803.08493, 2018"],"snippet":"… For example ”dog” and ”but” are both commonly used words, and in many spaces will have a smaller M-distance than ”Dachshund” and ”dog.” One solution to this issue is presented later in this paper 5300 dimensional word …","url":["https://arxiv.org/pdf/1803.08493"]}
-{"year":"2018","title":"Contextual-CNN: A Novel Architecture Capturing Unified Meaning for Sentence Classification","authors":["J Shin, Y Kim, S Yoon, K Jung"],"snippet":"… For word representation, we use the publicly available 300-dimensional GloVe trained on the Common Crawl with 42B tokens [5], hence our embedding dimension d = 300. Word embedding is normalized to unit norm and is fixed in the experiments without fine-tuning …","url":["http://milab.snu.ac.kr/pub/BigComp2018.pdf"]}
-{"year":"2018","title":"Convexification of Neural Graph","authors":["H Xiao - arXiv preprint arXiv:1801.02901, 2018"],"snippet":"… Specifically, we initialize the word embedding with 300-dimensional GloVe [Pennington et al., 2014] word vectors pre-trained in the 840B Common Crawl corpus [Pennington et al., 2014] and then set the hidden dimension as 100 for each LSTM …","url":["https://arxiv.org/pdf/1801.02901"]}
-{"year":"2018","title":"Convolutional Spatial Attention Model for Reading Comprehension with Multiple-Choice Questions","authors":["Z Chen, Y Cui, W Ma, S Wang, G Hu - arXiv preprint arXiv:1811.08610, 2018"],"snippet":"… among two datasets. The word embeddings are initialized by the pre-trained GloVe word vectors (Common Crawl, 6B tokens, 100-dimension) (Pennington, Socher, and Manning 2014), and keep fixed during training. The words …","url":["https://arxiv.org/pdf/1811.08610"]}
-{"year":"2018","title":"COVER: a linguistic resource combining common sense and lexicographic information","authors":["E Mensa, DP Radicioni, A Lieto - Language Resources and Evaluation"],"snippet":"… (2014)). In count based models, model vectors are learned by applying dimensionality reduction techniques to the co-occurrence counts matrix; in particular, GloVe embeddings have been acquired through a training …","url":["https://link.springer.com/article/10.1007/s10579-018-9417-z"]}
-{"year":"2018","title":"Creation and optimization of resource contents","authors":["M Tober, D Neumann - US Patent App. 15/284,739, 2018"],"snippet":"… 310. The crawler module 310 may automatically crawl a network and acquire contents from one or more resources in the network, acquire the contents from an open repository of web crawl data such as CommonCrawl.org …","url":["https://patents.google.com/patent/US20180096067A1/en"]}
-{"year":"2018","title":"Cross-lingual Decompositional Semantic Parsing Supplemental Material","authors":["S Zhang, X Ma, R Rudinger, K Duh, B Van Durme"],"snippet":"… Hidden states are zero initialized. All other parameters are sampled from U(−0.1,0.1). Decoder: Word embeddings are initialized by open-source GloVe vectors (Pennington et al., 2014) trained on Common Crawl 840B with 300 dimensions …","url":["http://anthology.aclweb.org/attachments/D/D18/D18-1194.Attachment.pdf"]}
-{"year":"2018","title":"Cross-Lingual Propagation for Deep Sentiment Analysis","authors":["X Dong, G de Melo - Proceedings of the 32nd AAAI Conference on Artificial …, 2018"],"snippet":"… each mini-batch. 3.2 Embeddings The standard pre-trained word vectors used for English are the GloVe (Pennington, Socher, and Manning 2014) ones trained on 840 billion tokens of Common Crawl data2, 1https://www.irit …","url":["http://iiis.tsinghua.edu.cn/~weblt/papers/sentiment-propagation.pdf"]}
-{"year":"2018","title":"Cross-Pair Text Representations for Answer Sentence Selection","authors":["K Tymoshenko, A Moschitti"],"snippet":"Page 1. Cross-Pair Text Representations for Answer Sentence Selection Kateryna Tymoshenko DISI, University of Trento (Adeptmind scholar) 38123 Povo (TN), Italy kateryna.tymoshenko@unitn.it Alessandro Moschitti∗ Amazon …","url":["https://m.media-amazon.com/images/G/01/amazon.jobs/Cross-PairTextRepresentationsforAnswerSentenceSelection._CB1538442919_.pdf"]}
-{"year":"2018","title":"CrumbTrail: an Efficient Methodology to Reduce Multiple Inheritance in Knowledge Graphs","authors":["S Faralli, I Finocchi, SP Ponzetto, P Velardi - Knowledge-Based Systems, 2018"],"snippet":"… 5]. Finally, the availability of vast amounts of knowledge encoded in heterogeneous sources, including both structured – eg, Freebase [6], DBpedia [7] – semi-structured – eg, Wikipedia – as well as unstructured resources …","url":["https://www.sciencedirect.com/science/article/pii/S095070511830162X"]}
-{"year":"2018","title":"CS224N Final SQuAD Improvements","authors":["RAV Misra - Context"],"snippet":"… U\"]. Page 5. 4 Experiments 4.1 Implementation and Metrics The model is trained and evaluated on the SQuAD dataset, and uses pretrained GloVe word vectors on the Common Crawl corpus (Pennington et al., 2014). Running …","url":["http://web.stanford.edu/class/cs224n/reports/6907927.pdf"]}
-{"year":"2018","title":"CUNI team: CLEF eHealth Consumer Health Search Task 2018","authors":["S Saleh, P Pecina - CEUR Workshop Proceedings: Working Notes of CLEF, 2018"],"snippet":"… Document collection in the CLEF 2018 consumer health search task is created using CommonCrawl platform 1. First, the query set (described in Section 2.2) is submitted to Microsoft Bing APIs, and a list of domains is extracted from the top retrieved results …","url":["http://ceur-ws.org/Vol-2125/paper_201.pdf"]}
-{"year":"2018","title":"CUNI Transformer Neural MT System for WMT18","authors":["M Popel - Proceedings of the Third Conference on Machine …, 2018"],"snippet":"… CzEng 1.7 57 065 618 424 543 184 Europarl v7 647 15 625 13 000 News Commentary v12 211 4 544 4 057 CommonCrawl 162 3 349 2 927 EN NewsCrawl 2016–17 47 483 934 981 CS NewsCrawl 2007–17 65 383 927 348 total 170 951 1 576 923 1 490 516 …","url":["http://www.aclweb.org/anthology/W18-6424"]}
-{"year":"2018","title":"Cuttlefish: A Lightweight Primitive for Adaptive Query Processing","authors":["T Kaftan, M Balazinska, A Cheung, J Gehrke - arXiv preprint arXiv:1802.09180, 2018"],"snippet":"Page 1. Cuttlefish: A Lightweight Primitive for Adaptive Query Processing Tomer Kaftan University of Washington Magdalena Balazinska University of Washington Alvin Cheung University of Washington Johannes Gehrke Microsoft …","url":["https://arxiv.org/pdf/1802.09180"]}
-{"year":"2018","title":"CytonMT: an Efficient Neural Machine Translation Open-source Toolkit Implemented in C++","authors":["X Wang, M Utiyama, E Sumita - arXiv preprint arXiv:1802.07170, 2018"],"snippet":"… Length penalty was applied through the formula in (Wu et al., 2016). Data Set # Sent. # Words Source Target CommonCrawl 2,399,123 54,572,703 58,869,785 Europarl v7 1,959,829 51,7061,34 54,327,972 News Comment. 223,153 5,689,117 5,660,789 Dev …","url":["https://arxiv.org/pdf/1802.07170"]}
-{"year":"2018","title":"Dank Learning: Generating Memes Using Deep Neural Networks","authors":["V Peirson, L Abel, EM Tolunay - arXiv preprint arXiv:1806.04510, 2018"],"snippet":"… In this context, pretrained GloVe [3] word embeddings constitute the most suitable choice of word representation for our project, based on the fact that they have been trained on very large corpora, offering an option of words …","url":["https://arxiv.org/pdf/1806.04510"]}
-{"year":"2018","title":"Data Augmentation and Deep Learning for Hate Speech Detection","authors":["K Hemker - 2018"],"snippet":"Page 1. IMPERIAL COLLEGE LONDON DEPARTMENT OF COMPUTING Data Augmentation and Deep Learning for Hate Speech Detection Author: Konstantin Hemker Supervisor: Dr. Björn Schuller Submitted in partial fulfillment …","url":["https://www.imperial.ac.uk/media/imperial-college/faculty-of-engineering/computing/public/1718-pg-projects/HemkerK-Data-Augmentation-and-Deep-Learning.pdf"]}
-{"year":"2018","title":"Data Science with Vadalog: Bridging Machine Learning and Reasoning Data Science with Vadalog: Bridging Machine Learning and Reasoning","authors":["L Bellomarini, RR Fayzrakhmanov, G Gottlob…"],"snippet":"… including streams of structured or unstructured data from internal systems (eg, Enterprise Resource Planning, Workflow Management, and Supply Chain Management), external streams of unstructured data (eg, news and …","url":["https://www.groundai.com/project/data-science-with-vadalog-bridging-machine-learning-and-reasoning/"]}
-{"year":"2018","title":"Data Science with Vadalog: Bridging Machine Learning and Reasoning","authors":["L Bellomarini, RR Fayzrakhmanov, G Gottlob… - arXiv preprint arXiv …, 2018"],"snippet":"… Workflow Management, and Supply Chain Management), external streams of unstructured data (eg, news and social media feeds, and Common Crawl1), publicly … 1 http://commoncrawl.org/ 2 http://www.cyc.com/researchcyc …","url":["https://arxiv.org/pdf/1807.08712"]}
-{"year":"2018","title":"Data-Driven Language Understanding for Spoken Dialogue Systems","authors":["N Mrkšić - 2018"],"snippet":"Page 1. Data-Driven Language Understanding for Spoken Dialogue Systems Nikola Mrkšic Supervisor: Professor Steve Young Department of Engineering University of Cambridge This dissertation is submitted for the degree of Doctor …","url":["https://www.repository.cam.ac.uk/bitstream/handle/1810/276689/Mrksic-2018-PhD.pdf?sequence=1&isAllowed=y"]}
-{"year":"2018","title":"Debunking Fake News One Feature at a Time","authors":["M Tosik, A Mallia, K Gangopadhyay - arXiv preprint arXiv:1808.02831, 2018"],"snippet":"… cosine tdidf Cosine similarity between headline/body TF-IDF vectors Real doc similarity Cosine similarity between averaged headline/body Common Crawl vectors Real doc similarity intro Cosine similarity between averaged …","url":["https://arxiv.org/pdf/1808.02831"]}
-{"year":"2018","title":"Deep Extrofitting: Specialization and Generalization of Expansional Retrofitting Word Vectors using Semantic Lexicons","authors":["H Jo - arXiv preprint arXiv:1808.07337, 2018"],"snippet":"… The algorithm learns word vectors by making the dot products of word vectors equal to the logarithm of the words' probability of co-occurrence. We use glove.42B.300d trained on Common Crawl data, which has 1,917,493 unique words as 300-dimensional vectors …","url":["https://arxiv.org/pdf/1808.07337"]}
-{"year":"2018","title":"Deep neural network architecture for sentiment analysis and emotion identification of Twitter messages","authors":["D Stojanovski, G Strezoski, G Madjarov, I Dimitrovski… - Multimedia Tools and …, 2018"],"snippet":"… SSWE 50 10M 137K Tweets word2vec 300 100B 3M GoogleNews GloVe Crawl 300 840B 2.2M Common Crawl GloVe Twitter 200 20B 1.2M Tweets Corpora size is expressed in token count with the exception of SSWE where only the number of tweets is provided …","url":["https://link.springer.com/article/10.1007/s11042-018-6168-1"]}
-{"year":"2018","title":"Deep neural networks and distant supervision for geographic location mention extraction","authors":["A Magge, D Weissenbacher, A Sarker, M Scotch… - Bioinformatics, 2018"],"snippet":"AbstractMotivation. Virus phylogeographers rely on DNA sequences of viruses and the locations of the infected hosts found in public sequence databases like Gen.","url":["https://academic.oup.com/bioinformatics/article/34/13/i565/5045808"]}
-{"year":"2018","title":"Deep Neural Networks for Query Expansion using Word Embeddings","authors":["A Imani, A Vakili, A Montazer, A Shakery - arXiv preprint arXiv:1811.03514, 2018"],"snippet":"… and newswire articles. This would make them more suitable for use in newswire collections. Using word embeddings pre-trained using common crawl data may yield better performance in web corpora. To summarize, the proposed …","url":["https://arxiv.org/pdf/1811.03514"]}
-{"year":"2018","title":"Deep Semantic Learning for Conversational Agents","authors":["M Morisio, M Mensio - 2018"],"snippet":"Page 1. POLITECNICO DI TORINO Master of Science in Computer Engineering Master's Thesis Deep Semantic Learning for Conversational Agents Supervisor Prof. Maurizio Morisio Candidate Martino Mensio Tutor …","url":["https://www.researchgate.net/profile/Martino_Mensio/publication/324877915_Deep_Semantic_Learning_for_Conversational_Agents/links/5aeb205f45851588dd82cbc6/Deep-Semantic-Learning-for-Conversational-Agents.pdf"]}
-{"year":"2018","title":"Deep-BGT at PARSEME Shared Task 2018: Bidirectional LSTM-CRF Model for Verbal Multiword Expression Identification","authors":["G Berk, B Erden, T Güngör - Proceedings of the Joint Workshop on Linguistic …, 2018"],"snippet":"… We chose the DEPREL tag as a feature in order to capture dependencies at sentence level. We use pre-trained word embeddings released by fastText (Grave et al., 2018), which were trained on Common Crawl and Wikipedia …","url":["http://www.aclweb.org/anthology/W18-4927"]}
-{"year":"2018","title":"DeepPhish: Simulating Malicious AI","authors":["AC Bahnsen, I Torroledo, LD Camacho, S Villegas"],"snippet":"… Forest (RF) algorithm. Using a database comprised of one million legitimate URLs from the Common Crawl database, and one million phishing URLs from Phishtank, both models showed great statistical results. On one hand …","url":["https://albahnsen.com/wp-content/uploads/2018/05/deepphish-simulating-malicious-ai_submitted.pdf"]}
-{"year":"2018","title":"DEPARTMENT OF INFORMATICS M. Sc. IN COMPUTER SCIENCE","authors":["II Koutsikakis, P Malakasiotis, J Pavlopoulos"],"snippet":"Page 1. DEPARTMENT OF INFORMATICS M.Sc. IN COMPUTER SCIENCE M.Sc. Thesis “Toxicity Detection in User Generated Content” Ioannis-Ion Koutsikakis ΕΥ1606 Supervisors: Ion Androutsopoulos Prodromos Malakasiotis …","url":["http://nlp.cs.aueb.gr/theses/koutsikakis_msc_thesis.pdf"]}
-{"year":"2018","title":"Department of Informatics MSc in Computer Science","authors":["E Kyriakakis"],"snippet":"… tasks. Pretrained word vectors are usually trained in large corpora like Wikipedia or/and Common Crawl. Dozat et al. use 100D word2vec (Mikolov et al., 2013) pretrained (on Wikipedia and Common Crawl) word embeddings1. Dozat …","url":["http://www2.aueb.gr/users/ion/docs/kyriakakis_msc_thesis.pdf"]}
-{"year":"2018","title":"Deriving Word Embeddings Using Multilingual Transfer Learning for Opinion Mining","authors":["K Stavridis, G Koloniari, E Keramopoulos - 2018 South-Eastern European Design …, 2018"],"snippet":"… A word's context refers to its neighboring words in a text corpus. The Word2Vec model was trained on a huge corpus from Google (news), while the GloVe model has several variations based on the training input such as Wikipedia, Twitter and Common Crawl …","url":["https://ieeexplore.ieee.org/abstract/document/8544940/"]}
-{"year":"2018","title":"Detecting Misogynous Tweets","authors":["R Ahluwalia, E Shcherbinina, E Callow, A Nascimento… - Proceedings of the Third …, 2018"],"snippet":"… For comparison, we trained the same LSTM-networks using a fastText model trained on Common Crawl and Wikipedia text that maps words to 300-dimensional vectors [8]. Document-level embedding is an extension …","url":["http://ceur-ws.org/Vol-2150/AMI_paper3.pdf"]}
-{"year":"2018","title":"Detecting Signs of Dementia Using Word Vector Representations","authors":["B Mirheidari, D Blackburn, T Walker, A Venneri… - Proc. Interspeech 2018, 2018"],"snippet":"… We initially used the 'w2vec' model pre-trained on the Google News dataset (3 million vocabulary size, 100 billions words and 300 vector size) and the 'GloVe' model pre-trained on the Common Crawl (2.2 million vocabulary …","url":["https://www.isca-speech.org/archive/Interspeech_2018/pdfs/1764.pdf"]}
-{"year":"2018","title":"Detection of mergeable Wikipedia articles based on overlapping topics","authors":["R Wang, M Iwaihara"],"snippet":"… Google News 3M vocabulary 100 billion tokens Skip-gram Common Crawl 2.2M vocabulary 840 billion tokens Glove … The results are shown in Table 3 Table 3: Combination model result Combining embedding result(Common Crawl and Google News) accuracy …","url":["http://db-event.jpn.org/deim2018/data/papers/157.pdf"]}
-{"year":"2018","title":"Determination of content score","authors":["A Kagoshima, K Londenberg, F Xu - US Patent App. 10/325,033, 2019","A Kagoshima, K Londenberg, F Xu - US Patent App. 15/337,268, 2018"],"snippet":"… 310. The crawler module 310 may automatically crawl a network and acquire contents from one or more resources in the network, or acquire the contents from an open repository of web crawl data such as CommonCrawl.org …","url":["https://patentimages.storage.googleapis.com/56/46/d7/219015bf015761/US10325033.pdf","https://patents.google.com/patent/US20180121430A1/en"]}
-{"year":"2018","title":"Developing Chatbots","authors":["NK Manaswi - Deep Learning with Applications Using Python, 2018"],"snippet":"… 200. 6B. 400,000. GloVe. 10+10. GloVe. Wikipedia + Gigaword 5. 300. 6B. 400,000. GloVe. 10+10. GloVe. Common Crawl 42B. 300. 42B. 1.9M. GloVe. AdaGrad. GloVe. Common Crawl 840B. 300. 840B. 2.2M. GloVe. AdaGrad …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-3516-4_11"]}
-{"year":"2018","title":"Di-LSTM Contrast: A Deep Neural Network for Metaphor Detection","authors":["K Swarnkar, AK Singh - NAACL HLT 2018, 2018"],"snippet":"… variations of our model. We use 300-dimensional GloVe vectors (Pennington et al., 2014) trained on 6B Common Crawl corpus as word embeddings, setting the embeddings of out- of-vocabulary words to zero. To prevent overfit …","url":["http://www.cl.cam.ac.uk/~es407/papers/Fig-Lang2018-proceedings.pdf#page=127"]}
-{"year":"2018","title":"Differential Approach to Web-Corpus Construction","authors":["T Shavrina"],"snippet":"… This approach does not allow saving maximum of metatext information, since all the boilerplate is deleted, but it allows to gather a lot in a short time (example – Common Crawl). 2) fitted – all the materials from the listed thousands of URLs are crawled …","url":["http://www.dialog-21.ru/media/4261/shavrina.pdf"]}
-{"year":"2018","title":"Discovering Implicit Knowledge with Unary Relations","authors":["M Glass, A Gliozzo - Proceedings of the 56th Annual Meeting of the …, 2018"],"snippet":"… As part of the contributions for this paper, we release the benchmark to the re- search community providing the software needed to generate it from Common Crawl and DBpedia as an open source project2. As a baseline, we adapt a state of the art deep learning based …","url":["http://www.aclweb.org/anthology/P18-1147"]}
-{"year":"2018","title":"Discovering Novel Emergency Events in Text Streams","authors":["D Deviatkin, A Shelmanov, D Larionov - 2018"],"snippet":"… of emergency related messages by incorporating more labeled data from CrisisLex corpora [24] and by exploring: ● Various embeddings: word-level: fastText [16] (trained on our own corpus / pre-trained on English Wikipedia) …","url":["http://ceur-ws.org/Vol-2277/paper36.pdf"]}
-{"year":"2018","title":"Discovering Phonesthemes with Sparse Regularization","authors":["NF Liu, GA Levow, NA Smith"],"snippet":"… 3 Data For our experiments, we use 300-dimensional GloVe (Pennington et al., 2014) English word em- beddings trained on the cased Common Crawl. Many of the terms in the set of pretrained vectors are not English words …","url":["https://homes.cs.washington.edu/~nfliu/papers/liu+levow+smith.sclem2018.pdf"]}
-{"year":"2018","title":"Discriminator at SemEval-2018 Task 10: Minimally Supervised Discrimination","authors":["A Kulmizev, M Abdou, V Ravishankar, M Nissim - Proceedings of The 12th …, 2018"],"snippet":"… The VSM used in our final submission consisted of an av- erage of three sets of embeddings: GloVe word embeddings trained on Common Crawl (840B to- kens) (Pennington et al., 2014), the same GloVe embeddings post …","url":["http://www.aclweb.org/anthology/S18-1167"]}
-{"year":"2018","title":"Distinguishing attributes using text corpora and relational knowledge","authors":["R Speer, J Lowry-Duda"],"snippet":"… Unicode CLDR emoji data • word2vec, precomputed on Google News • GloVe, precomputed on the Common Crawl • fastText, customized to learn from parallel text, trained on OpenSubtitles 2016 We used the embeddings …","url":["http://blog.conceptnet.io/2018/06/naacl2018-poster.pdf"]}
-{"year":"2018","title":"Distributed Evaluation of Subgraph Queries Using Worstcase Optimal LowMemory Dataflows","authors":["K Ammar, F McSherry, S Salihoglu, M Joglekar - arXiv preprint arXiv:1802.03760, 2018"],"snippet":"Page 1. Distributed Evaluation of Subgraph Queries Using Worst-case Optimal Low-Memory Dataflows Khaled Ammar†, Frank McSherry‡, Semih Salihoglu†, Manas Joglekar♯ †University of Waterloo, ‡ETH Zürich,♯Google …","url":["https://arxiv.org/pdf/1802.03760"]}
-{"year":"2018","title":"Distributed Representations of Tuples for Entity Resolution","authors":["MESTS Joty, MON Tang - Proceedings of the VLDB Endowment, 2018","MESTS Joty, MON Tang - Proceedings of the VLDB Endowment,(11), 2018"],"snippet":"… is not always possible or feasible. For example, the popular GloVe dictionary is trained on the Common Crawl corpus, which is almost 2 TB requiring exorbitant computing re- sources. Given an unseen word, another simplistic …","url":["http://da.qcri.org/ntang/pubs/vldb18-deeper.pdf","https://pdfs.semanticscholar.org/334e/9eb88738671a5c9a53dea174586e885ec00b.pdf"]}
-{"year":"2018","title":"DL Team at SemEval-2018 Task 1: Tweet Affect Detection using Sentiment Lexicons and Embeddings","authors":["D Kravchenko, L Pivovarova - Proceedings of The 12th International Workshop on …, 2018"],"snippet":"… We use the following two models: 1. Common Crawl: 300-dimensional vectors trained on huge Internet corpus of 840 billion tokens and 2.2 million distinct words … GloVe Common Crawl 46.93 53.98 43.66 56.31 66.38 59.26 Google …","url":["http://www.aclweb.org/anthology/S18-1025"]}
-{"year":"2018","title":"DMCB at SemEval-2018 Task 1: Transfer Learning of Sentiment Classification Using Group LSTM for Emotion Intensity prediction","authors":["Y Kim, H Lee - Proceedings of The 12th International Workshop on …, 2018"],"snippet":"… We try five pre-trained word embeddings to choose the best one for the target model. Two are trained with GloVe (Pennington et al., 2014) using different data sets: one1 is trained with very large data in Common crawl, and the …","url":["http://www.aclweb.org/anthology/S18-1044"]}
-{"year":"2018","title":"Domain Adapted Word Embeddings for Improved Sentiment Classification","authors":["PK Sarma, YI Liang, WA Sethares - arXiv preprint arXiv:1805.04576, 2018","PKSYL William, A Sethares"],"snippet":"… Word embedding Dimension GloVe 100 word2vec 300 LSA 70 CCA-DA 68 KCCA-DA 68 GloVe common crawl 300 AdaptGloVe 300 … WG ∈ R|VG|×d2 be the matrix of generic word embeddings (obtained by, eg, running …","url":["https://ar5iv.labs.arxiv.org/html/1805.04576","https://arxiv.org/pdf/1805.04576"]}
-{"year":"2018","title":"Dropout during inference as a model for neurological degeneration in an image captioning network","authors":["B Li, R Zhang, F Rudzicz - arXiv preprint arXiv:1808.03747, 2018"],"snippet":"… The neural network model is implemented us- ing PyTorch (Paszke et al., 2017). We use GLoVe embeddings from SpaCy (Pennington et al., 2014; Honnibal and Johnson, 2015) trained on Common Crawl. The network was trained using Adam (Kingma and Ba, 2014) …","url":["https://arxiv.org/pdf/1808.03747"]}
-{"year":"2018","title":"Dynamic Meta-Embeddings for Improved Sentence Representations","authors":["D Kiela, C Wang, K Cho - Proceedings of the 2018 Conference on Empirical …, 2018"],"snippet":"… Figure 4 shows a similar breakdown for open versus closed class. The analysis allows us to make several interesting observations: it appears that this model prefers GloVe embeddings, followed by the two FastText …","url":["http://www.aclweb.org/anthology/D18-1176"]}
-{"year":"2018","title":"Effective Strategies for Combining Attention Mechanism with LSTM for Aspect-Level Sentiment Classification","authors":["K Shuang, X Ren, H Guo, J Loo, P Xu - Proceedings of SAI Intelligent Systems …, 2018"],"snippet":"… 346. Neg. 807. 196. 870. 128. 1560. 173. Total. 3608. 1120. 2328. 638. 6248. 692. 4.2 Experimental Settings. In the experiments, pre-trained word vectors are trained by Glove on Common Crawl Corpus size and they are used to …","url":["https://link.springer.com/chapter/10.1007/978-3-030-01057-7_62"]}
-{"year":"2018","title":"Efficient and Robust Question Answering from Minimal Context over Documents","authors":["S Min, V Zhong, R Socher, C Xiong - arXiv preprint arXiv:1805.08092, 2018"],"snippet":"Page 1. Efficient and Robust Question Answering from Minimal Context over Documents Sewon Min1∗, Victor Zhong2, Richard Socher2, Caiming Xiong2 Seoul National University1, Salesforce Research2 shmsw25@snu …","url":["https://arxiv.org/pdf/1805.08092"]}
-{"year":"2018","title":"Efficient Unsupervised Word Sense Induction, Disambiguation and Embedding","authors":["BH Soleimani, H Naderi, S Matwin"],"snippet":"… as sentiment analysis, translation, etc. 2 Proposed Method Similar to word embeddings, sense embeddings should also be learned from a large text corpus such as Wikipedia or Common Crawl data. In our method, we first calculate …","url":["https://bigdata1.research.cs.dal.ca/behrouz/publication/nipsw2018/NIPSW2018_EfficientWordSenseDisambiguation.pdf"]}
-{"year":"2018","title":"Elastic ChatNoir: Search Engine for the ClueWeb and the Common Crawl","authors":["J Bevendorff, B Stein, M Hagen, M Potthast - European Conference on Information …, 2018"],"snippet":"Abstract Elastic ChatNoir (Search: www. chatnoir. eu Code: www. github. com/chatnoir-eu) is an Elasticsearch-based search engine offering a freely accessible search interface for the two ClueWeb corpora and the Common Crawl …","url":["https://link.springer.com/chapter/10.1007/978-3-319-76941-7_83"]}
-{"year":"2018","title":"EmbNum: Semantic labeling for numerical values with deep metric learning","authors":["P Nguyen, K Nguyen, R Ichise, H Takeda - arXiv preprint arXiv:1807.01367, 2018"],"snippet":"… In a study of Lehmberg et al. [1], 233 million table data resources have extracted from the July 2015 version of the Common Crawl3. Additionally, Mitlohner et al … Table schema is 3 http://commoncrawl.org/ arXiv:1807.01367 …","url":["https://arxiv.org/pdf/1807.01367"]}
-{"year":"2018","title":"Emergency Vocabulary","authors":["DM Nemeskey, A Kornai - Information Systems Frontiers"],"snippet":"… 2004) and CommonCrawl.1 In the normal course of events, emergencies like natural disasters, military escalation, epidemic outbreaks etc … 5 Originally, the embedding contains 2,196,017 words with the associated 300-dimension …","url":["https://link.springer.com/article/10.1007/s10796-018-9843-x"]}
-{"year":"2018","title":"Emotion Detection and Classification in a Multigenre Corpus with Joint Multi-Task Deep Learning","authors":["S Tafreshi, M Diab - Proceedings of the 27th International Conference on …, 2018"],"snippet":"… Common training set for word embedding models are wiki+news, news, tweets, and common crawl, and the methods are Word2Vec (Mikolov et al., 2013), GloVe (Pennington et al., 2014), and fasText (Bojanowski et al., 2016) …","url":["http://www.aclweb.org/anthology/C18-1246"]}
-{"year":"2018","title":"EmotionLines: An Emotion Corpus of Multi-Party Conversations","authors":["SY Chen, CC Hsu, CC Kuo, LW Ku - arXiv preprint arXiv:1802.08379, 2018"],"snippet":"… Given a utterance of M words, the one-hot encoding for utterance words is denoted by U = {w1, w2, w3,..., wM }. We first embed the words to the word embedding , which is publicly available 300-dimensional GloVe pre-trained on Common Crawl data (Pennington et al., 2014) …","url":["https://arxiv.org/pdf/1802.08379"]}
-{"year":"2018","title":"EmotionX-JTML: Detecting emotions with Attention","authors":["J Torres - Proceedings of the Sixth International Workshop on …, 2018"],"snippet":"… Each column of the matrix stores the em- beddings of the corresponding word, resulting in d dimensional input matrix M ∈ RM×d. The weights of the word embeddings use the 300dimensional GloVe Embeddings …","url":["http://www.aclweb.org/anthology/W18-3510"]}
-{"year":"2018","title":"End-to-End Retrieval in Continuous Space","authors":["D Gillick, A Presta, GS Tomar - arXiv preprint arXiv:1811.08008, 2018"],"snippet":"… embeddings using Inverse Document Frequency (IDF)4, and try 3 different settings for pre-training: standard word2vec, word2vec trained with the Paralex dataset (closer to the question domain), and Glove (Pennington …","url":["https://arxiv.org/pdf/1811.08008"]}
-{"year":"2018","title":"Energy-Aware Data Throughput Optimization for Next Generation Internet","authors":["T Kosar, I Alan, MF Bulut - Information Sciences, 2018"],"snippet":"… Three different representative datasets were used during experiments in order to capture the throughput and power consumption differences based on the dataset type: (i) the HTML dataset is a set of raw HTML files from the …","url":["https://www.sciencedirect.com/science/article/pii/S0020025518307874"]}
-{"year":"2018","title":"Engaging English Speaking Facebook Users in an Anti-ISIS Awareness Campaign","authors":["A Shajkovci - Journal of Strategic Security, 2018"],"snippet":"… STRONG VERY LOW 0 133 able, act, adult, advantage, aggressive, agreement, army, assistance, attack, aware, benefit, b . . . WEAK LOW 16 41 admit, apologize, ashamed, bum, common, crawl, death, depression, desperate, die, disgrace, dis …","url":["https://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=1679&context=jss"]}
-{"year":"2018","title":"English-Basque Statistical and Neural Machine Translation","authors":["IJ Unanue, LG Arratibel, EZ Borzeshi, M Piccardi - Proceedings of the Eleventh …, 2018"],"snippet":"… For English, we have used the available CommonCrawl pre-trained embeddings3. We have evaluated the use of these embeddings in two different ways: maintaining them fixed during both training and testing (f-emb) …","url":["http://www.aclweb.org/anthology/L18-1141"]}
-{"year":"2018","title":"Entity-Oriented Search","authors":["K Balog - 2018"],"snippet":"Page 1. The Information Retrieval Series Krisztian Balog EntityOriented Search Page 2. The Information Retrieval Series Volume 39 Series Editors ChengXiang Zhai Maarten de Rijke Editorial Board Nicholas J. Belkin Charles …","url":["https://link.springer.com/content/pdf/10.1007/978-3-319-93935-3.pdf"]}
-{"year":"2018","title":"ERASeD: Exposing Racism And Sexism using Deep Learning","authors":["S Paul, J Bhaskaran","SPJ Bhaskaran"],"snippet":"… We tried out the following methods: • Pretrained Embeddings – GloVe (Twitter) – GloVe (Common Crawl) The biggest drawback of using pretrained embeddings is that 20% of the words we see in the dataset from Twitter do not have embeddings …","url":["http://web.stanford.edu/class/cs224n/reports/6908288.pdf","https://pdfs.semanticscholar.org/7d21/50c3d9028b6b58fb7fb01d70e4ffe08d2c58.pdf"]}
-{"year":"2018","title":"eSCAPE: a Large-scale Synthetic Corpus for Automatic Post-Editing","authors":["M Negri, M Turchi, R Chatterjee, N Bertoldi - arXiv preprint arXiv:1803.07274, 2018"],"snippet":"… It consists of 4.3 million instances created by first filtering a subset of IT-related sentences from the German Common Crawl corpus6, and then by using two English–German and German–English PBMT systems trained on …","url":["https://arxiv.org/pdf/1803.07274"]}
-{"year":"2018","title":"Evaluating MT for massive open online courses","authors":["S Castilho, J Moorkens, F Gaspari, R Sennrich, A Way… - Machine Translation, 2018"],"snippet":"… 2012) as distributed in OPUS (Tiedemann 2012) – OPUS European Central Bank (ECB) – OPUS European Medicines Agency (EMEA) – OPUS EU Bookshop – OPUS OpenSubtitles5 – WMT News Commentary – WMT …","url":["https://link.springer.com/article/10.1007/s10590-018-9221-y"]}
-{"year":"2018","title":"Evaluating the psychological plausibility of word2vec and GloVe distributional semantic models","authors":["I Kajic, C Eliasmith"],"snippet":"… In this work, we use pre-trained GloVe and word2vec vectors. GloVe vectors were trained using the Common Crawl dataset containing approximately 840 billion word tokens. Word2vec vectors were trained on the Google News …","url":["http://compneuro.uwaterloo.ca/files/publications/kajic.2018a.pdf"]}
-{"year":"2018","title":"Evaluation of High-Dimensional Word Embeddings using Cluster and Semantic Similarity Analysis","authors":["S Atakishiyev - 2018"],"snippet":"Page 1. Evaluation of High-Dimensional Word Embeddings using Cluster and Semantic Similarity Analysis by Shahin Atakishiyev A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science …","url":["https://www.researchgate.net/profile/Shahin_Atakishiyev/publication/325945300_Evaluation_of_High-Dimensional_Word_Embeddings_using_Cluster_and_Semantic_Similarity_Analysis/links/5b2de0ac0f7e9b0df5be7f0d/Evaluation-of-High-Dimensional-Word-Embeddings-using-Cluster-and-Semantic-Similarity-Analysis.pdf"]}
-{"year":"2018","title":"Evaluation of sentence embeddings in downstream and linguistic probing tasks","authors":["CS Perone, R Silveira, TS Paula - arXiv preprint arXiv:1806.06259, 2018"],"snippet":"… 1024 Word2Vec (BoW, Google news) Self-supervised 300 p-mean (monolingual) – 3600 FastText (BoW, Common Crawl) Self-supervised 300 GloVe (BoW, Common Crawl) Self-supervised 300 USE (DAN) Supervised 512 USE (Transformer) Supervised 512 …","url":["https://arxiv.org/pdf/1806.06259"]}
-{"year":"2018","title":"Evidence of semantic processing difficulty in naturalistic reading","authors":["C Shain, R Futrell, M van Schijndel, E Gibson…"],"snippet":"… a novel measure — incremental semantic relatedness — for three naturalistic reading time corpora: Dundee [12], UCL [7], and Natural Stories [9]. In particular, we embedded all three corpora using GloVe vectors [20] pretrained …","url":["https://vansky.github.io/assets/pdf/shain_etal-2018-cuny.pdf"]}
-{"year":"2018","title":"Existing Web Archives","authors":["P Webster - The SAGE Handbook of Web History. London: Sage, 2018"]}
-{"year":"2018","title":"Explicit Ensemble Attention Learning for Improving Visual Question Answering","authors":["V Lioutas, N Passalis, A Tefas - Pattern Recognition Letters, 2018"],"snippet":"Visual Question Answering (VQA) is among the most difficult multi-modal problems as it requires a machine to be able to properly understand a question about ar.","url":["https://www.sciencedirect.com/science/article/pii/S0167865518301600"]}
-{"year":"2018","title":"Explicit Retrofitting of Distributional Word Vectors","authors":["G Glavaš, I Vulić - Proceedings of the 56th Annual Meeting of the …, 2018"],"snippet":"… al., 2013) using the Skip-Gram algorithm with Negative Sampling (SGNS) (Mikolov et al., 2013b) by Levy and Goldberg (2014b), using the context windows of size 2; (2) GLOVE-CC – vectors trained with the GloVe (Pennington …","url":["http://www.aclweb.org/anthology/P18-1004"]}
-{"year":"2018","title":"Exploiting Efficient and Effective Lazy Semi-Bayesian Strategies for Text Classification","authors":["F Viegas, L Rocha, E Resende, T Salles, W Martins… - Neurocomputing, 2018"],"snippet":"Automatic Document Classification (ADC) has become the basis of many important applications, eg, authorship identification, opinion mining, spam filtering, co.","url":["https://www.sciencedirect.com/science/article/pii/S0925231218304636"]}
-{"year":"2018","title":"Exploring and Mitigating Gender Bias in GloVe Word Embeddings","authors":["MFLC Vera"],"snippet":"… and the cosine similarity. Finally, to show that gender 100 biases exist across different types of embeddings, we use both the GloVe word embeddings 101 pretrained on Wiki and pretrained on Common Crawl. 102 Plotting all ���","url":["https://pdfs.semanticscholar.org/512f/ccca0d3a5f454d5360d32d48e3d4d5ddd578.pdf"]}
-{"year":"2018","title":"Exploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural Networks","authors":["L Song, Z Wang, M Yu, Y Zhang, R Florian, D Gildea - arXiv preprint arXiv …, 2018"],"snippet":"Page 1. Exploring Graph-structured Passage Representation for Multi-hop Reading Comprehension with Graph Neural Networks Linfeng Song1∗, Zhiguo Wang2†, Mo Yu2†, Yue Zhang3, Radu Florian2 and Daniel Gildea1 …","url":["https://arxiv.org/pdf/1809.02040"]}
-{"year":"2018","title":"Exploring Neural Methods for Parsing Discourse Representation Structures","authors":["R van Noord, L Abzianidze, A Toral, J Bos - arXiv preprint arXiv:1810.12579, 2018"],"snippet":"… We simply add the word embedding vector after the sequence of character-embeddings for each word in the input and still initialise these embeddings using the pre-trained GloVe embeddings. 6The Common …","url":["https://arxiv.org/pdf/1810.12579"]}
-{"year":"2018","title":"Exploring Optimism and Pessimism in Twitter Using Deep Learning","authors":["C Caragea, LP Dinu, B Dumitru"],"snippet":"… We used mini-batches of 40 samples. Dropout rate was set to 0.5 and the classifier's last three layers have 300, 200, and 100 neurons. We used GloVe vectors (Pennington et al., 2014) trained on Common Crawl …","url":["https://www.cs.uic.edu/~cornelia/papers/emnlp18_op.pdf"]}
-{"year":"2018","title":"Exploring speed and memory trade-offs for achieving optimum performance on SQuAD dataset","authors":["R Aksitov"],"snippet":"… bidirectional in this architecture was not producing any measurable gains for some time, until I also switched to Common Crawl embedding with … When I switched to CommonCrawl embeddings, I have found out that Tensorflow …","url":["http://web.stanford.edu/class/cs224n/reports/6909117.pdf"]}
-{"year":"2018","title":"Exploring the importance of context and embeddings in neural NER models for task-oriented dialogue systems","authors":["P Jayarao, C Jain, A Srivastava - arXiv preprint arXiv:1812.02370, 2018"],"snippet":"… We used the publicly available Glove embeddings1 (Pennington et al., 2014) trained on Wikipedia 2014 corpus with dimension sizes 50 (G50W) and 300 (G300W) and another 300 di- mensional embeddings (G300C) trained on …","url":["https://arxiv.org/pdf/1812.02370"]}
-{"year":"2018","title":"ExtRA: Extracting Prominent Review Aspects from Customer Feedback","authors":["Z Luo, S Huang, FF Xu, BY Lin, H Shi, K Zhu - … of the 2018 Conference on Empirical …, 2018"],"snippet":"Page 1. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 3477–3486 Brussels, Belgium, October 31 - November 4, 2018. c 2018 Association for Computational Linguistics 3477 …","url":["http://www.aclweb.org/anthology/D18-1384"]}
-{"year":"2018","title":"Extrofitting: Enriching Word Representation and its Vector Space with Semantic Lexicons","authors":["H Jo, SJ Choi - arXiv preprint arXiv:1804.07946, 2018"],"snippet":"… 3 Experiment Data 3.1 Pretrained Word Vectors GloVe (Pennington et al., 2014) has lots of variations in respect to word dimension, number of to- kens, and train sources. We used glove.6B trained on Wikipedia+Gigawords …","url":["https://arxiv.org/pdf/1804.07946"]}
-{"year":"2018","title":"Facebook Use of Sensitive Data for Advertising in Europe","authors":["JG Cabañas, Á Cuevas, R Cuevas - arXiv preprint arXiv:1802.05030, 2018"],"snippet":"Page 1. arXiv:1802.05030v1 [cs.SI] 14 Feb 2018 Facebook Use of Sensitive Data for Advertising in Europe José González Caba˜nas Universidad Carlos III de Madrid jgcabana@it.uc3m.es ´Angel Cuevas Universidad Carlos III de Madrid acrumin@it.uc3m.es …","url":["https://arxiv.org/pdf/1802.05030"]}
-{"year":"2018","title":"Facilitating mapping of control policies to regulatory documents","authors":["SB Tirumala, A Jagmohan, E Khabiri, TH Li… - US Patent App. 15/349,766, 2018"],"snippet":"… dictionary 206). The global corpora 203 can comprise a general internet-based collection of texts derived from various sources (eg, GUTENBERG®, REUTERS®, COMMON CRAWL®, and/or GOOGLE NEWS®). The regulatory …","url":["https://patents.google.com/patent/US20180137107A1/en"]}
-{"year":"2018","title":"Fast Dictionary-Based Compression for Inverted Indexes","authors":["GE Pibiri, M Petri, A Moffat - 2019"],"snippet":"… We use the standard Gov2 collection containing 426 GiB of text; and CCNEWS, an English subset of the freely available NEWS subset of the CommonCrawl1, consisting of news articles in the period 09/01/16 to …","url":["http://pages.di.unipi.it/pibiri/papers/WSDM19.pdf"]}
-{"year":"2018","title":"Filtering and Mining Parallel Data in a Joint Multilingual Space","authors":["H Schwenk - arXiv preprint arXiv:1805.09822, 2018"],"snippet":"… only a limited amount of parallel training data is available (4.5M sentences). 2.1M are high quality human translations and 2.4M are crawled and aligned sentences (Common Crawl corpus). As in other works, we use …","url":["https://arxiv.org/pdf/1805.09822"]}
-{"year":"2018","title":"Fine-grained Entity Typing through Increased Discourse Context and Adaptive Classification Thresholds","authors":["S Zhang, K Duh, B Van Durme - arXiv preprint arXiv:1804.08000, 2018"],"snippet":"… 3.2 Hyperparameters We use open-source GloVe vectors (Pennington et al., 2014) trained on Common Crawl 840B with 300 dimensions to initialize word embeddings used in all encoders. All weight parameters are sampled from U(−0.01,0.01) …","url":["https://arxiv.org/pdf/1804.08000"]}
-{"year":"2018","title":"Focused Crawling Through Reinforcement Learning","authors":["M Han, PH Wuillemin, P Senellart - International Conference on Web Engineering, 2018"],"snippet":"… efficiently crawl relevant pages. In future work, we hope to evaluate our method in larger and various datasets, such as full English Wikipedia and dataset from the site http://commoncrawl.org/, etc. Another challenging possibility …","url":["https://link.springer.com/chapter/10.1007/978-3-319-91662-0_20"]}
-{"year":"2018","title":"Follow The Money: Online Piracy and Self-Regulation in the Advertising Industry","authors":["M Batikas, J Claussen, C Peukert - 2018"],"snippet":"… Get HTML source code files from Commoncrawl and parse them (∼500,000 webpages) … 10 Page 14. Figure 2: Timing of data snapshots 2016w7 2016w15 2016w23 2016w31 2016w39 2016w47 2017w3 2017w11 Note: Available data snapshots from Common Crawl …","url":["http://www.cesifo-group.de/DocDL/cesifo1_wp6852.pdf"]}
-{"year":"2018","title":"Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities: Supplementary Material","authors":["H Pham, PP Liang, T Manzini, LP Morency, B Poczós"],"snippet":"… visual and acoustic modalities. Language: We used 300 dimensional Glove word embeddings trained on 840 billion tokens from the common crawl dataset (Pennington, Socher, and Manning, 2014). These word embeddings …","url":["http://www.cs.cmu.edu/~pliang/papers/aaai2019_seq2seq_supp.pdf"]}
-{"year":"2018","title":"Freezing Subnetworks to Analyze Domain Adaptation in Neural Machine Translation","authors":["B Thompson, H Khayrallah, A Anastasopoulos… - arXiv preprint arXiv …, 2018"],"snippet":"… 1 For De–En and Ru– En, we also use data from WMT 2017 (Bojar et al., 2017),2 which contains data from several sources: Europarl (parliamentary proceedings) (Koehn, 2005),3 News Commentary (political and economic …","url":["https://arxiv.org/pdf/1809.05218"]}
-{"year":"2018","title":"From Mad Men to Maths Men: Concentration and Buyer Power in Online Advertising","authors":["F Decarolis, G Rovigatti"],"snippet":"Page 1. From Mad Men to Maths Men: Concentration and Buyer Power in Online Advertising ∗ Francesco Decarolis Gabriele Rovigatti PRELIMINARY AND INCOMPLETE PLEASE DO NOT CIRCULATE Abstract This paper …","url":["https://www.tse-fr.eu/sites/default/files/TSE/documents/ChaireJJL/Digital-Economics-Conference/Conference/decarolis_franceso.pdf"]}
-{"year":"2018","title":"FROM TEXT CLASSIFICATION TO IMAGE CLUSTERING, PROBLEMS LESS OPTIMIZED","authors":["A Herandi - 2018"],"snippet":"… We have used similar models for our BiLSTM and BiGRU models. We are using two layers stacked on top of each other and use only the last output from each direction from the second layer for our inference, because we are 1 http://commoncrawl.org/ Page 18. 10 …","url":["https://uta-ir.tdl.org/uta-ir/bitstream/handle/10106/27492/HERANDI-THESIS-2018.pdf?sequence=1"]}
-{"year":"2018","title":"Full text document","authors":["Z Bouraoui, S Jameel, S Schockaert"],"snippet":"… set3 (SG-GN). We also use two embeddings that have been learned with GloVe, one from the same english Wikipedia dump (GloVe-Wiki) and one from the 840B words Common Crawl data set4 (GloVe-CC). For relations with …","url":["https://kar.kent.ac.uk/67263/1/Shoaib-COLING-2018.pdf"]}
-{"year":"2018","title":"Fully Convolutional Speech Recognition","authors":["N Zeghidour, Q Xu, V Liptchinsky, N Usunier… - arXiv preprint arXiv …, 2018"],"snippet":"… 5.83 12.69 (12k training hours AM, common crawl LM) Sequence-to- sequence [9] 3.54 11.52 3.82 12.76 … (speaker adaptation, 3k acoustic states) DeepSpeech 2 [7] 5 3.6 (12k training hours AM, common crawl LM) Frontend …","url":["https://arxiv.org/pdf/1812.06864"]}
-{"year":"2018","title":"Garbage In, Garbage Out","authors":["H Sanders"],"snippet":"… VirusTotal 10 million URLs from January 2017 ≈ 4% malware CommonCrawl & PhishTank Sophos 10 million internal URLs from January … VirusTotal 10 million URLs from January 2017 ≈ 4% malware CommonCrawl & Phishtank …","url":["https://pdfs.semanticscholar.org/c940/a2144b1e5cc89bbeb9003b5f3541e50fc9e1.pdf"]}
-{"year":"2018","title":"Gated Convolutional Neural Network for Sentence Matching","authors":["P Chen, W Guo, Z Chen, J Sun, L You - memory, 2018"],"snippet":"… 3.2. Training We implement our models on Tensorflow [26] and train them on an Nvidia GeForce GTX 1080 GPU. We initialize the word em- beddings with 300-dimensional GloVe word vectors pretrained from 840B Common Crawl corpus [19] …","url":["https://www.isca-speech.org/archive/Interspeech_2018/pdfs/0070.pdf"]}
-{"year":"2018","title":"Generalizing and Improving Bilingual Word Embedding Mappings with a Multi-Step Framework of Linear Transformations","authors":["M Artetxe, G Labaka, E Agirre - 2018"],"snippet":"… The corpora used consisted of 2.8 billion words for English (ukWaC + Wikipedia + BNC), 1.6 billion words for Italian (itWaC), 0.9 billion words for German (SdeWaC), and 2.8 billion words for Finnish (Common Crawl from WMT 2016) …","url":["http://ixa.eus/sites/default/files/dokumentuak/11455/aaai18.pdf"]}
-{"year":"2018","title":"Generating Wikipedia by Summarizing Long Sequences","authors":["PJ Liu, M Saleh, E Pot, B Goodrich, R Sepassi, L Kaiser… - arXiv preprint arXiv …, 2018"],"snippet":"… To encourage further research on large-scale summarization, we will release the URLs used in our experiments (the Wikipedia URL as well as the URLs of its references) that are available as part of the CommonCrawl dataset4, which is freely available for download …","url":["https://arxiv.org/pdf/1801.10198"]}
-{"year":"2018","title":"Generation of code from text description with syntactic parsing and Tree2Tree model","authors":["A Stehnii - 2017"],"snippet":"Page 1 …","url":["http://www.er.ucu.edu.ua/bitstream/handle/1/1191/Stehnii-master-thesis.pdf?sequence=1&isAllowed=y"]}
-{"year":"2018","title":"Global normalized reader systems and methods","authors":["J RAIMAN, J Miller - US Patent App. 15/706,486, 2018"],"snippet":"… prediction. The hidden dimensions of all recurrent layers were 200. In embodiments, the 300 dimensional 8.4B token Common Crawl GloVe vectors were used. Words missing from the Common Crawl vocabulary were set to zero. In …","url":["https://patentimages.storage.googleapis.com/de/9c/d5/dabff582992ff9/US20180300312A1.pdf"]}
-{"year":"2018","title":"GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding","authors":["A Wang, A Singh, J Michael, F Hill, O Levy… - arXiv preprint arXiv …, 2018"],"snippet":"Page 1. arXiv:1804.07461v1 [cs.CL] 20 Apr 2018 GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Wang1, Amanpreet Singh1, Julian Michael2, Felix Hill3, Omer Levy2, and Samuel R. Bowman1 …","url":["https://arxiv.org/pdf/1804.07461"]}
-{"year":"2018","title":"GraphIt-A High-Performance DSL for Graph Analytics","authors":["Y Zhang, M Yang, R Baghdadi, S Kamil, J Shun… - arXiv preprint arXiv …, 2018"],"snippet":"Page 1. GraphIt – A High-Performance DSL for Graph Analytics YUNMING ZHANG, MIT CSAIL MENGJIAO YANG, MIT CSAIL RIYADH BAGHDADI, MIT CSAIL SHOAIB KAMIL, Adobe Research JULIAN SHUN, MIT CSAIL SAMAN AMARASINGHE, MIT CSAIL …","url":["https://arxiv.org/pdf/1805.00923"]}
-{"year":"2018","title":"Harnessing NLG to Create Finnish Poetry Automatically","authors":["M Hämäläinen"],"snippet":"… This is 3The semantic repository can be browsed and downloaded on https://mikakalevi. com/semfi/ 4http://commoncrawl.org/ due to the Finnish agreement rule which requires the case of an adjective attribute to agree with the case of the noun …","url":["http://computationalcreativity.net/iccc2018/sites/default/files/papers/ICCC_2018_paper_6.pdf"]}
-{"year":"2018","title":"Heuristics-based Query Reordering for Federated Queries in SPARQL 1.1 and SPARQL-LD","authors":["T Yannakis, P Fafalios, Y Tzitzikas"],"snippet":"… The question is: how 3 http://commoncrawl.org/ 4 http://webdatacommons. org/structureddata/2016-10/stats/stats.html Page 2. 2 Thanos Yannakis, Pavlos Fafalios, and Yannis Tzitzikas can we efficiently query this large, distributed …","url":["http://l3s.de/~fafalios/files/pubs/fafalios2018_QuWeDa.pdf"]}
-{"year":"2018","title":"HFL-RC System at SemEval-2018 Task 11: Hybrid Multi-Aspects Model for Commonsense Reading Comprehension","authors":["Z Chen, Y Cui, W Ma, S Wang, T Liu, G Hu - arXiv preprint arXiv:1803.05655, 2018"],"snippet":"… Page 4. 3 Experiments 3.1 Experimental Setups We listed the main hyper-parameters of our model in Table 1. The word embeddings are initialized by the pre-trained GloVe word vectors (Common Crawl, 6B tokens, 100-dimension) (Pennington et al., 2014) …","url":["https://arxiv.org/pdf/1803.05655"]}
-{"year":"2018","title":"Hierarchical Neural Networks for Sequential Sentence Classification in Medical Scientific Abstracts","authors":["D Jin, P Szolovits - arXiv preprint arXiv:1808.06161, 2018"],"snippet":"… pus of Wikipedia 2014 + Gigaword 57 (denoted as “Glove-wiki”), fastText embeddings pre-trained on Wikipedia8 (denoted as “FastText-wiki”), and fastText embeddings initialized with the standard GloVe Common Crawl …","url":["https://arxiv.org/pdf/1808.06161"]}
-{"year":"2018","title":"Historical Web as a Tool for Analyzing Social Change","authors":["R Schroeder, N Brügger, J Cowls - Second International Handbook of Internet …, 2018"],"snippet":"… are themselves responsible for the curation and selection of what to archive (eg, Archive-It), and, second, publicly available collections, archived by “amateurs,” with no cultural heritage obligations (eg, The Archive Team …","url":["https://link.springer.com/content/pdf/10.1007/978-94-024-1202-4_24-1.pdf"]}
-{"year":"2018","title":"Hourglass-Incremental Graph Processing on Heterogeneous Infrastructures","authors":["P Joaquim"],"snippet":"… On June 2016 Facebook reportes[13] an average of 1.13 billion daily active users. Another example is the largest World Wide Web hyperlink graph made publicly available by Common Crawl[14] that has over 3.5 billion web pages and 128 billion hyperlinks between them …","url":["https://pdfs.semanticscholar.org/92bf/f88f18c632327f7d503c9a7ab72cb433b7c1.pdf"]}
-{"year":"2018","title":"How to Do Things with Translations","authors":["J Jacobs - 2018"],"snippet":"… 17 Page 18. as the Common Crawl corpus19 often have vocabulary sizes v exceeding 2 million, thus re … 19http://commoncrawl.org/ 20For a comprehensive survey of the most popular embedding algorithms, see Goldberg (2017). 18 Page 19 …","url":["https://www-cs.stanford.edu/~jjacobs3/Jacobs-How_to_Do_Things_with_Translations.pdf"]}
-{"year":"2018","title":"Human versus automatic quality evaluation of NMT and PBSMT","authors":["D Shterionov, R Superbo, P Nagle, L Casanellas… - Machine Translation, 2018"],"snippet":"… 2015) is built with TED talks, EPPS, news commentary,8 and Common Crawl data; the NMT system they compare to (Luong and Manning 2015) is a pre-trained NMT system that was further improved with data provided by the IWSLT2015 organizers …","url":["https://link.springer.com/article/10.1007/s10590-018-9220-z"]}
-{"year":"2018","title":"Hybrid Self-Attention Network for Machine Translation","authors":["K Song, T Xu, F Peng, J Lu - arXiv preprint arXiv:1811.00253, 2018"],"snippet":"… 2016) shared vocabulary. WMT14 English-German WMT14 EnglishGerman dataset (Buck, Heafield, and van Ooyen 2014) comprises about 4.5 million sentence pairs that are extracted from three corpora: Common …","url":["https://arxiv.org/pdf/1811.00253"]}
-{"year":"2018","title":"Hypothesis Only Baselines in Natural Language Inference","authors":["A Poliak, J Naradowsky, A Haldar, R Rudinger… - arXiv preprint arXiv …, 2018"],"snippet":"… Following Conneau et al. (2017), we map the resulting to- kens to 300-dimensional GloVe vectors (Pennington et al., 2014) trained on 840 billion tokens from the Common Crawl, using the GloVe OOV vector for unknown words …","url":["https://arxiv.org/pdf/1805.01042"]}
-{"year":"2018","title":"Identifying Semantic Divergences in Parallel Text without Annotations","authors":["Y Vyas, X Niu, M Carpuat - arXiv preprint arXiv:1803.11112, 2018","YVXNM Carpuat"],"snippet":"… On the CommonCrawl test set, the examples with disagreement are more diverse, ranging from Page 7. Divergence Detection OpenSubtitles Common Crawl Approach +P +R +F -P -R -F Overall F +P +R +F -P -R …","url":["https://arxiv.org/pdf/1803.11112","https://deeplearn.org/arxiv/30360/identifying-semantic-divergences-in-parallel-text-without-annotations"]}
-{"year":"2018","title":"Identifying the Most Effective Feature Category in Machine Learning-based Phishing Website Detection","authors":["CL Tan, KL Chiew, N Musa, DHA Ibrahim - International Journal of Engineering & …, 2018"],"snippet":"… [31] “Common Crawl”, available online: http://commoncrawl.org/, last visit: 10.01.2017. [32] Selenium Project (2017), “Selenium WebDriver”, available online: http://www.seleniumhq.org/projects/webdriver/, last visit: 10.01.2017 …","url":["https://www.researchgate.net/profile/Choon_Lin_Tan/publication/329554643_Identifying_the_Most_Effective_Feature_Category_in_Machine_Learning-based_Phishing_Website_Detection/links/5c0f183e299bf139c74fb929/Identifying-the-Most-Effective-Feature-Category-in-Machine-Learning-based-Phishing-Website-Detection.pdf"]}
-{"year":"2018","title":"Improved Text Analytics Transfer Learning","authors":["M Riemer, E Khabiri, R Goodwin - 2018"],"snippet":"… Our GRU model was fed a sequence of fixed 300 dimensional Glove vectors (Pennington et al., 2014), representing words based on analysis of 840 billion words from a common crawl of the internet, as the input xt for all tasks …","url":["https://openreview.net/pdf?id=HyggjiiMz6m"]}
-{"year":"2018","title":"Improving Cross-Lingual Word Embeddings by Meeting in the Middle","authors":["Y Doval, J Camacho-Collados, L Espinosa-Anke… - arXiv preprint arXiv …, 2018"],"snippet":"… For Italian and German, we use the itWaC and sdeWaC corpora from the WaCky project (Baroni et al., 2009), containing 2 and 0.8 billion words, respectively.2 Lastly, for Finnish, we use the Common Crawl monolingual …","url":["https://arxiv.org/pdf/1808.08780"]}
-{"year":"2018","title":"Improving Machine Translation of Educational Content via Crowdsourcing","authors":["M Behnke, AVM Barone, R Sennrich, V Sosoni…"],"snippet":"… et al., 2012) as distributed in OPUS (Tiedemann, 2012); ● OPUS European Central Bank (ECB); ● OPUS European Medicines Agency (EMEA); ● OPUS EU Bookshop; ● OPUS OpenSubtitles 7; ● WMT News Commentary; ● …","url":["http://www.lrec-conf.org/proceedings/lrec2018/pdf/855.pdf"]}
-{"year":"2018","title":"Improving Neural Machine Translation with External Information","authors":["J Helcl"],"snippet":"… image descriptions, we selected similar sentence pairs from the parallel SDEWAC corpus (Faaß and Eckart, 2013) and German parts of WMT parallel corpora, such as EU Bookshop (Skadinš et al., 2014), News Commentary (Tiedemann, 2012), and CommonCrawl (Smith et al …","url":["https://pdfs.semanticscholar.org/5449/aa3ca855cee1a80fe5f6bc97f7c0742e3e99.pdf"]}
-{"year":"2018","title":"Improving Personalized Consumer Health Search: Notebook for eHealth at CLEF 2018","authors":["H Yang, T Gonçalves - CEUR Workshop Proceedings: Working Notes of CLEF, 2018"],"snippet":"… Page 4. 3.2 Dataset The dataset used in CLEF 2018 CHS task consisted of web pages acquired from the CommonCrawl. By submitting the task queries to the Microsoft Bing APIs repeatedly over a period of time, an initial …","url":["http://ceur-ws.org/Vol-2125/paper_195.pdf"]}
-{"year":"2018","title":"Improving the learning of chemical-protein interactions from literature using transfer learning and word embeddings.","authors":["P Corbett, J Boyle"],"snippet":"… GloVe offers both some public pre-trained embeddings (based on Wikipedia and Common Crawl), and also the software to compile your own – in previous work (6) we had success with the public embeddings, but here, we compiled our own …","url":["http://www.biocreative.org/media/store/files/2018/BC6_track5_10.pdf"]}
-{"year":"2018","title":"Improving Word Embedding Compositionality using Lexicographic Definitions","authors":["T Scheepers, E Gavves, E Kanoulas - 2017"],"snippet":"… We used GloVe representations that where trained on the Common Crawl which has 840B tokens and a vocabulary of 2.2M. fastText uses a training algorithm that is based on skip-gram, however it represents each word as a bag of character n-grams …","url":["https://thijs.ai/papers/scheepers-gavves-kanoulas-improving-embedding-lexicographic.pdf"]}
-{"year":"2018","title":"Improving Word Embedding Coverage in Less-Resourced Languages Through Multi-Linguality and Cross-Linguality: A Case Study with Aspect-Based Sentiment …","authors":["MS Akhtar, P Sawant, S Sen, A Ekbal, P Bhattacharyya - ACM Transactions on Asian …, 2018","S SEN, A EKBAL"],"snippet":"… However, these systems require a large corpus for training and building the models (eg, the pretrained Google News Word2Vec model was trained on 100 billion words, pretrained common-crawl GloVe model was trained on 840 billion words) …","url":["https://dl.acm.org/citation.cfm?id=3273931","https://dl.acm.org/doi/fullHtml/10.1145/3273931"]}
-{"year":"2018","title":"Incorporating Statistical Machine Translation Word Knowledge into Neural Machine Translation","authors":["X Wang, Z Tu, M Zhang - IEEE/ACM Transactions on Audio, Speech, and …, 2018"],"snippet":"Page 1. 2329-9290 (c) 2018 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/8421063/"]}
-{"year":"2018","title":"Incorporating the Structure of the Belief State in End-to-End Task-Oriented Dialogue Systems","authors":["L Shu, P Molino, M Namazifar, B Liu, H Xu, H Zheng…"],"snippet":"Page 1. Incorporating the Structure of the Belief State in End-to-End Task-Oriented Dialogue Systems Lei Shu∗1, Piero Molino2, Mahdi Namazifar3, Bing Liu1, Hu Xu1, Huaixiu Zheng3, and Gokhan Tur3 1University …","url":["http://alborz-geramifard.com/workshops/nips18-Conversational-AI/Papers/18convai-Incorporating%20the%20Structure.pdf"]}
-{"year":"2018","title":"Inducing Grammars with and for Neural Machine Translation","authors":["K Tran, Y Bisk - arXiv preprint arXiv:1805.10850, 2018","Y Bisk, K Tran - Proceedings of the 2nd Workshop on Neural Machine …, 2018"],"snippet":"… Table 1 shows the statistics of the data. For En↔De, we use a concatenation of Europarl, Common Crawl, Rapid corpus of EU press releases, and News Commentary v12 … For En↔Ru, we use Common Crawl, News Commentary v12, and Yandex Corpus …","url":["http://www.aclweb.org/anthology/W18-2704","https://arxiv.org/pdf/1805.10850"]}
-{"year":"2018","title":"Inducing Implicit Relations from Text Using Distantly Supervised Deep Nets","authors":["M Glass, A Gliozzo, O Hassanzadeh… - International Semantic Web …, 2018"],"snippet":"… We also evaluate on a web-scale knowledge base population benchmark that we called CC-DBP 5 . It combines the text of Common Crawl 6 with the triples from 298 frequent relations in DBpedia [1]. Mentions of DBpedia entities …","url":["https://link.springer.com/chapter/10.1007/978-3-030-00671-6_3"]}
-{"year":"2018","title":"InferLite: Simple Universal Sentence Representations from Natural Language Inference Data","authors":["J Kiros, W Chan - Proceedings of the 2018 Conference on Empirical …, 2018"],"snippet":"… (2018) describe a contextual gating Feature dataset dim method Glove Common Crawl 300 News Google News 500 CBOW Query Google Search 800 CBOW Table 1: Comparison of word representations used. method for word embedding selection …","url":["http://www.aclweb.org/anthology/D18-1524"]}
-{"year":"2018","title":"Inferring gender of Reddit users","authors":["E Vasilev - 2018"],"snippet":"Page 1. People and Knowledge Networks WeST Fachbereich 4: Informatik Institute for Web Science and Technologies Inferring gender of Reddit users Masterarbeit zur Erlangung des Grades einer Master of Science (M.Sc.) im Studiengang Web Science …","url":["https://kola.opus.hbz-nrw.de/files/1619/Master_thesis_Vasilev.pdf"]}
-{"year":"2018","title":"Inferring Missing Categorical Information in Noisy and Sparse Web Markup","authors":["N Tempelmeier, E Demidova, S Dietze - arXiv preprint arXiv:1803.00446, 2018"],"snippet":"… information. For instance, from 26 million nodes describing events within the Common Crawl in 2016, 59% of nodes provide less than six statements and only 257,000 nodes (0.96%) are typed with more specific event subtypes …","url":["https://arxiv.org/pdf/1803.00446"]}
-{"year":"2018","title":"Integrating Multiplicative Features into Supervised Distributional Methods for Lexical Entailment","authors":["T Vu, V Shwartz - arXiv preprint arXiv:1804.08845, 2018"],"snippet":"… We used 300-dimensional pre-trained word em- beddings, namely, GloVe (Pennington et al., 2014b) containing 1.9M word vectors trained on a corpus of web data from Common Crawl (42B to- kens),1 and Word2vec (Mikolov …","url":["https://arxiv.org/pdf/1804.08845"]}
-{"year":"2018","title":"Intent Generation for Goal-Oriented Dialogue Systems based on Schema. org Annotations","authors":["U Şimşek, D Fensel - arXiv preprint arXiv:1807.01292, 2018"],"snippet":"… These vectors are trained based on existing ConceptNet 5.5 knowledge graph3 data, word2vec embeddings [11] trained with 300B words from Google News Dataset and GloVe embeddings [15] trained with 840B words from …","url":["https://arxiv.org/pdf/1807.01292"]}
-{"year":"2018","title":"Interactions and influence of world painters from the reduced Google matrix of Wikipedia networks","authors":["SE Zant, K Jaffrès-Runser, KM Frahm… - arXiv preprint arXiv …, 2018"],"snippet":"… At present, directed networks of real systems can be very large (about 4.2 million articles for the English Wikipedia edition in 2013 [16] or 3.5 billion web pages for a publicly accessible web crawl that was gathered by the Common Crawl Foundation in 2012 [25]) …","url":["https://arxiv.org/pdf/1807.01255"]}
-{"year":"2018","title":"Investigating open data portals automatically: a methodology and some illustrations","authors":["AS Correa, PO Zander, FSC da Silva - Proceedings of the 19th Annual International …, 2018"],"snippet":"Page 1. Investigating open data portals automatically: a methodology and some illustrations Andreiwid Sheffer Correa Federal Institute of Sao Paulo Campinas, Sao Paulo, Brazil University of Sao Paulo Sao Paulo, Brazil andreiwid@ifsp.edu.br …","url":["https://dl.acm.org/citation.cfm?id=3209292"]}
-{"year":"2018","title":"Iterative reasoning with bi-directional attention flow for machine comprehension","authors":["ADA Gupta"],"snippet":"… [2016] pre-trained on the common crawl dataset … 4.2 Implementation Details We used pre-trained case sensitive 300-dimensional pre-trained word embeddings trained on Common Crawl and Wikipedia using fastText …","url":["http://web.stanford.edu/class/cs224n/reports/6908250.pdf"]}
-{"year":"2018","title":"Iterative Recursive Attention Model for Interpretable Sequence Classification","authors":["M Tutek, J Šnajder - arXiv preprint arXiv:1808.10503, 2018"],"snippet":"… We clip the global norm of the gradients to 1.0 and set weight decay to 0.00003. We use 300-dimensional GloVe word embeddings trained on the Common Crawl corpus and 100-dimensional character embeddings. We follow the recommendation of Mu et al …","url":["https://arxiv.org/pdf/1808.10503"]}
-{"year":"2018","title":"KnowMore-Knowledge Base Augmentation with Structured Web Markup","authors":["R Yua, U Gadirajua, B Fetahua, O Lehmbergb…"],"snippet":"Page 1. Semantic Web 0 (0) 1 1 IOS Press KnowMore - Knowledge Base Augmentation with Structured Web Markup Editor(s): Name Surname, University, Country Solicited review(s): Name Surname, University, Country Open review(s): Name Surname, University, Country …","url":["http://www.semantic-web-journal.net/system/files/swj1773.pdf"]}
-{"year":"2018","title":"L'optimisation des plongements de mots pour le français: une application de la classification des phrases","authors":["J Park - Actes de la conférence Traitement Automatique de la …"],"snippet":"… c ATALA 2018 283 Page 299. Wikipedia Europarl New crawls Common crawl Giga in-domain total 675M 64M 223M 89M 793M 664M 2.5 B TABLE 1–The size (# of token) of corpora for embedding 2.3 Lemma-aware …","url":["https://hal.archives-ouvertes.fr/hal-01843560/document#page=296"]}
-{"year":"2018","title":"LA3: A Scalable Link-and Locality-Aware Linear Algebra-Based Graph Analytics System","authors":["Y Ahmad, O Khattab, A Malik, A Musleh, M Hammoud… - Proceedings of the VLDB …, 2018"],"snippet":"Page 1. LA3: A Scalable Linkand Locality-Aware Linear Algebra-Based Graph Analytics System Yousuf Ahmad, Omar Khattab, Arsal Malik, Ahmad Musleh, Mohammad Hammoud Carnegie Mellon University in Qatar 1myahmad …","url":["http://www.vldb.org/pvldb/vol11/p920-ahmad.pdf"]}
-{"year":"2018","title":"Language Modeling at Scale","authors":["M Patwary, M Chabbi, H Jun, J Huang, G Diamos… - arXiv preprint arXiv …, 2018"],"snippet":"… The figure shows four datasets: 1-Billion word [6] (1b), Gutenberg [7] (gb), Common crawl [8] (cc), and Amazon review [9] (ar) … The 4 lines correspond to 4 datasets: one Billion word (1b), Gutenberg (gb), Common Crawl (cc), and Amazon Review (ar). TABLE I DATASETS …","url":["https://arxiv.org/pdf/1810.10045"]}
-{"year":"2018","title":"Language use shapes cultural norms: Large scale evidence from gender","authors":["M Lewis, G Lupyan"],"snippet":"… Results Figure 2 shows the effect size measures derived from the English Wikipedia corpus plotted against effect size estimates reported by CBN from two different models (trained on the Common Crawl and Google News corpora) … model Common Crawl (GloVe) …","url":["http://home.uchicago.edu/~mollylewis/papers/gender_cogsci_2018.pdf"]}
-{"year":"2018","title":"Large scale distributed neural network training through online distillation","authors":["AT Passos, G Pereyra, G Hinton, G Dahl, R Ormandi… - 2018","R Anil, G Pereyra, A Passos, R Ormandi, GE Dahl… - arXiv preprint arXiv …, 2018"],"snippet":"… 2http://commoncrawl.org/2017/07/june-2017-crawl-archive-now-available/ 3It is still infeasible to train on all of this data set with large neural language models, so our experiments did not … We use the ADAM optimizer Kingma …","url":["https://arxiv.org/pdf/1804.03235","https://research.google.com/pubs/pub46642.html"]}
-{"year":"2018","title":"Large-Scale Analysis of Style Injection by Relative Path Overwrite","authors":["S Arshad, SA Mirheidari, T Lauinger, B Crispo, E Kirda… - 2018"],"snippet":"… using RPO. We extract pages using relativepath stylesheets from the Common Crawl dataset [9], automatically test if style directives can be injected using RPO, and determine whether they are interpreted by the browser. Out …","url":["http://www.ccs.neu.edu/home/arshad/publications/www2018rpo.pdf"]}
-{"year":"2018","title":"Latent Question Interpretation Through Parameter Adaptation Using Stochastic Neuron","authors":["T Parshakova, DS Kim"],"snippet":"… In effect, it led to maximally effective behaviour in the question-answering task. 6 Experiments Implementation Details For the word embeddings we use GloVe embeddings pretrained on the 840B Common Crawl corpus [Pennington et al., 2014] …","url":["http://ceur-ws.org/Vol-2134/paper07.pdf"]}
-{"year":"2018","title":"Latent Semantic Analysis Approach for Document Summarization Based on Word Embeddings","authors":["K Al-Sabahi, Z Zuping, Y Kang - arXiv preprint arXiv:1807.02748, 2018"],"snippet":"… Training is performed on aggregated global word-word co-occurrence statistics from a corpus. In this work, we use the one trained on Common Crawl (840B tokens, 2.2M vocab, cased, 300d vectors, 2.03 GB download): glove.840B.300d.zip. 3.2. LSA algorithm …","url":["https://arxiv.org/pdf/1807.02748"]}
-{"year":"2018","title":"LATEX GLOVES: Protecting Browser Extensions from Probing and Revelation Attacks","authors":["A Sjösten, S Van Acker, P Picazo-Sanchez, A Sabelfeld - Power, 2018"],"snippet":"Page 1. LATEX GLOVES: Protecting Browser Extensions from Probing and Revelation Attacks Alexander Sjösten∗, Steven Van Acker∗, Pablo Picazo-Sanchez and Andrei Sabelfeld Chalmers University of Technology …","url":["http://www.cse.chalmers.se/~andrei/ndss19.pdf"]}
-{"year":"2018","title":"Learning Emotion-enriched Word Representations","authors":["A Agrawal, A An, M Papagelis - Proceedings of the 27th International Conference on …, 2018"],"snippet":"… GloVe 6B Wiki + Gigaword 6B tokens 400K GloVe 42B Common Crawl 42B tokens 1.9M … Paired t-tests using the results on all four datasets indicate EWE is significantly better than all the other methods with p-values < 0.02. uncased …","url":["http://www.aclweb.org/anthology/C18-1081"]}
-{"year":"2018","title":"Learning Multimodal Word Representation via Dynamic Fusion Methods","authors":["S Wang, J Zhang, C Zong - arXiv preprint arXiv:1801.00532, 2018"],"snippet":"… Experimental Setup Datasets We use 300-dimensional GloVe vectors3 which are trained on the Common Crawl corpus consisting of 840B tokens and a vocabulary of 2.2M words. Our source of visual vectors are collected from ImageNet (Russakovsky et al …","url":["https://arxiv.org/pdf/1801.00532"]}
-{"year":"2018","title":"Learning Neural Emotion Analysis from 100 Observations: The Surprising Effectiveness of Pre-Trained Word Representations","authors":["S Buechel, J Sedoc, HA Schwartz, L Ungar - arXiv preprint arXiv:1810.10949, 2018"],"snippet":"… For ANET, we rely on the FastText embeddings trained on Common Crawl (Mikolov et al., 2018). For ANPST and MAS, we use the FastText embeddings by Grave et al. (2018) trained on the respective Wikipedias … ANET English …","url":["https://arxiv.org/pdf/1810.10949"]}
-{"year":"2018","title":"Learning Patent Speak: Investigating Domain-Specific Word Embeddings","authors":["J Risch, R Krestel"],"snippet":"… used to train word embeddings. It contains more than twice the number of tokens of the English Wikipedia (16 billion) and is only exceeded by the Common Crawl dataset, which consists of 600 billion tokens. We assume that the …","url":["https://www.researchgate.net/profile/Julian_Risch/publication/327317674_Learning_Patent_Speak_Investigating_Domain-Specific_Word_Embeddings/links/5b87ea484585151fd13c55ce/Learning-Patent-Speak-Investigating-Domain-Specific-Word-Embeddings.pdf"]}
-{"year":"2018","title":"Learning representations for sentiment classification using Multi-task framework","authors":["H Meisheri, H Khadilkar - Proceedings of the 9th Workshop on Computational …, 2018"],"snippet":"… First set of embeddings are generated by using three different pre-trained embeddings. • Pre-trained embeddings which are generated from common crawl corpus have 6 Billion to- kens which help in a better encoding of the …","url":["http://www.aclweb.org/anthology/W18-6244"]}
-{"year":"2018","title":"Learning Robust Joint Representations for Multimodal Sentiment Analysis","authors":["H Pham, PP Liang, T Manzini, LP Morency, B Póczos"],"snippet":"Page 1. Learning Robust Joint Representations for Multimodal Sentiment Analysis Hai Pham*, Paul Pu Liang*, Thomas Manzini, Louis-Philippe Morency, Barnabás Póczos School of Computer Science, Carnegie Mellon University …","url":["http://www.cs.cmu.edu/~pliang/papers/nips2018ws_translations.pdf"]}
-{"year":"2018","title":"Learning semantic similarity in a continuous space","authors":["M Deudon - Advances in Neural Information Processing Systems, 2018"],"snippet":"… that connect those parts. Word2Vec [5] and GloVe [6] are semantic embeddings of words based on their context and frequency of co-occurence in a text corpus such as Wikipedia, Google News or Common-Crawl. The key idea …","url":["http://papers.nips.cc/paper/7377-learning-semantic-similarity-in-a-continuous-space.pdf"]}
-{"year":"2018","title":"Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs","authors":["G Maheshwari, P Trivedi, D Lukovnikov, N Chakraborty… - arXiv preprint arXiv …, 2018"],"snippet":"… All our models pe- formed poorly on QALD-7, with the best being DAM dot. 4in keeping with the train-test splits suggested by the authors. 5Trained over the common Crawl corpus. 300 dimensions, and with 1.9M tokens in the …","url":["https://arxiv.org/pdf/1811.01118"]}
-{"year":"2018","title":"Learning Word Embeddings for Data Sparse and Sentiment Rich Data Sets","authors":["PK Sarma - Proceedings of the 2018 Conference of the North …, 2018"],"snippet":"… a very different distribution from generic corpora, so pre-trained generic word embeddings such as those trained on Common Crawl or Wikipedia … d2 be the matrix of generic word embeddings (obtained by, eg, running the GloVe …","url":["http://www.aclweb.org/anthology/N18-4007"]}
-{"year":"2018","title":"Learning Word Meta-Embeddings by Autoencoding","authors":["C Bao, D Bollegala"],"snippet":"… (2014). The released version we used contains 1,917,494 word embeddings with dimensionality of 300 that is trained on Common Crawl dataset. The intersection of two vocabularies contains 154,076 words for which we create meta-embeddings …","url":["http://danushka.net/papers/aeme.pdf"]}
-{"year":"2018","title":"Learning Word Vectors for 157 Languages","authors":["E Grave, P Bojanowski, P Gupta, A Joulin, T Mikolov - arXiv preprint arXiv …, 2018"],"snippet":"… In this work, we contribute word vectors trained on Wikipedia and the Common Crawl, as well as three new analogy datasets to evaluate these … We also show that using the common crawl data, while being noisy, can lead to models with larger coverage, and better models for …","url":["https://arxiv.org/pdf/1802.06893"]}
-{"year":"2018","title":"Lecture Video Search Engine Using Hadoop MapReduce","authors":["PP Deolikar - 2017"],"snippet":"… While doing so, they dont need to bother. about crawling the data. Gil Elbaz, former Google employee funded Common CrawlCommonCrawl is implemented using Hadoop MapReduce Technology. Their strategy is to crawl. broadly and frequently, to cover all the web pages …","url":["http://search.proquest.com/openview/94314da495ab40e1ea0d1c2490d6d62a/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2018","title":"Legal Deposit Web Archives and the Digital Humanities: A Universe of Lost Opportunity?","authors":["P Gooding, M Terras, L Berube - 2018"],"snippet":"… Restricted deposit library ac- cess requires researchers to look elsewhere for portable web data: by undertaking their own web crawls, or by utilising datasets from Common Crawl (http://commoncrawl. org/) and the Internet Archive (https://archive.org) …","url":["http://eprints.gla.ac.uk/168229/1/168229.pdf"]}
-{"year":"2018","title":"Lessons from Natural Language Inference in the Clinical Domain","authors":["A Romanov, C Shivade - arXiv preprint arXiv:1808.06752, 2018"],"snippet":"… fastText[Wiki]: fastText embeddings (Bo- janowski et al., 2017), trained on Wikipedia. 7http://commoncrawl.org/ Page 7. • fastText[CC]: fastText embeddings, trained on Common Crawl. Furthermore, we trained fastText …","url":["https://arxiv.org/pdf/1808.06752"]}
-{"year":"2018","title":"Lessons Learned and Research Agenda for Big Data Integration of Product Specifications (Discussion Paper)","authors":["L Barbosa, V Crescenzi, XL Dong, P Merialdo, F Piai…"],"snippet":"… About 68% of the sources discovered by our approach were not present in Common Crawl … these sources were product pages: on a sample set of 12 websites where Common Crawl presented … DEXTER) is an extension …","url":["http://ceur-ws.org/Vol-2161/paper29.pdf"]}
-{"year":"2018","title":"Leveraging Meta-Embeddings for Bilingual Lexicon Extraction from Specialized Comparable Corpora","authors":["A Hazem, E Morin - Proceedings of the 27th International Conference on …, 2018"],"snippet":"… Common crawl corpus (CC) is an open repository of data collected over 7 years of web crawling sets of raw web page data and text extracts7. 4 www.sciencedirect.com/ 5 www.ttc-project.eu/index.php/releases-publications …","url":["http://www.aclweb.org/anthology/C18-1080"]}
-{"year":"2018","title":"Leveraging textual properties of bug reports to localize relevant source files","authors":["R Gharibi, AH Rasekh, MH Sadreddini… - Information Processing & …, 2018"],"snippet":"Skip to main content …","url":["https://www.sciencedirect.com/science/article/pii/S0306457318301092"]}
-{"year":"2018","title":"Lifelong Domain Word Embedding via Meta-Learning","authors":["H Xu, B Liu, L Shu, PS Yu - arXiv preprint arXiv:1805.09991, 2018"],"snippet":"… Page 6. GloVe.6B: This is the lower-cased embeddings pre-trained from Wikipedia and Gigaword 5, which has 6 billion tokens. GloVe.840B: This is the cased embeddings pre-trained from Common Crawl corpus, which has 840 billion tokens …","url":["https://arxiv.org/pdf/1805.09991"]}
-{"year":"2018","title":"Linguistic Features of Helpfulness in Automated Support for Creative Writing","authors":["M Roemmele, AS Gordon"],"snippet":"… tween the context and suggestion in terms of their Jaccard similarity (proportion of overlapping words; Metric 8), GloVe word embeddings7 trained on the Common Crawl corpus (Metric 9), and sentence (skip-thought) …","url":["http://people.ict.usc.edu/~gordon/publications/NAACL-WS18B.PDF"]}
-{"year":"2018","title":"List Intersection for Web Search: Algorithms, Cost Models, and Optimizations","authors":["S Kim, T Lee, S Hwang, S Elnikety - Proceedings of the VLDB Endowment"],"snippet":"Page 1. List Intersection for Web Search: Algorithms, Cost Models, and Optimizations Sunghwan Kim POSTECH sunghwan08@gmail.com Taesung Lee IBM Research AI Taesung.Lee@ibm.com Seung-won …","url":["http://www.vldb.org/pvldb/vol12/p1-kim.pdf"]}
-{"year":"2018","title":"LMU Munich's Neural Machine Translation Systems at WMT 2018","authors":["M Huck, D Stojanovski, V Hangya, A Fraser - Proceedings of the Third Conference on …, 2018"],"snippet":"… BLEU (Pa- pineni et al., 2002)) of different system setups after several development stages is presented in the top section of Table 1. WMT_parallel de- notes the Europarl, News Commentary, and Common Crawl parallel …","url":["http://www.aclweb.org/anthology/W18-6446"]}
-{"year":"2018","title":"Local Homology of Word Embeddings","authors":["T Temčinas - arXiv preprint arXiv:1810.10136, 2018"],"snippet":"Page 1. Local Homology of Word Embeddings Tadas Temcinas 1 Abstract Topological data analysis (TDA) has been widely used to make progress on a number of problems. However, it seems that TDA application in natural …","url":["https://arxiv.org/pdf/1810.10136"]}
-{"year":"2018","title":"Local-Global Graph Clustering with Applications in Sense and Frame Induction","authors":["D Ustalov, A Panchenko, C Biemann, SP Ponzetto - arXiv preprint arXiv:1808.06696, 2018"],"snippet":"Page 1. Local-Global Graph Clustering with Applications in Sense and Frame Induction Dmitry Ustalov∗ University of Mannheim Alexander Panchenko∗∗ University of Hamburg Chris Biemann University of Hamburg Simone Paolo Ponzetto University of Mannheim …","url":["https://arxiv.org/pdf/1808.06696"]}
-{"year":"2018","title":"Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion","authors":["A Joulin, P Bojanowski, T Mikolov, H Jégou, E Grave - Proceedings of the 2018 …, 2018"],"snippet":"… word vectors of Mikolov et al. (2018) to Spanish. It leads to an improvement of 1% both for vectors trained on Common Crawl (85% to 86%) and Wikipedia + News (87% to 88%). 5 Conclusion This paper shows that minimizing …","url":["http://www.aclweb.org/anthology/D18-1330"]}
-{"year":"2018","title":"M1. 2–Corpora for the Machine Translation Engines","authors":["C Espana-Bonet, J Stiller, S Henning - 2018"],"snippet":"… Table 5: Size of the parallel corpora obtained from the different sources described in Section 2.1: United Nations (UN), Europarl V7 (EP), Common Crawl (ComCrawl), EMEA and Scielo. Figures of the PubPsych corpus are …","url":["https://www.clubs-project.eu/assets/publications/project/CLUBS_MTcorpora.v3.pdf"]}
-{"year":"2018","title":"MAC: Mining Activity Concepts for Language-based Temporal Localization","authors":["R Ge, J Gao, K Chen, R Nevatia - arXiv preprint arXiv:1811.08925, 2018"],"snippet":"… We only keep the twoword tuple as our VO. ie open door, wash hands. After lemmatizing every word, we use the GloVe [22] word en- coder which is pre-trained on the Common Crawl data to get each word a 300-dimensional word embedding …","url":["https://arxiv.org/pdf/1811.08925"]}
-{"year":"2018","title":"Machine Learning with and for Semantic Web Knowledge Graphs","authors":["H Paulheim - Reasoning Web International Summer School, 2018"],"snippet":"… To that end, it scans the Common Crawl Web corpus 20 for so-called Hearst patterns, eg X such as Y, to infer relations like X skos:broader Y. The graph comes with very detailed provenance data, including the patterns used …","url":["https://link.springer.com/chapter/10.1007/978-3-030-00338-8_5"]}
-{"year":"2018","title":"Machine Reading Comprehension on SQuAD","authors":["DMT Tan"],"snippet":"… The end-to-end neural architecture consists of the following components. Page 3. Input vectors. For each word in context (C) and question (Q), we use the 300-dim GloVe embeddings pretrained on the 840B Common Crawl corpus [5] as input vectors …","url":["http://web.stanford.edu/class/cs224n/reports/6909266.pdf"]}
-{"year":"2018","title":"MAJE Submission to the WMT2018 Shared Task on Parallel Corpus Filtering","authors":["M Fomicheva, J González-Rubio - Proceedings of the Third Conference on Machine …, 2018"],"snippet":"… We also conducted some initial experiments us- ing the Common Crawl corpus, under the rationale that it would be closer to the domain of the noisy data from the Paracrawl corpus. However, Common Crawl data …","url":["http://www.aclweb.org/anthology/W18-6476"]}
-{"year":"2018","title":"Making Caches Work for Graph Analytics","authors":["Y Zhang, V Kiriansky, C Mendis, S Amarasinghe…"],"snippet":"… The system has 128GB of DDR3-1600 memory. The machine runs with Transparent Huge Pages (THP) enabled. Data Sets: We used the social networks, including LiveJournal [10] and Twitter [8], the SD web graph from 2012 common crawl [11], and the RMAT graphs …","url":["http://groups.csail.mit.edu/commit/papers/2017/zhang-bigdata17-cagra.pdf"]}
-{"year":"2018","title":"Manifold Scholarship: Hybrid Publishing in a Print/Digital Era","authors":["MK Gold, J Karlin, Z Davis, P Gooding, M Terras… - Digital Humanities 2018 …, 2018"],"snippet":"… Restricted deposit library ac- cess requires researchers to look elsewhere for portable web data: by undertaking their own web crawls, or by utilising datasets from Common Crawl (http://commoncrawl. org/) and the Internet Archive (https://archive. org) …","url":["https://pdfs.semanticscholar.org/7cf9/f2db34ac1b5791de374b78b2fdbe97dc27af.pdf#page=590"]}
-{"year":"2018","title":"Manual vs Automatic Bitext Extraction","authors":["A Makazhanov, B Myrzakhmetov, Z Assylbekov - Proceedings of the Eleventh …, 2018"],"snippet":"… Biometrika, 52(3/4):591–611. Smith, JR, Saint-Amand, H., Plamada, M., Koehn, P., Callison-Burch, C., and Lopez, A. (2013). Dirt cheap web-scale parallel text from the common crawl. In ACL (1), pages 1374–1383. Tiedemann, J. (2007) …","url":["http://www.aclweb.org/anthology/L18-1606"]}
-{"year":"2018","title":"Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings","authors":["M Artetxe, H Schwenk - arXiv preprint arXiv:1811.01136, 2018"],"snippet":"Page 1. Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings Mikel Artetxe University of the Basque Country (UPV/EHU)∗ mikel.artetxe@ehu.eus Holger Schwenk Facebook AI Research schwenk@fb.com Abstract …","url":["https://arxiv.org/pdf/1811.01136"]}
-{"year":"2018","title":"MEADE: Towards a Malicious Email Attachment Detection Engine","authors":["EM Rudd, R Harang, J Saxe - arXiv preprint arXiv:1804.08162, 2018"],"snippet":"… To this end, we collected a dataset of over 5 million malicious/benign Microsoft Office documents from VirusTotal for evaluation as well as a dataset of benign Microsoft Office documents from the Common Crawl …","url":["https://arxiv.org/pdf/1804.08162"]}
-{"year":"2018","title":"Measuring Semantic Coherence of a Conversation","authors":["S Vakulenko, M de Rijke, M Cochez, V Savenkov… - arXiv preprint arXiv …, 2018"],"snippet":"… We utilise two publicly available word embedding models: GloVe embeddings pretrained on the Common Crawl corpus (2.2M words, 300 dimensions)14 and Word2Vec model trained on the Google News corpus …","url":["https://arxiv.org/pdf/1806.06411"]}
-{"year":"2018","title":"Measuring the Effects of Data Parallelism on Neural Network Training","authors":["CJ Shallue, J Lee, J Antognini, J Sohl-Dickstein… - arXiv preprint arXiv …, 2018"],"snippet":"… For LM1B, we chose the Transformer model and an LSTM model. For Common Crawl, we chose the Transformer model … Common Crawl Text Language modeling ∼25.8 billion sentences Cross entropy error Table …","url":["https://arxiv.org/pdf/1811.03600"]}
-{"year":"2018","title":"Meet the Data","authors":["K Balog - Entity-Oriented Search, 2018"],"snippet":"… Size refers to compressed data ahttps://lemurproject.org/clueweb09/ bhttps://lemurproject.org/clueweb12/ chttp://commoncrawl.org/2017/06/may … Common Crawl Common Crawl5 is a nonprofit organization that regularly …","url":["https://link.springer.com/content/pdf/10.1007/978-3-319-93935-3_2.pdf"]}
-{"year":"2018","title":"Memory Fusion Network for Multi-view Sequential Learning","authors":["A Zadeh, PP Liang, N Mazumder, S Poria, E Cambria… - arXiv preprint arXiv …, 2018"],"snippet":"… The Glove embeddings used are 300 dimensional word embeddings trained on 840 billion tokens from the common crawl dataset, resulting in a sequence of dimension T × dxtext = T × 300 after alignment. The timing of word utterances is extracted using P2FA forced aligner …","url":["https://arxiv.org/pdf/1802.00927"]}
-{"year":"2018","title":"Merging Search Results Generated by Multiple Query Variants Using Data Fusion","authors":["N Motlogelwa, T Leburu-Dingalo, E Thuma - CEUR Workshop Proceedings: Working …, 2018"],"snippet":"… In Section 3.2 we describe the queries used for retrieval. 3.1 Document Collection “The document collection used in CLEF 2018 consists of web pages acquired from the CommonCrawl. An initial list of websites was identified for acquisition …","url":["http://ceur-ws.org/Vol-2125/paper_194.pdf"]}
-{"year":"2018","title":"METHODS AND SYSTEMS FOR QUERY SEGMENTATION","authors":["AG Kale, T Taula, A Srivastava, S Hewavitharana - US Patent App. 15/681,663, 2018"],"snippet":"… This process may be repeated but using pre-trained GloVe vectors on common crawl and facebook fasttext pretrained model over a Wikipedia corpus with 2.5 M word vocabulary. Table 2 shows the experimental results of this analysis …","url":["http://www.freepatentsonline.com/y2018/0329999.html"]}
-{"year":"2018","title":"microNER: A Micro-Service for German Named Entity Recognition based on BiLSTM-CRF","authors":["G Wiedemann, R Jindal, C Biemann - arXiv preprint arXiv:1811.02902, 2018"],"snippet":"… It is rather determined by the fact that it was trained on several billion tokens of the Common Crawl corpus.2 To evaluate the contribution of different German word … 2http://commoncrawl org 3For fastText, we use the publicly available German model from Bojanowski et al …","url":["https://arxiv.org/pdf/1811.02902"]}
-{"year":"2018","title":"Mining Training Data for Language Modeling Across the World's Languages","authors":["M Prasad, T Breiner, D van Esch - 2018"],"snippet":"… 64 Page 5. [16] Common crawlCommon Crawl Foundation. Ac- cessed: June 4, 2018. [Online]. Available: https://www.commoncrawl.org [17] UL Abteilung Automatische Sprachverarbeitung. Corpora collection. Deutscher …","url":["https://www.isca-speech.org/archive/SLTU_2018/pdfs/Manasa.pdf"]}
-{"year":"2018","title":"Miracl at Clef 2018: Consumer Health Search Task","authors":["S ZAYANI, N KSENTINI, M TMAR, F GARGOURI - CEUR Workshop Proceedings …, 2018"],"snippet":"… concepts. Page 6. 4 Resources employed 4.1 Datasets The document collection used in CLEFeHealth 2018 is composed of web pages acquired from the CommonCrawl An initial list of websites was identified for acquisition. The …","url":["http://ceur-ws.org/Vol-2125/paper_141.pdf"]}
-{"year":"2018","title":"MIsA: Multilingual\" IsA\" Extraction from Corpora","authors":["S Faralli, E Lefever, S Paolo Ponzetto - the Eleventh International Conference on …, 2018"],"snippet":"… 2016). Our MIsA is an extension of the WebIsADb framework (Seitner et al., 2016) - a publicly available database with more than 400 million English hypernymy relations ex- tracted from the CommonCrawl web corpus - where: 1 …","url":["https://biblio.ugent.be/publication/8562721/file/8562722"]}
-{"year":"2018","title":"Mitigating Bottlenecks in Wide Area Data Analytics via Machine Learning","authors":["H Wang, B Li - IEEE Transactions on Network Science and …, 2018"],"snippet":"Page 1. 2327-4697 (c) 2018 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["http://ieeexplore.ieee.org/abstract/document/8319505/"]}
-{"year":"2018","title":"Mixture of Expert/Imitator Networks: Scalable Semi-supervised Learning Framework","authors":["S Kiyono, J Suzuki, K Inui - arXiv preprint arXiv:1810.05788, 2018"],"snippet":"… in DNNs has been gaining the performance. For example, several studies have utilized unlabeled 1http://commoncrawl.org arXiv:1810.05788v1 [cs.CL] 13 Oct 2018 Page 2. data as additional training data, which essentially …","url":["https://arxiv.org/pdf/1810.05788"]}
-{"year":"2018","title":"Modeling Empathy and Distress in Reaction to News Stories","authors":["S Buechel, A Buffone, B Slaff, L Ungar, J Sedoc - arXiv preprint arXiv:1808.10399, 2018"],"snippet":"… problems. The input to our models is based on word embeddings, namely the publicly available FastText embeddings which were trained on Common Crawl (≈600B tokens) (Bojanowski et al., 2017; Mikolov et al., 2018). Ridge …","url":["https://arxiv.org/pdf/1808.10399"]}
-{"year":"2018","title":"Modeling voice calls to improve an outcome of a call between a representative and a customer","authors":["R Raanani, R Levy, MY Breakstone - US Patent App. 16/017,646, 2018","R Raanani, R Levy, MY Breakstone - US Patent App. 16/689,688, 2020"],"snippet":"… At the same time, natural language processing (NLP) approaches to both topic modeling and world-knowledge modeling, have become much more efficient due to the availability of large, freely accessible natural language corpora (eg, CommonCrawl), as well as freely …","url":["https://patentimages.storage.googleapis.com/89/79/27/c037a0d312fd5d/US20180309873A1.pdf","https://patents.google.com/patent/US20200092420A1/en"]}
-{"year":"2018","title":"Multi-task Projected Embedding for Igbo","authors":["I Ezeani, M Hepple, I Onyenwe, C Enemuo - International Workshop on Temporal …, 2018"],"snippet":"… igSwproj from same as igWkproj but with subword information. igCrlproj from fastText Common Crawl dataset. Table 3 shows the vocabulary lengths (\\(Vocabs^L\\)), and the dimensions (Dimension) of each of the models used in our experiments …","url":["https://link.springer.com/chapter/10.1007/978-3-030-00794-2_31"]}
-{"year":"2018","title":"Multi-turn QA: A RNN Contextual Approach to Intent Classification for Goal-oriented Systems","authors":["M Mensio, G Rizzo, M Morisio - Companion of the The Web Conference 2018 on The …, 2018"],"snippet":"… 8. Christian Buck, Kenneth Heafield, and Bas van Ooyen. 2014. N-gram Counts and Language Models from the Common Crawl Proceedings of the Language Resources and Evaluation Conference (LREC), Vol. Vol. 2. Citeseer, Reykjavik, Iceland, 4 …","url":["https://dl.acm.org/citation.cfm?id=3191539"]}
-{"year":"2018","title":"Multilingual word embeddings and their utility in cross-lingual learning","authors":["A Kulmizev - 2018"],"snippet":"… language corpus. When said corpus is large enough (eg Wikipedia, Common Crawl, or the concatenation of the two), the resulting DSM can be assumed to represent the distributional semantics of an entire language. The algorithms …","url":["https://addi.ehu.es/bitstream/handle/10810/29083/TFM_Artur_Kulmizev.pdf?sequence=1"]}
-{"year":"2018","title":"Multimodal Language Analysis with Recurrent Multistage Fusion","authors":["PP Liang, Z Liu, A Zadeh, LP Morency - arXiv preprint arXiv:1808.03920, 2018"],"snippet":"Page 1. Multimodal Language Analysis with Recurrent Multistage Fusion Paul Pu Liang1, Ziyin Liu2, Amir Zadeh2, Louis-Philippe Morency2 1Machine Learning Department, 2Language Technologies Institute Carnegie Mellon …","url":["https://arxiv.org/pdf/1808.03920"]}
-{"year":"2018","title":"Multimodal Language Analysis with Recurrent Multistage Fusion: Supplementary Material","authors":["PP Liang, Z Liu, A Zadeh, LP Morency"],"snippet":"… 1.1 Multimodal Features Here we present extra details on feature extraction for the language, visual and acoustic modalities. Language: We used 300 dimensional Glove word embeddings trained on 840 billion tokens from …","url":["http://www.cs.cmu.edu/~pliang/papers/emnlp2018-recurrent-fusion-supp.pdf"]}
-{"year":"2018","title":"Natural language processing using a neural network","authors":["B McCann, C Xiong, R Socher - US Patent App. 16/000,638, 2018"],"snippet":"… in the second language. In some examples, training of an MT-LSTM of the encoder 310 uses fixed 300-dimensional word vectors, such as the CommonCrawl-840B GloVe model for English word vectors. These word vectors …","url":["https://patentimages.storage.googleapis.com/f0/42/0e/084fa3f0799a39/US20180349359A1.pdf"]}
-{"year":"2018","title":"Navigating Online Semantic Resources for Entity Set Expansion","authors":["WT Adrian, M Manna - International Symposium on Practical Aspects of …, 2018"],"snippet":"… the given entry (synset) in BabelNet. WebIsADatabase [25] is a publicly available database containing more than 400 million hypernymy relations extracted from the CommonCrawl web corpus. The tuples of the database are …","url":["https://link.springer.com/chapter/10.1007/978-3-319-73305-0_12"]}
-{"year":"2018","title":"Near Human-Level Performance in Grammatical Error Correction with Hybrid Machine Translation","authors":["R Grundkiewicz, M Junczys-Dowmunt - arXiv preprint arXiv:1804.05945, 2018"],"snippet":"�� ops). All systems use a 5-gram Language Model (LM) and OSM (Durrani et al., 2011) both estimated from the target side of the training data, and a 5-gram LM and 9-gram WCLM trained on Common Crawl data (Buck et al., 2014) …","url":["https://arxiv.org/pdf/1804.05945"]}
-{"year":"2018","title":"Neural Adaptation Layers for Cross-domain Named Entity Recognition","authors":["BY Lin, W Lu - arXiv preprint arXiv:1810.06368, 2018"],"snippet":"… ter stream grab4); 3) general emb, which is pretrained on CommonCrawl containing both formal and user-generated content.5 We obtain the intersection of the top 5K words from source and target vocabularies sorted by frequency to build P1 …","url":["https://arxiv.org/pdf/1810.06368"]}
-{"year":"2018","title":"Neural Cross-Lingual Named Entity Recognition with Minimal Resources","authors":["J Xie, Z Yang, G Neubig, NA Smith, J Carbonell - arXiv preprint arXiv:1808.09861, 2018"],"snippet":"Page 1. Neural Cross-Lingual Named Entity Recognition with Minimal Resources Jiateng Xie,1 Zhilin Yang,1 Graham Neubig,1 Noah A. Smith,2,3 and Jaime Carbonell1 1Language Technologies Institute, Carnegie Mellon University …","url":["https://arxiv.org/pdf/1808.09861"]}
-{"year":"2018","title":"Neural Fine-Grained Entity Type Classification with Hierarchy-Aware Loss","authors":["P Xu, D Barbosa - arXiv preprint arXiv:1803.03378, 2018"],"snippet":"… appearing in the training set. For this purpose, we used the freely available 300-dimensional cased word embedding trained on 840 billion tokens from the Common Crawl supplied by Pennington et al. (2014). For both datasets, we …","url":["https://arxiv.org/pdf/1803.03378"]}
-{"year":"2018","title":"Neural Learning for Question Answering in Italian","authors":["D Croce, A Zelenanska, R Basili - International Conference of the Italian Association …, 2018"],"snippet":"… In [5], both the paragraph and the question encodings use \\(d=128\\) hidden units. The best performing system reported in [5] uses GloVe embeddings [14] trained on Common Crawl of dimension \\(n=300\\) with more than 2 millions of tokens …","url":["https://link.springer.com/chapter/10.1007/978-3-030-03840-3_29"]}
-{"year":"2018","title":"Neural Machine Translation with Decoding History Enhanced Attention","authors":["M Wang, J Xie, Z Tan, J Su, D Xiong, C Bian - … of the 27th International Conference on …, 2018"],"snippet":"… translation are presented in Table 2. We compare our NMT systems with various other systems including the winning system in WMT14 (Buck et al., 2014), a phrase-based system whose language models were trained on …","url":["http://www.aclweb.org/anthology/C18-1124"]}
-{"year":"2018","title":"Neural models of factuality","authors":["R Rudinger, AS White, B Van Durme - arXiv preprint arXiv:1804.02472, 2018"],"snippet":"Page 1. Neural models of factuality Rachel Rudinger Johns Hopkins University Aaron Steven White University of Rochester Benjamin Van Durme Johns Hopkins University Abstract We present two neural models for event fac …","url":["https://arxiv.org/pdf/1804.02472"]}
-{"year":"2018","title":"NEURAL NETWORKS FOR NARRATIVE CONTINUATION","authors":["M Roemmele - 2018"],"snippet":"Page 1. NEURAL NETWORKS FOR NARRATIVE CONTINUATION by Melissa Roemmele A Ph.D. Dissertation Presented to the FACULTY OF THE GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA …","url":["http://people.ict.usc.edu/~roemmele/publications/dissertation.pdf"]}
-{"year":"2018","title":"Neural Networks for Semantic Textual Similarity","authors":["DS Prijatelj, J Ventura, J Kalita"],"snippet":"… tors. This specific set of word vectors have 300 dimensions and were pre-trained on 840 billion tokens taken from Common Crawl3. Different pre-trained word vectors may be used in place of this specific pre-trained set. After …","url":["http://cs.uccs.edu/~jkalita/papers/2017/DerekPrijateljICON2017.pdf"]}
-{"year":"2018","title":"Neural Quality Estimation of Grammatical Error Correction","authors":["S Chollampatt, HT Ng - Proceedings of the 2018 Conference on Empirical …, 2018"],"snippet":"Page 1. Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2528–2539 Brussels, Belgium, October 31 - November 4, 2018. c 2018 Association for Computational Linguistics 2528 …","url":["http://www.aclweb.org/anthology/D18-1274"]}
-{"year":"2018","title":"Next Utterance Ranking Based On Context Response Similarity","authors":["BEA Boussaha, N Hernandez, C Jacquin, E Morin"],"snippet":"… E. Parameter tuning Word embeddings were initialized with Glove [21] pretrained on Common Crawl Corpus4 then fine tuned during training5 … 4http://commoncrawl.org/the-data/ 5Note that we trained word embeddings …","url":["https://basma-b.github.io/assets/publications/nextUtterance/paper.pdf"]}
-{"year":"2018","title":"NICT's Neural and Statistical Machine Translation Systems for the WMT18 News Translation Task","authors":["B Marie, R Wang, A Fujita, M Utiyama, E Sumita - arXiv preprint arXiv:1809.07037, 2018"],"snippet":"… As English monolingual data, we used all the available data except the “Common Crawl” and “News Discussions” corpora.2 For all other languages, we used all the available monolingual corpora, except for Turkish for which we …","url":["https://arxiv.org/pdf/1809.07037"]}
-{"year":"2018","title":"NL-FIIT at IEST-2018: Emotion Recognition utilizing Neural Networks and Multi-level Preprocessing","authors":["S Pecar, M Farkaš, M Simko, P Lacko, M Bielikova - Proceedings of the 9th Workshop …, 2018"],"snippet":"… input words, we used various pre-trained word embeddings available online like GloVe em- beddings1. With GloVe embeddings, we experimented with domain specific embeddings trained on Twitter data but also with embeddings …","url":["http://www.aclweb.org/anthology/W18-6231"]}
-{"year":"2018","title":"Noising and Denoising Natural Language: Diverse Backtranslation for Grammar Correction","authors":["Z Xie, G Genthial, S Xie, A Ng, D Jurafsky - Proceedings of the 2018 Conference of …, 2018"],"snippet":"… h) (Wu et al., 2016). The final scoring function also incorporates a 5-gram language model trained on a subset of Common Crawl, estimated with Kneser-Ney smoothing using KenLM (Heafield, 2011). We in- corporate the …","url":["http://www.aclweb.org/anthology/N18-1057"]}
-{"year":"2018","title":"Not just about size-A Study on the Role of Distributed Word Representations in the Analysis of Scientific Publications","authors":["A Garcia, JM Gomez-Perez - arXiv preprint arXiv:1804.01772, 2018","A Garcia-Silva, JM Gomez-Perez"],"snippet":"… our evaluation task, embeddings from a scientific publication corpus consistently generate classifiers with a top performance that is only matched by classifiers learned from embeddings from very large document corpora …","url":["http://ceur-ws.org/Vol-2106/paper3.pdf","https://arxiv.org/pdf/1804.01772"]}
-{"year":"2018","title":"Novelty Goes Deep. A Deep Neural Solution To Document Level Novelty Detection","authors":["T Ghosal, V Edithal, A Ekbal, P Bhattacharyya…"],"snippet":"… Training is done with a mini-batch size of 64. GloVe vectors trained on Common Crawl 840B (https://nlp.stanford.edu/projects/glove/) with 300 dimensions are used as fixed word embeddings. 7SNLI has 3 classes of …","url":["https://www.cse.iitb.ac.in/~pb/papers/coling18-novelty.pdf"]}
-{"year":"2018","title":"NTT's Neural Machine Translation Systems for WMT 2018","authors":["M Morishita, J Suzuki, M Nagata - Proceedings of the Third Conference on Machine …, 2018"],"snippet":"… This year's submission includes the following features: • Noisy data filtering for Common Crawl and ParaCrawl corpora (Section 3.1) … This year, ParaCrawl and Common Crawl corpora, which were created by crawling parallel websites, were provided for training …","url":["http://www.aclweb.org/anthology/W18-6421"]}
-{"year":"2018","title":"NTU NLP Lab System at SemEval-2018 Task 10: Verifying Semantic Differences by Integrating Distributional Information and Expert Knowledge","authors":["YT Shiue, HH Huang, HH Chen - Proceedings of The 12th International Workshop on …, 2018"],"snippet":"… al., 2017). We use the pre-trained embeddings of English concepts3. 4. GloVe(Common Crawl): The GloVe model (Pennington et al., 2014) obtains word representation according to global co-occurrence statistics. We use …","url":["http://www.aclweb.org/anthology/S18-1171"]}
-{"year":"2018","title":"On Link Stability Detection for Online Social Networks","authors":["J Zhang, X Tao, L Tan, JCW Lin, H Li, L Chang - International Conference on …, 2018"],"snippet":"… Since the social network we obtain from the repositories of common crawl contains missing links and partial information, stochastic estimations are used to measure the accuracy and reliability of our experimental MVVA results [12] …","url":["https://link.springer.com/chapter/10.1007/978-3-319-98809-2_20"]}
-{"year":"2018","title":"On NDN and (“lack of”) Measurement","authors":["T Silverston"],"snippet":"… URLs Dataset • Web Crawling of 7 main organizations – Amazon, Ask, Stackoverflow, BBC, CNN, Google, Yahoo – Common Crawl Data Set repository • 1.73B URLs -> 7M for each organization /(Organization) …","url":["https://pdfs.semanticscholar.org/presentation/08d7/0e3f0b27b03a5f99f22bfeebeafa47c9bbb7.pdf"]}
-{"year":"2018","title":"On the Compressed Sensing Properties of Word Embeddings","authors":["M Khodak - 2018"],"snippet":"… word2vec embeddings trained on Google News and GloVe vectors trained on Common Crawl were obtained from public repositories [20, 23] while Amazon and Wikipedia embeddings were trained for 100 iterations using …","url":["ftp://ftp.cs.princeton.edu/techreports/2018/008.pdf"]}
-{"year":"2018","title":"On the Design and Tuning of Machine Learning Models for Language Toxicity Classification in Online Platforms","authors":["M Rybinski, W Miller, J Del Ser, MN Bilbao… - International Symposium on …, 2018"],"snippet":"… For (B) we have used vectors pre-trained on Common Crawl corpus with GloVe algorithm [9]. A more complete description of the text representations involved in our experiments is given below … For pre-trained embeddings …","url":["https://link.springer.com/chapter/10.1007/978-3-319-99626-4_29"]}
-{"year":"2018","title":"Ontology Augmentation Through Matching with Web Tables","authors":["O Lehmberg, O Hassanzadeh"],"snippet":"… 3 http://commoncrawl.org … The used PageRank values are obtained from the publicly available Common Crawl WWW Ranking.4 For each partition of columns, we use the maximum PageRank of all source web pages and …","url":["http://disi.unitn.it/~pavel/om2018/papers/om2018_LTpaper4.pdf"]}
-{"year":"2018","title":"Ontology Driven Extraction of Research Processes","authors":["V Pertsas, P Constantopoulos, I Androutsopoulos"],"snippet":"… Our experiments with other general-purpose, publicly available embeddings, such as those trained on the Common Crawl corpus using GloVe9, or those trained on Wikipedia articles with word2vec, showed inferior performance …","url":["http://www2.aueb.gr/users/ion/docs/iswc2018.pdf"]}
-{"year":"2018","title":"Open Bibliometrics and Undiscovered Public Knowledge","authors":["D Stuart - Online Information Review, 2018"],"snippet":"… Whether altmetrics is really any more open than traditional citation analysis is a matter of debate, although services such as Common Crawl (http://commoncrawl.org), an open repository of web crawl data, provides …","url":["https://www.emeraldinsight.com/doi/abs/10.1108/OIR-07-2017-0209"]}
-{"year":"2018","title":"OpenSeq2Seq: extensible toolkit for distributed and mixed precision training of sequence-to-sequence models","authors":["O Kuchaiev, B Ginsburg, I Gitman, V Lavrukhin, C Case… - arXiv preprint arXiv …, 2018"],"snippet":"… training). In our experiments, we used WMT 2016 English→German data set obtained by combining the Europarlv7, News Commentary v10, and Common Crawl corpora and resulting in roughly 4.5 million sentence pairs …","url":["https://arxiv.org/pdf/1805.10387"]}
-{"year":"2018","title":"Optimizing Automatic Evaluation of Machine Translation with the ListMLE Approach","authors":["M Li, M Wang - ACM Transactions on Asian and Low-Resource …, 2018"],"snippet":"… Bilingual parallel data comprising Europarl v7, Common Crawl corpus, and News Commentary v10, released by the WMT'2015 Machine Translation Shared Task [39] were employed to train the bidirectional lexical translation probability …","url":["https://dl.acm.org/citation.cfm?id=3226045"]}
-{"year":"2018","title":"Out-of-Distribution Detection using Multiple Semantic Label Representations","authors":["G Shalev, Y Adi, J Keshet - arXiv preprint arXiv:1808.06664, 2018"],"snippet":"… respectively. The third and forth representations were based on GloVe [36], where the third one was trained using both Wikipedia corpus and Gigawords [34] dataset, the fourth was trained using Common Crawl dataset. The …","url":["https://arxiv.org/pdf/1808.06664"]}
-{"year":"2018","title":"Pangloss: Fast Entity Linking in Noisy Text Environments","authors":["M Conover, M Hayes, S Blackburn, P Skomoroch… - arXiv preprint arXiv …, 2018"],"snippet":"… For each surface form Pangloss calls a RocksDB key-value store to retrieve candidate entries (represented by circles) based on associations between hyperlink anchor text and Wikipedia URLs in Wikipedia and Common Crawl (Section 3.5) … 3.3.4 Common Crawl …","url":["https://arxiv.org/pdf/1807.06036"]}
-{"year":"2018","title":"ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations","authors":["J Wieting, K Gimpel - Proceedings of the 56th Annual Meeting of the …, 2018"],"snippet":"… Dataset Avg. Length Avg. IDF Avg. Para. Score Vocab. Entropy Parse Entropy Total Size Common Crawl 24.0±34.7 7.7±1.1 0.83±0.16 7.2 3.5 0.16M … (2017). Its training data includes four sources: Common Crawl, CzEng 1.6 (Bojar …","url":["http://www.aclweb.org/anthology/P18-1042"]}
-{"year":"2018","title":"Periodizing Web Archiving: Biographical, Event-Based, National and Autobiographical Traditions","authors":["R Rogers"],"snippet":"Page 1. Periodizing Web Archiving: Biographical, Event-Based, National and Autobiographical Traditions Richard Rogers INTRODUCTION: HISTORIOGRAPHIES BUILT INTO WEB ARCHIVES The purpose of this chapter is …","url":["https://www.researchgate.net/profile/Richard_Rogers13/publication/327403018_Periodizing_Web_Archiving_Biographical_Event-Based_National_and_Autobiographical_Traditions/links/5b8d511e299bf114b7eeea4e/Periodizing-Web-Archiving-Biographical-Event-Based-National-and-Autobiographical-Traditions.pdf"]}
-{"year":"2018","title":"Phrase-Level Metaphor Identification using Distributed Representations of Word Meaning","authors":["O Zayed, JP McCrae, P Buitelaar - NAACL HLT 2018, 2018"],"snippet":"… 10. –GloVe Common Crawl5: We used a pretrained model on the Common Crawl dataset containing 840 billion tokens of web data (about 2 million words). The vectors are 300dimensional using 100 training iteration. For …","url":["http://www.cl.cam.ac.uk/~es407/papers/Fig-Lang2018-proceedings.pdf#page=93"]}
-{"year":"2018","title":"Phrase-level Self-Attention Networks for Universal Sentence Encoding","authors":["W Wu, H Wang, T Liu, S Ma - Proceedings of the 2018 Conference on Empirical …, 2018"],"snippet":"… and sentence textual similarity. 3.1 Model Configuration 300-dimensional GloVe (Pennington et al., 2014) word embeddings (Common Crawl, uncased) are used to represent words. Following Parikh et al. (2016), out-of-vocabulary …","url":["http://www.aclweb.org/anthology/D18-1408"]}
-{"year":"2018","title":"Platypus–A Multilingual Question Answering Platform for Wikidata","authors":["TP Tanon, MD de Assunçao, E Caron, FM Suchanek"],"snippet":"… The template analyzer is implemented using RasaNLU [34]. We used the Glove [35] word vectors trained on Common Crawl provided by Spacy and the RasaNLU entity extractor based on the CRFsuite library [36]. Our system can be accessed in three ways …","url":["https://2018.eswc-conferences.org/wp-content/uploads/2018/02/ESWC2018_paper_130.pdf"]}
-{"year":"2018","title":"Pointer-CNN for Visual Question Answering","authors":["J Svidt, JS Jepsen - 2018"],"snippet":"Page 1. Pointer-CNN for Visual Question Answering Jakob Svidt Aalborg University jsvidt13@student.aau.dk Jens Søholm Jepsen Aalborg University jjepse12@student. aau June 14, 2018 Abstract Visual Question Answering …","url":["https://projekter.aau.dk/projekter/files/281551620/SvidtJepsen.pdf"]}
-{"year":"2018","title":"Pooling Word Vector Representations Across Models","authors":["AC Graesser, V Rus - … Linguistics and Intelligent Text Processing: 18th …"],"snippet":"… The model was trained on non-zero elements in a global word co-occurrence matrix. We used the pre-trained model GloVe-42B which was trained on 42 billion words of Common Crawl corpus and it contains about 1.9 million unique tokens …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=dDNyDwAAQBAJ&oi=fnd&pg=PA17&dq=commoncrawl&ots=qmDDIrUYu6&sig=KN6CvMWGvERnEsXe5NqWJlRnqnM"]}
-{"year":"2018","title":"Predicting and Generating Discussion Inspiring","authors":["YJWJ Park"],"snippet":"… response time before being presented to the human. • An LSTM model [2] [4] using pretrained 300 dimensional GloVe word embeddings [5] on Common Crawl to embed the comments. A self-attention layer was added on top …","url":["http://web.stanford.edu/class/cs224n/reports/6879446.pdf"]}
-{"year":"2018","title":"Predicting Company Ratings through Glassdoor","authors":["TE Whittle"],"snippet":"… This dataset has 300-dimnesional vectors for 3 million words and phrases. The GloVe pre-trained embeddings come from a model trained on 42 billion tokens encountered by Common Crawl, a program designed to crawl the web and extract text …","url":["http://web.stanford.edu/class/cs224n/reports/6880837.pdf"]}
-{"year":"2018","title":"Predictive Embeddings for Hate Speech Detection on Twitter","authors":["R Kshirsagar, T Cukuvac, K McKeown, S McGregor - arXiv preprint arXiv:1809.10644, 2018"],"snippet":"… 5 Experimental Setup We tokenize the data using Spacy (HonnibalandJohnson, 2015). We use 300 Dimensional Glove Common Crawl Embeddings (840B Token) (Pennington et al., 2014) and fine tune them for the task. We …","url":["https://arxiv.org/pdf/1809.10644"]}
-{"year":"2018","title":"Preferred Answer Selection in Stack Overflow: Better Text Representations... and Metadata, Metadata, Metadata","authors":["X Xu, A Bennett, D Hoogeveen, JH Lau, T Baldwin"],"snippet":"… Word embeddings were set to 150 di- mensions. The co-occurrence weighting function's maximum value xmax was kept at the default of 10. For SEMEVAL, we used pretrained Common Crawl cased embeddings with 840G tokens …","url":["http://noisy-text.github.io/2018/pdf/W-NUT201819.pdf"]}
-{"year":"2018","title":"Preserved Structure Across Vector Space Representations","authors":["A Amatuni, E He, E Bergelson - arXiv preprint arXiv:1802.00840, 2018"],"snippet":"… We use the set of vectors pretrained by the GloVe authors on the Common Crawl corpus with 42 billion tokens, resulting in 300 dimensional vectors for 1.9 million unique words1. Such vectors have shown promise in modeling early semantic networks (Amatuni & Bergelson …","url":["https://arxiv.org/pdf/1802.00840"]}
-{"year":"2018","title":"Probabilistic German Morphosyntax","authors":["R Schäfer"],"snippet":"Page 1. Probabilistic German Morphosyntax HABILITATIONSSCHRIFT zur Erlangung der Lehrbefähigung für das Fach Germanistische und Allgemeine Sprachwissenschaft vorgelegt der Philosophischen Fakultät II der …","url":["http://rolandschaefer.net/wp-content/uploads/RolandSchaefer_2018_ProbabilisticGermanMorphosyntax_Habil_DRAFT.pdf"]}
-{"year":"2018","title":"PROMT Systems for WMT 2018 Shared Translation Task","authors":["A Molchanov - Proceedings of the Third Conference on Machine …, 2018"],"snippet":"… The CommonCrawl and (especially) ParaCrawl corpora were heavily filtered and normalized using the PROMT tools and algorithms (including language recognition, removal of meaningless sentences, in-house tools for parallel …","url":["http://www.aclweb.org/anthology/W18-6420"]}
-{"year":"2018","title":"Pseudo Descriptions for Meta-Data Retrieval","authors":["T Gollub, E Genc, N Lipka, B Stein - Proceedings of the 2018 ACM SIGIR International …, 2018"],"snippet":"… As reference collections, the TREC collections themselves as well as Wikipedia and the CommonCrawl are used … 2Not considered were lists, disambiguations, and short (#words < 250) articles. 3http://commoncrawl …","url":["https://dl.acm.org/citation.cfm?id=3234957"]}
-{"year":"2018","title":"QED: A fact verification system for the FEVER shared task","authors":["J Luken, N Jiang, MC de Marneffe - Proceedings of the First Workshop on Fact …, 2018"],"snippet":"… described below. 4.2 Embedding We used GloVe word embeddings (Pennington et al., 2014) with 300 dimensions pre-trained us- ing CommonCrawl to get a vector representation of the evidence sentence. We also experimented …","url":["http://www.aclweb.org/anthology/W18-5526"]}
-{"year":"2018","title":"Quantifying macroeconomic expectations in stock markets using Google Trends","authors":["J Bock - arXiv preprint arXiv:1805.00268, 2018"],"snippet":"… trends.google.com/trends/, March 5, 2018. 3 Common Crawl (42B tokens) GloVe word embeddings, retrieved from Stanford University, https://nlp.stanford.edu/projects/ glove/, March 4, 2018. 4 GloVe word embeddings are vector …","url":["https://arxiv.org/pdf/1805.00268"]}
-{"year":"2018","title":"Quantitative Web History Methods","authors":["A Cocciolo - The SAGE Handbook of Web History, 2018"]}
-{"year":"2018","title":"Quantum-like Generalization of Complex Word Embedding: a lightweight approach for textual classification","authors":["H Liu"],"snippet":"… (B) - crawl-300d-2M-vec ‡ 2 Million 600 Billion (C) - GloVe.Common Crawl.840B.300d † 2.2 Million 840 Billion Table 1. The pre-trained word embedding models selected for this experiment, where †= GloVe algorithm embeddings, ‡= Fasttext algorithm embeddings …","url":["http://ceur-ws.org/Vol-2191/paper19.pdf"]}
-{"year":"2018","title":"Quester: A Speech-Based Question Answering Support System for Oral Presentations","authors":["R Asadi, H Trinh, HJ Fell, TW Bickmore - … of the 23rd International Conference on …, 2018"],"snippet":"… ( , ) = √ 2 =0 (2) ( ) is the word vector representation of keyword k. We used a pre-trained GloVe [14] vector representation with 1.9 million uncased words and vectors with 300 elements, trained using 42 billion tokens of web data from Common Crawl …","url":["http://relationalagents.com/publications/IUI18.pdf"]}
-{"year":"2018","title":"Question Answering on SQuAD Dataset","authors":["ZDJ Dong, J Geng"],"snippet":"… We use the 300-dimensional case-insensitive Common Crawl GloVe word embeddings [7], and do not retrain the embeddings during training … We believe this is mainly because the Common Crawl version has a much larger …","url":["http://web.stanford.edu/class/cs224n/reports/6878267.pdf"]}
-{"year":"2018","title":"Question Answering System with Question Type Modelling","authors":["K Ponomareva"],"snippet":"… and bug fixing. It might be also useful to consider additional training data sets with more variety of question types present and using a larger pretrained word vectors set, such as CommonCrawl.840B.300d. Acknowledgments I …","url":["http://web.stanford.edu/class/cs224n/reports/6904810.pdf"]}
-{"year":"2018","title":"Ranking Documents by Answer-Passage Quality","authors":["E Yulianti, RC Chen, F Scholer, WB Croft, M Sanderson - 2018"],"snippet":"… We use the same set of word embeddings learned from the Y!A data (as with EmbYA), but the effectiveness is roughly comparable to a pre-trained model learned on the Common Crawl data [9]. For all methods tested in …","url":["http://rueycheng.com/paper/answer-passages.pdf"]}
-{"year":"2018","title":"Reaching Human-level Performance in Automatic Grammatical Error Correction: An Empirical Study","authors":["T Ge, F Wei, M Zhou - arXiv preprint arXiv:1807.01270, 2018"],"snippet":"Page 1. Microsoft Research Technical Report REACHING HUMAN-LEVEL PERFORMANCE IN AUTOMATIC GRAMMATICAL ERROR CORRECTION: AN EMPIRICAL STUDY Tao Ge, Furu Wei, Ming Zhou Natural Language …","url":["https://arxiv.org/pdf/1807.01270"]}
-{"year":"2018","title":"Reasoning with Sarcasm by Reading In-between","authors":["Y Tay, LA Tuan, SC Hui, J Su - arXiv preprint arXiv:1805.02856, 2018"],"snippet":"… We use the GloVe model trained on 2B Tweets for the Tweets and Reddit dataset. The Glove model trained on Common Crawl is used for the Debates corpus. The size of the word em- beddings is fixed at d = 100 and are fine-tuned during training …","url":["https://arxiv.org/pdf/1805.02856"]}
-{"year":"2018","title":"Recommendation System Developer","authors":["E Nandini, J Neal, T Olson, C Prater-Lee"],"snippet":"… This matrix is mapped to a vector space; GloVe uses a least squares regression model to minimize the dot product between word vectors. spaCy trains GloVe on Common Crawl corpus by default, which offers free web page data …","url":["https://taylorlolson.com/docs/recommendation-system-developer.pdf"]}
-{"year":"2018","title":"Refining Word Embeddings Using Intensity Scores for Sentiment Analysis","authors":["LC Yu, J Wang, KR Lai, X Zhang"],"snippet":"Page 1. 2329-9290 (c) 2017 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://www.researchgate.net/profile/Jin_Wang115/publication/322143064_Refining_Word_Embeddings_Using_Intensity_Scores_for_Sentiment_Analysis/links/5a4d9ad50f7e9b8284c4e442/Refining-Word-Embeddings-Using-Intensity-Scores-for-Sentiment-Analysis.pdf"]}
-{"year":"2018","title":"Regularized Training Objective for Continued Training for Domain Adaptation in Neural Machine Translation","authors":["H Khayrallah, B Thompson, K Duh, P Koehn - Proceedings of the 2nd Workshop on …, 2018"],"snippet":"… large, out-of-domain corpus we utilize bi- text from WMT2017 (Bojar et al., 2017),4 which contains data from several sources: Europarl parliamentary proceedings (Koehn, 2005),5 News Commentary (political and economic …","url":["http://www.aclweb.org/anthology/W18-2705"]}
-{"year":"2018","title":"Report on the Third Quality Translation Shared Task","authors":["P Williams, P Koehn, O Bojar, T Kocmi, L Specia… - 2018"],"snippet":"Page 1. This document is part of the Research and Innovation Action “Quality Translation 21 (QT21)”. This project has received funding from the European Union's Horizon 2020 program for ICT under grant agreement no. 645452 …","url":["http://www.qt21.eu/wp-content/uploads/2018/08/QT21-D4.3.pdf"]}
-{"year":"2018","title":"Representativeness of Latent Dirichlet Allocation Topics Estimated from Data Samples with Application to Common Crawl","authors":["Y Du, A Herzog, A Luckow, R Nerella, C Gropp, A Apon"],"snippet":"Abstract—Common Crawl is a massive multi-petabyte dataset hosted by Amazon. It contains archived HTML web page data from 2008 to date. Common Crawl has been widely used for text mining purposes. Using data extracted from Common Crawl has several advantages","url":["https://www.researchgate.net/profile/Yuheng_Du/publication/322512712_Representativeness_of_latent_dirichlet_allocation_topics_estimated_from_data_samples_with_application_to_common_crawl/links/5a67b4980f7e9b76ea8f086e/Representativeness-of-latent-dirichlet-allocation-topics-estimated-from-data-samples-with-application-to-common-crawl.pdf"]}
-{"year":"2018","title":"Reproducible Web Corpora: Interactive Archiving with Automatic Quality Assessment","authors":["J KIESEL, F KNEIST, M ALSHOMARY, B STEIN… - 2018"],"snippet":"… since disappeared. The Common Crawl [36] is also missing many of such resources. Other … the web. As a population of web pages to draw a sample from, we resort to the recent billion-page Common Crawl 2017-04 [36]. From …","url":["https://webis.de/downloads/publications/papers/stein_2018q.pdf"]}
-{"year":"2018","title":"Research Data Management","authors":["S Kühne"],"snippet":"… the web as graph data - 886 m. nodes (07/2018) - 5.4 bn. edges (07/2018) THE COMMON CRAWL ARCHIVE, http://commoncrawl.org Some research questions - prevalence of Web advertising - etymologies of words …","url":["https://www.ral.uni-leipzig.de/fileadmin/user_upload/dokumente/Schleyer/Kuehne_Introduction.pdf"]}
-{"year":"2018","title":"Research Frontiers in Information Retrieval Report from the Third Strategic Workshop on Information Retrieval in Lorne (SWIRL 2018)","authors":["JS Culpepper, F Diaz, MD Smucker"],"snippet":"Page 1. WORKSHOP REPORT Research Frontiers in Information Retrieval Report from the Third Strategic Workshop on Information Retrieval in Lorne (SWIRL 2018) Editors J. Shane Culpepper, Fernando Diaz, and Mark D. Smucker …","url":["http://www.damianospina.com/wp-content/uploads/2018/04/swirl3-report.pdf"]}
-{"year":"2018","title":"RI-Match: Integrating Both Representations and Interactions for Deep Semantic Matching","authors":["L Chen, Y Lan, L Pang, J Guo, J Xu, X Cheng - Asia Information Retrieval Symposium, 2018"],"snippet":"… First, we introduce our experimental settings, including parameter setting, and evaluation metrics. Parameter Settings. We initialize word embeddings in the word embedding layer with 300-dimensional Glove word vectors pre-trained in the 840B Common Crawl corpus …","url":["https://link.springer.com/chapter/10.1007/978-3-030-03520-4_9"]}
-{"year":"2018","title":"Rigging Research Results by Manipulating Top Websites Rankings","authors":["VL Pochat, T Van Goethem, W Joosen - arXiv preprint arXiv:1806.01156, 2018"],"snippet":"Page 1. Rigging Research Results by Manipulating Top Websites Rankings Victor Le Pochat, Tom Van Goethem and Wouter Joosen imec-DistriNet, KU Leuven 3001 Leuven, Belgium Email: firstname.lastname@cs.kuleuven.be …","url":["https://arxiv.org/pdf/1806.01156"]}
-{"year":"2018","title":"Risk Analysis of Information-Leakage Through Interest Packets in NDN","authors":["D Kondo, T Silverston, H Tode, T Asami, O Perrin"],"snippet":"… We collected URLs from the data repository provided by Common Crawl and we evaluate the performances of our per-packet filters … All the URLs in our data set provided by Common Crawl did not necessarily have <fragment> part as defined in RFC 1808 …","url":["http://ieeexplore.ieee.org/iel7/8106907/8116300/08116403.pdf"]}
-{"year":"2018","title":"Robots Learn Social Skills: End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots","authors":["Y Yoon, WR Ko, M Jang, J Lee, J Kim, G Lee - arXiv preprint arXiv:1810.12541, 2018"],"snippet":"… In the space of word embedding, words of similar meaning have similar representations, so understanding natural language is easier. We used the pretrained word embedding model GloVe, trained on the Common Crawl corpus [21] …","url":["https://arxiv.org/pdf/1810.12541"]}
-{"year":"2018","title":"S3BD: Secure Semantic Search over Encrypted Big Data in the Cloud","authors":["J Woodworth, MA Salehi - arXiv preprint arXiv:1809.07927, 2018"],"snippet":"Page 1. CONCURRENCY AND COMPUTATION: PRACTICE AND EXPERIENCE Concurrency Computat.: Pract. Exper. 0000; 00:1–22 Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cpe …","url":["https://arxiv.org/pdf/1809.07927"]}
-{"year":"2018","title":"Sandpiper: Scaling Probabilistic Inferencing to Large Scale Graphical Models","authors":["A Ulanov, M Marwah, M Kim, R Dathathri, C Zubieta…"],"snippet":"… It is the hyperlinked graph obtained from a web crawl conducted by Common Crawl in August 2012 [32] … We used a real, large-scale web graph for this use case. We derived it from the web graph available at Web Data Commons [30], based on the Common Crawl data [32] …","url":["http://marwah.org/publications/papers/bigdata2017.pdf"]}
-{"year":"2018","title":"Scheduled Multi-Task Learning: From Syntax to Translation","authors":["E Kiperwasser, M Ballesteros - arXiv preprint arXiv:1804.08915, 2018"],"snippet":"Page 1. Scheduled Multi-Task Learning: From Syntax to Translation Eliyahu Kiperwasser∗ Computer Science Department Bar-Ilan University Ramat-Gan, Israel elikip@gmail.com Miguel Ballesteros IBM Research 1101 …","url":["https://arxiv.org/pdf/1804.08915"]}
-{"year":"2018","title":"SDC: structured data collection by yourself","authors":["T Ohshima, M Toyama - Proceedings of the 8th International Conference on …, 2018"],"snippet":"… PVLDB 1, 1 (2008), 538--549. http://www.vldb.org/pvldb/171453916.pdf. 2. Common Crawl [nd]. Common Crawl. http://commoncrawl.org/. ([nd]). 3. DataHub - Frictionless Data [nd]. DataHub - Frictionless Data. http://datahub.io/. ([nd]) …","url":["https://dl.acm.org/citation.cfm?id=3200849"]}
-{"year":"2018","title":"Searching Arguments in German with ArgumenText","authors":["C Stahlhut"],"snippet":"… for arguments on a topic such as “nuclear energy”, it first retrieves relevant documents via Elasticsearch from a large collection of documents, such as Common Crawl2. In the … 1A demonstrator is publicly available at …","url":["http://desires.dei.unipd.it/papers/paper20.pdf"]}
-{"year":"2018","title":"Searching for the X-Factor: Exploring Corpus Subjectivity for Word Embeddings","authors":["M Tkachenko, CC Chia, H Lauw - Proceedings of the 56th Annual Meeting of the …, 2018"],"snippet":"… embeddings. The previous preoccupation centers around corpus size, ie, a larger corpus is perceived to be richer in statistical information. For instance, popular corpora include Wikipedia, Common Crawl, and Google News. We …","url":["http://www.aclweb.org/anthology/P18-1112"]}
-{"year":"2018","title":"SEGBOT: A Generic Neural Text Segmentation Model with Pointer Network","authors":["J Li, A Sun, S Joty - IJCAI. Under Review, 2018"],"snippet":"Page 1. SEGBOT: A Generic Neural Text Segmentation Model with Pointer Network Jing Li, Aixin Sun and Shafiq Joty School of Computer Science and Engineering, Nanyang Technological University, Singapore …","url":["https://www.researchgate.net/profile/Aixin_Sun/publication/325168535_SEGBOT_A_Generic_Neural_Text_Segmentation_Model_with_Pointer_Network/links/5afb9f710f7e9b3b0bf2a964/SEGBOT-A-Generic-Neural-Text-Segmentation-Model-with-Pointer-Network.pdf"]}
-{"year":"2018","title":"Semantic Term\" Blurring\" and Stochastic\" Barcoding\" for Improved Unsupervised Text Classification","authors":["RF Martorano III - arXiv preprint arXiv:1811.02456, 2018"],"snippet":"… trained on millions of documents from Google News. In the case of later models, they have trained on common crawl, a dataset of billions of web pages. The high level intuition with these models, is that terms used in similar contexts, likely have similar semantics …","url":["https://arxiv.org/pdf/1811.02456"]}
-{"year":"2018","title":"Semi-Supervised Neural System for Tagging, Parsing and Lemmatization","authors":["P Rybak, A Wróblewska - CoNLL 2018, 2018"],"snippet":"… For Uyghur language only 3M words are available. The provided data sets come either from Wikipedia or Commom Crawl. Where it is possible we choose the sentences from Common Crawl, due to longer (on average) sentence sizes …","url":["http://universaldependencies.org/conll18/proceedings/K18-2.pdf#page=53"]}
-{"year":"2018","title":"Sentence Classification for Investment Rules Detection","authors":["Y Mansar, S Ferradans - Proceedings of the First Workshop on Economics and …, 2018"],"snippet":"… embedding. This is justified by the fact that some words used in prospectuses are uncommon in the general use of language and thus are not included in available word vectors pre-trained on Wikipedia or common crawl alone …","url":["http://www.aclweb.org/anthology/W18-3106"]}
-{"year":"2018","title":"Sentence Encoding with Tree-constrained Relation Networks","authors":["L Yu, CM d'Autume, C Dyer, P Blunsom, L Kong… - arXiv preprint arXiv …, 2018"],"snippet":"Page 1. SENTENCE ENCODING WITH TREE-CONSTRAINED RE- LATION NETWORKS Lei Yu Cyprien de Masson d'Autume Chris Dyer Phil Blunsom Lingpeng Kong Wang Ling DeepMind {leiyu, cyprien, cdyer, pblunsom, lingpenk, lingwang}@google.com ABSTRACT …","url":["https://arxiv.org/pdf/1811.10475"]}
-{"year":"2018","title":"Sentence Modeling via Multiple Word Embeddings and Multi-level Comparison for Semantic Textual Similarity","authors":["HN Tien, MN Le, Y Tomohiro, I Tatsuya - arXiv preprint arXiv:1805.07882, 2018"],"snippet":"… The em- bedding representations in fastText are 300dimensional vectors. • GloVe is a 300-dimensional word embedding model learned on aggregated global wordword co-occurrence statistics from Common Crawl (840 billion tokens) …","url":["https://arxiv.org/pdf/1805.07882"]}
-{"year":"2018","title":"Sentence Selection and Weighting for Neural Machine Translation Domain Adaptation","authors":["R Wang, M Utiyama, A Finch, L Liu, K Chen, E Sumita - IEEE/ACM Transactions on …, 2018"],"snippet":"Page 1. 2329-9290 (c) 2018 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/8360031/"]}
-{"year":"2018","title":"Sentence Similarity Learning Method based on Attention Hybrid Model","authors":["Y Wang, X Di, J Li, H Yang, L Bi - Journal of Physics: Conference Series, 2018"],"snippet":"… with our method. 4.3. Experimental Setup We initialize word representation in the word embedding layer with the 300-dimensional GloVe word vectors pre-trained from the Common Crawl Corpus [18]. Embeddings for words …","url":["http://iopscience.iop.org/article/10.1088/1742-6596/1069/1/012119/pdf"]}
-{"year":"2018","title":"Sentence Simplification with Memory-Augmented Neural Networks","authors":["T Vu, B Hu, T Munkhdalai, H Yu - arXiv preprint arXiv:1804.07445, 2018"],"snippet":"… We used the same hyperparameters across all datasets. Word embeddings were initialized either randomly or with Glove vectors (Pennington et al., 2014) pre-trained on Common Crawl data (840B tokens), and fine-tuned during training …","url":["https://arxiv.org/pdf/1804.07445"]}
-{"year":"2018","title":"SentEval: An Evaluation Toolkit for Universal Sentence Representations","authors":["A Conneau, D Kiela - arXiv preprint arXiv:1803.05449, 2018"],"snippet":"… Continuous bag-of-words embeddings (average of word vectors). We consider the most commonly used pretrained word vectors available, namely the fastText (Mikolov et al., 2017) and the GloVe (Pennington et al., 2014) vectors trained on CommonCrawl …","url":["https://arxiv.org/pdf/1803.05449"]}
-{"year":"2018","title":"Sentiment Bias in Predictive Text Recommendations Results in Biased Writing","authors":["KC Arnold, K Chauncey, KZ Gajos"],"snippet":"… lending, or law enforcement—if the data sets used to train the algorithms are bi- ased [2]. Such biased data sets are more common than initially suspected: Recent work demonstrated that two popular text corpora, the …","url":["https://www.eecs.harvard.edu/~kgajos/papers/2018/arnold18sentiment.pdf"]}
-{"year":"2018","title":"Sentiment Expression Boundaries in Sentiment Polarity Classification","authors":["R Kaljahi, J Foster - Proceedings of the 9th Workshop on Computational …, 2018"],"snippet":"… The input layer for these systems is the concatenation of an embedding layer, which uses pre-trained GloVe (Pennington et al., 2014) word embeddings 2 (1.9M vocabulary Common Crawl), concatenated with a one-hot vector …","url":["http://www.aclweb.org/anthology/W18-6222"]}
-{"year":"2018","title":"Seq2Sick: Evaluating the Robustness of Sequence-to-Sequence Models with Adversarial Examples","authors":["M Cheng, J Yi, H Zhang, PY Chen, CJ Hsieh - arXiv preprint arXiv:1803.01128, 2018"],"snippet":"… one is trained from scratch. For the machine translation task, we train our model using 453k pairs from the Europal corpus of German-English WMT 157, common crawl and news-commentary. We use the hyper-parameters suggested …","url":["https://arxiv.org/pdf/1803.01128"]}
-{"year":"2018","title":"Sequence-to-sequence Models for Cache Transition Systems","authors":["X Peng, L Song, D Gildea, G Satta"],"snippet":"… Hidden state sizes for both encoder and decoder are set to 100. The word embeddings are initialized from Glove pretrained word embeddings (Pennington et al., 2014) on Common Crawl, and are not updated during training …","url":["https://www.cs.rochester.edu/u/gildea/pubs/peng-acl18.pdf"]}
-{"year":"2018","title":"Shortcutting Label Propagation for Distributed Connected Components","authors":["S Stergiou, D Rughwani, K Tsioutsiouliklis - … Conference on Web Search and Data …, 2018"],"snippet":"… Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references. 1. 2016. Common Crawl. (2016). http://commoncrawl.org/. 2. 2016. Twitter Graph. (2016) …","url":["https://dl.acm.org/citation.cfm?id=3159696"]}
-{"year":"2018","title":"Simple Algorithms For Sentiment Analysis On Sentiment Rich, Data Poor Domains.","authors":["PK Sarma, W Sethares - Proceedings of the 27th International Conference on …, 2018"],"snippet":"… Furthermore, in some of these domains, representing words from off-the-shelf word embeddings such as ones obtained from training word2vec, GloVe on Wikipedia or common-crawl may not be efficient. This is because the …","url":["http://www.aclweb.org/anthology/C18-1290"]}
-{"year":"2018","title":"SLIND: Identifying Stable Links in Online Social Networks","authors":["J Zhang, L Tan, X Tao, X Zheng, Y Luo, JCW Lin - International Conference on …, 2018"],"snippet":"… The dataset chosen for this study, as well as for the demo, was crawled from Facebook and obtained from the repositories of the Common Crawl (August 2016) 1 . It is de-anonymized to reveal the following relational …","url":["https://link.springer.com/chapter/10.1007/978-3-319-91458-9_54"]}
-{"year":"2018","title":"Smart Focused Web Crawler for Hidden Web","authors":["S Kaur, G Geetha - Information and Communication Technology for …, 2019"],"snippet":"… The number of partitions will depend on the number of URLs in site database. Tel-8 and common crawl datasets will be used. MapReduce function will be called, and the input will split into 64 MB plus copies of this on other clusters …","url":["https://link.springer.com/chapter/10.1007/978-981-13-0586-3_42"]}
-{"year":"2018","title":"SocialLink: exploiting graph embeddings to link DBpedia entities to Twitter profiles","authors":["Y Nechaev, F Corcoglioniti, C Giuliano - Progress in Artificial Intelligence, 2018"],"snippet":"Page 1. Progress in Artificial Intelligence https://doi.org/10.1007/s13748-018-0160-x REGULAR PAPER SocialLink: exploiting graph embeddings to link DBpedia entities to Twitter profiles Yaroslav Nechaev1,2 · Francesco Corcoglioniti1 · Claudio Giuliano1 …","url":["https://link.springer.com/article/10.1007/s13748-018-0160-x"]}
-{"year":"2018","title":"Software Requirements Classification Using Word Embeddings and Convolutional Neural Networks","authors":["VL Fong - 2018"],"snippet":"Page 1. SOFTWARE REQUIREMENTS CLASSIFICATION USING WORD EMBEDDINGS AND CONVOLUTIONAL NEURAL NETWORKS A Thesis presented to the Faculty of California Polytechnic State University, San Luis Obispo In Partial Fulfillment …","url":["https://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=3249&context=theses"]}
-{"year":"2018","title":"SOLVENT: A Mixed Initiative System for Finding Analogies between Research Papers","authors":["J CHAN, JC CHANG, TOM HOPE, D SHAHAF… - 2018"],"snippet":"… We originally used pre-trained GloVe [35] vectors trained on the Common Crawl dataset 5. However, baseline performance was very poor … Finally, we used an initial prototype GloVe model (with Common Crawl) to suggest new matches we might have missed …","url":["http://joelchan.me/assets/pdf/2018-cscw-schema-highlighter.pdf"]}
-{"year":"2018","title":"Speech-Based Real-Time Presentation Tracking Using Semantic Matching","authors":["R Asadi - 2017"],"snippet":"Speech-Based Real-Time Presentation Tracking Using Semantic Matching. Abstract. Oral presentations are an essential yet challenging aspect of academic and professional life. To date, many commercial and research products …","url":["http://search.proquest.com/openview/a91c85d71f1e130a00bee5b6f95d90e3/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2018","title":"Stop Illegal Comments: A Multi-Task Deep Learning Approach","authors":["A Elnaggar, B Waltl, I Glaser, J Landthaler… - arXiv preprint arXiv …, 2018"],"snippet":"… 12] and our Glove). The Fast Text is 2 million word vectors trained on Common Crawl with dimension 300, while Glove is 2.2 million word vectors trained on Common Crawl with dimension 300. Furthermore, we trained a custom …","url":["https://arxiv.org/pdf/1810.06665"]}
-{"year":"2018","title":"Studio Ousia's Quiz Bowl Question Answering System at NIPS HCQA 2017","authors":["I Yamada"],"snippet":"… Moreover, we use the GloVe word embeddings [10] trained on the 840 billion Common Crawl corpus to initialize the word representations. We randomly select 10% questions from the dataset as a validation set and use the remaining questions to train the model …","url":["http://www.cs.umd.edu/~miyyer/data/Ikuya.pdf"]}
-{"year":"2018","title":"Studio Ousia's Quiz Bowl Question Answering System","authors":["I Yamada, R Tamaki, H Shindo, Y Takefuji"],"snippet":"… 1,000. We use filter window sizes of 2, 3, 4, and 5, and 1,000 feature maps for each filter. We use the GloVe word embeddings [12] trained on the 840 billion Common Crawl corpus to initialize the word representations. As in …","url":["https://www.researchgate.net/profile/Yoshiyasu_Takefuji/publication/323535360_Studio_Ousia%27s_Quiz_Bowl_Question_Answering_System/links/5a9a6cde45851586a2aa0ade/Studio-Ousias-Quiz-Bowl-Question-Answering-System.pdf"]}
-{"year":"2018","title":"Studying the Difference Between Natural and Programming Language Corpora","authors":["C Casalnuovo, K Sagae, P Devanbu - arXiv preprint arXiv:1806.02437, 2018"],"snippet":"… The German and Spanish corpora were selected from a sample of files from the unlabeled datasets from the ConLL 2017 Shared Task (Ginter et al, 2017), which consist of web text obtained from CommonCrawl.8 Like the 1 billion …","url":["https://arxiv.org/pdf/1806.02437"]}
-{"year":"2018","title":"Style Transfer Through Back-Translation","authors":["S Prabhumoye, Y Tsvetkov, R Salakhutdinov, AW Black - arXiv preprint arXiv …, 2018"],"snippet":"… We used data from Workshop in Statistical Machine Translation 2015 (WMT15) (Bojar et al., 2015) to train our translation models. We used the French– English data from the Europarl v7 corpus, the news commentary …","url":["https://arxiv.org/pdf/1804.09000"]}
-{"year":"2018","title":"SumeCzech: Large Czech News-Based Summarization Dataset","authors":["M Straka, N Mediankin, T Kocmi, Z Žabokrtský… - Proceedings of the Eleventh …, 2018"],"snippet":"… The raw data for the dataset was collected from the Common Crawl project2 using the Common Crawl API. Initially, five Czech news websites were selected to create the dataset: novinky.cz, lidovky.cz, denik.cz, idnes.cz, and ihned.cz …","url":["http://www.aclweb.org/anthology/L18-1551"]}
-{"year":"2018","title":"Supplementary Material for “Improved Fusion of Visual and Language Representations by Dense Symmetric Co-Attention for Visual Question Answering”","authors":["DK Nguyen, T Okatani"],"snippet":"… All the questions were tokenized using Python Natural Language Toolkit (nltk) [2]. We used the vocabulary provided by the CommonCrawl-840B Glove model for English word vectors [11], and set out-of-vocabulary words to unk …","url":["http://openaccess.thecvf.com/content_cvpr_2018/Supplemental/3586-supp.pdf"]}
-{"year":"2018","title":"Survey of Simple Neural Networks in Semantic Textual Similarity Analysis","authors":["DS Prijatelj, J Ventura, J Kalita"],"snippet":"… vectors. This specific set of word vectors have 300 dimensions and were pre-trained on 840 billion tokens taken from Common Crawl3. Different pretrained word vectors may be used in-place of this specific pretrained set …","url":["http://cs.uccs.edu/~jkalita/work/reu/REU2017/11Prijatelj.pdf"]}
-{"year":"2018","title":"SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference","authors":["R Zellers, Y Bisk, R Schwartz, Y Choi - arXiv preprint arXiv:1808.05326, 2018"],"snippet":"… We consider three different types of word representations: 300d GloVe vectors from Common Crawl (Pennington et al., 2014), 300d Numberbatch vectors retrofitted using ConceptNet relations (Speer et al., 2017), and …","url":["https://arxiv.org/pdf/1808.05326"]}
-{"year":"2018","title":"Systems and methods for improved user interface","authors":["Z Wei, T Nguyen, I Chan, KM Liou, H Wang, H Lu - US Patent App. 15/621,647, 2018"],"snippet":"Aspects of the present disclosure relate to systems and methods for a voice-centric virtual or soft keyboard (or keypad). Unlike other keyboards, embodiments of the present disclosure prioritize the voice keyboard, meanwhile providing users with a quick and uniform navigation to …","url":["https://patents.google.com/patent/US20180011688A1/en"]}
-{"year":"2018","title":"T2S: An Encoder-Decoder Model for Topic-Based Natural Language Generation","authors":["W Ou, C Chen, J Ren - International Conference on Applications of Natural …, 2018"],"snippet":"… We initialize our word embeddings with publicly available 300-dimensional Glove vectors [13], which is trained on 840 billion tokens of Common Crawl data 2 . Words that do not exist in the pretrained Glove vectors are replaced by “<unk>” token …","url":["https://link.springer.com/chapter/10.1007/978-3-319-91947-8_15"]}
-{"year":"2018","title":"TabVec: Table Vectors for Classification of Web Tables","authors":["M Ghasemi-Gol, P Szekely - arXiv preprint arXiv:1802.06290, 2018"],"snippet":"… They evaluated their system on the common crawl dataset, and reported signi cant improvement compared to previous feature based methods … Three of these datasets are from unusual domains, and one is a sample from Common Crawl …","url":["https://arxiv.org/pdf/1802.06290"]}
-{"year":"2018","title":"TCS Research at SemEval-2018 Task 1: Learning Robust Representations using Multi-Attention Architecture","authors":["H Meisheri, L Dey - Proceedings of The 12th International Workshop on …, 2018"],"snippet":"… corpus which results in parallel attention mechanism - one set from the twitter space and another from a common crawl corpus … 2014) trained over common crawl corpus with 300 dimension vector, Character1 level embeddings trained …","url":["http://www.aclweb.org/anthology/S18-1043"]}
-{"year":"2018","title":"Temporal Modular Networks for Retrieving Complex Compositional Activities in Videos","authors":["L Fei-Fei, JC Niebles"],"snippet":"… 4.2. The Stanford Parser [27] is used to obtain the initial parse trees for the compositional structure. For word vectors as part of the base module input, we use the 300-dimensional GloVe [36] vectors pretrained on Common Crawl (42 billion tokens) …","url":["http://svl.stanford.edu/assets/papers/liu2018eccv.pdf"]}
-{"year":"2018","title":"Ten Years of WebTables","authors":["M Cafarella, A Halevy, H Lee, J Madhavan, C Yu… - Proceedings of the VLDB …, 2018"],"snippet":"… Several researchers produced web tables from the public Common Crawl [1, 24, 15], thereby making them available to a broad audience outside the large Web companies. Wang, et al. [36] improved ex- traction quality by leveraging curated knowledge bases …","url":["http://www.vldb.org/pvldb/vol11/p2140-cafarella.pdf"]}
-{"year":"2018","title":"Text Embeddings for Retrieval From a Large Knowledge Base","authors":["T Cakaloglu, C Szegedy, X Xu - arXiv preprint arXiv:1810.10176, 2018"],"snippet":"… We specially utilized the ”glove-840B-300d” pre-trained word vectors where it was trained on using the common crawl within 840B tokens, 2.2M vocab, cased, 300d vectors. We created the GloVe representation of our corpus …","url":["https://arxiv.org/pdf/1810.10176"]}
-{"year":"2018","title":"Text-based Sentiment Analysis and Music Emotion Recognition","authors":["E Çano - 2018"],"snippet":"… 38 3.4 Confusion matrix of lexicon-generated song labels . . . . . 42 5.1 Listofwordembeddingcorpora . . . . . 65 5.2 Google News compared with Common Crawl . . . . . 69 5.3 Propertiesofself_w2vmodels . . . . . 70 …","url":["https://www.researchgate.net/profile/Erion_Cano/publication/325651523_Text-based_Sentiment_Analysis_and_Music_Emotion_Recognition/links/5b1a8d640f7e9b68b429cdae/Text-based-Sentiment-Analysis-and-Music-Emotion-Recognition.pdf"]}
-{"year":"2018","title":"Text-Driven Head Motion Synthesis Using Neural Networks","authors":["BTS Bojlén"],"snippet":"… We also compared embeddings trained on Common Crawl (a large collection of websites), and on Wikipedia and the Gigaword corpus of news articles. The model trained was a baseline RNN with the architecture specified in Table 4.2 …","url":["https://btao.org/static/dissertation.pdf"]}
-{"year":"2018","title":"TEXTBUGGER: Generating Adversarial Text Against Real-world Applications","authors":["J Li, S Ji, T Du, B Li, T Wang"],"snippet":"… This is because we observe that the stop-words also have impact on the prediction results. In particular, our experiments utilize the 300-dimension GloVe embeddings7 trained on 840 billion tokens of Common Crawl. Words …","url":["https://nesa.zju.edu.cn/download/TEXTBUGGER%20Generating%20Adversarial%20Text%20Against%20Real-world%20Applications.pdf"]}
-{"year":"2018","title":"The ADAPT System Description for the IWSLT 2018 Basque to English Translation Task","authors":["A Poncelas, A Way, K Sarasola - International Workshop on Spoken Language …, 2018"],"snippet":"… pair (see Table 4)[12]. In particular, we use the CommonCrawl, Europarl V7, NewsCommentary V12 and UN datasets for training, 5 the NewsTest 2008-2012 corpora for validation and NewsTest 2013 for testing. We did not use …","url":["https://workshop2018.iwslt.org/downloads/Proceedings_IWSLT_2018.pdf#page=91"]}
-{"year":"2018","title":"The AFRL WMT18 Systems: Ensembling, Continuation and Combination","authors":["J Gwinnup, T Anderson, G Erdmann, K Young - … of the Third Conference on Machine …, 2018"],"snippet":"… We took the Russian and English monolingual CommonCrawl (Smith et al., 2013) data provided by the organizers and applied tokenization and BPE with our common, joint model … 2013. Dirt cheap web-scale parallel text from the common crawl …","url":["http://www.aclweb.org/anthology/W18-6411"]}
-{"year":"2018","title":"The Geometry of Culture: Analyzing Meaning through Word Embeddings","authors":["AC Kozlowski, M Taddy, JA Evans - arXiv preprint arXiv:1803.09288, 2018"],"snippet":"Page 1. The Geometry of Culture: Analyzing Meaning through Word Embeddings Austin C. Kozlowski​1 Matt Taddy​2,3 James A. Evans​1 1 ​University of Chicago, Department of Sociology 2 ​University of Chicago, Booth School of Business 3 ​Amazon …","url":["https://arxiv.org/pdf/1803.09288"]}
-{"year":"2018","title":"The Importance of Subword Embeddings in Sentence Pair Modeling","authors":["W Lan, W Xu"],"snippet":"… GloVe word vectors (Pennington et al.), trained on 27 billion words from Twitter (vocabulary size of 1.2 milion words) for social media datasets, and 300-dimensional GloVe vectors, trained on 840 billion words (vocabulary …","url":["https://pdfs.semanticscholar.org/c99f/e106e7d1cc62f7cb73ea6fc745b8679e4d2f.pdf"]}
-{"year":"2018","title":"The Knowledge and Language Gap in Medical Information Seeking","authors":["L Soldaini - 2018"],"snippet":"The Knowledge and Language Gap in Medical Information Seeking. Abstract. Interest in medical information retrieval has risen significantly in the last few years. The Internet has become a primary source for consumers looking …","url":["http://search.proquest.com/openview/e669cd1478b33d52fa4cc71e8393c639/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2018","title":"The MLLP-UPV German-English Machine Translation System for WMT18","authors":["J Iranzo-Sánchez, P Baquero-Arnal, GVG Dıaz-Munıo…"],"snippet":"… 422 Page 2. Table 1: Size by corpus of the WMT18 parallel dataset Corpus Sentences (M) News Commentary v13 0.3 Rapid (press releases) 1.3 Common Crawl 1.9 Europarl v7 2.4 ParaCrawl 36.4 WMT18 total 42.3 the rest of the WMT corpora …","url":["http://www.statmt.org/wmt18/pdf/WMT041.pdf"]}
-{"year":"2018","title":"The Natural Language Decathlon: Multitask Learning as Question Answering","authors":["B McCann, NS Keskar, C Xiong, R Socher - arXiv preprint arXiv:1806.08730, 2018"],"snippet":"Page 1. The Natural Language Decathlon: Multitask Learning as Question Answering Bryan McCann, Nitish Shirish Keskar, Caiming Xiong, Richard Socher Salesforce Research {bmccann,nkeskar,cxiong,rsocher}@salesforce.com Abstract …","url":["https://arxiv.org/pdf/1806.08730"]}
-{"year":"2018","title":"The RWTH Aachen Machine Translation Systems for IWSLT 2017","authors":["P Bahar, J Rosendahl, N Rossenbach, H Ney"],"snippet":"… The majority of removed sentence pairs are part of the Common Crawl (300k sentences ie 14% of Common Crawl) and the OpenSubtitles corpora (1000k sentences ie 8% of OpenSubtitles) … Common Crawl Europarl UN News Comment OpenSub QED TED Wiki Total …","url":["https://www-i6.informatik.rwth-aachen.de/publications/download/1061/BaharParniaRosendahlJanRossenbachNickNeyHermann--TheRWTHAachenMachineTranslationSystemsforIWSLT2017--2017.pdf"]}
-{"year":"2018","title":"The RWTH Aachen University Filtering System for the WMT 2018 Parallel Corpus Filtering Task","authors":["N Rossenbach, J Rosendahl, Y Kim, M Graça… - Proceedings of the Third …, 2018"],"snippet":"… We train IBM1 models for both directions (s2t and t2s) using the bilingual data from the WMT 2018 German↔English task namely the Europarl, CommonCrawl, NewsCommentary and Rapid corpus. 4.3 Neural Network Language Model …","url":["http://www.aclweb.org/anthology/W18-6487"]}
-{"year":"2018","title":"The RWTH Aachen University Supervised Machine Translation Systems for WMT 2018","authors":["J Schamper, J Rosendahl, P Bahar, Y Kim, A Nix… - Proceedings of the Third …, 2018"],"snippet":"… 1.4% BLEU. The Transformer model was trained using the standard parallel WMT 2018 data sets (namely Europarl, CommonCrawl, NewsCommentary and Rapid, in total 5.9M sentence pairs) as well as the 4.2M sen3http://www …","url":["http://www.aclweb.org/anthology/W18-6426"]}
-{"year":"2018","title":"The Speechmatics Parallel Corpus Filtering System for WMT18","authors":["T Ash, R Francis, W Williams - Proceedings of the Third Conference on Machine …, 2018"],"snippet":"… This data comprises the data for the WMT 2018 news translation task data for German-English without the Paracrawl parallel corpus. This data is approximately 130M words, drawn from Europarl, Common Crawl, News …","url":["http://www.aclweb.org/anthology/W18-6472"]}
-{"year":"2018","title":"The study of keyword search in open source search engines and digital forensics tools with respect to the needs of cyber crime investigations","authors":["J Hansen - 2017"],"snippet":"Page 1. The study of keyword search in open source search engines and digital forensics tools with respect to the needs of cyber crime investigations Joachim Hansen Master in Information Security Supervisor: Katrin Franke …","url":["https://brage.bibsys.no/xmlui/bitstream/handle/11250/2479196/18187_FULLTEXT.pdf?sequence=1"]}
-{"year":"2018","title":"The University of Cambridge's Machine Translation Systems for WMT18","authors":["F Stahlberg, A de Gispert, B Byrne - arXiv preprint arXiv:1808.09465, 2018"],"snippet":"… Page 3. Corpus Over-sampling #Sentences Common Crawl 2x 4.43M Europarl v7 2x 3.76M News Commentary v13 2x 0.57M Rapid 2016 2x 2.27M ParaCrawl 1x 11.16M Synthetic (news-2017) 1x 20.00M Total 42.19M Table …","url":["https://arxiv.org/pdf/1808.09465"]}
-{"year":"2018","title":"The University of Edinburgh's Submissions to the WMT18 News Translation Task","authors":["B Haddow, N Bogoychev, D Emelin, U Germann… - Proceedings of the Third …, 2018"],"snippet":"… closely Corpus % Back translations1 50% CommonCrawl 5% Europarl 15% News-commentary 10% ParaCrawl 10% Rapid 10% Table 1: Blend of data for training the DE↔EN en- semble models (40M sentence pairs total) …","url":["http://www.aclweb.org/anthology/W18-6412"]}
-{"year":"2018","title":"The USTC-NEL Speech Translation system at IWSLT 2018","authors":["D Liu, J Liu, W Guo, S Xiong, Z Ma, R Song, C Wu… - arXiv preprint arXiv …, 2018"],"snippet":"… Page 2. Table 2: text training data. Corpus raw filtered commoncrawl 2.39M 1.80M rapid 1.32M 1.00M europal 1.92M 1.81M commentary 0.284M 0.233M paracrawl 36.35M 12.35M opensubtitles 22.51M 14.24M WIT3(in domain) 0.209M 0.207M …","url":["https://arxiv.org/pdf/1812.02455"]}
-{"year":"2018","title":"Topic coherence analysis for the classification of Alzheimer's disease}}","authors":["A Pompili, A Abad, DM de Matos, IP Martins - Proc. IberSPEECH 2018, 2018"],"snippet":"… regularities among sentences. To this purpose, we rely on a pre-trained model of word vector representations containing 2 million word vectors, in 300 dimensions, trained with fastText on Common Crawl [27]. In the process …","url":["https://www.isca-speech.org/archive/IberSPEECH_2018/pdfs/IberS18_O5-1_Pompili.pdf"]}
-{"year":"2018","title":"Topic Modeling for Analyzing Open-Ended Survey Responses","authors":["AS Pietsch, S Lessmann"],"snippet":"… Word2Vec [32] and the second one on Common Crawl web data via Global Vectors for Word Representation (GloVe) [33] … The set is trained on 42 billion tokens of Common Crawl web data and contains 300-dimensional vectors …","url":["https://www.wiwi.hu-berlin.de/de/forschung/irtg/results/discussion-papers/discussion-papers-2017-1/irtg1792dp2018-054.pdf"]}
-{"year":"2018","title":"Toward better reasoning from natural language","authors":["A Purtee - 2018"],"snippet":"Page 1. Toward Better Reasoning from Natural Language by Adam Lee Purtee Submitted in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy Supervised by Professor Lenhart Schubert and …","url":["https://urresearch.rochester.edu/fileDownloadForInstitutionalItem.action?itemId=34810&itemFileId=186239"]}
-{"year":"2018","title":"Towards Automated Factchecking: Developing an Annotation Schema and Benchmark for Consistent Automated Claim Detection","authors":["L Konstantinovskiy, O Price, M Babakar, A Zubiaga - arXiv preprint arXiv:1809.08193, 2018"],"snippet":"… The method provided by InferSent involves words be- ing converted to their common crawl GloVe implementations before being passed through a bidirectional long-short-term memory (BiLSTM) network (Hochreiter & Schmidhuber, 1997) …","url":["https://arxiv.org/pdf/1809.08193"]}
-{"year":"2018","title":"Towards Knowledge Graph Construction from Entity Co-occurrence","authors":["N Heist"],"snippet":"… patterns. 2 https://www.mturk.com/ 3 Pages starting with List of in http://downloads. dbpedia.org/2016-10/corei18n/en/labels en.ttl.bz2 4 http://commoncrawl.org/ 5 http://webdatacommons.org/structureddata/#results-2017-1 Page 7 …","url":["https://people.kmi.open.ac.uk/francesco/wp-content/uploads/2018/11/EKAWDC2018_3.pdf"]}
-{"year":"2018","title":"Towards Linear Time Neural Machine Translation with Capsule Networks","authors":["M Wang, J Xie, Z Tan, J Su - arXiv preprint arXiv:1811.00287, 2018"],"snippet":"… French translation are presented in Table 1. We compare CAPSNMT with various other systems including the winning system in WMT'14 (Buck et al., 2014), a phrase-based system whose language models were trained on …","url":["https://arxiv.org/pdf/1811.00287"]}
-{"year":"2018","title":"Towards Personalized Learning using Counterfactual Inference for Randomized Controlled Trials","authors":["S Zhao - 2018"],"snippet":"Page 1. Towards Personalized Learning using Counterfactual Inference for Randomized Controlled Trials by Siyuan Zhao A Dissertation Submitted to the Faculty of the WORCESTER POLYTECHNIC INSTITUTE …","url":["https://web.wpi.edu/Pubs/ETD/Available/etd-042618-010745/unrestricted/szhao.pdf"]}
-{"year":"2018","title":"Towards Two-Dimensional Sequence to Sequence Model in Neural Machine Translation","authors":["P Bahar, C Brix, H Ney - arXiv preprint arXiv:1810.03975, 2018"],"snippet":"… 5 Experiments We have done the experiments on the WMT 2017 German→English and English→German news tasks consisting of 4.6M training samples collected from the well-known data sets Europarl-v7, News-Commentary-v10 and Common-Crawl …","url":["https://arxiv.org/pdf/1810.03975"]}
-{"year":"2018","title":"Training a Neural Network in a Low-Resource Setting on Automatically Annotated Noisy Data","authors":["MA Hedderich, D Klakow - arXiv preprint arXiv:1807.00745, 2018"],"snippet":"… Page 4. tries other than Britain until the scientific” where ”Britain” is the target word with label y = LOC. Sentence boundaries are padded. We encode the words using the 300-dimensional GloVe vectors trained on cased text …","url":["https://arxiv.org/pdf/1807.00745"]}
-{"year":"2018","title":"Training Tips for the Transformer Model","authors":["M Popel, O Bojar - arXiv preprint arXiv:1804.00247, 2018"],"snippet":"… commoncrawl 161 k 3.3 M 2.9 M … Most of our training data comes from the CzEng parallel treebank, version 1.7 (57M sentence pairs), and the rest (1M sentence pairs) comes from three smaller sources (Europarl, News …","url":["https://arxiv.org/pdf/1804.00247"]}
-{"year":"2018","title":"Transfer Learning from LDA to BiLSTM-CNN for Offensive Language Detection in Twitter","authors":["G Wiedemann, E Ruppert, R Jindal, C Biemann - Austrian Academy of Sciences …, 2018"],"snippet":"… classification labels per task. have not been seen during training the embedding model. We use a model pre-trained with German language data from Wikipedia and Common Crawl provided by Mikolov et al.(2018). First, we unify all …","url":["https://www.oeaw.ac.at/fileadmin/subsites/academiaecorpora/PDF/GermEval2018_Proceedings.pdf#page=91"]}
-{"year":"2018","title":"Transferred Embeddings for Igbo Similarity, Analogy and Diacritic Restoration Tasks","authors":["IEMHI Onyenwe, C Enemuo - COLING 2018, 2018"],"snippet":"… org news dataset. • igWkSbwd from same as igWkNews but with subword information. • igWkCrl from fastText Common Crawl dataset Table 1 shows the vocabulary lengths (vocabs), and the dimensions (vectors) of each of the models used in our experiments …","url":["http://www.aclweb.org/anthology/W18-40#page=40"]}
-{"year":"2018","title":"Transferred Embeddings for Igbo Similarity, Analogy, and Diacritic Restoration Tasks","authors":["I Ezeani, I Onyenwe, M Hepple - Proceedings of the Third Workshop on Semantic …, 2018"],"snippet":"… igWkSbwd from same as igWkNews but with subword information. • igWkCrl from fastText Common Crawl dataset Table 1 shows the vocabulary lengths (vocabs), and the dimensions (vectors) of each of the models used in our experiments. 3 Model Evaluation …","url":["http://www.aclweb.org/anthology/W18-4004"]}
-{"year":"2018","title":"Translation of Biomedical Documents with Focus on Spanish-English","authors":["MS Duma, W Menzel - Proceedings of the Third Conference on Machine …, 2018"],"snippet":"… 2http://commoncrawl.org/ 3https://paracrawl.eu/index.html … Track / Corpora EN-ES EN-PT EN-RO Commoncrawl 1.8M - - Paracrawl - 2.1M 2.4M Wikipedia 1.6M 1.6M - EMEA 678K 1.08M 994K Scielo-gma 2016 166K 613K - Table 1: Corpora used for DSTF 3.2 Tools …","url":["http://www.aclweb.org/anthology/W18-6444"]}
-{"year":"2018","title":"Two-Step Multi-factor Attention Neural Network for Answer Selection","authors":["P Zhang, Y Hou, Z Su, Y Su - Pacific Rim International Conference on Artificial …, 2018"],"snippet":"… 3.3 Experimental Settings. We initialize word embeddings with 300-dimensional GloVe word vectors pre-trained from the 840B Common Crawl corpus [20]. For out of vocabulary (OOV) words, their embeddings are initialized randomly …","url":["https://link.springer.com/chapter/10.1007/978-3-319-97304-3_50"]}
-{"year":"2018","title":"UBC-NLP at IEST 2018: Learning Implicit Emotion With an Ensemble of Language Models","authors":["H Alhuzali, M Elaraby, M Abdul-Mageed"],"snippet":"… morphology like English. Additionally, fastText partially solves issues with out-of-vocabulary words since it exploits character sequences. FastText is trained on the Common Crawl dataset, consisting of 600B tokens. For this and the …","url":["https://mageed.sites.olt.ubc.ca/files/2018/09/emnlp18_IEST_WASSA_2018.pdf"]}
-{"year":"2018","title":"Uncovering divergent linguistic information in word embeddings with lessons for intrinsic and extrinsic evaluation","authors":["M Artetxe, G Labaka, I Lopez-Gazpio, E Agirre - arXiv preprint arXiv:1809.02094, 2018"],"snippet":"… analogies. We use the largest pre-trained model published by the authors9, which was trained on 840 billion words of the Common Crawl corpus and contains 300dimensional vectors for 2.2 million words. Fasttext (Bojanowski …","url":["https://arxiv.org/pdf/1809.02094"]}
-{"year":"2018","title":"Understanding Back-Translation at Scale","authors":["S Edunov, M Ott, M Auli, D Grangier - arXiv preprint arXiv:1808.09381, 2018"],"snippet":"… It also allows us to estimate the value of BT data for domain adaptation since the newscrawl corpus (BT-news) is pure news whereas the bitext is a mixture of eu- roparl and commoncrawl with only a small newscommentary portion …","url":["https://arxiv.org/pdf/1808.09381"]}
-{"year":"2018","title":"Understanding Search Queries in Natural Language","authors":["Z Neverilová, M Kvaššay - RASLAN 2018 Recent Advances in Slavonic Natural …, 2018"],"snippet":"… stop-words are removed. Tokens are mapped to 300-dimensional word embeddings using publicly available vocabulary of FastText [2] vectors trained on CommonCrawl dataset. Missing words are ignored. Vectors are then …","url":["http://nlp.fi.muni.cz/raslan/raslan18.pdf#page=93"]}
-{"year":"2018","title":"Unsupervised Disambiguation of Abstract Syntax","authors":["O KALLDAL, M LUDVIGSSON"],"snippet":"Page 1. NoPConj : PConj AAnter : Ant TTAnt : Temp whoever_NP : NP NoVoc : Voc PPos : Pol is_right_VP : VP PhrUtt : Phr TPast : Tense PredVP : Cl UseCl : S UttS : Utt Unsupervised Disambiguation of Abstract Syntax A Language …","url":["http://publications.lib.chalmers.se/records/fulltext/255307/255307.pdf"]}
-{"year":"2018","title":"Unsupervised Domain Adaptation by Adversarial Learning for Robust Speech Recognition","authors":["P Denisov, NT Vu, MF Font - arXiv preprint arXiv:1807.11284, 2018"],"snippet":"… Summary of the used corpora is given in Tab. 1. In addition to that, 197 millions words of Italian Deduplicated CommonCrawl Text are used to build Italian language model. Italian dictionary ILE with pronunciations for 588k words is used as a lexicon. 3.2 Baseline …","url":["https://arxiv.org/pdf/1807.11284"]}
-{"year":"2018","title":"Unsupervised Mining of Analogical Frames by Constraint Satisfaction","authors":["L De Vine, S Geva, P Bruza - Australasian Language Technology Association …"],"snippet":"… 2 a3, 3 Figure 4: Determining an analogy completion from a larger frame We conducted experiments with embeddings constructed by ourselves as well as with publicly accessible embeddings from the fastText web site2 trained …","url":["http://alta2018.alta.asn.au/alta2018-draft-proceedings.pdf#page=44"]}
-{"year":"2018","title":"Unsupervised Neural Machine Translation Initialized by Unsupervised Statistical Machine Translation","authors":["B Marie, A Fujita - arXiv preprint arXiv:1810.12703, 2018"],"snippet":"… These methods usually exploit existing accurate translation models and have shown to be useful especially when targeting 1See for instance the Common Crawl project: http:// commoncrawl.org/ low-resource language pairs and domains …","url":["https://arxiv.org/pdf/1810.12703"]}
-{"year":"2018","title":"Unsupervised Post-processing of Word Vectors via Conceptor Negation","authors":["T Liu, L Ungar, J Sedoc - arXiv preprint arXiv:1811.11001, 2018"],"snippet":"… We use the publicly available pre-trained Google News Word2Vec (Mikolov et al. 2013)5 and Common Crawl GloVe6 (Pennington, Socher, and Manning 2014) to perform lexical-level experiments. For CN, we fix α = 2 for …","url":["https://arxiv.org/pdf/1811.11001"]}
-{"year":"2018","title":"Unsupervised semantic frame induction using triclustering","authors":["D Ustalov, A Panchenko, A Kutuzov, C Biemann… - arXiv preprint arXiv …, 2018"],"snippet":"… In our evaluation, we use triple frequencies from the DepCC dataset (Panchenko et al., 2018) , which is a dependency-parsed version of the Common Crawl corpus, and the standard 300-dimensional word embeddings …","url":["https://arxiv.org/pdf/1805.04715"]}
-{"year":"2018","title":"Unsupervised Sense-Aware Hypernymy Extraction","authors":["D Ustalov, A Panchenko, C Biemann, SP Ponzetto - arXiv preprint arXiv:1809.06223, 2018"],"snippet":"… Recent approaches to hypernym extraction went into three directions: (1) unsupervised methods based on such huge corpora as CommonCrawl1 to ensure extraction coverage using Hearst (1992) patterns (Seitner et al …","url":["https://arxiv.org/pdf/1809.06223"]}
-{"year":"2018","title":"User-Centric Ontology Population","authors":["K Clarkson, AL Gentile, D Gruhl, P Ristoski, J Terdiman…"],"snippet":"… Ristoski et al. [29] use standard word embeddings and graph embeddings to align instances extracted from the Common Crawl4 to the DBpedia ontology. The use of deep learning models has also been explored for this task. Dong et al …","url":["https://2018.eswc-conferences.org/wp-content/uploads/2018/02/ESWC2018_paper_10.pdf"]}
-{"year":"2018","title":"Using a Stacked Residual LSTM Model for Sentiment Intensity Prediction","authors":["J Wang, B Peng, X Zhang - Neurocomputing, 2018"],"snippet":"… To enhance performance of LSTM layers, we also introduce a bi-directional strategy [34]. The word embeddings used in this experiment was respectively pre-trained on Common Crawl 840B 2 (English) and wiki dumps 3 (Chinese) by GloVe [55] …","url":["https://www.sciencedirect.com/science/article/pii/S0925231218311226"]}
-{"year":"2018","title":"Using context to identify the language of face-saving","authors":["N Naderi, G Hirst"],"snippet":"… For all our Neural Network models, we initialized our word representations using the publicly available GloVe pre-trained word embeddings (Pennington et al., 2014)8 (300-dimensional vectors trained on Common Crawl data) …","url":["ftp://ftp.db.toronto.edu/public_html/cs/ftp/public_html/pub/gh/Naderi+Hirst-ArgMining-2018.pdf"]}
-{"year":"2018","title":"Using Deep Learning For Title-Based Semantic Subject Indexing To Reach Competitive Performance to Full-Text","authors":["F Mai, L Galke, A Scherp - arXiv preprint arXiv:1801.06717, 2018"],"snippet":"… We adopt the preprocessing and tokenization scheme of Galke et. al [5]. For the LSTM and CNN, we use 300-dimensional pretrained word embeddings obtained from training GloVe [28] on Common Crawl with 840 billion tokens7. Out-of-vocabulary words are discarded …","url":["https://arxiv.org/pdf/1801.06717"]}
-{"year":"2018","title":"Using Machine Learning to Detect Malicious Websites","authors":["R Elsaleh - 2018"],"snippet":"… Benign Data Benign data was obtained from the Common Crawl6. The Common Crawl is a massive, continuously updated collection of crawled websites available for download … PhishTank 36,485 65,000 VirusTotal 5,036 0 6 http://commoncrawl.org/ Page 21. 12 …","url":["http://search.proquest.com/openview/da712bc2891c9bddbdc64e287a72dcc1/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2018","title":"Using Monolingual Data in Neural Machine Translation: a Systematic Study","authors":["F Burlot, F Yvon - Proceedings of the Third Conference on Machine …, 2018"],"snippet":"… For German, we use samples from News-Commentary-11, Rapid, Common-Crawl (WMT 2017) and Multi- UN (see table 1). Bilingual BPE units (Sennrich et al., 2016b) are learned with 50k merge operations, yielding …","url":["http://www.aclweb.org/anthology/W18-6315"]}
-{"year":"2018","title":"Using Wikipedia Edits in Low Resource Grammatical Error Correction","authors":["A Boyd"],"snippet":"… 2.4 Language Model For reranking, we train a language model on the first one billion lines (~12 billion tokens) of the deduplicated German Common Crawl corpus (Buck et al., 2014). 3 Method … 2014. N-gram counts and language models from the Common Crawl …","url":["http://noisy-text.github.io/2018/pdf/W-NUT201811.pdf"]}
-{"year":"2018","title":"Using Word Embeddings for Information Retrieval: How Collection and Term Normalization Choices Affect Performance","authors":["D Roy, D Ganguly, S Bhatia, S Bedathur, M Mitra - 2018"],"snippet":"… In future, we plan to solidify these observations to offer general best practices for a range of different neural IR methods (eg DRRM[7]) as well as experiment using large datasets (eg Common Crawl). REFERENCES [1] Qingyao Ai …","url":["http://sumitbhatia.net/papers/cikm18.pdf"]}
-{"year":"2018","title":"Utilizing Neural Networks and Linguistic Metadata for Early Detection of Depression Indications in Text Sequences","authors":["M Trotzek, S Koitka, CM Friedrich - arXiv preprint arXiv:1804.07000, 2018"],"snippet":"Page 1. SUBMITTED FOR PUBLICATION TO THE IEEE, 2018 1 Utilizing Neural Networks and Linguistic Metadata for Early Detection of Depression Indications in Text Sequences Marcel Trotzek, Sven Koitka, and Christoph M. Friedrich, Member, IEEE …","url":["https://arxiv.org/pdf/1804.07000"]}
-{"year":"2018","title":"UWB at SemEval-2018 Task 10: Capturing Discriminative Attributes from Word Distributions","authors":["T Brychcín, T Hercig, J Steinberger, M Konkol - … of The 12th International Workshop on …, 2018"],"snippet":"… SS-GloVe 6B, Wikipedia + Gigaword 5 n = 300 62.0% 62.5% SS-GloVe 42B, Common Crawl n = 300 62.6% 62.7% SS-GloVe 840B, Common Crawl n = 300 62.1% 62.6 … SS-LDA 1-5B, Wikipedia n = 200 60.5% 63.1 …","url":["http://www.aclweb.org/anthology/S18-1153"]}
-{"year":"2018","title":"Vecsigrafo: Corpus-based Word-Concept Embeddings","authors":["R Denaux, JM Gomez-Perez"],"snippet":"… To compare our embeddings to those trained on a very large corpus, we use pre-calculated GloVe embeddings that were trained on CommonCrawl7. Besides the text corpora, the tested embeddings con …","url":["http://semantic-web-journal.net/system/files/swj1864.pdf"]}
-{"year":"2018","title":"Visual and affective grounding in language and mind","authors":["S De Deyne, DJ Navarro, G Collell, A Perfors"],"snippet":"… We also included an extremely large corpus consisting of 840 billion words from the Common Crawl project.5 As before, the language vectors were combined in a multimodal visual or affective model and the correlations were optimized by fitting values of β …","url":["https://compcogscisydney.org/publications/DeDeyneNCP_grounding.pdf"]}
-{"year":"2018","title":"Visual Concept Selection with Textual Knowledge for Understanding Activities of Daily Living and Life Moment Retrieval","authors":["TH Tang12, MH Fu, HH Huang, KT Chen, HH Chen13"],"snippet":"… Page 8. GloVe [9] trained on Common Crawl with 840B tokens and ConceptNet Numberbatch [8]. The comparison in percentage dissimilarity [1] is shown in Table 1, where (G) and (N) denote GloVe and ConceptNet Numberbatch word vectors, respectively …","url":["http://ceur-ws.org/Vol-2125/paper_124.pdf"]}
-{"year":"2018","title":"Visual Question Answering using Explicit Visual Attention","authors":["V Lioutas, N Passalis, A Tefas - Circuits and Systems (ISCAS), 2018 IEEE …, 2018"],"snippet":"… For extracting textual representations we used pre-trained GloVe embedding vectors (Common Crawl (42B tokens), 300d) [1]. Note that the GloVe embeddings were used only for initialization and then they were optimized during the training …","url":["https://ieeexplore.ieee.org/abstract/document/8351158/"]}
-{"year":"2018","title":"Visual Relationship Detection Based on Guided Proposals and Semantic Knowledge Distillation","authors":["F Plesse, A Ginsca, B Delezoide, F Prêteux - arXiv preprint arXiv:1805.10802, 2018"],"snippet":"… iterations. The word embeddings used by the semantic knowledge introduced in Section 2.1 were obtained from the publicly available Glove model [19] trained on the Common Crawl corpus, consisting of 42B tokens. 4.2. Results …","url":["https://arxiv.org/pdf/1805.10802"]}
-{"year":"2018","title":"Von Mises-Fisher Loss for Training Sequence to Sequence Models with Continuous Outputs","authors":["S Kumar, Y Tsvetkov - arXiv preprint arXiv:1812.04616, 2018"],"snippet":"… target word embeddings for English and French on corpora constructed using WMT'16 (Bojar et al., 2016) monolingual datasets containing data from Europarl, News Commentary, News Crawl from 2007 to 2015 and News …","url":["https://arxiv.org/pdf/1812.04616"]}
-{"year":"2018","title":"WBI at CLEF eHealth 2018 Task 1: Language-independent ICD-10 coding using multi-lingual embeddings and recurrent neural networks","authors":["J Ševa, M Sänger, U Leser - 2018"],"snippet":"… Each token is represented using pre-trained fastText5 word embeddings [4]. We utilize fastText embedding models for French, Italian and Hungarian trained on Common Crawl and Wikipedia articles6. Independently from …","url":["http://ceur-ws.org/Vol-2125/paper_118.pdf"]}
-{"year":"2018","title":"Weaver: Deep Co-Encoding of Questions and Documents for Machine Reading","authors":["M Raison, PE Mazaré, R Das, A Bordes - arXiv preprint arXiv:1804.10490, 2018"],"snippet":"… Unless otherwise noted, we use 300dimensional FastText word embeddings trained on Common Crawl (Mikolov et al., 2017) and keep them fixed during training. Out-of-vocabulary words are represented with a fixed randomly initialized vector …","url":["https://arxiv.org/pdf/1804.10490"]}
-{"year":"2018","title":"Web archives and Knowledge organisation","authors":["NO Finnemann, D Phil"],"snippet":"… Internet Archive, established in 1996, and Common Crawl (commoncrawl.org) established in 2007.12 Since 2006 the Internet Archive also provide a subscriptionbased archive service, Archive-it (archive-it.org) allowing anybody …","url":["https://curis.ku.dk/ws/files/189392223/Web_Archives_Manuscript.pdf"]}
-{"year":"2018","title":"What can we learn from Semantic Tagging?","authors":["M Abdou, A Kulmizev, V Ravishankar, L Abzianidze… - arXiv preprint arXiv …, 2018"],"snippet":"… sets of experiments: we optimized using Adam with a learning rate of 0.00005; we weight the auxiliary semantic tagging loss with λ = 0.1; the pre-trained word embeddings we use are GloVe embeddings of dimension 300 trained …","url":["https://arxiv.org/pdf/1808.09716"]}
-{"year":"2018","title":"What's Cached is Prologue: Reviewing Recent Web Archives Research Towards Supporting Scholarly Use","authors":["E Maemura"],"snippet":"… Internet Archive. Samar et al. (2016) analyze coverage of trending topics for the Netherlands in 2014 by comparing the National Library of the Netherlands' web archive to the Common Crawl dataset. Milligan et al. (2016) use …","url":["https://tspace.library.utoronto.ca/bitstream/1807/89426/1/Maemura%20AM2018%20Paper-Postprint.pdf"]}
-{"year":"2018","title":"When data permutations are pathological: the case of neural natural language inference","authors":["N Schluter, D Varab - Proceedings of the 2018 Conference on Empirical …, 2018"],"snippet":"… via an LSTM. Other hyperparameters. We use 300 dimensional GloVe embeddings trained on the Common Crawl 840B tokens dataset (Pennington et al., 2014), which remain fixed during training. Out of vocabulary (OOV …","url":["http://www.aclweb.org/anthology/D18-1534"]}
-{"year":"2018","title":"Who gets held accountable when a facial recognition algorithm fails?","authors":["E Broad - IQ: The RIM Quarterly, 2018"],"snippet":"… In that experiment, the machine learning tool was trained on what's called a “common crawl” corpus: a list of 840 billion words in material published on the Web. Training AI on historical data can freeze our society in its current setting, or even turn it back …","url":["https://search.informit.com.au/documentSummary;dn=965944620566147;res=IELBus"]}
-{"year":"2018","title":"WikiAtomicEdits: A Multilingual Corpus of Wikipedia Edits for Modeling Language and Discourse Supplementary Material","authors":["M Faruqui, E Pavlick, I Tenney, D Das"],"snippet":"… 3.3 Experimental Setting We use FastText (Mikolov et al., 2018; Grave et al., 2018)3 word vectors of length 300, originally trained on more than 600 billion word to- kens each from Common Crawl corpus for each language …","url":["http://anthology.aclweb.org/attachments/D/D18/D18-1028.Attachment.pdf"]}
-{"year":"2018","title":"Wikipedia Text Reuse: Within and Without","authors":["M Alshomary, M Völske, T Licht, H Wachsmuth, B Stein… - arXiv preprint arXiv …, 2018"],"snippet":"… Abstract. We study text reuse related to Wikipedia at scale by compiling the first corpus of text reuse cases within Wikipedia as well as without (ie, reuse of Wikipedia text in a sample of the Common Crawl) … 3 …","url":["https://arxiv.org/pdf/1812.09221"]}
-{"year":"2018","title":"WikiRef: Wikilinks as a route to recommending appropriate references for scientific Wikipedia pages","authors":["A Jana, P Kanojiya, A Mukherjee, P Goyal - arXiv preprint arXiv:1806.04092, 2018"],"snippet":"… proposed by Conneau et al. (2017). Note that, for applying this architecture we use the GloVe vectors trained on Common Crawl data (840B tokens)7as seeds for representing words in a document. We name these variants of …","url":["https://arxiv.org/pdf/1806.04092"]}
-{"year":"2018","title":"Will it Blend? Blending Weak and Strong Labeled Data in a Neural Network for Argumentation Mining","authors":["E Shnarch, C Alzate, L Dankin, M Gleize, Y Hou… - Proceedings of the 56th …, 2018"],"snippet":"… maximum global norm of 1.0. Words are represented using the 300 dimensional GloVe embeddings learned on 840B Common Crawl tokens and are left untouched during training (Pennington et al., 2014). We note that even …","url":["http://www.aclweb.org/anthology/P18-2095"]}
-{"year":"2018","title":"Word embedding for French natural language in healthcare: a comparative study","authors":["E DYNOMANT, R LELONG, B DAHAMNA…"],"snippet":"… [30] compared the three word embedding methods but the three models were trained on different datasets (Word2Vec on news data, while FastText and GloVe trained on more definitional data, Wikipedia and Common Crawl respectively) …","url":["https://preprints.jmir.org/preprint/download/12310/pdf"]}
-{"year":"2018","title":"Word embeddings for monolingual and cross-lingual domain-specific information retrieval","authors":["C Wigder - 2018"],"snippet":"Page 1. Word embeddings for monolingual and cross-lingual domain-specific information retrieval CHAYA WIGDER Master in Computer Science Date: June 4, 2018 Supervisor: Johan Boye Examiner: Viggo Kann Swedish title …","url":["http://www.nada.kth.se/~ann/exjobb/chaya_wigder.pdf"]}
-{"year":"2018","title":"Word Emotion Induction for Multiple Languages as a Deep Multi-Task Learning Problem","authors":["S Buechel, U Hahn"],"snippet":"… experiments, we rely on the following widely used, publicly available embedding models trained on very large corpora (summarized in Table 3): the SGNS model trained on the Google News corpus2 (GOOGLE), the …","url":["https://www.researchgate.net/profile/Sven_Buechel/publication/325019685_Word_Emotion_Induction_for_Multiple_Languages_as_a_Deep_Multi-Task_Learning_Problem/links/5af1b275aca272bf425628a9/Word-Emotion-Induction-for-Multiple-Languages-as-a-Deep-Multi-Task-Learning-Problem.pdf"]}
-{"year":"2018","title":"Word2Bits-Quantized Word Vectors","authors":["M Lam - arXiv preprint arXiv:1803.05651, 2018"],"snippet":"… complete picture of the relative performance of the two. We would also like to train quantized word vectors on much larger corpuses of data such as Common Crawl or Google News. Another task is to validate that overfitting occurs …","url":["https://arxiv.org/pdf/1803.05651"]}
-{"year":"2018","title":"XNLI: Evaluating Cross-lingual Sentence Representations","authors":["A Conneau, G Lample, R Rinott, A Williams… - arXiv preprint arXiv …, 2018"],"snippet":"… on the word translation task. In this paper, we pretrain our embeddings using the common-crawl word embeddings (Grave et al., 2018) aligned with the MUSE library of Conneau et al. (2018b). 4.2.2 Universal Multilingual Sentence …","url":["https://arxiv.org/pdf/1809.05053"]}
-{"year":"2018","title":"YouTube AV 50K: an Annotated Corpus for Comments in Autonomous Vehicles","authors":["T Li, L Lin, M Choi, K Fu, S Gong, J Wang - arXiv preprint arXiv:1807.11227, 2018"],"snippet":"Page 1. YouTube AV 50K: an Annotated Corpus for Comments in Autonomous Vehicles Tao Li Department of Computer Science Purdue University West Lafayette, IN 47907 Email: taoli@purdue.edu Kaiming Fu Weldon School …","url":["https://arxiv.org/pdf/1807.11227"]}
-{"year":"2018","title":"Zero-Shot Object Detection by Hybrid Region Embedding","authors":["B Demirel, RG Cinbis, N Ikizler-Cinbis - arXiv preprint arXiv:1805.06157, 2018"],"snippet":"… 4.2 Class Embeddings For the Fashion-ZSD dataset, we generate 300-dimensional GloVe word embedding vectors [31] for each class name, using Common Crawl Data1. For the class names that contain multiple words, we take the average of the word vectors …","url":["https://arxiv.org/pdf/1805.06157"]}
-{"year":"2018","title":"Zewen at SemEval-2018 Task 1: An Ensemble Model for Affect Prediction in Tweets","authors":["Z Chi, H Huang, J Chen, H Wu, R Wei - … of The 12th International Workshop on …, 2018"],"snippet":"… GloVe (Pennington et al., 2014) trained by Common Crawl … the same model hyperparameters which are listed in Table 1 and Table 2. Also, the four methods use the same word em- beddings, which is a pre-trained …","url":["http://www.aclweb.org/anthology/S18-1046"]}
-{"year":"2019","title":"% 0 Conference Proceedings% TA Large DataBase of Hypernymy Relations Extracted from the Web.% A Seitner, Julian% A Bizer, Christian% A Eckert, Kai","authors":["A Ponzetto, S Paolo"],"snippet":"… for many word understanding applications. We present a publicly available database containing more than 400 million hypernymy relations we extracted from the CommonCrawl web corpus. We describe the infrastructure we …","url":["https://www.aclweb.org/anthology/papers/L/L16/L16-1056.endf"]}
-{"year":"2019","title":"A 6-month Analysis of Factors Impacting Web Browsing Quality for QoE Prediction","authors":["A Saverimoutou, B Mathieu, S Vaton - Computer Networks, 2019"],"snippet":"… Fourth Party [15] instruments the Mozilla-Firefox browser and Web Xray [16] is a PhantomJS based tool for measuring HTTP traffic. XRay [17] and AdFisher [18] run automated personalization detection experiments and …","url":["https://www.sciencedirect.com/science/article/pii/S1389128619307546"]}
-{"year":"2019","title":"A Bilingual Adversarial Autoencoder for Unsupervised Bilingual Lexicon Induction","authors":["X Bai, H Cao, K Chen, T Zhao - IEEE/ACM Transactions on Audio, Speech, and …, 2019"],"snippet":"… [29]. This dataset consists of gold dictionaries and 300-dimensional CBOW5 embeddings trained on WacKy crawling corpora (English, Italian, German), Common Crawl (Finish) and WMT News Crawl (Spanish). We report the results 2We set k = 10 …","url":["https://ieeexplore.ieee.org/abstract/document/8754809/"]}
-{"year":"2019","title":"A Combined Approach to Automatic Taxonomy Extraction","authors":["S Pecar, M Simko"],"snippet":"… [10] presented publicly available database of hypernym relations called WebIsA. This database was created using Hearst-like patterns on CommonCrawl web corpus. They extracted more than 400 million hypernymy relations …","url":["https://ieeexplore.ieee.org/iel7/8859030/8864801/08864911.pdf"]}
-{"year":"2019","title":"A Common Semantic Space for Monolingual and Cross-Lingual Meta-Embeddings","authors":["I García Ferrero - 2019","I García, R Agerri, G Rigau - arXiv preprint arXiv:2001.06381, 2020"],"snippet":"… From GloVe (GV) [34], the Common Crawl vectors (600 billion words) … The WS353 dataset is di- vided in two subsets [1]. In this section all the meta-embeddings have been mapped to the vector space of the English FastText (Common Crawl, 600B tokens) …","url":["https://addi.ehu.eus/bitstream/handle/10810/36183/MAL-Iker_Garcia.pdf?sequence=1&isAllowed=y","https://arxiv.org/pdf/2001.06381"]}
-{"year":"2019","title":"A COMPARATIVE STUDY ON END-TO-END SPEECH TO TEXT TRANSLATION","authors":["P Bahar, T Bieschke, H Ney"],"snippet":"… We select our checkpoints based on the dev set. For the MT training, we use the TED, OpenSubtitles2018, Europarl, ParaCrawl, CommonCrawl, News Commentary, and Rapid corpora resulting in 32M sentence pairs after filtering noisy samples …","url":["https://www-i6.informatik.rwth-aachen.de/publications/download/1121/BaharParniaBieschkeTobiasNeyHermann--Acomparativestudyonend-to-endspeechtotexttranslation--2019.pdf"]}
-{"year":"2019","title":"A Comparison of Context-sensitive Models for Lexical Substitution","authors":["AG Soler, A Cocos, M Apidianaki, C Callison-Burch"],"snippet":"… to two context-insensitive baselines that solely rely on the target-to-substitute similarity of standard, pre-trained word embeddings: 300-dimensional GloVe vectors (Pennington et al., 2014)5 and 300-dimensional FastText vectors …","url":["http://www.cis.upenn.edu/~ccb/publications/comparison-of-context-sensitive-models-for-lexical-substitution.pdf"]}
-{"year":"2019","title":"A Comparison of Neural Document Classification Models","authors":["M Nitsche, S Halbritter"],"snippet":"… Bojanowski et al. (2016). It is available for 294 languages. An updated version, trained on Common Crawl in addition to Wikipedia and with adapted parameters is available for 157 languages (Grave et al., 2018). These are the …","url":["https://users.informatik.haw-hamburg.de/~ubicomp/projekte/master2019-proj/nitsche-halbritter2.pdf"]}
-{"year":"2019","title":"A Comparison on Fine-grained Pre-trained Embeddings for the WMT19Chinese-English News Translation Task","authors":["Z Li, L Specia - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… In addition, the Common Crawl Corpus from WMT is used as monolingual data to pre-train the embeddings … We trained the embeddings on the Common Crawl Corpus provided by WMT19 and fine-tuned them on the task data when training the RNN …","url":["https://www.aclweb.org/anthology/W19-5324"]}
-{"year":"2019","title":"A Contextualized Word Representation Approach for Irony Detection","authors":["L Garcıa, D Moctezuma, V Muniz - Proceedings of the Iberian Languages Evaluation …, 2019"],"snippet":"… 2.2 Word Embeddings We use the ELMo pre-trained word embeddings provided by [4], which were trained with a corpus of 20 million-words randomly sampled from the raw text released by the CoNLL 2018 shared …","url":["http://ceur-ws.org/Vol-2421/IroSvA_paper_5.pdf"]}
-{"year":"2019","title":"A Dataset for Content Error Detection in Web Archives","authors":["J Kiesel, F Hubricht, B Stein, M Potthast"],"snippet":"… The Webis Web Archive 2017 [9] contains 10,000 web pages sampled from the Common Crawl [11] in a way which ensured that both well-known and less … January 2017 Common Crawl Archive, 2017. http: //commoncrawl.org …","url":["https://webis.de/downloads/publications/papers/stein_2019e.pdf"]}
-{"year":"2019","title":"A Deep Dive into Supervised Extractive and Abstractive Summarization from Text","authors":["M Dey, D Das - Data Visualization and Knowledge Engineering, 2020"],"snippet":"… 7.1. As mentioned in the algorithm, estimated frequency p(w) of every words have been found from datasets (enwiki, poliblogs, commoncrawl, text8) [1]. The parameter “a” for our task is fixed at \\(3 * 10^{-3}\\). The vector of all …","url":["https://link.springer.com/chapter/10.1007/978-3-030-25797-2_5"]}
-{"year":"2019","title":"A Deep Learning Approach for Identification of Confusion in Unstructured Crowdsourced Annotations","authors":["R Gardner, M Varma, C Zhu"],"snippet":"… improvements in model performance. We also compared the VQR binary classification model based on GLoVe embeddings with a model based on FastText embeddings trained on Common Crawl (3; 14). Since the FastText …","url":["https://pdfs.semanticscholar.org/ad70/7fc8b36a8f3daf8742cf92fcf099de434cec.pdf"]}
-{"year":"2019","title":"A Dynamic Evolutionary Framework for Timeline Generation based on Distributed Representations","authors":["D Liang, G Wang, J Nie - arXiv preprint arXiv:1905.05550, 2019"],"snippet":"… To learn the distributed representations, we use pre-trained word vectors2, trained on Common Crawl and Wikipedia by fastText tookit [2]. Furthermore, each v(q) is only embedded by the name of the topic q as a experimental control …","url":["https://arxiv.org/pdf/1905.05550"]}
-{"year":"2019","title":"A Framework to Estimate the Nutritional Value of Food in Real Time Using Deep Learning Techniques","authors":["R Yunus, O Arif, H Afzal, MF Amjad, H Abbas… - IEEE Access, 2019"],"snippet":"… First is Common-Crawl, which is an archive hosted on an Amazon S3 bucket … is more relevant as it return pages corresponding to precise labels while the text from Common-Crawl is more generic. The raw text data obtained …","url":["https://ieeexplore.ieee.org/iel7/6287639/8600701/08590712.pdf"]}
-{"year":"2019","title":"A Language Invariant Neural Method for TimeML Event Detection","authors":["S Prabhu, P Goel, A Debnath, M Shrivastava"],"snippet":"… The CNN uses 40 filters with a window size of 3. For our contextual word embeddings, we use fastText embeddings for English (Bojanowski et al., 2017) which are pretrained on commonCrawl and the Wikipedia corpus. FastText …","url":["https://www.researchgate.net/profile/Pranav_Goel/publication/337387464_A_Language_Invariant_Neural_Method_for_TimeML_Event_Detection/links/5dd4c5ec299bf11ec8629470/A-Language-Invariant-Neural-Method-for-TimeML-Event-Detection.pdf"]}
-{"year":"2019","title":"A Massive Collection of Cross-Lingual Web-Document Pairs","authors":["A El-Kishky, V Chaudhary, F Guzman, P Koehn - arXiv preprint arXiv:1911.06154, 2019"],"snippet":"… Other works (Smith et al., 2013) have mined Common Crawl for bitexts for machine … and restrictions, we mined 54 million aligned documents across 12 Common Crawl snapshots … 2: NMT performance on comparable directions …","url":["https://arxiv.org/pdf/1911.06154"]}
-{"year":"2019","title":"A Multi-Task Approach for Disentangling Syntax and Semantics in Sentence Representations","authors":["S Wiseman, K Gimpel, Q Tang, M Chen"],"snippet":"04/02/19 - We propose a generative model for a sentence that uses two latent variables, with one intended to represent the syntax of the sent...","url":["https://deepai.org/publication/a-multi-task-approach-for-disentangling-syntax-and-semantics-in-sentence-representations"]}
-{"year":"2019","title":"A New Corpus for Low-Resourced Sindhi Language with Word Embeddings","authors":["W Ali, J Kumar, J Lu, Z Xu - arXiv preprint arXiv:1911.12579, 2019"],"snippet":"… 3Available online at https://rdrr.io/cran/wordspace/man/WordSim353.html 4We denote Sindhi word representations as (SdfastText) recently revealed by fastText, available at (https://fasttext.cc/docs/en/crawl-vectors.html) trained …","url":["https://arxiv.org/pdf/1911.12579"]}
-{"year":"2019","title":"A New Hybrid Ensemble Feature Selection Framework for Machine Learning-based Phishing Detection System","authors":["KL Chiew, CL Tan, KS Wong, KSC Yong, WK Tiong - Information Sciences, 2019"],"snippet":"… June 2017. Specifically, we selected 5000 phishing webpages based on URLs from PhishTank 2 and OpenPhish 3 , and another 5000 legitimate webpages based on URLs from Alexa 4 and the Common Crawl 5 archive. The …","url":["https://www.sciencedirect.com/science/article/pii/S0020025519300763"]}
-{"year":"2019","title":"A Question-Entailment Approach to Question Answering","authors":["AB Abacha, D Demner-Fushman - arXiv preprint arXiv:1901.08079, 2019"],"snippet":"… We use the pretrained common crawl version with 840B tokens and 300d vectors, which are not updated during training. 3.3 Logistic Regression Classifier In this feature-based approach, we use Logistic Regression to …","url":["https://arxiv.org/pdf/1901.08079"]}
-{"year":"2019","title":"A Recurrent Deep Neural Network Model to measure Sentence Complexity for the Italian","authors":["D Schicchi"],"snippet":"… The authors have used FastText [3], a library for efficient learning of word representations and sentence classification, trained on Common Crawl [21] and Wikipedia to create a pre-trained word vector representation for …","url":["http://ceur-ws.org/Vol-2418/paper10.pdf"]}
-{"year":"2019","title":"A Robust Abstractive System for Cross-Lingual Summarization","authors":["J Ouyang, B Song, K McKeown"],"snippet":"… about 23k sentences for Somali and Swahili and 51k for Tagalog); noisy, web-crawled parallel data (So- mali only, about 354k sentences); and synthetic, backtranslated parallel data created from monolingual sources including …","url":["http://www.cs.columbia.edu/~ouyangj/OuyangSongMcKeown2019.pdf"]}
-{"year":"2019","title":"A Study of Neural Networks Models applied to Natural Language Inference","authors":["VG Noronha, JCP da Silva"],"snippet":"… word vectors of different size, in order to check whether the word space dimension plays an important role on the final results: – A 100d version trained on the Wikipedia 2014 + Gigaword 5 corpus, with 6B tokens; – The 300d …","url":["https://www.researchgate.net/profile/Joao_Silva45/publication/320711838_A_Study_of_Neural_Networks_Models_applied_to_Natural_Language_Inference/links/5b23a863458515270fcff1e1/A-Study-of-Neural-Networks-Models-applied-to-Natural-Language-Inference.pdf"]}
-{"year":"2019","title":"A Survey of URL-based Phishing Detection","authors":["ES Aung, CT Zan, H YAMANA"],"snippet":"… 2017 [40] 98.76 98.60 98.93 98.76 99.91 Common Crawl PhishTank 1M 1M Balanced Path length, URL entropy, length ratio, '@' and '-' count, punctuation count, TLDs count, IP address, suspicious words count …","url":["https://db-event.jpn.org/deim2019/post/papers/201.pdf"]}
-{"year":"2019","title":"A Survey on Document-level Machine Translation: Methods and Evaluation","authors":["S Maruf, F Saleh, G Haffari - arXiv preprint arXiv:1912.08494, 2019"],"snippet":"Page 1. A Survey on Document-level Machine Translation: Methods and Evaluation Sameen Maruf, Fahimeh Saleh, and Gholamreza Haffari Faculty of Information Technology, Monash University, Clayton VIC, Australia {firstname.lastname}@monash.edu …","url":["https://arxiv.org/pdf/1912.08494"]}
-{"year":"2019","title":"A System to Monitor Cyberbullying based on Message Classification and Social Network Analysis","authors":["S Menini, G Moretti, M Corazza, E Cabrio, S Tonelli… - Proceedings of the Third …, 2019"],"snippet":"… timestep. We use English Fasttext embeddings1 trained on Common Crawl with a size of 300. Concerning hy- perparameters, our model uses no dropout and no batch normalization on the outputs of the hidden layer. Instead …","url":["https://www.aclweb.org/anthology/W19-3511"]}
-{"year":"2019","title":"A Systematic Comparison Between SMT and NMT on Translating User-Generated Content","authors":["P Lohar, M Popovic, H Afli, A Way"],"snippet":"… Morever, as the Europarl corpus is a fix-domain and did not work well for our experiments, we plan to utilise other types of mix-domain parallel resource such as common crawl corpus9 … WASSA '12 (2012) 52–60 9 http://www.statmt …","url":["http://www.computing.dcu.ie/~away/PUBS/2019/A_Systematic_Comparison_Between_SMT_and_NMT_on_Translating_User_Generated_Content.pdf"]}
-{"year":"2019","title":"A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Computer Science","authors":["N Naderi - 2019"],"snippet":"Page 1. COMPUTATIONAL ANALYSIS OF ARGUMENTS AND PERSUASIVE STRATEGIES IN POLITICAL DISCOURSE by Nona Naderi A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy …","url":["ftp://ftp.db.toronto.edu/public_html/public_html/pub/gh/Naderi-PhD-thesis-2019.pdf"]}
-{"year":"2019","title":"A Vector Worth a Thousand Counts","authors":["DS Hain, R Jurowetzkiφ, T Buchmannψ, P Wolfψ"],"snippet":"… task convolutional neural network model trained on OntoNotes, with GloVe vectors (685k unique vectors with 300 dimensions) trained on Common Crawl. Given a patent abstract, spaCy predicts the meaning of each term in the document …","url":["https://pdfs.semanticscholar.org/69ba/b264607119c7928a9a25ea82823d9c346350.pdf"]}
-{"year":"2019","title":"Abstract Text Summarization: A Low Resource Challenge","authors":["S Parida, P Motlicek - 2019"],"snippet":"… We propose an iterative data augmentation approach which uses synthetic data along with the real summarization data for the German language. To generate synthetic data, the Common Crawl (German) dataset is exploited, which covers different domains …","url":["https://infoscience.epfl.ch/record/270135"]}
-{"year":"2019","title":"AC-Net: Assessing the Consistency of Description and Permission in Android Apps","authors":["Y Feng, L Chen, A Zheng, C Gao, Z Zheng - IEEE Access, 2019"],"snippet":"… Compared to the somewhat popular embeddings such as GloVe [22] (400 thousand word vectors trained on Wikipedia) and crawl [23] (2 million word vectors trained on Common Crawl), ours fully retains domain-specific characteristics of statements …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/08694776.pdf"]}
-{"year":"2019","title":"Acquiring Knowledge from Pre-trained Model to Neural Machine Translation","authors":["R Weng, H Yu, S Huang, S Cheng, W Luo - arXiv preprint arXiv:1912.01774, 2019"],"snippet":"… Following Song et al. (2019) , on the English and German, we use the monolingual data from WMT News Crawl. We select 50M sentence from year 2007 to 2017 for English and German respectively. Then, we choose 50M sentence from Common Crawl for Chinese …","url":["https://arxiv.org/pdf/1912.01774"]}
-{"year":"2019","title":"Adapting Transformer-XL Techniques to QANet Architecture for SQuAD 2.0 Challenge","authors":["L Zhang"],"snippet":"… set data. • glove.840B.300dglove.840B.300d.txt: Pretrained GloVevectors. Theseare300dimensional embeddings trained on the CommonCrawl 840B corpus. • {word,char}_emb.json: Word and character embeddings. Only the …","url":["https://pdfs.semanticscholar.org/0760/248f62e5a313fb088cce37495ce79c9ba8a1.pdf"]}
-{"year":"2019","title":"Adaptive Cross-Modal Few-Shot Learning","authors":["C Xing, N Rostamzadeh, BN Oreshkin, PO Pinheiro - arXiv preprint arXiv:1902.07104, 2019"],"snippet":"… category labels. GloVe is an unsupervised approach based on wordword co-occurrence statistics from large text corpora. We use the Common Crawl version trained on 840B tokens. The embeddings are of dimension 300. When …","url":["https://arxiv.org/pdf/1902.07104"]}
-{"year":"2019","title":"Advanced Deep learning Methods and Applications in Open-domain Question Answering","authors":["MT Nguyễn - 2019"],"snippet":"Page 1. VIETNAM NATIONAL UNIVERSITY, HANOI UNIVERSITY OF ENGINEERING AND TECHNOLOGY Nguyen Minh Trang ADVANCED DEEP LEARNING METHODS AND APPLICATIONS IN OPEN-DOMAIN QUESTION ANSWERING MASTER THESIS …","url":["http://lib.uet.vnu.edu.vn/bitstream/123456789/1021/1/2.ToanVanLuanVan.pdf"]}
-{"year":"2019","title":"Adversarial NLI: A New Benchmark for Natural Language Understanding","authors":["Y Nie, A Williams, E Dinan, M Bansal, J Weston… - arXiv preprint arXiv …, 2019"],"snippet":"… transfer. In addition to contexts from Wikipedia for Round 3, we also included contexts from the following domains: News (ex- tracted from Common Crawl), fiction (extracted from Mostafazadeh et al. 2016, Story Cloze, and Hill et al …","url":["https://arxiv.org/pdf/1910.14599"]}
-{"year":"2019","title":"Adverse drug event detection from electronic health records using hierarchical recurrent neural networks with dual-level embedding","authors":["S Wunnava, X Qin, T Kakar, C Sen, EA Rundensteiner… - Drug Safety, 2019"],"snippet":"… compared the results from DLADE, which uses domainand task-specific MADE1.0 word embedding trained using wiki, and Pittsburgh EHR and PubMed articles (1,352,550 word vectors) [10, 21], with two systems that use …","url":["https://link.springer.com/article/10.1007/s40264-018-0765-9"]}
-{"year":"2019","title":"AELA-DLSTMs: Attention-Enabled and Location-Aware Double LSTMs for Aspect-level Sentiment Classification","authors":["K Shuang, X Ren, Q Yang, R Li, J Loo - Neurocomputing, 2018"],"snippet":"Skip to main content …","url":["https://www.sciencedirect.com/science/article/pii/S0925231218315054"]}
-{"year":"2019","title":"Aiding Intra-Text Representations with Visual Context for Multimodal Named Entity Recognition","authors":["O Arshad, I Gallo, S Nawaz, A Calefati - arXiv preprint arXiv:1904.01356, 2019"],"snippet":"… Page 5. B. Word embeddings We used 300D fasttext crawl embeddings. It contains 2 million word vectors trained with subword information on Common Crawl (600B tokens). However, we do not apply fine-tuning on these embeddings during the training stage …","url":["https://arxiv.org/pdf/1904.01356"]}
-{"year":"2019","title":"Algorithmic Bias and the Biases of the Bias Catchers","authors":["D Rozado - arXiv preprint arXiv:1905.11985, 2019"],"snippet":"… This work systematically analyzed 3 popular word embedding methods: Word2vec (Skipgram) (4), Glove (9) and FastText (10), externally pretrained on a wide array of corpora such as Google News, Wikipedia, Twitter and Common Crawl …","url":["https://arxiv.org/pdf/1905.11985"]}
-{"year":"2019","title":"All-in-One: Emotion, Sentiment and Intensity Prediction using a Multi-task Ensemble Framework","authors":["S Akhtar, D Ghosal, A Ekbal, P Bhattacharyya… - IEEE Transactions on …, 2019"],"snippet":"… IEEE TRANSACTIONS ON AFFECTIVE COMPUTING. 4 A. Deep Learning Models We employ the architecture of Figure 1a to train and tune all the deep learning models using pre-trained GloVe (common crawl 840 billion) word embeddings [32] …","url":["https://ieeexplore.ieee.org/abstract/document/8756111/"]}
-{"year":"2019","title":"AMR-to-Text Generation with Cache Transition Systems","authors":["L Jin, D Gildea - arXiv preprint arXiv:1912.01682, 2019"],"snippet":"… 6.2 Setup The word embeddings are initialized with 300-dimensional GloVe embeddings (Penningtonetal., 2014) from the Common Crawl and are fixed during training. This embedding vocabulary consists of both English tokens and AMR concept labels …","url":["https://arxiv.org/pdf/1912.01682"]}
-{"year":"2019","title":"An effective approach to candidate retrieval for cross-language plagiarism detection: A fusion of conceptual and keyword-based schemes","authors":["M Roostaee, MH Sadreddini, SM Fakhrahmad - Information Processing & …, 2020"],"snippet":"Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0306457318310148"]}
-{"year":"2019","title":"An Efficient Framework for Processing and Analyzing Unstructured Text to Discover Delivery Delay and Optimization of Route Planning in Realtime","authors":["M Alshaer - 2019"],"snippet":"Page 1. HAL Id: tel-02310852 https://tel.archives-ouvertes.fr/tel-02310852 Submitted on 10 Oct 2019 HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not …","url":["https://tel.archives-ouvertes.fr/tel-02310852/document"]}
-{"year":"2019","title":"An Empirical Evaluation of Text Representation Schemes on Multilingual Social Web to Filter the Textual Aggression","authors":["S Modha, P Majumder - arXiv preprint arXiv:1904.08770, 2019"],"snippet":"… Glove pre-trained model available with different embed size and trained on common crawl, Twitter. We have use Glove pre-trained model with vocabulary size 2.2 million and trained on common crawl. fastText pretrained models are available in 157 language …","url":["https://arxiv.org/pdf/1904.08770"]}
-{"year":"2019","title":"An Empirical study on Pre-trained Embeddings and Language Models for Bot Detection","authors":["A Garcia-Silva, C Berrio, JM Gómez-Pérez - Proceedings of the 4th Workshop on …, 2019"],"snippet":"… scratch. We use pre-trained embeddings learned from Twitter it- self, urban dictionary definitions to accommodate the informal vocabulary often used in the social network, and common crawl as a general source of information …","url":["https://www.aclweb.org/anthology/W19-4317"]}
-{"year":"2019","title":"An Ensemble Method for Producing Word Representations for the Greek Language","authors":["M Lioudakis, S Outsios, M Vazirgiannis - arXiv preprint arXiv:1912.04965, 2019"],"snippet":"… In addition, we show that CBOS outperforms the CBOW and Skip-gram models when they are trained on the same data. The future work of this research could include training of our newly proposed model with the Common Crawl dataset for the Greek language …","url":["https://arxiv.org/pdf/1912.04965"]}
-{"year":"2019","title":"An Exploration of Sarcasm Detection Using Deep Learning","authors":["E SAVINI - 2019"],"snippet":"… not appear in the training data (”out-of-vocabulary” words). It also supports 157 different languages. In our research we use 300-dimensional word vectors pre-trained on Common Crawl3 (600B tokens). 4.3 ELMo ELMo (Embeddings …","url":["https://webthesis.biblio.polito.it/12440/1/tesi.pdf"]}
-{"year":"2019","title":"An Extended CLEF eHealth Test Collection for Cross-Lingual Information Retrieval in the Medical Domain","authors":["S Saleh, P Pecina - European Conference on Information Retrieval, 2019"],"snippet":"… However, an additional assessment was performed [15]. CLEF eHealth 2018 Consumer Health Search Task released a document collection created using CommonCrawl platform [8] containing more than five million documents from more than thousand websites …","url":["https://link.springer.com/chapter/10.1007/978-3-030-15719-7_24"]}
-{"year":"2019","title":"An integrated neural decoder of linguistic and experiential meaning","authors":["AJ Anderson, JR Binder, L Fernandino, CJ Humphries… - Journal of Neuroscience, 2019"],"snippet":"… occurrence 210 matrix (vocabulary size is 2.2million words and co-occurrences were measured across 840 billion 211 tokens from Common Crawl https://commoncrawl.org). GloVe in particular was used because it yielded 212 state-of …","url":["https://www.jneurosci.org/content/early/2019/09/27/JNEUROSCI.2575-18.2019.abstract"]}
-{"year":"2019","title":"An Open-Domain System for Retrieval and Visualization of Comparative Arguments from Text","authors":["M Schildwächter"],"snippet":"… parts of the Page 23. 3.1. Retrieval of Sentences 19 CommonCrawl: Full text search index Retrieval of Sentences: Elasticsearch API Sentence Classification: Keyword or ML approach Sentence Ranking: Ordering of sentences","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2018-ma-schildwaechter-cam.pdf"]}
-{"year":"2019","title":"Analysing Coreference in Transformer Outputs","authors":["ELKC Espana-Bonet, J van Genabith","ELKC Espana-Bonet, J van Genabith - DiscoMT 2019, 2019"],"snippet":"… Recent NMT systems that include context deal with both phenomena, coreference and coherence, but usually context is limited to the previous sen- # lines S1, S3 S2 Common Crawl 2394878 x1 x4 Europarl 1775445 …","url":["https://www.aclweb.org/anthology/D19-65.pdf#page=11","https://www.cs.upc.edu/~cristinae/CV/docs/coref_DiscoMT.pdf"]}
-{"year":"2019","title":"Analysing Representations of Memory Impairment in a Clinical Notes Classification Model","authors":["M Ormerod, J Martínez-del-Rincón, N Robertson… - Proceedings of the 18th …, 2019"],"snippet":"… In this study we use 300-dimensional fastText word embeddings (Bojanowski et al., 2017) which were pretrained on the Common Crawl dataset using the skipgram schema (Mikolov et al., 2013), which in- volves predicting a target word based on nearby words …","url":["https://www.aclweb.org/anthology/W19-5005"]}
-{"year":"2019","title":"Analysis of Joint Multilingual Sentence Representations and Semantic K-Nearest Neighbor Graphs","authors":["H Schwenk, D Kiela, M Douze - Proceedings of the AAAI Conference on Artificial …, 2019"],"snippet":"… All the statistics in this section are calculated on ten million sentences of Common Crawl data. Please remember that we apply romanization for the languages which use a Cyrillic script (Greek, Bosnian, Bulgarian, Macedonian, Serbian and Russian) …","url":["https://www.aaai.org/ojs/index.php/AAAI/article/download/4677/4555"]}
-{"year":"2019","title":"Analysis of Positional Encodings for Neural Machine Translation","authors":["J Rosendahl, VAK Tran, W Wang, H Ney"],"snippet":"… We train our models on the data from the De→En and the Zh→En news translation task of WMT 2019. For the De→En task we train on CommonCrawl, Europarl, NewsCommentary and Rapid summing up …","url":["https://zenodo.eu/record/3525024/files/IWSLT2019_paper_21.pdf"]}
-{"year":"2019","title":"Annotating and Recognising Visually Descriptive Language","authors":["T Alrashid, J Wang, R Gaizauskas - … on Interoperable Semantic Annotation (ISA-15), 2019"],"snippet":"… Stop words were only removed for the word embedding representation. We did not remove stop words for tf-idf because the approach 5https://spacy. io/. We use the model en vectors web lg. 6http://commoncrawl. org/the-data/ 7http://www. scikit-learn. org/ 27 Page 34 …","url":["https://sigsem.uvt.nl/isa15/ISA-15_proceedings.pdf#page=28"]}
-{"year":"2019","title":"Answering Comparative Questions: Better than Ten-Blue-Links?","authors":["M Schildwächter, A Bondarenko, J Zenker, M Hagen… - arXiv preprint arXiv …, 2019"],"snippet":"… CommonCrawl: Full text search index … Clicking on a result sentence reveals its Common Crawl context—by default the ±3 sentences around it, with the … underlying corpus of our CAM system and the keyword-based search …","url":["https://arxiv.org/pdf/1901.05041"]}
-{"year":"2019","title":"Architecture for semantic search over encrypted data in the cloud","authors":["J Woodworth, MA Salehi - US Patent App. 16/168,919, 2019"],"snippet":"… The dataset has a total size of 357 MB and is made up of 6,942 text files. To evaluate S3C under large scale datasets, a second dataset, the Common Crawl Corpus from AWS (a web crawl composed of over five billion web pages) was used …","url":["https://patentimages.storage.googleapis.com/f7/5f/a4/c986d736bd81ab/US20190121873A1.pdf"]}
-{"year":"2019","title":"Are we consistently biased? Multidimensional analysis of biases in distributional word vectors","authors":["A Lauscher, G Glavaš - arXiv preprint arXiv:1904.11783, 2019"],"snippet":"… 4 we compare the biases of em- beddings trained with the same model (GLOVE) but on different corpora: Common Crawl (ie, noisy … Table 4: WEAT bias effects for GLOVE embeddings trained on different corpora: Wikipedia …","url":["https://arxiv.org/pdf/1904.11783"]}
-{"year":"2019","title":"Are We Safe Yet? The Limitations of Distributional Features for Fake News Detection","authors":["T Schuster, R Schuster, DJ Shah, R Barzilay - arXiv preprint arXiv:1908.09805, 2019"],"snippet":"… 2019). The generator is trained with a LM objective on a large news corpus from Common Crawl dumps. The fake news detector is a simple linear classifier on top of the last hidden state of Grover's LM on the examined article …","url":["https://arxiv.org/pdf/1908.09805"]}
-{"year":"2019","title":"Argument Generation with Retrieval, Planning, and Realization","authors":["X Hua, Z Hu, L Wang - arXiv preprint arXiv:1906.03717, 2019"],"snippet":"… Wachsmuth et al., 2017b, 2018b). Recent work by Stab et al. (2018) in- dexes all web documents collected in Common Crawl, which inevitably incorporates noisy, lowquality content. Besides, existing work treats individual …","url":["https://arxiv.org/pdf/1906.03717"]}
-{"year":"2019","title":"Argument Search: Assessing Argument Relevance","authors":["M Potthast, L Gienapp, F Euchner, N Heilenkötter… - 2019"],"snippet":"… online debating portals. Thereafter, ArgumenText [19], which retrieves argumentative sentences from the Common Crawl, and “multi-perspective answers” in the US version of Bing3 have been published. Another loosely related …","url":["https://webis.de/downloads/publications/papers/stein_2019j.pdf"]}
-{"year":"2019","title":"Articles Classification in Myanmar Language","authors":["MS Phyu, KT Nwet - 2019 International Conference on Advanced …, 2019"],"snippet":"… Fortunately, Grave et al. [3] recently released pretrained vectors for 246 languages trained on Wikipedia and common crawl … Data source Method Number of word vectors Dimension Wikipedia fastText (skip-gram) 91,497 …","url":["https://ieeexplore.ieee.org/abstract/document/8920927/"]}
-{"year":"2019","title":"Artificial Intelligence: An Overview","authors":["P Grogono"],"snippet":"Page 1. Chapter 1 Artificial Intelligence: An Overview Peter Grogono Department of Computer Science and Software Engineering Concordia University Montréal, Québec The smart devices that we have become so familiar with …","url":["https://www.worldscientific.com/doi/abs/10.1142/9789811203527_0001"]}
-{"year":"2019","title":"Aspect Detection using Word and Char Embeddings with (Bi) LSTM and CRF","authors":["Ł Augustyniak, T Kajdanowicz, P Kazienko - 2019 IEEE Second International …, 2019"],"snippet":"… Glove 840B - Global Vectors for Word Representation proposed by Stanford NLP Group, trained based on Common Crawl. fastText - Distributed Word Representation proposed by Facebook, trained on Common Crawl as well …","url":["https://ieeexplore.ieee.org/abstract/document/8791735/"]}
-{"year":"2019","title":"Aspect-Based Sentiment Analysis Using Deep Neural Networks and Transfer Learning","authors":["S Dugar"],"snippet":"Page 1. DEPARTMENT OF INFORMATICS TECHNISCHE UNIVERSITÄT MÜNCHEN Master's Thesis in Informatics Aspect-Based Sentiment Analysis Using Deep Neural Networks and Transfer Learning Sumit Dugar Page 2. DEPARTMENT OF INFORMATICS …","url":["https://www.social.in.tum.de/fileadmin/w00bwc/www/Gerhard_Hagerer/thesis-sumit-dugar.pdf"]}
-{"year":"2019","title":"Assessing Social and Intersectional Biases in Contextualized Word Representations","authors":["YC Tan, LE Celis - arXiv preprint arXiv:1911.01485, 2019"],"snippet":"Page 1. Assessing Social and Intersectional Biases in Contextualized Word Representations Yi Chern Tan, L. Elisa Celis Yale University {yichern.tan, elisa.celis}@yale.edu Abstract Social bias in machine learning has drawn …","url":["https://arxiv.org/pdf/1911.01485"]}
-{"year":"2019","title":"Assessing the Impact of Contextual Embeddings for Portuguese Named Entity Recognition","authors":["J Santos, B Consoli, C dos Santos, J Terra, S Collonini… - 2019 8th Brazilian …, 2019"],"snippet":"… 2019. [19] C. Buck, K. Heafield, and B. van Ooyen, “N-gram counts and language models from the common crawl,” in Proceedings of the Language Resources and Evaluation Conference, Reykjavik, Iceland, May 2014. [20] N …","url":["https://ieeexplore.ieee.org/abstract/document/8923652/"]}
-{"year":"2019","title":"Assessing the Lexico-Semantic Relational Knowledge Captured by Word and Concept Embeddings","authors":["R Denaux, JM Gomez-Perez - arXiv preprint arXiv:1909.11042, 2019"],"snippet":"… three different corpora, which we chose to study whether relation prediction capacity varies depending on the corpus size: the English United Nations corpus[Ziemski et al., 2016] (517M tokens), the En- glish Wikipedia (just under …","url":["https://arxiv.org/pdf/1909.11042"]}
-{"year":"2019","title":"Assessment of text coherence using an ontology‐based relatedness measurement method","authors":["G Giray, MO Ünalır - Expert Systems"],"snippet":"Abstract This paper proposes a novel method for assessing text coherence. Central to this approach is an ontology‐based representation of text, which captures the level of relatedness between conse...","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.12505"]}
-{"year":"2019","title":"AStylometric INVESTIGATION OF CHARACTER VOICES IN LITERARY FICTION","authors":["K Vishnubhotla - 2019"],"snippet":"Page 1. ASTYLOMETRIC INVESTIGATION OF CHARACTER VOICES IN LITERARY FICTION by Krishnapriya Vishnubhotla A thesis submitted in conformity with the requirements for the degree of Master of Science …","url":["ftp://ftp.db.toronto.edu/public_html/cs/ftp/dist/gh/Vishnubhotla-MSc-thesis-2019.pdf"]}
-{"year":"2019","title":"Asymmetry Sensitive Architecture for Neural Text Matching","authors":["T Belkacem, JG Moreno, T Dkaki, M Boughanem - European Conference on …, 2019"],"snippet":"… We adopted a cross-validation with \\(80\\%\\) to train, \\(10\\%\\) to test and \\(10\\%\\) to validate the different models. We used a public pre-trained 300-dimensional word vectors of GloVe 3 , which are trained in a Common crawl dataset …","url":["https://link.springer.com/chapter/10.1007/978-3-030-15719-7_8"]}
-{"year":"2019","title":"Asynchronous pipelines for processing huge corpora on medium to low resource infrastructures","authors":["PJ Ortiz Suárez, B Sagot, L Romary - 2019"],"snippet":"… 7http://commoncrawl.org/about/ 8http://microformats.org/wiki/ rel-nofollow 9https://www.robotstxt.org … In order to download, extract, filter, clean and classify Common Crawl we base ourselves on … Each of these processes first …","url":["https://ids-pub.bsz-bw.de/files/9021/Suarez_Sagot_Romary_Asynchronous_Pipeline_for_Processing_Huge_Corpora_2019.pdf"]}
-{"year":"2019","title":"At the Lower End of Language—Exploring the Vulgar and Obscene Side of German","authors":["E Eder, U Krieg-Holz, U Hahn - Proceedings of the Third Workshop on Abusive …, 2019"],"snippet":"… 123 FASTTEXT (Grave et al., 2018) word embeddings, the latter being based on COMMON CRAWL and WIKIPEDIA … et al., 2017) trained on German tweets (TWITTER) and, finally, FASTTEXT word embeddings (Grave et al., 2018) …","url":["https://www.aclweb.org/anthology/W19-3513"]}
-{"year":"2019","title":"Attending the Emotions to Detect Online Abusive Language","authors":["NS Samghabadi, A Hatami, M Shafaei, S Kar, T Solorio - arXiv preprint arXiv …, 2019"],"snippet":"… Then, we extract 5For ask.fm data, we use 300-dimensional Common Crawl Glove pre-trained embeddings, since it works better than the Twitter embedding. the DeepMoji vector for each sentence and calculate the average vector per post …","url":["https://arxiv.org/pdf/1909.03100"]}
-{"year":"2019","title":"Attention Guided Graph Convolutional Networks for Relation Extraction","authors":["Z Guo, Y Zhang, W Lu - arXiv preprint arXiv:1906.07510, 2019"],"snippet":"… 5https://nlp.stanford.edu/projects/ tacred/ 6We use the 300-dimensional Glove word vectors trained on the Common Crawl corpus https://nlp. stanford.edu/projects/glove/ 7The results are produced by the open implementation of Zhang et al. (2018). Page 6. Model …","url":["https://arxiv.org/pdf/1906.07510"]}
-{"year":"2019","title":"Attenuating Bias in Word Vectors","authors":["S Dev, J Phillips - arXiv preprint arXiv:1901.07656, 2019"],"snippet":"Page 1. Attenuating Bias in Word Vectors Sunipa Dev Jeff Phillips University of Utah University of Utah Abstract Word vector representations are well developed tools for various NLP and Machine Learning tasks and are known …","url":["https://arxiv.org/pdf/1901.07656"]}
-{"year":"2019","title":"Attribute Sentiment Scoring With Online Text Reviews: Accounting for Language Structure and Attribute Self-Selection","authors":["I Chakraborty, M Kim, K Sudhir - 2019"],"snippet":"Page 1. Attribute Sentiment Scoring with Online Text Reviews: Accounting for Language Structure and Attribute Self-Selection Ishita Chakraborty, Minkyung Kim, K. Sudhir Yale School of Management March 2019 We thank the …","url":["http://sics.haas.berkeley.edu/pdf_2019/paper_cks.pdf"]}
-{"year":"2019","title":"Augmenting Neural Machine Translation through Round-Trip Training Approach","authors":["B Ahmadnia, BJ Dorr"],"snippet":"… For the high-resource scenario (En- Es) we utilize the English-Spanish bilingual corpora from WMT'18² [29] which contains 10M sentence pairs extracting from Europarl, News-Commentary, UN and Common Crawl collections …","url":["https://www.researchgate.net/profile/Benyamin_Ahmadnia/publication/336485784_Augmenting_Neural_Machine_Translation_through_Round-Trip_Training_Approach/links/5da2b06d92851c6b4bd100ab/Augmenting-Neural-Machine-Translation-through-Round-Trip-Training-Approach.pdf"]}
-{"year":"2019","title":"AutoEncoder Guided Bootstrapping of Semantic Lexicon","authors":["C Hu, M Nakano, M Okumura - Pacific Rim International Conference on Artificial …, 2019"],"snippet":"… The top-5 best candidate instances were then added to the expanded seed list for the next iteration. For the inputs of the AutoEncoder model, Glove embeddings (300 dimensions) trained on Common Crawl were used (Pennington et al …","url":["https://link.springer.com/chapter/10.1007/978-3-030-29894-4_17"]}
-{"year":"2019","title":"Automated Dictionary Creation for Analyzing Text: An Illustration from Stereotype Content","authors":["G Nicolas, X Bai, ST Fiske - 2019"],"snippet":"… The Glove word embeddings used here were trained using around 840 billion words from the common crawl (a very large database of web text), and it has word-vectors with 300 dimensions for 2.2 million words (available …","url":["https://psyarxiv.com/afm8k/download?format=pdf"]}
-{"year":"2019","title":"Automated extraction of attributes from natural language attribute-based access control (ABAC) Policies","authors":["M Alohaly, H Takabi, E Blanco - Cybersecurity, 2019"],"snippet":"The National Institute of Standards and Technology (NIST) has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC...","url":["https://link.springer.com/article/10.1186/s42400-018-0019-2"]}
-{"year":"2019","title":"Automated Grading of Short Text Answers: Preliminary Results in a Course of Health Informatics","authors":["G De Gasperis, S Menini, S Tonelli, P Vittorini - International Conference on Web …, 2019"],"snippet":"… vectors representing both words and sub-words. To generate these embeddings we start from the pre-computed Italian language model 3 , trained on Common Crawl and Wikipedia. The latter, in particular, is suitable for our …","url":["https://link.springer.com/chapter/10.1007/978-3-030-35758-0_18"]}
-{"year":"2019","title":"Automated lifelog moment retrieval based on image segmentation and similarity scores","authors":["S Taubert, S Kahl, D Kowerko, M Eibl - CLEF2019 Working Notes. CEUR Workshop …, 2019"],"snippet":"… Page 8. 4 Resources We only used resources which were open source. Our word vectors were pretrained GloVe vectors from Common Crawl which had 300 dimensions and a vocabulary of 2.2 million tokens [27]. Furthermore …","url":["http://ceur-ws.org/Vol-2380/paper_83.pdf"]}
-{"year":"2019","title":"Automated organ-level classification of free-text pathology reports to support a radiology follow-up tracking engine","authors":["JM Steinkamp, CM Chambers, D Lalevic, HM Zafar… - Radiology: Artificial …, 2019"],"snippet":"… GloVe word embeddings pretrained on the Common Crawl dataset of web pages were used as input to both networks; no performance benefit was observed from continuing to train word embeddings during the experiments …","url":["https://pubs.rsna.org/doi/abs/10.1148/ryai.2019180052"]}
-{"year":"2019","title":"Automatic Knowledge Extraction to build Semantic Web of Things Applications","authors":["M Noura, A Gyrard, S Heil, M Gaedke - IEEE Internet of Things Journal, 2019"],"snippet":"… The naming process used additional hypernym information derived from WebIsALOD12 the Linked Open Data version of the WebIsA Database, a database containing 11.7 million hypernymy re- lations extracted from the CommonCrawl web corpus …","url":["http://knoesis.wright.edu/sites/default/files/IEEE_IoT_Journal_2019_Concept_Extraction_Paper_Extended.pdf"]}
-{"year":"2019","title":"Automatic stance detection on political discourse in Twitter","authors":["E Zotova - 2019"],"snippet":"Page 1. Automatic Stance Detection on Political Discourse in Twitter Author: Elena Zotova Advisors: Rodrigo Agerri and German Rigau Hizkuntzaren Azterketa eta Prozesamendua Language Analysis and Processing Master's Thesis …","url":["https://addi.ehu.es/bitstream/handle/10810/36184/MAL-Elena_Zotova.pdf?sequence=1&isAllowed=y"]}
-{"year":"2019","title":"Automatic Text Difficulty Estimation Using Embeddings and Neural Networks","authors":["A Filighera, T Steuer, C Rensing - European Conference on Technology Enhanced …, 2019"],"snippet":"… Next, the resulting tokens are embedded. The following pre-trained embedding models were used in our experiments: the word2vec [14], the uncased Common Crawl GloVe [15], the original ELMo [16], the uncased …","url":["https://link.springer.com/chapter/10.1007/978-3-030-29736-7_25"]}
-{"year":"2019","title":"Automatic Text Summarization of News Articles in Serbian Language","authors":["D Kosmajac, V Kešelj - 2019 18th International Symposium INFOTEH …, 2019"],"snippet":"… 1). A. Auxiliary word2vec generated from Bosnian Wikidumps For input representation we used pre-trained glove word embeddings for Bosnian language2. They were trained on Common Crawl and Wikipedia using fastText [20] …","url":["https://ieeexplore.ieee.org/abstract/document/8717655/"]}
-{"year":"2019","title":"Automating Analysis and Feedback to Improve Mathematics' Teachers' Classroom Discourse","authors":["A Suresh, T Sumner, J Jacobs, B Foland, W Ward - Paper submitted to the ninth …, 2019"],"snippet":"… GloVe or Global vectors for word representation is an unsupervised learning algorithm trained on aggregated word-word co-occurrence statistics from a corpus. In our model, we use the vectors trained on Common Crawl with 840 billion tokens and 300 dimensions …","url":["https://www.researchgate.net/profile/Jennifer_Jacobs8/publication/332233671_Automating_Analysis_and_Feedback_to_Improve_Mathematics%27_Teachers%27_Classroom_Discourse/links/5ca7c7394585157bd32535fc/Automating-Analysis-and-Feedback-to-Improve-Mathematics-Teachers-Classroom-Discourse.pdf"]}
-{"year":"2019","title":"Automating the Fact-Checking Task: Challenges and Directions","authors":["DNE da Silva - 2019"],"snippet":"Page 1. Automating the Fact-Checking Task: Challenges and Directions Dissertation zur Erlangung des Doktorgrades (Dr. rer. nat.) der Mathematisch-Naturwissenschaftlichen Fakultät der Rheinischen Friedrich-Wilhelms-Universität Bonn …","url":["http://hss.ulb.uni-bonn.de/2019/5500/5500.pdf"]}
-{"year":"2019","title":"Backlink Analyser using Apache Spark","authors":["M Zeeshan, S Asim, A Nadeem Anwar - 2019"],"snippet":"… Google Page Rank is assigned by Google based on different website factors (Design, Visitors, and Quality of content). Common Crawl [1] is an open repository for web crawl data … We will use subset of Common Crawl dataset good enough to demonstrate our system …","url":["http://dspace.cuilahore.edu.pk/xmlui/bitstream/handle/123456789/1438/SE29_Backlink%20Analyzer%20using%20Apache%20Spark.pdf?sequence=1&isAllowed=y"]}
-{"year":"2019","title":"BEING PROFILED: COGITAS ERGO SUM: 10 Years of Profiling the European Citizen","authors":["I Baraliuc, E Bayamlioglu, M Hildebrandt, L Janssens - 2019"],"snippet":""}
-{"year":"2019","title":"Beyond Bag-of-Concepts: Vectors of Locally Aggregated Concepts","authors":["M Grootendorst, J Vanschoren"],"snippet":"… Word2Vec pre-trained embeddings were trained on the Google News data set and contain vectors for 3 million English words.1 GloVe pre-trained embeddings were trained on the Common Crawl data set and contain vectors for 1.9 million English words.2 Pre-trained …","url":["https://ecmlpkdd2019.org/downloads/paper/489.pdf"]}
-{"year":"2019","title":"Bidirectional Text Compression in External Memory","authors":["P Dinklage, J Ellert, J Fischer, D Köppl, M Penschuck - arXiv preprint arXiv …, 2019"],"snippet":"Page 1. Bidirectional Text Compression in External Memory Patrick Dinklage Technische Universität Dortmund, Department of Computer Science patrick.dinklage@ tu-dortmund.de Jonas Ellert Technische Universität Dortmund …","url":["https://arxiv.org/pdf/1907.03235"]}
-{"year":"2019","title":"Big Bidirectional Insertion Representations for Documents","authors":["L Li, W Chan - arXiv preprint arXiv:1910.13034, 2019"],"snippet":"… Eu- Page 3. Figure 1: Big Bidirectional Insertion Representations for Documents roparl, Rapid, News-Commentary) and parallel sentence-level data (WikiTitles, Common Crawl, Paracrawl). The test set is newstest2019. The …","url":["https://arxiv.org/pdf/1910.13034"]}
-{"year":"2019","title":"Big BiRD: A Large, Fine-Grained, Bigram Relatedness Dataset for Examining Semantic Composition","authors":["S Asaadi, SM Mohammad, S Kiritchenko"],"snippet":"… Word representations: We use GloVe word embeddings pre-trained on 840B-token CommonCrawl corpus16 and fastText word embeddings pre-trained on Common Crawl and Wikipedia using CBOW.17 For the …","url":["http://saifmohammad.com/WebDocs/BiRD-NAACL2019.pdf"]}
-{"year":"2019","title":"Big Data Competence Center ScaDS Dresden/Leipzig: Overview and selected research activities","authors":["E Rahm, WE Nagel, E Peukert, R Jäkel, F Gärtner… - Datenbank-Spektrum"],"snippet":"… devise multiple research activities. The most promising direction resulted in the publication of the “Dresden WebTable Corpus” (DWTC) 2 [9] based on the freely available web crawl “CommonCrawl”. The DWTC corpus consists …","url":["https://link.springer.com/article/10.1007/s13222-018-00303-6"]}
-{"year":"2019","title":"Boosting Implicit Discourse Relation Recognition with Connective-based Word Embeddings","authors":["C Wu, J Su, Y Chen, X Shi - Neurocomputing, 2019"],"snippet":"Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0925231219312196"]}
-{"year":"2019","title":"Bornholmsk Natural Language Processing: Resources and Tools","authors":["L Derczynski, ITU Copenhagen, AS Kjeldsen - Proceedings of the Nordic Conference …, 2019"],"snippet":"… of compensating for the high data sparsity. Embeddings are induced with 300 dimensions, in order to be compatible with the public Common Crawl-based FastText embeddings. Having induced these embeddings for Bornholmsk …","url":["http://www.derczynski.com/papers/bornholmsk.pdf"]}
-{"year":"2019","title":"BTC-2019: The 2019 Billion Triple Challenge Dataset","authors":["JM Herrera, A Hogan, T Käfer - International Semantic Web Conference, 2019"],"snippet":"… Meusel et al. [43] have published the WebDataCommons, extracting RDFa, Microdata and Microformats from the massive Common Crawl dataset; the result is a collection of 17,241,313,916 RDF triples, which, to the best of …","url":["https://link.springer.com/chapter/10.1007/978-3-030-30796-7_11"]}
-{"year":"2019","title":"Building and using parallel text for translation","authors":["M Simard - The Routledge Handbook of Translation and …, 2019"]}
-{"year":"2019","title":"Building Knowledge Base through Deep Learning Relation Extraction and Wikidata","authors":["P Subasic, H Yin, X Lin"],"snippet":"… Very large high-quality training data set is then generated automatically by matching Common Crawl data with relation keywords extracted from knowledge database … We solve this problem by matching Common Crawl …","url":["http://ceur-ws.org/Vol-2350/paper5.pdf"]}
-{"year":"2019","title":"BUILDING TYPE CLASSIFICATION FROM SOCIAL MEDIA TEXTS VIA GEO-SPATIAL TEXT MINING","authors":["M Häberle, M Werner, XX Zhu"],"snippet":"… We applied the ReLU activation function [18] after each hidden layer and the softmax function after the output layer. The neural network has been trained for 100 epochs and a batch size of 64 samples. 2http …","url":["https://elib.dlr.de/127637/1/preprint.pdf"]}
-{"year":"2019","title":"Building Unbiased Comment Toxicity Classification Model with Natural Language Processing","authors":["LQ Huang, MJ Yu"],"snippet":"… For this project, we investigated word embeddings GloVe300D (11) and fastText300D (12), where both are pretrained on Common Crawl. We also implemented character level embedding layer introduced in the paper (13) …","url":["http://cs229.stanford.edu/proj2019spr/report/79.pdf"]}
-{"year":"2019","title":"Building Unbiased Comment Toxicity Classification Model","authors":["LQ Huang, MJ Yu"],"snippet":"… combined them together to mitigate the potential biases in any embeddings. We experimented with GloVe 300D trained on Common Crawl [3] and fastText 300D trained on Common Crawl [2]. We also implemented …","url":["http://cs229.stanford.edu/proj2019spr/poster/79.pdf"]}
-{"year":"2019","title":"CamemBERT: a Tasty French Language Model","authors":["L Martin, B Muller, PJO Suárez, Y Dupont, L Romary… - arXiv preprint arXiv …, 2019"],"snippet":"… Later (Grave et al., 2018) trained fastText word embeddings for 157 languages using Common Crawl and showed that using crawled data significantly increased the performance of the embeddings relatively to those trained only on Wikipedia …","url":["https://arxiv.org/pdf/1911.03894"]}
-{"year":"2019","title":"Can Character Embeddings Improve Cause-of-Death Classification for Verbal Autopsy Narratives?","authors":["Z Yan, S Jeblee, G Hirst"],"snippet":"… Page 3. Figure 1: Embedding concatenation model architecture. d1 is the dimensionality of the word embedding (100), and d2 is the dimensionality of the character em- bedding (24). rived from GloVe vectors (Pennington et al., 2014) trained on Common Crawl …","url":["ftp://ftp.db.toronto.edu/public_html/cs/ftp/public_html/pub/gh/Yan-etal-2019.pdf"]}
-{"year":"2019","title":"Capturing and measuring thematic relatedness","authors":["M Kacmajor, JD Kelleher - Language Resources and Evaluation, 2019"],"snippet":"Page 1. ORIGINAL PAPER Capturing and measuring thematic relatedness Magdalena Kacmajor1 • John D. Kelleher2 © The Author(s) 2019 Abstract In this paper we explain the difference between two aspects of semantic …","url":["https://link.springer.com/article/10.1007/s10579-019-09452-w"]}
-{"year":"2019","title":"Capturing Discriminative Attributes Using Convolution Neural Network Over ConceptNet Numberbatch Embedding","authors":["V Vinayan, MA Kumar, KP Soman - … Research in Electronics, Computer Science and …, 2019"],"snippet":"… network. There the model is represented over the various dimensions of GloVe embedding, of those the 300 dimensions (trained over a common crawl corpus of size 840B) embedding performed the best for the task. Building …","url":["https://link.springer.com/chapter/10.1007/978-981-13-5802-9_69"]}
-{"year":"2019","title":"Cardiff University at SemEval-2019 Task 4: Linguistic Features for Hyperpartisan News Detection","authors":["C Pérez-Almendros, LE Anke, S Schockaert - … of the 13th International Workshop on …, 2019"],"snippet":"… GloVe vectors (Pennington et al., 2014) for all the words occurring in them. To this end, we used the un- cased Common Crawl pretrained GloVe embeddings, with 300 dimensions and a vocabulary of 1.9 million words. The …","url":["https://www.aclweb.org/anthology/S19-2158"]}
-{"year":"2019","title":"CatchPhish: detection of phishing websites by inspecting URLs","authors":["RS Rao, T Vaishnavi, AR Pais - Journal of Ambient Intelligence and Humanized …, 2019"],"snippet":"… 4.1 Dataset We have collected the dataset from three different sources. Legitimate sites are collected from common-crawl and Alexa database whereas phishing sites are collected from PhishTank … D2: Legitimate sites from common-crawl and phishing sites from PhishTank …","url":["https://link.springer.com/article/10.1007/s12652-019-01311-4"]}
-{"year":"2019","title":"Categorising AWS Common Crawl Dataset using MapReduce","authors":["A Chiniah, A Chummun, Z Burkutally - 2019 Conference on Next Generation …, 2019"],"snippet":"Keeping track of websites connected to the Web is an impossible task given the amplitude and fluctuation of new sites being created and those going offline. In this paper we took the task to create a directory by categorising the websites using …","url":["https://ieeexplore.ieee.org/abstract/document/8883665/"]}
-{"year":"2019","title":"Categorizing Comparative Sentences","authors":["A Panchenko, A Bondarenko, M Franzek, M Hagen…"],"snippet":"… containing both items from a web-scale corpus. Our sentence source is the publicly available in- dex of the DepCC (Panchenko et al., 2018), an index of more then 14 billion dependency-parsed English sentences from the Common Crawl filtered for duplicates …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2019-panchenkoetal-argminingws-compsent.pdf"]}
-{"year":"2019","title":"Categorizing Emails Using Machine Learning with Textual Features","authors":["F Rudzicz, K Malikov - Advances in Artificial Intelligence: 32nd Canadian …","H Zhang, J Rangrej, S Rais, M Hillmer, F Rudzicz… - Canadian Conference on …, 2019"],"snippet":"… Lastly, domain-specific email inboxes such as DDM-Support will contain highly specific subject-matter terminology such as organization acronyms or hospital names, which are generally not present in large text corpora such as common crawl …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=7GiZDwAAQBAJ&oi=fnd&pg=PA3&dq=commoncrawl&ots=pxG3RFx1gg&sig=XpsK2sgWrDKsYko4OCiNHIo5Meg","https://link.springer.com/chapter/10.1007/978-3-030-18305-9_1"]}
-{"year":"2019","title":"CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB","authors":["H Schwenk, G Wenzek, S Edunov, E Grave, A Joulin - arXiv preprint arXiv …, 2019"],"snippet":"… We are using ten snapshots of a curated common crawl corpus (Wenzek et al., 2019), totaling 32.7 billion unique sentences … we use the same underlying mining approach based on LASER and scale to a much larger …","url":["https://arxiv.org/pdf/1911.04944"]}
-{"year":"2019","title":"CCMT 2019 Machine Translation Evaluation Report","authors":["M Yang, X Hu, H Xiong, J Wang, Y Jiaermuhamaiti… - China Conference on …, 2019","Y Jiaermuhamaiti, Z He, W Luo, S Huang - … , China, September 27–29, 2019, Revised …, 2019"],"snippet":"… (2) English and Chinese monolingual Corpus (Europarl v7/v8, News Commentary, Common Crawl, News Crawl, News Discussions, etc.); LDC for English and Gigaword for Chinese (LDC2011T07, LDC2009T13, LDC2007T07, LDC2009T27) …","url":["https://link.springer.com/chapter/10.1007/978-981-15-1721-1_11","https://link.springer.com/content/pdf/10.1007/978-981-15-1721-1.pdf#page=117"]}
-{"year":"2019","title":"CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data","authors":["G Wenzek, MA Lachaux, A Conneau, V Chaudhary… - arXiv preprint arXiv …, 2019"],"snippet":"… (2019) used a large scale dataset based on Common Crawl to train text … Russian, Chinese and Urdu (∆ for average) for BERT-BASE models trained either on Wikipedia or CommonCrawl … We preprocess Common Crawl by …","url":["https://arxiv.org/pdf/1911.00359"]}
-{"year":"2019","title":"Characterizing the impact of geometric properties of word embeddings on task performance","authors":["B Whitaker, D Newman-Griffis, A Haldar… - arXiv preprint arXiv …, 2019"],"snippet":"… 1 3M 300-d GoogleNews vectors from https:// code.google.com/archive/p/ word2vec/ 2 2M 300-d 840B Common Crawl vectors from https: //nlp.stanford.edu/projects/glove/ 3 1M 300-d WikiNews vectors with subword …","url":["https://arxiv.org/pdf/1904.04866"]}
-{"year":"2019","title":"CITIZENS IN DATA LAND","authors":["AP DE VRIES"],"snippet":"… And Indie music'. 3 https://github.com/webis-de/wasp/. 4 Consider a new service provided by The Common Crawl Foundation, http://commoncrawl org/, or, alternatively, a new community service provided via public libraries …","url":["https://www.jstor.org/stable/pdf/j.ctvhrd092.19.pdf"]}
-{"year":"2019","title":"CLaC at clpsych 2019: Fusion of neural features and predicted class probabilities for suicide risk assessment based on online posts","authors":["E Mohammadi, H Amini, L Kosseim - Proceedings of the Sixth Workshop on …, 2019"],"snippet":"… 2.1 Word Embeddings As shown in Figure 1, GloVe (Pennington et al., 2014) and ELMo (Peters et al., 2018) have been used as pretrained word embeddings. The 300d GloVe word embedder has been pretrained on 840B tokens of web data from Common Crawl …","url":["https://www.aclweb.org/anthology/W19-3004"]}
-{"year":"2019","title":"Classification Approaches to Identify Informative Tweets","authors":["P Aggarwal - Proceedings of the Student Research Workshop …, 2019"],"snippet":"… After these preprocessing steps, we represent each posting by a dense embedding, created by the mean of the individual words embeddings. We use the pretrained embeddings provided by (Mikolov et al., 2018) …","url":["https://www.researchgate.net/profile/Piush_Aggarwal/publication/335243720_Classification_approaches_to_identify_Informative_Tweets/links/5d5af768a6fdcc55e8198141/Classification-approaches-to-identify-Informative-Tweets.pdf"]}
-{"year":"2019","title":"Classification of Anti-phishing Solutions","authors":["S Chanti, T Chithralekha - SN Computer Science, 2020"],"snippet":"… WestPac. PhishTank. PIRT report. Legitimate. –. Google whitelist. Manual. Alexa, Yahoo. Web crawler. World Wide Web. WestPac. Common crawl Google search. Data set size. Phishing. 203 Archives. 200 websites. 600 …","url":["https://link.springer.com/article/10.1007/s42979-019-0011-2"]}
-{"year":"2019","title":"Classification of the Answers of the OMT","authors":["F Meyer, C Biemann"],"snippet":"Page 1. Universität Hamburg Fachbereich Informatik Fakultät für Mathematik, Informatik und Naturwissenschaften Classi cation of the Answers of the OMT Bachelor-Thesis Mensch-Computer-Interaktion Arbeitsbereich …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2019-ba-meyer-omt.pdf"]}
-{"year":"2019","title":"Classification of virtual patent marking web-pages using machine learning techniques","authors":["A Calvo Ibañez - 2018"],"snippet":"… Having found the best model, this was then used to predict Common Crawl instances (nonseen observations). Figure 6.1 shows a schema of the first approach. Figure 6.1 – First Approach Framework Adapted from https://www.analyticsvidhya.com …","url":["https://upcommons.upc.edu/bitstream/handle/2117/127682/133741.pdf"]}
-{"year":"2019","title":"Classification of Web History Tools Through Web Analysis","authors":["JRG Evangelista, DD de Oliveira Gatto, RJ Sassi - International Conference on …, 2019"],"snippet":"… 02. Archive.fo. http://archive.fo. 03. CashedPages. http://www.cachedpages. com. 04. CachedView. http://cachedview.com. 05. Common Crawl http://commoncrawl.org. 06. Screenshots.com. http://www.screenshots.com …","url":["https://link.springer.com/chapter/10.1007/978-3-030-22351-9_18"]}
-{"year":"2019","title":"Classifying Pastebin Content Through the Generation of PasteCC Labeled Dataset","authors":["A Riesco, E Fidalgo, MW Al-Nabki, F Jáñez-Martino… - International Conference on …, 2019"],"snippet":"… Panchenko et al. [17] took English text from Common Crawl and constructed a large web-scale corpus using text classification … Panchenko, A., Ruppert, E., Faralli, S., Ponzetto, SP, Biemann, C.: Building a web-scale dependency-parsed corpus from commoncrawl …","url":["https://link.springer.com/chapter/10.1007/978-3-030-29859-3_39"]}
-{"year":"2019","title":"Classifying Websites Using Word Vectors and Other Techniques: An Application of Zipf's Law","authors":["A Robles - 2019"],"snippet":"Page 1. CLASSIFYING WEBSITES USING WORD VECTORS AND OTHER TECHNIQUES: AN APPLICATION OF ZIPF'S LAW A THESIS Presented to the Department of Mathematics and Statistics California State University, Long Beach In Partial Fulfillment …","url":["http://search.proquest.com/openview/7a6b97a2b1aa841198182ea77c38efb6/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2019","title":"Clinical Data Extraction and Normalization of Cyrillic Electronic Health Records Via Deep-Learning Natural Language Processing","authors":["B Zhao - JCO Clinical Cancer Informatics, 2019"],"snippet":"… The medical text in the hematic was modified from the actual patient record for the purposes of illustration. (B) Word embeddings used were fastText embeddings pretrained on Wikipedia and Common Crawl data for English (EN) and Bulgarian (BG) …","url":["https://ascopubs.org/doi/pdfdirect/10.1200/CCI.19.00057"]}
-{"year":"2019","title":"Cloze-driven Pretraining of Self-attention Networks","authors":["A Baevski, S Edunov, Y Liu, L Zettlemoyer, M Auli - arXiv preprint arXiv:1903.07785, 2019"],"snippet":"… We pretrain on individual examples as they oc- cur in the training corpora (§5.1). For News Crawl this is individual sentences while on Wikipedia, Bookcorpus, and Common Crawl examples are paragraph length … Common Crawl …","url":["https://arxiv.org/pdf/1903.07785"]}
-{"year":"2019","title":"ClustCrypt: Privacy-Preserving Clustering of Unstructured Big Data in the Cloud","authors":["SM Zobaed, S Ahmad, R Gottumukkala, MA Salehi"],"snippet":"Page 1. ClustCrypt: Privacy-Preserving Clustering of Unstructured Big Data in the Cloud SM Zobaed∗, Sahan Ahmad∗, Raju Gottumukkala†, and Mohsen Amini Salehi∗ ∗ School of Computing & Informatics †Informatics Research …","url":["https://www.researchgate.net/profile/Mohsen_Salehi2/publication/333561272_ClustCrypt_Privacy-Preserving_Clustering_of_Unstructured_Big_Data_in_the_Cloud/links/5cfaa9f0299bf13a38457fe9/ClustCrypt-Privacy-Preserving-Clustering-of-Unstructured-Big-Data-in-the-Cloud.pdf"]}
-{"year":"2019","title":"CluWords: Exploiting Semantic Word Clustering Representation for Enhanced Topic Modeling","authors":["F Viegas, S Canuto, C Gomes, W Luiz, T Rosa, S Ribas… - Proceedings of the Twelfth …, 2019"],"snippet":"… In this section we compare the proposed CluWords with three pre-trained word em- beddings spaces: (i) Word2Vec trained with GoogleNews [21]; (ii) FastText trained with WikiNews [22] and (iii) Fasttext trained on Common Crawl [22] …","url":["https://dl.acm.org/citation.cfm?id=3291032"]}
-{"year":"2019","title":"CoFiF: A Corpus of Financial Reports in French Language","authors":["T Daudert, S Ahmadi - The First Workshop on Financial Technology and …, 2019"],"snippet":"… com/CoFiF/Corpus [Merity et al., 2016], or CommonCrawl 2. Considering the domain of business and economics, especially for English, corpora such as the Wall Street Journal (WSJ) Corpus [Paul and Baker, 1992], the …","url":["https://www.aclweb.org/anthology/W19-55#page=31"]}
-{"year":"2019","title":"Cognition and the Structure of Bias","authors":["GM Johnson - 2019"],"snippet":"Page 1. UCLA UCLA Electronic Theses and Dissertations Title Cognition and the Structure of Bias Permalink https://escholarship.org/uc/item/7hf582vz Author Johnson, Gabbrielle Michelle Publication Date 2019 Peer reviewed|Thesis/dissertation eScholarship.org …","url":["https://cloudfront.escholarship.org/dist/prd/content/qt7hf582vz/qt7hf582vz.pdf"]}
-{"year":"2019","title":"CogniVal: A Framework for Cognitive Word Embedding Evaluation","authors":["N Hollenstein, A de la Torre, N Langer, C Zhang - arXiv preprint arXiv:1909.09001, 2019"],"snippet":"… et al., 2018). We evaluate the embeddings with and without subword information trained on 16 billion to- kens of Wikipedia sentences as well as the ones trained on 600 billion tokens of Common Crawl. • ELMo models both …","url":["https://arxiv.org/pdf/1909.09001"]}
-{"year":"2019","title":"Collaborative Attention Network with Word and N-Gram Sequences Modeling for Sentiment Classification","authors":["J Bao, L Zhang, B Han - International Conference on Artificial Neural Networks, 2019"],"snippet":"… words in text. In our experiments, we adopt global vectors for word representation (GloVe) [17] in the embedding layer of our model, which consists of 840 billion 300-dimension tokens trained on Common Crawl. We don't use …","url":["https://link.springer.com/chapter/10.1007/978-3-030-30490-4_8"]}
-{"year":"2019","title":"Combating Fake News with Adversarial Domain Adaptation and Neural Models","authors":["B Xu - 2019"],"snippet":"Page 1. Combating Fake News with Adversarial Domain Adaptation and Neural Models by Brian Xu BS, Massachusetts Institute of Technology (2018) Submitted to the Department of Electrical Engineering and Computer Science …","url":["https://groups.csail.mit.edu/sls/publications/2019/BrianXu_MEng-Thesis.pdf"]}
-{"year":"2019","title":"Combining and learning word embedding with WordNet for semantic relatedness and similarity measurement","authors":["YY Lee, H Ke, TY Yen, HH Huang, HH Chen - Journal of the Association for …, 2019"],"snippet":"… ahttps://nlp.stanford.edu/projects/glove/. bhttp://dumps.wikimedia.org/enwiki/20140102/. chttps://catalog.ldc.upenn.edu/LDC2011T07. dThe Common Crawl corpus contains raw web page data, extracted metadata and text extractions. http://commoncrawl.org …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/asi.24289"]}
-{"year":"2019","title":"Comparison of Machine Learning Approaches for Industry Classification Based on Textual Descriptions of Companies","authors":["A Tagarev, N Tulechki, S Boytcheva"],"snippet":"… GloVe vector embeddings are used. Specifically the 300dimensional GloVe vectors trained on the large Common Crawl corpus of 840 billion tokens with a vocabulary of 2.2 million words. While there is no additional training …","url":["https://acl-bg.org/proceedings/2019/RANLP%202019/pdf/RANLP134.pdf"]}
-{"year":"2019","title":"Complex Security Policy? A Longitudinal Analysis of Deployed Content Security Policies","authors":["S Roth, T Barron, S Calzavara, N Nikiforakis, B Stock"],"snippet":"… server response. To determine this IA-specific influence, we chose a second archive service to corroborate the IA's data. In particular, Common Crawl (CC) [10] has been collecting snapshots of popular sites since 2013. For each …","url":["https://swag.cispa.saarland/papers/roth2020csp.pdf"]}
-{"year":"2019","title":"Comprehensive Analysis of Aspect Term Extraction Methods using Various Text Embeddings","authors":["Ł Augustyniak, T Kajdanowicz, P Kazienko - arXiv preprint arXiv:1909.04917, 2019"],"snippet":"… 1. word2vec - protoplast model of any neural word embedding trained on Google News. 2. glove.840B - Global Vectors for Word Representation proposed by Stanford NLP Group, trained based on Common Crawl with …","url":["https://arxiv.org/pdf/1909.04917"]}
-{"year":"2019","title":"Comprehensive trait attributions show that face impressions are organized in four dimensions","authors":["C Lin, U Keles, R Adolphs - 2019"],"snippet":"… we represented each of them with a vector of 300 computationally extracted semantic features (describing word embeddings and text classification) using a state-of-the-art neural network provided within the FastText library (61) …","url":["https://psyarxiv.com/87nex/download?format=pdf"]}
-{"year":"2019","title":"Compressing Inverted Indexes with Recursive Graph Bisection: A Reproducibility Study","authors":["J Mackenzie, A Mallia, M Petri, JS Culpepper, T Suel"],"snippet":"… tool8, – Gov2 is a crawl of .gov domains from 2004, – ClueWeb09 and ClueWeb12 both correspond to the 'B' portion of the 2009 and 2012 ClueWeb crawls of the world wide web, respectively, and – CC-News contains English …","url":["https://jmmackenzie.io/pdf/mm+19-ecir.pdf"]}
-{"year":"2019","title":"Computational Argumentation Synthesis as a Language Modeling Task","authors":["R El Baff, H Wachsmuth, K Al-Khatib, M Stede, B Stein"],"snippet":"Page 1. Computational Argumentation Synthesis as a Language Modeling Task Roxanne El Baff 1 Henning Wachsmuth 2 Khalid Al-Khatib 1 Manfred Stede 3 Benno Stein 1 1 Bauhaus-Universität Weimar, Weimar, Germany …","url":["https://webis.de/downloads/publications/papers/stein_2019y.pdf"]}
-{"year":"2019","title":"Conceptor Debiasing of Word Representations Evaluated on WEAT","authors":["S Karve, L Ungar, J Sedoc - arXiv preprint arXiv:1906.05993, 2019"],"snippet":"… For context-independent embeddings, we used off-the-shelf Fasttext subword embeddings6, which were trained with subword information on the Common Crawl (600B tokens), the GloVe embeddings 7 trained on Wikipedia and …","url":["https://arxiv.org/pdf/1906.05993"]}
-{"year":"2019","title":"Constructing the Wavelet Tree and Wavelet Matrix in Distributed Memory","authors":["P Dinklage, J Fischer, F Kurpicz - 2020 Proceedings of the Twenty-Second Workshop on …"],"snippet":"Page 1. Constructing the Wavelet Tree and Wavelet Matrix in Distributed Memory ∗ Patrick Dinklage † Johannes Fischer† Florian Kurpicz† Abstract The wavelet tree (Grossi et al. [SODA,2003]) is a compact index for texts …","url":["https://epubs.siam.org/doi/abs/10.1137/1.9781611976007.17"]}
-{"year":"2019","title":"Content Similarity Analysis of Written Comments under Posts in Social Media","authors":["M Mozafari, R Farahbakhsh, N Crespi"],"snippet":"… The GloVe vectors were trained from 840 billion tokens of Common Crawl web data and have 300 dimensions [23]. This feature is extracted similar to the Google-word2vec similarity by using equation 6 for each post and comment pair …","url":["http://servicearchitecture.wp.imtbs-tsp.eu/files/2019/09/RC_SNAMS2019_37.pdf"]}
-{"year":"2019","title":"Context Matters: Recovering Human Semantic Structure from Machine Learning Analysis of Large-Scale Text Corpora","authors":["MC Iordan, T Giallanza, CT Ellis, N Beckage, JD Cohen - arXiv preprint arXiv …, 2019"],"snippet":"… We also compared performance of the four Word2Vec embedding spaces to another commonly used embedding space known as GloVe28 for two main reasons; first, the GloVe embeddings are learned from the Common …","url":["https://arxiv.org/pdf/1910.06954"]}
-{"year":"2019","title":"Context-Aware Crosslingual Mapping","authors":["H Aldarmaki, M Diab - arXiv preprint arXiv:1903.03243, 2019"],"snippet":"… data. We trained monolingual ELMo and FastText with de- fault parameters. We used the WMT'13 commoncrawl data for cross-lingual mapping, and the WMT'13 test sets for evaluating sentence translation retrieval. For all …","url":["https://arxiv.org/pdf/1903.03243"]}
-{"year":"2019","title":"Continual Learning for Sentence Representations Using Conceptors","authors":["T Liu, L Ungar, J Sedoc - arXiv preprint arXiv:1904.09187, 2019"],"snippet":"… zero-shot CA. Best results are in boldface and the second best results are underscored. dimensional GloVe vectors (trained on the 840 billion token Common Crawl) (Pennington et al., 2014). Additional experiments with Word2Vec …","url":["https://arxiv.org/pdf/1904.09187"]}
-{"year":"2019","title":"CONTRIBUTIONS TO CLINICAL INFORMATION EXTRACTION IN PORTUGUESE: CORPORA, NAMED ENTITY RECOGNITION, WORD EMBEDDINGS","authors":["FA da Costa Lopes - 2019"],"snippet":"Page 1. Fábio André da Costa Lopes CONTRIBUTIONS TO CLINICAL INFORMATION EXTRACTION IN PORTUGUESE:CORPORA,NAMED ENTITY RECOGNITION,WORD EMBEDDINGS Thesis submitted to the Faculty of Science …","url":["https://www.researchgate.net/profile/Fabio_Lopes17/publication/335639414_Contributions_to_Clinical_Information_Extraction_in_Portuguese_Corpora_Named_Entity_Recognition_Word_Embeddings/links/5d717af2a6fdcc9961b1facd/Contributions-to-Clinical-Information-Extraction-in-Portuguese-Corpora-Named-Entity-Recognition-Word-Embeddings.pdf"]}
-{"year":"2019","title":"Controlling Grammatical Error Correction Using Word Edit Rate","authors":["K Hotate, M Kaneko, S Katsumata, M Komachi - … of the 57th Conference of the …, 2019"],"snippet":"… the lowest WER). In the ranking experiment, we used a 5-gram KenLM (Heafield, 2011) with Kneser-Ney smoothing trained on the web-scale Common Crawl corpus (Junczys-Dowmunt and Grundkiewicz, 2016). As an evaluation …","url":["https://www.aclweb.org/anthology/P19-2020"]}
-{"year":"2019","title":"Conversing by Reading: Contentful Neural Conversation with On-demand Machine Reading","authors":["L Qin, M Galley, C Brockett, X Liu, X Gao, B Dolan… - arXiv preprint arXiv …, 2019"],"snippet":"… informative response. To enable reproducibility of our experiments, we crawled web pages using Common Crawl (http://commoncrawl.org), a service that crawls web pages and makes its historical crawls available to the public. We …","url":["https://arxiv.org/pdf/1906.02738"]}
-{"year":"2019","title":"Correlation Coefficients and Semantic Textual Similarity","authors":["V Zhelezniak, A Savkov, A Shen, NY Hammerla - arXiv preprint arXiv:1905.07790, 2019"],"snippet":"… In all experiments we rely on the following publicly available word embeddings: GloVe (Pennington et al., 2014) trained on Common Crawl (840B tokens), fastText (Bojanowski et al., 2017) trained on Common Crawl …","url":["https://arxiv.org/pdf/1905.07790"]}
-{"year":"2019","title":"Correlations between Word Vector Sets","authors":["V Zhelezniak, A Shen, D Busbridge, A Savkov…"],"snippet":"… For methods involving pretrained word embeddings, we use fastText (Bo- janowski et al., 2017) trained on Common Crawl (600B tokens), as previous evaluations have in- dicated that fastText vectors have uniformly the best …","url":["https://www.april.sh/assets/files/emnlp2019.pdf"]}
-{"year":"2019","title":"Creation of Sentence Embeddings Based on Topical Word Representations","authors":["P Wenig"],"snippet":"Page 1. Topical Sentence Embeddings Creation of Sentence Embeddings Based on Topical Word Representations Phillip Wenig 160361 Master's thesis to obtain the degree of Master of Science in Information Systems University of Liechtenstein …","url":["https://www.researchgate.net/profile/Phillip_Wenig/publication/330761695_Creation_of_Sentence_Embeddings_Based_on_Topical_Word_Representations/links/5c531d44458515a4c74d4719/Creation-of-Sentence-Embeddings-Based-on-Topical-Word-Representations.pdf"]}
-{"year":"2019","title":"Cross-collection Multi-aspect Sentiment Analysis","authors":["H Kaporo - Computer Science On-line Conference, 2019"],"snippet":"… 3.1, we set \\(n=10\\), \\(m=5\\) and run the algorithm over topic-words returned by CPTM and word vectors from glove pre-trained embeddings 2 . These embeddings are trained over common crawl (Google data) and contain 2.2 Million words …","url":["https://link.springer.com/chapter/10.1007/978-3-030-19810-7_11"]}
-{"year":"2019","title":"Cross-Domain Sentiment Classification With Bidirectional Contextualized Transformer Language Models","authors":["B Myagmar, J Li, S Kimura - IEEE Access, 2019"],"snippet":"… For pre-training data, in addition to the BookCorpus and English Wikipedia datasets, cased XLNet-Large model, refered to simply as XLNet henceforth, uses Giga5 (16GB text) [35], ClueWeb 2012-B [36] and Common Crawl [37] as part of its pre-training data …","url":["https://ieeexplore.ieee.org/iel7/6287639/8600701/08894409.pdf"]}
-{"year":"2019","title":"Cross-Layer Optimization of Big Data Transfer Throughput and Energy Consumption","authors":["L Di Tacchio, MDSQZ Nine, T Kosar, MF Bulut… - 2019 IEEE 12th …, 2019"],"snippet":"… The algorithms have been compared using four different datasets: i) a small files dataset, including 20,000 HTML files form the Common Crawl project [1]; ii) a medium files dataset, consisting of 5,000 image files from Flickr …","url":["https://ieeexplore.ieee.org/abstract/document/8814571/"]}
-{"year":"2019","title":"Cross-Lingual Alignment of Word & Sentence Embeddings","authors":["H Aldarmaki - 2019"],"snippet":"Page 1. Cross-Lingual Alignment of Word & Sentence Embeddings by Hanan Aldarmaki B.Sc. in Computer Engineering, May 2008, The American University of Sharjah M.Phil. in Computer Speech, Text, and Internet Technology, May 2009, University of Cambridge …","url":["http://search.proquest.com/openview/97f58b5d99e2ed81065054a170f2dcda/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2019","title":"Cross-lingual Data Transformation and Combination for Text Classification","authors":["J Jiang, S Pang, X Zhao, L Wang, A Wen, H Liu… - arXiv preprint arXiv …, 2019"],"snippet":"… There are word vectors for 157 languages1, trained on Common Crawl and Wikipedia, and these models were trained using CBOW with position-weights, in dimension 300, with character n-grams of length 5, a window size of 5 and 10 negatives …","url":["https://arxiv.org/pdf/1906.09543"]}
-{"year":"2019","title":"Cross-lingual Parsing with Polyglot Training and Multi-treebank Learning: A Faroese Case Study","authors":["J Barry, J Wagner, J Foster - arXiv preprint arXiv:1910.07938, 2019"],"snippet":"… the source languages. We use the precomputed Word2Vec embeddings11 released as part of the 2017 CoNLL shared task on UD parsing (Zeman et al., 2017) which were trained on CommonCrawl and Wikipedia. In order to …","url":["https://arxiv.org/pdf/1910.07938"]}
-{"year":"2019","title":"Cross-Platform Evaluation for Italian Hate Speech Detection","authors":["M Corazza, S Menini, E Cabrio, S Tonelli, S Villata…"],"snippet":"… Generic embeddings: we use embedding spaces obtained directly from the Fasttext website4 for Italian. In particular, we use the Italian embeddings trained on Common Crawl and Wikipedia (Grave et al., 2018) with size 300 …","url":["http://ceur-ws.org/Vol-2481/paper22.pdf"]}
-{"year":"2019","title":"CrossLang: the system of cross-lingual plagiarism detection","authors":["O Bakhteev, A Ogaltsov, A Khazov, K Safin… - 2019"],"snippet":"… They were obtained from open-source parallel OPUS [46] corpora, but also we mine parallel sentences from Common Crawl.4 Algo … the machine translation stage generates texts that differ too much from 3https://tensorflow …","url":["http://ml4ed.cc/attachments/Bakhteev.pdf"]}
-{"year":"2019","title":"CUNI Submission for Low-Resource Languages in WMT News 2019","authors":["T Kocmi, O Bojar - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… Words in English Commoncrawl Russian-English 878k 17.4M 18.8M … Words News crawl 2018 EN 15.4M 344.3M Common Crawl KK 12.5M 189.2M News commentary KK 13.0k 218.7k News crawl Kk 772.9k 10.3M Common Crawl …","url":["https://www.aclweb.org/anthology/W19-5322"]}
-{"year":"2019","title":"CUNI System for the WMT19 Robustness Task","authors":["J Helcl, J Libovický, M Popel - arXiv preprint arXiv:1906.09246, 2019"],"snippet":"… Corpus # Sentences P arallel 109 English-French Corpus 22,520k Europarl 2,007k News Commentary 200k UN Corpus 12,886k Common Crawl 3,224k M onoFrench News Crawl ('08–'14) 37,320k English News Crawl ('11–'17) 127,554k …","url":["https://arxiv.org/pdf/1906.09246"]}
-{"year":"2019","title":"Curriculum Learning for Domain Adaptation in Neural Machine Translation","authors":["X Zhang, P Shapiro, G Kumar, P McNamee, M Carpuat… - arXiv preprint arXiv …, 2019"],"snippet":"… and WMT 2017 (Bojar et al., 2017), which contains data from several domains, eg parliamentary proceedings (Europarl, UN Parallel Corpus), political/economic news (news commentary, Rapid corpus), and …","url":["https://arxiv.org/pdf/1905.05816"]}
-{"year":"2019","title":"Customizing Neural Machine Translation for Subtitling","authors":["E Matusov, P Wilken, Y Georgakopoulou - Proceedings of the Fourth Conference on …, 2019"],"snippet":"… These data included all other publicly available training data, including ParaCrawl, CommonCrawl, EUbookshop, JRCAcquis, EMEA, and other corpora from the OPUS collection … This was done to avoid oversampling …","url":["https://www.aclweb.org/anthology/W19-5209"]}
-{"year":"2019","title":"D-NET: A Simple Framework for Improving the Generalization of Machine Reading Comprehension","authors":["H Li, X Zhang, Y Liu, Y Zhang, Q Wang, X Zhou, J Liu…"],"snippet":"… by introducing two-stream self attention. Besides BooksCorpus and Wikipedia, on which the BERT is trained, XLNET uses more corpus in its pretraining, including Giga5, ClueWeb and Common Crawl. In our system, we use …","url":["https://mrqa.github.io/assets/papers/64_Paper.pdf"]}
-{"year":"2019","title":"Détection automatique de la thématique et adaptation des modèles de langage","authors":["S ZHANG"],"snippet":"Page 1. Si ZHANG SIGMA 2018/2019 AUTHÔT 52Av. Pierre Sémard 94200 Ivry-sur-Seine Détection automatique de la thématique et adaptation des modèles de langage from 01/03/2019 to 16/08/2019 Confidentiality : yes …","url":["ftp://ftp.irit.fr/IRIT/SAMOVA/INTERNSHIPS/zhang_si_2019.pdf"]}
-{"year":"2019","title":"Danish Stance Classification and Rumour Resolution","authors":["AE Lillie, ER Middelboe - arXiv preprint arXiv:1907.01304, 2019"],"snippet":"Page 1. IT University of Copenhagen MSc in Software Development Thesis project KISPECI1SE Danish Stance Classification and Rumour Resolution Authors: Anders E. Lillie aedl@itu.dk Emil R. Middelboe erem@itu.dk …","url":["https://arxiv.org/pdf/1907.01304"]}
-{"year":"2019","title":"Data Augmentation in Deep Learning for Hate Speech Detection in Lower Resource Settings","authors":["M Benk"],"snippet":"Page 1. Masterarbeit zur Erlangung des akademischen Grades Master of Arts der Philosophischen Fakultät der Universität Zürich Data Augmentation in Deep Learning for Hate Speech Detection in Lower Resource Settings …","url":["https://www.cl.uzh.ch/dam/jcr:57406b34-02c8-496d-9b95-9968cee3a134/benk_ma_data_augmentation.pdf"]}
-{"year":"2019","title":"Data4UrbanMobility: Towards Holistic Data Analytics for Mobility Applications in Urban Regions","authors":["N Tempelmeier, Y Rietz, I Lishchuk, T Kruegel… - arXiv preprint arXiv …, 2019"],"snippet":"… Web Event-centric Web markup Annotated Web pages, eg us- ing schema.org. Web Data Commons event subset: 263 × 106 facts until November 2017 Common Crawl ToU RDFa, MicroData Focused crawls Event-centric crawls, news11 …","url":["https://arxiv.org/pdf/1903.12064"]}
-{"year":"2019","title":"Debiasing Embeddings for Reduced Gender Bias in Text Classification","authors":["F Prost, N Thain, T Bolukbasi - Proceedings of the First Workshop on Gender Bias in …, 2019"],"snippet":"… 2 Classification Task This work utilizes the BiosBias dataset introduced in (De-Arteaga et al., 2019). This dataset consists of biographies identified within the Common Crawl 397,340 biographies were extracted from sixteen crawls from 2014 to 2018 …","url":["https://www.aclweb.org/anthology/W19-3810"]}
-{"year":"2019","title":"DebiasingWord Embeddings Improves Multimodal Machine Translation","authors":["T Hirasawa, M Komachi - arXiv preprint arXiv:1905.10464, 2019"],"snippet":"Page 1. Debiasing Word Embeddings Improves Multimodal Machine Translation Tosho Hirasawa Tokyo Metropolitan University hirasawa-tosho@ed.tmu.ac.jp Mamoru Komachi Tokyo Metropolitan University komachi@tmu.ac.jp Abstract …","url":["https://arxiv.org/pdf/1905.10464"]}
-{"year":"2019","title":"Deca: A Garbage Collection Optimizer for In-Memory Data Processing","authors":["X Shi, Z Ke, Y Zhou, H Jin, L Lu, X Zhang, L He, Z Hu… - ACM Transactions on …, 2019"],"snippet":"Page 1. 3 Deca: A Garbage Collection Optimizer for In-Memory Data Processing XUANHUA SHI and ZHIXIANG KE, Huazhong University of Science and Technology, China YONGLUAN ZHOU, University of Copenhagen, Denmark …","url":["https://dl.acm.org/ft_gateway.cfm?id=3310361&type=pdf"]}
-{"year":"2019","title":"DECO: A Dataset of Annotated Spreadsheets for Layout and Table Recognition","authors":["E Koci, M Thiele, J Rehak, O Romero, W Lehner - the 15th IAPR International …, 2019"],"snippet":"… 50 files). The performance is manually assessed per file. 1http://info.nuix.com/Enron. html 2http://commoncrawl.org/ 3http://lemurproject.org/clueweb09.php/ Koci et al. [15] use a dataset of 216 annotated spreadsheets. Unlike …","url":["https://wwwdb.inf.tu-dresden.de/wp-content/uploads/deco_paper.pdf"]}
-{"year":"2019","title":"Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing--A Tale of Two Parsers Revisited","authors":["A Kulmizev, M de Lhoneux, J Gontrum, E Fano, J Nivre - arXiv preprint arXiv …, 2019"],"snippet":"… 2018), who train ELMo on 20 million words randomly sampled from raw WikiDump and Common Crawl datasets for … In other words, while the standalone ELMo models were trained on the tokenized WikiDump and …","url":["https://arxiv.org/pdf/1908.07397"]}
-{"year":"2019","title":"Deep Learning for NLP and Speech Recognition","authors":["U Kamath, J Liu, J Whitaker"],"snippet":"Page 1. Uday Kamath · John Liu · James Whitaker Deep Learning for NLP and Speech Recognition Page 2. Deep Learning for NLP and Speech Recognition Page 3. Uday Kamath • John Liu • James Whitaker Deep …","url":["https://link.springer.com/content/pdf/10.1007/978-3-030-14596-5.pdf"]}
-{"year":"2019","title":"Deep learning for pollen allergy surveillance from twitter in Australia","authors":["J Rong, S Michalska, S Subramani, J Du, H Wang - BMC Medical Informatics and …, 2019"],"snippet":"… embeddings - as alternative. The pre-trained Common Crawl 840B tokens GloVe embeddings were downloaded from the website 2 . Both 50 dimensions (min) and 300 dimensions (max) options were tested. The HF embeddings …","url":["https://link.springer.com/article/10.1186/s12911-019-0921-x"]}
-{"year":"2019","title":"Deep learning models for speech recognition","authors":["A Hannun, C Case, J Casper, B Catanzaro, G DIAMOS… - US Patent App. 16/542,243, 2019"],"snippet":"US20190371298A1 - Deep learning models for speech recognition - Google Patents. Deep learning models for speech recognition. Download PDF Info. Publication number US20190371298A1. US20190371298A1 US16/542,243 …","url":["https://patents.google.com/patent/US20190371298A1/en"]}
-{"year":"2019","title":"Deep Learning vs. Classic Models on a New Uzbek Sentiment Analysis Dataset","authors":["E Kuriyozov, S Matlatipov, MA Alonso…"],"snippet":"… We use as input the FastText pre-trained word embeddings of size 300 (Grave et al., 2018) for Uzbek language, that were created from Wiki pages and CommonCrawl, 9 which, to our knowledge, are the only available pre-trained …","url":["http://www.grupolys.org/biblioteca/KurMatAloGom2019a.pdf"]}
-{"year":"2019","title":"Deep Learning-based Categorical and Dimensional Emotion Recognition for Written and Spoken Text","authors":["BT Atmaja, K Shirai, M Akagi - INA-Rxiv. June, 2019"],"snippet":"… meaning. Glove captured the global corpus statistics from the corpus, for example, a Wikipedia document or a common crawl document. In GloVe model, the cost function is given by V ∑ i,j=1 f(Xi,j)(uT i,jvj + bi + cj − log Xi,j)2 (2) …","url":["https://osf.io/fhu29/download/?format=pdf"]}
-{"year":"2019","title":"Deep Structured Semantic Model for Recommendations in E-commerce","authors":["A Larionova, P Kazakova, N Nikitinsky - International Conference on Hybrid Artificial …, 2019"],"snippet":"… We generated a vector representation for each text by inferring FastText embeddings [4] from their tokens and averaging them (FastText model is pretrained on the Russian language subset of the Common Crawl corpus [10]) …","url":["https://link.springer.com/chapter/10.1007/978-3-030-29859-3_8"]}
-{"year":"2019","title":"Deepening Hidden Representations from Pre-trained Language Models for Natural Language Understanding","authors":["J Yang, H Zhao - arXiv preprint arXiv:1911.01940, 2019","JYH Zhao"],"snippet":"… objective during pre-training on the other hand. In addition to BooksCorpus and English Wikipedia, it also uses Giga5, ClueWeb 2012-B and Common Crawl for pre-training. Trained with dynamic masking, large mini-batches …","url":["https://arxiv.org/pdf/1911.01940","https://deeplearn.org/arxiv/101390/deepening-hidden-representations-from-pre-trained-language-models-for-natural-language-understanding"]}
-{"year":"2019","title":"Defending Against Neural Fake News","authors":["R Zellers, A Holtzman, H Rashkin, Y Bisk, A Farhadi… - arXiv preprint arXiv …, 2019"],"snippet":"… Dataset. We present RealNews, a large corpus of news articles from Common Crawl … Thus, we construct one by scraping dumps from Common Crawl, limiting ourselves to the 5000 news domains indexed by Google News …","url":["https://arxiv.org/pdf/1905.12616"]}
-{"year":"2019","title":"Deliverable 4.2: Data Integration (v. 1)","authors":["A Haller, JD Fernández, A Polleres, MR Kamdar - Work, 2019"],"snippet":"Page 1. Cyber-Physical Social Systems for City-wide Infrastructures Deliverable 4.2: Data Integration (v.1) Authors : Armin Haller, Javier D. Fernández, Axel Polleres, Maulik R. Kamdar Dissemination Level : Public Due date …","url":["http://cityspin.net/wp-content/uploads/2017/10/D4.2-Data-Integration.pdf"]}
-{"year":"2019","title":"Design and implementation of an open source Greek POS Tagger and Entity Recognizer using spaCy","authors":["E Partalidou, E Spyromitros-Xioufis, S Doropoulos… - IEEE/WIC/ACM International …, 2019"],"snippet":"… 3.4 Evaluation and comparison of results In the first experiment the model was trained using pretrained vectors extracted from two different sources, Common Crawl and Wikipedia and can be found at the official FastText …","url":["https://dl.acm.org/citation.cfm?id=3352543"]}
-{"year":"2019","title":"Detecting Aggression and Toxicity using a Multi Dimension Capsule Network","authors":["S Srivastava, P Khurana - Proceedings of the Third Workshop on Abusive …, 2019"],"snippet":"… The code for tokenization was taken from (Devlin et al., 2018) which seems to properly separate the word tokens and special characters. For training all our classification models, we have used fastText embeddings of dimension 300 trained on a common crawl …","url":["https://www.aclweb.org/anthology/W19-3517"]}
-{"year":"2019","title":"Detecting associations between dietary supplement intake and sentiments within mental disorder tweets","authors":["Y Wang, Y Zhao, J Zhang, J Bian, R Zhang - Health Informatics Journal, 2019"],"snippet":"Many patients with mental disorders take dietary supplement, but their use patterns remain unclear. In this study, we developed a method to detect signals of associations between dietary supplement...","url":["https://journals.sagepub.com/doi/full/10.1177/1460458219867231"]}
-{"year":"2019","title":"Detecting Clitics Related Orthographic Errors in Turkish","authors":["U Arıkan, O Güngör, S Uskudarli"],"snippet":"… For this task, GloVe was used with the dimension size of 300 and window size of 15. The pretrained word vectors for Turkish were obtained from the model trained on Common Crawl and Wikipedia using fastText (Grave et al., 2018) …","url":["https://www.researchgate.net/profile/Onur_Guengoer2/publication/337425054_Detecting_Clitics_Related_Orthographic_Errors_in_Turkish/links/5dd7e92792851c1feda68471/Detecting-Clitics-Related-Orthographic-Errors-in-Turkish.pdf"]}
-{"year":"2019","title":"Detecting Hacker Threats: Performance of Word and Sentence Embedding Models in Identifying Hacker Communications","authors":["AL Queiroz, S Mckeever, B Keegan"],"snippet":"… model Source Dim. size MDL-1 SVM WEMB Word2vec Google News 300 MDL-2 SVM WEMB Glove Common Crawl 300 … MDL-4 SVM SEMB InferSent Wikipedia 4096 MDL-5 SVM SEMB SentEncoder Wiki, Web News, SNLI …","url":["http://aics2019.datascienceinstitute.ie/papers/aics_13.pdf"]}
-{"year":"2019","title":"Detecting Incivility and Impoliteness in Online Discussions. Classification Approaches for German User Comments.","authors":["A Stoll, M Ziegele, O Quiring - 2019"],"snippet":"Page 1. DETECTING INCIVILITY AND IMPOLITENESS Preprint on SSRN, 22.11.2019 Anke Stoll HHU Düsseldorf anke.stoll@hhu.de Marc Ziegele HHU Düsseldorf marc.ziegele@hhu.de Oliver Quiring JGU Main quiring@uni-mainz.de ABSTRACT …","url":["https://osf.io/preprints/socarxiv/a47ch/download"]}
-{"year":"2019","title":"Detecting offensive language using transfer learning","authors":["A de Bruijn, V Muhonen, T Albinonistraat, W Fokkink… - 2019"],"snippet":"Page 1. Detecting offensive language using transfer learning Alissa de Bruijn September 2019 Page 2. Master Thesis Business Analytics Detecting offensive language using transfer learning Author: Alissa de Bruijn …","url":["https://beta.vu.nl/nl/Images/stageverslag-bruijn_tcm235-926516.pdf"]}
-{"year":"2019","title":"Detecting Relational States in Online Social Networks","authors":["J Zhang, L Tan, X Tao, T Pham, X Zhu, H Li, L Chang - 2018 5th International …, 2019"],"snippet":"… Since the social network we obtain from the repositories of common crawl contains missing links and partial information, stochastic estimations are used to measure the accuracy and reliability of our experimental MVVA results [19] …","url":["https://ieeexplore.ieee.org/abstract/document/8697237/"]}
-{"year":"2019","title":"Detecting Topic-Oriented Speaker Stance in Conversational Speech}}","authors":["C Lai, B Alex, JD Moore, L Tian, T Hori, G Francesca - Proc. Interspeech 2019, 2019"],"snippet":"… 3.3. Lexical Features We build lexical representations over turns and topic segments using 300 dimensional GloVe word embeddings (Common Crawl, 840B tokens) [26]. We perform basic tokenization to map between the CallHome transcripts and word embeddings …","url":["https://www.isca-speech.org/archive/Interspeech_2019/pdfs/2632.pdf"]}
-{"year":"2019","title":"Detection of contradictions in pairs of texts in Kazakh","authors":["Y Yamalutdinova - 2019"],"snippet":"Page 1. BACHELOR THESIS Yuliya Yamalutdinova Detection of contradictions in pairs of texts in Kazakh Institute of Formal and Applied Linguistics Supervisor of the bachelor thesis: Mgr. Rudolf Rosa, Ph.D. Study programme: Computer Science …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/109076/130266752.pdf?sequence=1"]}
-{"year":"2019","title":"Determining How Citations Are Used in Citation Contexts","authors":["M Färber, A Sampath - International Conference on Theory and Practice of …, 2019"],"snippet":"… 2. See https://fasttext.cc/. The pretrained vectors were trained on Common Crawl and Wikipedia using the CBOW model of fastText. fastText operates at the character level, and therefore can generate vectors for words not seen in the training corpus …","url":["https://link.springer.com/chapter/10.1007/978-3-030-30760-8_38"]}
-{"year":"2019","title":"Development of a Song Lyric Corpus for the English Language","authors":["MAG Rodrigues, A de Paiva Oliveira, A Moreira - International Conference on …, 2019"],"snippet":"… languages. According to the authors, the texts that compose the corpus were extracted from CommonCrawl (commoncrawl.org), the largest publicly available general Web crawl to date with about 2 billion crawled URLs. The …","url":["https://link.springer.com/chapter/10.1007/978-3-030-23281-8_33"]}
-{"year":"2019","title":"Development of an End-to-End Deep Learning Pipeline","authors":["M Nitsche, S Halbritter"],"snippet":"Page 1. Development of an End-to-End Deep Learning Pipeline Matthias Nitsche, Stephan Halbritter {matthias.nitsche, stephan.halbritter}@hawhamburg.de Hamburg University of Applied Sciences, Department of …","url":["https://users.informatik.haw-hamburg.de/~ubicomp/projekte/master2019-proj/nitsche-halbritter.pdf"]}
-{"year":"2019","title":"Digital audio track suggestions for moods identified using analysis of objects in images from video content","authors":["N Brochu - US Patent App. 15/392,705, 2019"],"snippet":"… the response from the natural language model 240. Exemplary training corpuses of words can include, for example, Common Crawl (eg, 840B tokens, 2.2M vocabulary terms). The natural language model 240 can be improved …","url":["http://www.freepatentsonline.com/10276189.html"]}
-{"year":"2019","title":"Diversicon: Pluggable Lexical Domain Knowledge","authors":["G Bella, F McNeill, D Leoni, FJQ Real, F Giunchiglia - Journal on Data Semantics, 2019"],"snippet":"Page 1. Journal on Data Semantics https://doi.org/10.1007/s13740-019-00107-1 ORIGINAL ARTICLE Diversicon: Pluggable Lexical Domain Knowledge Gábor Bella1 · Fiona McNeill2 · David Leoni1 · Francisco José Quesada Real3 · Fausto Giunchiglia1 …","url":["https://link.springer.com/article/10.1007/s13740-019-00107-1"]}
-{"year":"2019","title":"Do It Like a Syntactician: Using Binary Gramaticality Judgements to Train Sentence Encoders and Assess Their Sensitivity to Syntactic Structure","authors":["P Gonzalez Martinez - 2019"],"snippet":"Page 1. City University of New York (CUNY) CUNY Academic Works Dissertations, Theses, and Capstone Projects Graduate Center 9-2019 Do It Like a Syntactician: Using Binary Gramaticality Judgements to Train …","url":["https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=4521&context=gc_etds"]}
-{"year":"2019","title":"Do It Like a Syntactician: Using Binary Grammaticality Judgements to Train Sentence Encoders and Assess Their Sensitivity to Syntactic Structure","authors":["PG Martinez - 2019"],"snippet":"Page 1. Do it like a syntactician: using binary grammaticality judgments to train sentence encoders and assess their sensitivity to syntactic structure by Pablo González Mart´ınez A dissertation submitted to the Graduate Faculty in Linguistics in partial fulfillment of the …","url":["http://search.proquest.com/openview/f9bad35a6cc78921f32a9f8f6e0efde3/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2019","title":"Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?","authors":["I Vulić, G Glavaš, R Reichart, A Korhonen - arXiv preprint arXiv:1909.01638, 2019"],"snippet":"… Monolingual Embeddings. We use the 300-dim vectors of Grave et al. (2018) for all 15 languages, pretrained on Common Crawl and Wikipedia with fastText (Bojanowski et al., 2017).7 We trim all 5While BLI is an intrinsic task, as discussed by Glavaš et al …","url":["https://arxiv.org/pdf/1909.01638"]}
-{"year":"2019","title":"Document Embedding Models on Environmental Legal Documents","authors":["S Kralj, Ž Urbancic, E Novak, K Kenda"],"snippet":"… Instead of having aa large vocabulary of pre-computed word embeddings trained on Wikipedia and Common Crawl, this newly trained model is trained on documents from a more specific domain - resulting in a vocabulary …","url":["http://ailab.ijs.si/dunja/SiKDD2019/Papers/Kralj_Urbancic_Final.pdf"]}
-{"year":"2019","title":"Document Summarization Using Sentence-Level Semantic Based on Word Embeddings","authors":["K Al-Sabahi, Z Zuping - International Journal of Software Engineering and …, 2019"],"snippet":"… Training is performed on aggregated global word-word co-occurrence statistics from a corpus. In this work, we use the one trained on Common Crawl (840B tokens, 2.2M vocab, cased, 300d vectors, 2.03 GB download): glove.840B. 300d.zip …","url":["https://www.worldscientific.com/doi/abs/10.1142/S0218194019500086"]}
-{"year":"2019","title":"Domain adaptation for part-of-speech tagging of noisy user-generated text","authors":["L März, D Trautmann, B Roth - arXiv preprint arXiv:1905.08920, 2019"],"snippet":"… The pretrained vectors for German are based on Wikipedia articles and data from Common Crawl3. We obtain 97.988 different embeddings for the tokens in TIGER and the Twitter corpus of which 75.819 were already contained …","url":["https://arxiv.org/pdf/1905.08920"]}
-{"year":"2019","title":"Domain-specific word embeddings for patent classification","authors":["J Risch, R Krestel - Data Technologies and Applications, 2019"],"snippet":"… used to train word embeddings. It contains more than twice the number of tokens of the English Wikipedia (16bn) and is only exceeded by the Common Crawl data set, which consists of 600bn tokens. We assume that the embeddings …","url":["https://www.emeraldinsight.com/doi/abs/10.1108/DTA-01-2019-0002"]}
-{"year":"2019","title":"Dual Monolingual Cross-Entropy Delta Filtering of Noisy Parallel Data","authors":["A Axelrod, A Kumar, S Sloto - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… gual English corpus comparable in size and content to the Sinhala one by randomly selecting 150k lines from Wikipedia and 6M lines from Common Crawl … Each SentencePiece model was trained on 1M lines of monolin …","url":["https://www.aclweb.org/anthology/W19-5433"]}
-{"year":"2019","title":"Dynamic Packed Compact Tries Revisited","authors":["K Tsuruta, D Köppl, S Kanda, Y Nakashima, S Inenaga… - arXiv preprint arXiv …, 2019"],"snippet":"… name column. • commoncrawl is a web crawl containing the ASCII-encoded content (without HTML tags) of random web pages extracted from Common Crawl. • vital is the main text extracted from the most vital Wikipedia articles …","url":["https://arxiv.org/pdf/1904.07467"]}
-{"year":"2019","title":"Dynamically Route Hierarchical Structure Representation to Attentive Capsule for Text Classification","authors":["W Zheng, Z Zheng, H Wan, C Chen"],"snippet":"Page 1. Dynamically Route Hierarchical Structure Representation to Attentive Capsule for Text Classification Wanshan Zheng1,2 , Zibin Zheng1,2 , Hai Wan1 , Chuan Chen1,2 1School of Data and Computer Science, Sun Yat …","url":["https://www.ijcai.org/proceedings/2019/0759.pdf"]}
-{"year":"2019","title":"EasyChair Preprint","authors":["NS Resolution - 2019"],"snippet":"… Fancellu et al. (2016) show in their work that Page 4. Crawl data set with 840B tokens. Additionally we will try 300-dimensional pre-trained fastText2 that were also trained on Common Crawl but on a subset of 600B tokens. This differs from Fancellu et al …","url":["https://easychair.org/publications/preprint_download/QHml"]}
-{"year":"2019","title":"EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks","authors":["JW Wei, K Zou - arXiv preprint arXiv:1901.11196, 2019"],"snippet":"… We suspect that EDA will work with any thesaurus. Word embeddings. We use 300-dimensional Common-Crawl word embeddings trained using GloVe (Pennington et al., 2014). We suspect that EDA will work with any pre-trained word embeddings. CNN …","url":["https://arxiv.org/pdf/1901.11196"]}
-{"year":"2019","title":"Edge Computing for User-Centric Secure Search on Cloud-Based Encrypted Big Data","authors":["S Ahmad, SM Zobaed, R Gottumukkala, MA Salehi - arXiv preprint arXiv:1908.03668, 2019"],"snippet":"… We used two datasets, namely Amazon Common Crawl Corpus (ACCC) [35] and Request For Comments (RFC) [36], that have distinct characteristics and volumes. ACCC is ≈ 150 terabytes, contains web contents, and is not domain-specific …","url":["https://arxiv.org/pdf/1908.03668"]}
-{"year":"2019","title":"EDUCE: Explaining model Decisions through Unsupervised Concepts Extraction","authors":["D Bouchacourt, L Denoyer - arXiv preprint arXiv:1905.11852, 2019"],"snippet":"… We test on the full test dataset composed of 7, 600 samples. We use pre-trained word vectors trained on Common Crawl [8], and keep them fixed … We use pre-trained word vectors trained on Common Crawl [8], and keep them fixed …","url":["https://arxiv.org/pdf/1905.11852"]}
-{"year":"2019","title":"Efficient Classification and Unsupervised Keyphrase Extraction for Web Pages","authors":["T Haarman - 2019"],"snippet":"Page 1. MASTER'S THESIS Efficient Classification and Unsupervised Keyphrase Extraction for Web Pages Tim Haarman s2404184 Department of Artificial Intelligence University of Groningen, The Netherlands Primary …","url":["https://www.ai.rug.nl/~mwiering/Thesis_Tim_Haarman.pdf"]}
-{"year":"2019","title":"Efficient Contextual Representation Learning With Continuous Outputs","authors":["LH Li, PH Chen, CJ Hsieh, KW Chang - Transactions of the Association for …, 2019"],"snippet":"Create a new account. Email. Returning user. Can't sign in? Forgot your password? Enter your email address below and we will send you the reset instructions. Email. Cancel. If the address matches an existing account you will …","url":["https://www.mitpressjournals.org/doi/full/10.1162/tacl_a_00289"]}
-{"year":"2019","title":"Efficient Contextual Representation Learning Without Softmax Layer","authors":["LH Li, PH Chen, CJ Hsieh, KW Chang - arXiv preprint arXiv:1902.11269, 2019"],"snippet":"… The output layer is a sampled softmax with 8192 negative samples per batch. This model is provided in AllenNLP by Peters et al. (2018a). • ELMO-S: The input layer is the FastText embedding trained on Common Crawl (Mikolovetal …","url":["https://arxiv.org/pdf/1902.11269"]}
-{"year":"2019","title":"Efficient Sentence Embedding using Discrete Cosine Transform","authors":["N Almarwani, H Aldarmaki, M Diab - arXiv preprint arXiv:1909.03104, 2019"],"snippet":"… CoordInv Coordination Inversion Table 1: Probing Tasks 3.2 Experimental setup For the word embeddings, we use pre-trained FastText embeddings of size 300 (Mikolov et al., 2018) trained on Common-Crawl. We generate DCT …","url":["https://arxiv.org/pdf/1909.03104"]}
-{"year":"2019","title":"Embedding Imputation with Grounded Language Information","authors":["Z Yang, C Zhu, V Sachidananda, E Darve - arXiv preprint arXiv:1906.03753, 2019"],"snippet":"… KG2Vec 0.02% 7% 0.04% 12% 58.6 56.9 60.1 54.3 GloVe Common Crawl 1% 29% 2% 44% 44.0 33.0 45.1 27.3 … We test on two types of pre-trained word vectors GloVe (Common crawl, cased 300d) and ConceptNet Numberbatch (300d) …","url":["https://arxiv.org/pdf/1906.03753"]}
-{"year":"2019","title":"EmbNum+: Effective, Efficient, and Robust Semantic Labeling for Numerical Values","authors":["P Nguyen, K Nguyen, R Ichise, H Takeda - New Generation Computing, 2019"],"snippet":"… Data portals. For example, 233 million tables were extracted from the July 2015 version of the Common Crawl [10].1 Additionally, 200,000 tables from 232 Open Data portals were analyzed by Mitlohner et al. [12]. These resources …","url":["https://link.springer.com/article/10.1007/s00354-019-00076-w"]}
-{"year":"2019","title":"Emerging Cross-lingual Structure in Pretrained Language Models","authors":["A Conneau, S Wu, H Li, L Zettlemoyer, V Stoyanov - … of the 58th Annual Meeting of …, 2020","S Wu, A Conneau, H Li, L Zettlemoyer, V Stoyanov - arXiv preprint arXiv:1911.01464, 2019"],"snippet":"… We consider domain difference by training on Wikipedia for English and a random subset of Common Crawl of the same size for the other languages (Wiki-CC). We also consider a model trained with Wikipedia only, the same as XLM (Default) for comparison …","url":["https://arxiv.org/pdf/1911.01464","https://www.aclweb.org/anthology/2020.acl-main.536.pdf"]}
-{"year":"2019","title":"Emoji Powered Capsule Network to Detect Type and Target of Offensive Posts in Social Media","authors":["H Hettiarachchi, T Ranasinghe"],"snippet":"… Also character embeddings handle in- frequent words better than word2vec embedding as later one suffers from lack of enough training opportunity for those rare words. We used fasttext embeddings pre trained on Common Crawl (Mikolov et al., 2018) …","url":["https://www.researchgate.net/profile/Tharindu_Ranasinghe2/publication/336775156_Emoji_Powered_Capsule_Network_to_Detect_Type_and_Target_of_Offensive_Posts_in_Social_Media/links/5db1a79992851c577eba8219/Emoji-Powered-Capsule-Network-to-Detect-Type-and-Target-of-Offensive-Posts-in-Social-Media.pdf"]}
-{"year":"2019","title":"EmoLabel: Semi-Automatic Methodology for Emotion Annotation of Social Media Text","authors":["L Canales, W Daelemans, E Boldrini, P Martínez-Barco - IEEE Transactions on …, 2019"],"snippet":"Page 1. 1949-3045 (c) 2019 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/8758380/"]}
-{"year":"2019","title":"EMOMINER at SemEval-2019 Task 3: A Stacked BiLSTM Architecture for Contextual Emotion Detection in Text","authors":["N Chakravartula, V Indurthi - Proceedings of the 13th International Workshop on …, 2019"],"snippet":"… them with GloVe vectors. As a result, Glove vectors will have syntactic information of words (Rezaeinia et al., 2017). 3.2 Feature Extraction • Word Embeddings: Glove840B - common crawl (Pennington et al., 2014) pre-trained …","url":["https://www.aclweb.org/anthology/S19-2033"]}
-{"year":"2019","title":"Emotional Embeddings: Refining Word Embeddings to Capture Emotional Content of Words","authors":["A Seyeditabari, N Tabari, S Gholizadeh, W Zadrozny - arXiv preprint arXiv …, 2019"],"snippet":"… vector spaces used here are: • Word2Vec trained full English Wikipedia dump • GloVe from their own website • fastText trained with subword information on Common Crawl • ConceptNet Numberbatch It is clear that each emotionally …","url":["https://arxiv.org/pdf/1906.00112"]}
-{"year":"2019","title":"Encoder-Decoder Network with Cross-Match Mechanism for Answer Selection","authors":["Z Xie, X Yuan, J Wang, S Ju - China National Conference on Chinese Computational …, 2019"],"snippet":"… 4.2 Implementation Details. We initialized word embedding with 300d-GloVe vectors pre-trained from the 840B Common Crawl corpus [8], while the word embeddings for the out-of-vocabulary words were initialized randomly …","url":["https://link.springer.com/chapter/10.1007/978-3-030-32381-3_6"]}
-{"year":"2019","title":"End-to-End Learning of Co-Speech Gesture Generation for Humanoid Robots","authors":["Y Yoon, WR Ko, M Jang, J Lee, J Kim"],"snippet":"… We used the pretrained word embedding model GloVe, trained on the Common Crawl corpus [5]. The dimension of word embedding is 300, and a zero vector is used for unknown words. A gesture is represented as a sequence of human poses …","url":["http://robotics.auckland.ac.nz/wp-content/uploads/2018/06/Final_ETRI_YoungwooYoon.pdf"]}
-{"year":"2019","title":"End-to-end Neural Information Retrieval","authors":["W Yang - 2019"],"snippet":"Page 1. End-to-end Neural Information Retrieval by Wei Yang A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master in Computer Science Waterloo, Ontario, Canada, 2019 c Wei Yang 2019 Page 2 …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/14597/Yang_Wei.pdf?sequence=4&isAllowed=y"]}
-{"year":"2019","title":"End-to-End Speech Recognition","authors":["U Kamath, J Liu, J Whitaker - Deep Learning for NLP and Speech Recognition, 2019"],"snippet":"… of certain words. Therefore, an n-gram language model was trained using the KenLM [Hea+ 13] toolkit on the Common Crawl Repository, 1 using the 400,000 most frequent words from 250 million lines of text. The decoding …","url":["https://link.springer.com/chapter/10.1007/978-3-030-14596-5_12"]}
-{"year":"2019","title":"English-Czech Systems in WMT19: Document-Level Transformer","authors":["M Popel, D Macháček, M Auersperger, O Bojar… - arXiv preprint arXiv …, 2019"],"snippet":"… brevity. sentence words (k) data set pairs (k) EN CS CzEng 1.7 57 065 618 424 543 184 Europarl v7 647 15 625 13 000 News Commentary v12 211 4 544 4 057 CommonCrawl 162 3 349 2 927 WikiTitles 361 896 840 EN NewsCrawl …","url":["https://arxiv.org/pdf/1907.12750"]}
-{"year":"2019","title":"Enhancing AMR-to-Text Generation with Dual Graph Representations","authors":["LFR Ribeiro, C Gardent, I Gurevych - arXiv preprint arXiv:1909.00352, 2019"],"snippet":"… 5 Experiments and Discussion Implementation Details We extract vocabularies (size of 20,000) from the training sets and initialize the node embeddings from GloVe word em- beddings (Pennington et al., 2014) on Common Crawl …","url":["https://arxiv.org/pdf/1909.00352"]}
-{"year":"2019","title":"Enhancing Semantic Word Representations by Embedding Deeper Word Relationships","authors":["A Nugaliyadde, KW Wong, F Sohel, H Xie - arXiv preprint arXiv:1901.07176, 2019"],"snippet":"… 2 https://commoncrawl.org/ differentiating similarity from association and relatedness which is reflected in table 1. The context to create the word embedding in order to test on SimLex-999 is created based on Common …","url":["https://arxiv.org/pdf/1901.07176"]}
-{"year":"2019","title":"Environmental hazards, rigid institutions, and transformative change: How drought affects the consideration of water and climate impacts in infrastructure management","authors":["N Ulibarri, TA Scott - Global Environmental Change, 2019"],"snippet":"Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0959378019302213"]}
-{"year":"2019","title":"eTranslation's Submissions to the WMT 2019 News Translation Task","authors":["C Oravecz, K Bontcheva, A Lardilleux, L Tihanyi… - Proceedings of the Fourth …, 2019"],"snippet":"… En→De the reduction in ParaCrawl was from 31M to 18M segments and in CommonCrawl from 2.3M to 1.4M segments with a drop of 0.2 BLEU points compared to us- ing the full sets3. No additional cleaning was ap- plied to …","url":["https://www.aclweb.org/anthology/W19-5334"]}
-{"year":"2019","title":"Europarl-ST: A Multilingual Corpus For Speech Translation Of Parliamentary Debates","authors":["J Iranzo-Sánchez, JA Silvestre-Cerdà, J Jorge… - arXiv preprint arXiv …, 2019"],"snippet":"… De↔Fr eubookshop, JRC-Acquis, 14.3 TildeModel En↔Es commoncrawl, eubookshop, 21.1 EU-TT2, UN, Wikipedia En↔Fr commoncrawl, giga, 38.2 undoc, news-commentary Es↔Fr DGT, eubookshop, 37.2 JRC-Acquis, UNPC …","url":["https://arxiv.org/pdf/1911.03167"]}
-{"year":"2019","title":"Evaluating Commonsense in Pre-trained Language Models","authors":["X Zhou, Y Zhang, L Cui, D Huang - arXiv preprint arXiv:1911.11931, 2019"],"snippet":"… Note that XLNet-base is trained with the same data as BERT, while XLNet-large is trained with a larger dataset that consists of 32.98B subword pieces coming from Wiki, BookCorpus, Giga5, ClueWeb, and Common Crawl. RoBERTa (Liu et al …","url":["https://arxiv.org/pdf/1911.11931"]}
-{"year":"2019","title":"Evaluating KGR10 Polish word embeddings in the recognition of temporal expressions using BiLSTM-CRF.","authors":["J Kocoń, M Gawor - arXiv preprint arXiv:1904.04055, 2019"],"snippet":"… The second one, called FASTTEXT4, is original FastText word embeddings set, created for 157 languages (including Polish). Authors used Wikipedia and Common Crawl5 as the linguistic data source … C2 Common Crawl …","url":["https://arxiv.org/pdf/1904.04055"]}
-{"year":"2019","title":"Evaluating the Supervised and Zero-shot Performance of Multi-lingual Translation Models","authors":["C Hokamp, J Glover, D Gholipour - arXiv preprint arXiv:1906.09675, 2019"],"snippet":"… We use all available parallel data from the WMT19 news-translation task for training, with the exception of commoncrawl, which we found to be very noisy after manually checking a sample of the data, and paracrawl, which …","url":["https://arxiv.org/pdf/1906.09675"]}
-{"year":"2019","title":"Evaluation of basic modules for isolated spelling error correction in Polish texts","authors":["S Rutkowski - arXiv preprint arXiv:1905.10810, 2019"],"snippet":"… How this representation is constructed is informed by the whole corpus on which the embedder was trained. The pretrained ELMo model that we used (Che et al., 2018) was trained on Wikipedia and Common Crawl corpora of Polish …","url":["https://arxiv.org/pdf/1905.10810"]}
-{"year":"2019","title":"Evaluation of Czech Distributional Thesauri","authors":["P Rychlý - RASLAN 2019 Recent Advances in Slavonic Natural …, 2019"],"snippet":"… The results are summarized in Table 2. The czTenTen12 corpus was evaluated with Sketch Engine thesaurus and also with word vectors compiled by FastText. We have also included prebuild model from Common Crawl. Table …","url":["http://raslan2019.nlp-consulting.net/proceedings/raslan19.pdf#page=145","https://nlp.fi.muni.cz/raslan/raslan19.pdf#page=145"]}
-{"year":"2019","title":"Evaluation of State Of Art Open-source ASR Engines with Local Inferencing","authors":["B Rizk"],"snippet":"Page 1. Institute Of Information Systems (iisys) Hof University in exchange for Media Engineering and Technology Faculty German University in Cairo Evaluation of State Of Art Open-source ASR Engines with Local …","url":["https://www.researchgate.net/profile/Basem_Rizk/publication/335524542_Evaluation_of_State_Of_Art_Open-source_ASR_Engines_with_Local_Inferencing/links/5d6aa4ae299bf1808d5c87dd/Evaluation-of-State-Of-Art-Open-source-ASR-Engines-with-Local-Inferencing.pdf"]}
-{"year":"2019","title":"Evaluation of vector embedding models in clustering of text documents","authors":["T Walkowiak, M Gniewkowski"],"snippet":"… The second group of sources of word2vec models for Polish are web pages of word embedding tools like fastText, ELMo and BERT. They were trained on Polish Common Crawl and Wikipedia. However, the BERT …","url":["https://acl-bg.org/proceedings/2019/RANLP%202019/pdf/RANLP149.pdf"]}
-{"year":"2019","title":"Event-Argument Linking in Hindi for Information Extraction in Disaster Domain","authors":["SK Sahoo, S Saha, A Ekbal, P Bhattacharyya…"],"snippet":"… 3.3 Word Embedding For word embedding (WE) of each word, we use pre-trained fastText [5] word vectors. These embeddings were trained on Hindi Common Crawl and Wikipedia dataset. The size of the word embedding used in our experiments is 300 …","url":["https://www.iitp.ac.in/~ai-nlp-ml/papers/Sovan_CICLing_2019.pdf"]}
-{"year":"2019","title":"Evolution of the PAN Lab on Digital Text Forensics","authors":["P Rosso, M Potthast, B Stein, E Stamatatos, F Rangel… - … Retrieval Evaluation in a …, 2019"],"snippet":"… The static web search environment is comprised of the web search engine ChatNoir, which indexes the ClueWeb 2009, the ClueWeb 2012, and (as of 2017) the CommonCrawl, delivering search results in milliseconds while …","url":["https://link.springer.com/chapter/10.1007/978-3-030-22948-1_19"]}
-{"year":"2019","title":"Example-Driven Question Answering","authors":["D Wang - 2019"],"snippet":"Page 1. August 19, 2019 DRAFT Example-Driven Question Answering Di Wang August 2019 School of Computer Science Carnegie Mellon University Pittsburgh, PA 15213 Thesis Committee: Eric Nyberg (chair) (Carnegie Mellon …","url":["http://www.cs.cmu.edu/~diw1/thesis.pdf"]}
-{"year":"2019","title":"Explicit Discourse Argument Extraction for German","authors":["P Bourgonje, M Stede - International Conference on Text, Speech, and …, 2019"],"snippet":"… The word embeddings are trained on Common Crawl and Wikipedia [6]. We generated the part-of-speech embeddings from the TIGER corpus [4]. We use a CNN with four fully connected layers. Training this on all classes from Table 1 results in an accuracy of 94.52 …","url":["https://link.springer.com/chapter/10.1007/978-3-030-27947-9_3"]}
-{"year":"2019","title":"Exploitation vs. exploration—computational temporal and semantic analysis explains semantic verbal fluency impairment in Alzheimer's disease","authors":["J Tröger, N Linz, A König, P Robert, J Alexandersson… - Neuropsychologia, 2019"],"snippet":"… For deriving semantic metrics, the semantic distance between produced words was calculated based on a fastText (Joulin et al., 2016) neural word embedding, pre-trained on the French Common Crawl and Wikipedia corpora (Grave et al., 2018; Linz et al., 2017) …","url":["https://www.sciencedirect.com/science/article/pii/S0028393218305116"]}
-{"year":"2019","title":"Exploiting EuroVoc's Hierarchical Structure for Classifying Legal Documents","authors":["E Filtz, S Kirrane, A Polleres, G Wohlgenannt - … \" On the Move to Meaningful Internet …, 2019","G Wohlgenannt - On the Move to Meaningful Internet Systems: OTM …"],"snippet":"… First, we tested large-scale pre-trained language models trained with generalpurpose text corpora such as GoogleNews and the CommonCrawl, but as expected both performed badly on the legal dataset, for example the Common …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=hm21DwAAQBAJ&oi=fnd&pg=PA164&dq=commoncrawl&ots=pdUzWNZpkR&sig=nBv58MNJuj5jkkROfHpNIYLbyTs","https://link.springer.com/chapter/10.1007/978-3-030-33246-4_10"]}
-{"year":"2019","title":"Exploiting knowledge graphs for entity-centric prediction","authors":["S Jiang - 2018"],"snippet":"Page 1. © 2018 Shan Jiang Page 2. EXPLOITING KNOWLEDGE GRAPHS FOR ENTITY-CENTRIC PREDICTION BY SHAN JIANG DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of …","url":["https://www.ideals.illinois.edu/bitstream/handle/2142/102463/JIANG-DISSERTATION-2018.pdf?sequence=1"]}
-{"year":"2019","title":"Exploiting Temporal Relationships in Video Moment Localization with Natural Language","authors":["S Zhang, J Su, J Luo - arXiv preprint arXiv:1908.03846, 2019"],"snippet":"… extracted from VGG [24] fc7 layer, optical flow features are extracted from the penultimate layer [27] and the 300-d Glove feature [21] pretrained on Common Crawl (42 billion tokens) are used as the word embedding. The segment …","url":["https://arxiv.org/pdf/1908.03846"]}
-{"year":"2019","title":"Exploiting the Hierarchical Structure of a Thesaurus for Document Classification","authors":["E Filtz, S Kirrane, A Polleres, G Wohlgenannt"],"snippet":"… First, we tested large-scale pre-trained language models trained with generalpropose text corpora such as GoogleNews and the CommonCrawl, but as ex- pected both performed badly on the legal dataset, for example the …","url":["https://aic.ai.wu.ac.at/~polleres/publications/filt-etal-2019COOPIS.pdf"]}
-{"year":"2019","title":"Explore FREDDY","authors":["M Günther, M Thiele, W Lehner, Z Yanakiev - BTW 2019, 2019"],"snippet":"… The configuration of the search function is defined in the sidebar (Figure 3b) just as in the query view. 4 Screencast on our FREDDY website https://wwwdb.inf.tu-dresden.de/research-projects/freddy/ 5 https://dblp.uni …","url":["https://dl.gi.de/bitstream/handle/20.500.12116/21558/E08-1.pdf?sequence=1&isAllowed=y"]}
-{"year":"2019","title":"Explore FREDDY: Fast Word Embeddings in Database Systems","authors":["M Günther, Z Yanakiev, M Thiele, W Lehner"],"snippet":"… The configuration of the search function is defined in the sidebar (Figure 3b) just as in the query view. 4 Screencast on our FREDDY website https://wwwdb.inf.tu-dresden.de/research-projects/freddy/ 5 https://dblp.uni …","url":["https://btw.informatik.uni-rostock.de/download/tagungsband/E08-1.pdf"]}
-{"year":"2019","title":"Exploring Numeracy in Word Embeddings","authors":["A Naik, A Ravichander, C Rose, E Hovy - Proceedings of the 57th Conference of the …, 2019"],"snippet":"… FastText (Bojanowski et al., 2017): Extended Skipgram model representing words as character n-grams to incorporate sub-word information. We evaluate Wikipedia and Common Crawl variants. 3.1 Retrained Word Vectors …","url":["https://www.aclweb.org/anthology/P19-1329"]}
-{"year":"2019","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","authors":["C Raffel, N Shazeer, A Roberts, K Lee, S Narang… - arXiv preprint arXiv …, 2019"],"snippet":"… unsupervised pre-training for NLP is particularly attractive because unlabeled text data is available en masse thanks to the Internet – for example, the Common Crawl project2 produces about 20TB of text data extracted from web pages each month …","url":["https://arxiv.org/pdf/1910.10683"]}
-{"year":"2019","title":"Extending Cross-Domain Knowledge Bases with Long Tail Entities using Web Table Data","authors":["Y Oulabi, C Bizer - genre, 2019"],"snippet":"… In a second experiment, we apply the system to a large corpus of web tables extracted from the Common Crawl. This experiment allows us to get an overall im- pression of the potential of web tables for augmenting knowledge bases with long tail entities …","url":["https://www.uni-mannheim.de/media/Einrichtungen/dws/Files_Research/Web-based_Systems/pub/OulabiBizer-LongTailEntities-EDBT2019.pdf"]}
-{"year":"2019","title":"Extracting and Analyzing Context Information in User-Support Conversations on Twitter","authors":["D Martens, W Maalej - arXiv preprint arXiv:1907.13395, 2019"],"snippet":"… As the list of marketing names also includes common words (eg, 'five', 'go', or 'plus'), we used the natural language processing library spaCy [33] to remove words that appear in the vocabulary of the included …","url":["https://arxiv.org/pdf/1907.13395"]}
-{"year":"2019","title":"Extracting Novel Facts from Tables for Knowledge Graph Completion (Extended version)","authors":["B Kruit, P Boncz, J Urbani - arXiv preprint arXiv:1907.00083, 2019"],"snippet":"… The first one is the T2D dataset [23], which contains a subset of the WDC Web Tables Corpus – a set of tables extracted from the CommonCrawl web scrape6. We use the latest available version of this dataset (v2, released 2017/02). In …","url":["https://arxiv.org/pdf/1907.00083"]}
-{"year":"2019","title":"Extracting Novel Facts from Tables for Knowledge Graph Completion","authors":["B Kruit, P Boncz, J Urbani - International Semantic Web Conference, 2019"],"snippet":"… The first one is the T2D dataset [25], which contains a subset of the WDC Web Tables Corpus – a set of tables extracted from the CommonCrawl web scrape 2 . We use the latest available version of this dataset (v2, released 2017/02) …","url":["https://link.springer.com/chapter/10.1007/978-3-030-30793-6_21"]}
-{"year":"2019","title":"Facebook AI's WAT19 Myanmar-English Translation Task Submission","authors":["PJ Chen, J Shen, M Le, V Chaudhary, A El-Kishky… - arXiv preprint arXiv …, 2019"],"snippet":"… For Myanmar language, we take five snapshots of the Commoncrawl dataset and combine them with the raw data from Buck et al. (2014) … The Myanmar monolingual data we collect from Commoncrawl contains text in both Unicode and Zawgyi encodings …","url":["https://arxiv.org/pdf/1910.06848"]}
-{"year":"2019","title":"Facebook FAIR's WMT19 News Translation Task Submission","authors":["N Ng, K Yee, A Baevski, M Ott, M Auli, S Edunov - arXiv preprint arXiv:1907.06616, 2019"],"snippet":"… We train two language models LI and LN on Newscrawl and Commoncrawl respectively, then score every sentence s in Commoncrawl by HI(s)−HN (s). We select a cu- toff of 0.01, and use all sentences that score higher than …","url":["https://arxiv.org/pdf/1907.06616"]}
-{"year":"2019","title":"Facilitating access to health web pages with different language complexity levels","authors":["M Alfano, B Lenzitti, D Taibi, M Helfert - 2019"],"snippet":"… The Web Data Commons (WDC) (Meusel, 2014) contains all Microformat, Microdata and RDFa data extracted from the open repository of web crawl data named Common Crawl (CC)16 … 15 http://webdatacommons.org/ 16 http://commoncrawl.org …","url":["http://doras.dcu.ie/23104/1/ICT4AWE_2019_30_CR.pdf"]}
-{"year":"2019","title":"Fast and Accurate Network Embeddings via Very Sparse Random Projection","authors":["H Chen, SF Sultan, Y Tian, M Chen, S Skiena - arXiv preprint arXiv:1908.11512, 2019"],"snippet":"… WWW-200K and WWW-10K [11]: these graphs are derived from the Web graph provided by Common Crawl, where the nodes are hostnames and the edges are the hyperlinks between these websites. For simplicity, we treat this graph as an undirected graph …","url":["https://arxiv.org/pdf/1908.11512"]}
-{"year":"2019","title":"Faster Neural Network Training with Data Echoing","authors":["D Choi, A Passos, CJ Shallue, GE Dahl - arXiv preprint arXiv:1907.05550, 2019"],"snippet":"… 2http://commoncrawl.org/2017/07/june-2017-crawl-archive-now-available/ 3Each time a training example is read from disk, it counts as a fresh example. 420k steps for LM1B, 60k for Common Crawl, 110k for ImageNet, 150k for CIFAR-10, and 30k for COCO …","url":["https://arxiv.org/pdf/1907.05550"]}
-{"year":"2019","title":"FastSV: A Distributed-Memory Connected Component Algorithm with Fast Convergence","authors":["Y Zhang, A Azad, Z Hu - arXiv preprint arXiv:1910.05971, 2019"],"snippet":"Page 1. FastSV: A Distributed-Memory Connected Component Algorithm with Fast Convergence Yongzhe Zhang ∗ Ariful Azad † Zhenjiang Hu ‡ Abstract This paper presents a new distributed-memory algorithm called FastSV …","url":["https://arxiv.org/pdf/1910.05971"]}
-{"year":"2019","title":"FastText-Based Intent Detection for Inflected Languages","authors":["K Balodis, D Deksne - Information, 2019"],"snippet":"… For the word embeddings released by Facebook, we used the ones trained on Wikipedia (https: //fasttext.cc/docs/en/pretrained-vectors.html) because the ones trained on Common Crawl (https: //fasttext.cc/docs/en/crawl-vectors.html) showed inferior results in our tests …","url":["https://www.mdpi.com/2078-2489/10/5/161/pdf"]}
-{"year":"2019","title":"Feature Engineering for Text Representation","authors":["D Sarkar - Text Analytics with Python, 2019"],"snippet":"In the previous chapters, we saw how to understand, process, and wrangle text data. However, all machine learning or deep learning models are limited because they cannot understand text data directly...","url":["https://link.springer.com/chapter/10.1007/978-1-4842-4354-1_4"]}
-{"year":"2019","title":"Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels","authors":["L Lange, MA Hedderich, D Klakow - arXiv preprint arXiv:1910.06061, 2019"],"snippet":"… clustering. While the Brown clustering was trained on the relatively small Europarl corpus, k- Means clustering seems to benefit from the word embeddings trained on documents from the much larger common crawl. 7 Analysis …","url":["https://arxiv.org/pdf/1910.06061"]}
-{"year":"2019","title":"Feature2Vec: Distributional semantic modelling of human property knowledge","authors":["S Derby, P Miller, B Devereux - arXiv preprint arXiv:1908.11439, 2019"],"snippet":"… For our experiments, we make use of the pretrained GloVe embeddings (Pennington et al., 2014) provided in the Spacy1 package trained on the Common Crawl2. The GloVe model includes 685,000 tokens … 1https://spacy …","url":["https://arxiv.org/pdf/1908.11439"]}
-{"year":"2019","title":"Feeling Anxious? Perceiving Anxiety in Tweets using Machine Learning","authors":["D Gruda, S Hasan - Computers in Human Behavior, 2019"],"snippet":"… tweets. Words-to-vectors mapping is based on the deep neural network learning GloVe (Pennington, Socher, & Manning, 2014) embedding space built from the Common Crawl Web Data (42 Billion tokens, 1.9M vocab). The …","url":["https://www.sciencedirect.com/science/article/pii/S0747563219301608"]}
-{"year":"2019","title":"FIESTA: Fast IdEntification of State-of-The-Art models using adaptive bandit algorithms","authors":["HB Moss, A Moore, DS Leslie, P Rayson - arXiv preprint arXiv:1906.12230, 2019"],"snippet":"… optimiser settings and the same regularisation. All words are lower cased and we use the same Glove common crawl 840B token 300 dimension word embedding (Pennington et al., 2014). We use variational (Gal and Ghahramani …","url":["https://arxiv.org/pdf/1906.12230"]}
-{"year":"2019","title":"Figurative Usage Detection of Symptom Words to Improve Personal Health Mention Detection","authors":["A Iyer, A Joshi, S Karimi, R Sparks, C Paris - arXiv preprint arXiv:1906.05466, 2019"],"snippet":"… The first four are a random initialisation, and three pre-trained embeddings. The pretrained embeddings are: (a) word2vec (Mikolov et al., 2013); (b) GloVe (trained on Common Crawl) (Pennington et al., 2014); and, (c) Numberbatch (Speer et al., 2017) …","url":["https://arxiv.org/pdf/1906.05466"]}
-{"year":"2019","title":"Finding Generalizable Evidence by Learning to Convince Q&A Models","authors":["E Perez, S Karamcheti, R Fergus, J Weston, D Kiela… - arXiv preprint arXiv …, 2019"],"snippet":"… fastText We define a function BoWFT that computes the average bag-of-words representation of some text using fastText embeddings (Joulin et al., 2017). We use 300-dimensional fastText word vectors pretrained on Common Crawl …","url":["https://arxiv.org/pdf/1909.05863"]}
-{"year":"2019","title":"Findings of the First Shared Task on Machine Translation Robustness","authors":["X Li, P Michel, A Anastasopoulos, Y Belinkov… - arXiv preprint arXiv …, 2019"],"snippet":"… To explore effective approaches to leverage abundant out-of-domain parallel data. • To explore novel approaches to leverage abundant monolingual data on the Web (eg, tweets, Reddit comments, commoncrawl, etc.). • To …","url":["https://arxiv.org/pdf/1906.11943"]}
-{"year":"2019","title":"Findings of the WMT 2019 Shared Task on Parallel Corpus Filtering for Low-Resource Conditions","authors":["P Koehn, F Guzmán, V Chaudhary, J Pino - Proceedings of the Fourth Conference on …, 2019"],"snippet":"… Corpus Sentences Words Wikipedia Sinhala 155,946 4,695,602 Nepali 92,296 2,804,439 English 67,796,935 1,985,175,324 CommonCrawl Sinhala 5,178,491 110,270,445 Nepali 3,562,373 102,988,609 English 380,409,891 8,894,266,960 …","url":["https://www.aclweb.org/anthology/W19-5404"]}
-{"year":"2019","title":"FlauBERT: Unsupervised Language Model Pre-training for French","authors":["H Le, L Vial, J Frej, V Segonne, M Coavoux… - arXiv preprint arXiv …, 2019"],"snippet":"… Common Crawl).11 The data were collected from three main sources: (1) monolingual data for French provided in WMT19 shared tasks (Li et al., 2019, 4 sub-corpora); (2) French text corpora offered in the OPUS collection …","url":["https://arxiv.org/pdf/1912.05372"]}
-{"year":"2019","title":"Frame Augmented Alternating Attention Network for Video Question Answering","authors":["W Zhang, S Tang, Y Cao, S Pu, F Wu, Y Zhuang - IEEE Transactions on Multimedia, 2019"],"snippet":"Page 1. 1520-9210 (c) 2019 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/8811730/"]}
-{"year":"2019","title":"Frequency, acceptability, and selection: A case study of clause-embedding","authors":["AS White, K Rawlins"],"snippet":"Page 1. Frequency, acceptability, and selection: A case study of clause-embedding Aaron Steven White University of Rochester aaron.white@rochester.edu Kyle Rawlins Johns Hopkins University kgr@jhu.edu Abstract We investigate …","url":["https://ling.auf.net/lingbuzz/004596/current.pdf"]}
-{"year":"2019","title":"From Legal to Technical Concept: Towards an Automated Classification of German Political Twitter Postings as Criminal Offenses","authors":["F Zufall, T Horsmann, T Zesch"],"snippet":"… We use a bi-directional LSTM (Hochreiter and Schmidhuber, 1997) for classification.30 We use the 300-dimensional German pre-trained word embeddings provided by Grave et al. (2018), which are trained on the German common crawl …","url":["https://www.researchgate.net/profile/Frederike_Zufall/publication/331475806_From_Legal_to_Technical_Concept_Towards_an_Automated_Classification_of_German_Political_Twitter_Postings_as_Criminal_Offenses/links/5ccbe9b0a6fdcc4719838905/From-Legal-to-Technical-Concept-Towards-an-Automated-Classification-of-German-Political-Twitter-Postings-as-Criminal-Offenses.pdf"]}
-{"year":"2019","title":"Frontiersinpatternrecognitionandartificialintelligence","authors":["B Marleah, N Nicola, SC Yee - 2019"],"snippet":""}
-{"year":"2019","title":"Frowning Frodo, Wincing Leia, and a Seriously Great Friendship: Learning to Classify Emotional Relationships of Fictional Characters","authors":["E Kim, R Klinger - arXiv preprint arXiv:1903.12453, 2019"],"snippet":"… We obtain word vectors for the embedding layer from GloVe (pre-trained on Common Crawl, d = 300, Pennington et al., 2014) and initialize out- of-vocabulary terms with zeros (including the po- sition indicators). 4 Experiments Experimental Setting …","url":["https://arxiv.org/pdf/1903.12453"]}
-{"year":"2019","title":"Fusing Vector Space Models for Domain-Specific Applications","authors":["L Rettig, J Audiffren, P Cudré-Mauroux - arXiv preprint arXiv:1909.02307, 2019"],"snippet":"… Despite the convenience they bring, using such readilyavailable, pre-trained models is often suboptimal in vertical applications [2], [3]; as these models are pre-trained on large, non-specific sources (eg, Wikipedia and the Common …","url":["https://arxiv.org/pdf/1909.02307"]}
-{"year":"2019","title":"Gating Mechanisms for Combining Character and Word-level Word Representations: An Empirical Study","authors":["JA Balazs, Y Matsuo - arXiv preprint arXiv:1904.05584, 2019"],"snippet":"Page 1. Gating Mechanisms for Combining Character and Word-level Word Representations: An Empirical Study Jorge A. Balazs and Yutaka Matsuo Graduate School of Engineering The University of Tokyo {jorge, matsuo}@weblab.tu-tokyo.ac.jp Abstract …","url":["https://arxiv.org/pdf/1904.05584"]}
-{"year":"2019","title":"General Purpose Vector Representation for Swedish Documents: An application of Neural Language Models","authors":["S Hedström - 2019"],"snippet":"Page 1. General Purpose Vector Representation for Swedish Documents An application of Neural Language Models Simon Hedström Master's Thesis in Engineering Physics, Department of Physics, Umeå University, 2019 Page …","url":["https://umu.diva-portal.org/smash/get/diva2:1323994/FULLTEXT01.pdf"]}
-{"year":"2019","title":"Generalizable prediction of academic performance from short texts on social media","authors":["I Smirnov - arXiv preprint arXiv:1912.00463, 2019"],"snippet":"… We obtained significantly better results with a model that used word-embeddings (see Methods). We also find that embeddings trained on the VK corpus outperform models trained on the Wikipedia and Common Crawl corpora (Table 1). 3 Page 4 …","url":["https://arxiv.org/pdf/1912.00463"]}
-{"year":"2019","title":"Generalizing Question Answering System with Pre-trained Language Model Fine-tuning","authors":["D Su, Y Xu, GI Winata, P Xu, H Kim, Z Liu, P Fung - … of the 2nd Workshop on Machine …, 2019"],"snippet":"… (2009)) and Common Crawl (Buck et al., 1https://github.com/mrqa/MRQA-SharedTask-2019 2014) for pre-training … 2014. N-gram counts and language models from the common crawl. In LREC, volume 2, page 4. Citeseer …","url":["https://mrqa.github.io/assets/papers/63_Paper.pdf"]}
-{"year":"2019","title":"Generating Black-Box Adversarial Examples for Text Classifiers Using a Deep Reinforced Model","authors":["P Vijayaraghavan, D Roy - arXiv preprint arXiv:1909.07873, 2019"],"snippet":"… These paraphrase datasets together contains text from various sources: Common Crawl, CzEng1.6, Europarl, News Commentary, Quora questions, and Twitter trending topic tweets. We do not use all the data for our pretraining …","url":["https://arxiv.org/pdf/1909.07873"]}
-{"year":"2019","title":"Generating composite SQL queries from natural language","authors":["M De Groote - 2018"],"snippet":"… of the questions. We decided to use the Common Crawl embedding that is trained on 42 billion tokens, consists of a vocabulary of 1.9 million tokens and embeds these tokens in the 300-dimensional vector space5. All the words …","url":["https://lib.ugent.be/fulltxt/RUG01/002/494/903/RUG01-002494903_2018_0001_AC.pdf"]}
-{"year":"2019","title":"Generating Language-Independent Neural Sentence Embeddings for Natural Language Classification Tasks","authors":["S Erhardt"],"snippet":"… [Rud17] At the time this thesis was written, there are Word Embeddings for more than 150 languages, trained on Common Crawl1 and Wikipedia, available. [Rud17] 1An open repository of web crawl data that can be …","url":["https://www.social.in.tum.de/fileadmin/w00bwc/www/Gerhard_Hagerer/thesis.pdf"]}
-{"year":"2019","title":"Generic Web Content Extraction with Open-Source Software","authors":["A Barbaresi"],"snippet":"… Because of the vastly increasing variety of corpora, text types and use cases, it becomes more and more difficult to assess the usefulness and appropriateness of certain web texts 1https://commoncrawl.org for given research objectives …","url":["https://corpora.linguistik.uni-erlangen.de/data/konvens/proceedings/papers/kaleidoskop/camera_ready_barbaresi.pdf"]}
-{"year":"2019","title":"Geo-spatial text-mining from Twitter–a feature space analysis with a view toward building classification in urban regions","authors":["M Häberle, M Werner, XX Zhu - European Journal of Remote Sensing, 2019"],"snippet":"Skip to Main Content …","url":["https://www.tandfonline.com/doi/full/10.1080/22797254.2019.1586451"]}
-{"year":"2019","title":"Ghmerti at SemEval-2019 Task 6: A Deep Word-and Character-based Approach to Offensive Language Identification","authors":["E Doostmohammadi, H Sameti, A Saffar - … of the 13th International Workshop on …, 2019"],"snippet":"… The indices include 256 of the most common characters, plus 0 for padding and 1 for un- known characters. 2. xw which is the embeddings of the words in the input tweet based on FastText's 600Btoken common crawl model (Mikolov et al., 2018) …","url":["https://www.aclweb.org/anthology/S19-2110"]}
-{"year":"2019","title":"GLOSS: Generative Latent Optimization of Sentence Representations","authors":["SP Singh, A Fan, M Auli - arXiv preprint arXiv:1907.06385, 2019"],"snippet":"… representations. This could be as simple as using a bag-of-words averaging of Glove (Pennington et al., 2014) word embeddings trained on a corpus such as CommonCrawl, which we re- fer to as Glove-BoW. Methods such …","url":["https://arxiv.org/pdf/1907.06385"]}
-{"year":"2019","title":"GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding","authors":["Z Zhu, S Xu, M Qu, J Tang - arXiv preprint arXiv:1903.00757, 2019"],"snippet":"Page 1. GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding Zhaocheng Zhu Mila - Québec AI Institute Université de Montréal zhaocheng.zhu@ umontreal.ca Shizhen Xu Tsinghua University xsz12@mails.tsinghua.edu.cn …","url":["https://arxiv.org/pdf/1903.00757"]}
-{"year":"2019","title":"Green AI","authors":["R Schwartz, J Dodge, NA Smith, O Etzioni - arXiv preprint arXiv:1907.10597, 2019"],"snippet":"… For example, the June 2019 Common Crawl contains 242 TB of uncompressed data,12 so even simple filtering to extract usable text is difficult … 11https://opensource.google.com/ projects/open-images-dataset 12http://commoncrawl.org/2019/07 …","url":["https://arxiv.org/pdf/1907.10597"]}
-{"year":"2019","title":"Grounded Response Generation Task at DSTC7","authors":["M Galley, C Brockett, X Gao, J Gao, B Dolan"],"snippet":"… Turn 4 still pretty incredible , but quite a bit different that 10,000 meters . Table 1: Sample of the DSTC7 Sentence Generation data, which combines Reddit data (Turns 1-4) along with documents (extracted from Common Crawl) discussed in the conversations …","url":["http://workshop.colips.org/dstc7/papers/DSTC7_Task_2_overview_paper.pdf"]}
-{"year":"2019","title":"Happy Together: Learning and Understanding Appraisal From Natural Language","authors":["A Rajendran, C Zhang, M Abdul-Mageed"],"snippet":"… language models (ULMFiT). Exploiting Simple GloVe Embeddings For the embedding layer, we obtain the 300-dimensional embedding vector for tokens using GloVe's Common Crawl pre-trained model [13]. GloVe embeddings …","url":["https://mageed.sites.olt.ubc.ca/files/2019/01/AffCon_aaai2019_happyDB.pdf"]}
-{"year":"2019","title":"HARE: a Flexible Highlighting Annotator for Ranking and Exploration","authors":["D Newman-Griffis, E Fosler-Lussier - arXiv preprint arXiv:1908.11302, 2019"],"snippet":"… ated three commonly used benchmark embedding sets: word2vec skipgram (Mikolov et al., 2013) using GoogleNews,6 FastText skipgram with subword information on WikiNews,7 and GloVe (Pennington et al., 2014) on 840 …","url":["https://arxiv.org/pdf/1908.11302"]}
-{"year":"2019","title":"HATEMINER at SemEval-2019 Task 5: Hate speech detection against Immigrants and Women in Twitter using a Multinomial Naive Bayes Classifier","authors":["N Chakravartula - Proceedings of the 13th International Workshop on …, 2019"],"snippet":"… Word Embeddings: Glove840B - common crawl, GloveTwitter27B - twitter crawl (Pennington et al., 2014) and fasttext - common crawl (Mikolov et al., 2018) pre-trained word embeddings are used to analyze their impact on the classification …","url":["https://www.aclweb.org/anthology/S19-2071"]}
-{"year":"2019","title":"HealthSuggestions: moving beyond the beta version","authors":["PMP dos Santos - 2019"],"snippet":"Page 1. FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Health Suggestions: Moving Beyond the Beta Version Paulo Miguel Pereira dos Santos Master in Informatics and Computing Engineering Supervisor …","url":["https://repositorio-aberto.up.pt/bitstream/10216/121948/2/347008.2.pdf"]}
-{"year":"2019","title":"Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition","authors":["GI Winata, Z Lin, J Shin, Z Liu, P Fung - arXiv preprint arXiv:1909.08504, 2019"],"snippet":"… We use FastText word embeddings trained from Common Crawl and Wikipedia (Grave et al., 2018) for English (es), Spanish (es), including four Romance languages: Catalan (ca), Portuguese (pt), French (fr), Italian …","url":["https://arxiv.org/pdf/1909.08504"]}
-{"year":"2019","title":"High Quality ELMo Embeddings for Seven Less-Resourced Languages","authors":["M Ulčar, M Robnik-Šikonja - arXiv preprint arXiv:1911.10049, 2019"],"snippet":"… They used 20-million-words data randomly sampled from the raw text released by the CoNLL 2017 Shared Task - Automatically Annotated Raw Texts and Word Embeddings (Ginter et al., 2017), which is a combination of Wikipedia dump and common crawl …","url":["https://arxiv.org/pdf/1911.10049"]}
-{"year":"2019","title":"Hitachi at MRP 2019: Unified Encoder-to-Biaffine Network for Cross-Framework Meaning Representation Parsing","authors":["Y Koreeda, G Morio, T Morishita, H Ozaki, K Yanai - arXiv preprint arXiv:1910.01299, 2019"],"snippet":"… Named entity label Named entity (NE) recognition is applied to the input text (see Section 7.1). GloVe We use 300-dimensional GloVe (Pennington et al., 2014) pretrained on Common Crawl2 which are kept fixed during the training …","url":["https://arxiv.org/pdf/1910.01299"]}
-{"year":"2019","title":"HMM, Is This Ethical? Predicting the Ethics of Reddit Life Protips","authors":["M Coots, P Lu, L Wang"],"snippet":"… large corpus of text. GloVe representations have been trained on several large datasets that are publicly available, including corpuses from Wikipedia, Gigaword, Twitter, and Common Crawl [4]. 3. Task Definition Our problem is …","url":["https://madisoncoots.com/files/ethics.pdf"]}
-{"year":"2019","title":"How Decoding Strategies Affect the Verifiability of Generated Text","authors":["L Massarelli, F Petroni, A Piktus, M Ott, T Rocktäschel… - arXiv preprint arXiv …, 2019"],"snippet":"… consisting of roughly 3 Billion Words; (iv) CC- NEWS, a de-duplicated subset of the English portion of the CommonCrawl news dataset (Nagel, 2016; Bakhtin et al., 2019; Liu et al., 2019a), which totals around 16 Billion words …","url":["https://arxiv.org/pdf/1911.03587"]}
-{"year":"2019","title":"How to Ask Better Questions? A Large-Scale Multi-Domain Dataset for Rewriting Ill-Formed Questions","authors":["Z Chu, M Chen, J Chen, M Wang, K Gimpel, M Faruqui… - arXiv preprint arXiv …, 2019"],"snippet":"… and En↔Fr. The English-German translation models are trained on WMT datasets, including News Commentary 13, Europarl v7, and Common Crawl, and evaluated on newstest2013 for early stopping. On the newstest2013 …","url":["https://arxiv.org/pdf/1911.09247"]}
-{"year":"2019","title":"How Well Do Embedding Models Capture Non-compositionality? A View from Multiword Expressions","authors":["N Nandakumar, T Baldwin, B Salehi - Proceedings of the 3rd Workshop on Evaluating …, 2019"],"snippet":"… It tokenises text at the character level. fastText We used the 300-dimensional fastText model pre-trained on Common Crawl and Wikipedia using CBOW (fastTextpre), as well as one trained over the same Wikipedia corpus4 us- ing skip-gram (fastText) …","url":["https://www.aclweb.org/anthology/W19-2004"]}
-{"year":"2019","title":"Hybrid Rule-Based Model for Phishing URLs Detection","authors":["KS Adewole, AG Akintola, SA Salihu, N Faruk… - International Conference for …, 2019","N Faruk, RG Jimoh - … International Conference, iCETiC 2019, London, UK …, 2019"],"snippet":"… 1. From this figure, data collected from different servers such as Yahoo, Alexa, Common Crawl, PhishTank and OpenPhish are preprocessed in order to extract meaningful features that can be used for categorizing phishing websites from legitimate ones …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=QF6mDwAAQBAJ&oi=fnd&pg=PA119&dq=commoncrawl&ots=T7vreYeKah&sig=sO3M90XucnzXO7OeF6horBncwb4","https://link.springer.com/chapter/10.1007/978-3-030-23943-5_9"]}
-{"year":"2019","title":"Hybrid Words Representation for Airlines Sentiment Analysis","authors":["U Naseem, SK Khan, I Razzak, IA Hameed"],"snippet":"… GloVe uses ratios of co-occurrence probabilities. It is favourable to concatenate ELMo embeddings with traditional word embeddings. In this work, we have used pre-trained GloVe embedding (trained on 840 billion token from common crawl) of 300 dimensions …","url":["https://www.researchgate.net/profile/Ibrahim_Hameed/publication/336579383_Hybrid_Words_Representation_for_Airlines_Sentiment_Analysis/links/5da6e53892851caa1ba6f8c6/Hybrid-Words-Representation-for-Airlines-Sentiment-Analysis.pdf"]}
-{"year":"2019","title":"Hyper: Distributed Cloud Processing for Large-Scale Deep Learning Tasks","authors":["D Buniatyan - arXiv preprint arXiv:1910.07172, 2019"],"snippet":"… [4] MinIO high performance object storage server compatible with Amazon S3 API. https://github.com/minio/minio, 2018. [Online; accessed 31- May-2019]. [5] Common Crawl Dataset. https://commoncrawl.org, 2019. [Online; accessed 31-May-2019] …","url":["https://arxiv.org/pdf/1910.07172"]}
-{"year":"2019","title":"Hyperparameter Tuning for Deep Learning in Natural Language Processing","authors":["A Aghaebrahimian, M Cieliebak - 2019"],"snippet":"… on the Common Crawl, one on 42 and the other on 840 billion tokens), FastText (Bojanowski et al., 2016), dependency based (Levy and Goldberg, 2014), and ELMo (Peters et al., 2018). As shown in Ta- ble 1, the Glove …","url":["http://ceur-ws.org/Vol-2458/paper5.pdf"]}
-{"year":"2019","title":"Identification Of Bot Accounts In Twitter Using 2D CNNs On User-generated Contents","authors":["M Polignano, MG de Pinto, P Lops, G Semeraro - 2019"],"snippet":"… FastTextEmb)8: 300 dimensionality vectors, composed by a vocabulary of 2 million words and n-grams of the words, case sensitive and obtained from 600 billion of tokens trained on data crawled from generic Internet web pages by Common Crawl nonprofit organization; …","url":["https://www.researchgate.net/profile/Marco_Polignano/publication/334636395_Identification_Of_Bot_Accounts_In_Twitter_Using_2D_CNNs_On_User-generated_Contents/links/5d373c10a6fdcc370a59e892/Identification-Of-Bot-Accounts-In-Twitter-Using-2D-CNNs-On-User-generated-Contents.pdf"]}
-{"year":"2019","title":"Identification of Good and Bad News on Twitter","authors":["P Aggarwal, A Aker"],"snippet":"… We use tf-idf representation for each vocabulary term. 5.2.3 Embeddings Finally, we also use fasttext based embedding (Mikolov et al., 2018) vectors which are trained on common crawl having 600 billion tokens. 5.3 Classifiers …","url":["https://www.researchgate.net/profile/Ahmet_Aker3/publication/334825190_Identification_of_Good_and_Bad_News_on_Twitter/links/5d42c34992851cd04697548a/Identification-of-Good-and-Bad-News-on-Twitter.pdf"]}
-{"year":"2019","title":"Identifying and Addressing Structural Inequalities in the Representativeness of Geographic Technologies","authors":["IL Johnson - 2019"],"snippet":"… knowledge graphs (Wikipedia and Google [289]), word embeddings (Wikipedia, Twitter, and Common Crawl in GloVe embeddings [238]), object detection (Instagram hashtags and Facebook [292])—and adding …","url":["http://search.proquest.com/openview/dccae6679751f41f283b33f555947aa8/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2019","title":"Identifying transfer models for machine learning tasks","authors":["P Watson, B Bhattacharjee, NC CODELLA… - US Patent App. 15/982,622, 2019"],"snippet":"US20190354850A1 - Identifying transfer models for machine learning tasks - Google Patents. Identifying transfer models for machine learning tasks. Download PDF Info. Publication number US20190354850A1. US20190354850A1 …","url":["https://patents.google.com/patent/US20190354850A1/en"]}
-{"year":"2019","title":"Idiap Abstract Text Summarization System for German Text Summarization Task","authors":["S Parida, P Motlicek - 2019"],"snippet":"… The experiments performed over 1http://opennmt.net/OpenNMT-py/ Summarization.html 2https://www.swisstext.org/ 3http://commoncrawl.org/ these datasets are described in the Section 4 (de- noted as S1 experimental …","url":["http://ceur-ws.org/Vol-2458/paper9.pdf"]}
-{"year":"2019","title":"IIT Varanasi at HASOC 2019: Hate Speech and Offensive Content Identification in Indo-European Languages","authors":["A Mishra, S Pal - Proceedings of the 11th annual meeting of the Forum …"],"snippet":"… embedding. One of the pretrained glove embeddings is based on the common crawl which represents each word in the dimension of 300, and the other one is based on Twitter data which represents each word in the dimension of 200 …","url":["http://irlab.daiict.ac.in/~Parth/T3-22.pdf"]}
-{"year":"2019","title":"IIT-BHU at CIQ 2019: Classification of Insincere Questions","authors":["A Mishra, S Pal"],"snippet":"… Different versions of glove pre-trained em- bedding exist; however, we use embedding trained of dimension 300 on common crawl using 840B tokens and 2.2M vocabulary3. We generated random embedding of dimension 300 for out of vocabulary words …","url":["http://irlab.daiict.ac.in/~Parth/T5-4.pdf"]}
-{"year":"2019","title":"Impact of Debiasing Word Embeddings on Information Retrieval","authors":["E Gerritse - 2019"],"snippet":"… Bolukbasi et al. [1] show that there is a high correlation in bias in Word2Vec trained on Google News and Glove trained on the common crawl, so we still cannot infer whether the method or the dataset is more important for creating the bias …","url":["http://www.emmagerritse.com/pdfs/FDIA_2019_paper.pdf"]}
-{"year":"2019","title":"Improved Quality Estimation of Machine Translation with Pre-trained Language Representation","authors":["G Miao, H Di, J Xu, Z Yang, Y Chen, K Ouchi - CCF International Conference on …, 2019"],"snippet":"… The former is mainly obtained from the open news datasets of the WMT17 and WMT18 MT evaluation tasks, including five data sets: Europarl v7, Europarl v12, Europarl v13, Common Crawl corpus, and Rapid corpus of EU press releases …","url":["https://link.springer.com/chapter/10.1007/978-3-030-32233-5_32"]}
-{"year":"2019","title":"Improving Conditioning in Context-Aware Sequence to Sequence Models","authors":["X Wang, J Weston, M Auli, Y Jernite - arXiv preprint arXiv:1911.09728, 2019"],"snippet":"… 2019) for LFQA. The dataset consists of 272,000 complex questions and answer pairs, along with supporting documents created by gathering and concatenating passages from CommonCrawl web pages which are relevant to the question …","url":["https://arxiv.org/pdf/1911.09728"]}
-{"year":"2019","title":"Improving Grammatical Error Correction via Pre-Training a Copy-Augmented Architecture with Unlabeled Data","authors":["W Zhao, L Wang, K Shen, R Jia, J Liu - arXiv preprint arXiv:1903.00138, 2019"],"snippet":"… We do not use reranking when evaluating the CoNLL-2014 data sets. But we rerank the top 12 hypothesizes us- ing the language model trained on Common Crawl (Junczys-Dowmunt and Grundkiewicz, 2016) for …","url":["https://arxiv.org/pdf/1903.00138"]}
-{"year":"2019","title":"Improving Implicit Stance Classification in Tweets Using Word and Sentence Embeddings","authors":["R Schaefer, M Stede - Joint German/Austrian Conference on Artificial …, 2019"],"snippet":"… combinations. 4.2 fastText Embeddings. We use pre-trained 300-dimensional fastText [11] word vectors that have been trained on Wikipedia and Common Crawl data. For training, an extension of the CBOW model has been used …","url":["https://link.springer.com/chapter/10.1007/978-3-030-30179-8_26"]}
-{"year":"2019","title":"Improving Named Entity Recognition with Commonsense Knowledge Pre-training","authors":["G Dekhili, NT Le, F Sadat - Pacific Rim Knowledge Acquisition Workshop, 2019"],"snippet":"… which is the concatenation of ConceptNet PPMI embeddings with Word2Vec embeddings trained on 100 billion words of Google News using skip-grams with negative sampling [14] and GloVe 1.2 embeddings trained on 840 billion words of the Common Crawl [16] …","url":["https://link.springer.com/chapter/10.1007/978-3-030-30639-7_2"]}
-{"year":"2019","title":"Improving Neural Machine Translation of Subtitles with Finetun-ing","authors":["S Reinsperger - 2019"],"snippet":"… 3 Results 53 3.1 ParallelCorpora . . . . . 54 3.1.1 Europarl. . . . . 54 3.1.2 Common Crawl . . . . . 54 3.1.3 NewsCommentary . . . . . 56 3.1.4 Subtitles …","url":["http://www.simonrsp.com/masterthesis.pdf"]}
-{"year":"2019","title":"Improving Neural Machine Translation Robustness via Data Augmentation: Beyond Back Translation","authors":["Z Li, L Specia - arXiv preprint arXiv:1910.03009, 2019"],"snippet":"… 3.1 Corpora We used all parallel corpora from the WMT19 Robustness Task on Fr↔En. For out-of-domain training, we used the WMT15 Fr↔En News Translation Task data, including Europarl v7, Common Crawl, UN, News Commentary v10, and Gigaword Corpora …","url":["https://arxiv.org/pdf/1910.03009"]}
-{"year":"2019","title":"Improving Neural Machine Translation with Pre-trained Representation","authors":["R Weng, H Yu, S Huang, W Luo, J Chen - arXiv preprint arXiv:1908.07688, 2019"],"snippet":"… We use newstest2015 (NST15) as our validation set, and newstest2016 (NST16) as test sets 4. We use 40 million monolingual sentences from WMT-16 Common Crawl data-set … We use 5 million monolingual sentences …","url":["https://arxiv.org/pdf/1908.07688"]}
-{"year":"2019","title":"Improving orienteering-based tourist trip planning with social sensing","authors":["F Persia, G Pilato, M Ge, P Bolzoni, D D'Auria… - Future Generation …, 2019"],"snippet":"… This is a popular technique in machine learning for uncovering subsymbolic meanings, such as word analogies. We utilized a pre-trained word vector encoding for Italian provided by fastText [32], which was trained on Common Crawl and Wikipedia …","url":["https://www.sciencedirect.com/science/article/pii/S0167739X19303929"]}
-{"year":"2019","title":"Improving Quality Estimation of Machine Translation by Using Pre-trained Language Representation","authors":["G Miao, H Di, J Xu, Z Yang, Y Chen, K Ouchi - China Conference on Machine …, 2019","Y Chen, K Ouchi - Machine Translation: 15th China Conference, CCMT …, 2019"],"snippet":"… Metrics We first train the bilingual expert model [9] with large-scale parallel corpus released for the WMT17/WMT18 News Machine Translation Task, which mainly consists of five data sets, including Europarl v7, Europarl v12 …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=WuK_DwAAQBAJ&oi=fnd&pg=PA11&dq=commoncrawl&ots=XTi4UL5q8i&sig=lCeqF4TBBuqQrg4EE0rN09FZeVs","https://link.springer.com/chapter/10.1007/978-981-15-1721-1_2"]}
-{"year":"2019","title":"Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader","authors":["W Xiong, M Yu, S Chang, X Guo, WY Wang - arXiv preprint arXiv:1905.07098, 2019"],"snippet":"… Page 6. A Implementation Details Throughout our experiments, we use the 300-dimension GloVe embeddings trained on the Common Crawl corpus. The hidden dimension of LSTM and the dimension of entity embeddings are both 100 …","url":["https://arxiv.org/pdf/1905.07098"]}
-{"year":"2019","title":"In-call virtual assistant","authors":["R Raanani, R Levy, MY Breakstone - US Patent App. 16/165,566, 2019"],"snippet":"… At the same time, natural language processing (NLP) approaches to both topic modeling and world-knowledge modeling, have become much more efficient due to the availability of large, freely accessible natural language corpora (eg, CommonCrawl), as well as freely …","url":["https://patentimages.storage.googleapis.com/b2/cd/2c/a7fa39e3002b4f/US20190057698A1.pdf"]}
-{"year":"2019","title":"Incendiary News Detection","authors":["EB Coban, E Filatova - 2019"],"snippet":"… features. We run classification experiments for unigrams, and combination of uniand bi-grams. 10https://www.nltk.org/ 11http://scikit-learn.org 12https://github.com/ otuncelli/turkish-stemmer-python 13http://commoncrawl.org/ For …","url":["https://pdfs.semanticscholar.org/8c78/f9da879fc5936ef84dc7128db691d7042fef.pdf"]}
-{"year":"2019","title":"Incorporating Domain Knowledge into Natural Language Inference on Clinical Texts","authors":["M Lu, Y Fang, F Yan, M Li - IEEE Access, 2019"],"snippet":"… two domain-specific corpus: • GloVe[CC]: GloVe embeddings [21], trained on Common Crawl. • fastText[BioASQ]: fastText embeddings [22], trained on PubMed abstracts from the BioASQ challenge [23]. • fastText[MIMIC-III]: fastText …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/08701433.pdf"]}
-{"year":"2019","title":"Incorporating Syntactic Knowledge in Neural Quality Estimation for Machine Translation","authors":["N Ye, Y Wang, D Cai - China Conference on Machine Translation, 2019"],"snippet":"… One is the large-scale bilingual dataset for training the feature extraction module. It comes from the parallel corpus of WMT machine translation task, including Europarl v7, Common Crawl corpus, News Commentary v11 and so on …","url":["https://link.springer.com/chapter/10.1007/978-981-15-1721-1_3"]}
-{"year":"2019","title":"Inducing Relational Knowledge from BERT","authors":["Z Bouraoui, J Camacho-Collados, S Schockaert - arXiv preprint arXiv:1911.12753, 2019"],"snippet":"… As static word embeddings for the baselines, we will use the Skip-gram word vectors that were pre-trained from the 100B words Google News data set6 (SG-GN) and GloVe word vectors which were pre-trained from the …","url":["https://arxiv.org/pdf/1911.12753"]}
-{"year":"2019","title":"Inducing Schema. org Markup from Natural Language Context","authors":["GK Shahi, D Nandini, S Kumari - Kalpa Publications in Computing, 2019"],"snippet":"… extension, in 2012 another data hub called Web Data Commons [5] came up with structured data extracted from the Common Crawl … 5http:// commoncrawl.org/ 6http://webdatacommons.org/ 7The WARC file format …","url":["https://easychair.org/publications/download/DXGr"]}
-{"year":"2019","title":"Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings","authors":["M Le, S Roller, L Papaxanthos, D Kiela, M Nickel - arXiv preprint arXiv:1902.00913, 2019"],"snippet":"Page 1. Inferring Concept Hierarchies from Text Corpora via Hyperbolic Embeddings Matt Le1 and Stephen Roller1 and Laetitia Papaxanthos2 Douwe Kiela1 and Maximilian Nickel1 1Facebook AI Research, New York …","url":["https://arxiv.org/pdf/1902.00913"]}
-{"year":"2019","title":"Information extraction","authors":["S Razniewski"],"snippet":"… 8 Page 9. Taxi [Panchenko et al., 2016] 1. Crawl domain-specific text corpora in addition to WP, Commoncrawl 2. Candidate hypernymy extraction 1. Via substrings • “biomedical science” isA “science” • “microbiology” isA “biology” • “toast with bacon” isA “toast” …","url":["https://www.mpi-inf.mpg.de/fileadmin/inf/d5/teaching/ws19-20_ie/5_Taxonomy_induction_coreference_disambiguation.pdf"]}
-{"year":"2019","title":"InriaFBK Drawing Attention to Offensive Language at Germeval2019","authors":["M Corazza, S Menini, E Cabrio, S Tonelli, S Villata…"],"snippet":"… This is the main reason why we chose to use FastText embeddings (Bojanowski et al., 2016), pretrained on Common Crawl and Wikipedia 3. 4.3 Recurrent model We develop a simple recurrent neural network model and use it for all subtasks …","url":["https://corpora.linguistik.uni-erlangen.de/data/konvens/proceedings/papers/germeval/Germeval_Task_2_2019_paper_1.INRIA.pdf"]}
-{"year":"2019","title":"Integrating Grammatical Features into CNN Model for Emotion Classification","authors":["AC Le - 2018 5th NAFOSTED Conference on Information and …, 2018"],"snippet":"… a sentence s = 11 In this study we used the vector set GloVe [16], it is pretrained word vectors for Common Crawl (glove.42B.300d) with 300 dimensions for word embeddings to use for English data. For Vietnamese emotion …","url":["https://ieeexplore.ieee.org/abstract/document/8606875/"]}
-{"year":"2019","title":"Integrating UMLS for Early Detection of Sings of Anorexia","authors":["FM Plaza-del-Arco, P López-Úbeda, MC Dıaz-Galiano… - 2019"],"snippet":"… Specifically, we use Page 6. the available pre-trained statistical models for English ”en core web md” wich version is 1.2.0. It is composed of 685k keys, 20k unique vectors (300 dimensions) and it was trained on OntoNotes …","url":["http://www.dei.unipd.it/~ferro/CLEF-WN-Drafts/CLEF2019/paper_76.pdf"]}
-{"year":"2019","title":"Integrating word embeddings and document topics with deep learning in a video classification framework","authors":["Z Kastrati, AS Imran, A Kurti - Pattern Recognition Letters, 2019"],"snippet":"… GloVe contains word embeddings for a vocabulary of 400K words trained on 42 billion words from Wikipedia pages and newswire, and fastText includes word embeddings for a vocabulary of 2 million words trained on 600 billion tokens from Common Crawl …","url":["https://www.sciencedirect.com/science/article/pii/S0167865519302326"]}
-{"year":"2019","title":"Intelligent sentiment analysis approach using edge computing‐based deep learning technique","authors":["H Sankar, V Subramaniyaswamy, V Vijayakumar… - Software: Practice and Experience"],"snippet":"… Word2Vec, 300d, 3 Million, 100 Billion. Common Crawl, 300d, 42 Billion, 1.9 Million. Common Crawl, 300d, 840 Billion, 2.2 Million. The main drawback of unsupervised word embedding learning is that it does not hold the sentiment …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2687"]}
-{"year":"2019","title":"Interactive Language Learning by Question Answering","authors":["X Yuan, MA Cote, J Fu, Z Lin, C Pal, Y Bengio… - arXiv preprint arXiv …, 2019"],"snippet":"Page 1. Interactive Language Learning by Question Answering Xingdi Yuan♥∗ Marc-Alexandre Côté♥∗ Jie Fu♣♠ Zhouhan Lin♦♠ Christopher Pal♣♠ Yoshua Bengio♦♠ Adam Trischler♥ ♥Microsoft Research, Montréal ♣Polytechnique …","url":["https://arxiv.org/pdf/1908.10909"]}
-{"year":"2019","title":"Interactive Machine Comprehension with Information Seeking Agents","authors":["X Yuan, J Fu, MA Cote, Y Tay, C Pal, A Trischler - arXiv preprint arXiv:1908.10449, 2019"],"snippet":"… Word embeddings are initialized by the 300-dimension fastText (Mikolov et al. 2018) vectors trained on Common Crawl (600B tokens), and are fixed during training. Character embeddings are initialized by 200-dimension random vectors …","url":["https://arxiv.org/pdf/1908.10449"]}
-{"year":"2019","title":"Internet of Things Anomaly Detection using Multivariate Analysis","authors":["S Ezekiel, AA Alshehri, L Pearlstein, XW Wu, A Lutz - The 3rd ICICPE 2019 Conference …"],"snippet":"… Our model uses the GloVe (Pennington et al., 2014) 300-dimensional vectors trained on the Common Crawl corpus with 42B tokens as word level features, as this resulted in the best performance in preliminary experiments …","url":["http://icicpe.org/wp-content/uploads/2019/12/ICICPE-2019-vol.31.pdf#page=90"]}
-{"year":"2019","title":"Iot-based call assistant device","authors":["R Raanani, R Levy, MY Breakstone - US Patent App. 16/168,663, 2019"],"snippet":"… At the same time, natural language processing (NLP) approaches to both topic modeling and world-knowledge modeling, have become much more efficient due to the availability of large, freely accessible natural language corpora (eg, CommonCrawl), as well as freely …","url":["https://patentimages.storage.googleapis.com/c3/a1/97/799532a8db7406/US20190057079A1.pdf"]}
-{"year":"2019","title":"Iterative Keyword Optimization","authors":["A Elyashar, M Reuben, R Puzis"],"snippet":"… The model was trained on Common Crawl 4 and Wikipedia 5 using the fastText library 6. We used Euclidean as the distance measure … 4 http://commoncrawl.org/ 5 https://www.wikipedia.org/ 6 https://fasttext …","url":["http://sbp-brims.org/2019/proceedings/papers/working_papers/Elyashar.pdf"]}
-{"year":"2019","title":"JHU 2019 Robustness Task System Description","authors":["M Post, K Duh - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… the best million lines each of CommonCrawl, Gigaword, and the UN corpus; and • the MTNT training data. Data sizes are indicated in Table 1. dataset segments words Europarl 2.0m 50.2m News Commentary 200k 4.4m …","url":["https://www.aclweb.org/anthology/W19-5366"]}
-{"year":"2019","title":"Johns Hopkins University Submission for WMT News Translation Task","authors":["K Marchisio, YK Lal, P Koehn - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… sampled bitext (x2). ParaCrawl1 and Common Crawl2 are filtered similarly, and added to form the training set for the final models. We … Crawl. ParaCrawl and Common Crawl were combined into a single corpus before filtering …","url":["https://www.aclweb.org/anthology/W19-5329"]}
-{"year":"2019","title":"Joint Training for Neural Machine Translation","authors":["Y Cheng"],"snippet":"Page 1. Springer Recognizing Theses Outstanding Ph.D. Research Yong Cheng Joint Neural Translation Training Machine for Page 2. Springer Theses Recognizing Outstanding Ph.D. Research Page 3. Aims and Scope The …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=KIOrDwAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=vy1Stpb4X-&sig=1d6kjXbtaE3McDjxvY7O9-JJQOk"]}
-{"year":"2019","title":"Jointly Learning to Align and Translate with Transformer Models","authors":["S Garg, S Peitz, U Nallasamy, M Paulik - arXiv preprint arXiv:1909.02074, 2019","SGSPU Nallasamy, M Paulik"],"snippet":"… by Vilar et al. (2006). We use all available bilingual data (Europarl v7, Common Crawl corpus, News Commentary v13 and Rapid corpus of EU press releases) excluding the ParalCrawl corpus. We remove sentences longer …","url":["https://arxiv.org/pdf/1909.02074","https://www.researchgate.net/profile/Stephan_Peitz/publication/336996532_Jointly_Learning_to_Align_and_Translate_with_Transformer_Models/links/5ec41124458515626cb813b1/Jointly-Learning-to-Align-and-Translate-with-Transformer-Models.pdf"]}
-{"year":"2019","title":"JParaCrawl: A Large Scale Web-Based English-Japanese Parallel Corpus","authors":["M Morishita, J Suzuki, M Nagata - arXiv preprint arXiv:1911.10668, 2019"],"snippet":"… To select the candidate domains, we first identified the language of all the Common Crawl text data by CLD26 and counted how much … Since the crawled data stored on Common Crawl may not contain the entire website or might …","url":["https://arxiv.org/pdf/1911.10668"]}
-{"year":"2019","title":"KaWAT: A Word Analogy Task Dataset for Indonesian","authors":["K Kurniawan - arXiv preprint arXiv:1906.09912, 2019"],"snippet":"… We used fastText pretrained embeddings introduced in (Bojanowskietal.,2017) and (Grave et al., 2018), which have been trained on Indonesian Wikipedia and Indonesian Wikipedia plus Common Crawl data respectively. We …","url":["https://arxiv.org/pdf/1906.09912"]}
-{"year":"2019","title":"Keyphrase Extraction from Scholarly Articles as Sequence Labeling using Contextualized Embeddings","authors":["D Sahrawat, D Mahata, M Kulkarni, H Zhang… - arXiv preprint arXiv …, 2019"],"snippet":"… and OpenAI GPT-2 (small, medium). As a baseline, we also use 300 dimensional fixed embeddings from Glove2, Word2Vec3, and FastText4 (common-crawl, wiki-news). We also compare the proposed architecture against …","url":["https://arxiv.org/pdf/1910.08840"]}
-{"year":"2019","title":"KiloGrams: Very Large N-Grams for Malware Classification","authors":["E Raff, W Fleming, R Zak, H Anderson, B Finlayson… - arXiv preprint arXiv …, 2019"],"snippet":"… A ccuracy s = 1 s = ⌈n/4⌉ Figure 1: Balanced Accuracy results (y-axis) on the Public PDF dataset as we increase then-gram size (x-axis, log-scale), and alter the hashing stride s. Using a hashing-stride retains more …","url":["https://arxiv.org/pdf/1908.00200"]}
-{"year":"2019","title":"KIT's Submission to the IWSLT 2019 Shared Task on Text Translation","authors":["F Schneider, A Waibel"],"snippet":"… We made use of all allowed data, which is broken down in table 1. The allowed parallel data from WMT consists of Commoncrawl, CzEng (which makes up the vast majority of the parallel training data), Europarl, news commentrary and paracrawl …","url":["https://zenodo.eu/record/3525496/files/IWSLT2019_paper_30.pdf"]}
-{"year":"2019","title":"Knowledge empowered prominent aspect extraction from product reviews","authors":["Z Luo, S Huang, KQ Zhu - Information Processing & Management, 2019"],"snippet":"Skip to main content …","url":["https://www.sciencedirect.com/science/article/pii/S0306457318305193"]}
-{"year":"2019","title":"Knowledge Graph-Driven Conversational Agents","authors":["J Bockhorst, D Conathan, G Fung"],"snippet":"… We use a CNN with max pooling and pretrained Glove embeddings trained on the Common Crawl 840B dataset [6] [7]. By applying our CNN classifier as a straightforward 1-of-k document classification task, we are able to achieve …","url":["https://kr2ml.github.io/2019/papers/KR2ML_2019_paper_42.pdf"]}
-{"year":"2019","title":"Knowledge-based Conversational Search","authors":["S Vakulenko - arXiv preprint arXiv:1912.06859, 2019"],"snippet":"Page 1. arXiv:1912.06859v1 [cs.IR] 14 Dec 2019 Page 2. Page 3. Knowledge-based Conversational Search DISSERTATION submitted in partial fulfillment of the requirements for the degree of Doktorin der Technischen Wissenschaften by Svitlana Vakulenko, MSc …","url":["https://arxiv.org/pdf/1912.06859"]}
-{"year":"2019","title":"Kyoto University participation to the WMT 2019 news shared task","authors":["F Cromieres, S Kurohashi - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… Page 2. 164 3 Data preprocessing 3.1 Data used For bilingual data, we used the provided corpora: europarl (≈ 1.7M sentence pairs), common crawl(≈ 620k sentence pairs) and newscommentary (≈ 255k sentence pairs). We did not use the paracrawl corpus …","url":["https://www.aclweb.org/anthology/W19-5312"]}
-{"year":"2019","title":"Language Modelling Makes Sense: Propagating Representations through WordNet for Full-Coverage Word Sense Disambiguation","authors":["D Loureiro, A Jorge - arXiv preprint arXiv:1906.10007, 2019"],"snippet":"… tokens in the sentence. We choose fastText (Bojanowski et al., 2017) embeddings (pretrained on CommonCrawl), which are biased towards morphology, and avoid Out-of-Vocabulary issues as explained in §2.1. We use fastText …","url":["https://arxiv.org/pdf/1906.10007"]}
-{"year":"2019","title":"Language Models are Unsupervised Multitask Learners","authors":["A Radford, J Wu, R Child, D Luan, D Amodei…"],"snippet":"… A promising source of diverse and nearly unlimited text is web scrapes such as Common Crawl … Trinh & Le (2018) used Common Crawl in their work on commonsense reasoning but noted a large amount of documents “whose content are mostly unintelligible” …","url":["https://www.techbooky.com/wp-content/uploads/2019/02/Better-Language-Models-and-Their-Implications.pdf"]}
-{"year":"2019","title":"Language Models with Pre-Trained (GloVe) Word Embeddings","authors":["L Rokach, B Shapira, V Makarenkov"],"snippet":"… Despite the huge size of the Common Crawl corpus, some words may not exist with the embeddings, so we set these words to random vectors, and use the same embeddings consistently if we encounter the same unseen word again in the text …","url":["https://deepai.org/publication/language-models-with-pre-trained-glove-word-embeddings"]}
-{"year":"2019","title":"Large Memory Layers with Product Keys","authors":["G Lample, A Sablayrolles, MA Ranzato, L Denoyer… - arXiv preprint arXiv …, 2019","MA Ranzato, L Denoyer, H Jégou"],"snippet":"… Experiments Page 20. Dataset 20 ▶ Extracted from the public Common Crawl. ▶ 40 million English news articles in training set, 5000 in validation and test set each. ▶ Did not shuffle sentences, allowing the model to learn …","url":["https://arxiv.org/pdf/1907.05242","https://pdfs.semanticscholar.org/3a54/100803474df3b98e54a1693010d12c9718b5.pdf"]}
-{"year":"2019","title":"Large Scale Linguistic Processing of Tweets to Understand Social Interactions among Speakers of Less Resourced Languages: The Basque Case","authors":["J Fernandez de Landa, R Agerri, I Alegria - Information, 2019"],"snippet":"… resourced languages such as Basque. However, FastText provides pre-trained models for many languages, including Basque [33] by using the common crawl data (http://commoncrawl.org). The Basque model they distribute …","url":["https://www.mdpi.com/2078-2489/10/6/212/pdf"]}
-{"year":"2019","title":"Last-Mile TLS Interception: Analysis and Observation of the Non-Public HTTPS Ecosystem","authors":["XC de Carnavalet - 2019"],"snippet":"Page 1. Last-Mile TLS Interception: Analysis and Observation of the Non-Public HTTPS Ecosystem Xavier de Carné de Carnavalet A thesis in The Concordia Institute for Information Systems Engineering Presented …","url":["http://users.encs.concordia.ca/~mmannan/student-resources/Thesis-PhD-Carnavalet-2019.pdf"]}
-{"year":"2019","title":"Latent Question Interpretation Through Parameter Adaptation","authors":["T Parshakova, F Rameau, A Serdega, I Kweon, DS Kim - IEEE/ACM Transactions on …, 2019"],"snippet":"… A. Implementation Details For the sake of reproducibility, we provide the technical details related to the implementation of our approach. First of all, the initial word embeddings are initialized with GloVe embeddings, which …","url":["https://www.researchgate.net/profile/Francois_Rameau/publication/334633405_Latent_Question_Interpretation_Through_Parameter_Adaptation/links/5d37e05ca6fdcc370a5a3a43/Latent-Question-Interpretation-Through-Parameter-Adaptation.pdf"]}
-{"year":"2019","title":"Laying the foundations for benchmarking open data automatically: a method for surveying data portals from the whole web","authors":["A Sheffer Correa, F Soares Correa Da Silva - 20th Annual International Conference …, 2019"],"snippet":"… KEYWORDS Open Data, Common Crawl, CKAN, Socrata, ArcGIS, OpenDataSoft … Common Crawl conducts crawls once a month and persists all the content in Web Archive (WARC) file format to allow multibillion web page archives with hundreds of terabytes in size …","url":["https://dl.acm.org/citation.cfm?id=3325257"]}
-{"year":"2019","title":"LCEval: Learned Composite Metric for Caption Evaluation","authors":["N Sharif, L White, M Bennamoun, W Liu, SAA Shah"],"snippet":"… Table 1: The details of pre-trained embeddings used in our experiments Name Source Dimensions Corpus Corpus Size Vocabulary Size GloVE 840B 300d [40] 300 Common Crawl 8.40E+11 2.20E+06 Word2vec Google 300d [34] …","url":["https://www.researchgate.net/profile/Naeha_Sharif2/publication/334760575_LCEval_Learned_Composite_Metric_for_Caption_Evaluation/links/5d429677a6fdcc370a715269/LCEval-Learned-Composite-Metric-for-Caption-Evaluation.pdf"]}
-{"year":"2019","title":"Learning as the Unsupervised Alignment of Conceptual Systems","authors":["BD Roads, BC Love - arXiv preprint arXiv:1906.09012, 2019"],"snippet":"… We found that alignment correlations positively correlated with mapping accuracy across a variety of scenarios (Figure 3A-C). The three conceptual systems were derived from a Common Crawl text corpus (Pennington et …","url":["https://arxiv.org/pdf/1906.09012"]}
-{"year":"2019","title":"Learning from Personal Longitudinal Dialog Data","authors":["C Welch, V Pérez-Rosas, JK Kummerfeld, R Mihalcea…"],"snippet":"… Message Embeddings: We also obtain word vector representations for each message using the GloVe Common Crawl pre-trained model.19 We chose this word embedding over other off-theshelf options because the Common …","url":["https://sentic.net/personal-longitudinal-dialog-data.pdf"]}
-{"year":"2019","title":"Learning multilingual topics through aspect extraction from monolingual texts","authors":["J Huber, M Spiliopoulou - Proceedings of the Fifth International Workshop on …, 2019"],"snippet":"… Xu et al., 2018). It was trained on the CommonCrawl corpus, a general-purpose text corpus that includes text from several billion web pages; the GloVe embeddings were trained on 840 billion tokens. The GloVe set includes …","url":["http://www.aclweb.org/anthology/W19-0313"]}
-{"year":"2019","title":"Learning Outside the Box: Discourse-level Features Improve Metaphor Identification","authors":["J Mu, H Yannakoudakis, E Shutova - arXiv preprint arXiv:1904.02246, 2019"],"snippet":"… To learn representations, we use several widelyused embedding methods:4 GloVe We use 300-dimensional pre-trained GloVe embeddings (Pennington et al., 2014) trained on the Common Crawl corpus as representations of a lemma and its arguments …","url":["https://arxiv.org/pdf/1904.02246"]}
-{"year":"2019","title":"Learning Relational Fractals for Deep Knowledge Graph Embedding in Online Social Networks","authors":["J Zhang, L Tan, X Tao, D Wang, JJC Ying, X Wang - International Conference on Web …, 2019"],"snippet":"… Our twitter dataset was live streamed from a twitter API account and contains a maximum of 1675882 nodes and 160799842 links. The Google dataset was obtained from the repositories of common crawl and was sentilyzed from the stripped down WET file contents …","url":["https://link.springer.com/chapter/10.1007/978-3-030-34223-4_42"]}
-{"year":"2019","title":"Learning to Generate Personalized Product Descriptions","authors":["G Elad, I Guy, K Radinsky, S Novgorodov, B Kimelfeld - 2019"],"snippet":"… For the title representation, we used fastText word embeddings2 pre-trained on Common Crawl and Wikipedia [25, 33], weighted based on each word's TF-IDF score [4].3 In addition, we included as features the participant's demo …","url":["http://www.kiraradinsky.com/files/Learning_to_Generate_Personalized_Product_Descriptions.pdf"]}
-{"year":"2019","title":"Learning to Speak and Act in a Fantasy Text Adventure Game","authors":["J Urbanek, A Fan, S Karamcheti, S Jain, S Humeau… - arXiv preprint arXiv …, 2019","JUA Fan, SKSJS Humeau, EDT Rocktäschel…"],"snippet":"Page 1. Learning to Speak and Act in a Fantasy Text Adventure Game Jack Urbanek1 Angela Fan1,2 Siddharth Karamcheti1 Saachi Jain1 Samuel Humeau1 Emily Dinan1 Tim Rocktäschel1,3 Douwe Kiela1 Arthur Szlam1 Jason …","url":["https://arxiv.org/pdf/1903.03094","https://research.fb.com/wp-content/uploads/2019/11/Learning-to-Speak-and-Act-in-a-Fantasy-Text-Adventure-Game.pdf"]}
-{"year":"2019","title":"Learning Word Ratings for Empathy and Distress from Document-Level User Responses","authors":["J Sedoc, S Buechel, Y Nachmany, A Buffone, L Ungar - arXiv preprint arXiv …, 2019"],"snippet":"… (2013) using 10-fold crossvalidation. For word embeddings we used off-the-shelf Fasttext subword embeddings (Mikolov et al., 2018).4 The embeddings are trained with subword information on Common Crawl (600B tokens) …","url":["https://arxiv.org/pdf/1912.01079"]}
-{"year":"2019","title":"Leveraging Distributional and Relational Semantics for Knowledge Extraction from Textual Corpora","authors":["G ROSSIELLO, G SEMERARO, M DI CIANO - 2019"],"snippet":"Page 1. Page 2 …","url":["https://www.researchgate.net/profile/Gaetano_Rossiello/publication/333448156_Leveraging_Distributional_and_Relational_Semantics_for_Knowledge_Extraction_from_Textual_Corpora/links/5cee4fcca6fdcc18c8e9913b/Leveraging-Distributional-and-Relational-Semantics-for-Knowledge-Extraction-from-Textual-Corpora.pdf"]}
-{"year":"2019","title":"Leveraging End-to-End Speech Recognition with Neural Architecture Search","authors":["A Baruwa, M Abisiga, I Gbadegesin, A Fakunle - arXiv preprint arXiv:1912.05946, 2019"],"snippet":"… We train a 3-gram, 5-gram and a 7-gram language model on common crawl 1. The relative performances are summarised in tables 1 and 2. Decoding is done by beam-searching for the output y that maximizes φ(c) given by …","url":["https://arxiv.org/pdf/1912.05946"]}
-{"year":"2019","title":"Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text","authors":["O Feyisetan, T Diethe, T Drake - arXiv preprint arXiv:1910.08917, 2019"],"snippet":"Page 1. Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text Oluwaseyi Feyisetan Amazon sey@amazon.com Tom Diethe Amazon tdiethe@amazon.co.uk Thomas Drake Amazon draket@amazon.com …","url":["https://arxiv.org/pdf/1910.08917"]}
-{"year":"2019","title":"Leveraging Pretrained Image Classifiers for Language-Based Segmentation","authors":["D Golub, R Martín-Martín, A El-Kishky, S Savarese - arXiv preprint arXiv:1911.00830, 2019"],"snippet":"… With Word2Vec we first embed the target labels l and the labels in the set of possible proxy labels in a shared vector space using 300-dimensional GloVe embeddings [29] trained on the Common Crawl 840B word corpus. For labels that contains multiple words …","url":["https://arxiv.org/pdf/1911.00830"]}
-{"year":"2019","title":"Leveraging Unpaired Out-of-Domain Data for Image Captioning","authors":["X Chen, M Zhang, Z Wang, L Zuo, B Li, Y Yang - Pattern Recognition Letters, 2018"],"snippet":"Skip to main content …","url":["https://www.sciencedirect.com/science/article/pii/S0167865518309358"]}
-{"year":"2019","title":"Leveraging Web Semantic Knowledge in Word Representation Learning","authors":["H Liu, L Fang, JG Lou, Z Li - 2019"],"snippet":"… We extract a large collection of semantic lists from the Common Crawl data7 using the patterns defined in Table 1 and filter out entries that do not exist in the vocabulary of the training data … 6http://dumps.wikimedia.org/enwiki/ 7http://commoncrawl.org/ Page 5 …","url":["https://www.aaai.org/Papers/AAAI/2019/AAAI-LiuHaoyan.142.pdf"]}
-{"year":"2019","title":"Limsi-multisem at the ijcai semdeep-5 wic challenge: Context representations for word usage similarity estimation","authors":["AG Soler, M Apidianaki, A Allauzen - Proceedings of the 5th Workshop on Semantic …, 2019"],"snippet":"… Di- mensionality reduction is applied to a weighted average of the vectors of words in a sentence. Weighting is based on word frequency in Common Crawl. We use SIF in combination with 300- d GloVe vectors trained …","url":["https://www.aclweb.org/anthology/W19-5802"]}
-{"year":"2019","title":"Lingua Custodia at WMT'19: Attempts to Control Terminology","authors":["F Burlot - arXiv preprint arXiv:1907.04618, 2019"],"snippet":"… to the decoder. Page 2. 2 Baseline The training parallel data provided for the task consisted of nearly 10M sentences, including Europarl (Koehn, 2005), Common-crawl, Newscommentary and Bicleaner07. The former was …","url":["https://arxiv.org/pdf/1907.04618"]}
-{"year":"2019","title":"Linked Open Data Validity--A Technical Report from ISWS 2018","authors":["TA Ghor, E Agrawal, M Alam, O Alqawasmeh… - arXiv preprint arXiv …, 2019"],"snippet":"Page 1. Linked Open Data Validity A Technical Report from ISWS 2018 April 1, 2019 Bertinoro, Italy arXiv:1903.12554v1 [cs.DB] 26 Mar 2019 Page 2. Authors Main Editors Mehwish Alam, Semantic Technology Lab, ISTC-CNR …","url":["https://arxiv.org/pdf/1903.12554"]}
-{"year":"2019","title":"Linking artificial and human neural representations of language","authors":["J Gauthier, R Levy - arXiv preprint arXiv:1910.01244, 2019"],"snippet":"… contrasts between the 384 sentences tested. 9We use publicly available GloVe vectors computed on Common Crawl, available in the spaCy toolkit as en vectors web lg. Page 6. 3 Results We first present the performance of …","url":["https://arxiv.org/pdf/1910.01244"]}
-{"year":"2019","title":"LINSPECTOR: Multilingual Probing Tasks for Word Representations","authors":["GG Şahin, C Vania, I Kuznetsov, I Gurevych - arXiv preprint arXiv:1903.09442, 2019"],"snippet":"Page 1. LINSPECTOR Multilingual Probing Tasks for Word Representations Gözde Gül Sahin∗ UKP Lab / TU Darmstadt Clara Vania∗∗ ILCC / University of Edinburgh Ilia Kuznetsov UKP Lab / TU Darmstadt Iryna Gurevych UKP Lab / TU Darmstadt …","url":["https://arxiv.org/pdf/1903.09442"]}
-{"year":"2019","title":"LIUM's Contributions to the WMT2019 News Translation Task: Data and Systems for German-French Language Pairs","authors":["F Bougares, J Wottawa, A Baillot, L Barrault, A Bardet - … 2: Shared Task Papers, Day 1 …, 2019"],"snippet":"… As it can be seen from tables 1 and 2, the effect of the cleaning step is more pronounced for the noisy parallel corpora (ie ParaCrawl and Common Crawl) … Page 3. 131 #lines #token FR #token DE europarl-v7 1.7M 45.9M 40.9 …","url":["https://www.aclweb.org/anthology/W19-5307"]}
-{"year":"2019","title":"Local bow-tie structure of the web","authors":["Y Fujita, Y Kichikawa, Y Fujiwara, W Souma, H Iyetomi - Applied Network Science, 2019"],"snippet":"… This fact means that the absence of self-similarity between page level and host/domain levels. Meusel et al. (2014, 2015) investigated the publicly accessible crawl of the web gathered by the Common Crawl Foundation in 2012 (CC12) (Meusel et al. 2014; 2015) …","url":["https://link.springer.com/article/10.1007/s41109-019-0127-2"]}
-{"year":"2019","title":"Logical Layout Analysis using Deep Learning","authors":["A Zulfiqar, A Ul-Hasan, F Shafait"],"snippet":"… of the text zones. GloVE provides 300 dimensional vectors, one vector for each word. We have used the one trained on common crawl having 840 billion tokens and vectors for a total of 2.2 million words. Since we also want …","url":["https://tukl.seecs.nust.edu.pk/members/projects/conference/Logical-Layout-Analysis-using-Deep-Learning.pdf"]}
-{"year":"2019","title":"Longitudinal Analysis of Misuse of Bitcoin⋆","authors":["K Eldefrawy, A Gehani, A Matton"],"snippet":"… its labels). Seed data was used from previously published onion data sets, references to onions in a large collection of DNS resolver logs, and an open repository of (non-onion) web crawl data, called the Common Crawl. The …","url":["http://www.csl.sri.com/users/gehani/papers/ACNS-2019.Bitcoin_Study.pdf"]}
-{"year":"2019","title":"Look Who's Talking: Inferring Speaker Attributes from Personal Longitudinal Dialog","authors":["C Welch, V Pérez-Rosas, JK Kummerfeld, R Mihalcea - arXiv preprint arXiv …, 2019"],"snippet":"… The word embedding inputs to the context encoder are 300 dimensional. 8 Features Word Embeddings: We obtain word vector representations for each message using the GloVe Common Crawl pre-trained model [12]. We …","url":["https://arxiv.org/pdf/1904.11610"]}
-{"year":"2019","title":"Low Resource Sequence Tagging with Weak Labels","authors":["E Simpson, J Pfeiffer, I Gurevych"],"snippet":"… For FAMULUS, we use 300-dimensional German fastText embeddings (Grave et al. 2018), and for NER and PICO we use 300-dimensional English GloVe 3 embeddings trained on 840 billion tokens from Common Crawl. To …","url":["https://public.ukp.informatik.tu-darmstadt.de/UKP_Webpage/publications/2020/2020_AAAI_SE_LowResourceSequence.pdf"]}
-{"year":"2019","title":"Low Supervision, Low Corpus size, Low Similarity! Challenges in cross-lingual alignment of word embeddings: An exploration of the limitations of cross-lingual word …","authors":["A Dyer - 2019"],"snippet":"Page 1. Low Supervision, Low Corpus size, Low Similarity! Challenges in cross-lingual alignment of word embeddings An exploration of the limitations of cross-lingual word embedding alignment in truly low resource scenarios Andrew Dyer …","url":["http://www.diva-portal.org/smash/get/diva2:1365879/FULLTEXT01.pdf"]}
-{"year":"2019","title":"LSTM for Dialogue Breakdown Detection: Exploration of Different Model Types and Word Embeddings","authors":["M Hendriksen, A Leeuwenberg, MF Moens"],"snippet":"… The words are uncased. GloVe Common Crawl … The results presented in the Table 2, allow to conclude that GloVe Common Crawl demonstrate the best performance, the GloVe Twitter being the second best, the word2vec Google News is the worst. Page 9 …","url":["http://workshop.colips.org/wochat/@iwsds2019/documents/dbdc4-mariya-hendriksen-etal.pdf"]}
-{"year":"2019","title":"LTL-UDE at SemEval-2019 Task 6: BERT and Two-Vote Classification for Categorizing Offensiveness","authors":["P Aggarwal, T Horsmann, M Wojatzki, T Zesch - … of the 13th International Workshop on …, 2019"],"snippet":"… word representations. The resulting posting vector is re-scaled into the range zero to one. We use the pre-trained embeddings provided by Mikolov et al. (2018), which are trained on the common crawl corpus. Classifiers We …","url":["https://www.aclweb.org/anthology/S19-2121"]}
-{"year":"2019","title":"ltl. uni-due at SemEval-2019 Task 5: Simple but Effective Lexico-Semantic Features for Detecting Hate Speech in Twitter","authors":["H Zhang, M Wojatzki, T Horsmann, T Zesch - … of the 13th International Workshop on …, 2019"],"snippet":"… of LSTMs and CNNs (LSTM + CNN). We initialize all setups with the 300-dimensional word embeddings provided by Mikolov et al. (2018), which were trained on the common crawl corpus. Furthermore, in all setups, we use …","url":["https://www.aclweb.org/anthology/S19-2078"]}
-{"year":"2019","title":"Machine Reading of Clinical Notes for Automated ICD Coding","authors":["M Morisio, S Malacrino"],"snippet":"Page 1. Master degree course in Computer Engineering Master Degree Thesis Machine Reading of Clinical Notes for Automated ICD Coding Supervisor Prof. Maurizio Morisio Candidate Stefano Malacrin`o Internship tutors …","url":["https://webthesis.biblio.polito.it/10958/1/tesi.pdf"]}
-{"year":"2019","title":"Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness","authors":["A Bérard, I Calapodescu, M Dymetman, C Roux… - arXiv preprint arXiv …, 2019"],"snippet":"… data, we built a new training corpus named UGC (User Generated Content), closer to our domain, by combining: Multi UN, OpenSubtitles, Wikipedia, Books, Tatoeba, TED talks, ParaCrawl11 and Gourmet12 (See Table 3) …","url":["https://arxiv.org/pdf/1910.14589"]}
-{"year":"2019","title":"Mapping languages and demographics with georeferenced corpora","authors":["J Dunn, B Adams - 2019"],"snippet":"… To answer this question, we collect and analyze two large global-scale datasets: web-crawled data from the Common Crawl (16.65 billion words) and social media data from Twitter (4.14 billion words). This paper evaluates demographic-type informa …","url":["https://ir.canterbury.ac.nz/bitstream/handle/10092/17132/GeoComputation_19.pdf?sequence=2"]}
-{"year":"2019","title":"Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yor\\ub\\'a and Twi","authors":["JO Alabi, K Amponsah-Kaakyire, DI Adelani… - arXiv preprint arXiv …, 2019"],"snippet":"… The resource par excellence is Wikipedia2, an online encyclopedia currently available in 307 languages3. Other initiatives such as Common Crawl4 or the Jehovahs Witnesses site5 are also repositories for multilingual …","url":["https://arxiv.org/pdf/1912.02481"]}
-{"year":"2019","title":"Massively multilingual transfer for NER","authors":["A Rahimi, Y Li, T Cohn - Proceedings of the 57th Conference of the Association …, 2019"],"snippet":"Page 1. Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 151–164 Florence, Italy, July 28 - August 2, 2019. c 2019 Association for Computational Linguistics 151 Massively Multilingual Transfer for NER …","url":["https://www.aclweb.org/anthology/P19-1015"]}
-{"year":"2019","title":"MASTER UNIVERSITARIO EN INGENIERÍA DE TELECOMUNICACION","authors":["DB SANCHEZ - 2019"],"snippet":"Page 1. M´ASTER UNIVERSITARIO EN INGENIERÍA DE TELECOMUNICACI´ON TRABAJO FIN DE M´ASTER DESING AND DEVELOPMENT OF A HATE SPEECH DETECTOR IN SOCIAL NETWORKS BASED ON DEEP LEARNING TECHNOLOGIES …","url":["http://oa.upm.es/55618/1/TESIS_MASTER_DIEGO_BENITO_SANCHEZ_2019.pdf"]}
-{"year":"2019","title":"Measuring Gender Bias in Word Embeddings across Domains and Discovering New Gender Bias Word Categories","authors":["K Chaloner, A Maldonado - Proceedings of the First Workshop on Gender Bias in …, 2019"],"snippet":"… WEAT's authors applied these tests to the publicly-available GloVe embeddings trained on the English-language “Common Crawl” corpus (Pennington et al., 2014) as well as the Skip-Gram (word2vec) embeddings …","url":["https://www.aclweb.org/anthology/W19-3804"]}
-{"year":"2019","title":"Medical Word Embeddings for Spanish: Development and Evaluation","authors":["F Soares, M Villegas, A Gonzalez-Agirre, M Krallinger… - Proceedings of the 2nd …, 2019"],"snippet":"… makes available Word2Vec models pre-trained on about 100 billion words from Google News corpus in English1. Regarding other languages, on FastText website2 one can download pre-trained embeddings for 157 lan …","url":["https://www.aclweb.org/anthology/W19-1916"]}
-{"year":"2019","title":"Meemi: Finding the Middle Ground in Cross-lingual Word Embeddings","authors":["Y Doval, J Camacho-Collados, L Espinosa-Anke… - arXiv preprint arXiv …, 2019"],"snippet":"… 10 Page 11. the WaCky project [23], containing 2 and 0.8 billion words, respectively.6 For Finnish and Russian, we use their corresponding Common Crawl monolingual corpora from the Machine Translation of News Shared Task 20167, composed of …","url":["https://arxiv.org/pdf/1910.07221"]}
-{"year":"2019","title":"Membership Inference Attacks on Sequence-to-Sequence Models","authors":["S Hisamoto, M Post, K Duh - arXiv preprint arXiv:1904.05506, 2019"],"snippet":"… For example, e (d) i with d = l1 and i = 1 might refer to the first sentence in the Europarl subcorpus, while e (d) i with d = l2 and i = 1 might refer to the first sentence in the CommonCrawl subcorpus … CommonCrawl 5,000 5,000 2,389,123 2,379,123 N/A …","url":["https://arxiv.org/pdf/1904.05506"]}
-{"year":"2019","title":"Metaphor Interpretation Using Word Embeddings","authors":["K Bar, N Dershowitz, L Dankin"],"snippet":"… relatively large corpus. Specifically, we use DepCC,1 a dependency-parsed “web-scale corpus” based on CommonCrawl.2 There are 365 million documents in the corpus, comprising about 252B tokens. Among other preprocessing …","url":["https://pdfs.semanticscholar.org/2033/a3f7b8b53ea277a811ac450139422793b08b.pdf"]}
-{"year":"2019","title":"Methods and apparatus for detection of malicious documents using machine learning","authors":["JD Saxe, R HARANG - US Patent App. 16/257,749, 2019"],"snippet":"… decision tree, etc.). The memory 120 includes one or more datasets 112 (eg, a VirusTotal dataset and/or a Common Crawl dataset, as described in further detail below) and one or more training models 124. The malware detection …","url":["https://patentimages.storage.googleapis.com/fa/f8/d7/5843fb31e01d95/US20190236273A1.pdf"]}
-{"year":"2019","title":"Microsoft Research Asia's Systems for WMT19","authors":["Y Xia, X Tan, F Tian, F Gao, W Chen, Y Fan, L Gong…"],"snippet":"… Dataset We concatenate “Europarl v9”, “News Commentary v14”, “Common Crawl corpus” and “Document-split Rapid corpus” as the ba- sic bilingual … We merge the “commoncrawl”, “europarl-v7” and part of “de-fr.bicleaner07” …","url":["http://www.statmt.org/wmt19/pdf/WMT0048.pdf"]}
-{"year":"2019","title":"MIDAS: A Dialog Act Annotation Scheme for Open Domain Human Machine Spoken Conversations","authors":["D Yu, Z Yu - arXiv preprint arXiv:1908.10023, 2019"],"snippet":"… An example can be seen in the last USER2 utterance in Table 1. Word em- beddings are pre-trained with fastText (Mikolov et al., 2018) using Common Crawl. We evaluate the segmentation model on human labeled 2K human utterances of collected data …","url":["https://arxiv.org/pdf/1908.10023"]}
-{"year":"2019","title":"Mining Discourse Markers for Unsupervised Sentence Representation Learning","authors":["D Sileo, T Van-De-Cruys, C Pradel, P Muller - arXiv preprint arXiv:1903.11850, 2019"],"snippet":"… We use sentences from the Depcc corpus (Panchenko et al., 2017), which consists of En- glish texts harvested from commoncrawl web data … Word embeddings are fixed GloVe embeddings with 300 dimensions, trained …","url":["https://arxiv.org/pdf/1903.11850"]}
-{"year":"2019","title":"Mix-review: Alleviate Forgetting in the Pretrain-Finetune Framework for Neural Language Generation Models","authors":["T He, J Liu, K Cho, M Ott, B Liu, J Glass, F Peng - arXiv preprint arXiv:1910.07117, 2019"],"snippet":"… For pre-training, we use the large-scale CCNEWS data (Bakhtin et al., 2019) which is a de- duplicated subset of the English portion of the CommonCrawl news data-set1. The dataset contains news articles published worldwide …","url":["https://arxiv.org/pdf/1910.07117"]}
-{"year":"2019","title":"MLT-DFKI at CLEF eHealth 2019: Multi-label Classification of ICD-10 Codes with BERT","authors":["S Amin, G Neumann, K Dunfield, A Vechkaeva… - CLEF (Working Notes), 2019"],"snippet":"… have stronger linguistic signals to classify the classes where German models make mistakes [1]. The baseline proved to be a strong one, with the highest precision of all and outperforming HAN and CNN models, for both German …","url":["https://www.researchgate.net/profile/Saadullah_Amin2/publication/335681972_MLT-DFKI_at_CLEF_eHealth_2019_Multi-label_Classification_of_ICD-10_Codes_with_BERT/links/5d742a00299bf1cb809043cd/MLT-DFKI-at-CLEF-eHealth-2019-Multi-label-Classification-of-ICD-10-Codes-with-BERT.pdf"]}
-{"year":"2019","title":"Mono-and Cross-lingual Semantic Word Similarity for Urdu Language","authors":["G Fatima - 2019"],"snippet":"Page 1. I Monoand Cross-lingual Semantic Word Similarity for Urdu Language By Ghazeefa Fatima CIIT/FA17-RCS-016/LHR MS Thesis In Computer Science COMSATS University Islamabad Lahore Campus Page …","url":["http://dspace.cuilahore.edu.pk/xmlui/bitstream/handle/123456789/1571/Thesis.pdf?sequence=1"]}
-{"year":"2019","title":"MoRTy: Unsupervised Learning of Task-specialized Word Embeddings by Autoencoding","authors":["N Rethmeier, B Plank - Proceedings of the 4th Workshop on Representation …, 2019"],"snippet":"… Hence, we demonstrate the method's application for single-task, multi-task, small, medium and web-scale (common crawl) corpus-size settings (Section 4). Learning to scale-up by pretraining on more (un-)labeled data is both: (a) not always possible in low-resource …","url":["https://www.aclweb.org/anthology/W19-4307"]}
-{"year":"2019","title":"Multi-class Document Classification Using Improved Word Embeddings","authors":["BA Rabut, AC Fajardo, RP Medina - Proceedings of the 2nd International Conference …, 2019"],"snippet":"… ACM ISBN 978-1-4503-7290-9/19/10…$15.00 https://doi.org/10.1145/3366650.3366661 42 Page 2. Common crawl)[7]. The pre-trained word embedding vectors serve as input in the classification algorithm for evaluation and prediction …","url":["https://dl.acm.org/citation.cfm?id=3366661"]}
-{"year":"2019","title":"Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering","authors":["L Zhou, K Small - arXiv preprint arXiv:1911.06192, 2019"],"snippet":"… For experiments with GloVe embeddings, we use GloVe embeddings pre-trained on Common Crawl dataset.3 The dimension of GloVe embeddings is 300, and the dimension of character-level embeddings is 100, such that Dw = 400 …","url":["https://arxiv.org/pdf/1911.06192"]}
-{"year":"2019","title":"Multi-Granular Text Encoding for Self-Explaining Categorization","authors":["Z Wang, Y Zhang, M Yu, W Zhang, L Pan, L Song, K Xu… - arXiv preprint arXiv …, 2019"],"snippet":"… for each set. Hyperparameters We use the 300-dimensional GloVe word vectors pre-trained from the 840B Common Crawl corpus (Pennington et al., 2014), and set the hidden size as 100 for node embeddings. We apply dropout …","url":["https://arxiv.org/pdf/1907.08532"]}
-{"year":"2019","title":"Multi-Hop Paragraph Retrieval for Open-Domain Question Answering","authors":["Y Feldman, R El-Yaniv - arXiv preprint arXiv:1906.06606, 2019"],"snippet":"Page 1. Multi-Hop Paragraph Retrieval for Open-Domain Question Answering Yair Feldman and Ran El-Yaniv Department of Computer Science Technion – Israel Institute of Technology Haifa, Israel {yairf11, rani}@cs.technion.ac.il Abstract …","url":["https://arxiv.org/pdf/1906.06606"]}
-{"year":"2019","title":"Multi-Resolution Models for Learning Multilevel Abstract Representation with Application to Information Retrieval","authors":["T Cakaloglu - 2019"],"snippet":"Page 1. MULTI-RESOLUTION MODELS FOR LEARNING MULTILEVEL ABSTRACT REPRESENTATION WITH APPLICATION TO INFORMATION RETRIEVAL A Dissertation Submitted to the Graduate School University of Arkansas at Little Rock …","url":["http://search.proquest.com/openview/4bce4201a6d742c4c771e08b17dec0cb/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2019","title":"Multi-Team: A Multi-attention, Multi-decoder Approach to Morphological Analysis.","authors":["A Ustün, R van der Goot, G Bouma, G van Noord"],"snippet":"… 2018). For FastText, two sets of pre-trained embeddings are available: one is trained only on Wikipedia (Bojanowski et al., 2017), whereas the newer versions are also trained on CommonCrawl (Grave et al., 2018). Whenever …","url":["http://www.robvandergoot.com/doc/sigmorphon2019.pdf"]}
-{"year":"2019","title":"Multilingual Culture-Independent Word Analogy Datasets","authors":["M Ulčar, M Robnik-Šikonja - arXiv preprint arXiv:1911.10038, 2019"],"snippet":"… language is shown in the Table 6. Table 6: Percentage of constructed analogy pairs covered by the first 200,000 word vectors from common crawl fastText embeddings. Language Coverage (%) Croatian 81.67 English 97.05 …","url":["https://arxiv.org/pdf/1911.10038"]}
-{"year":"2019","title":"Multilingual Fake News Detection with Satire","authors":["G Guibon, L Ermakova, H Seffih, A Firsov…"],"snippet":"… Detection of Deception. Non-verbal communication (2014), https://nvc.uvt.nl/pdf/7.pdf 6. Bevendorff, J., Stein, B., Hagen, M., Potthast, M.: Elastic chatnoir: Search engine for the clueweb and the common crawl. In: Pasi, G., Piwowarski …","url":["https://www.researchgate.net/profile/Guillaume_Le_Noe-Bienvenu/publication/332803834_Multilingual_Fake_News_Detection_with_Satire_on_Vaccination_Topic/links/5d24917a458515c11c1f8724/Multilingual-Fake-News-Detection-with-Satire-on-Vaccination-Topic.pdf"]}
-{"year":"2019","title":"Multilingual is not enough: BERT for Finnish","authors":["A Virtanen, J Kanerva, R Ilo, J Luoma, J Luotolahti… - arXiv preprint arXiv …, 2019"],"snippet":"… Second, we selected texts from the Common Crawl project6 by running aa map-reduce language detection job on the plain text material from Common Crawl. These sources were supplemented with plain text extracted …","url":["https://arxiv.org/pdf/1912.07076"]}
-{"year":"2019","title":"Multilingual Sentence-Level Bias Detection in Wikipedia","authors":["D Aleksandrova, F Lareau, PA Ménard"],"snippet":"… Same BOW n-gram size and BOW size and value type as SGD. 5Available for 157 languages, pretrained on Common Crawl and Wikipedia (Grave et al., 2018) https:// fasttext.cc/docs/en/crawl-vectors.html 6Version 0.21.2 of the sklearn toolkit …","url":["https://www.researchgate.net/profile/Desislava_Aleksandrova/publication/334612399_Multilingual_Sentence-Level_Bias_Detection_in_Wikipedia/links/5d5bd0c392851c37636bfdf2/Multilingual-Sentence-Level-Bias-Detection-in-Wikipedia.pdf"]}
-{"year":"2019","title":"Multimodal deep networks for text and image-based document classification","authors":["N Audebert, C Herold, K Slimani, C Vidal - APIA"],"snippet":"… For both methods, we use the SpaCy small English model [33] to perform the tokenization and punctuation removal. Individual word embeddings are then inferred using FastText [29] pretrained on the Common Crawl dataset …","url":["https://www.irit.fr/pfia2019/wp-content/uploads/2019/07/Actes_CH_PFIA2019.pdf#page=14"]}
-{"year":"2019","title":"Multimodal Machine Translation with Embedding Prediction","authors":["T Hirasawa, H Yamagishi, Y Matsumura, M Komachi - arXiv preprint arXiv …, 2019"],"snippet":"… model. “+ pretrained” models are initialized with pretrained embeddings. 2018). These word embeddings are trained on Wikipedia and Common Crawl using the CBOW algorithm, and the dimension is 300. The embedding …","url":["https://arxiv.org/pdf/1904.00639"]}
-{"year":"2019","title":"Multimodal Sentiment Analysis Using Deep Learning","authors":["R Sharma, N Le Tan, F Sadat - 2018 17th IEEE International Conference on Machine …, 2018"],"snippet":"… For the CNN model we used pre-trained word embeddings (GloVe 840B.300d). This is a 300-dimensional word embedding trained on 840 billion tokens from the common crawl dataset. The maximum sequence length is 200 …","url":["https://ieeexplore.ieee.org/abstract/document/8614265/"]}
-{"year":"2019","title":"Named entity recognition for Polish","authors":["M Marcińczuk, A Wawer - Poznan Studies in Contemporary Linguistics, 2019"],"snippet":"AbstractIn this article we discuss the current state-of-the-art for named entity recognition for Polish. We present publicly available resources and open-source tools for named entity recognition. The overview includes various …","url":["https://www.degruyter.com/view/j/psicl.2019.55.issue-2/psicl-2019-0010/psicl-2019-0010.xml"]}
-{"year":"2019","title":"Named Entity Recognition for Social Media Text","authors":["Y Zhang - 2019"],"snippet":"… We use two different pre-trained word embeddings based on Common Crawl data, which contains 840 billion tokens and 2.2 million vocabulary and Twitter data which contains 2 billion tweets, 27 billion tokens, and 1.2 million vocabulary …","url":["https://uu.diva-portal.org/smash/get/diva2:1366031/FULLTEXT01.pdf"]}
-{"year":"2019","title":"Named Entity Recognition Using Gazetteer of Hierarchical Entities","authors":["M Štravs, J Zupančič - … Conference on Industrial, Engineering and Other …, 2019"],"snippet":"… To summarize, the proposed entity recognition method was tested using two languages (Slovenian and English), six different distance measures, and two different vector embeddings from Wikipedia (Wiki WV) and Common Crawl (CC WV) …","url":["https://link.springer.com/chapter/10.1007/978-3-030-22999-3_65"]}
-{"year":"2019","title":"Named-entity recognition in Czech historical texts: Using a CNN-BiLSTM neural network model","authors":["H Hubková - 2019"],"snippet":"… We also tried to work with published pretrained word embeddings of contemporary Czech words provided by fastText6. These were trained on more than 178 millions of tokens from Wikipedia and 13 billions tokens based on common crawl (Grave et al., 2018) …","url":["http://www.diva-portal.org/smash/get/diva2:1325355/FULLTEXT01.pdf"]}
-{"year":"2019","title":"Natural Language Processing for Book Recommender Systems","authors":["H Alharthi - 2019"],"snippet":"Page 1. Natural Language Processing for Book Recommender Systems by Haifa Alharthi Thesis submitted in partial fulfillment of the requirements for the PhD degree in Computer Science School of Electrical Engineering and Computer Science Faculty of Engineering …","url":["https://www.ruor.uottawa.ca/bitstream/10393/39134/1/Alharthi_Haifa_2019_thesis.pdf"]}
-{"year":"2019","title":"Natural language processing using context-specific word vectors","authors":["B McCann, C Xiong, R Socher - US Patent App. 15/982,841, 2018"],"snippet":"… in the second language. In some examples, training of an MT-LSTM of the encoder 310 uses fixed 300-dimensional word vectors, such as the CommonCrawl-840B GloVe model for English word vectors. These word vectors …","url":["https://patentimages.storage.googleapis.com/49/87/1a/0d4e316e8e4194/US20180373682A1.pdf"]}
-{"year":"2019","title":"Naver Labs Europe's Systems for the WMT19 Machine Translation Robustness Task","authors":["A Bérard, I Calapodescu, C Roux - arXiv preprint arXiv:1907.06488, 2019"],"snippet":"… 3.1 Pre-processing CommonCrawl filtering We first spent efforts on filtering and cleaning the WMT data (in particular CommonCrawl) … We filtered CommonCrawl as follows: we trained a baseline FR→EN model on WMT without …","url":["https://arxiv.org/pdf/1907.06488"]}
-{"year":"2019","title":"Nested Variational Autoencoder for Topic Modeling on Microtexts with Word Vectors","authors":["T Trinh, T Quan, T Mai - arXiv preprint arXiv:1905.00195, 2019"],"snippet":"Page 1. Noname manuscript No. (will be inserted by the editor) Nested Variational Autoencoder for Topic Modeling on Microtexts with Word Vectors Trung Trinh · Tho Quan · Trung Mai Received: date / Accepted: date Abstract …","url":["https://arxiv.org/pdf/1905.00195"]}
-{"year":"2019","title":"NeuMorph: Neural Morphological Tagging for Low-Resource Languages—An Experimental Study for Indic Languages","authors":["A Chakrabarty, A Chaturvedi, U Garain - ACM Transactions on Asian and Low …, 2019"],"snippet":"Page 1. 16 NeuMorph: Neural Morphological Tagging for Low-Resource Languages— An Experimental Study for Indic Languages ABHISEK CHAKRABARTY, AKSHAY CHATURVEDI, and UTPAL GARAIN, Indian Statistical Institute, India …","url":["https://dl.acm.org/citation.cfm?id=3342354"]}
-{"year":"2019","title":"Neural Conversation Recommendation with Online Interaction Modeling","authors":["X Zeng, J Li, L Wang, KF Wong"],"snippet":"Page 1. Neural Conversation Recommendation with Online Interaction Modeling Xingshan Zeng1,2, Jing Li3∗, Lu Wang4, Kam-Fai Wong1,2 1The Chinese University of Hong Kong, Hong Kong, China 2MoE Key Laboratory …","url":["https://www.ccs.neu.edu/home/luwang/papers/EMNLP2019_zeng_li_wang_wong.pdf"]}
-{"year":"2019","title":"Neural Facet Detection on Medical Resources","authors":["T Steffek - 2019"],"snippet":"Page 1. Neural Facet Detection on Medical Resources Thomas Steffek April 2, 2019 Page 2. Page 3. Beuth Hochschule für Technik Fachbereich VI - Informatik und Medien Database Systems and Text-based Information Systems (DATEXIS) Bachelor's thesis …","url":["https://prof.beuth-hochschule.de/fileadmin/prof/aloeser/Bachelorarbeit_Thomas-Steffek_with-title-page-1.1.pdf"]}
-{"year":"2019","title":"Neural Feature Extraction for Contextual Emotion Detection","authors":["E Mohammadi, H Amini, L Kosseim"],"snippet":"… pretrained word embeddings. As the first word embedder, we chose GloVe (Pennington et al., 2014), which is pretrained on 840B tokens of web data from Common Crawl, and provides 300d vectors as word embeddings. As our sec …","url":["https://www.researchgate.net/profile/Hessam_Amini/publication/335704122_Neural_Feature_Extraction_for_Contextual_Emotion_Detection/links/5d76d6764585151ee4ab0908/Neural-Feature-Extraction-for-Contextual-Emotion-Detection.pdf"]}
-{"year":"2019","title":"Neural Grammatical Error Correction by Simulating the Human Learner and the Human Proofreader","authors":["F Gaim, JW Chung, JC Park - 한국정보과학회 학술발표논문집, 2018"],"snippet":"… For this and the contrastive learning, we use a large 5-gram language model trained on the Common Crawl data [8]. Training and Decoding: To effectively handle out-of- vocabulary words, we use sub-word level tokenization and …","url":["http://www.dbpia.co.kr/Journal/ArticleDetail/NODE07613671"]}
-{"year":"2019","title":"Neural Machine Translation for English–Kazakh with Morphological Segmentation and Synthetic Data","authors":["A Toral, L Edman, G Yeshmagambetova, J Spenader - … 2: Shared Task Papers, Day 1 …, 2019"],"snippet":"… 7.5 0.19 0.16 Wikititles 117.0 0.23 0.19 Table 1: Preprocessed EN–KK parallel training data. Words (M) Corpus Sentences (k) EN RU Common crawl 871.8 20.82 19.97 News-comm … Corpus Threshold Pairs left (k) CommonCrawl 0.7323 568.50 News Comm …","url":["https://www.aclweb.org/anthology/W19-5343"]}
-{"year":"2019","title":"Neural network learning engine","authors":["CM Ormerod - US Patent App. 16/286,566, 2019"],"snippet":"… skill and not to limit the invention to any one embodiment, commercial word embedding tools can include Google News word embedding, which has been trained on an extensive corpus of news items, and/or GloVe word …","url":["https://patentimages.storage.googleapis.com/94/fd/43/d4a3cbb7706fec/US20190266234A1.pdf"]}
-{"year":"2019","title":"Neural network-based approaches for biomedical relation classification: A review","authors":["Y Zhang, H Lin, Z Yang, J Wang, Y Sun, B Xu, Z Zhao - Journal of Biomedical …, 2019"],"snippet":"… Word2vec, Google news, https://code.google.com/archive/p/word2vec. GloVe, Wikipedia, Gigaword, Common Crawl, Twitter, https://nlp.stanford. edu/projects/glove. fastText, Wikipedia, UMBC corpus, news corpus …","url":["https://www.sciencedirect.com/science/article/pii/S1532046419302138"]}
-{"year":"2019","title":"Neural NLP models under low-supervision scenarios","authors":["Y Zhang - 2019"],"snippet":"Page 1. Copyright by Ye Zhang 2019 Page 2. The Dissertation Committee for Ye Zhang certifies that this is the approved version of the following dissertation: Neural NLP Models Under Low-supervision Scenarios Committee: Matthew A Lease, Supervisor …","url":["https://repositories.lib.utexas.edu/bitstream/handle/2152/75032/ZHANG-DISSERTATION-2019.pdf?sequence=1"]}
-{"year":"2019","title":"Neural Text Style Transfer via Denoising and Reranking","authors":["J Lee, Z Xie, C Wang, M Drach, D Jurafsky, AY Ng - … of the Workshop on Methods for …, 2019"],"snippet":"… 3. Fluency The post-transfer sentence should remain grammatical and fluent. We use the average log probability of the sentence posttransfer with respect to a language model trained on CommonCrawl as our measure of fluency …","url":["https://www.aclweb.org/anthology/W19-2309"]}
-{"year":"2019","title":"NLNDE: The Neither-Language-Nor-Domain-Experts' Way of Spanish Medical Document De-Identification","authors":["L Lange, H Adel, J Strötgen - 2019"],"snippet":"… S2 (FLAIR+fastText): In contrast to all other runs, the second run uses only domain-independent embeddings, ie, embeddings that have been trained on standard narrative and news data from Common Crawl and Wikipedia …","url":["http://ceur-ws.org/Vol-2421/MEDDOCAN_paper_5.pdf"]}
-{"year":"2019","title":"NLP@ UIOWA at SemEval-2019 Task 6: Classifying the Crass using Multi-windowed CNNs","authors":["J Rusert, P Srinivasan - Proceedings of the 13th International Workshop on …, 2019"],"snippet":"… Word embeddings for Non-Out of Vocabulary (OOV) words are obtained from Glove (Pennington et al., 2014) which has been trained on Twitter data3. Experiments were also conducted with Glove common crawl data, but no visible improvement was found …","url":["https://www.aclweb.org/anthology/S19-2125"]}
-{"year":"2019","title":"Noisy Parallel Corpus Filtering through Projected Word Embeddings","authors":["M Kurfalı, R Östling - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… Larger monolingual corpora based on Wikipedia and common crawl data were also provided.2 To train our model, we use all the parallel data available for the English-Sinhala and EnglishNepali pairs (summarized …","url":["https://www.aclweb.org/anthology/W19-5438"]}
-{"year":"2019","title":"NRC Parallel Corpus Filtering System for WMT 2019","authors":["G Bernier-Colborne, C Lo - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… embedding models. Common Crawl data was not used to train the bilingual word embeddings. 2.2 … representation layer. We used XLM to train a model using almost all the available data, except for the monolingual English Common Crawl data. This …","url":["https://www.aclweb.org/anthology/W19-5434"]}
-{"year":"2019","title":"Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes","authors":["J Cao, M Tanana, ZE Imel, E Poitras, DC Atkins…"],"snippet":"Page 1. Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes Jie Cao†, Michael Tanana‡, Zac E. Imel‡, Eric Poitras‡, David C. Atkins♦, Vivek Srikumar† †School of Computing, University of Utah …","url":["https://svivek.com/research/publications/cao2019observing.pdf"]}
-{"year":"2019","title":"Observing LOD Using Equivalent Set Graphs: It Is Mostly Flat and Sparsely Linked","authors":["L Asprino, W Beek, P Ciancarini, F van Harmelen… - International Semantic Web …, 2019"],"snippet":"… The two largest available crawls of LOD available today are WebDataCommons and LOD-a-lot. WebDataCommons 2 [12] consists of \\(\\sim \\)31B triples that have been extracted from the CommonCrawl datasets (November 2018 version) …","url":["https://link.springer.com/chapter/10.1007/978-3-030-30793-6_4"]}
-{"year":"2019","title":"Observing the LOD Cloud using Equivalent Set Graphs: the LOD Cloud is mostly flat and sparsely linked","authors":["L Asprino, W Beek, P Ciancarini, F van Harmelen…"],"snippet":"… The two largest available crawls of LOD available today are WebDataCommons and LOD-a-lot. WebDataCommons5 [12] consists of ∼31B triples that have been extracted from the CommonCrawl datasets (November 2018 version) …","url":["https://www.cs.vu.nl/~frankh/postscript/ISWC2019-LODanalytics.pdf"]}
-{"year":"2019","title":"OECD Analytical Database on Individual Multinationals and their Affiliates (ADIMA)","authors":["G Pilgrim, N Ahmad, D Doyle - 2019"],"snippet":"… Secondly, information from MNE webpages is used from an open source 'copy of the internet' generated via web crawling from the Common Crawl 4 . This process develops a graph of the links between companies, from …","url":["https://www.gtap.agecon.purdue.edu/resources/download/9310.docx"]}
-{"year":"2019","title":"Offensive Language and Hate Speech Detection for Danish","authors":["GI Sigurbergsson, L Derczynski - arXiv preprint arXiv:1908.04531, 2019"],"snippet":"… sample of text. Pre-trained Embeddings. The pre-trained FastText [24] embeddings are trained on data from the Common Crawl project and Wikipedia, in 157 languages (including English and Danish). FastText also provides …","url":["https://arxiv.org/pdf/1908.04531"]}
-{"year":"2019","title":"On extracting data from tables that are encoded using HTML","authors":["JC Roldán, P Jiménez, R Corchuelo - Knowledge-Based Systems, 2019"],"snippet":"Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S095070511930509X"]}
-{"year":"2019","title":"On Implementing the Binary Interpolative Coding Algorithm","authors":["GE PIBIRI - 2019"],"snippet":"… Table 4. Decoding time measured in average nanoseconds spent per decoded integer, for the run-aware implementation (ra) and for the not run-aware implementation. • CCNews is an English subset of the freely available news from CommonCrawl 3, consisting of …","url":["http://pages.di.unipi.it/pibiri/papers/BIC.pdf"]}
-{"year":"2019","title":"On Measuring and Mitigating Biased Inferences of Word Embeddings","authors":["S Dev, T Li, J Phillips, V Srikumar - arXiv preprint arXiv:1908.09369, 2019"],"snippet":"Page 1. arXiv:1908.09369v1 [cs.CL] 25 Aug 2019 On Measuring and Mitigating Biased Inferences of Word Embeddings Sunipa Dev, Tao Li, Jeff Phillips, Vivek Srikumar School of Computing University of Utah Abstract Word …","url":["https://arxiv.org/pdf/1908.09369"]}
-{"year":"2019","title":"On Measuring Social Biases in Sentence Encoders","authors":["C May, A Wang, S Bordia, SR Bowman, R Rudinger - arXiv preprint arXiv:1903.10561, 2019"],"snippet":"Page 1. On Measuring Social Biases in Sentence Encoders Chandler May1 Alex Wang2 Shikha Bordia2 Samuel R. Bowman2 Rachel Rudinger1 1Johns Hopkins University 2New York University {cjmay,rudinger}@jhu.edu {alexwang,sb6416,bowman}@nyu.edu Abstract …","url":["https://arxiv.org/pdf/1903.10561"]}
-{"year":"2019","title":"On Optimally Partitioning Variable-Byte Codes","authors":["GE Pibiri, R Venturini - IEEE Transactions on Knowledge and Data …, 2019"],"snippet":"Page 1. 1041-4347 (c) 2018 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/8691421/"]}
-{"year":"2019","title":"On relevance of enriching word embeddings in solving Natural Language Inference problem","authors":["T Wesołowski"],"snippet":"Page 1. Jagiellonian University Faculty of Mathematics and Computer Science Theoretical Computer Science Stationary Studies Index number: 1079621 Tomasz Wesołowski On relevance of enriching word embeddings in solving Natural Language Inference problem …","url":["http://algo.edu.pl/OnRelevanceOfWordEmbeddings.pdf"]}
-{"year":"2019","title":"On Slicing Sorted Integer Sequences","authors":["GE Pibiri - arXiv preprint arXiv:1907.01032, 2019"],"snippet":"… 2009. • CCNews is a dataset of news freely available from CommonCrawl: http://commoncrawl.org/ 2016/10/news-dataset-available. Precisely, the datasets consists of the news appeared from 09/01/16 to 30/03/18. Identifiers …","url":["https://arxiv.org/pdf/1907.01032"]}
-{"year":"2019","title":"On the Effect of Low-Frequency Terms on Neural-IR Models","authors":["S Hofstätter, N Rekabsaz, C Eickhoff, A Hanbury - arXiv preprint arXiv:1904.12683, 2019"],"snippet":"… collection. The details of the resulting 1Provided in the form of evaluation tuples: top1000.dev.tsv 242B lower-cased (CommonCrawl) from: https://nlp.stanford.edu/ projects/glove/ Table 1: Left: Details of the vocabularies. Right …","url":["https://arxiv.org/pdf/1904.12683"]}
-{"year":"2019","title":"On the Robustness of Unsupervised and Semi-supervised Cross-lingual Word Embedding Learning","authors":["Y Doval, J Camacho-Collados, L Espinosa-Anke… - arXiv preprint arXiv …, 2019"],"snippet":"… google.com/site/rmyeid/projects/polyglot 2The sources of the web-corpora are: UMBC (Han et al., 2013), 1-billion (Cardellino, 2016), itWaC and sdeWaC (Ba- roni et al., 2009), Hamshahri (AleAhmad et al., 2009), and Common Crawl downloaded from http://www …","url":["https://arxiv.org/pdf/1908.07742"]}
-{"year":"2019","title":"On Using Machine Learning to Identify Knowledge in API Reference Documentation","authors":["D Fucci, A Mollaalizadehbahnemiri, W Maalej - arXiv preprint arXiv:1907.09807, 2019"],"snippet":"… For the deep learning classifiers in our benchmark, we train GloVe [19] embeddings based on four large corpora, summarized in Table 3. The Common Crawl (CC) is a pre-trained embedding downloaded in …","url":["https://arxiv.org/pdf/1907.09807"]}
-{"year":"2019","title":"On Using SpecAugment for End-to-End Speech Translation","authors":["P Bahar, A Zeyer, R Schlüter, H Ney"],"snippet":"… For MT training, we use the TED, and the OpenSubtitles2018 corpora, as well as the data provided by the WMT 2018 evaluation (Europarl, ParaCrawl, CommonCrawl, News Commentary, and Rapid), a total of 65M lines of parallel sentences …","url":["https://www-i6.informatik.rwth-aachen.de/publications/download/1122/Bahar-IWSLT-2019.pdf"]}
-{"year":"2019","title":"One Epoch Is All You Need","authors":["A Komatsuzaki - arXiv preprint arXiv:1906.06669, 2019"],"snippet":"… Trinh & Le (2018) pointed out that CommonCrawl contains a large portion of corrupt samples, which makes it unsuitable for the training. The proportion of the corrupt samples in CommonCrawl is substantially higher than 50 …","url":["https://arxiv.org/pdf/1906.06669"]}
-{"year":"2019","title":"Online Parallel Data Extraction with Neural Machine Translation","authors":["D Ruiter - 2019"],"snippet":"Page 1. Universität des Saarlandes Master's Thesis Online Parallel Data Extraction with Neural Machine Translation submitted in fulfillment of the degree requirements of the MSc in Language Science and Technology at Saarland University …","url":["https://www.clubs-project.eu/assets/publications/other/MSc_Thesis_Ruiter.pdf"]}
-{"year":"2019","title":"Ontological Traceability using Natural Language Processing","authors":["R Benitez - 2019"],"snippet":"Page 1. Ontological Traceability using Natural Language Processing A master thesis presented by Edder de la Rosa Benitez Submitted to the Department of Organization and Information in partial fulfillment of the …","url":["https://dspace.library.uu.nl/bitstream/handle/1874/383214/Master_Thesis_E_De_la_Rosa.pdf?sequence=2"]}
-{"year":"2019","title":"OpenCeres: When Open Information Extraction Meets the Semi-Structured Web","authors":["C Lockard, P Shiralkar, XL Dong"],"snippet":"… 5.1 Experimental Setup Datasets: Our primary dataset is the augmented SWDE corpus described in Section 4. In addition, we used the set of 315 movie websites (comprising 433,000 webpages) found in Common …","url":["http://lunadong.com/publication/openCeres_naacl.pdf"]}
-{"year":"2019","title":"OPTIMIZE THE LEARNING RATE OF NEURAL ARCHITECTURE IN MYANMAR STEMMER","authors":["Y Oo, KM Soe"],"snippet":"… Word vector pre-trained on large text corpora have been released on [10] \"Learning Word Vectors for 157 Languages \" that trained on 3 billion words from Wikipedia and Common Crawl using Continuous bag-of-words (CBOW) 300-dimension …","url":["https://www.academia.edu/download/61248451/120191117-8847-1ko3nhm.pdf"]}
-{"year":"2019","title":"Optimizer Comparison with Dropout for Neural Sequence Labeling in Myanmar Stemmer","authors":["O Yadanar, KM Soe - 2019 IEEE International Conference on Industry 4.0 …, 2019"],"snippet":"… Parameter initialization: It has used Learning Word Vectors for 157 Languages that trained on 3 billion words from Wikipedia and Common Crawl using CBOW 300-dimension (E. Grave, P. Bojanowski, P. Gupta, A. Joulin, T. Mikolov,2018) for both word and character …","url":["https://ieeexplore.ieee.org/abstract/document/8784850/"]}
-{"year":"2019","title":"Optimizing Social Media Data Using Genetic Algorithm","authors":["S Das, AK Kolya, D Das - Metaheuristic Approaches to Portfolio Optimization, 2019"],"snippet":"Page 1. 126 Copyright © 2019, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited. Chapter 6 DOI: 10.4018/978-1-5225-8103-1.ch006 ABSTRACT Twitter-based …","url":["https://www.igi-global.com/chapter/optimizing-social-media-data-using-genetic-algorithm/233176"]}
-{"year":"2019","title":"Overview of the CLEF eHealth Evaluation Lab 2019","authors":["E Kanoulas, D Li, L Azzopardi, R Spijker, G Zuccon… - Experimental IR Meets …"],"snippet":"… More specifically, for the Abstract and Title Screening subtask the PubMed Document Identifiers (PMIDs) of potentially relevant 4http://commoncrawl. org/(last accessed on 28 May 2019) … It consists of web pages acquired from the CommonCrawl …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=LqGsDwAAQBAJ&oi=fnd&pg=PA322&dq=commoncrawl&ots=8duC39Wv1R&sig=Tt9HYmgrR17eWjcTJPZvsij9B5g"]}
-{"year":"2019","title":"P-SIF: Document Embeddings Using Partition Averaging","authors":["V Gupta, A Saw, P Nokhiz, P Netrapalli, P Rai…"],"snippet":"… Page 5. evaluation. We use the PARAGRAM-SL999 (PSL) as word embeddings, obtained by training on the PPDB dataset. 7 We use the fixed weighting parameter a value of 10−3, and the word frequencies p(w) are estimated from the commoncrawl dataset …","url":["https://vgupta123.github.io/docs/AAAI-GuptaV.3656.pdf"]}
-{"year":"2019","title":"P2L: Predicting Transfer Learning for Images and Semantic Relations","authors":["B Bhattacharjee, N Codella, JR Kender, S Huo… - arXiv preprint arXiv …, 2019"],"snippet":"… We use the CC-DBP [12] dataset: the text of Common Crawl1 and the semantic relations schema and training data from DBpedia [1]. DBpedia is a knowledge graph extracted from the infoboxes from Wikipedia … 4.3.2 Validation on Common Crawl - DBpedia …","url":["https://arxiv.org/pdf/1908.07630"]}
-{"year":"2019","title":"PaDAWaNS","authors":["TLM Brands"],"snippet":"Page 1. PaDAWaNS Proactive Domain Abuse Warning and Notification System by TLM Brands to obtain the degree of Master of Science at the Delft University of Technology, to be defended publicly on Tuesday January 15, 2019 at 11:00 AM …","url":["https://www.sidnlabs.nl/downloads/theses/thesis_brands_padawans.pdf"]}
-{"year":"2019","title":"Parallel External Memory Wavelet Tree and Wavelet Matrix Construction","authors":["J Ellert, F Kurpicz - International Symposium on String Processing and …, 2019"],"snippet":"… CC \\((\\sigma =242)\\) contains websites (without HTML tags) that have been crawled by the Common Crawl corpus (http://commoncrawl.org), and. Wiki \\((\\sigma =213)\\) are recent Wikipedia dumps containing XML files that …","url":["https://link.springer.com/chapter/10.1007/978-3-030-32686-9_28"]}
-{"year":"2019","title":"Paraphrase-Sense-Tagged Sentences","authors":["A Cocos, C Callison-Burch, S Chen, D Khashabi… - Transactions, 2019"],"snippet":"Skip to main content …","url":["http://callison-burch.github.io/publications.html"]}
-{"year":"2019","title":"PDRCNN: Precise Phishing Detection with Recurrent Convolutional Neural Networks","authors":["W Wang, F Zhang, X Luo, S Zhang - Security and Communication Networks, 2019"],"snippet":"… This method first encodes the URL string using the one-hot encoding method, and then inputs each encoded character vector into the LSTM neurons for training and testing. The method achieved an accuracy of 0.935 on the …","url":["http://downloads.hindawi.com/journals/scn/2019/2595794.pdf"]}
-{"year":"2019","title":"Peer Review and the Production of Scholarly Knowledge: Automated Textual Analysis of Manuscripts Revised for Publication in Administrative Science Quarterly","authors":["D Strang, F Dokshin - The Production of Managerial Knowledge and …, 2019"],"snippet":"… numbers, and filter out “stop words.” Stop words are the most common words in the English language (eg, “the,” “not,” “a”). 2 Next, for each word in the pre-processed sentences, we generate word vectors from a GloVe model …","url":["https://www.emeraldinsight.com/doi/abs/10.1108/S0733-558X20190000059006"]}
-{"year":"2019","title":"PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization","authors":["J Zhang, Y Zhao, M Saleh, PJ Liu - arXiv preprint arXiv:1912.08777, 2019"],"snippet":"… T5 (Raffel et al., 2019) generalized the text-to- text framework to a variety of NLP tasks and showed the advantage of scaling up model size (to 11 billion parameters) and pre-training corpus, introducing C4, a massive text corpus …","url":["https://arxiv.org/pdf/1912.08777"]}
-{"year":"2019","title":"People represent mental states in terms of rationality, social impact, and valence: Validating the 3d Mind Model","authors":["MA Thornton, D Tamir"],"snippet":"Page 1. Running head: MENTAL STATE DIMENSIONS 1 People represent mental states in terms of rationality, social impact, and valence: Validating the 3d Mind Model Mark A. Thornton* and Diana I. Tamir Department of …","url":["https://psyarxiv.com/akhpq/download?format=pdf"]}
-{"year":"2019","title":"PhishFry–A Proactive Approach to Classify Phishing Sites using SCIKIT Learn","authors":["D Brites, M Wei"],"snippet":"… [Online]. Available: http://5000best.com/websites/. [Accessed 2019]. [26] OpenPhish, \"OpenPhish,\" 2019. [Online]. Available: https://openphish.com/. [27] Amazon Web Services, \"Common Crawl,\" Amazon, 2019. [Online] …","url":["https://www.shsu.edu/mxw032/publication/19gc-bw.pdf"]}
-{"year":"2019","title":"Phishing Detection Based on Machine Learning and Feature Selection Methods","authors":["M Almseidin, AMA Zuraiq, M Al-kasassbeh, N Alnidami - International Journal of …, 2019"],"snippet":"… Phishing webpages are collected from Phish-Tank and Open-Phish, while legitimate web-pages are collected from Alexa and Common Crawl. These web-pages are downloaded on two distinct sessions, from January to May 2015 and through May to June 2017 …","url":["https://onlinejour.journals.publicknowledgeproject.org/index.php/i-jim/article/download/11411/6259"]}
-{"year":"2019","title":"Phishing URL Detection Via Capsule-Based Neural Network","authors":["Y Huang, J Qin, W Wen - 2019 IEEE 13th International Conference on Anti …, 2019"],"snippet":"… [27] VirusTotal, https://www.virustotal.com/ [28] Common Crawl, https://commoncrawl.org/ [29] J. Ma, LK Saul, S. Savage, and GM VoelNer, “Beyond blacNlists: learning to detect malicious web sites from suspicious …","url":["https://ieeexplore.ieee.org/abstract/document/8925000/"]}
-{"year":"2019","title":"Pivot-based Transfer Learning for Neural Machine Translation between Non-English Languages","authors":["Y Kim, P Petrov, P Petrushkov, S Khadivi, H Ney - arXiv preprint arXiv:1909.09524, 2019"],"snippet":"Page 1. Pivot-based Transfer Learning for Neural Machine Translation between Non-English Languages Yunsu Kim1∗ Petre Petrov1,2∗ Pavel Petrushkov2 Shahram Khadivi2 Hermann Ney1 1RWTH Aachen University, Aachen …","url":["https://arxiv.org/pdf/1909.09524"]}
-{"year":"2019","title":"PKUSE at SemEval-2019 Task 3: Emotion Detection with Emotion-Oriented Neural Attention Network","authors":["L Ma, L Zhang, W Ye, W Hu - Proceedings of the 13th International Workshop on …, 2019"],"snippet":"… Table 1: Datasets for Semeval-2019 Task 3. 4.2 Experiments The model is implemented using Keras 2.0 (Chollet et al., 2017). We experiment with Stanford's GloVe 300 dimensional word embeddings trained on 840 billion words from Common Crawl …","url":["https://www.aclweb.org/anthology/S19-2049"]}
-{"year":"2019","title":"PLAGO: A SYSTEM FOR PLAGIARISM DETECTION AND INTERVENTION IN MASSIVE COURSES","authors":["CT Guida - 2019"],"snippet":"… Web Crawl: Used for queuing and monitoring of importing web pages from the CommonCrawl.org public dataset (described in 3.5.2). • Admin Options … pages. Common Crawl is a non-profit organization which offers a public …","url":["https://smartech.gatech.edu/bitstream/handle/1853/61787/GUIDA-THESIS-2019.pdf?sequence=1&isAllowed=y"]}
-{"year":"2019","title":"Poetry: Identification, Entity Recognition, and Retrieval","authors":["IV Foley, J John - 2019"],"snippet":"Page 1. University of Massachusetts Amherst ScholarWorks@UMass Amherst Doctoral Dissertations Dissertations and Theses 2019 Poetry: Identification, Entity Recognition, and Retrieval John J. Foley IV Follow this and additional …","url":["https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=2628&context=dissertations_2"]}
-{"year":"2019","title":"Populating Web Scale Knowledge Graphs using Distantly Supervised Relation Extraction and Validation","authors":["A Gliozzo, MR Glass, S Dash, M Canim - arXiv preprint arXiv:1908.08104, 2019"],"snippet":"… Also, a web-scale experiment conducted to extend DBPedia with knowledge from Common Crawl shows that our system is not only scalable but also does not require any adaptation cost, while yielding substantial accuracy gain. 1 Introduction …","url":["https://arxiv.org/pdf/1908.08104"]}
-{"year":"2019","title":"Precise Detection of Content Reuse in the Web","authors":["C Ardi, J Heidemann - ACM SIGCOMM Computer Communication Review, 2019"],"snippet":"… We verify our algorithm and its choices with controlled experiments over three web datasets: Common Crawl (2009/10), GeoCities (1990s–2000s), and a phishing corpus (2014) … In the Common Crawl dataset of 40.5×109 chunks, we set the threshold to 105 …","url":["https://dl.acm.org/citation.cfm?id=3336940"]}
-{"year":"2019","title":"Predicting ConceptNet Path Quality Using Crowdsourced Assessments of Naturalness","authors":["Y Zhou, S Schockaert, JA Shah - arXiv preprint arXiv:1902.07831, 2019"],"snippet":"… The number in parenthesis after each feature name indicates the dimension of that feature. Vertex embedding (300) This feature is taken directly from the 300dimensional GloVe (25) embedding, pre-trained on the Common Crawl2 dataset with 840 billion tokens …","url":["https://arxiv.org/pdf/1902.07831"]}
-{"year":"2019","title":"Predicting Word Concreteness and Imagery","authors":["J Charbonnier, C Wartena - Proceedings of the 13th International Conference on …, 2019"],"snippet":"… The other two version (also available with and without subword information) with 2 million word vectors trained on the Common Crawl with 600B tokens. In our experiments we used the version trained on Common Crawl without …","url":["https://www.aclweb.org/anthology/W19-0415"]}
-{"year":"2019","title":"Probing Contextualized Sentence Representations with Visual Awareness","authors":["Z Zhang, R Wang, K Chen, M Utiyama, E Sumita… - arXiv preprint arXiv …, 2019"],"snippet":"… We used newsdev2016 as the dev set and newstest2016 as the test set. 2) For the EN-DE translation task, 4.43M bilingual sentence pairs of the WMT14 dataset were used as training data, including Common Crawl, News Commentary, and Europarl v7 …","url":["https://arxiv.org/pdf/1911.02971"]}
-{"year":"2019","title":"Product Classification Using Microdata Annotations","authors":["Z Zhang, M Paramita - International Semantic Web Conference, 2019"],"snippet":"… dimension of the continuous vector representation of each word. In this work, we use the GloVe word embedding vectors pre-trained on the Common Crawl corpus 3 with 300 dimensions. Since we are dealing with content from e …","url":["https://link.springer.com/chapter/10.1007/978-3-030-30793-6_41"]}
-{"year":"2019","title":"Provision and Usage of Provenance Data in the WebIsALOD Knowledge Graph","authors":["S Hertling, H Paulheim - CEUR Workshop Proceedings, 2018"],"snippet":"… As described in [6], the Copyright c 2018 for this paper by its authors. Copying permitted for private and academic purposes. 1 https://commoncrawl.org 2 NP stands for noun phrase. 3 https://www.w3.org/TR/skos-reference/ Page 2. isa:concept/_Gmail …","url":["http://ceur-ws.org/Vol-2317/article-06.pdf"]}
-{"year":"2019","title":"PT-CoDE: Pre-trained Context-Dependent Encoder for Utterance-level Emotion Recognition","authors":["W Jiao, MR Lyu, I King - arXiv preprint arXiv:1910.08916, 2019"],"snippet":"… Here, we utilize the 300-dimensional pre-trained GloVe word vectors1 (Pennington et al., 2014) trained over 840B Common Crawl to initialize the word embedding layer. Those words that cannot be found in the GloVe …","url":["https://arxiv.org/pdf/1910.08916"]}
-{"year":"2019","title":"QE BERT: Bilingual BERT using Multi-task Learning for Neural Quality Estimation","authors":["H Kim, JH Lim, HK Kim, SH Na - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… We used parallel data provided for the WMT19 news machine translation task6 to pre-train QE BERT. The English-Russian parallel data set consisted of the ParaCrawl corpus, Common Crawl corpus, News Commentary corpus, and Yandex …","url":["https://www.aclweb.org/anthology/W19-5407"]}
-{"year":"2019","title":"QED: A Fact Verification and Evidence Support System","authors":["J Luken - 2019"],"snippet":"… embedding layers, as described below. 4.3.2 Embedding We use GloVe word embeddings (Pennington et al., 2014) with 300 dimensions pretrained using CommonCrawl to get a vector representation of the evidence sentence. We","url":["https://etd.ohiolink.edu/!etd.send_file?accession=osu1555074124008897&disposition=inline"]}
-{"year":"2019","title":"Quantifying the Semantic Core of Gender Systems","authors":["DBPH Wallach"],"snippet":"… 4The FASTTEXT word embeddings were trained using Common Crawl and Wikipedia data, using CBOW with po- sition weights, with character n-grams of length 5. For more information, see http://fasttext.cc/docs/en …","url":["https://openreview.net/pdf?id=ByxcApoPwS"]}
-{"year":"2019","title":"QuAVONet: Answering Questions on the SQuAD Dataset with QANet and Answer Verifier","authors":["J Cervantes"],"snippet":"… 5.2 Implementation Details For the word embeddings, I used the starter code's 300-dimensional GloVE vectors trained on the CommonCrawl dataset [6]. These embeddings remained unchanged and were not trained for any of my models …","url":["https://pdfs.semanticscholar.org/f71e/5c6cdd9e06068625eb82b3d9647823e80503.pdf"]}
-{"year":"2019","title":"Quick and (maybe not so) Easy Detection of Anorexia in Social Media Posts","authors":["E Mohammadi, H Amini, L Kosseim - 2019"],"snippet":"… As shown in Figure 1, these token vectors are then fed to the hidden layer. Two different pretrained word embeddings were experimented with. The first word embedder was the 300d version of GloVe [26] that was pretrained …","url":["https://www.researchgate.net/profile/Hessam_Amini/publication/334848955_Quick_and_maybe_not_so_Easy_Detection_of_Anorexia_in_Social_Media_Posts/links/5d434b9992851cd04699c9ce/Quick-and-maybe-not-so-Easy-Detection-of-Anorexia-in-Social-Media-Posts.pdf"]}
-{"year":"2019","title":"Quotient Hash Tables-Efficiently Detecting Duplicates in Streaming Data","authors":["R Géraud, M Lombard-Platet, D Naccache - arXiv preprint arXiv:1901.04358, 2019"],"snippet":"Page 1. arXiv:1901.04358v1 [cs.DS] 14 Jan 2019 Quotient Hash Tables - Efficiently Detecting Duplicates in Streaming Data Rémi Gérauda,c, Marius Lombard-Platet∗ a,b, and David Naccachea,c aDépartement d'informatique …","url":["https://arxiv.org/pdf/1901.04358"]}
-{"year":"2019","title":"Racial bias in legal language","authors":["D Rice, JH Rhodes, T Nteta - Research & Politics, 2019"],"snippet":"Although racial bias in the law is widely recognized, it remains unclear how these biases are in entrenched in the language of the law, judicial opinions. In th...","url":["https://journals.sagepub.com/doi/pdf/10.1177/2053168019848930"]}
-{"year":"2019","title":"Random Projection in Deep Neural Networks","authors":["PI Wójcik - arXiv preprint arXiv:1812.09489, 2018"],"snippet":"Page 1. Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie Wydzia�� Informatyki, Elektroniki i Telekomunikacji Katedra Informatyki Rozprawa doktorska Zastosowania metody rzutu przypadkowego w głębokich …","url":["https://arxiv.org/pdf/1812.09489"]}
-{"year":"2019","title":"Real or Fake? Learning to Discriminate Machine from Human Generated Text","authors":["A Bakhtin, S Gross, M Ott, Y Deng, MA Ranzato… - arXiv preprint arXiv …, 2019"],"snippet":"… CCNews: We collect a de-duplicated subset of the English portion of the CommonCrawl news dataset [Nagel, 2016], which totals around 16 Billion words … Sebastian Nagel. Cc-news. http://web.archive.org/save/http …","url":["https://arxiv.org/pdf/1906.03351"]}
-{"year":"2019","title":"Real-time Claim Detection from News Articles and Retrieval of Semantically-Similar Factchecks","authors":["B Adler, G Boscaini-Gilroy - arXiv preprint arXiv:1907.02030, 2019"],"snippet":"… new problem. Many unsupervised text embeddings are trained on the CommonCrawl 1 dataset of approx. 840 billion tokens. This … dataset. Supervised datasets are 1CommonCrawl found at http://commoncrawl.org/ unlikely ever …","url":["https://arxiv.org/pdf/1907.02030"]}
-{"year":"2019","title":"Real-time event detection using recurrent neural network in social sensors","authors":["VQ Nguyen, TN Anh, HJ Yang - International Journal of Distributed Sensor Networks, 2019"],"snippet":"We proposed an approach for temporal event detection using deep learning and multi-embedding on a set of text data from social media. First, a convolutional neural network augmented with multiple w...","url":["https://journals.sagepub.com/doi/pdf/10.1177/1550147719856492"]}
-{"year":"2019","title":"Real-world Conversational AI for Hotel Bookings","authors":["B Li, N Jiang, J Sham, H Shi, H Fazal - arXiv preprint arXiv:1908.10001, 2019"],"snippet":"… We compare the following models: 1) Averaged GloVe + feedforward: We use 100dimensional, trainable GloVe embeddings [17] trained on Common Crawl, and produce sentence embeddings for each of the two inputs by averaging across all tokens …","url":["https://arxiv.org/pdf/1908.10001"]}
-{"year":"2019","title":"Recommendation System with Aspect-Based Sentiment Analysis","authors":["Q Du, D Zhu, W Duan"],"snippet":"… The word vectors model we use is the \"en_core_web_lg\" model in spaCy. The model contains English multi-task CNN trained on OntoNotes 5[3], with GloVe[8] vectors trained on Common Crawl. It provides 300dimensional …","url":["http://rafaelsilva.com/wp-content/uploads/2018/12/014-Aspect-based-sentiment-analysis.pdf"]}
-{"year":"2019","title":"Refining Word Reesprentations by Manifold Learning","authors":["C Yonghe, H Lin, L Yang, Y Diao, S Zhang, F Xiaochao"],"snippet":"… judgment. This is exemplified by the WS353[Finkelstein et al., 2001]word similarity ground truth in Figure 1. Based on the Common Crawl corpus (42B), the Glove model is used to train 300-dimensional word vectors. The similarity …","url":["https://www.ijcai.org/proceedings/2019/0749.pdf"]}
-{"year":"2019","title":"Regressing Word and Sentence Embeddings for Regularization of Neural Machine Translation","authors":["IJ Unanue, EZ Borzeshi, M Piccardi - arXiv preprint arXiv:1909.13466, 2019"],"snippet":"… De-En: The German-English dataset (de-en) has been taken from the WMT18 news translation shared task1. The training set contains over 5M sentence pairs collected from the Europarl, CommonCrawl and Newscommentary parallel corpora …","url":["https://arxiv.org/pdf/1909.13466"]}
-{"year":"2019","title":"Rel4KC: A Reinforcement Learning Agent for Knowledge Graph Completion and Validation","authors":["X Lin, P Subasic, H Yin - 2019"],"snippet":"… The fact triples extracted from free text (Common Crawl) are then fed to the trained RL agent to determine their trustworthiness. If passing the validation, a triple is entered into target KG … The free text used in this study is Common Crawl corpus …","url":["http://www.cse.msu.edu/~zhaoxi35/DRL4KDD/1.pdf"]}
-{"year":"2019","title":"Repositioning privacy concerns: Web servers controlling URL metadata","authors":["R Ferreira, RL Aguiar - Journal of Information Security and Applications, 2019"],"snippet":"… on empirical observation of web browsers and HTTP server implementations, and while some implementations allow longer URLs (eg, 100.000 octets) this value remains a reasonable assumption for practical purposes 1 . Our …","url":["https://www.sciencedirect.com/science/article/pii/S2214212618302588"]}
-{"year":"2019","title":"Representation Learning for Question Classification via Topic Sparse Autoencoder and Entity Embedding","authors":["D Li, J Zhang, P Li - IEEE Big Data, 2018"],"snippet":"… WordNet 2. The embeddings of entity-related information are also trained with skip-gram. The word embeddings are initialized with the 300 dimensional pretrained vectors 3 from the Common Crawl of 840 billion tokens and 2.2 …","url":["http://research.baidu.com/Public/uploads/5c1c9ab3069f4.pdf"]}
-{"year":"2019","title":"Representing Overlaps in Sequence Labeling Tasks with a Novel Tagging Scheme: bigappy-unicrossy","authors":["G Berk, B Erden, T Güngör"],"snippet":"… a language-independent system based on the bidirectional LSTM-CRF model provided by [7]. Similar to Deep-BGT system [2], we make use of the pretrained word embeddings provided by fastText [6]. The word embeddings …","url":["https://www.cmpe.boun.edu.tr/~gungort/papers/Representing%20Overlaps%20in%20Sequence%20Labeling%20Tasks%20with%20a%20Novel%20Tagging%20Scheme%20-%20bigappy-unicrossy.pdf"]}
-{"year":"2019","title":"Review and Visualization of Facebook's FastText Pretrained Word Vector Model","authors":["JC Young, A Rusli - … International Conference on Engineering, Science, and …, 2019"],"snippet":"… Machine Learning (ML). Currently, FastText provides pretrained Word2Vec model for 157 language that trained on Common Crawl and Wikipedia (Bahasa Indonesia is one from the provided model) [15]. In its Word2Vec model …","url":["https://ieeexplore.ieee.org/abstract/document/8863015/"]}
-{"year":"2019","title":"RIPPED: Recursive Intent Propagation using Pretrained Embedding Distances","authors":["M Ball - 2019"],"snippet":"… GloVe (Pennington et al., 2014) is a word embedding model trained on data from the Common Crawl corpus6. GloVe is a log-bilinear regression model that incorporates both local context windows and global matrix …","url":["https://cs.brown.edu/research/pubs/theses/ugrad/2019/ball.michael.pdf"]}
-{"year":"2019","title":"RNN Embeddings for Identifying Difficult to Understand Medical Words","authors":["H Pylieva, A Chernodub, N Grabar, T Hamon - … of the 18th BioNLP Workshop and …, 2019"],"snippet":"… improve classification accuracy for our specific problem. We note that FastText word embeddings trained on Wikipedia and Common Crawl5 texts have an important part of words from our dataset. According to our analysis, the …","url":["https://www.aclweb.org/anthology/W19-5011"]}
-{"year":"2019","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","authors":["Y Liu, M Ott, N Goyal, J Du, M Joshi, D Chen, O Levy… - arXiv preprint arXiv …, 2019"],"snippet":"… (16GB). • CC-NEWS, which we collected from the En- glish portion of the CommonCrawl News dataset (Nagel, 2016) … STORIES, a dataset introduced in Trinh and Le (2018) containing a subset of CommonCrawl data filtered …","url":["https://arxiv.org/pdf/1907.11692"]}
-{"year":"2019","title":"Robust Argument Unit Recognition and Classification","authors":["D Trautmann, J Daxenberger, C Stab, H Schütze… - arXiv preprint arXiv …, 2019"],"snippet":"… 2http://commoncrawl.org/2016/02/ february-2016-crawl-archive-now-available/ 3https://www.elastic.co/products/ elasticsearch the topic. Each document was checked for its corresponding WARC file at the Common Crawl In …","url":["https://arxiv.org/pdf/1904.09688"]}
-{"year":"2019","title":"Robust Named Entity Recognition with Truecasing Pretraining","authors":["S Mayhew, N Gupta, D Roth - arXiv preprint arXiv:1912.07095, 2019"],"snippet":"… and Kauchak (2011) and used in Susanto, Chieu, and Lu (2016), and a specially preprocessed large dataset from English Common Crawl (CC).1 … 1commoncrawl.org 2In a naming clash, the moses script is called …","url":["https://arxiv.org/pdf/1912.07095"]}
-{"year":"2019","title":"SACABench: Benchmarking Suffix Array Construction","authors":["J Bahne, N Bertram, M Böcker, J Bode, J Fischer… - International Symposium on …, 2019"],"snippet":"… We removed every character but A, C, G, and T. CommonCrawl (\\(\\sigma =242,\\mathrm {avg\\_lcp}=3,995, \\mathrm {max\\_lcp}=605,632\\)), which is a crawl of the web done by the CommonCrawl Corpus (http://commoncrawl.org) without any HTML tags …","url":["https://link.springer.com/chapter/10.1007/978-3-030-32686-9_29"]}
-{"year":"2019","title":"Samsung and University of Edinburgh's System for the IWSLT 2019","authors":["J Wetesko, M Chochowski, P Przybysz, P Williams… - 2019"],"snippet":"… CommonCrawl and NewsCrawl corpora we used the approach de- scribed in [5]. Two RNN language models were constructed using Marian toolkit: in-domain trained with MUST-C corpus and out-of-domain created using …","url":["https://www.zora.uzh.ch/id/eprint/176328/1/IWSLT2019_paper_34.pdf"]}
-{"year":"2019","title":"Satellite System Graph: Towards the Efficiency Up-Boundary of Graph-Based Approximate Nearest Neighbor Search","authors":["C Fu, C Wang, D Cai - arXiv preprint arXiv:1907.06146, 2019"],"snippet":"Page 1. Satellite System Graph: Towards the Efficiency Up-Boundary of Graph-Based Approximate Nearest Neighbor Search Cong Fu, Changxu Wang, Deng Cai ∗ The State Key Lab of CAD&CG, College of Computer Science …","url":["https://arxiv.org/pdf/1907.06146"]}
-{"year":"2019","title":"SberQuAD--Russian Reading Comprehension Dataset: Description and Analysis","authors":["P Efimov, L Boytsov, P Braslavski - arXiv preprint arXiv:1912.09723, 2019"],"snippet":"… We tokenized text using spaCy16. To initialize the embedding layer for BiDAF, DocQA, DrQA, and R-Net we use Russian case-sensitive fastText embeddings trained on Common Crawl and Wikipedia17. This initialization is used for both questions and paragraphs …","url":["https://arxiv.org/pdf/1912.09723"]}
-{"year":"2019","title":"SC-UPB at the VarDial 2019 Evaluation Campaign: Moldavian vs. Romanian Cross-Dialect Topic Identification","authors":["C Onose, DC Cercel, S Trausan-Matu - Proceedings of the Sixth Workshop on NLP …, 2019"],"snippet":"… (2018), Nordic Language Processing Laboratory (NLPL) word embedding repository (Kutuzov et al., 2017) and Common Crawl (CC) word vectors (Grave et al., 2018). The relevant details for each word vector representation model can be viewed in Table 2 …","url":["https://www.aclweb.org/anthology/W19-1418"]}
-{"year":"2019","title":"Scalable Cross-Lingual Transfer of Neural Sentence Embeddings","authors":["H Aldarmaki, M Diab - arXiv preprint arXiv:1904.05542, 2019"],"snippet":"… We used WMT'12 Common Crawl data for crosslingual alignment, and WMT'12 test sets for evaluations. We used the augmented SNLI data de- scribed in (Dasgupta et al., 2018) and their translations for training the mono-lingual and joint InferSent models …","url":["https://arxiv.org/pdf/1904.05542"]}
-{"year":"2019","title":"SECNLP: A Survey of Embeddings in Clinical Natural Language Processing","authors":["K KS, S Sangeetha - arXiv preprint arXiv:1903.01039, 2019","KK Subramanyam, S Sivanesan - Journal of Biomedical Informatics, 2019"],"snippet":"Skip to main content Skip to article …","url":["https://arxiv.org/pdf/1903.01039","https://www.sciencedirect.com/science/article/pii/S1532046419302436"]}
-{"year":"2019","title":"Security In Plain TXT","authors":["A Portier, H Carter, C Lever"],"snippet":"… These seed domains are compiled from a combination of sources, including the Alexa top 1 million, the TLD zone files for COM, NAME, NET, ORG, and BIZ, sites captured by the Common Crawl project, multiple public domain …","url":["http://www.henrycarter.org/papers/plaintxt19.pdf"]}
-{"year":"2019","title":"Security Posture Based Incident Forecasting","authors":["D Mulugeta - 2019"],"snippet":"Page 1. Page 2. Page 3. Security Posture Based Incident Forecasting A Thesis Submitted to the Faculty of Drexel University by Dagmawi Mulugeta in partial fulfillment of the requirements for the degree of Master of Science June 2019 Page 4 …","url":["http://search.proquest.com/openview/a6f070655e6045b93b595adc3b0965ae/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2019","title":"See-Through-Text Grouping for Referring Image Segmentation","authors":["DJ Chen, S Jia, YC Lo, HT Chen, TL Liu - … of the IEEE International Conference on …, 2019"],"snippet":"… The representation st is visual-attended and its goodness is linked to the predicted segmentation map Pt−1. The GloVe model in our implementation is pre-trained on Common Crawl in 840B tokens. Following …","url":["http://openaccess.thecvf.com/content_ICCV_2019/papers/Chen_See-Through-Text_Grouping_for_Referring_Image_Segmentation_ICCV_2019_paper.pdf"]}
-{"year":"2019","title":"Semantic Characteristics of Schizophrenic Speech","authors":["K Bar, V Zilberstein, I Ziv, H Baram, N Dershowitz… - arXiv preprint arXiv …, 2019"],"snippet":"… Specifically, we used Hebrew pretrained vectors provided by fastText (Grave et al., 2018), which were created from Wikipedia,3 as well as from other content extracted from the web with Common Crawl.4 Overall, 97% of the words in our corpus exist in fastText …","url":["https://arxiv.org/pdf/1904.07953"]}
-{"year":"2019","title":"Semantic similarity measure for Thai language","authors":["P Wongchaisuwat"],"snippet":"… In this paper, pre-trained word vectors from fastText [10] and Thai2vec [1] corpus are used to compute the similarity between given words. The facebook research distributed the word vector trained on a common crawl and Wikipedia using the fastText model …","url":["https://saki.siit.tu.ac.th/isai-nlp2018/uploads_final/5__a25c56af02784c266f98ef0378499ff1/iSAI-NLP2018_0005_final.pdf"]}
-{"year":"2019","title":"Semantic Textual Similarity Measures for Case-Based Retrieval of Argument Graphs","authors":["M Lenz, S Ollinger, P Sahitaj, R Bergmann - International Conference on Case-Based …, 2019"],"snippet":"… Word2vec GoogleNews 3 vectors are trained on the Google News dataset on about 100B tokens. GloVe 4 is trained on the Common Crawl dataset on 840B tokens. fastText 5 vectors are trained on Wikipedia and Common Crawl …","url":["https://link.springer.com/chapter/10.1007/978-3-030-29249-2_15"]}
-{"year":"2019","title":"Semi-supervised machine learning with word embedding for classification in price statistics","authors":["H Martindale, E Rowland, T Flower - 16th Meeting of the Ottawa Group on Price …, 2019"],"snippet":"Page 1. Office for National Statistics 1 Semi-supervised machine learning with word embedding for classification: April 2019 26/04/2019 Semi-supervised machine learning with word embedding for classification in price statistics …","url":["https://eventos.fgv.br/sites/eventos.fgv.br/files/arquivos/u161/semi-supervised_ml_for_price_stats-ottawa_group.pdf"]}
-{"year":"2019","title":"Semi-supervised Neural Machine Translation via Marginal Distribution Estimation","authors":["Y Wang, Y Xia, L Zhao, J Bian, T Qin, E Chen, TY Liu - IEEE/ACM Transactions on …, 2019"],"snippet":"Page 1. 2329-9290 (c) 2019 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/8732422/"]}
-{"year":"2019","title":"SENPAI: Supporting Exploratory Text Analysis through Semantic & Syntactic Pattern Inspection","authors":["M Samory, T Mitra - 2019"],"snippet":"… lemmatization, so as to remove surface form variations which do not alter the meaning of a word, eg the lemma for both “moved” and “moves” is “move.” Then, we encode lemmas with the corresponding 300-dimensional word …","url":["http://people.cs.vt.edu/tmitra/public/papers/icwsm19-SENPAI.pdf"]}
-{"year":"2019","title":"Sense disambiguation for Punjabi language using supervised machine learning techniques","authors":["VP Singh, P Kumar - Sādhanā, 2019"],"snippet":"… The character n-grams of length 5 have been applied to words in window of size 5 with 10 negative samples [10]. It has been trained on the Punjabi Wikipedia and the raw web data fetched by common crawl method. 6 Working of WSD System for Punjabi language …","url":["https://link.springer.com/article/10.1007/s12046-019-1206-x"]}
-{"year":"2019","title":"Sentence and Word Weighting for Neural Machine Translation Domain Adaptation","authors":["PP Chen"],"snippet":"Page 1. Sentence and Word Weighting for Neural Machine Translation Domain Adaptation Pinzhen (Patrick) Chen Undergraduate Dissertation Artificial Intelligence and Software Engineering School of Informatics The …","url":["https://project-archive.inf.ed.ac.uk/ug4/20191530/ug4_proj.pdf"]}
-{"year":"2019","title":"Sentence Classification and Information Retrieval for Petroleum Engineering","authors":["TF Ferraz, GABA Ferreira, FG Cozman, I Santos"],"snippet":"… Accordingly, we used a word embedding representation in order to represent the words as vectors and then be able to define and compute distances between terms. We used a pre-trained embedding model called ”Common Crawl” [Pennington et al. 2014] …","url":["http://www.bracis2019.ufba.br/Camera_Ready/199118_1.pdf"]}
-{"year":"2019","title":"Sentence Mover's Similarity: Automatic Evaluation for Multi-Sentence Texts","authors":["E Clark, A Celikyilmaz, NA Smith"],"snippet":"… We obtain GloVe embeddings, which are type-based, 300-dimensional embeddings trained on Common Crawl,9 using spaCy,10 while the ELMo em- beddings are character-based, 1,024-dimensional, contextual …","url":["https://homes.cs.washington.edu/~nasmith/papers/clark+celikyilmaz+smith.acl19.pdf"]}
-{"year":"2019","title":"Sentence-Level Content Planning and Style Specification for Neural Text Generation","authors":["X Hua, L Wang - arXiv preprint arXiv:1909.00734, 2019"],"snippet":"… Statistics are shown in Table 1. Input Keyphrases and Label Construction. To obtain the input keyphrase candidates and their sentence-level selection labels, we first construct queries to retrieve passages from Wikipedia and news articles collected from commoncrawl …","url":["https://arxiv.org/pdf/1909.00734"]}
-{"year":"2019","title":"Sentiment Analysis","authors":["D Sarkar - Text Analytics with Python, 2019"],"snippet":"In this chapter, we cover one of the most interesting and widely used aspects pertaining to natural language processing (NLP), text analytics, and machine learning. The problem at hand is sentiment...","url":["https://link.springer.com/chapter/10.1007/978-1-4842-4354-1_9"]}
-{"year":"2019","title":"Separate Chaining Meets Compact Hashing","authors":["D Köppl - arXiv preprint arXiv:1905.00163, 2019"],"snippet":"Page 1. Separate Chaining Meets Compact Hashing Dominik Köppl Department of Informatics, Kyushu University, Japan Society for Promotion of Science Abstract While separate chaining is a common strategy for resolving …","url":["https://arxiv.org/pdf/1905.00163"]}
-{"year":"2019","title":"Sequence Labeling to Detect Stuttering Events in Read Speech","authors":["S Alharbi, M Hasan, AJH Simons, S Brumfitt, P Green - Computer Speech & …, 2019"],"snippet":"… In the present study, we used a pre-trained GloVe model to generate word embeddings for each utterance. This model was trained on the Common Crawl (CC) corpus (1.9 M vocab) Pennington et al. (2014). 6. Automatic Speech Recognition System …","url":["https://www.sciencedirect.com/science/article/pii/S0885230819302967"]}
-{"year":"2019","title":"Sequence Time Expression Recognition in the Spanish Clinical Narrative","authors":["A Ruiz-de-la-Cuadra, JL López-Cuadrado… - 2019 IEEE 32nd …, 2019"],"snippet":"… embedding (Table 1). Name Training Words Size Resource Glo200Ve Non-zero entries [37] 840 B 300 Common Crawl Spanish Billion Word [38] Word2Vec [39] 1.5 B 300 Sensem, Ancora Corpus, OPUS Project, etc. EVEX Word2Vec …","url":["https://ieeexplore.ieee.org/abstract/document/8787434/"]}
-{"year":"2019","title":"Sequence-to-sequence Pre-training with Data Augmentation for Sentence Rewriting","authors":["Y Zhang, T Ge, F Wei, M Zhou, X Sun - arXiv preprint arXiv:1909.06002, 2019"],"snippet":"… Specifically, for a correct sentence, a back translation model trained with the public GEC data first generates 10 best outputs; then a 5-gram language model (JunczysDowmunt and Grundkiewicz, 2016) trained on Common …","url":["https://arxiv.org/pdf/1909.06002"]}
-{"year":"2019","title":"Sequential Attention-based Network for Noetic End-to-End Response Selection","authors":["Q Chen, W Wang - arXiv preprint arXiv:1901.02609, 2019"],"snippet":"… Embedding Training corpus #Words glove.6B.300d Wikipedia + Gigaword 0.4M glove.840B.300d Common Crawl 2.2M glove.twitter.27B.200d Twitter 1.2M … 1.0M crawl-300d-2M.vec Common Crawl 2.0M word2vec.300d Linux manual pages 0.3M …","url":["https://arxiv.org/pdf/1901.02609"]}
-{"year":"2019","title":"Sequential Matching Model for End-to-end Multi-turn Response Selection","authors":["Q Chen, W Wang - ICASSP 2019-2019 IEEE International Conference on …, 2019"],"snippet":"… Re- sults on the Ubuntu development set are shown in Table 3. We can see that word2vec embedding trained on the training dataset achieves better results than Fasttext [23] embedding trained on the unlabeled corpus …","url":["https://ieeexplore.ieee.org/abstract/document/8682538/"]}
-{"year":"2019","title":"Sequential transfer learning in NLP for text summarization","authors":["P Fecht"],"snippet":"… With W and ˜W, the model generates two sets of word vectors which are supposed to perform equally if X is symmetric [64]. The GloVe model has been trained on varying sized datasets from one up to 42 billion (Common Crawl) tokens of data …","url":["https://www.inovex.de/fileadmin/files/Fachartikel_Publikationen/Theses/sequential-transfer-learning-in-nlp-for-text-summarization-pascal-fecht-2019.pdf"]}
-{"year":"2019","title":"Should John Be More Likely A Physician Than Lisa: Bias-Performance Trade-Off for Gendered Pronoun Resolution","authors":["S Goel, J Li, H Zheng"],"snippet":"… the female gendered words. For our case, we are using the pre-trained Glove6 (these cotain 840B tokens and are trained on the Common Crawl corpus) embeddings to get the hard-debiased em- beddings. To obtain these …","url":["https://shivankgoel.github.io/notes/ds/Gendered_Pronoun_Resolution.pdf"]}
-{"year":"2019","title":"Similarity Driven Approximation for Text Analytics","authors":["G Hu, Y Zhang, S Rigo, TD Nguyen - arXiv preprint arXiv:1910.07144, 2019"],"snippet":"… For example, the Google Books Ngram data set contains 2.2 TB of data [1], and the Common Crawl corpus contains petabytes of data [2]. Processing such large text data sets can be computationally expensive, especially if it involves sophisticated algorithms …","url":["https://arxiv.org/pdf/1910.07144"]}
-{"year":"2019","title":"Situating Sentence Embedders with Nearest Neighbor Overlap","authors":["LH Lin, NA Smith - arXiv preprint arXiv:1909.10724, 2019"],"snippet":"… GloVe average 100 Wikipedia 2014 + Gigaword 5 (6B tokens, uncased) 300 Wikipedia 2014 + Gigaword 5 (6B tokens, uncased) 300 Common Crawl (840B tokens, cased) FastText average 300 Wikipedia + UMBC + statmt.org …","url":["https://arxiv.org/pdf/1909.10724"]}
-{"year":"2019","title":"Six dimensions describe action understanding: the ACT-FASTaxonomy","authors":["MA Thornton, D Tamir, PS Hall - PsyArXiv. June, 2019"],"snippet":"… different algorithm. For the present purposes, we used a pre-trained version of GloVe based on the Common Crawl: a set of 840 billion tokens generated by scraping the entire web. For model comparison, we derived an …","url":["https://psyarxiv.com/gt6bw/download/?format=pdf"]}
-{"year":"2019","title":"SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization","authors":["H Jiang, P He, W Chen, X Liu, J Gao, T Zhao - arXiv preprint arXiv:1911.03437, 2019"],"snippet":"… For example, the well-known “Common Crawl project” is producing text data extracted from web pages at a rate of about 20TB per month. The resulting extremely large text corpus allows us to train extremely large neural network-based general language models …","url":["https://arxiv.org/pdf/1911.03437"]}
-{"year":"2019","title":"Social Relation Extraction from Chatbot Conversations: A Shortest Dependency Path Approach","authors":["M Glas - SKILL 2019-Studierendenkonferenz Informatik, 2019"],"snippet":"… The dictionary used here, 5 https://github.com/zalandoresearch/flair 6 https://spacy.io/ 7 http://commoncrawl.org/ 8 https://catalog.ldc.upenn.edu/LDC2013T19 Page 8. 8 Markus Glas Fig. 3: Example of a dependency path within a sentence containing two entities …","url":["https://dl.gi.de/bitstream/handle/20.500.12116/28989/SKILL2019-01.pdf?sequence=1"]}
-{"year":"2019","title":"Social Sensing for Improving the User Experience in Orienteering","authors":["F Persia, S Helmer, S Pugacs, G Pilato - 2019 IEEE 13th International Conference on …, 2019"],"snippet":"… ing. In particular, we have used the spaCy “en core web md” language model, which is an “English multi-task Convolutional Neural Network trained on OntoNotes [34], with GloVe [35] vectors trained on Common Crawl [36]” …","url":["https://ieeexplore.ieee.org/abstract/document/8665498/"]}
-{"year":"2019","title":"SOK: A Comprehensive Reexamination of Phishing Research from the Security Perspective","authors":["A Das, S Baki, AE Aassal, R Verma, A Dunbar - arXiv preprint arXiv:1911.00953, 2019"],"snippet":"Page 1. REEXAMINING PHISHING RESEARCH 1 SOK: A Comprehensive Reexamination of Phishing Research from the Security Perspective Avisha Das, Shahryar Baki, Ayman El Aassal, Rakesh Verma, and Arthur Dunbar …","url":["https://arxiv.org/pdf/1911.00953"]}
-{"year":"2019","title":"Sparse Victory–A Large Scale Systematic Comparison of Count-Based and Prediction-Based Vectorizers for Text Classification","authors":["R Chakraborty, K Arora, A Elhence"],"snippet":"… Corpus (100 billion words). For greater ease of comparison both the GloVe and fastText models have a dimension of 300 and have been trained on the Common Crawl Corpus (640 billion words). The ELMo embedding has …","url":["https://acl-bg.org/proceedings/2019/RANLP%202019/pdf/RANLP022.pdf"]}
-{"year":"2019","title":"ST-Sem: A Multimodal Method for Points-of-Interest Classification Using Street-Level Imagery","authors":["SS Noorian, A Psyllidis, A Bozzon - International Conference on Web Engineering, 2019"],"snippet":"… representing each word as a bag of character n-grams. We use pre-trained word vectors for 2 languages (English and German), trained on Common Crawl and Wikipedia 6 . According to the detected language l, the corresponding pre …","url":["https://link.springer.com/chapter/10.1007/978-3-030-19274-7_3"]}
-{"year":"2019","title":"STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems","authors":["J Zhang, X Shi, S Zhao, I King - arXiv preprint arXiv:1905.13129, 2019"],"snippet":"… For movie features, we concatenate the title name, release year, and one-hot encoded genres. We process title names by averaging the off-the-shelf 300-dimensional GloVe CommonCrawl word vector [Pennington et al., 2014] of each word …","url":["https://arxiv.org/pdf/1905.13129"]}
-{"year":"2019","title":"STD: An Automatic Evaluation Metric for Machine Translation Based on Word Embeddings","authors":["P Li, C Chen, W Zheng, Y Deng, F Ye, Z Zheng - IEEE/ACM Transactions on Audio …, 2019"],"snippet":"… H and M are their means respectively. The word embedding used in our STD implementation is the freely-available fastText word embedding1 [11], which has 2 million word vectors trained on Common Crawl (600B tokens) …","url":["https://ieeexplore.ieee.org/abstract/document/8736840/"]}
-{"year":"2019","title":"Streaming Infrastructure and Natural Language Modeling with Application to Streaming Big Data","authors":["Y Du - 2019"],"snippet":"… In our research, we try to find an alternative resource to study such data. Common Crawl is a massive multi-petabyte dataset hosted by Amazon. It contains archived HTML web page data from 2008 to date. Common …","url":["https://tigerprints.clemson.edu/all_dissertations/2329/"]}
-{"year":"2019","title":"Structured Two-Stream Attention Network for Video Question Answering","authors":["L Gao, P Zeng, J Song, YF Li, W Liu, T Mei, HT Shen - Proceedings of the AAAI …, 2019"],"snippet":"… consisting of M words, is first converted into a sequence Q = {qm}M m=1, where qm is a one-hot vector representing the word at position m. Next, we employ the word embedding GloVe (Pennington, Socher, and Manning …","url":["https://www.aaai.org/ojs/index.php/AAAI/article/view/4602/4480"]}
-{"year":"2019","title":"Study of Tibetan Text Classification based on fastText","authors":["W Ma, H Yu, J Ma - 3rd International Conference on Computer Engineering …"],"snippet":"… Every single text in all data is a line, and the \"__label__ + tag\" is added at the beginning of each line. Pre-training data set: fastText publishes word vectors in 157 languages [13], which are trained on Common Crawl and Wikipedia using fastText …","url":["https://download.atlantis-press.com/article/125913150.pdf"]}
-{"year":"2019","title":"SUBMISSION OF WRITTEN WORK","authors":["O ERSITY, F CO"],"snippet":"Page 1. IT U N IV ERSITY O F CO PEN H A G EN SUBMISSION OF WRITTEN WORK Class code: Name of course: Course manager: Course e-portfolio: Thesis or project title: Supervisor: Full Name: Birthdate (dd/mm-yyyy) …","url":["http://www.derczynski.com/itu/docs/Multilingual%20hate%20speech%20detection.pdf","https://www.derczynski.com/itu/docs/Multilingual%20hate%20speech%20detection.pdf"]}
-{"year":"2019","title":"Subword-based Compact Reconstruction of Word Embeddings","authors":["S Sasaki, J Suzuki, K Inui - Proceedings of the 2019 Conference of the North …, 2019"],"snippet":"… or embedding vectors), especially those trained on a vast amount of text data, such as the Common Crawl (CC) cor … word embeddings trained from GloVe.840B and fastText.600B are available: https://github.com/losyer …","url":["https://www.aclweb.org/anthology/N19-1353"]}
-{"year":"2019","title":"SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems","authors":["A Wang, Y Pruksachatkun, N Nangia, A Singh…"],"snippet":"… We also include a baseline where for each task we simply predict the majority class, as well as a bag-of-words baseline where each input is represented as an average of its tokens' GloVe word vectors (300-dimensional and trained …","url":["https://w4ngatang.github.io/static/papers/superglue.pdf"]}
-{"year":"2019","title":"Supervised Multimodal Bitransformers for Classifying Images and Text","authors":["D Kiela, S Bhooshan, H Firooz, D Testuggine - arXiv preprint arXiv:1909.02950, 2019"],"snippet":"… We describe each of the baselines in more detail below. • Bag of words (Bow) We sum 300-dimensional GloVe embeddings (Pennington, Socher, and Manning 2014) (trained on Common Crawl) for all words in the text …","url":["https://arxiv.org/pdf/1909.02950"]}
-{"year":"2019","title":"Supplementary Material for “Multi-task Learning of Hierarchical Vision-Language Representation”","authors":["DK Nguyen, T Okatani"],"snippet":"… Questions and captions were tokenized using Python Natural Language Toolkit (nltk) [2]. We used the vocabulary provided by the CommonCrawl-840B GloVe model for English word vectors [8], and set out-of-vocabulary words to unk …","url":["https://pdfs.semanticscholar.org/83a6/fd8eadd36c22bdac861bd2b20aba87968c3d.pdf"]}
-{"year":"2019","title":"Survey on Publicly Available Sinhala Natural Language Processing Tools and Research","authors":["N de Silva - arXiv preprint arXiv:1906.02358, 2019"],"snippet":"… [21] further provided two monolingual corpora for Sinhala. Those were a 155k+ sentences of filtered Sinhala Wikipedia8 and 5178k+ sentences of Sinhala common crawl9. 2.2 Data Sets Specific data sets for Sinhala, as expected. is scarce …","url":["https://arxiv.org/pdf/1906.02358"]}
-{"year":"2019","title":"Synchronous Bidirectional Neural Machine Translation","authors":["L Zhou, J Zhang, C Zong - Transactions of the Association for Computational …, 2019"],"snippet":"Create a new account. Email. Returning user. Can't sign in? Forgot your password? Enter your email address below and we will send you the reset instructions. Email. Cancel. If the address matches an existing account you will …","url":["https://www.mitpressjournals.org/doi/full/10.1162/tacl_a_00256"]}
-{"year":"2019","title":"Syntactic dependencies correspond to word pairs with high mutual information","authors":["R Futrell, P Qian, E Gibson, E Fedorenko, IA Blank"],"snippet":"… 2.5 Dataset We use the Common Crawl corpus (Buck et al., 2014) of English web text … Entropy, 19:275–307. Buck, C., Heafield, K., and Van Ooyen, B. (2014). N-gram counts and language models from the common crawl. In …","url":["http://socsci.uci.edu/~rfutrell/papers/futrell2019syntactic.pdf"]}
-{"year":"2019","title":"Syntactically Supervised Transformers for Faster Neural Machine Translation","authors":["N Akoury, K Krishna, M Iyyer - arXiv preprint arXiv:1906.02780, 2019"],"snippet":"… For English-German, we evaluate on WMT 2014 En↔De as well as IWSLT 2016 En→De, while for English-French we train on the Europarl / Common Crawl subset of the full WMT 2014 En→Fr data and evaluate over the full dev/test sets …","url":["https://arxiv.org/pdf/1906.02780"]}
-{"year":"2019","title":"Syntax-aware Multilingual Semantic Role Labeling","authors":["S He, Z Li, H Zhao - arXiv preprint arXiv:1909.00310, 2019"],"snippet":"… The pre-trained word em- bedding is 100-dimensional GloVe vectors (Pennington et al., 2014) for English, 300-dimensional fastText vectors (Grave et al., 2018) trained on Common Crawl and Wikipedia for other languages …","url":["https://arxiv.org/pdf/1909.00310"]}
-{"year":"2019","title":"Syntax-Aware Sentence Matching with Graph Convolutional Networks","authors":["Y Lei, Y Hu, X Wei, L Xing, Q Liu - International Conference on Knowledge Science …, 2019"],"snippet":"… 4.2 Experiment Setting. In order to compare with the baseline, we use the same setting as BiMPM. We initialize word embeddings in the word representation layer with the 300-dimensional GloVe word vectors …","url":["https://link.springer.com/chapter/10.1007/978-3-030-29563-9_31"]}
-{"year":"2019","title":"System and method for chat community question answering","authors":["N Londhe, S Kannan, N Bojja - US Patent App. 16/272,142, 2019"],"snippet":"US20190260694A1 - System and method for chat community question answering - Google Patents. System and method for chat community question answering. Download PDF Info. Publication number US20190260694A1. US20190260694A1 …","url":["https://patentimages.storage.googleapis.com/0c/f5/b6/7687c26806b141/US20190260694A1.pdf"]}
-{"year":"2019","title":"System and method for concise display of query results via thumbnails with indicative images and differentiating terms","authors":["TP O'hara - US Patent 10,459,999, 2019"],"snippet":"… grams). In the case of a meta-search engine without access to the underlying indexes, one approach is to use data from the Common Crawl to derive global n-gram counts for TF-IDF and language modeling filtering. Another …","url":["http://www.freepatentsonline.com/10459999.html"]}
-{"year":"2019","title":"System for creating a reasoning graph and for ranking of its nodes","authors":["B Agapiev - US Patent App. 15/793,751, 2019"],"snippet":"… View, Calif. and Common Crawl Foundation of Beverly Hills, Calif.) are processed (20) to identify statements of causal relationships (22, 24), which are then analyzed to extract causes and associated effect pairs (26). These …","url":["https://patentimages.storage.googleapis.com/ca/d2/fd/8b3a7f8fa4ec15/US20190073420A1.pdf"]}
-{"year":"2019","title":"TüBa-D/DP Stylebook","authors":["D de Kok, S Pütz - 2019"],"snippet":"… Table 1: Subcorpora of the TüBa-D/DP. Subcorpus Genre Sentences Tokens Europarl Parliamentary proceedings 2.2M 55M taz (1986-2009) Newspaper 29.9M 393.7M Wikipedia (2019) Encyclopedia 42.2M …","url":["https://sfb833-a3.github.io/tueba-ddp/stylebook/stylebook-r4.pdf"]}
-{"year":"2019","title":"TabbyXL: Rule-Based Spreadsheet Data Extraction and Transformation","authors":["A Shigarov, V Khristyuk, A Mikhailov, V Paramonov - International Conference on …, 2019"],"snippet":"… a spreadsheet-like format. Barik et al. [2] extracted 0.25M unique spreadsheets from Common Crawl 1 archive. Chen and Cafarella [6] reported about 0.4M spreadsheets of ClueWeb09 Crawl 2 archive. Spreadsheets can be …","url":["https://link.springer.com/chapter/10.1007/978-3-030-30275-7_6"]}
-{"year":"2019","title":"Tackling Graphical NLP problems with Graph Recurrent Networks","authors":["L Song - 2019"],"snippet":"Page 1. Tackling Graphical NLP problems with Graph Recurrent Networks by Linfeng Song Submitted in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy Supervised by Professor Daniel Gildea Department of Computer Science …","url":["https://www.cs.rochester.edu/~lsong10/papers/Linfeng_Song_PhD_thesis.pdf"]}
-{"year":"2019","title":"TARGER: Neural Argument Mining at Your Fingertips","authors":["A Chernodub, O Oliynyk, P Heidenreich, A Bondarenko…"],"snippet":"… Our background collection for the retrieval of argumentative sentences is formed by the DepCC corpus (Panchenko et al., 2018), a linguistically pre-processed subset of the Common Crawl containing 14.3 … Building a …","url":["https://webis.de/downloads/publications/papers/bondarenko_2019b.pdf"]}
-{"year":"2019","title":"Task definition, annotated dataset, and supervised natural language processing models for symptom extraction from unstructured clinical notes","authors":["JM Steinkamp, W Bala, A Sharma, JJ Kantrowitz - Journal of Biomedical Informatics, 2019"],"snippet":"… Our word embeddings consisted of 300-dimensional Global Vectors (GloVe) [35] trained on the web common crawl data set concatenated with 300-dimensional custom trained FastText [28] vectors trained on the entirety …","url":["https://www.sciencedirect.com/science/article/pii/S153204641930276X"]}
-{"year":"2019","title":"Team EP at TAC 2018: Automating data extraction in systematic reviews of environmental agents","authors":["A Nowak, P Kunstman - arXiv preprint arXiv:1901.02081, 2019"],"snippet":"… The model architecture is shown in Figure 3. Embeddings layer: Each token is represented by 1452 dimensional vector, consisting of: • 300-dimensional GloVe (Pennington et al., 2014) embedding (cased, trained on 840B tokens from Common Crawl) …","url":["https://arxiv.org/pdf/1901.02081"]}
-{"year":"2019","title":"Techniques for Inverted Index Compression","authors":["GE Pibiri, R Venturini - arXiv preprint arXiv:1908.10598, 2019"],"snippet":"Page 1. Techniques for Inverted Index Compression GIULIO ERMANNO PIBIRI, ISTI-CNR, Italy ROSSANO VENTURINI, University of Pisa, Italy The data structure at the core of large-scale search engines is the inverted index …","url":["https://arxiv.org/pdf/1908.10598"]}
-{"year":"2019","title":"Tell me you can read me","authors":["CE SUM, T THEOR"],"snippet":"Page 55. Complying with the obligation of transparency imposes indeed on the data controller the prior obligation to determine–deliberately or not, consciously or not–who are the targeted data subjects, and what are they supposed to find intelligible and easily accessible …","url":["https://pdfs.semanticscholar.org/8c2a/8c105a49e59c457c68b8390b49694c4c4c20.pdf#page=55"]}
-{"year":"2019","title":"Temporal Context-Aware Representation Learning for Question Routing","authors":["X Zhang, W Cheng, B Zong, Y Chen, J Xu, D Li…"],"snippet":"… The state-of-the-art document embedding model, InferSent [3], is applied to compute the similarity between questions. We use the pre-trained 300-dimensional word vectors from fastText[19], which is trained on Common Crawl containing 600B tokens …","url":["https://xuczhang.github.io/papers/wsdm20_tcqr.pdf"]}
-{"year":"2019","title":"Temporally Grounding Language Queries in Videos by Contextual Boundary-aware Prediction","authors":["J Wang, L Ma, W Jiang - arXiv preprint arXiv:1909.05010, 2019"],"snippet":"… 2015) features are adopted for all compared methods. Each word from the query is represented by GloVe (Pennington, Socher, and Manning 2014) word embedding vectors pre-trained on Common Crawl. We set hidden neuron size of LSTM to 512 …","url":["https://arxiv.org/pdf/1909.05010"]}
-{"year":"2019","title":"Text Classification Using SVM Enhanced by Multithreading and CUDA","authors":["S Chatterjee, PG Jose, D Datta - International Journal of Modern Education and …, 2019"],"snippet":"Page 1. IJ Modern Education and Computer Science, 2019, 1, 11-23 Published Online January 2019 in MECS (http://www.mecs-press.org/) DOI: 10.5815/ijmecs.2019.01.02 Copyright © 2019 MECS IJ Modern Education and Computer Science, 2019, 1, 11-23 …","url":["http://search.proquest.com/openview/ab6d5a2cbbb23e2cba642a09784b043e/1?pq-origsite=gscholar&cbl=2026674"]}
-{"year":"2019","title":"Text Corpus for NLP","authors":["C Room"],"snippet":"… Sep 2019. Common Crawl publishes 240 TiB of uncompressed data from 2.55 billion web pages. Of these, 1 billion URLs were not present in previous crawls. Common Crawl started in 2008. In 2013, they moved from ARC to Web ARChive (WARC) file format …","url":["https://devopedia.org/text-corpus-for-nlp"]}
-{"year":"2019","title":"TEXT QUALITY EVALUATION METHODS AND PROCESSES","authors":["AA Pala, A Kagoshima, M Tober - US Patent App. 15/863,408, 2019"],"snippet":"… In one possible implementation, the reference text 2000 can be parts, or the complete version, of Wikipedia, for a given language, or one or more books, or Common Crawl, or any other corpus that consists of human-written high quality text …","url":["http://www.freepatentsonline.com/y2019/0213247.html"]}
-{"year":"2019","title":"The AFRL WMT19 Systems: Old Favorites and New Tricks","authors":["J Gwinnup, G Erdmann, T Anderson - Proceedings of the Fourth Conference on …, 2019"],"snippet":"… Corpus Total Retained CommonCrawl 723,256 655,069 newscommentary 290,866 264,089 Yandex 1,000,000 901,307 ParaCrawl 12,061,155 5,173,675 UN2016 11,365,709 9,871,406 Total Lines 25,440,968 16,865,546 …","url":["https://www.aclweb.org/anthology/W19-5318"]}
-{"year":"2019","title":"The BEA-2019 Shared Task on Grammatical Error Correction","authors":["C Bryant, M Felice, ØE Andersen, T Briscoe - … Workshop on Innovative Use of NLP for …, 2019"],"snippet":"Page 1. Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications, pages 52–75 Florence, Italy, August 2, 2019. c 2019 Association for Computational Linguistics 52 The BEA-2019 …","url":["https://www.aclweb.org/anthology/W19-4406"]}
-{"year":"2019","title":"The BLCU System in the BEA 2019 Shared Task","authors":["L Yang, C Wang - Proceedings of the Fourteenth Workshop on Innovative …, 2019"],"snippet":"… JunczysDowmunt and Grundkiewicz (2016); JunczysDowmunt et al. (2018) utilize the Common Crawl corpus to train the language model and pre-train part of the NMT model. Inspired by these studies, we also try to use a monolingual corpus for data augmentation …","url":["https://www.aclweb.org/anthology/W19-4421"]}
-{"year":"2019","title":"The Geometry of Culture: Analyzing the Meanings of Class through Word Embeddings","authors":["AC Kozlowski, M Taddy, JA Evans - American Sociological Review, 2019"],"snippet":"We argue word embedding models are a useful tool for the study of culture using a historical analysis of shared understandings of social class as an empirical case. Word embeddings represent semant...","url":["https://journals.sagepub.com/doi/abs/10.1177/0003122419877135"]}
-{"year":"2019","title":"The impact of individual audit partners on their clients' narrative disclosures","authors":["C Mauritz, M Nienhaus, C Oehler - 2019"],"snippet":"Page 1. The impact of individual audit partners on their clients' narrative disclosures ∗ Christoph Mauritz1, Martin Nienhaus2, and Christopher Oehler2 1University of Münster 2Goethe-University Frankfurt September 5, 2019 Abstract …","url":["http://www.geaba.de/wp-content/uploads/2019/09/Mauritz-Nienhaus-Oehler_2.pdf"]}
-{"year":"2019","title":"The LAIX Systems in the BEA-2019 GEC Shared Task","authors":["R Li, C Wang, Y Zha, Y Yu, S Guo, Q Wang, Y Liu… - … on Innovative Use of NLP for …, 2019"],"snippet":"… Table 1 lists the data sets used in Restricted Track and Unrestricted Track, including FCE (Yannakoudakis et al., 2011), Lang-82 (Mizumoto et al., 2012), NUCLE (Ng et al., 2014), W&I+LOCNESS (Bryant et al., 2019) and Com …","url":["https://www.aclweb.org/anthology/W19-4416"]}
-{"year":"2019","title":"The LIG system for the English-Czech Text Translation Task of IWSLT 2019","authors":["L Vial, B Lecouteux, D Schwab, H Le, L Besacier - arXiv preprint arXiv:1911.02898, 2019"],"snippet":"… C is a speech translation corpus of TED talks, similar to the test data of the task, and we added the News Commentary corpus, which consists of political and economic commentaries, be- cause it was the second smallest corpus …","url":["https://arxiv.org/pdf/1911.02898"]}
-{"year":"2019","title":"The Linked Open Data cloud is more abstract, flatter and less linked than you may think!","authors":["L Asprino, W Beek, P Ciancarini, F van Harmelen… - arXiv preprint arXiv …, 2019"],"snippet":"… The two largest available crawls of LOD that are available today are WebDataCommons and LOD-a-lot. WebDataCommons5 [12] consists of ∼31B triples that have been extracted from the CommonCrawl datasets (November 2018 version) …","url":["https://arxiv.org/pdf/1906.08097"]}
-{"year":"2019","title":"The NiuTrans Machine Translation Systems for WMT19","authors":["B Li, Y Li, C Xu, Y Lin, J Liu, H Liu, Z Wang, Y Zhang…"],"snippet":"… For EN↔RU, we used the following resource provided by WMT, including News Commentaryv14, ParaCrawl-v3, CommonCrawl and Yandex … corpus via random samplimng from 2M monolingual data selected by Xenc in the …","url":["http://nlplab.com/members/xiaotong_files/2019-wmt.pdf"]}
-{"year":"2019","title":"The Quest to Automate Fact-checking","authors":["C Li"],"snippet":"… The model contains 300-dimensional vectors for 3 million words and phrases. https://code.google.com/archive/p/word2vec/ 2: Global Vectors for Word Representation using The Common Crawl corpus which contains …","url":["https://pdfs.semanticscholar.org/13e0/ef9f40c767060b510e2aa75740a3eda60ad4.pdf"]}
-{"year":"2019","title":"The relationship between implicit intergroup attitudes and beliefs","authors":["B Kurdi, TC Mann, TES Charlesworth, MR Banaji - Proceedings of the National …, 2019"],"snippet":"Skip to main content. Submit; About: Editorial Board; PNAS Staff; FAQ; Rights and Permissions; Site Map. Contact; Journal Club; Subscribe: Subscription Rates; Subscriptions FAQ; Open Access; Recommend PNAS to Your …","url":["https://www.pnas.org/content/early/2019/02/26/1820240116.short"]}
-{"year":"2019","title":"The RWTH Aachen University Machine Translation Systems for WMT 2019","authors":["J Rosendahl, C Herold, Y Kim, M Graça, W Wang… - Proceedings of the Fourth …, 2019"],"snippet":"… For De→En, we use data from CommonCrawl, Europarl, NewsCommentary and Rapid … (2017)), but without tied embedding weights, on the data from CommonCrawl, Europarl, NewsCommentary and Rapid ie about 6M sentence pairs …","url":["https://www.aclweb.org/anthology/W19-5338"]}
-{"year":"2019","title":"The Semantic Web: Two Decades On","authors":["A Hogan"],"snippet":"Page 1. Semantic Web 0 (0) 1 1 IOS Press 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 …","url":["http://www.semantic-web-journal.net/system/files/swj2303.pdf"]}
-{"year":"2019","title":"The Source-Target Domain Mismatch Problem in Machine Translation","authors":["J Shen, PJ Chen, M Le, J He, J Gu, M Ott, M Auli… - arXiv preprint arXiv …, 2019"],"snippet":"… For Myanmar monolingual data, we use the language split Commoncrawl data from (Buck et al., 2014) which includes texts in various domains crawled from the web. We use the myanmar-tools2 library to classify and convert all Zawgyi text to Unicode …","url":["https://arxiv.org/pdf/1909.13151"]}
-{"year":"2019","title":"The TALP-UPC Machine Translation Systems for WMT19 News Translation Task: Pivoting Techniques for Low Resource MT","authors":["N Casas, JAR Fonollosa, C Escolano, C Basta… - Proceedings of the Fourth …, 2019"],"snippet":"… 4.2 English-Russian The available parallel English-Russian corpora for the shared task included News Commentary v14, Wiki Titles v1, Common Crawl corpus, ParaCrawl v3, Yandex Corpus and the United Nations Parallel Corpus v1.0 (Ziemski et al., 2016) …","url":["https://www.aclweb.org/anthology/W19-5311"]}
-{"year":"2019","title":"The Universitat d'Alacant submissions to the English-to-Kazakh news translation task at WMT 2019","authors":["VM Sánchez-Cartagena, JA Pérez-Ortiz…"],"snippet":"… 556 corpus lang. raw cleaned News Crawl kk 783k 783k Wiki dumps kk 1.7M 1.7M Common Crawl kk 10.9M 5.4M News Crawl en 200M 200M … The same filtering was applied to the monolingual Kazakh Common Crawl corpus …","url":["https://www.dlsi.ua.es/~fsanchez/pub/pdf/sanchez-cartagena19a.pdf"]}
-{"year":"2019","title":"The University of Helsinki submissions to the WMT19 news translation task","authors":["A Talman, U Sulubacak, R Vázquez, Y Scherrer… - arXiv preprint arXiv …, 2019"],"snippet":"… removing all sentence pairs with a length difference ratio above a certain threshold: for CommonCrawl, ParaCrawl and Rapid we used a threshold of 3, for WikiTitles a threshold of 2, and for all other data sets a threshold of 9; …","url":["https://arxiv.org/pdf/1906.04040"]}
-{"year":"2019","title":"The University of Sydney's Machine Translation System for WMT19","authors":["L Ding, D Tao - arXiv preprint arXiv:1907.00494, 2019"],"snippet":"… 3 Data Preparation We used all available parallel corpus 3 for Finnish→ English except the “Wiki Headlines” due to the large number of incomplete sentences, and for monolingual target side English data, we selected all …","url":["https://arxiv.org/pdf/1907.00494"]}
-{"year":"2019","title":"The Web is missing an essential part of infrastructure: an Open Web Index","authors":["D Lewandowski - arXiv preprint arXiv:1903.03846, 2019"],"snippet":"… A search engine needs to keep its index current, meaning it needs to update at least a part of it every minute. This is an important requirement that is not being met by any of the current projects (like Common Crawl) …","url":["https://arxiv.org/pdf/1903.03846"]}
-{"year":"2019","title":"TiFi: Taxonomy Induction for Fictional Domains [Extended version]","authors":["CX Chu, S Razniewski, G Weikum - arXiv preprint arXiv:1901.10263, 2019"],"snippet":"Page 1. TiFi: Taxonomy Induction for Fictional Domains [Extended version] ∗ Cuong Xuan Chu Max Planck Institute for Informatics Saarbrücken, Germany cxchu@mpi-inf. mpg.de Simon Razniewski Max Planck Institute for Informatics …","url":["https://arxiv.org/pdf/1901.10263"]}
-{"year":"2019","title":"TLR at BSNLP2019: A Multilingual Named Entity Recognition System","authors":["JG Moreno, EL Pontes, M Coustaty, A Doucet - Proceedings of the 7th Workshop on …, 2019"],"snippet":"… in Figure 1. 3.1 FastText Embedding In this layer, we used pre-trained embeddings for each language trained on Common Crawl and Wikipedia using fastText (Bojanowski et al., 2017; Grave et al., 2018). These models were …","url":["https://www.aclweb.org/anthology/W19-3711"]}
-{"year":"2019","title":"TMU Transformer System Using BERT for Re-ranking at BEA 2019 Grammatical Error Correction on Restricted Track","authors":["M Kaneko, K Hotate, S Katsumata, M Komachi - … Workshop on Innovative Use of NLP …, 2019"],"snippet":"… The 5-gram language model for re-ranking was trained on a subset of the Common Crawl corpus (Chollampatt and Ng, 2018a).5 We used a Python spell checker tool6 on the GEC model hy- pothesis sentences. 3.3 Evaluation …","url":["https://www.aclweb.org/anthology/W19-4422"]}
-{"year":"2019","title":"Top-K Attention Mechanism for Complex Dialogue System","authors":["CU Shina, JW Chab - 2019"],"snippet":"… Then, the model submit the candidate with the highest value among the given candidates as the final correct an- swer. They randomly sampled one of the 99 negative samples to prevent bias during learning and used …","url":["http://workshop.colips.org/dstc7/papers/33.pdf"]}
-{"year":"2019","title":"Toponym Identification in Epidemiology Articles--A Deep Learning Approach","authors":["MR Davari, L Kosseim, TD Bui - arXiv preprint arXiv:1904.11018, 2019"],"snippet":"… In order to measure the effect of such domain specific information, we experimented with 2 other pretrained word embedding models: Google News Word2vec [11], and a GloVe Model trained on Common Crawl [24] … Common Crawl GloVe 2.2M 300 29.84 …","url":["https://arxiv.org/pdf/1904.11018"]}
-{"year":"2019","title":"Toward Automated Worldwide Monitoring of Network-Level Censorship","authors":["Z Weinberg - 2018"],"snippet":"Page 1. Toward Automated Worldwide Monitoring of Network-level Censorship Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Electrical and Computer Engineering Zachary Weinberg BA Chemistry, Columbia University …","url":["http://search.proquest.com/openview/11a5908644ea63a6b01b3f0c4d23ce4e/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2019","title":"Toward Gender-Inclusive Coreference Resolution","authors":["YT Cao, H Daumé III - arXiv preprint arXiv:1910.13913, 2019"],"snippet":"Page 1. Toward Gender-Inclusive Coreference Resolution YANG TRISTA CAO, University of Maryland HAL DAUMÉ III, Microsoft Research & University of Maryland ABSTRACT Correctly resolving textual mentions of people …","url":["https://arxiv.org/pdf/1910.13913"]}
-{"year":"2019","title":"Towards a Global Perspective on Web Tracking","authors":["N Samarasinghe, M Mannan - Computers & Security, 2019"],"snippet":"… Schelter et al. Schelter and Kunegis (2016) performed a large scale analysis of third-party trackers using the Common Crawl 2012 corpus. The corpus may contain tracking information of residential as well as institutional users …","url":["https://www.sciencedirect.com/science/article/pii/S0167404818314007"]}
-{"year":"2019","title":"Towards an Automated Extraction of ABAC Constraints from Natural Language Policies","authors":["M Alohaly, H Takabi, E Blanco - IFIP International Conference on ICT Systems …, 2019"],"snippet":"… model. To configure the model, we set one hyper-parameter value at a time. Our default settings: dropout = 0, decay rate = 0, number of BiLSTM cells (ie, layers) = 1, and GloVe (Common crawl) with 300 dimensions. To determine …","url":["https://link.springer.com/chapter/10.1007/978-3-030-22312-0_8"]}
-{"year":"2019","title":"Towards an automated method to assess data portals in the deep web","authors":["AS Correa, RM de Souza, FSC da Silva - Government Information Quarterly, 2019"],"snippet":"Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0740624X18305185"]}
-{"year":"2019","title":"Towards Content Expiry Date Determination: Predicting Validity Periods of Sentences","authors":["A Almquist, A Jatowt2r0000"],"snippet":"… For this, we use Common Crawl dataset 16 which is a web dump composed of billions of websites with plain text versions available … For each sentence found in the Common Crawl dataset we identify DATE, TIME and DURATION …","url":["http://www.dl.kuis.kyoto-u.ac.jp/~adam/ecir19a.pdf"]}
-{"year":"2019","title":"Towards Content Transfer through Grounded Text Generation","authors":["RE Dataset","S Prabhumoye, C Quirk, M Galley - arXiv preprint arXiv:1905.05293, 2019"],"snippet":"05/13/19 - Recent work in neural generation has attracted significant interest in controlling the form of text, such as style, persona, and p...","url":["https://arxiv.org/pdf/1905.05293","https://deepai.org/publication/towards-content-transfer-through-grounded-text-generation"]}
-{"year":"2019","title":"Towards countering hate speech and personal attack in social media","authors":["P Charitidis, S Doropoulos, S Vologiannidis… - arXiv preprint arXiv …, 2019"],"snippet":"… each language. After conducting some preliminary experiments, the best pre-trained embedding choice for Greek and French language was using fastText embeddings [45], trained on Common Crawl and Wikipedia. For English …","url":["https://arxiv.org/pdf/1912.04106"]}
-{"year":"2019","title":"Towards Functionally Similar Corpus Resources for Translation","authors":["M Kunilovskaya, S Sharoff"],"snippet":"… Secondly, we used lemmatised texts, with stop words filtered out (biLSTMlex in Table 1). For both scenarios we used pre-trained word embeddings of size 300, trained on the English Wikipedia and CommonCrawl data, using …","url":["http://corpus.leeds.ac.uk/serge/publications/2019-RANLP.pdf"]}
-{"year":"2019","title":"Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning","authors":["D Cevher, S Zepf, R Klinger - arXiv preprint arXiv:1909.02764, 2019"],"snippet":"… We use a neural network with an embedding layer (frozen weights, pretrained on Common Crawl and Wikipedia (Grave et al., 2018)), a bidirectional LSTM (Schuster and Paliwal, 1997), and two dense layers followed by a soft max output layer …","url":["https://arxiv.org/pdf/1909.02764"]}
-{"year":"2019","title":"Towards Multimodal Sarcasm Detection (An _Obviously_ Perfect Paper)","authors":["S Castro, D Hazarika, V Pérez-Rosas, R Zimmermann… - arXiv preprint arXiv …, 2019"],"snippet":"… 768. We also considered averaging Common Crawl pre-trained 300 dimensional GloVe word vectors (Pennington et al., 2014) for each token; however, it resulted in lower performance as compared to BERT-based features …","url":["https://arxiv.org/pdf/1906.01815"]}
-{"year":"2019","title":"Towards Non-task-specific Distillation of BERT via Sentence Representation Approximation","authors":["B Wu, H Zhang, M Li, Z Wang, Q Feng, J Huang… - arXiv preprint arXiv …, 2020","HZ Bowen Wu, M Li, Z Wang, Q Feng, J Huang…"],"snippet":"… paper. 4.3 Hyperparameters For the student model in our proposed distilling method, we employ the 300-dimension GloVe (840B Common Crawl version; Pennington et al., 2014) to initialize the word embeddings. The number …","url":["https://arxiv.org/pdf/2004.03097","https://www.researchgate.net/profile/Bowen_Wu10/publication/337113946_Towards_Non-task-specific_Distillation_of_BERT_via_Sentence_Representation_Approximation/links/5dc5cffc4585151435f7df39/Towards-Non-task-specific-Distillation-of-BERT-via-Sentence-Representation-Approximation.pdf"]}
-{"year":"2019","title":"Towards Robust Named Entity Recognition for Historic German","authors":["S Schweter, J Baiter - arXiv preprint arXiv:1906.07592, 2019"],"snippet":"… 69.59% Common Crawl 68.97% Wikipedia + Common Crawl 72.00% Wikipedia + Common Crawl + Character 74.50 … 69.62% Riedl and Padó (2018) (with transfer-learning) 74.33% ONB Wikipedia 75.80% CommonCrawl 78.70% Wikipedia + CommonCrawl 79.46 …","url":["https://arxiv.org/pdf/1906.07592"]}
-{"year":"2019","title":"Towards semantic-rich word embeddings","authors":["G Beringer, M Jabłonski, P Januszewski, A Sobecki…"],"snippet":"… collected (III), for the our approach. We use a pretrained embedding model from spaCy - en_vectors_web_lg, which contains 300-dimensional word vectors trained on Common Crawl with GloVe2. We compare results on the …","url":["https://annals-csis.org/Volume_18/drp/pdf/120.pdf"]}
-{"year":"2019","title":"Towards Unsupervised Grammatical Error Correction using Statistical Machine Translation with Synthetic Comparable Corpus","authors":["S Katsumata, M Komachi - arXiv preprint arXiv:1907.09724, 2019"],"snippet":"… makes up for the synthetic target data. To compare the fluency, the outputs of each best iter on JFLEG were evaluated with the perplexity based on the Common Crawl language model10. The perplexity of USMTforward in iter …","url":["https://arxiv.org/pdf/1907.09724"]}
-{"year":"2019","title":"Tracking Naturalistic Linguistic Predictions with Deep Neural Language Models","authors":["M Heilbron, B Ehinger, P Hagoort, FP de Lange - arXiv preprint arXiv:1909.04400, 2019"],"snippet":"… Non-predictive controls We included two non-predictive and potentially confounding variables: first, frequency which we quantified as unigram surprise (−log p(w)) which was based on a word's lemma count in the CommonCrawl corpus, obtained via spaCy …","url":["https://arxiv.org/pdf/1909.04400"]}
-{"year":"2019","title":"Transfer Learning across Languages from Someone Else's NMT Model","authors":["T Kocmi, O Bojar - arXiv preprint arXiv:1909.10955, 2019"],"snippet":"… WMT 2012 WMT 2018 English - French Commoncrawl, Europarl, Giga FREN, News commentary, UN corpus WMT 2013 WMT dis. 2015 … Based on our previous experiments, we ex- clude the noisiest corpus, ie web crawled ParaCrawl or Commoncrawl …","url":["https://arxiv.org/pdf/1909.10955"]}
-{"year":"2019","title":"Transfer Learning from Transformers to Fake News Challenge Stance Detection (FNC-1) Task","authors":["V Slovikovskaya - arXiv preprint arXiv:1910.14353, 2019"],"snippet":"… 9XLNet is named after TransformerXL 10These corpora include (1) BOOK CORPUS [Zhu et al., 2015] plus English Wikipedia, the original data used to train BERT (16GB); (2) CC-NEWS, which authors collected from the English …","url":["https://arxiv.org/pdf/1910.14353"]}
-{"year":"2019","title":"Transforma at SemEval-2019 Task 6: Offensive Language Analysis using Deep Learning Architecture","authors":["R Ong - arXiv preprint arXiv:1903.05280, 2019"],"snippet":"… This allows us to evaluate the increase in di- mensionality on the performance of our models 3. GloVe: Common Crawl (300d) - Trained on 42B tokens, 1.9M vocabulary of unique words … Table 7: T - GloVe Twitter, CC - GloVe Common Crawl …","url":["https://arxiv.org/pdf/1903.05280"]}
-{"year":"2019","title":"transformers. zip: Compressing Transformers with Pruning and Quantization","authors":["R Cheong, R Daniel - 2019"],"snippet":"… 9: return M 4 Page 5. 4 Experiments 4.1 Dataset We train and evaluate on the WMT English - German translation task. Specifically, we train on all of Europarl, Common Crawl, and News Commentary, validate on the …","url":["https://pdfs.semanticscholar.org/fe82/735fe8ae2163a37aa2787eee0db8efc745b6.pdf"]}
-{"year":"2019","title":"Translating Translationese: A Two-Step Approach to Unsupervised Machine Translation","authors":["N Pourdamghani, N Aldarrab, M Ghazvininejad…"],"snippet":"… For Arabic we use MultiUN (Tiedemann, 2012). For French we use CommonCrawl For German we use a mix of CommonCrawl (1.7M), and NewsCommentary (300K) … For Spanish we use CommonCrawl (1.8M), and Europarl (200K) …","url":["https://www.isi.edu/~jonmay/pubs/acl19.pdf"]}
-{"year":"2019","title":"Tree Edit Distance Learning via Adaptive Symbol Embeddings","authors":["BPCGA Micheli, B Hammer"],"snippet":"Deep Learning Monitor. Paper Detail. Close This Page. Tree Edit Distance Learning via Adaptive Symbol Embeddings. 2018-06-18 13:54:45; Benjamin Paaßen, Claudio Gallicchio, Alessio Micheli, Barbara Hammer; 0. Abstract …","url":["https://deeplearn.org/arxiv/38595/tree-edit-distance-learning-via-adaptive-symbol-embeddings"]}
-{"year":"2019","title":"TU Wien@ TREC Deep Learning'19--Simple Contextualization for Re-ranking","authors":["S Hofstätter, M Zlabinger, A Hanbury - arXiv preprint arXiv:1912.01385, 2019"],"snippet":"… For the full task we generated initial rankings with Anserini using BM25 and utilized the validation sets to tune the re-ranking 1https://github.com/microsoft/BlingFire 242B CommonCrawl lower-cased: https://nlp.stanford.edu/projects/glove …","url":["https://arxiv.org/pdf/1912.01385"]}
-{"year":"2019","title":"Twitter Sentiment on Affordable Care Act using Score Embedding","authors":["M Farhadloo - arXiv preprint arXiv:1908.07061, 2019"],"snippet":"… The embeddings pre-trained on Common Crawl data were only available in dimension 300 and were trained on 840 billion tokens with vocabulary … of available unlabeled training data had an impact on the performance …","url":["https://arxiv.org/pdf/1908.07061"]}
-{"year":"2019","title":"Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala-English","authors":["F Guzmán, PJ Chen, M Ott, J Pino, G Lample, P Koehn… - arXiv preprint arXiv …, 2019"],"snippet":"… M monolingual Wikipedia (en) 67.8M 2.0B Common Crawl (ne) 3.6M 103.0M Wikipedia (ne) 92.3K 2.8M Sinhala–English … 5M monolingual Wikipedia (en) 67.8M 2.0B Common Crawl (si) 5.2M 110.3M Wikipedia (si) 155.9K 4.7M …","url":["https://arxiv.org/pdf/1902.01382"]}
-{"year":"2019","title":"Type: Report Dissemination level: Public Due Date (in months): 24 (August 2019)","authors":["CSGOER Network"],"snippet":"Page 1. X Modal X Cultural X Lingual X Domain X Site Global OER Network Grant Agreement Number: 761758 Project Acronym: X5GON Project title: Cross Modal, Cross Cultural, Cross Lingual, Cross Domain, and Cross Site …","url":["https://www.x5gon.org/wp-content/uploads/2019/10/D5.2_afterJSTrev_26Aug19.pdf"]}
-{"year":"2019","title":"UdS-DFKI Participation at WMT 2019: Low-Resource (en-gu) and Coreference-Aware (en-de) Systems","authors":["C España-Bonet, D Ruiter - Proceedings of the Fourth Conference on Machine …, 2019"],"snippet":"… proportions. Our base system uses CommonCrawl … x1 Parallel CommonCrawl 2,394,878 x1 x4 Europarl 1,775,445 x1 x4 NewsCommentary 328,059 x4 x16 Rapid 1,105,651 x1 x4 ParaCrawlFiltered 12,424,790 x0 x1 Table …","url":["https://www.aclweb.org/anthology/W19-5315"]}
-{"year":"2019","title":"Understanding and Mitigating the Security Risks of Content Inclusion in Web Browsers","authors":["S Arshad - 2019"],"snippet":"… 47 5.1 Sample URL grouping. . . . . 73 5.2 Narrowing down the Common Crawl to the candidate set used in our analysis (from left to right) . . . . 79 5.3 Vulnerable pages and sites in the candidate set …","url":["http://search.proquest.com/openview/5a3bdc0060c7ad7004f26c77dae937c2/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2019","title":"Uni-and Multimodal and Structured Representations for Modeling Frame Semantics","authors":["T Botschen - 2019"],"snippet":"Page 1. Uniand Multimodal and Structured Representations for Modeling Frame Semantics Vom Fachbereich Informatik der Technischen Universität Darmstadt genehmigte Dissertation zur Erlangung des akademischen Grades …","url":["http://tuprints.ulb.tu-darmstadt.de/8484/1/Dissertation_TeresaBotschen.pdf"]}
-{"year":"2019","title":"Unified Visual-Semantic Embeddings: Bridging Vision and Language with Structured Meaning Representations","authors":["H Wu, J Mao, Y Zhang, Y Jiang, L Li, W Sun, WY Ma - arXiv preprint arXiv:1904.05521, 2019"],"snippet":"Page 1. Unified Visual-Semantic Embeddings: Bridging Vision and Language with Structured Meaning Representations Hao Wu1,3,4,6,∗,†, Jiayuan Mao5,6,∗,†, Yufeng Zhang2,6,†, Yuning Jiang6, Lei Li6, Weiwei Sun1,3,4, Wei-Ying Ma6 …","url":["https://arxiv.org/pdf/1904.05521"]}
-{"year":"2019","title":"Unraveling the Search Space of Abusive Language in Wikipedia with Dynamic Lexicon Acquisition","authors":["WF Chen, K Al-Khatib, M Hagen, H Wachsmuth…"],"snippet":"… The hidden state is employed to predict the probability of 'not-attack' using a linear regression layer. We use 300-dimensional word embeddings (Pennington et al., 2014) pre-trained on the Common Crawl with 840 …","url":["https://webis.de/downloads/publications/papers/stein_2019z.pdf"]}
-{"year":"2019","title":"Unsupervised Cross-lingual Representation Learning at Scale","authors":["A Conneau, K Khandelwal, N Goyal, V Chaudhary… - arXiv preprint arXiv …, 2019"],"snippet":"… As shown in Figure 1, the CommonCrawl Corpus that we collected has significantly more monolingual data than the previously used Wikipedia corpora. Figure 3 shows that for the same BERTBase architecture, all models …","url":["https://arxiv.org/pdf/1911.02116"]}
-{"year":"2019","title":"Unsupervised Extraction of Partial Translations for Neural Machine Translation","authors":["B Marie, A Fujita - Proceedings of the 2019 Conference of the North …, 2019"],"snippet":"… We extracted monolingual data ourselves from the Common Crawl project8 for Bengali (5.3M lines) and Malay (4.6M lines … 8http://commoncrawl org/ 9https://fasttext.cc/ 10The extraction of 100k partial translations from …","url":["https://www.aclweb.org/anthology/N19-1384"]}
-{"year":"2019","title":"Unsupervised Joint Training of Bilingual Word Embeddings","authors":["B Marie, A Fujita - Proceedings of the 57th Conference of the Association …, 2019"],"snippet":"… For en- id, we used English (100M lines) and Indonesian (77M lines) Common Crawl corpora.5 We then mapped the word embeddings into a BWE space using VECMAP,6 one of the best and most robust methods for unsupervised mapping (Glavas et al., 2019) …","url":["https://www.aclweb.org/anthology/P19-1312"]}
-{"year":"2019","title":"Unsupervised Lemmatization as Embeddings-Based Word Clustering","authors":["R Rosa, Z Žabokrtský - arXiv preprint arXiv:1908.08528, 2019"],"snippet":"… For the experiments reported in this paper, we use the pretrained word embedding dictionaries available from the FastText website.78 The word embeddings had been trained on Wikipedia9 and Common Crawl10 texts …","url":["https://arxiv.org/pdf/1908.08528"]}
-{"year":"2019","title":"Unsupervised Question Answering by Cloze Translation","authors":["P Lewis, L Denoyer, S Riedel - arXiv preprint arXiv:1906.04980, 2019"],"snippet":"… Question Corpus We mine questions from En- glish pages from a recent dump of common crawl using simple selection criteria:3 We select sen … 3http:// commoncrawl.org/ 4We also experimented with language model pretraining …","url":["https://arxiv.org/pdf/1906.04980"]}
-{"year":"2019","title":"Updating Pre-trained Word Vectors and Text Classifiers using Monolingual Alignment","authors":["P Bojanowski, O Celebi, T Mikolov, E Grave, A Joulin - arXiv preprint arXiv …, 2019"],"snippet":"… Indeed, despite their size, large web data such as Common Crawl lack coverage for highly technical expert fields such as medicine or law … Training data. We take two subsets of the May 2017 dump of the Common Crawl …","url":["https://arxiv.org/pdf/1910.06241"]}
-{"year":"2019","title":"Updating verbal fluency analysis for the 21st century: Applications for psychiatry","authors":["TB Holmlund, J Cheng, PW Foltz, AS Cohen, B Elvevåg - Psychiatry Research, 2019"],"snippet":"… To base the analysis on a corpus with a wide variety of animal-word sources, we used a set of pre-trained word vectors calculated from approximately 42 billion tokens from the entire internet, courtesy of the Common Crawl project (Pennington et al., 2014) …","url":["https://www.sciencedirect.com/science/article/pii/S0165178118324181"]}
-{"year":"2019","title":"Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs","authors":["A Fan, C Gardent, C Braud, A Bordes - 2019"],"snippet":"… WikiSum Second, we experiment on the WikiSum CommonCrawl (Liu et al., 2018b) summarization dataset4 with 1.5 million examples … denotes results from (Liu et al., 2018b) that use data scraped from unrestricted web search, not the static CommonCrawl version …","url":["https://hal.archives-ouvertes.fr/hal-02277063/document"]}
-{"year":"2019","title":"Using logical form encodings for unsupervised linguistic transformation: Theory and applications","authors":["T Gröndahl, N Asokan - arXiv preprint arXiv:1902.09381, 2019"],"snippet":"Page 1. arXiv:1902.09381v1 [cs.CL] 25 Feb 2019 Using logical form encodings for unsupervised linguistic transformation: Theory and applications Tommi Gröndahl N. Asokan Abstract We present a novel method to architect …","url":["https://arxiv.org/pdf/1902.09381"]}
-{"year":"2019","title":"Using the Semantic Web as a source of training data","authors":["C Bizer, A Primpeli, R Peeters - Datenbank-Spektrum, 2019"],"snippet":"… The Web Data Commons (WDC) project 4 monitors the adoption of schema.org annotations on the Web by analysing the Common Crawl 5 , a series of public web corpora each containing several billion HTML pages [12]. The …","url":["https://link.springer.com/article/10.1007/s13222-019-00313-y"]}
-{"year":"2019","title":"Using Whole Document Context in Neural Machine Translation","authors":["V Macé, C Servan - arXiv preprint arXiv:1910.07481, 2019"],"snippet":"… models are evaluated on the same standard corpora that have Page 3. Corpora #lines # EN # DE Common Crawl 2.2M 54M 50M Europarl V9† 1.8M 50M 48M News Comm. V14† 338K 8.2M 8.3M ParaCrawl V3 27.5M 569M …","url":["https://arxiv.org/pdf/1910.07481"]}
-{"year":"2019","title":"Variational Auto-Decoder: Neural Generative Modeling from Partial Data","authors":["A Zadeh, YC Lim, PP Liang, LP Morency - arXiv preprint arXiv:1903.00840, 2019"],"snippet":"… CMU-MOSEI consists of 23,500 sentences and CMU-MOSI consists of 2199 sentences. For text modality, the datasets contain GloVe word embeddings (Pennington et al., 2014) trained on 840 billion tokens from the Common Crawl dataset …","url":["https://arxiv.org/pdf/1903.00840"]}
-{"year":"2019","title":"Vernon-fenwick at SemEval-2019 Task 4: Hyperpartisan News Detection using Lexical and Semantic Features","authors":["V Srivastava, A Gupta, D Prakash, SK Sahoo, RR Rohit… - Proceedings of the 13th …, 2019"],"snippet":"… semantic space. We have used 300-dimensional Glove embeddings trained on Common Crawl data of 2.2 million words and 840 billion tokens. An ar- ticle was tokenized into sentences and further into words to obtain it's article representation …","url":["https://www.aclweb.org/anthology/S19-2189"]}
-{"year":"2019","title":"Video Question Answering with Spatio-Temporal Reasoning","authors":["Y Jang, Y Song, CD Kim, Y Yu, Y Kim, G Kim - International Journal of Computer …, 2019"],"snippet":"Page 1. International Journal of Computer Vision https://doi.org/10.1007/s11263-01901189-x Video Question Answering with Spatio-Temporal Reasoning Yunseok Jang1 · Yale Song2 · Chris Dongjoo Kim1 · Youngjae Yu1 · Youngjin Kim1 · Gunhee Kim1 …","url":["https://link.springer.com/article/10.1007/s11263-019-01189-x"]}
-{"year":"2019","title":"Vir is to Moderatus as Mulier is to Intemperans Lemma Embeddings for Latin","authors":["R Sprugnoli, M Passarotti, G Moretti"],"snippet":"… Both Facebook and the organizers of the CoNLL shared tasks on multilingual parsing have pre-computed and released word embeddings trained on Latin texts crawled from the web: the former using the fastText model on …","url":["https://www.researchgate.net/profile/Rachele_Sprugnoli/publication/336798734_Vir_is_to_Moderatus_as_Mulier_is_to_Intemperans_Lemma_Embeddings_for_Latin/links/5db2a47e92851c577ec259b4/Vir-is-to-Moderatus-as-Mulier-is-to-Intemperans-Lemma-Embeddings-for-Latin.pdf"]}
-{"year":"2019","title":"Vision-based Page Rank Estimation with Graph Networks","authors":["TI Denk, S Güner"],"snippet":"… The Open PageRank initiative provides freely available data that was built on top of Common Crawl [do/19], which provides high quality crawl data of webp ages since 2013. Open PageRank uses the number of backlinks of …","url":["https://www.researchgate.net/profile/Timo_Denk/publication/334824445_Vision-based_Page_Rank_Estimation_with_Graph_Networks/links/5d429cb692851cd04696fd56/Vision-based-Page-Rank-Estimation-with-Graph-Networks.pdf"]}
-{"year":"2019","title":"VizNet: Towards A Large-Scale Visualization Learning and Benchmarking Repository","authors":["K Hu, N Gaikwad, M Bakker, M Hulsebos, E Zgraggen…"],"snippet":"… Corpora The first category of corpora includes data tables harvested from the web. In particular, we use horizontal relational tables from the WebTables 2015 corpus [6], which extracts structured tables from the Common Crawl …","url":["https://hci.stanford.edu/~cagatay/projects/viznet/VizNet-CHI19-Submission.pdf"]}
-{"year":"2019","title":"Wanca in Korp: Text corpora for underresourced Uralic languages","authors":["H Jauhiainen, T Jauhiainen, K Lindén - DATA AND HUMANITIES (RDHUM) 2019 …"],"snippet":"… In addition to conducting our own crawling, we also used the pre-crawled corpus distributed by the Common Crawl Foundation … 2 In addition to conducting our own crawling, we used the pre-crawled corpus distributed by the Common Crawl Foundation …","url":["https://researchportal.helsinki.fi/files/126205806/Proceedings_RDHum2019.pdf#page=23"]}
-{"year":"2019","title":"WDC Product Data Corpus and Gold Standard for Large-Scale Product Matching-Version 2.0","authors":["R Peeters, A Primpeli, C Bizer"],"snippet":"… methods. The Web Data Commons project regularly extracts schema.org annotations from the Common Crawl, a large public web corpus. November 2017 version of the WDC schema.org data set contains 365 million offers …","url":["http://webdatacommons.org/largescaleproductcorpus/v2/"]}
-{"year":"2019","title":"Weakly-Supervised Concept-based Adversarial Learning for Cross-lingual Word Embeddings","authors":["H Wang, J Henderson, P Merlo - arXiv preprint arXiv:1904.09446, 2019"],"snippet":"… (2018a)11, we use their pretrained CBOW embeddings of 300 dimensions. For English, Italian and German, the models are trained on the WacKy corpus. The Finnish model is trained from Common Crawl and the Spanish model is trained from WMT News Crawl …","url":["https://arxiv.org/pdf/1904.09446"]}
-{"year":"2019","title":"Web Archive Analysis Using Hive and SparkSQL","authors":["X Wang, Z Xie - 2019 ACM/IEEE Joint Conference on Digital Libraries …, 2019"],"snippet":"… Keywords web archive, big data, distributed computation 1 Introduction Web preservation organizations such as Common Crawl or Internet Archive are common sources of web archive data … We use a data set from Common Crawl May 2018 collection …","url":["https://ieeexplore.ieee.org/abstract/document/8791112/"]}
-{"year":"2019","title":"Web Engineering: 19th International Conference, ICWE 2019, Daejeon, South Korea, June 11–14, 2019, Proceedings","authors":["M Bakaev"],"snippet":"Page 1. Maxim Bakaev Flavius Frasincar In-Young Ko (Eds.) Web Engineering 19th International Conference, ICWE 2019 Daejeon, South Korea, June 11–14, 2019 Proceedings 123 Page 2. Lecture Notes in Computer Science …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=5R6VDwAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=X57GCPV1TC&sig=41aU_I70hr0H-D_h9MbSG1Ruryc"]}
-{"year":"2019","title":"Web table integration and profiling for knowledge base augmentation","authors":["O Lehmberg - 2019"],"snippet":"Page 1. Web Table Integration and Profiling for Knowledge Base Augmentation Inauguraldissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften der Universität Mannheim …","url":["https://madoc.bib.uni-mannheim.de/52346/1/thesis.pdf"]}
-{"year":"2019","title":"Web View: Measuring & Monitoring Representative Information on Websites","authors":["A Saverimoutou, B Mathieu, S Vaton - ICIN 2019-QOE-MANAGEMENT 2019, 2019"],"snippet":"… XRay [8] and AdFisher run automated personalization detection experiments and Common Crawl 7 uses an Apache Nutch based crawler … 4http://phantomjs. org/ 5https://www.seleniumhq.org/ 6https://github.com/ghostwords/chameleon …","url":["https://hal.archives-ouvertes.fr/hal-02072471/document"]}
-{"year":"2019","title":"WebIsAGraph: A Very Large Hypernymy Graph from a Web Corpus","authors":["F Stefano, I Finocchi, SP Ponzetto, V Paola - Sixth Italian Conference on …, 2019","S Faralli, I Finocchi, SP Ponzetto, P Velardi - 2019"],"snippet":"… Abstract In this paper, we present WebIsAGraph, a very large hypernymy graph compiled from a dataset of is-a relationships ex- tracted from the CommonCrawl … This is because, due to their large size, source input corpora …","url":["https://iris.luiss.it/handle/11385/192535","https://www.researchgate.net/profile/Stefano_Faralli2/publication/336899588_WebIsAGraph_A_Very_Large_Hypernymy_Graph_from_a_Web_Corpus/links/5db9a6c24585151435d5b691/WebIsAGraph-A-Very-Large-Hypernymy-Graph-from-a-Web-Corpus.pdf"]}
-{"year":"2019","title":"What a neural language model tells us about spatial relations","authors":["M Ghanimifard, S Dobnik - Proceedings of the Combined Workshop on Spatial …, 2019"],"snippet":"… Finally, we also use pre-trained GloVe embeddings on the Common Crawl (CC) dataset with 42B tokens4 … On multi-word test suite the P-vectors perform slightly better. On both test suites, GloVe trained on Common Crawl performs …","url":["https://www.aclweb.org/anthology/W19-1608"]}
-{"year":"2019","title":"What are Links in Linked Open Data? A Characterization and Evaluation of Links between Knowledge Graphs on the Web","authors":["A Haller, JD Fernández, MR Kamdar, A Polleres - Working Papers on Information …, 2019"],"snippet":"Page 1. What are Links in Linked Open Data? A Characterization and Evaluation of Links between Knowledge Graphs on the Web Armin Haller, Javier D. Fernández, Maulik R. Kamdar, Axel Polleres Arbeitspapiere zum Tätigkeitsfeld …","url":["http://epub.wu.ac.at/7193/1/20191002ePub_LOD_link_analysis.pdf"]}
-{"year":"2019","title":"What does Neural Bring? Analysing Improvements in Morphosyntactic Annotation and Lemmatisation of Slovenian, Croatian and Serbian","authors":["N Ljubešić, K Dobrovoljc - Proceedings of the 7th Workshop on Balto-Slavic …, 2019"],"snippet":"… neural morphosyntactic taggers, we also experiment with various embeddings, mostly (1) the original CoNLL 2017 word2vec (w2v) embeddings for Slovenian and Croatian (Ginter et al., 2017) (there are none available for …","url":["https://www.aclweb.org/anthology/W19-3704"]}
-{"year":"2019","title":"Who Needs Words? Lexicon-Free Speech Recognition","authors":["T Likhomanenko, G Synnaeve, R Collobert - arXiv preprint arXiv:1904.04479, 2019"],"snippet":"… char GCNN-20B no 6.4 2.7 3.6 1.5 4https://github.com/facebookresearch/wav2letter 5Speaker adaptation; pronunciation lexicon 612k hours AM train set and common crawl LM 7Speaker adaptation; 3k acoustic states 8Data augmentation; n-gram LM …","url":["https://arxiv.org/pdf/1904.04479"]}
-{"year":"2019","title":"WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia","authors":["H Schwenk, V Chaudhary, S Sun, H Gong, F Guzmán - arXiv preprint arXiv …, 2019"],"snippet":"… recall. In this work, we chose the global mining op- tion. This will allow us to scale the same ap- proach to other, potentially huge, corpora for which document-level alignments are not easily available, eg Common Crawl. An …","url":["https://arxiv.org/pdf/1907.05791"]}
-{"year":"2019","title":"WINOGRANDE: An Adversarial Winograd Schema Challenge at Scale","authors":["K Sakaguchi, RL Bras, C Bhagavatula, Y Choi - arXiv preprint arXiv:1907.10641, 2019"],"snippet":"… Ensemble Neural LMs Trinh and Le (2018) is one of the first attempts to apply a neural language model which is pre-trained on a very large corpora (including LM-1-Billion, CommonCrawl, SQuAD, and Gutenberg Books). In …","url":["https://arxiv.org/pdf/1907.10641"]}
-{"year":"2019","title":"Word Embedding Based Extension of Text Categorization Topic Taxonomies","authors":["T Eljasik-Swoboda, F Engel, M Kaufmann, M Hemmje"],"snippet":"… ArgumenText is a practical implementation of an AM engine (Stab et al., 2018). It employs a two-step mechanism in which a large collection of documents (http://commoncrawl.org/, in Stab et al.'s experiment with 683 …","url":["http://ceur-ws.org/Vol-2348/paper01.pdf"]}
-{"year":"2019","title":"Word Embedding Models for Query Expansion in Answer Passage Retrieval","authors":["S MASTER"],"snippet":"Page 1. MASTER'S THESIS Word Embedding Models for Query Expansion in Answer Passage Retrieval NIRMAL ROY Page 2. Page 3. Word Embedding Models for Query Expansion in Answer Passage Retrieval THESIS submitted …","url":["https://pdfs.semanticscholar.org/f436/c49151fd8d00c59655a939bbbd552f1577c4.pdf"]}
-{"year":"2019","title":"Word Embedding Visualization Via Dictionary Learning","authors":["J Zhang, Y Chen, B Cheung, BA Olshausen - arXiv preprint arXiv:1910.03833, 2019"],"snippet":"… similar. For simplicity, we show the results for the 300 dimensional GloVe word vectors[30] pretrained on CommonCrawl [2]. We shall discuss the difference across different embedding models at the end in this section. Once …","url":["https://arxiv.org/pdf/1910.03833"]}
-{"year":"2019","title":"Word Embeddings (Also) Encode Human Personality Stereotypes","authors":["O Agarwal, F Durupınar, NI Badler, A Nenkova - … of the Eighth Joint Conference on …, 2019"],"snippet":"… or profession. We experimented with GloVe representations (Pennington et al., 2014) trained on Common crawl (6B tokens, 400K vocab, 300d) and symmetric pattern (SP) based representations (Schwartz et al., 2015). We …","url":["https://www.aclweb.org/anthology/S19-1023"]}
-{"year":"2019","title":"Word Embeddings and Gender Stereotypes in Swedish and English","authors":["R Précenth - 2019"],"snippet":"Page 1. UUDM Project Report 2019:15 Examensarbete i matematik, 30 hp Handledare: David Sumpter Examinator: Denis Gaidashev Maj 2019 Department of Mathematics Uppsala University Word Embeddings and Gender Stereotypes in Swedish and English …","url":["https://uu.diva-portal.org/smash/get/diva2:1313459/FULLTEXT01.pdf"]}
-{"year":"2019","title":"Word Embeddings for Fine-Grained Sentiment Analysis","authors":["D Bacon, R Dalal, MRD Kodandarama, MR Hari…"],"snippet":"… Lastly, we considered the word embedding sub-model. We used the GLoVe word vectoring [11] trained on Common Crawl [https://commoncrawl.org/] as implemented by spaCy [7]. This resulted in a vector-dimension of 300 for each word …","url":["https://divatekodand.github.io/files/word_embeddings.pdf"]}
-{"year":"2019","title":"Word Embeddings for Sentiment Analysis: A Comprehensive Empirical Survey","authors":["E Çano, M Morisio - arXiv preprint arXiv:1902.00753, 2019"],"snippet":"… This bundle contains data of Common Crawl (http: //commoncrawl.org/), a nonprofit organization that builds and maintains free and public text sets by crawling the Web. CommonCrawl42 is a highly reduced version easier and faster to work with …","url":["https://arxiv.org/pdf/1902.00753"]}
-{"year":"2019","title":"Word Embeddings for the Armenian Language: Intrinsic and Extrinsic Evaluation","authors":["K Avetisyan, T Ghukasyan - arXiv preprint arXiv:1906.03134, 2019"],"snippet":"… A year later, Facebook released another batch of fastText embeddings, trained on Common Crawl and Wikipedia [2]. Other publicly available embeddings include 4 … these embeddings were trained on Wikipedia and Common Crawl, using CBOW architecture with …","url":["https://arxiv.org/pdf/1906.03134"]}
-{"year":"2019","title":"Word Embeddings in Low Resource Gujarati Language","authors":["I Joshi, P Koringa, S Mitra - 2019 International Conference on Document Analysis …, 2019"],"snippet":"… (2014) released GloVe models trained on Wikipedia, Gigaword and Common Crawl (840B tokens). A notable effort is the work of Al-Rfou et al … Word embeddings for Gujarati language were released as a part of …","url":["https://ieeexplore.ieee.org/abstract/document/8893052/"]}
-{"year":"2019","title":"Word Similarity Datasets for Thai: Construction and Evaluation","authors":["P Netisopakul, G Wohlgenannt, A Pulich - arXiv preprint arXiv:1904.04307, 2019"],"snippet":"… The models are trained on Common Crawl and Wikipedia corpora using fastText [13], regarding settings they report the us- age of the CBOW algorithm, 300 dimensions, a window size of 5 and 10 negatives. The model is large and contains 2M vectors …","url":["https://arxiv.org/pdf/1904.04307"]}
-{"year":"2019","title":"Word Usage Similarity Estimation with Sentence Representations and Automatic Substitutes","authors":["AG Soler, M Apidianaki, A Allauzen - arXiv preprint arXiv:1905.08377, 2019"],"snippet":"… al., 2014). We use 300-dimensional GloVe embeddings pre-trained on Common Crawl (840B tokens).5 The representation of a sentence is obtained by averaging the GloVe embeddings of the words in the sentence. SIF (Smooth …","url":["https://arxiv.org/pdf/1905.08377"]}
-{"year":"2019","title":"Word-embedding data as an alternative to questionnaires for measuring the affective meaning of concepts","authors":["A van Loon, J Freese - 2019"],"snippet":"… Here we include information from both algorithms. The GloVe embeddings we use have been trained on text obtained from Wikipedia, Twitter, and Common Crawl. The Word2vec embeddings we use are trained on the Google News Corpus …","url":["https://osf.io/preprints/socarxiv/r7ewx/download"]}
-{"year":"2019","title":"Word-Embeddings and Grammar Features to Detect Language Disorders in Alzheimer's Disease Patients","authors":["JS Guerrero-Cristancho, JC Vásquez-Correa… - TecnoLógicas, 2020"],"snippet":"… occurrence in a document [13]. Said authors considered a pre-trained model with the Common Crawl dataset, whose vocabulary size exceeds the 2 million and contains 840 billion words. A logistic regression classifier and …","url":["https://revistas.itm.edu.co/index.php/tecnologicas/article/download/1387/1456"]}
-{"year":"2019","title":"WTMED at MEDIQA 2019: A Hybrid Approach to Biomedical Natural Language Inference","authors":["Z Wu, Y Song, S Huang, Y Tian, F Xia - Proceedings of the 18th BioNLP Workshop …, 2019"],"snippet":"Page 1. Proceedings of the BioNLP 2019 workshop, pages 415–426 Florence, Italy, August 1, 2019. c 2019 Association for Computational Linguistics 415 WTMED at MEDIQA 2019: A Hybrid Approach to Biomedical Natural Language Inference …","url":["https://www.aclweb.org/anthology/W19-5044"]}
-{"year":"2019","title":"X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension","authors":["M Abdou, C Sas, R Aralikatte, I Augenstein, A Søgaard - arXiv preprint arXiv …, 2019"],"snippet":"… All monolingual models' word embeddings were initialised using fastText embeddings trained on each language's Wikipedia and common crawl corpora,7 except for the comparison experiments described in sub-section …","url":["https://arxiv.org/pdf/1908.05111"]}
-{"year":"2019","title":"XLNet: Generalized Autoregressive Pretraining for Language Understanding","authors":["Z Yang, Z Dai, Y Yang, J Carbonell, R Salakhutdinov… - arXiv preprint arXiv …, 2019"],"snippet":"Page 1. XLNet: Generalized Autoregressive Pretraining for Language Understanding Zhilin Yang∗1, Zihang Dai∗12, Yiming Yang1, Jaime Carbonell1, Ruslan Salakhutdinov1, Quoc V. Le2 1Carnegie Mellon University, 2Google …","url":["https://arxiv.org/pdf/1906.08237"]}
-{"year":"2019","title":"YNU Wb at HASOC 2019: Ordered Neurons LSTM with Attention for Identifying Hate Speech and Offensive Language","authors":["B Wang, SL Yunxia Ding, X Zhou - Proceedings of the 11th annual meeting of the …, 2019"],"snippet":"… And the pre-training word vector we used is fastText, which is provided by Mikolov et al. [7]. It is a 2 million word vector trained using subword information on Common Crawl with 600B tokens, and its dimension is 300. 4.3 Result …","url":["http://ceur-ws.org/Vol-2517/T3-2.pdf"]}
-{"year":"2019","title":"YNUWB at SemEval-2019 Task 6: K-max pooling CNN with average meta-embedding for identifying offensive language","authors":["B Wang, X Zhou, X Zhang - Proceedings of the 13th International Workshop on …, 2019"],"snippet":"… FastText is provided by Mikolov et al. (Mikolov et al., 2018), it is a 2 million word vector trained using subword information on Common Crawl with 600B tokens, and its dimension is 300. Glove is provided by Jeffrey Pennington et al …","url":["https://www.aclweb.org/anthology/S19-2143"]}
-{"year":"2019","title":"Zastosowania metody rzutu przypadkowego w głębokich sieciach neuronowych","authors":["PI Wójcik"],"snippet":"Page 1. Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie Wydział Informatyki, Elektroniki i Telekomunikacji Katedra Informatyki Rozprawa doktorska Zastosowania metody rzutu przypadkowego w głębokich …","url":["http://www.doktoraty.iet.agh.edu.pl/_media/2018:pwojcik:phd.pdf"]}
-{"year":"2019","title":"Zero-Resource Cross-Lingual Named Entity Recognition","authors":["MS Bari, S Joty, P Jwalapuram - arXiv preprint arXiv:1911.09812, 2019"],"snippet":"… We use FastText embeddings (Grave et al. 2018), which are trained on Common Crawl and Wikipedia, and SGD with a gradient clipping of 5.0 to train the model. We found that the learning rate was crucial for training, and …","url":["https://arxiv.org/pdf/1911.09812"]}
-{"year":"2019","title":"Zero-Resource Neural Machine Translation with Monolingual Pivot Data","authors":["A Currey, K Heafield"],"snippet":"… We use all available parallel corpora for EN↔DE (Europarl v7, Common Crawl, and News Commentary v11) and for EN↔RU (Common Crawl, News Commentary v11, Yandex Corpus, and Wiki Headlines) to train the initial …","url":["https://kheafield.com/papers/edinburgh/pivot.pdf"]}
-{"year":"2019","title":"Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging","authors":["J Choi, J Lee, J Park, J Nam - arXiv preprint arXiv:1906.08615, 2019"],"snippet":"… We utilized a pretrained GloVe model available online. It contains 19 million vocabularies with 300 dimensional embedding trained from documents in Common Crawl data. We then evaluated the model on MTAT and GTZAN …","url":["https://arxiv.org/pdf/1906.08615"]}
-{"year":"2019","title":"Zero-Shot Question Classification Using Synthetic Samples","authors":["H Fu, C Yuan, X Wang, Z Sang, S Hu, Y Shi - 2018 5th IEEE International Conference …, 2019"],"snippet":"… The detailed data set is listed in Table 1. All experiments follow the principle of counterpart parameters. The Chinese and English word vectors are pre-trained using Glove respectively on Samsung and Common Crawl corpus. The word dimension is 300 …","url":["https://ieeexplore.ieee.org/abstract/document/8691209/"]}
-{"year":"2019","title":"Zero-Shot Semantic Segmentation via Variational Mapping","authors":["N Kato, T Yamasaki, K Aizawa - Proceedings of the IEEE International Conference on …, 2019"],"snippet":"… Dataset Unseen classes PASCAL-50 aeroplane, bicycle, bird, boat, bottle PASCAL-51 bus, car, cat, chair, cow PASCAL-52 diningtable, dog, horse, motorbike, person PASCAL-53 potted plant, sheep, sofa, train, tv/monitor …","url":["http://openaccess.thecvf.com/content_ICCVW_2019/papers/MDALC/Kato_Zero-Shot_Semantic_Segmentation_via_Variational_Mapping_ICCVW_2019_paper.pdf"]}
-{"year":"2020","title":"18 Evaluation of Greek Word Embeddings","authors":["S Outsios, C Karatsalos, K Skianis, M Vazirgiannis"],"snippet":"… wiki. The last model has been trained on Common Crawl and Wikipedia data using FastText based on CBOW model with position-weights (Grave et al., 2018), mentioned as cc+wiki. Category gr_def gr_neg1 0 cc.el.300 …","url":["http://www.eleto.gr/download/Conferences/12th%20Conference/Papers-and-speakers/12th_18-02-20_OutsiosStamatis-KaratsalosChristos-SkianisK-VazirgiannisMichalis_Paper1_V04.pdf"]}
-{"year":"2020","title":"\" Thy algorithm shalt not bear false witness\": An Evaluation of Multiclass Debiasing Methods on Word Embeddings","authors":["T Schlender, G Spanakis - arXiv preprint arXiv:2010.16228, 2020"],"snippet":"… However, surprisingly, the WEAT score measured in ConceptNet is the worst of all three. The GloVe embeddings seem to carry the most bias concerning the RNSB and MAC metrics, which is intuitive when considering the common crawl data it was trained on …","url":["https://arxiv.org/pdf/2010.16228"]}
-{"year":"2020","title":"A Benchmark of Rule-Based and Neural Coreference Resolution in Dutch Novels and News","authors":["C Poot, A van Cranenburgh - arXiv preprint arXiv:2011.01615, 2020"],"snippet":"… 5 Evaluation Before presenting our main benchmark results, we discuss the issue of coreference evaluation metrics. 6We use Fasttext common crawl embeddings, https://fasttext.cc/docs/en/crawl-vectors.html Page 6 …","url":["https://arxiv.org/pdf/2011.01615"]}
-{"year":"2020","title":"A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer","authors":["V Iashin, E Rahtu - arXiv preprint arXiv:2005.08271, 2020"],"snippet":"Page 1. IASHIN, RAHTU: A BETTER USE OF AUDIO-VISUAL CUES 1 A Better Use of Audio-Visual Cues: Dense Video Captioning with Bi-modal Transformer Vladimir Iashin vladimir.iashin@tuni.fi Esa Rahtu esa.rahtu@tuni.fi …","url":["https://arxiv.org/pdf/2005.08271"]}
-{"year":"2020","title":"A brief tour to the NLP Sesame Street","authors":["E Montoya"],"snippet":"… In addition to the strategy to verify fake news this research provided of a large corpus of news articles from Common Crawl named RealNews, as Grover needed a large corpus of news with metadata which was not available or …","url":["https://chatbotslife.com/a-brief-tour-to-the-nlp-sesame-street-7bba02d75ae3"]}
-{"year":"2020","title":"A Call for More Rigor in Unsupervised Cross-lingual Learning","authors":["M Artetxe, S Ruder, D Yogatama, G Labaka, E Agirre - arXiv preprint arXiv …, 2020"],"snippet":"… However, as of November 2019, Wikipedia exists in only 307 languages3 of which nearly half have less than 10,000 articles. While one could hope to overcome this by taking the entire web as a corpus, as …","url":["https://arxiv.org/pdf/2004.14958"]}
-{"year":"2020","title":"A Character-Level BiGRU-Attention for Phishing Classification","authors":["L Yuan, Z Zeng, Y Lu, X Ou, T Feng - International Conference on Information and …, 2019"],"snippet":"… In addition, Common Crawl that stored a great deal of websites is an open website for crawler learners. There are 800,000 websites provided as legitimate websites data … Phish urls. Legal urls. Data sources. Phish Tank. Common Crawl …","url":["https://link.springer.com/chapter/10.1007/978-3-030-41579-2_43"]}
-{"year":"2020","title":"A Comprehensive Survey of Grammar Error Correction","authors":["Y Wang, Y Wang, J Liu, Z Liu - arXiv preprint arXiv:2005.06600, 2020"],"snippet":"… Common Crawl. The Common Crawl corpus [10] is a repository of web crawl data which is open to everyone. It completes crawls monthly since 2011. • EVP … [28] Word-Level L1 Yes None Error Selection Wikipedia, 2014 Common Crawl …","url":["https://arxiv.org/pdf/2005.06600"]}
-{"year":"2020","title":"A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models","authors":["U Naseem, I Razzak, SK Khan, M Prasad - arXiv preprint arXiv:2010.15036, 2020"],"snippet":"Page 1. A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models USMAN NASEEM∗, School of Computer Science, The University of Sydney, Australia …","url":["https://arxiv.org/pdf/2010.15036"]}
-{"year":"2020","title":"A Cross-lingual Natural Language Processing Framework for Infodemic Management","authors":["R Pal, R Pandey, V Gautam, K Bhagat, T Sethi - arXiv preprint arXiv:2010.16357, 2020"],"snippet":"… The algorithm effectively minimizes this function to learn meaningful vector representations. The version of Glove used for experimentation is the publicly available common Crawl (840B tokens, 2.2M vocab, cased, 300 dimension vectors) …","url":["https://arxiv.org/pdf/2010.16357"]}
-{"year":"2020","title":"A Deep Learning Approach to Interest Analysis","authors":["T Meer - 2020"],"snippet":"Page 1. A Deep Learning Approach to Interest Analysis Thomas van der Meer A thesis submitted for the degree of Master of Business Informatics Department of Information and Computing Sciences Utrecht University The …","url":["https://dspace.library.uu.nl/bitstream/handle/1874/398939/scriptie_eindversie_tvdm.pdf?sequence=1"]}
-{"year":"2020","title":"A Deep Learning-Based Approach for Identifying the Medicinal Uses of Plant-Derived Natural Compounds. Front. Pharmacol. 11: 584875. doi: 10.3389/fphar …","authors":["S Yoo, HC Yang, S Lee, J Shin, S Min, E Lee, M Song… - Frontiers in Pharmacology …, 2020"],"snippet":"… alphaisothiocyanatotoluene.” In this study, we used the pre-trained fastText model with Wikipedia and Common Crawl (Grave et al., 2018). The model additionally learned from the DrugBank indication and PubMed literature …","url":["https://pdfs.semanticscholar.org/2105/4ac827a06c594f54e1ffe9c865fcbb994980.pdf"]}
-{"year":"2020","title":"A deep search method to survey data portals in the whole web: toward a machine learning classification model","authors":["AS Correa, A Melo Jr, FSC da Silva - Government Information Quarterly, 2020"],"snippet":"… Later, the same authors (AS Correa & da Silva, 2019) took advantage of the URL index of the Common Crawl project (an open repository of web crawl data) to survey potential data portals by searching the URL text strings …","url":["https://www.sciencedirect.com/science/article/pii/S0740624X20302896"]}
-{"year":"2020","title":"A Deep-Learning-Based Blocking Technique for Entity Linkage","authors":["F Azzalini, M Renzi, L Tanca - International Conference on Database Systems for …, 2020"],"snippet":"… attribute value \\(t[A_{k}]\\) is transformed into a real-valued vector \\(\\mathbf{v} (w)\\). The fastText model we use is crawl-300d-2M-subword [3] where each word is represented as a 300-dimensional vector and the …","url":["https://link.springer.com/chapter/10.1007/978-3-030-59410-7_37"]}
-{"year":"2020","title":"A Focused Study to Compare Arabic Pre-training Models on Newswire IE Tasks","authors":["W Lan, Y Chen, W Xu, A Ritter - arXiv preprint arXiv:2004.14519, 2020"],"snippet":"… three times; (2) add the Arabic shuffled Os- car data (Ortiz Suárez et al., 2019), a large-scale multilingual dataset obtained by language identification and filtering of the Common Crawl corpus … XLM-Rbase CommonCrawl 55.6B …","url":["https://arxiv.org/pdf/2004.14519"]}
-{"year":"2020","title":"A Framework for Word Embedding Based Automatic Text Summarization and Evaluation","authors":["TT Hailu, J Yu, TG Fantaye - Information, 2020"],"snippet":"Text summarization is a process of producing a concise version of text (summary) from one or more information sources. If the generated summary preserves meaning of the original text, it will help the users to make fast and …","url":["https://www.mdpi.com/2078-2489/11/2/78/pdf"]}
-{"year":"2020","title":"A German Language Voice Recognition System using DeepSpeech","authors":["J Xu, K Matta, S Islam, A Nürnberger"],"snippet":"… 1, pp. 517–520, 1992. [14] Christopher Cieri, David Miller and Kevin Walker, “The Fisher Corpus: a Resource for the Next Generations of Speech-to-Text,” LREC, 2004. [15] CommomCrawl, “English language model,” http://commoncrawl.org/, 2020 …","url":["https://www.researchgate.net/profile/Kaveen_Matta_Kumaresh/publication/342657372_German_Voice_Recognition_System_using_DeepSpeech/links/5efee6e3a6fdcc4ca447681a/German-Voice-Recognition-System-using-DeepSpeech.pdf"]}
-{"year":"2020","title":"A Gradient Boosting-Seq2Seq System for Latin POS Tagging and Lemmatization","authors":["GGA Celano - LREC 2020 Workshop Language Resources and …"],"snippet":"… prefixes, infixes, or suffixes to be weighted. Some models for Latin, such as the one based on texts from Common Crawl and Wikipedia, have already been computed and are freely available. 7 However, since the data released …","url":["https://www.academia.edu/download/63734156/LT4HALAbook20200624-19244-er3k3d.pdf#page=126"]}
-{"year":"2020","title":"A graph based framework for structured prediction tasks in sanskrit","authors":["A Krishna, A Gupta, P Goyal, B Santra, P Satuluri - Computational Linguistics, 2020"],"snippet":"Page 1. A Graph Based Framework for Structured Prediction Tasks in Sanskrit Amrith Krishna* University of Cambridge Bishal Santra Indian Institute of Technology Kharagpur Ashim Gupta† University of Utah Pavankumar Satuluri Chinmaya Vishwavidyapeeth …","url":["https://www.mitpressjournals.org/doi/pdf/10.1162/coli_a_00390"]}
-{"year":"2020","title":"A Graph-Theoretic Approach for the Detection of Phishing Webpages","authors":["CL Tan, KL Chiew, KSC Yong, J Abdullah, Y Sebastian - Computers & Security, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S016740482030078X"]}
-{"year":"2020","title":"A Hybrid Approach for Aspect-Based Sentiment Analysis Using Deep Contextual Word Embeddings and Hierarchical Attention","authors":["MM Trusca, D Wassenberg, F Frasincar, R Dekker - arXiv preprint arXiv:2004.08673, 2020","R Dekker - Web Engineering: 20th International Conference, ICWE …"],"snippet":"… The last two conditions for f are necessary to prevent overweighting of either rare or frequent co-occurrences. In this paper, we choose to use 300-dimension GloVe word embeddings trained on the Common Crawl (42 billion words)[14]. Word2vec …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=XpnqDwAAQBAJ&oi=fnd&pg=PA365&dq=commoncrawl&ots=-hereKCQai&sig=PCXnLnE9TjyMtqs05nolBDRi69g","https://arxiv.org/pdf/2004.08673"]}
-{"year":"2020","title":"A Large Scale Study on Health Information Retrieval for Laypersons","authors":["Z Liu - 2020"],"snippet":"… 3.1 Description of Document Collection The consumer-oriented health search task uses a dataset called clefehealth2018 corpus, which was created by acquiring web pages from various health do- mains(websites) using the CommonCrawl platform1 …","url":["https://cs.anu.edu.au/courses/CSPROJECTS/20S1/reports/u6022937_report.pdf"]}
-{"year":"2020","title":"A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal","authors":["D Gholipour Ghalandari, C Hokamp, J Glover, G Ifrim - arXiv, 2020","DG Ghalandari, C Hokamp, NT Pham, J Glover, G Ifrim - arXiv preprint arXiv …, 2020"],"snippet":"… We also automatically extend these source articles by looking for related articles in the Common Crawl archive … Table 1: Example event summary and linked source ar- ticles from the Wikipedia Current Events Portal, and …","url":["https://arxiv.org/pdf/2005.10070","https://ui.adsabs.harvard.edu/abs/2020arXiv200510070G/abstract"]}
-{"year":"2020","title":"A Large-Scale Semi-Supervised Dataset for Offensive Language Identification","authors":["S Rosenthal, P Atanasova, G Karadzhov, M Zampieri… - arXiv preprint arXiv …, 2020"],"snippet":"… The first layer of the LSTM model is an embedding layer, which we initialize with a concatenation of the GloVe 300-dimensional (Pennington et al., 2014) and FastText's Common Crawl 300dimensional embeddings (Grave et al., 2018). The Page 5 …","url":["https://arxiv.org/pdf/2004.14454"]}
-{"year":"2020","title":"A Longitudinal Analysis of Job Skills for Entry-Level Data Analysts","authors":["T Dong, J Triche - Journal of Information Systems Education, 2020"],"snippet":"… Therefore, we used the Common Crawl dataset to address this problem (http:// commoncrawl.org/). Common Crawl is a non-profit organization that builds and maintains an open repository of web crawl data that is, in essence, a copy of the Internet …","url":["http://jise.org/Volume31/n4/JISEv31n4p312.pdf"]}
-{"year":"2020","title":"A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages","authors":["P Ortiz Suárez, L Romary, B Sagot - arXiv, 2020","PO Suárez, L Romary, B Sagot - arXiv preprint arXiv:2006.06202, 2020"],"snippet":"… al., 2019), a freely available2 multilingual dataset obtained by performing language classification, filtering and cleaning of the whole Common Crawl corpus.3 … 1 https://commoncrawl.org 2 https://traces1.inria.fr/oscar/ 3Snapshot …","url":["https://arxiv.org/pdf/2006.06202","https://ui.adsabs.harvard.edu/abs/2020arXiv200606202O/abstract"]}
-{"year":"2020","title":"A Multilingual Evaluation for Online Hate Speech Detection","authors":["M Corazza, S Menini, E Cabrio, S Tonelli, S Villata - ACM Transactions on Internet …, 2020"],"snippet":"… In particular, we use the Italian and German embeddings trained on Common Crawl and Wikipedia [33] with size 300 … English Fasttext Crawl embeddings: English embeddings trained by Fasttext9 on Common Crawl with an embedding size of 300 …","url":["https://dl.acm.org/doi/abs/10.1145/3377323"]}
-{"year":"2020","title":"A Neural-based model to Predict the Future Natural Gas Market Price through Open-domain Event Extraction","authors":["MT Chau, D Esteves, J Lehmann"],"snippet":"… Strong baseline We feed the price and sentence embedding of filtered news using spaCy small English (Context tensor trained on [39], 300-d embedding vector) and large English model (trained on both [39] and Common Crawl …","url":["http://ceur-ws.org/Vol-2611/paper2.pdf"]}
-{"year":"2020","title":"A NOVEL APPROACH FOR NAMED ENTITY RECOGNITION ON HINDI LANGUAGE USING RESIDUAL BILSTM NETWORK","authors":["R Shelke, D Thakore"],"snippet":"… It provides word embeddings for Hindi (and 157 other languages) and is based on the CBOW (Continuous Bag-of-Words) model. The CBOW model learns by predicting the current word based on its context, and it was trained …","url":["http://www.academia.edu/download/63216061/120200506-26612-102sbv8.pdf"]}
-{"year":"2020","title":"A novel approach to sentiment analysis in Persian using discourse and external semantic information","authors":["R Dehkharghani, H Emami - arXiv preprint arXiv:2007.09495, 2020"],"snippet":"Page 1. * Corresponding Author A novel approach to sentiment analysis in Persian using discourse and external semantic information *Rahim Dehkharghani, Faculty of Engineering, University of Bonab, Bonab, Iran rdehkharghani …","url":["https://arxiv.org/pdf/2007.09495"]}
-{"year":"2020","title":"A Novel BGCapsule Network for Text Classification","authors":["AK Gangwar, V Ravi - arXiv preprint arXiv:2007.04302, 2020"],"snippet":"… GloVe. We used GloVe [21] pretrained model. The GloVe model trained on 2.2 million vocabularies, 840 billion tokens of web data from Common Crawl. This Glove embedding projected each word to a 300-dimensional vector …","url":["https://arxiv.org/pdf/2007.04302"]}
-{"year":"2020","title":"A novel reasoning mechanism for multi-label text classification","authors":["R Wang, R Ridley, W Qu, X Dai - Information Processing & Management"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0306457320309341"]}
-{"year":"2020","title":"A Performance Comparison among Different Amounts of Context on Deep Learning Based Intent Classification Models","authors":["M Jung, J Kim, JY Jang, H Jung, S Shin - 2020 International Conference on …, 2020"],"snippet":"… We also employ word embeddings trained on Common Crawl of fastText [13], a library for efficient text classification and representation learning. We apply a bidirectional LSTM (Bi-LSTM) network [6] to build an LSTM based intent classification model …","url":["https://ieeexplore.ieee.org/abstract/document/9289467/"]}
-{"year":"2020","title":"A Practical Approach for Taking Down Avalanche Botnets Under Real-World Constraints","authors":["D Preuveneers, A Duda, W Joosen, M Korczynski"],"snippet":"Page 1. A Practical Approach for Taking Down Avalanche Botnets Under Real-World Constraints Victor Le Pochat∗, Tim Van hamme∗, Sourena Maroofi§, Tom Van Goethem∗, Davy Preuveneers∗, Andrzej Duda§, Wouter Joosen …","url":["https://lirias.kuleuven.be/retrieve/567093/"]}
-{"year":"2020","title":"A Practical Guide to Hybrid Natural Language Processing: Combining Neural Models and Knowledge Graphs for NLP","authors":["JM Gomez-Perez, R Denaux, A Garcia-Silva - 2020"],"snippet":"Page 1. Jose Manuel Gomez-Perez Ronald Andres Garcia-Silva Denaux A to Practical Hybrid Natural Guide Language Processing Combining Neural Models and Knowledge Graphs for NLP Page 2. A Practical Guide …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=Ou_rDwAAQBAJ&oi=fnd&pg=PR7&dq=commoncrawl&ots=7ExXbVHzPG&sig=WOLotv9GbQ2RA9QHICwuff_hHVM"]}
-{"year":"2020","title":"A Recipe for Creating Multimodal Aligned Datasets for Sequential Tasks","authors":["AS Lin, S Rao, A Celikyilmaz, E Nouri, C Brockett… - arXiv preprint arXiv …, 2020"],"snippet":"… We extract text recipes from Common Crawl,2 one of the largest web sources of text … CommonCrawl text-text recipe pairs We randomly choose 200 text-text recipes pairs (spanning 5 dishes) from the test … Table 3: Results for …","url":["https://arxiv.org/pdf/2005.09606"]}
-{"year":"2020","title":"A Revised Generative Evaluation of Visual Dialogue","authors":["D Massiceti, V Kulharia, PK Dokania, N Siddharth… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. A Revised Generative Evaluation of Visual Dialogue Daniela Massiceti Viveka Kulharia Puneet K. Dokania N. Siddharth Philip HS Torr University of Oxford {daniela, viveka, puneet, nsid, phst} @robots.ox.ac.uk Abstract …","url":["https://arxiv.org/pdf/2004.09272"]}
-{"year":"2020","title":"A Study on Transformer-based Machine Comprehension with Curriculum Learning","authors":["MQ BUI - 2020"],"snippet":"Page 1. Japan Advanced Institute of Science and Technology JAIST Repository https://dspace.jaist.ac.jp/ Title A Study on Transformer-based Machine Comprehension with Curriculum Learning Author(s) BUI, MINH …","url":["https://dspace.jaist.ac.jp/dspace/bitstream/10119/16864/5/paper.pdf"]}
-{"year":"2020","title":"A Survey of Document Grounded Dialogue Systems (DGDS)","authors":["L Ma, WN Zhang, M Li, T Liu - arXiv preprint arXiv:2004.13818, 2020"],"snippet":"Page 1. A Survey of Document Grounded Dialogue Systems (DGDS) LONGXUAN MA, Research Center for Social Computing and Information Retrieval, Harbin Institute of Technology, China WEI-NAN ZHANG, Research Center …","url":["https://arxiv.org/pdf/2004.13818"]}
-{"year":"2020","title":"A Survey on Contextual Embeddings","authors":["Q Liu, MJ Kusner, P Blunsom - arXiv preprint arXiv:2003.07278, 2020"],"snippet":"… T5 introduces a new pre-training dataset, Colossal Clean Crawled Corpus by cleaning the web pages from Common Crawl … by training a Transformerbased masked language model on one hundred languages, using more …","url":["https://arxiv.org/pdf/2003.07278"]}
-{"year":"2020","title":"A Systematic Study of Inner-Attention-Based Sentence Representations in Multilingual Neural Machine Translation","authors":["R Vázquez, A Raganato, M Creutz, J Tiedemann - Computational Linguistics, 2020"],"snippet":"Page 1. Computational Linguistics Just Accepted MS. https://doi.org/10.1162/ COLI_a_00377 © Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license A Systematic Study of Inner-Attention-Based …","url":["https://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_00377"]}
-{"year":"2020","title":"A Text Augmentation Approach using Similarity Measures based on Neural Sentence Embeddings for Emotion Classification on Microblogs","authors":["YK Shyang, JLS Yan - 2020 IEEE 2nd International Conference on Artificial …, 2020"],"snippet":"… vectors. We used two InferSent models available, which were InferSent trained using GloVe on Common Crawl 840B (InferSent-GloVe) and InferSent trained using fastText on Common Crawl 600B (InferSentfastText). Four …","url":["https://ieeexplore.ieee.org/abstract/document/9257826/"]}
-{"year":"2020","title":"A Transformer-based Audio Captioning Model with Keyword Estimation","authors":["Y Koizumi, R Masumura, K Nishida, M Yasuda, S Saito - arXiv preprint arXiv …, 2020"],"snippet":"… sions different. We use the bottleneck feature of VGGish [11] (Dx = 128) for audio embedding, and fastText [18] trained on the Common Crawl corpus (Dw = 300) for caption-word and keyword embedding, respectively. Since the …","url":["https://arxiv.org/pdf/2007.00222"]}
-{"year":"2020","title":"A web analytics approach to map the influence and reach of CCAFS","authors":["B Carneiro, G Resce, Y Ma, G Pacillo, P Läderach - 2020"],"snippet":"Page 1. A web analytics approach to map the influence and reach of CCAFS Working Paper No. 326 CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS) Page 2. A web analytics …","url":["https://cgspace.cgiar.org/bitstream/handle/10568/110588/Working%20Paper-326.pdf?sequence=1&isAllowed=y"]}
-{"year":"2020","title":"A WRITTEN TEST FOR ARTIFICIAL GENERAL INTELLIGENCE","authors":["M Casteluccio - Strategic Finance, 2020"],"snippet":"… If you input a few words, GPT-3 will write a completed thought or sentence. The model was trained on data from Common Crawl, a nonprofit that builds and maintains an open repository of web crawl data accessible to the public for free (common crawl.org) …","url":["http://search.proquest.com/openview/e8f242b31761f187b35a3bb15ab0e724/1?pq-origsite=gscholar&cbl=48426"]}
-{"year":"2020","title":"Accenture at CheckThat! 2020: If you say so: Post-hoc fact-checking of claims using transformer-based models","authors":["E Williams, P Rodrigues, V Novak - arXiv preprint arXiv:2009.02431, 2020","V Novak"],"snippet":"… BPE) instead of WordPiece. [23] The base-roberta model was pre-trained on 160GB of text extracted from BookCorpus, English Wikipedia, CC-News, OpenWebText, and Stories (a subset of CommonCrawl Data) [14]. At the time …","url":["http://ceur-ws.org/Vol-2696/paper_226.pdf","https://arxiv.org/pdf/2009.02431"]}
-{"year":"2020","title":"Accurate and Fast URL Phishing Detector: A Convolutional Neural Network Approach","authors":["W Wei, Q Ke, J Nowak, M Korytkowski, R Scherer… - Computer Networks, 2020"],"snippet":"… The database downloaded during the article writing contained 10,604 records. To obtain legitimate websites, the second part of the training dataset was downloaded from the Common Crawl Foundation (http://commoncrawl.org/) …","url":["https://www.sciencedirect.com/science/article/pii/S1389128620301109"]}
-{"year":"2020","title":"Active Learning for Spreadsheet Cell Classification","authors":["J Gonsior, J Rehak, M Thiele, E Koci, M Günther…"],"snippet":"… Another recent corpus is Fuse [4], which comprises 249, 376 unique spreadsheets, extracted from Common Crawl2. Each spreadsheet is accompanied by a JSON file, which includes NLP token extraction and metrics …","url":["https://wwwdb.inf.tu-dresden.de/wp-content/uploads/SEAData2.pdf"]}
-{"year":"2020","title":"Adaptive GloVe and FastText Model for Hindi Word Embeddings","authors":["V Gaikwad, Y Haribhakta - Proceedings of the 7th ACM IKDD CoDS and 25th …, 2020"],"snippet":"… developed using original GloVe model, FastText model (FastTextHin), Adaptive FastText model (AFM) (trained on Hindi monolingual corpus [11] and FastText embeddings published on the website [25] (FastTextWeb) …","url":["https://dl.acm.org/doi/abs/10.1145/3371158.3371179"]}
-{"year":"2020","title":"ADD: Academic Disciplines Detector Based on Wikipedia","authors":["A Gjorgjevikj, K Mishev, D Trajanov - IEEE Access, 2020"],"snippet":"… For representation of the textual data into fixed-length vector form using pre-trained text encoding models, in addition to the model files, word vectors trained with GloVe [38] on Common Crawl (840B tokens)6 and with FastText …","url":["https://ieeexplore.ieee.org/iel7/6287639/8948470/08948031.pdf"]}
-{"year":"2020","title":"Advanced Semantics for Commonsense Knowledge Extraction","authors":["TP Nguyen, S Razniewski, G Weikum - arXiv preprint arXiv:2011.00905, 2020"],"snippet":"Page 1. Advanced Semantics for Commonsense Knowledge Extraction Tuan-Phong Nguyen Max Planck Institute for Informatics tuanphong@mpi-inf.mpg.de Simon Razniewski Max Planck Institute for Informatics srazniew@mpi-inf.mpg.de …","url":["https://arxiv.org/pdf/2011.00905"]}
-{"year":"2020","title":"Advanced Web Crawlers","authors":["JM Patel - Getting Structured Data from the Internet, 2020"],"snippet":"… A good starting point is using common crawl's fork of Apache Nutch 1.x–based crawler. The codebase is open sourced and available on the GitHub repo (https://github.com/commoncrawl), and it's not only well …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-6576-5_8"]}
-{"year":"2020","title":"Advancements in Deep Learning Theory and Applications: Perspective in 2020 and beyond","authors":["MN Saadat, M Shuaib - Advances and Applications in Deep Learning, 2020"],"snippet":"The aim of this chapter is to introduce newcomers to deep learning, deep learning platforms, algorithms, applications, and open-source datasets. This chapter will give you a broad overview of the term deep learning, in context …","url":["https://www.intechopen.com/books/advances-and-applications-in-deep-learning/advancements-in-deep-learning-theory-and-applications-perspective-in-2020-and-beyond"]}
-{"year":"2020","title":"Advancing Neural Language Modeling in Automatic Speech Recognition","authors":["K Irie - 2020"],"snippet":"Page 1. Advancing Neural Language Modeling in Automatic Speech Recognition Von der Fakultät für Mathematik, Informatik und Naturwissenschaften der RWTH Aachen University zur Erlangung des akademischen Grades …","url":["https://www-i6.informatik.rwth-aachen.de/publications/download/1142/IrieKazuki--AdvancingNeuralLanguageModelinginAutomaticSpeechRecognition--2020.pdf"]}
-{"year":"2020","title":"Adversarial Self-Supervised Data-Free Distillation for Text Classification","authors":["X Ma, Y Shen, G Fang, C Chen, C Jia, W Lu - arXiv preprint arXiv:2010.04883, 2020"],"snippet":"… DeepFace (Taigman et al., 2014) is trained on user images under confidential policies for protecting users. Further, some datasets, like Common Crawl dataset used in GPT3 (Brown et al., 2020), contain nearly a trillion words and are difficult to transmit and store …","url":["https://arxiv.org/pdf/2010.04883"]}
-{"year":"2020","title":"Adversarial Training for Large Neural Language Models","authors":["X Liu, H Cheng, P He, W Chen, Y Wang, H Poon, J Gao - arXiv preprint arXiv …, 2020"],"snippet":"… For continual pre-training of RoBERTa, we use Wikipedia (13GB), OPENWEBTEXT (public Reddit content (Gokaslan and Cohen); 38GB), STORIES (a subset of CommonCrawl (Trinh and Le, 2018); 31GB). 2https://dumps.wikimedia.org/enwiki/ Page 5 …","url":["https://arxiv.org/pdf/2004.08994"]}
-{"year":"2020","title":"Affective Conditioning on Hierarchical Attention Networks applied to Depression Detection from Transcribed Clinical Interviews","authors":["D Xezonaki, G Paraskevopoulos, A Potamianos…"],"snippet":"… Next, for both corpora we tokenize the speaker turns by splitting them into words. We use 300D GloVe [31] pretrained word embeddings, trained on the Common Crawl corpus, to extract word representations. Implementation …","url":["https://indico2.conference4me.psnc.pl/event/35/contributions/3166/attachments/895/934/Thu-3-1-3.pdf"]}
-{"year":"2020","title":"Affective Conditioning on Hierarchical Networks applied to Depression Detection from Transcribed Clinical Interviews","authors":["D Xezonaki, G Paraskevopoulos, A Potamianos… - arXiv preprint arXiv …, 2020"],"snippet":"… Next, for both corpora we tokenize the speaker turns by splitting them into words. We use 300D GloVe [31] pretrained word embeddings, trained on the Common Crawl corpus, to extract word representations. Implementation …","url":["https://arxiv.org/pdf/2006.08336"]}
-{"year":"2020","title":"AgglutiFiT: Efficient Low-Resource Agglutinative Language Model Fine-Tuning","authors":["Z Li, X Li, J Sheng, W Slamu - IEEE Access, 2020"],"snippet":"… test set. For crosslingual pre-training language models, we use the XLM − R model loaded from the torch.Hub that It is trained on 2.5TB of CommonCrawl data, in 17 languages and uses a large vocabulary size of 95K. XLM …","url":["https://ieeexplore.ieee.org/iel7/6287639/8948470/09164940.pdf"]}
-{"year":"2020","title":"AI4Bharat-IndicNLP Corpus: Monolingual Corpora and Word Embeddings for Indic Languages","authors":["A Kunchukuttan, D Kakwani, S Golla, A Bhattacharyya… - arXiv preprint arXiv …, 2020"],"snippet":"… FastText also provides embeddings trained on Wikipedia + CommonCrawl corpus … 1. We augmented our crawls with some data from other sources: Leipzig corpus (Goldhahn et al., 2012) (Tamil and Bengali), WMT NewsCrawl …","url":["https://arxiv.org/pdf/2005.00085"]}
-{"year":"2020","title":"Algorithmic Bias: On the Implicit Biases of Social Technology","authors":["G Johnson - 2020"],"snippet":"… This study found that parsing software trained on a dataset called “the common crawl”—an assemblage of 840 billion words collected by crawling the internet—resulted in the program producing “human-like semantic …","url":["http://philsci-archive.pitt.edu/17169/1/Algorithmic%20Bias.pdf"]}
-{"year":"2020","title":"ALOD2Vec Matcher Results for OAEI 2020","authors":["H Paulheim"],"snippet":"… like DBpedia [8] – but instead on the whole Web: The dataset consists of hypernymy relations extracted from the Common Crawl3, a … 3 see http://commoncrawl.org/ 4 see http://webisa.webdatacommons.org/concept …","url":["http://disi.unitn.it/~pavel/om2020/papers/oaei20_paper2.pdf"]}
-{"year":"2020","title":"An AI-Based System for Formative and Summative Assessment in Data Science Courses","authors":["P Vittorini, S Menini, S Tonelli - International Journal of Artificial Intelligence in …, 2020"],"snippet":"Massive open online courses (MOOCs) provide hundreds of students with teaching materials, assessment tools, and collaborative instruments. The assessment a.","url":["https://link.springer.com/article/10.1007/s40593-020-00230-2"]}
-{"year":"2020","title":"An Analysis of Dataset Overlap on Winograd-Style Tasks","authors":["A Emami, A Trischler, K Suleman, JCK Cheung - arXiv preprint arXiv:2011.04767, 2020"],"snippet":"… This is a form of data contamination. One of the earliest works that trained a language model on Common Crawl data identified and removed a training documents that overlapped with one of their evaluation datasets (Trinh and Le, 2018) …","url":["https://arxiv.org/pdf/2011.04767"]}
-{"year":"2020","title":"An Approach to NMT Re-Ranking Using Sequence-Labeling for Grammatical Error Correction","authors":["B Wang, K Hirota, C Liu, Y Dai, Z Jia"],"snippet":"Page 1. NMT Re-Ranking Using Sequence-Labeling for GEC Paper: An Approach to NMT Re-Ranking Using Sequence-Labeling for Grammatical Error Correction Bo Wang, Kaoru Hirota, Chang Liu, Yaping Dai † , and Zhiyang Jia …","url":["https://www.jstage.jst.go.jp/article/jaciii/24/4/24_557/_pdf"]}
-{"year":"2020","title":"An Effective Phishing Detection Model Based on Character Level Convolutional Neural Network from URL","authors":["A Aljofey, Q Jiang, Q Qu, M Huang, JP Niyigena - Electronics, 2020"],"snippet":"Phishing is the easiest way to use cybercrime with the aim of enticing people to give accurate information such as account IDs, bank details, and passwords. This type of cyberattack is usually triggered by emails, instant messages, or …","url":["https://www.mdpi.com/2079-9292/9/9/1514/pdf"]}
-{"year":"2020","title":"An Empirical Investigation of Performances of Different Word Embedding Algorithms in Comment Clustering","authors":["E Dorani, N Duru, T Yıldız - 2019 Innovations in Intelligent Systems and …"],"snippet":"… In this study, we used the Common Crawl (1.9 million words)1 and (2.0 million word)2 pre-trained word vectors for Glove and FastText, respectively … Such that we used the Common Crawl (1.9 million words) and (2.0 million word) …","url":["https://ieeexplore.ieee.org/abstract/document/8946379/"]}
-{"year":"2020","title":"An Empirical Investigation Towards Efficient Multi-Domain Language Model Pre-training","authors":["K Arumae, Q Sun, P Bhatia - arXiv preprint arXiv:2010.00784, 2020"],"snippet":"… We processed publicly available bio-medical and non-bio-medical corpora for pre-training our models. For non-bio-medical data, we use BookCorpus and English Wikipedia data, CommonCrawl Stories (Trinh and Le, 2018) …","url":["https://arxiv.org/pdf/2010.00784"]}
-{"year":"2020","title":"An Empirical Study of Pre-trained Transformers for Arabic Information Extraction","authors":["W Lan, Y Chen, W Xu, A Ritter - Proceedings of the 2020 Conference on Empirical …, 2020"],"snippet":"… XLM-Rlarge CommonCrawl 295B/55.6B/2.9B SentencePiece 250k/80k/ 14k yes large 550M … and the Gigaword portion three times; (2) adding the Arabic section of the Oscar corpus (Ortiz Suárez et al., 2019), a large-scale …","url":["https://www.aclweb.org/anthology/2020.emnlp-main.382.pdf"]}
-{"year":"2020","title":"An Empirical Study of Transformer-Based Neural Language Model Adaptation","authors":["K Li, Z Liu, T He, H Huang, F Peng, D Povey… - ICASSP 2020-2020 IEEE …, 2020"],"snippet":"… We denote the merged corpus as “Source1” in all tables. The second corpus is an English subset (10%) of the Common Crawl News (CCNews) [27], a news corpus contains articles published worldwide between September 2016 and February 2019 …","url":["https://ieeexplore.ieee.org/abstract/document/9053399/"]}
-{"year":"2020","title":"An Empirical Study on Explainable Prediction of Text Complexity: Preliminaries for Text Simplification","authors":["C Garbacea, M Guo, S Carton, Q Mei - arXiv preprint arXiv:2007.15823, 2020"],"snippet":"… In our experiments we use the 12 layer XLNeT base pre-trained model on 2https://docs.fast.ai/text.html 4 Page 5. the English Wikipedia and the Books corpus (similar to BERT), and additionally also on Giga5 ClueWeb …","url":["https://arxiv.org/pdf/2007.15823"]}
-{"year":"2020","title":"An Empirical Study on Release Engineering of Artificial Intelligence Products","authors":["M Xiu - arXiv preprint arXiv:2012.01403, 2020"],"snippet":"… SPIRAL CelebA HQ 10 (Config: Network Structure) hub.Module Text Embedding Albert Wikipedia, BooksCorpus, Stories, CommonCrawl, Giga5, Clue Web 4 (Config: Model Size) (Data Pre-processing: Cased or Not) hub.Module …","url":["https://arxiv.org/pdf/2012.01403"]}
-{"year":"2020","title":"An English–Swahili parallel corpus and its use for neural machine translation in the news domain","authors":["F Sánchez-Martınez, VM Sánchez-Cartagena…"],"snippet":"… 9https://commoncrawl.github.io/ cc-crawl-statistics/plots/languages 10https://github.com/ CLD2Owners/cld2 300 Page 3. of crawling and, from the remaining 3 232, only 908 ended up containing data in both languages. Document alignment …","url":["https://www.dlsi.ua.es/~fsanchez/pub/pdf/sanchez-martinez20b.pdf"]}
-{"year":"2020","title":"An Enhanced Sentiment Analysis Framework Based on Pre-Trained Word Embedding","authors":["EH Mohamed, MES Moussa, MH Haggag - International Journal of Computational …, 2020"],"snippet":"Login to your account …","url":["https://www.worldscientific.com/doi/abs/10.1142/S1469026820500315"]}
-{"year":"2020","title":"An Evaluation Benchmark for Testing the Word Sense Disambiguation Capabilities of Machine Translation Systems","authors":["A Raganato, Y Scherrer, J Tiedemann - … of The 12th Language Resources and …, 2020"],"snippet":"… Page 2. 3669 CS–EN DE–EN FI–EN FR–EN RU–EN Books GlobalVoices Europarl JW300 News-Comm. Tatoeba TED Talks EU Bookshop MultiUN Common Crawl Table 1: Corpora used to extract the MuCoW test suites. The …","url":["https://www.aclweb.org/anthology/2020.lrec-1.452.pdf"]}
-{"year":"2020","title":"An Evaluation Model for Auto-generated Cognitive Scripts","authors":["AM ELMougi, YMK Omar, R Hodhod"],"snippet":"… Fig. 6. The Cinema Linear Cognitive Script Converted into Text. B. Computing the GloVe Similarity Ratio Threshold The proposed model uses GloVe vectors of 300 dimensions that are created by training Common Crawl (840B tokens …","url":["https://pdfs.semanticscholar.org/14fd/085addcbcebe7e531198d52f041c4e86a3d9.pdf"]}
-{"year":"2020","title":"An Evaluation of Recent Neural Sequence Tagging Models in Turkish Named Entity Recognition","authors":["G Aras, D Makaroglu, S Demir, A Cakir - arXiv preprint arXiv:2005.07692, 2020"],"snippet":"Page 1. An Evaluation of Recent Neural Sequence Tagging Models in Turkish Named Entity Recognition Gizem Arasa,, Didem Makaroglua,b, Seniz Demirc and Altan Cakirb aDemiroren Teknoloji AS, Istanbul, Turkey bDepartment …","url":["https://arxiv.org/pdf/2005.07692"]}
-{"year":"2020","title":"An Exploration in L2 Word Embedding Alignment","authors":["P Liao"],"snippet":"… It is also run for Wikipedia Chinese fastText embeddings to Common Crawl English fastText embeddings to test the method on a large corpus of a different domain. All fastText embeddings are pretrained and downloaded from their website16 …","url":["https://pdfs.semanticscholar.org/513e/16939e369cf09be34ac4c983d20be53a94b1.pdf"]}
-{"year":"2020","title":"An Exploratory Approach to the Corpus Filtering Shared Task WMT20","authors":["A Kejriwal, P Koehn"],"snippet":"… We make the number of lines taken by the wikipedia data be between 40-50% of the number of lines taken by the CommonCrawl data … entropy as defined in Equation 5. We find that the scores we got were ex- tremely …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.108.pdf"]}
-{"year":"2020","title":"An Interactive Network for End-to-End Review Helpfulness Modeling","authors":["J Du, L Zheng, J He, J Rong, H Wang, Y Zhang - Data Science and Engineering, 2020"],"snippet":"Review helpfulness prediction aims to prioritize online reviews by quality. Existing methods largely combine review texts and star ratings for helpfulness.","url":["https://link.springer.com/article/10.1007/s41019-020-00133-1"]}
-{"year":"2020","title":"An Iterative Knowledge Transfer NMT System for WMT20 News Translation Task","authors":["J Kim, S Park, S Kim, Y Choi - Proceedings of the Fifth Conference on Machine …, 2020"],"snippet":"… Kyoto Free Translation Task 0.44M TED Talks 0.24M Monolingual Data (En) Europarl v10 2.29M News Commentary v15 0.6M News Crawl 23.35M News Discussions 63.51M Monolingual Data (Ja) News Crawl …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.11.pdf"]}
-{"year":"2020","title":"An Open-Domain Web Search Engine for Answering Comparative Questions","authors":["T Abye, T Sager, AJ Triebel"],"snippet":"… pp. 91–96 (2017) 3. Bevendorff, J., Stein, B., Hagen, M., Potthast, M.: Elastic ChatNoir: Search Engine for the ClueWeb and the Common Crawl. In: Azzopardi, L., Hanbury, A., Pasi, G., Piwowarski, B. (eds.) Advances in Information Retrieval …","url":["http://ceur-ws.org/Vol-2696/paper_130.pdf"]}
-{"year":"2020","title":"Analogical frames by constraint satisfaction","authors":["L De Vine - 2020"],"snippet":"Page 1. Analogical Frames by Constraint Satisfaction A THESIS SUBMITTED IN FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Lance De Vine BMaths …","url":["https://eprints.qut.edu.au/198036/1/Lance_De%20Vine_Thesis.pdf"]}
-{"year":"2020","title":"Analysis of the communication of smart city features through social media","authors":["JP Fontanilles"],"snippet":"Page 1. Jordi Pascual Fontanilles Analysis of the communication of smart city features through social media MASTER'S THESIS Supervised by Dr. Antonio Moreno Ribas Computer Security Engineering and Artificial …","url":["https://deim.urv.cat/~itaka/itaka2/PDF/acabats/MEMORIA_TFM_JordiPascual.pdf"]}
-{"year":"2020","title":"Analyzing Sustainability Reports Using Natural Language Processing","authors":["A Luccioni, E Bailor, N Duchene - arXiv preprint arXiv:2011.08073, 2020"],"snippet":"… In fact, research in financial NLP has found that using general-purpose NLP models trained on corpora such as Wikipedia and the Common Crawl fail to capture domainspecific terms and concepts which are critical for a coherent …","url":["https://arxiv.org/pdf/2011.08073"]}
-{"year":"2020","title":"Analyzing the Effect of Community Norms on Gender Bias","authors":["NR Raut - 2020"],"snippet":"… We use word2vec to train embeddings on the comment data for each of the subreddit. For fasttext, we use 2 million word vectors trained with subword information on Common Crawl …","url":["http://search.proquest.com/openview/18f1238b848a27a836459d849f5795c8/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2020","title":"ANDI@ CONCRETEXT: Predicting concreteness in context for English and Italian using distributional models and behavioural norms","authors":["A Rotaru - Proceedings of the 7th evaluation campaign of Natural …, 2020"],"snippet":"… Skip-gram (Google News – 100B) 21 21 21 21 GloVe (Common Crawl – 840B) 21 21 21 21 ConceptNet NumberBatch (ConceptNet + Skip-gram + GloVe) … abs(V(w) - V(c)) Behavioural norms (frequency, etc.) 20 20 20 20 …","url":["http://ceur-ws.org/Vol-2765/paper100.pdf"]}
-{"year":"2020","title":"Announcing CzEng 2.0 Parallel Corpus with over 2 Gigawords","authors":["T Kocmi, M Popel, O Bojar - arXiv preprint arXiv:2007.03006, 2020"],"snippet":"… format. New parallel data come from Europarl (v10), News commentary, Wikititles, Commoncrawl, Paracrawl2, WikiMatrix (Schwenketal., 2019), and Tilde MODEL Corpus (EESC, EMA, Rapid; Rozis and Skadinš, 2017). We …","url":["https://arxiv.org/pdf/2007.03006"]}
-{"year":"2020","title":"Anomaly detection with Generative Adversarial Networks and text patches","authors":["A Drozdyuk, N Eke"],"snippet":"… We used the model containing two million word vectors trained on Common Crawl … The depressive data was similarly cleaned. After cleaning the data it was converted to word vectors using the FastText model trained on Common Crawl and Wikipedia [12] …","url":["https://norberte.github.io/assets/pdf/GAN%20Project%20Report.pdf"]}
-{"year":"2020","title":"Another factor to consider is the user's perspective. Everyone uses web search. Using a search engine to look things up on the web is the most popular activity on the …","authors":["D Lewandowski"],"snippet":"… Indexes that offer complete access do, however, exist. At the top of this list is Common Crawl,NOTE 12 a nonprofit project that aims to provide a web index for anyone who's interested … Common Crawl represents an important development …","url":["https://pandoc.networkcultures.org/epub/SotQreader/ch010.xhtml"]}
-{"year":"2020","title":"Answering Comparative Questions with Arguments","authors":["A Bondarenko, A Panchenko, M Beloucif, C Biemann… - Datenbank-Spektrum, 2020"],"snippet":"… analyzing Wikidata and DBpedia as additional sources of (structured) information besides the retrieval of sentences/documents from the Common Crawl … Ruppert E, Faralli S, Ponzetto SP, Biemann C (2018) Building a …","url":["https://link.springer.com/article/10.1007/s13222-020-00346-8"]}
-{"year":"2020","title":"Answering Event-Related Questions over Long-term News Article Archives","authors":["J Wang, A Jatowt, M Färber, M Yoshikawa"],"snippet":"… We can see that the actual time scope (January, 1988) of the first question is reflected relatively well by its distribution of relevant documents as generally 4 We use Glove [23] embeddings trained on the Common Crawl dataset with 300 dimensions. Page 6 …","url":["http://www.aifb.kit.edu/images/1/19/QA_ECIR2020.pdf"]}
-{"year":"2020","title":"Application of Machine Learning Techniques for Text Generation","authors":["S Martí Román - 2020"],"snippet":"Page 1. Escola Tècnica Superior d'Enginyeria Informàtica Universitat Politècnica de València Application of Machine Learning Techniques for Text Generation DEGREE FINAL WORK Degree in Computer Engineering Author: Salvador Martí Román …","url":["https://riunet.upv.es/bitstream/handle/10251/149583/Mart%C3%AD%20-%20Uso%20de%20t%C3%A9cnicas%20de%20aprendizaje%20autom%C3%A1tico%20para%20la%20generaci%C3%B3n%20de%20texto.pdf?sequence=1"]}
-{"year":"2020","title":"Application of Machine Learning to Classify News Headlines","authors":["P Guttula, RM Aburas, S Srijan"],"snippet":""}
-{"year":"2020","title":"AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document Summarization","authors":["S Kulkarni, S Chammas, W Zhu, F Sha, E Ie - arXiv preprint arXiv:2010.12694, 2020"],"snippet":"… is a nontrivial task in itself and there are several con1https://commoncrawl org … paragraphs, we use a pre-processed and cleaned version of the Common Crawl corpus (Raffel et al … We illustrate our approach us- ing Google's Natural …","url":["https://arxiv.org/pdf/2010.12694"]}
-{"year":"2020","title":"AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddings","authors":["A Lauscher, R Takieddin, SP Ponzetto, G Glavaš - arXiv preprint arXiv:2011.01575, 2020"],"snippet":"… For FT, we investigate two models, one trained on the portions of Wikipedia and CommonCrawl corpora written in Modern Standard Arabic (MS) and the other on portions written in Egyptian Arabic.9 We evaluate the four variants …","url":["https://arxiv.org/pdf/2011.01575"]}
-{"year":"2020","title":"ArchiMeDe@ DANKMEMES: A New Model Architecture for Meme Detection","authors":["J Setpal, G Sarti"],"snippet":"… We fine-tune representations over the available meme textual data and use them as components of our end-to-end system. 1umberto-commoncrawl-cased-v1 in the HuggingFace's model hub (Wolf et al., 2019) Page 4. 2.3 Visual input …","url":["http://ceur-ws.org/Vol-2765/paper138.pdf"]}
-{"year":"2020","title":"Are All Good Word Vector Spaces Isomorphic?","authors":["I Vulić, S Ruder, A Søgaard - arXiv preprint arXiv:2004.04070, 2020"],"snippet":"… 3Recent initiatives replace training on Wikipedia with training on larger CommonCrawl data (Grave et al., 2018; Conneau et al., 2020), but the large differences in corpora sizes between high-resource and low-resource languages are not removed …","url":["https://arxiv.org/pdf/2004.04070"]}
-{"year":"2020","title":"Are All Languages Created Equal in Multilingual BERT?","authors":["S Wu, M Dredze - arXiv preprint arXiv:2005.09093, 2020"],"snippet":"… (2019) train a multilingual masked language model (Devlin et al., 2019) on 2.5TB of CommonCrawl filtered data covering 100 languages and show it outperforms a Wikipedia-based model on low resource languages (Urdu …","url":["https://arxiv.org/pdf/2005.09093"]}
-{"year":"2020","title":"Argumentative relation classification for argumentative dialogue systems","authors":["C Schindler - 2020"],"snippet":"… With this setup, args outperformed ArgumenText in the category related. 3.2.2. ArgumenText The search engine ArgumenText [35] uses the English part of CommonCrawl2 to retrieve relevant documents … 2http://commoncrawl …","url":["https://oparu.uni-ulm.de/xmlui/bitstream/handle/123456789/33973/BScThesis_SchindlerC.pdf?sequence=3&isAllowed=y"]}
-{"year":"2020","title":"Argumentative Topology: Finding Loop (holes) in Logic","authors":["S Tymochko, Z New, L Bynum, E Purvine, T Doster… - arXiv preprint arXiv …, 2020"],"snippet":"… Word embeddings are performed using two pretrained models: Word2Vec trained on the Google News dataset [12] and GloVe trained on Common Crawl [13]. We compute the persistence diagrams of the topological …","url":["https://arxiv.org/pdf/2011.08952"]}
-{"year":"2020","title":"ArgumenText: Argument Classification and Clustering in a Generalized Search Scenario","authors":["J Daxenberger, B Schiller, C Stahlhut, E Kaiser… - Datenbank-Spektrum, 2020"],"snippet":"… Full size image. For the public version of the ArgumenText search engine, we indexed more than 400 million English and German web pages from the CommonCrawl project and segmented all documents into sentences [21] …","url":["https://link.springer.com/article/10.1007/s13222-020-00347-7"]}
-{"year":"2020","title":"Artificial Intelligence in mental health and the biases of language based models","authors":["I Straw, C Callison-Burch - PloS one, 2020"],"snippet":"… 52]. As described by Pennington et al. GloVe embeddings were trained on text copora from Wikipedia data, Gigaword and web data from Common Crawl which built a vocabulary of 400,000 frequent words [57]. Word2Vec was …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0240376"]}
-{"year":"2020","title":"ASAPPpy: a Python Framework for Portuguese STS?","authors":["J Santos, A Alves, HG Oliveira"],"snippet":"… 20 Page 8. From those, CBOW Word2vec and GloVe, both with 300-dimensioned vectors, were selected; (ii) fastText.cc embeddings [9], which provide word vectors for 157 languages, trained on Common Crawl and Wikipedia using fastText …","url":["http://ceur-ws.org/Vol-2583/2_ASAPPpy.pdf"]}
-{"year":"2020","title":"Ascent of Pre-trained State-of-the-Art Language Models","authors":["K Nagda, A Mukherjee, M Shah, P Mulchandani… - Advanced Computing …, 2020"],"snippet":"… 6.2 Dataset. Similar to BERT, XLNet was pre-trained using English Wikipedia dataset (13 GB of plain text), as well as CommonCrawl, Giga5 and ClueWeb 2012-B datasets [11]. The large variant of the model has a sequence and …","url":["https://link.springer.com/chapter/10.1007/978-981-15-3242-9_26"]}
-{"year":"2020","title":"Aspect-Controlled Neural Argument Generation","authors":["B Schiller, J Daxenberger, I Gurevych - Training"],"snippet":"… Consequently, the following preprocessing steps ultimately target retrieval and classification of sentences. To evaluate different data sources, we use a dump from Common-Crawl2 (CC) and Reddit comments3 …","url":["https://public.ukp.informatik.tu-darmstadt.de/UKP_Webpage/publications/2020/2020_PP_BES_aspect_controlled_argument_generation_v0.2.pdf"]}
-{"year":"2020","title":"Assessing Demographic Bias in Named Entity Recognition","authors":["S Mishra, S He, L Belli"],"snippet":"… level confidence via the Constrained ForwardBackward algorithm [5]. Different versions of this model were trained on CoNLL 03 NER benchmark dataset [27] by utilizing varying embedding methods: (a) GloVe uses GloVe 840B …","url":["https://kg-bias.github.io/NER_Bias_KG_Bias.pdf"]}
-{"year":"2020","title":"Assessing Suitable Word Embedding Model for Malay Language through Intrinsic Evaluation","authors":["YT Phua, KH Yew, OM Foong, MYW Teow - 2020 International Conference on …, 2020"],"snippet":"… This mode was trained on Common Crawl and Wikipedia [26], and pre-trained word vectors for 294 languages were trained on Wikipedia [22]. The results of the evaluation were 0.477 for Pearson correlation coefficient and 0.51 …","url":["https://ieeexplore.ieee.org/abstract/document/9247707/"]}
-{"year":"2020","title":"ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations","authors":["F Alva-Manchego, L Martin, A Bordes, C Scarton… - arXiv preprint arXiv …, 2020"],"snippet":"… stopwords). We use the 50k most frequent words of the FastText word embeddings vo- cabulary (Bojanowski et al., 2016). This vo- cabulary was originally sorted with frequencies of words in the Common Crawl. This score …","url":["https://arxiv.org/pdf/2005.00481"]}
-{"year":"2020","title":"Attention-based hierarchical recurrent neural networks for MOOC forum posts analysis","authors":["N Capuano, S Caballé, J Conesa, A Greco - Journal of Ambient Intelligence and …, 2020"],"snippet":"… WikiNER corpora (Nivre et al. 2016) for Italian as well as the OntoNotes (Pradhan and Ramshaw 2017) and the Common Crawl Footnote 2 corpora for English. Text categorization model. Independently from the specific document …","url":["https://link.springer.com/article/10.1007/s12652-020-02747-9"]}
-{"year":"2020","title":"Attention-based Model for Evaluating the Complexity of Sentences in English Language","authors":["D Schicchi, G Pilato, GL Bosco - 2020 IEEE 20th Mediterranean Electrotechnical …, 2020"],"snippet":"… The output of the attention layer (context-vector) is given as input to a dense layer, which gives the probability that the sentence belongs to either hard-to-understand or easy-to- 1www.wikipedia.org 2www.commoncrawl …","url":["https://ieeexplore.ieee.org/abstract/document/9140531/"]}
-{"year":"2020","title":"Attribute Sentiment Scoring with Online Text Reviews: Accounting for Language Structure and Missing Attributes","authors":["I Chakraborty, M Kim, K Sudhir - 2020"],"snippet":"… 10These embeddings have been trained on different corpus like Wikipedia dumps, Gigaword news dataset and web data from Common Crawl and have more than 5 billion unique tokens. Page 18. 17 lenging text and image classification problems (Wang et al …","url":["https://www.ishitachakra.com/JobMarketPaper_IshitaYale.pdf"]}
-{"year":"2020","title":"Augmenting cross-domain knowledge bases using web tables","authors":["Y Oulabi - 2020"],"snippet":"Page 1. Augmenting Cross-Domain Knowledge Bases Using Web Tables Inauguraldissertation zur Erlangung des akademischen Grades eines Doktors der Naturwissenschaften der Universität Mannheim vorgelegt von Yaser …","url":["https://madoc.bib.uni-mannheim.de/55962/1/Oulabi2020_PhD_thesis.pdf"]}
-{"year":"2020","title":"Author2Vec: A Framework for Generating User Embedding","authors":["X Wu, W Lin, Z Wang, E Rastorgueva - arXiv preprint arXiv:2003.11627, 2020"],"snippet":"… the user. We used the Facebook FastText (https:// fasttext.cc/) pre-trained Word2Vec model: crawl-300d-2M, which is a model with 2 million word vectors trained on Common Crawl (600B to- kens). The baseline implementations …","url":["https://arxiv.org/pdf/2003.11627"]}
-{"year":"2020","title":"Autoencoding Improves Pre-trained Word Embeddings","authors":["M Kaneko, D Bollegala - arXiv preprint arXiv:2010.13094, 2020"],"snippet":"… 3M words learnt from the Google News corpus), GloVe2 (300-dimensional word embeddings for ca. 2.1M words learnt from the Common Crawl), and fastText3 (300dimensional embeddings for ca. 2M words learnt from the Common Crawl) …","url":["https://arxiv.org/pdf/2010.13094"]}
-{"year":"2020","title":"Automated coding of implicit motives: A machine‑learning approach","authors":["JS Pang, H Ring"],"snippet":"… experiments we decided to use Facebook's FastText subword embeddings of 300 dimensions trained on Common Crawl (600 billion tokens).5 This is the set of pre-trained vectors that we used to derive word features from …","url":["https://link.springer.com/content/pdf/10.1007/s11031-020-09832-8.pdf"]}
-{"year":"2020","title":"Automated Short Answer Grading: A Simple Solution for a Difficult Task","authors":["S Menini, S Tonelli, G De Gasperis, P Vittorini"],"snippet":"… combining vectors representing both words and subwords. To generate these embeddings we start from the pre-computed Italian language model3 trained on Common Crawl and Wikipedia. The latter, in particular, is suitable …","url":["https://pdfs.semanticscholar.org/9ff2/6a502dd1b3e0c136af4bc2ca9af9b901fce4.pdf"]}
-{"year":"2020","title":"Automatic Detection of Machine Generated Text: A Critical Survey","authors":["G Jawahar, M Abdul-Mageed, LVS Lakshmanan - arXiv preprint arXiv:2011.01314, 2020"],"snippet":"… GPT-3 (Brown et al., 2020) fragments from CommonCrawl (570GB / 175B) three previous news articles and title of a proposed article body of the proposed article top-p fake news Table 1: Summary of the characteristics of TGMs that can act as threat models …","url":["https://arxiv.org/pdf/2011.01314"]}
-{"year":"2020","title":"Automatic language identification of short texts","authors":["A Avenberg - 2020"],"snippet":"Page 1. UPTEC F 20043 Examensarbete 30 hp September 2020 Automatic language identification of short texts Anna Avenberg Page 2. Teknisknaturvetenskaplig fakultet UTH-enheten Besöksadress: Ångströmlaboratoriet …","url":["https://www.diva-portal.org/smash/get/diva2:1473718/FULLTEXT01.pdf"]}
-{"year":"2020","title":"Automatic Metaphor Interpretation Using Word Embeddings","authors":["K Bar, N Dershowitz, L Dankin - arXiv preprint arXiv:2010.02665, 2020"],"snippet":"… relatively large corpus. Specifically, we use DepCC,1 a dependency-parsed “web-scale corpus” based on CommonCrawl.2 There are 365 million documents in the corpus, comprising about 252B tokens. Among other preprocessing …","url":["https://arxiv.org/pdf/2010.02665"]}
-{"year":"2020","title":"Automatic Poetry Generation from Prosaic Text","authors":["T Van de Cruys - Proceedings of the 58th Annual Meeting of the …, 2020"],"snippet":"Page 1. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2471–2480 July 5 - 10, 2020. c 2020 Association for Computational Linguistics 2471 Automatic Poetry Generation from Prosaic Text …","url":["https://www.aclweb.org/anthology/2020.acl-main.223.pdf"]}
-{"year":"2020","title":"Automatic Short Answer Grading using Text-to-Text Transfer Transformer Model","authors":["S Haller - 2020"],"snippet":"Page 1. Faculty of Electrical Engineering, Mathematics & Computer Science Automatic Short Answer Grading using Text-to-Text Transfer Transformer Model Stefan Haller M.Sc. Thesis in Business Information …","url":["http://essay.utwente.nl/83879/7/Haller_MA_EEMCS.pdf"]}
-{"year":"2020","title":"Automatic Speech Recognition for ILSE-Interviews: Longitudinal Conversational Speech Recordings covering Aging and Cognitive Decline","authors":["A Abulimiti, J Weiner, T Schultz"],"snippet":"… In addition, we selected text data similar to ILSE from large amounts of Common Crawl Data1 based on Term Frequency–Inverse Document Frequency (tf-idf) for the training of Recurrent Neural Network (RNN) based …","url":["https://indico2.conference4me.psnc.pl/event/35/contributions/3209/attachments/742/780/Thu-SS-1-6-9.pdf"]}
-{"year":"2020","title":"Automatic text segmentation based on relevant context","authors":["S Kim, WW Chang, N Lipka, F Dernoncourt, CY Park - US Patent App. 16/368,334, 2020"],"snippet":"US20200311207A1 - Automatic text segmentation based on relevant context - Google Patents. Automatic text segmentation based on relevant context. Download PDF Info. Publication number US20200311207A1. US20200311207A1 …","url":["https://patents.google.com/patent/US20200311207A1/en"]}
-{"year":"2020","title":"Automating Just-In-Time Comment Updating","authors":["Z Liu, X Xia, M Yan, S Li","Z Liu, X Xia, M Yan, S Li - Automated Software Engineering, to appear, 2020"],"snippet":"Page 1. Automating Just-In-Time Comment Updating Zhongxin Liu∗† Zhejiang University China liu_zx@zju.edu.cn Xin Xia‡ Monash University Australia xin.xia@monash.edu Meng Yan Chongqing University China mengy@cqu.edu.cn …","url":["https://pdfs.semanticscholar.org/0b03/b1526e88c8780214697bbe9163b95a59cdbd.pdf","https://xin-xia.github.io/publication/ase202.pdf"]}
-{"year":"2020","title":"Automating Text Naturalness Evaluation of NLG Systems","authors":["E Çano, O Bojar - arXiv preprint arXiv:2006.13268, 2020"],"snippet":"… The model is trained on RealNews, a large news collection they derived from Page 4. 4 E. Çano and O. Bojar Common Crawl1 dumps … They are typically assessed by 1 https://commoncrawl.org/ 2 http://www.statmt.org …","url":["https://arxiv.org/pdf/2006.13268"]}
-{"year":"2020","title":"BanFakeNews: A Dataset for Detecting Fake News in Bangla","authors":["MZ Hossain, MA Rahman, MS Islam, S Kar - arXiv preprint arXiv:2004.08789, 2020"],"snippet":"… words in it. We experiment with the Bangla 300 dimensional word vectors pre-trained7 with Fasttext (Grave et al., 2018) on Wikipedia8 and Common Crawl9, where we have a coverage of 55.21%. Additionally, we experiment …","url":["https://arxiv.org/pdf/2004.08789"]}
-{"year":"2020","title":"Bangla Text Classification using Transformers","authors":["T Alam, A Khan, F Alam - arXiv preprint arXiv:2011.04446, 2020"],"snippet":"… NSP task is removed and only MLM loss is used for pretraining. XLM-RoBERTa [18] is the multilingual variant of RoBERTa trained with a multilingual MLM. It is trained on one hundred languages, with more than two terabytes of filtered Common Crawl data …","url":["https://arxiv.org/pdf/2011.04446"]}
-{"year":"2020","title":"Bankruptcy Map: A System for Searching and Analyzing US Bankruptcy Cases at Scale","authors":["E Choi, G Brassil, K Keller, J Ouyang, K Wang"],"snippet":"… layers [14]. The network was pre-trained on the large OntoNotes dataset, with GloVe vectors used for feature creation trained on Common Crawl data [3, 16]. The model recognized named entities and their types. We collected …","url":["https://cpb-us-w2.wpmucdn.com/express.northeastern.edu/dist/d/53/files/2020/02/CJ_2020_paper_57.pdf"]}
-{"year":"2020","title":"BARThez: a Skilled Pretrained French Sequence-to-Sequence Model","authors":["MK Eddine, AJP Tixier, M Vazirgiannis - arXiv preprint arXiv:2010.12321, 2020"],"snippet":"… Other than that, BARTHez corpus is similar to FlauBERT's. It primarily consists in the French part of CommonCrawl, NewsCrawl, Wikipedia and other smaller corpora that are listed in Table 1. To clean the corpus from noisy examples …","url":["https://arxiv.org/pdf/2010.12321"]}
-{"year":"2020","title":"Benchmarking Neural and Statistical Machine Translation on Low-Resource African Languages","authors":["K Duh, P McNamee, M Post, B Thompson"],"snippet":"… The columns CommonCrawl and Wikipedia indicate the amount of monolingual data on the web, which can be viewed as an indicator of the upper limit of how much web-crawled data we may be able to obtain. CommonCrawl …","url":["https://pdfs.semanticscholar.org/3bde/97a22dab1147b0f3209805315bbff9b82674.pdf"]}
-{"year":"2020","title":"BERT-based Ensembles for Modeling Disclosure and Support in Conversational Social Media Text","authors":["K Pant, T Dadu, R Mamidi - 2020"],"snippet":"… Gokaslan, A., Cohen, V.: Openwebtext corpus. http://Skylion007.github.io/ OpenWebTextCorpus (2019) 5. Nagel, S.: Cc-news (2016), http://web.archive.org/save/ http://commoncrawl. org/2016/10/newsdataset-available/ 6. Rajendran …","url":["http://web2py.iiit.ac.in/research_centres/publications/download/inproceedings.pdf.83b74a0e278a6d03.424552542d626173656420456e73656d626c657320666f72204d6f64656c696e6720446973636c6f73757265202620537570706f727420696e20436f6e766572736174696f6e616c20536f6369616c204d6564696120546578742e706466.pdf"]}
-{"year":"2020","title":"BERT-Based Simplification of Japanese Sentence-Ending Predicates in Descriptive Text","authors":["T Kato, R Miyata, S Sato - Proceedings of the 13th International Conference on …, 2020"],"snippet":"… For any parts having more than one word, the average of the embedding is used. To obtain the embedding vectors, we used existing Japanese pre-trained word vectors that were trained on Common Crawl and Wikipedia using fastText.7 …","url":["https://www.aclweb.org/anthology/2020.inlg-1.31.pdf"]}
-{"year":"2020","title":"BERTweet: A pre-trained language model for English Tweets","authors":["DQ Nguyen, T Vu, AT Nguyen - arXiv preprint arXiv:2005.10200, 2020"],"snippet":"… The pre-trained RoBERTa is a strong language model for English, learned from 160GB of texts covering books, Wikipedia, CommonCrawl news, CommonCrawl stories, and web text contents. XLM-R is a cross-lingual variant …","url":["https://arxiv.org/pdf/2005.10200"]}
-{"year":"2020","title":"Better Web Corpora For Corpus Linguistics And NLP","authors":["V Suchomel"],"snippet":"Page 1. Masaryk University Faculty of Informatics Better Web Corpora For Corpus Linguistics And NLP Doctoral Thesis Vít Suchomel Brno, Spring 2020 Page 2. Masaryk University Faculty of Informatics Better Web Corpora …","url":["https://is.muni.cz/th/u4rmz/Better_Web_Corpora_For_Corpus_Linguistics_And_NLP.pdf"]}
-{"year":"2020","title":"Beyond English-Centric Multilingual Machine Translation","authors":["A Fan, S Bhosale, H Schwenk, Z Ma, A El-Kishky… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Beyond English-Centric Multilingual Machine Translation Angela Fan∗, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines, Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary …","url":["https://arxiv.org/pdf/2010.11125"]}
-{"year":"2020","title":"Beyond Instructional Videos: Probing for More Diverse Visual-Textual Grounding on YouTube","authors":["J Hessel, Z Zhu, B Pang, R Soricut - arXiv preprint arXiv:2004.14338, 2020"],"snippet":"… corresponding visual content. However, in contrast to the highly diverse corpora utilized for text-based pretraining (Wikipedia, Common Crawl, etc.), pretraining for web videos so far has been limited to instructional videos. This domain …","url":["https://arxiv.org/pdf/2004.14338"]}
-{"year":"2020","title":"Biases as Values: Evaluating Algorithms in Context","authors":["M Díaz - 2020"],"snippet":"Page 1. NORTHWESTERN UNIVERSITY Biases as Values: Evaluating Algorithms in Context A DISSERTATION SUBMITTED TO THE GRADUATE SCHOOL IN PARTIAL FULFILLMENT OF THE REQUIREMENTS for the degree DOCTOR OF PHILOSOPHY …","url":["http://search.proquest.com/openview/83eed19485a394e067ee5a9b03d84ef2/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2020","title":"Biomedical Information Extraction Pipelines for Public Health in the Age of Deep Learning","authors":["AM Ranganatha - 2019"],"snippet":"Page 1. Biomedical Information Extraction Pipelines for Public Health in the Age of Deep Learning by Arjun Magge Ranganatha A Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy …","url":["http://search.proquest.com/openview/bf6cbc4695dc3135c8e78ff548e670f8/1?pq-origsite=gscholar&cbl=2026366&diss=y"]}
-{"year":"2020","title":"Blocking Techniques for Entity Linkage: A Semantics-Based Approach","authors":["F Azzalini, S Jin, M Renzi, L Tanca - Data Science and Engineering, 2020"],"snippet":"… each attribute value \\(t[A_{k}]\\) is transformed into a real-valued vector \\(\\mathbf{v }(w)\\). The fastText model we use is crawl-300d-2M-subword [23] where each word is represented as a 300-dimensional vector and the …","url":["https://link.springer.com/article/10.1007/s41019-020-00146-w"]}
-{"year":"2020","title":"Bottom-Up Modeling of Permissions to Reuse Residual Clinical Biospecimens and Health Data","authors":["E Umberfield - 2020"],"snippet":"Page 1. Bottom-Up Modelling of Permissions to Reuse Residual Clinical Biospecimens and Health Data by Elizabeth Umberfield A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/162937/eliewolf_1.pdf?sequence=1"]}
-{"year":"2020","title":"BREXIT: Psychometric Profiling the Political Salubrious through Machine Learning","authors":["J Usher, P Dondio"],"snippet":"… We used the English multi-task Convoluted Neural Network trained on OntoNotes, with GloVe vectors trained on Common Crawl, which assigns word vectors, context-specific token vectors, POS tags, dependency parse …","url":["http://wims2020.sigappfr.org/wp-content/uploads/2020/06/WIMS'20/p178-Usher.pdf"]}
-{"year":"2020","title":"BREXIT: Psychometric Profiling the Political Salubrious through Machine Learning: Predicting personality traits of Boris Johnson through Twitter political text","authors":["J Usher, P Dondio - Proceedings of the 10th International Conference on …, 2020"],"snippet":"… We used the English multi-task Convoluted Neural Network trained on OntoNotes, with GloVe vectors trained on Common Crawl, which assigns word vectors, context-specific token vectors, POS tags, dependency parse …","url":["https://dl.acm.org/doi/abs/10.1145/3405962.3405981"]}
-{"year":"2020","title":"Building a user-generated content north-african arabizi treebank: Tackling hell","authors":["D Seddah, F Essaidi, A Fethi, M Futeral, B Muller… - Proceedings of the 58th …, 2020"],"snippet":"… used data-driven language identification models to extract NArabizi samples among the whole collection of the Common-Crawl-based OSCAR … one based on search query-based web-crawling and the other from a cleaned version …","url":["https://www.aclweb.org/anthology/2020.acl-main.107.pdf"]}
-{"year":"2020","title":"Building a Wide Reach Corpus for Secure Parser Development","authors":["T Allison, W Burke, V Constantinou, E Goh…"],"snippet":"… [17] CGR Lavanya Pamulaparty and MS Rao, “A novel approach for avoiding overload in the web crawling.” Odisha, India: High Performance Computing and Applications (ICHPCA), 2014. [18] “Common Crawl,” https://commoncrawl.org …","url":["http://spw20.langsec.org/papers/corpus_LangSec2020.pdf"]}
-{"year":"2020","title":"Building LARO: Language Agnostic Sentence Embeddings from finetuned RoBERTa⋆","authors":["AS Salvado"],"snippet":"… XLM-RoBERTa is the successor of RoBERTa and a large multi-lingual language model. It is a Transformer-based model, technically a Transformer en- coder, and was trained on 2.5TB of filtered CommonCrawl data in 100 …","url":["https://users.informatik.haw-hamburg.de/~ubicomp/projekte/master2020-proj/soblechero.pdf"]}
-{"year":"2020","title":"Building Web Corpora for Minority Languages","authors":["H Jauhiainen, T Jauhiainen, K Lindén - Proceedings of the 12th Web as Corpus …, 2020"],"snippet":"… Common Crawl Foundation3 regularly crawls the Internet and offers the texts it finds for free download. Smith et al … Kanerva et al. (2014) used the morphological analyser OMorFi4 to find Finnish sentences in the Common Crawl corpus …","url":["https://www.aclweb.org/anthology/2020.wac-1.4.pdf"]}
-{"year":"2020","title":"Caliskan Et Al-authors-full","authors":["A Caliskan, JJ Bryson, A Narayanan"],"snippet":"… We use the largest of the four corpora provided—the “Common Crawl” corpus obtained from a large-scale crawl of the web, containing 840 billion tokens (roughly, words). Tokens in this corpus are casesensitive, resulting in 2.2 million different ones …","url":["https://www.studeersnel.nl/nl/document/technische-universiteit-delft/machine-learning/werkstukessay/caliskan-et-al-authors-full/9896508/view"]}
-{"year":"2020","title":"CALM: Continuous Adaptive Learning for Language Modeling","authors":["K Arumae, P Bhatia - arXiv preprint arXiv:2004.03794, 2020"],"snippet":"… We processed publicly available biomedical and non-biomedical corpora for pre-training our models. For non-biomedical data, we use BookCorpus and English Wikipedia data, CommonCrawl Stories (Trinh and Le, 2018), and OpenWebText (Gokaslan and Cohen) …","url":["https://arxiv.org/pdf/2004.03794"]}
-{"year":"2020","title":"Can Embeddings Adequately Represent Medical Terminology? New Large-Scale Medical Term Similarity Datasets Have the Answer!","authors":["C Schulz, D Juric - arXiv preprint arXiv:2003.11082, 2020"],"snippet":"… 3) Non-medical: As a comparison, we also include - the GloVe word embedding (Pennington, Socher, and Manning 2014); - 2 Fasttext embeddings trained on Wikipedia and Common Crawl (plus its model (M)) (Mikolov et al. 2018) …","url":["https://arxiv.org/pdf/2003.11082"]}
-{"year":"2020","title":"Can Emojis Convey Human Emotions? A Study to Understand the Association between Emojis and Emotions","authors":["AAM Shoeb, G de Melo - Proceedings of the 2020 Conference on Empirical …, 2020"],"snippet":"… Here, sim(v1,v2) denotes the cosine similarity be- tween two vectors. We first consider the widely used 300dimensional GloVe (Pennington et al., 2014) models pretrained on CommonCrawl 840B and Twitter, as these contain emojis …","url":["https://www.aclweb.org/anthology/2020.emnlp-main.720.pdf"]}
-{"year":"2020","title":"Can I Take Your Subdomain? Exploring Related-Domain Attacks in the Modern Web","authors":["M Squarcina, M Tempesta, L Veronese, S Calzavara… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Can I Take Your Subdomain? Exploring Related-Domain Attacks in the Modern Web Marco Squarcina1, Mauro Tempesta1, Lorenzo Veronese1, Stefano Calzavara2, Matteo Maffei1 1TU Wien, 2Università Ca' Foscari Venezia Abstract …","url":["https://arxiv.org/pdf/2012.01946"]}
-{"year":"2020","title":"Can Knowledge Rich Sentences Help Language Models to Solve Common Sense Reasoning Problems?","authors":["A Prakash - 2019"],"snippet":"… 20 Page 33. Figure 3. RoBERTa network architecture 2. CommonCrawl News was used, which contained 63 million news articles between September 2016 and February 2019 3. OPENWEBTEXT (Gokaslan and Cohen 2019) which is a text corpus containing …","url":["http://search.proquest.com/openview/08e0d3a7c85dcbbd4875abd0d3c48e17/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2020","title":"Capturing Word Order in Averaging Based Sentence Embeddings","authors":["JH Lee, JC Collados, LE Anke, S Schockaert"],"snippet":"… two million words. These word vectors were trained on Common Crawl with 600 billion tokens [19]. The sentences that we used for training, validation and testing were obtained from an English Wikipedia dump. All sentences …","url":["http://josecamachocollados.com/papers/ECAI2020_Capturing_Word_Order_in_Averaging_Based_Sentence_Embeddings.pdf"]}
-{"year":"2020","title":"Caspar: Extracting and Synthesizing User Stories of Problems from App Reviews","authors":["H Guo, MP Singh"],"snippet":"Page 1. Caspar: Extracting and Synthesizing User Stories of Problems from App Reviews Hui Guo Secure Computing Institute North Carolina State University Raleigh, North Carolina hguo5@ncsu.edu Munindar P. Singh Secure …","url":["https://hguo5.github.io/Caspar/docs/Caspar_ICSE_20.pdf"]}
-{"year":"2020","title":"CatchPhish: A URL and Anti-Phishing Research Platform","authors":["S Waddell"],"snippet":"Page 1. CatchPhish: A URL and Anti-Phishing Research Platform Stephen Waddell MInf Project (Part 2) Report Master of Informatics School of Informatics University of Edinburgh 2020 Page 2. Page 3. 3 Abstract In this work, I …","url":["https://groups.inf.ed.ac.uk/tulips/projects/19-20/waddell-2020.pdf"]}
-{"year":"2020","title":"CauseNet: Towards a Causality Graph Extracted from the Web","authors":["S Heindorf, Y Scholten, H Wachsmuth, ACN Ngomo…"],"snippet":"… Web To extract causal relations from the web at scale, we analyze the ClueWeb12 web crawl, which comprises about 733,019,372 English web pages crawled between February and May 2012.3 We chose this crawl over …","url":["https://webis.de/downloads/publications/papers/potthast_2020a.pdf"]}
-{"year":"2020","title":"CC-News-En: A Large English News Corpus","authors":["J Mackenzie, R Benham, M Petri, JR Trippas…"],"snippet":"… Temporal Growth. The Common Crawl foundation are constantly adding new documents to CC-News … 10DMOZ is now superseded by Curlie: https://www.curlie. org 11https://github.com/commoncrawl/news-crawl/issues/8 Page 4 …","url":["https://www.johannetrippas.com/papers/mackenzie2020ccnews.pdf"]}
-{"year":"2020","title":"CCAligned: A Massive Collection of Cross-Lingual Web-Document Pairs","authors":["A El-Kishky, V Chaudhary, F Guzmán, P Koehn - Proc. of EMNLP, 2020"],"snippet":"… we mined over 392 million aligned documents (100M with English and 292M without English) across 68 Common Crawl snapshots. We assess the efficacy of this rule-based alignment in the next section. We select a small subset …","url":["https://www.researchgate.net/profile/Ahmed_El-Kishky/publication/337273813_A_Massive_Collection_of_Cross-Lingual_Web-Document_Pairs/links/5f992509458515b7cfa40eb4/A-Massive-Collection-of-Cross-Lingual-Web-Document-Pairs.pdf"]}
-{"year":"2020","title":"Chart-based Zero-shot Constituency Parsing on Multiple Languages","authors":["T Kim, B Li, S Lee"],"snippet":"… (2019)), the XLM model trained with masked language modeling on 100 languages (XLM, Conneau and Lample (2019)), and the XLM-R and XLM-R-large models that are trained with the filtered CommonCrawl data (Wenzek et al. 2019) by Conneau et al. (2019) …","url":["https://openreview.net/pdf?id=JY-3BheD5LB"]}
-{"year":"2020","title":"ChemTables: A Dataset for Semantic Classification of Tables in Chemical Patents","authors":["Z Zhai, C Druckenbrodt, C Thorne, SA Akhondi… - 2020"],"snippet":"… This model and the baselines it compares to are evaluated on a web table dataset, built by extracting tables from top 500 web pages which contain the highest numbers of tables in a subset of the April 2016 Common Crawl corpus [20] …","url":["https://www.researchsquare.com/article/rs-127219/latest.pdf"]}
-{"year":"2020","title":"Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Embeddings and the Implications to Representation …","authors":["W Zhang, M Campbell, Y Yu, S Kumaravel - arXiv preprint arXiv:2012.01631, 2020"],"snippet":"Page 1. Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Word Embeddings and the Implications to Representation Learning Wei Zhang 1, Murray Campbell 1 …","url":["https://arxiv.org/pdf/2012.01631"]}
-{"year":"2020","title":"CiTIUS at the TREC 2020 Health Misinformation Track","authors":["M Fernández-Pichel, DE Losada, JC Pichel…"],"snippet":"… 2 DOCUMENTS AND TOPICS In the TREC 2020 Health Misinformation Track, a news corpus from January 2020 to April 2020 was provided. The documents were obtained from CommonCrawl News, which contains news articles from all over the world …","url":["http://persoal.citius.usc.es/jcpichel/docs/2020_TREC_MFernandezPichel.pdf"]}
-{"year":"2020","title":"Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Network","authors":["M Karim, BR Chakravarthi, M Arcan, JP McCrae… - arXiv preprint arXiv …, 2020"],"snippet":"… The fourth one called fastText [17], which is trained on common crawl and Wikipedia using CBOW with position-weights, in di- mension 300, with character n-grams of length 5, a window of size 5 and 10 negatives. Eventually …","url":["https://arxiv.org/pdf/2004.07807"]}
-{"year":"2020","title":"Classification of cancer pathology reports with Deep Learning methods","authors":["S Martina"],"snippet":"Page 1. PHD PROGRAM IN SMART COMPUTING DIPARTIMENTO DI INGEGNERIA DELL'INFORMAZIONE (DINFO) Classification of cancer pathology reports with Deep Learning methods Stefano Martina Dissertation presented …","url":["https://flore.unifi.it/bitstream/2158/1187936/1/thesis.pdf"]}
-{"year":"2020","title":"Classification of cancer pathology reports: a large-scale comparative study","authors":["S Martina, L Ventura, P Frasconi - IEEE Journal of Biomedical and Health Informatics, 2020"],"snippet":"… GloVe) [20]). It is a common practice to use pre-compiled libraries of word vectors trained on several billion tokens extracted from various sources such as Wikipedia, the English Gigaword 5, Common Crawl, or Twitter. These …","url":["https://arxiv.org/pdf/2006.16370"]}
-{"year":"2020","title":"Classification of Cyberbullying Text in Arabic","authors":["BA Rachid, H Azza, HHB Ghezala - 2020 International Joint Conference on Neural …, 2020"],"snippet":"… The second set of pre-trained embeddings is the one provided in [24], in which word vectors were trained on online encyclopedia Wikipedia and the Common Crawl corpus using an extension of the fastText model (Fasttext embeddings) …","url":["https://ieeexplore.ieee.org/abstract/document/9206643/"]}
-{"year":"2020","title":"Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection","authors":["E Raff, W Fleshman, R Zak, HS Anderson, B Filar… - arXiv preprint arXiv …, 2020"],"snippet":"… This better demonstrates the gap between current deep learning and domain knowledge based approaches for classifying malware. We also use the Common Crawl to collect 676,843 benign PDF 103 104 105 106 107 108 …","url":["https://arxiv.org/pdf/2012.09390"]}
-{"year":"2020","title":"CLEF eHealth Evaluation Lab 2020","authors":["M Krallinger"],"snippet":"… This collection consists of over 5 million medical webpages from selected domains acquired from the CommonCrawl [7]. Given the positive feedback received for this document collection, it will be used again in the 2020 CHS task …","url":["https://link.springer.com/content/pdf/10.1007/978-3-030-45442-5_76.pdf"]}
-{"year":"2020","title":"Clinical XLNet: Modeling Sequential Clinical Notes and Predicting Prolonged Mechanical Ventilation","authors":["K Huang, A Singh, S Chen, ET Moseley, C Deng… - arXiv preprint arXiv …, 2019"],"snippet":"… Pretraining Clinical XLNet. The text representation generated from large pre-training models depends on the corpus it is pre-trained on. XLNet is pre-trained on common language corpora such as BookCorpus, Wikipedia, Common Crawl and etc …","url":["https://arxiv.org/pdf/1912.11975"]}
-{"year":"2020","title":"CLUE: A Chinese Language Understanding Evaluation Benchmark","authors":["L Xu, X Zhang, L Li, H Hu, C Cao, W Liu, J Li, Y Li… - arXiv preprint arXiv …, 2020"],"snippet":"… CLUECorpus2020 (Xu et al., 2020) It contains 100 GB Chinese raw corpus, which is retrieved from Common Crawl … CLUEOSCAR6 OSCAR is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus …","url":["https://arxiv.org/pdf/2004.05986"]}
-{"year":"2020","title":"CLUECorpus2020: A Large-scale Chinese Corpus for Pre-trainingLanguage Model","authors":["L Xu, X Zhang, Q Dong - arXiv preprint arXiv:2003.01355, 2020"],"snippet":"… Common Crawl is an organization that crawls the web and freely provides its archives and datasets to the public. Common Crawl usually crawls internet web content once a month. Common Crawl's web archives consist of petabytes of data collected since 2011 …","url":["https://arxiv.org/pdf/2003.01355"]}
-{"year":"2020","title":"Clustering Approach to Topic Modeling in Users Dialogue","authors":["E Feldina, O Makhnytkina - Proceedings of SAI Intelligent Systems Conference, 2020"],"snippet":"… FastText using FastText weights based on the pre-trained CBOW model with a word window size of five trained on Common Crawl and Wikipedia, vector size 300. Table 2. Results of the implementation of the clustering …","url":["https://link.springer.com/chapter/10.1007/978-3-030-55187-2_44"]}
-{"year":"2020","title":"CO-EVOLUTION OF CULTURE AND MEANING REVEALED THROUGH LARGE-SCALE SEMANTIC ALIGNMENT","authors":["B THOMPSON, S ROBERTS, G LUPYAN"],"snippet":"… We also replicated on word embeddings derived from the OpenSubtitles database (Li- son & Tiedemann, 2016) and a combination of Wikipedia and the Common Crawl dataset (Grave, Bojanowski, Gupta, Joulin, & Mikolov, 2018)) …","url":["https://brussels.evolang.org/proceedings/papers/EvoLang13_paper_62.pdf"]}
-{"year":"2020","title":"COD3S: Diverse Generation with Discrete Semantic Signatures","authors":["N Weir, J Sedoc, B Van Durme - arXiv preprint arXiv:2010.02882, 2020"],"snippet":"… The model is trained on the co-released corpus CausalBank, which comprises causal statements harvested from English Common Crawl (Buck et al., 2014) … 2014. N-gram counts and language models from the common crawl …","url":["https://arxiv.org/pdf/2010.02882"]}
-{"year":"2020","title":"Combination of Neural Machine Translation Systems at WMT20","authors":["B Marie, R Rubino, A Fujita - Proceedings of the Fifth Conference on Machine …, 2020"],"snippet":"… As En- glish monolingual data, we used all the provided data, but sampled only 200M lines from the “Common Crawl” corpora, except the “News Discussions” and “Wiki Dumps” corpora … corpora but also sampled only …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.23.pdf"]}
-{"year":"2020","title":"Combinatorial feature embedding based on CNN and LSTM for biomedical named entity recognition","authors":["M Cho, C Park, J Ha, S Park - Journal of Biomedical Informatics, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S1532046420300083"]}
-{"year":"2020","title":"Combining Character and Word Embeddings for Affect in Arabic Informal Social Media Microblogs","authors":["AI Alharbi, M Lee - International Conference on Applications of Natural …, 2020"],"snippet":"… Here, the researchers derived the training data from three separate sources: Wikipedia, Twitter and Common Crawl webpages crawl data; they employed two word-level models to learn word representations for general NLP tasks …","url":["https://link.springer.com/chapter/10.1007/978-3-030-51310-8_20"]}
-{"year":"2020","title":"Combining Different Parsers and Datasets for CAPITEL UD Parsing","authors":["F Sánchez-León - Proceedings of the Iberian Languages Evaluation …, 2020"],"snippet":"… Besides, we have used fastText word embeddings trained on Common Crawl and Wikipedia corpora.5 Table 1 shows results on development set of a model built with the training material using different word embeddings.6 Increasing …","url":["http://ceur-ws.org/Vol-2664/capitel_paper1.pdf"]}
-{"year":"2020","title":"Combining Visual and Textual Features for Semantic Segmentation of Historical Newspapers","authors":["R Barman, M Ehrmann, S Clematide, SA Oliveira… - arXiv preprint arXiv …, 2020"],"snippet":"… First, four pre-trained embeddings of the Flair library14 are used with their default implementation settings, as follows: - fastText-fr, ie the French fastText embeddings of size 300 pre-trained on Common Crawl and Wikipedia; …","url":["https://arxiv.org/pdf/2002.06144"]}
-{"year":"2020","title":"Commonsense Aesthetics","authors":["AK Roek - 2020"],"snippet":"Page 1. COMMONSENSE AESTHETICS Aaron Kurosu Roek A DISSERTATION PRESENTED TO THE FACULTY OF PRINCETON UNIVERSITY IN CANDIDACY FOR THE DEGREE OF DOCTOR OF …","url":["http://search.proquest.com/openview/ec2e04cd24fc776ff0cb09566fcf7621/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2020","title":"Commonsense Learning: An Indispensable Path towards Human-centric Multimedia","authors":["B Huang, S Tang, G Shen, G Li, X Wang, W Zhu - … of the 1st International Workshop on …, 2020"],"snippet":"… BERT uses Bookcorpus [84] and English Wikipedia with a size of about 13GB, while XLNet uses more than 100GB of corpus. T5 uses Colossal Clean Crawled Corpus captured from the Common Crawl website with a size of 750GB …","url":["https://dl.acm.org/doi/abs/10.1145/3422852.3423484"]}
-{"year":"2020","title":"Communication-Efficient String Sorting","authors":["T Bingmann, P Sanders, M Schimek - arXiv preprint arXiv:2001.08516, 2020"],"snippet":"Page 1. arXiv:2001.08516v1 [cs.DC] 23 Jan 2020 Communication-Efficient String Sorting Timo Bingmann, Peter Sanders, Matthias Schimek Karlsruhe Institute of Technology, Karlsruhe, Germany {bingmann,sanders}@kit.edu, matthias schimek@gmx.de …","url":["https://arxiv.org/pdf/2001.08516"]}
-{"year":"2020","title":"Comparative Analysis of Deep Learning Models for Myanmar Text Classification","authors":["MS Phyu, KT Nwet - Asian Conference on Intelligent Information and …, 2020"],"snippet":"… Grave et al. [3] published pre-trained word vectors for two hundred forty-six languages trained on common crawl and Wikipedia. They proposed bag-of-character n-grams based on skip-gram that could capture sub-word information to enrich word vectors …","url":["https://link.springer.com/chapter/10.1007/978-3-030-41964-6_7"]}
-{"year":"2020","title":"Comparative Analysis of Machine Learning Algorithms for Computer-Assisted Reporting Based on Fully Automated Cross-Lingual RadLex® Mappings","authors":["ME Maros, CG Cho, AG Junge, B Kämpgen, V Saase… - 2020"],"snippet":"… However, pre-trained word vector models for 157 languages, which were pre-trained on Common Crawl and Wikipedia by the fastText package authors are available for direct download (https://fasttext.cc/docs/en/crawl-vectors.html) [58] …","url":["https://www.preprints.org/manuscript/202004.0354/download/final_file"]}
-{"year":"2020","title":"COMPARATIVE ANALYSIS OF SUBDOMAIN ENUMERATION TOOLS AND STATIC CODE ANALYSIS","authors":["GJ Kathrine, RT Baby, V Ebenzer"],"snippet":"… Certificates= censys,certspotter, Google CT APIs: AlienVault, BinaryEdge, BufferOver, CIRCL, CommonCrawl, DNSDB, GitHub, HackerTarget, NetworksDB, PassiveTotal, Pastebin.. Web Archives: ArchiveIt, ArchiveToday, Arquivo, Wayback and others …","url":["https://www.researchgate.net/profile/Ronnie_Joseph2/publication/342501456_COMPARATIVE_ANALYSIS_OF_SUBDOMAIN_ENUMERATION_TOOLS_AND_STATIC_CODE_ANALYSIS/links/5ef76e2d299bf18816eae517/COMPARATIVE-ANALYSIS-OF-SUBDOMAIN-ENUMERATION-TOOLS-AND-STATIC-CODE-ANALYSIS.pdf"]}
-{"year":"2020","title":"Comparative Analysis of Word Embeddings for Capturing Word Similarities","authors":["M Toshevska, F Stojanovska, J Kalajdjieski - arXiv preprint arXiv:2005.03812, 2020"],"snippet":"… architectures [23]. In our experiments, we have used pre-trained models both trained with subword information on Wikipedia 2017 (16B tokens) and trained with subword information on Common Crawl (600B tokens)4. 2 https …","url":["https://arxiv.org/pdf/2005.03812"]}
-{"year":"2020","title":"Comparing Different Methods for Named Entity Recognition in Portuguese Neurology Text","authors":["F Lopes, C Teixeira, HG Oliveira - Journal of Medical Systems, 2020"],"snippet":"… In order to check which was preferable, two different WE models were used: A pre-trained general Portuguese FastText model, Footnote 3 based on billions of tokens from Wikipedia and Common Crawl [41], with a 5-character window (general language) …","url":["https://link.springer.com/article/10.1007/s10916-020-1542-8"]}
-{"year":"2020","title":"Comparing High Dimensional Word Embeddings Trained on Medical Text to Bag-of-Words for Predicting Medical Codes","authors":["V Yogarajan, H Gouk, T Smith, M Mayo, B Pfahringer - Asian Conference on …, 2020"],"snippet":"… Our embeddings are trained to the exact same specifications as the Wikipedia and common crawl fastText models in [10] … For 300-dimensional embeddings, W300 are word embeddings that are trained by fastText on Wikipedia and other common crawl text …","url":["https://link.springer.com/chapter/10.1007/978-3-030-41964-6_9"]}
-{"year":"2020","title":"Comparing Neural Network Parsers for a Less-resourced and Morphologically-rich Language: Amharic Dependency Parser","authors":["BE Seyoum, Y Miyao, BY Mekonnen - Proceedings of the first workshop on …, 2020"],"snippet":"… For this purpose, we used the trained model for Amharic using fasttext7. The data for training the model is from Wikipedia and Common Crawl8. The models were trained using continuous bag of words (CBOW) …","url":["https://www.aclweb.org/anthology/2020.rail-1.5.pdf"]}
-{"year":"2020","title":"Comparing pre-trained language models for Spanish hate speech detection","authors":["FM Plaza-del-Arco, MD Molina-González… - Expert Systems with …, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S095741742030868X"]}
-{"year":"2020","title":"Comparing Probabilistic, Distributional and Transformer-Based Models on Logical Metonymy Interpretation","authors":["G Rambelli, E Chersoni, A Lenci, P Blache, CR Huang - … of the 1st Conference of the …, 2020"],"snippet":"… in random order. XLNet's training corpora were the same as BERT plus Giga5, ClueWeb 2012-B and Common Crawl, for a total of 32.89B subword piece. Also in this case, we used the large pre-trained model. GPT-2 (Radford …","url":["https://www.aclweb.org/anthology/2020.aacl-main.26.pdf"]}
-{"year":"2020","title":"Comparing supervised learning algorithms for Spatial Nominal Entity recognition","authors":["A Medad, M Gaio, L Moncla, S Mustière, YL Nir - AGILE: GIScience Series, 2020"],"snippet":"… We have made the hypothesis that as FastText is a model of pretrained vectors (300 dimensions) on Wikipedia and Common Crawl, it provides a generic representation of words … CC BY 4.0 License. Page 12. Common Crawl and Wikipedia using the CBOW method …","url":["https://agile-giss.copernicus.org/articles/1/15/2020/agile-giss-1-15-2020.pdf"]}
-{"year":"2020","title":"Comparison between machine learning and human learning from examples generated with machine teaching","authors":["GE Jaimovitch López - 2020"],"snippet":"… For instance, progress in areas like NLP (Natural Language Processing) has led to the development of outstanding deep neural networks such as GPT-3, a task-agnostic model trained using huge data repositories like …","url":["https://riunet.upv.es/bitstream/handle/10251/152771/Jaimovitch%20-%20Comparaci%C3%B3n%20entre%20el%20aprendizaje%20de%20machine%20learning%20y%20humanos%20desde%20ejemplos%20genera....pdf?sequence=1"]}
-{"year":"2020","title":"Comparison of Named Entity Recognition Tools Applied to News Articles","authors":["S Vychegzhanin, E Kotelnikov - 2019 Ivannikov Ispras Open Conference (ISPRAS), 2019"],"snippet":"… spaCy Python MIT Bloom embeddings and a residual convolutional neural network en_core_web_sm OntoNotes en_core_web_md OntoNotes, Common Crawl en_core_web_lg OntoNotes, Common Crawl xx_ent_wiki_sm WikiNER ru2 …","url":["https://ieeexplore.ieee.org/abstract/document/8991165/"]}
-{"year":"2020","title":"Comprehensive Stereotype Content Dictionaries Using a Semi‐Automated Method","authors":["G Nicolas, X Bai, ST Fiske - European Journal of Social Psychology"],"snippet":"… word embeddings used here are Word2Vec's model pretrained on Google News (Mikolov, Chen, Corrado, & Dean, 2013) and Glove' model pretrained on the Common Crawl (Pennington, Socher, & Manning, 2014; presented in Supplement) …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/ejsp.2724"]}
-{"year":"2020","title":"Computational Approaches for Identifying Sensational Soft News","authors":["V Indurthi - 2020"],"snippet":"Page 1. Computational Approaches for Identifying Sensational Soft News Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering by Research by Vijayasaradhi Indurthi 201450803 …","url":["http://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.a54f3e371a9ec80e.46696e616c5f5468657369735f4d535f42795f52657365617263685f56696a617961736172616468695f496e6475727468692e706466.pdf"]}
-{"year":"2020","title":"Computational explorations of semantic cognition","authors":["AS Rotaru - 2020"],"snippet":"Page 1. 1 UNIVERSITY COLLEGE LONDON (UCL) Computational explorations of semantic cognition PHD THESIS Armand Stefan Rotaru Supervisors: Primary: Prof. Gabriella Vigliocco Secondary: Prof. Lewis Griffin Page 2. 2 …","url":["https://discovery.ucl.ac.uk/id/eprint/10106344/13/Rotaru_10106344_thesis.pdf"]}
-{"year":"2020","title":"Computational Mechanisms of Language Understanding and Use in the Brain and Behaviour","authors":["I Kajic - 2020"],"snippet":"Page 1. Computational Mechanisms of Language Understanding and Use in the Brain and Behaviour by Ivana Kajić A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Doctor of Philosophy in Computer Science …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/16439/Kajic_Ivana.pdf?sequence=1"]}
-{"year":"2020","title":"Connections and selections: Comparing multivariate predictions and parameter associations from latent variable models of picture naming","authors":["GM Walker, J Fridriksson, G Hickok - Cognitive Neuropsychology, 2020"],"snippet":"Connectionist simulation models and processing tree mathematical models of picture naming have complementary advantages and disadvantages. These model types were compared in terms of their predicti...","url":["https://www.tandfonline.com/doi/abs/10.1080/02643294.2020.1837092"]}
-{"year":"2020","title":"Constraining the Transformer NMT Model with Heuristic Grid Beam Search","authors":["G Xie, A Way, J Du, L Wang"],"snippet":"… the training corpus consists of 4.4 Million segments from Europarl (Koehn, 2005) and CommonCrawl (Smith et al., 2013); … Smith, JR, Saint-Amand, H., Plamada, M., Koehn, P., Callison-Burch, C., and Lopez, A. (2013). Dirt cheap …","url":["http://www.computing.dcu.ie/~away/PUBS/2020/TransformerGridSearch.pdf"]}
-{"year":"2020","title":"Contemporary Polish Language Model (Version 2) Using Big Data and Sub-Word Approach","authors":["K Wołk"],"snippet":"… In this paper, we present a set of 6-gram language models based on a big-data training of the contemporary Polish language, using the Common Crawl corpus (a compilation of over 3.25 billion webpages) and other resources …","url":["https://indico2.conference4me.psnc.pl/event/35/contributions/3915/attachments/957/996/Thu-3-8-7.pdf"]}
-{"year":"2020","title":"Context-aware Feature Generation for Zero-shot Semantic Segmentation","authors":["Z Gu, S Zhou, L Niu, Z Zhao, L Zhang - arXiv preprint arXiv:2008.06893, 2020"],"snippet":"… in the supplementary. Following SPNet [43], we concatenate two different types of word embeddings (d = 600, 300 for each), ie, word2vec [30] trained on Google News and fast-Text [15] trained on Common Crawl. The word …","url":["https://arxiv.org/pdf/2008.06893"]}
-{"year":"2020","title":"Contextual Question Answering with Improved Embedding Models","authors":["G He"],"snippet":"… In the GloVe word embedding based BiDAF++ model, we utilize pretrained GloVe(Pennington et al., 2014) embeddings with 300 output dimensions (840B.300d). These embeddings have been prertrained on a common crawl of 840 billion to- kens …","url":["https://georgehe.me/coqa.pdf"]}
-{"year":"2020","title":"Contextualized Embeddings in Named-Entity Recognition: An Empirical Study on Generalization","authors":["B Taillé, V Guigue, P Gallinari - arXiv preprint arXiv:2001.08053, 2020"],"snippet":"… 3 Word Representations Word embeddings map each word to a single vector which results in a lexical representation. We take GloVe 840B embeddings [13] trained on Common Crawl as the pretrained word embeddings baseline …","url":["https://arxiv.org/pdf/2001.08053"]}
-{"year":"2020","title":"Contextualized Emotion Recognition in Conversation as Sequence Tagging","authors":["Y Wang, J Zhang, J Ma, S Wang, J Xiao - Proceedings of the 21th Annual Meeting of …, 2020"],"snippet":"… GloVe vectors trained on Common Crawl 840B with 300 dimensions are used as fixed word em- beddings. We use a 12-layers 4-heads Transformer encoder of which the inner-layer dimensionality is 2048 and the hidden size is 100 …","url":["https://www.aclweb.org/anthology/2020.sigdial-1.23.pdf"]}
-{"year":"2020","title":"Controllable Text Generation","authors":["S Prabhumoye - 2020"],"snippet":"Page 1. CARNEGIE MELLON UNIVERSITY Controllable Text Generation Should machines re ect the way humans interact in society? esis Proposal by Shrimai Prabhumoye esis proposal submi ed in partial ful llment for the degree of Doctor of Philosophy esis committee …","url":["https://www.cs.cmu.edu/~sprabhum/docs/proposal.pdf"]}
-{"year":"2020","title":"ConvBERT: Improving BERT with Span-based Dynamic Convolution","authors":["Z Jiang, W Yu, D Zhou, Y Chen, J Feng, S Yan - arXiv preprint arXiv:2008.02496, 2020"],"snippet":"Page 1. ConvBERT: Improving BERT with Span-based Dynamic Convolution Zihang Jiang1∗, Weihao Yu1∗, Daquan Zhou1, Yunpeng Chen2, Jiashi Feng1, Shuicheng Yan2 1National University of Singapore, 2Yitu Technology …","url":["https://res.arxiv.org/pdf/2008.02496"]}
-{"year":"2020","title":"Correcting the Autocorrect: Context-Aware Typographical Error Correction via Training Data Augmentation","authors":["K Shah, G de Melo - arXiv preprint arXiv:2005.01158, 2020"],"snippet":"… from 2We do not rely on embeddings trained on CommonCrawl, as Web data contains substantially more misspelling forms. 3Specifically, those with a character length three standard deviations above or below mean. Hence …","url":["https://arxiv.org/pdf/2005.01158"]}
-{"year":"2020","title":"Crawling the German Health Web: Exploratory Study and Graph Analysis","authors":["R Zowalla, T Wetter, D Pfeifer - Journal of Medical Internet Research, 2020"],"snippet":"Journal of Medical Internet Research - International Scientific Journal for Medical Research, Information and Communication on the Internet.","url":["https://www.jmir.org/2020/7/e17853/"]}
-{"year":"2020","title":"Creating semantic representations","authors":["FÅ Nielsen, LK Hansen - Statistical Semantics, 2020"],"snippet":"… Evaluations in 2017 with fastText trained for 3 days on either the very large Common Crawl data set or a combination of the English Wikipedia and news datasets set a new state-of-the-art on 88.5% for the accuracy on a …","url":["https://link.springer.com/chapter/10.1007/978-3-030-37250-7_2"]}
-{"year":"2020","title":"Creation of a database based on artificial intelligence in order to understand the role played by biofilms on outbreaks","authors":["APP de Melo - 2020"],"snippet":"Page 1. FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Creation of a database based on artificial intelligence in order to understand the role played by biofilms on outbreaks Ana Patrícia Pinheiro de Melo Integrated Master in Bioengineering …","url":["https://repositorio-aberto.up.pt/bitstream/10216/130013/2/428683.pdf"]}
-{"year":"2020","title":"Creative Natural Language Generation: Humor and Beyond","authors":["NT Hossain - 2020"],"snippet":"Page 1. Creative Natural Language Generation: Humor and Beyond by Nabil Tarique Hossain Submitted in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy Supervised by Professor Henry Kautz and Dr …","url":["https://urresearch.rochester.edu/fileDownloadForInstitutionalItem.action?itemId=36525&itemFileId=189977"]}
-{"year":"2020","title":"Credibility Assessment of User Generated health information of the Bengali language in microblogging sites employing NLP techniques","authors":["A Benazir, S Sharmin"],"snippet":"… word. We use the pre-trained word vectors of Fasttext 5 over Word2Vec 6 and GloVe 7 since it has the best multi lingual word vectors amongst the three, supporting 157 languages, trained on Common Crawl and Wikipedia. We …","url":["https://www.researchgate.net/profile/Afsara_Benazir2/publication/347524581_Credibility_Assessment_of_User_Generated_health_information_of_the_Bengali_language_in_microblogging_sites_employing_NLP_techniques/links/5fe0f9eaa6fdccdcb8ef603e/Credibility-Assessment-of-User-Generated-health-information-of-the-Bengali-language-in-microblogging-sites-employing-NLP-techniques.pdf"]}
-{"year":"2020","title":"Cross-Cultural Polarity and Emotion Detection Using Sentiment Analysis and Deep Learning--a Case Study on COVID-19","authors":["AS Imran, SM Doudpota, Z Kastrati, R Bhatra - arXiv preprint arXiv:2008.10031, 2020"],"snippet":"… corpora, a 2010 Wikipedia dump with 1 billion tokens; a 2014 Wikipedia dump with 1.6 billion tokens; Gigaword 5 which has 4.3 billion tokens; the combination Gigaword5 + Wikipedia2014, which has 6 billion tokens; and …","url":["https://arxiv.org/pdf/2008.10031"]}
-{"year":"2020","title":"Cross-lingual Inductive Transfer to Detect Offensive Language","authors":["K Pant, T Dadu - arXiv preprint arXiv:2007.03771, 2020"],"snippet":"… We further finetune XLM-R, pretrained on 2.5 TB Common Crawl corpus spanning 100 languages … XLM-R is a transformer-based cross-lingual model pretrained using a multilingual masked language model objective on 2.5 …","url":["https://arxiv.org/pdf/2007.03771"]}
-{"year":"2020","title":"Cross-Lingual Information Retrieval in the Medical Domain","authors":["S Saleh - 2020"],"snippet":"Page 1. DOCTORAL THESIS Shadi Saleh Cross-lingual Information Retrieval in the Medical Domain Institute of Formal and Applied Linguistics Supervisor of the doctoral thesis: doc. RNDr. Pavel Pecina, PhD. Study programme …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/123570/140087429.pdf?sequence=1"]}
-{"year":"2020","title":"Cross-Lingual Relation Extraction with Transformers","authors":["J Ni, T Moon, P Awasthy, R Florian - arXiv preprint arXiv:2010.08652, 2020"],"snippet":"… Conneau et al., 2020). mBERT was pre-trained with Wikipedia text of 104 languages with the largest sizes, and XLM-R were pre-trained with Wikipedia text and CommonCrawl Corpus of 100 languages. Both models use no …","url":["https://arxiv.org/pdf/2010.08652"]}
-{"year":"2020","title":"Cross-lingual Retrieval for Iterative Self-Supervised Training","authors":["C Tran, Y Tang, X Li, J Gu - arXiv preprint arXiv:2006.09526, 2020"],"snippet":"… 5 Experiment Evaluation We pretrained an mBART model with Common Crawl dataset constrained to the 25 languages as in [19] for which we have evaluation data … We subsample the resulting common crawl data to 100 million sentences in each language …","url":["https://arxiv.org/pdf/2006.09526"]}
-{"year":"2020","title":"Cross-lingual Transfer Learning for Semantic Role Labeling in Russian","authors":["I Alimova, E Tutubalina, A Kirillovich"],"snippet":"… The model is also based on Transformer architecture (Vaswani et al., 2017). We applied the XLM-R Masked Language Model, which is pretrained on 2.5 TB of CommonCrawl data, in 100 languages, with 8 heads, 6 layers, 1024 hidden units per layer …","url":["https://www.researchgate.net/profile/Alexander_Kirillovich/publication/342734555_Cross-lingual_Transfer_Learning_for_Semantic_Role_Labeling_in_Russian/links/5f0410d0299bf1881607dae8/Cross-lingual-Transfer-Learning-for-Semantic-Role-Labeling-in-Russian.pdf"]}
-{"year":"2020","title":"Cross-Lingual Word Embeddings for Turkic Languages","authors":["E Kuriyozov, Y Doval, C Gómez-Rodríguez - arXiv preprint arXiv:2005.08340, 2020"],"snippet":"… Cross-lingual embeddings used for both experiments were trained under the following conditions: • Monolingual word embeddings were obtained from available pre-trained word vectors (Grave et al., 2018) trained on …","url":["https://arxiv.org/pdf/2005.08340"]}
-{"year":"2020","title":"Cross-Modal Transfer Learning for Multilingual Speech-to-Text Translation","authors":["C Tran, C Wang, Y Tang, Y Tang, J Pino, X Li - arXiv preprint arXiv:2010.12829, 2020"],"snippet":"… This model is pretrained using two types of noise in g — random span masking and order permutation — as described in [3]. We re-use the finetuned mBART50 models from [13] which are pretrained on …","url":["https://arxiv.org/pdf/2010.12829"]}
-{"year":"2020","title":"CS-NLP team at SemEval-2020 Task 4: Evaluation of State-of-the-artNLP Deep Learning Architectures on Commonsense Reasoning Task","authors":["S Saeedi, A Panahi, S Saeedi, AC Fong - arXiv preprint arXiv:2006.01205, 2020"],"snippet":"… The architecture of RoBERTalarge is comprised of of 24-layer, 1024-hidden dimension, 16-self attention heads, 355M parameters and pretrained on book corpus plus English Wikipedia, English CommonCrawl News, and WebText corpus …","url":["https://arxiv.org/pdf/2006.01205"]}
-{"year":"2020","title":"Culprit Analytics from Detective Novels","authors":["A Motwani - 2020"],"snippet":"Page 1. Culprit Analytics from Detective Novels Thesis submitted in partial fulfillment of the requirements for the degree of Masters of Science in Computer Science and Engineering by Research by Aditya Motwani …","url":["http://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.8981260fae86b1a4.4d535f5468657369735f46696e616c202833292e706466.pdf"]}
-{"year":"2020","title":"Cultural Cartography with Word Embeddings","authors":["DS Stoltz, MA Taylor - arXiv preprint arXiv:2007.04508, 2020"],"snippet":"… fastText embeddings are trained on Wikipedia data dumps and the 25 billion web pages of the Common Crawl), and thus are not trained on the researcher's own corpus. Corpus-trained embeddings, by contrast, are word vectors trained exclusively on the …","url":["https://arxiv.org/pdf/2007.04508"]}
-{"year":"2020","title":"Cultural Differences in Bias? Origin and Gender Bias in Pre-Trained German and French Word Embeddings","authors":["M Kurpicz-Briki"],"snippet":"… The validation experiments in English were executed on the same pre-trained word embeddings as in the original experiments (Caliskan et al., 2017): • GloVe pre-trained word embeddings using the ”Common …","url":["http://ceur-ws.org/Vol-2624/paper6.pdf"]}
-{"year":"2020","title":"Cultural influences on word meanings revealed through large-scale semantic alignment","authors":["B Thompson, SG Roberts, G Lupyan - Nature Human Behaviour, 2020"],"snippet":"If the structure of language vocabularies mirrors the structure of natural divisions that are universally perceived, then the meanings of words in different languages should closely align. By contrast, if shared word meanings are …","url":["https://www.nature.com/articles/s41562-020-0924-8"]}
-{"year":"2020","title":"Current Limitations of Language Models: What You Need is Retrieval","authors":["A Komatsuzaki - arXiv preprint arXiv:2009.06857, 2020"],"snippet":"… Most naturally available samples as well as the reasonable output of most tasks have rather limited length, though others (eg books) do not. For example, the average sample length of WebText is only about 1000 tokens …","url":["https://arxiv.org/pdf/2009.06857"]}
-{"year":"2020","title":"Curriculum Pre-training for End-to-End Speech Translation","authors":["C Wang, Y Wu, S Liu, M Zhou, Z Yang - arXiv preprint arXiv:2004.10093, 2020"],"snippet":"… (2017) 6LibriSpeech En-Fr, IWSLT En-De and Fisher-CallHome Es-En 7https://wit3.fbk.eu/mt.php?release= 2017-01-trnted 8Europarl v7, Common Crawl, News Comentary v13 and Rapid corpus of EU press releases. using …","url":["https://arxiv.org/pdf/2004.10093"]}
-{"year":"2020","title":"CX DB8: A queryable extractive summarizer and semantic search engine","authors":["A Roush - arXiv preprint arXiv:2012.03942, 2020"],"snippet":"… unsupervised models. Since unsupervised models are usually trained on massive corpuses, like Wikipedia or Common Crawl (Penninglon et al., 2014), they do not overfit as much to any particular topic or domain. Furthermore …","url":["https://arxiv.org/pdf/2012.03942"]}
-{"year":"2020","title":"Dávid Márk Nemeskey Natural Language Processing Methods for Language Modeling","authors":["CV Erzsébet, Z Horváth, A Benczúr, A Kornai"],"snippet":"… 83 4.2.2 Common Crawl . . . . . 84 … Chapter 4 details our work of compiling Webcorpus 2.0, a new Hungarian gigaword corpus, from the Common Crawl and the Hungarian Wikipedia. Its main purpose being a …","url":["https://hlt.bme.hu/media/pdf/thesis.pdf"]}
-{"year":"2020","title":"DAN+: Danish Nested Named Entities and Lexical Normalization","authors":["B Plank, KN Jensen, R van der Goot"],"snippet":"… Twitter data. Bert variants For Danish BERT we use the model trained by Botxo (https://github.com/ botxo/nordic_bert), which is pre-trained on Wikipedia, Common Crawl, Danish debate forums and Danish open subtitles. For …","url":["http://www.robvandergoot.com/doc/danP.pdf"]}
-{"year":"2020","title":"Danish Clinical Event Extraction Developing a clinical event extraction system for electronic health records using deep learning and active learning","authors":["F WONSILD, MG MØLLER - 2020"],"snippet":"Page 1. Danish Clinical Event Extraction Developing a clinical event extraction system for electronic health records using deep learning and active learning FREDERIK WONSILD MATHIAS GIOVANNI MØLLER Master's thesis …","url":["https://www.derczynski.com/itu/docs/clin-events_frwo_mgmo.pdf"]}
-{"year":"2020","title":"Data augmentation techniques for the Video Question Answering task","authors":["A Falcon, O Lanz, G Serra - arXiv preprint arXiv:2008.09849, 2020"],"snippet":"… To compute the word embeddings for the question and the answers, we consider GloVe [23], pretrained on the Common Crawl dataset3, which outputs a vector of size E = 300 for 3 The Common Crawl dataset is available …","url":["https://arxiv.org/pdf/2008.09849"]}
-{"year":"2020","title":"Data selection for unsupervised translation of German–Upper Sorbian","authors":["L Edman, A Toral, G van Noord - Proceedings of the Fifth Conference on Machine …, 2020"],"snippet":"… gz. For German, we use monolingual data from News Crawl and Common Crawl … 19.57 Table 3: BLEU scores of models trained using 5 million sentences from News Crawl and various amounts of sentences from Common Crawl …","url":["https://www.aclweb.org/anthology/2020.wmt-1.130.pdf"]}
-{"year":"2020","title":"Data-driven Crosslinguistic Modeling of Constituent Ordering Preferences","authors":["ZY Liu - 2020"],"snippet":"Page 1. Data-driven Crosslinguistic Modeling of Constituent Ordering Preferences By Zoey (Ying) Liu Dissertation Submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Linguistics in the Office of Graduate Studies of the …","url":["https://www.researchgate.net/profile/Zoey_Liu2/publication/343836788_Data-driven_Crosslinguistic_Modeling_of_Constituent_Ordering_Preferences/links/5f4408cb92851cd3022569fe/Data-driven-Crosslinguistic-Modeling-of-Constituent-Ordering-Preferences.pdf"]}
-{"year":"2020","title":"Data-driven models and computational tools for neurolinguistics: a language technology perspective","authors":["E Artemova, A Bakarov, A Artemov, E Burnaev… - arXiv preprint arXiv …, 2020"],"snippet":"… The corpus size can be estimated by the number of tokens8: so, the size of English Wikipedia is 1M tokens, the size of Google news corpus is 1B tokens, and the size of CommonCrawl corpus is 600B tokens. Structured expert-based …","url":["https://arxiv.org/pdf/2003.10540"]}
-{"year":"2020","title":"Dataless Short Text Classification Based on Biterm Topic Model and Word Embeddings","authors":["Y Yang, H Wang, J Zhu, Y Wu, K Jiang, W Guo, W Shi"],"snippet":"… We set the number of iterations to 50 as our models achieve competitive performance since then. For word embeddings, we employ the widely used GloVe Common Crawl as mentioned before. It contains 840B to- kens, 2.2M vocab and 300d vectors …","url":["https://www.ijcai.org/Proceedings/2020/0549.pdf"]}
-{"year":"2020","title":"Dataset for Automatic Summarization of Russian News","authors":["I Gusev - arXiv preprint arXiv:2006.11063, 2020"],"snippet":"… 3.3 Abstractive methods All of the tested models are based on a sequence-to-sequence framework. Pointergenerator and CopyNet were trained only on our train dataset, and mBART was pretrained on texts of 25 languages extracted from the Common Crawl …","url":["https://arxiv.org/pdf/2006.11063"]}
-{"year":"2020","title":"Dataset for Automatic Summarization of Russian","authors":["I Gusev - arXiv preprint arXiv:2006.11063, 2020"],"snippet":"… sequence-to-sequence framework. Pointer-generator and CopyNet were trained only on our training dataset, and mBART was pretrained on texts of 25 languages extracted from the Common Crawl. We performed no additional …","url":["https://www.researchgate.net/profile/Ilya_Gusev2/publication/342352344_Dataset_for_Automatic_Summarization_of_Russian_News/links/5f16164a92851c1eff22059b/Dataset-for-Automatic-Summarization-of-Russian-News.pdf"]}
-{"year":"2020","title":"Datasets and Performance Metrics for Greek Named Entity Recognition","authors":["N Bartziokas, T Mavropoulos, C Kotropoulos - 11th Hellenic Conference on Artificial …, 2020"],"snippet":"… performance. Thus, most works omit such supplementary features. Established word embeddings, usually pre-trained on large corpora, such as Common Crawl's or Wikipedia's collections, are fine-tuned to a great extent. Google …","url":["https://dl.acm.org/doi/abs/10.1145/3411408.3411437"]}
-{"year":"2020","title":"DeBERTa: Decoding-enhanced BERT with Disentangled Attention","authors":["P He, X Liu, J Gao, W Chen - arXiv preprint arXiv:2006.03654, 2020"],"snippet":"… the setting of BERT [4], except that we use the BPE vocabulary as [2, 5]. For training data, we use Wikipedia (English Wikipedia dump3; 12GB), BookCorpus [26] (6GB), OPENWEBTEXT (public Reddit content [27]; 38GB) …","url":["https://arxiv.org/pdf/2006.03654"]}
-{"year":"2020","title":"DECAB-LSTM: Deep Contextualized Attentional Bidirectional LSTM for cancer hallmark classification","authors":["L Jiang, X Sun, F Mercaldo, A Santone - Knowledge-Based Systems, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0950705120306158"]}
-{"year":"2020","title":"Decoding individual identity from brain activity elicited in imagining common experiences","authors":["AJ Anderson, K McDermott, B Rooks, KL Heffner… - Nature Communications, 2020"],"snippet":"Everyone experiences common events differently. This leads to personal memories that presumably provide neural signatures of individual identity when events are reimagined. We present initial evidence that these signatures …","url":["https://www.nature.com/articles/s41467-020-19630-y"]}
-{"year":"2020","title":"Deep Exogenous and Endogenous Influence Combination for Social Chatter Intensity Prediction","authors":["S Dutta, S Masud, S Chakrabarti, T Chakraborty - arXiv preprint arXiv:2006.07812, 2020"],"snippet":"… news on discussions. We report on extensive experiments using a two-month-long discussion corpus of Reddit, and a contemporaneous corpus of online news articles from the Common Crawl. ChatterNet shows considerable …","url":["https://arxiv.org/pdf/2006.07812"]}
-{"year":"2020","title":"Deep Intelligent Contextual Embedding for Twitter Sentiment Analysis","authors":["K Musial-Gabrys, U Naseem - International Conference on Document Analysis and …, 2019"],"snippet":"… and GloVe. In our model we have used pre-trained GloVe embedding of 300 dimensions which are trained on 840 billion token from common crawl because it gives better results as compared to Word2Vec in our case. GloVe …","url":["https://opus.lib.uts.edu.au/bitstream/10453/137711/1/ICDAR_2019_paper_279.pdf"]}
-{"year":"2020","title":"Deep Learning Based Multi-Label Text Classification of UNGA Resolutions","authors":["F Sovrano, M Palmirani, F Vitali - arXiv preprint arXiv:2004.03455, 2020"],"snippet":"… The pre-trained models we are going to use are: a GloVe model from Spacy [19] and pre-trained on data from Common Crawl [20], and the Universal Sentence Encoder (USE) model for document embedding coming from …","url":["https://arxiv.org/pdf/2004.03455"]}
-{"year":"2020","title":"Deep Learning for Twitter Sentiment Analysis: The Effect of Pre-trained Word Embedding","authors":["A Krouska, C Troussas, M Virvou - Machine Learning Paradigms, 2020"],"snippet":"… The model contains 300-dimensional vectors for 3 million words and phrases. Crawl GloVe was trained on a Common Crawl dataset of 42 billion tokens (words), providing a vocabulary of 2 million words with an embedding vector …","url":["https://link.springer.com/chapter/10.1007/978-3-030-49724-8_5"]}
-{"year":"2020","title":"Deep learning model for end-to-end approximation of COSMIC functional size based on use-case names","authors":["M Ochodek, S Kopczyńska, M Staron - Information and Software Technology, 2020"],"snippet":"… we investigate different pre-trained word embeddings to learn that using the embeddings trained on Wikipedia+Gigaworld (300d), Common Crawl 840B/42B (300d), and Stack Overflow (200d) give the best prediction accuracy. This paper is structured as follows …","url":["https://www.sciencedirect.com/science/article/pii/S0950584920300628"]}
-{"year":"2020","title":"Deep N-ary Error Correcting Output Codes","authors":["H Zhang, JT Zhou, T Wang, IW Tsang, RSM Goh - arXiv preprint arXiv:2009.10465, 2020"],"snippet":"… For the Bi-LSTMs model of TREC and SST text datasets, we use the 300-dimensional publicly available pre-trained word embeddings as the word-level feature representation, which is trained by fastText4 package …","url":["https://arxiv.org/pdf/2009.10465"]}
-{"year":"2020","title":"Deep Neural Attention-Based Model for the Evaluation of Italian Sentences Complexity","authors":["D Schicchi, G Pilato, GL Bosco - 2020 IEEE 14th International Conference on …, 2020"],"snippet":"… based algorithms. To the best of our knowledge, the most prominent sentence-based corpus for the Italian language is the PACCSS-IT corpus [19]. It has 1www.wikipedia. org 2www.commoncrawl.org 254 Page 3. been created …","url":["https://ieeexplore.ieee.org/abstract/document/9031472/"]}
-{"year":"2020","title":"Deep Neural Networks Ensemble with Word Vector Representation Models to Resolve Coreference Resolution in Russian","authors":["A Sboev, R Rybka, A Gryaznov - Advanced Technologies in Robotics and Intelligent …, 2020"],"snippet":"… Among the context-insensitive vectorization models, the following were compared: Word2vec model, 3 trained on corpus of articles from the Russian part of Wikipedia (further referred to as RuWiki) and data from CommonCrawl 4 ; …","url":["https://link.springer.com/chapter/10.1007/978-3-030-33491-8_4"]}
-{"year":"2020","title":"Deep Neural Networks for Sentiment Analysis in Tweets with Emoticons","authors":["M Narayanaperumal - 2020"],"snippet":"Page 1. DEEP NEURAL NETWORKS FOR SENTIMENT ANALYSIS IN TWEETS WITH EMOTICONS by Mutharasu Narayanaperumal A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Information Systems …","url":["http://search.proquest.com/openview/ce5f7af40a2bea968b30a3ab132f22bb/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2020","title":"Deep Question Answering: A New Teacher For DistilBERT","authors":["F Tamburini, P Cimiano, S Preite"],"snippet":"Page 1. Alma Mater Studiorum · Universit`a di Bologna SCUOLA DI SCIENZE Corso di Laurea Magistrale in Informatica Deep Question Answering: A New Teacher For DistilBERT Relatore: Chiar.mo Prof. Fabio Tamburini Correlatore: Chiar.mo Prof. Philipp Cimiano …","url":["https://amslaurea.unibo.it/20384/1/MasterThesisBologna.pdf"]}
-{"year":"2020","title":"DeepPhish: Automated Phishing Detection Using Recurrent Neural Network","authors":["M Arivukarasi, A Antonidoss - Advances in Smart System Technologies"],"snippet":"… At that point, we prepared an irregular timberland classifier with 100 choice trees. 6 Conclusions. To assess the methodologies, we utilized a database that included one million real URLs from the common crawl database and …","url":["https://link.springer.com/chapter/10.1007/978-981-15-5029-4_18"]}
-{"year":"2020","title":"DeepSinger: Singing Voice Synthesis with Data Mined From the Web","authors":["Y Ren, X Tan, T Qin, J Luan, Z Zhao, TY Liu - arXiv preprint arXiv:2007.04590, 2020"],"snippet":"… A variety of tasks collect training data from the Web, such as the large-scale web-crawled text dataset ClueWeb [3] and Common Crawl3 for language modeling [40], LETOR [31] for search ranking [4], and WebVision [22] for image classification …","url":["https://arxiv.org/pdf/2007.04590"]}
-{"year":"2020","title":"Definition of Phishing Sites Based on the Team Model of Fuzzy Neural Networks","authors":["II Ismagilov, AA Murtazin, DV Kataseva, AS Katasev… - Helix, 2020"],"snippet":"… To obtain a set of data on legitimate sites, two sources were used: Alexa Internet and Common Crawl … Common Crawl is a non-profit organization; it crawls monthly the Internet and makes its archives and datasets available …","url":["https://helixscientific.pub/index.php/home/article/download/237/190"]}
-{"year":"2020","title":"DeL-haTE: A Deep Learning Tunable Ensemble for Hate Speech Detection","authors":["J Melton, A Bagavathi, S Krishnan - arXiv preprint arXiv:2011.01861, 2020"],"snippet":"… We compare the following five word embedding methods: Word2Vec vectors trained on Google News corpus [17], GloVe vectors trained on CommonCrawl (GLoVe-CC) and Twitter (GLoVe-Twitter) corpora [18], and FastText vectors …","url":["https://arxiv.org/pdf/2011.01861"]}
-{"year":"2020","title":"Delay Mitigation for Backchannel Prediction in Spoken Dialog System","authors":["AI Adiba, T Homma, D Bertero, T Sumiyoshi… - Conversational Dialogue Systems …"],"snippet":"… individual word. The word embedding is then used as input for our model architecture. We found that our dataset in the fastText model trained with the Common Crawl dataset 2 had the smallest number of unknown words. Thus, the …","url":["https://link.springer.com/chapter/10.1007/978-981-15-8395-7_10"]}
-{"year":"2020","title":"DeLFT and entity-fishing: Tools for CLEF HIPE 2020 Shared Task","authors":["T Kristanti, L Romary - CLEF 2020-Conference and Labs of the Evaluation …, 2020"],"snippet":"… Word Embeddings We use various static word embeddings: Global Vectors for Word Representation (GloVe) [14], English fastText Common Crawl [1,11], and French Wikipedia fastText.5 We also use ELMo [16] contextualized …","url":["https://hal.inria.fr/hal-02974946/document"]}
-{"year":"2020","title":"Depthwise Separable Convolutional Neural Network for Confidential Information Analysis","authors":["Y Lu, J Jiang, M Yu, C Liu, C Liu, W Huang, Z Lv - International Conference on …, 2020"],"snippet":"… Word2Vec. The Word2VecModified-Wikipedia are trained on Wikipedia through modified Word2vec. The GloVe-Crawl840B are trained on Common Crawl through GloVe. The GloVe-Wikipedia are trained on Wikipedia through GloVe …","url":["https://link.springer.com/chapter/10.1007/978-3-030-55393-7_40"]}
-{"year":"2020","title":"Design2Struct: Generating website structures from design images using neural networks","authors":["MM Velzel - 2020"],"snippet":"… The second contribution is the release of a large CommonCrawl2 based dataset, filtered and transformed to be used in the field of GUI to structure conversion. The dataset is 1https://github.com/mvelzel/Design2Struct 2https://commoncrawl.org …","url":["http://essay.utwente.nl/81988/1/VELZEL_BA_EEMCS.pdf"]}
-{"year":"2020","title":"Detecting Alzheimer's Disease by Exploiting Linguistic Information from Nepali Transcript","authors":["S Thapa, S Adhikari, U Naseem, P Singh, G Bharathy… - International Conference on …, 2020"],"snippet":"… For pre-trained Nepali Word2Vec model, the model created by Lamsal [15] is used in the study. Similarly, for the pre-trained fastText embeddings, the pre-trained word vectors trained on Common Crawl and Wikipedia using fastText were used [14] …","url":["https://link.springer.com/chapter/10.1007/978-3-030-63820-7_20"]}
-{"year":"2020","title":"Detecting and Visualizing Hate Speech in Social Media: A Cyber Watchdog for Surveillance","authors":["S Modha, P Majumder, T Mandl, C Mandalia - Expert Systems with Applications, 2020"],"snippet":"… The word vectors were trained on 600 billion tokens of the Common Crawl corpus (Simonite, 2013). The Common Crawl is a nonprofit organization that crawls the web and freely provides its archives and datasets to the public …","url":["https://www.sciencedirect.com/science/article/pii/S0957417420305492"]}
-{"year":"2020","title":"Detecting Deceptive Language in Crime Interrogation","authors":["YY Kao, PH Chen, CC Tzeng, ZY Chen, B Shmueli… - International Conference on …, 2020"],"snippet":"… fastText is a lightweight library for text representation. Its pre-trained model, trained on Common Crawl and Wikipedia corpus, has the ability to capture hidden information about a language such as word analogies or semantic …","url":["https://link.springer.com/chapter/10.1007/978-3-030-50341-3_7"]}
-{"year":"2020","title":"Detecting Emergent Intersectional Biases: Contextualized Word Embeddings Contain a Distribution of Human-like Biases","authors":["W Guo, A Caliskan - arXiv preprint arXiv:2006.03955, 2020"],"snippet":"… intersectional group members. Caliskan et al. [1] have shown that social biases are embedded in linguistic regularities learned by GloVe. These embeddings are trained on the word co-occurrence statistics of the Common Crawl corpus …","url":["https://arxiv.org/pdf/2006.03955"]}
-{"year":"2020","title":"Detecting Entailment in Code-Mixed Hindi-English Conversations","authors":["S Chakravarthy, A Umapathy, AW Black - Proceedings of the Sixth Workshop on …, 2020"],"snippet":"… XLM-RoBERTa (XLM-R) (Conneau et al., 2020) is trained on the CommonCrawl corpus, which in- cludes Romanized Hindi text, making this model the closest one to being pre-trained on Hinglish. 3 Task Definition Khanuja et al …","url":["https://www.aclweb.org/anthology/2020.wnut-1.22.pdf"]}
-{"year":"2020","title":"Detecting Fine-Grained Cross-Lingual Semantic Divergences without Supervision by Learning to Rank","authors":["E Briakou, M Carpuat - arXiv preprint arXiv:2010.03662, 2020"],"snippet":"… (2018) work on subtitles and Common Crawl corpora where sentence alignment errors abound, and Pham et al … di- vergence English-French parallel sentences drawn from OpenSubtitles and CommonCrawl corpora by prior work (Vyas et al., 2018) …","url":["https://arxiv.org/pdf/2010.03662"]}
-{"year":"2020","title":"Detecting Hallucinated Content in Conditional Neural Sequence Generation","authors":["C Zhou, J Gu, M Diab, P Guzman, L Zettlemoyer… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. DETECTING HALLUCINATED CONTENT IN CONDITIONAL NEURAL SEQUENCE GENERATION Chunting Zhou1∗, Jiatao Gu2, Mona Diab2, Paco Guzman2, Luke Zettlemoyer2, Marjan Ghazvininejad2 Language …","url":["https://arxiv.org/pdf/2011.02593"]}
-{"year":"2020","title":"Detecting Incivility and Impoliteness in Online Discussions.","authors":["AK Stoll, M Ziegele, O Quiring - Computational Communication Research, 2020"],"snippet":"Page 1. VOL. 2, NO. 1, 2020 109 Detecting Impoliteness and Incivility in Online Discussions Classification Approaches for German User Comments Anke Stoll, Marc Ziegele, Oliver Quiring CCR 2 (1): 109–134 DOI: 10.5117/CCR2020.1.005.KATH …","url":["https://computationalcommunication.org/ccr/article/download/19/10"]}
-{"year":"2020","title":"Detecting misogyny in Spanish Tweets. An approach based on linguistics features and word embeddings","authors":["JA García-Díaz, M Cánovas-García… - Future Generation …, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0167739X20301928"]}
-{"year":"2020","title":"DETECTING OUT-OF-DISTRIBUTION TRANSLATIONS WITH VARIATIONAL TRANSFORMERS","authors":["WAT ZEI"],"snippet":"… The following datasets were used in our experiments: (1) WMT EN ↔ DE: The training set for translation tasks between English (EN) and German (DE) composed of news-commentary-v13 with 284k sentences pairs …","url":["https://openreview.net/pdf/e2667f2c5169fcbdca8e1d0596e67792da06d3a0.pdf"]}
-{"year":"2020","title":"Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks","authors":["D Emelin, I Titov, R Sennrich - arXiv preprint arXiv:2011.01846, 2020"],"snippet":"Page 1. Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks Denis Emelin1, Ivan Titov1, 2, and Rico Sennrich3, 1 1University of Edinburgh, Scotland 2University of Amsterdam …","url":["https://arxiv.org/pdf/2011.01846"]}
-{"year":"2020","title":"Detecting, Classifying, and Mapping Retail Storefronts Using Street-level Imagery","authors":["S Sharifi Noorian, S Qiu, A Psyllidis, A Bozzon… - Proceedings of the 2020 …, 2020","SS Noorian, S Qiu, A Psyllidis, A Bozzon, GJ Houben"],"snippet":"… a bag of character n-grams. As our evaluation will focus on the Manhattan Borough of New York City, the pre-trained (on Common Crawl and Wikipedia 3) word vectors for English are used. According to the desired language …","url":["https://dl.acm.org/doi/pdf/10.1145/3372278.3390706","https://qiusihang.github.io/files/publications/icmr2020detecting.pdf"]}
-{"year":"2020","title":"Detection of Emerging Words in Portuguese Tweets","authors":["A Pinto, H Moniz, F Batista - 9th Symposium on Languages, Applications and …, 2020"],"snippet":"… We have used two pre-trained word vectors for Portuguese4, the first one trained on the Common Crawl5, and the second trained on the … www.nilc.icmc. usp.br/nilc/projects/unitex-pb/web/dicionarios.html 4 https://fasttext.cc/docs …","url":["https://drops.dagstuhl.de/opus/volltexte/2020/13016/pdf/OASIcs-SLATE-2020-3.pdf"]}
-{"year":"2020","title":"Detection of Harassment on Twitter with Deep Learning Techniques","authors":["I Espinoza, F Weiss - Machine Learning and Knowledge Discovery in …, 2020"],"snippet":"… trained embedding model. We use the implementation off Spacy library for Python4 with the pre-trained model called 'en vectors web lg', which has 300 dimensions and it's trained over common crawl texts. With Spacy we have …","url":["https://link.springer.com/content/pdf/10.1007/978-3-030-43887-6_24.pdf"]}
-{"year":"2020","title":"Determining Event Outcomes: The Case of# fail","authors":["S Murugan, D Chinnappa, E Blanco - Proceedings of the 2020 Conference on …, 2020"],"snippet":"… has variable length). Additionally, the word embeddings (GloVe embeddings pre-trained with CommonCrawl) allow us to leverage a distributional representation of tags, including those not seen during training. The second …","url":["https://www.aclweb.org/anthology/2020.findings-emnlp.359.pdf"]}
-{"year":"2020","title":"Developing a Twitter bot that can join a discussion using state-of-the-art architectures","authors":["YM Çetinkaya, İH Toroslu, H Davulcu - Social Network Analysis and Mining, 2020"],"snippet":"… requests. Radford et al. (2019) construct an auto-regressive feed-forward model instead of seq2seq-RNN as a language model using Common Crawl as a dataset and generate sentences with predicting next word. Generative …","url":["https://link.springer.com/article/10.1007/s13278-020-00665-4"]}
-{"year":"2020","title":"Developing an online hate classifier for multiple social media platforms","authors":["J Salminen, M Hopf, SA Chowdhury, S Jung… - Human-centric Computing …, 2020"],"snippet":"The proliferation of social media enables people to express their opinions widely online. However, at the same time, this has resulted in the emergence of conflict and hate, making online...","url":["https://link.springer.com/article/10.1186/s13673-019-0205-6"]}
-{"year":"2020","title":"Development and evaluation of a Polish Automatic Speech Recognition system using the TLK toolkit","authors":["NU Roselló Beneitez - 2020"],"snippet":"… 12 2.8 Trellis representing the decoding step . . . . . 15 3.1 Examples of sentences extracted from the Common Crawl corpus . . . . . 21 4.1 Actions performed to create the final acoustic models . . . . . 24 4.2 Phonetic transcription of a Polish word …","url":["https://riunet.upv.es/bitstream/handle/10251/150495/Rosell%C3%B3%20-%20Desarrollo%20y%20evaluaci%C3%B3n%20de%20un%20sistema%20de%20Reconocimiento%20Autom%C3%A1tico%20del%20Habla%20en%20Polaco%20....pdf?sequence=1"]}
-{"year":"2020","title":"Development of a Search Engine to Answer Comparative Queries","authors":["J Huck"],"snippet":"… extraction and tuning the retrieval model. Page 6. References 1. Bevendorff, J., Stein, B., Hagen, M., Potthast, M.: Elastic chatnoir: Search engine for the clueweb and the common crawl. In: ECIR (2018) 2. Bondarenko, A., Fröbe …","url":["http://www.dei.unipd.it/~ferro/CLEF-WN-Drafts/CLEF2020/paper_178.pdf"]}
-{"year":"2020","title":"Development of Word Embeddings for Uzbek Language","authors":["B Mansurov, A Mansurov - arXiv preprint arXiv:2009.14384, 2020"],"snippet":"… variant of Uzbek. As far as we're aware, only fastText [5] word embeddings exist for the Latin variant. However, fastText was trained on the relatively low quality Uzbek Wikipedia and noisy Common Crawl corpus. In this paper …","url":["https://arxiv.org/pdf/2009.14384"]}
-{"year":"2020","title":"Dialog Response Generation Using Adversarially Learned Latent Bag-of-Words","authors":["K Khan - 2020"],"snippet":"Page 1. Dialog Response Generation Using Adversarially Learned Latent Bag-of-Words by Kashif Khan A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Master of Mathematics in Computer Science …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/16188/Khan_Kashif.pdf?sequence=3&isAllowed=y"]}
-{"year":"2020","title":"Dictionary for Computer-Assisted Text Analysis of Cyber Security (TACS)","authors":["A Levordashka, A Joinson, S Jones"],"snippet":"… algorithm [372] implemented via the Python package textacy [7]. We then grouped the terms by semantic similarity, with the help of a vector space model available via the Python library spacy ('en_core_web_lg'), with 685k …","url":["https://nbviewer.jupyter.org/github/anidroid/tacs/blob/master/tacs-soups.pdf"]}
-{"year":"2020","title":"Dictionary-based Data Augmentation for Cross-Domain Neural Machine Translation","authors":["W Peng, C Huang, T Li, Y Chen, Q Liu - arXiv preprint arXiv:2004.02577, 2020"],"snippet":"… The OOD data used for pre-training for the baseline model are extracted from WMT 144 including Eu- roparl V7, New-commentary V9 and Common Crawl corpora … Train Dataset (OOD) Europarl,News-commentary, Common …","url":["https://arxiv.org/pdf/2004.02577"]}
-{"year":"2020","title":"Differences Beyond Identity: Perceived Construal Distance and Interparty Animosity in the United States","authors":["A van Loon, A Goldberg, S Srivastava - SocArXiv. July, 2020"],"snippet":"Page 1. Differences Beyond Identity: Perceived Construal Distance and Interparty Animosity in the United States ∗ Austin van Loon Stanford University Amir Goldberg Stanford University Sameer B. Srivastava …","url":["https://osf.io/j2f6u/download"]}
-{"year":"2020","title":"Dilated Convolution Networks for Classification of ICD-9 based Clinical Summaries","authors":["M Morisio, N Kanwal, I Tutor, DG Rizzo - 2020","N Kanwal - 2020"],"snippet":"… This architecture uses multiple dilation layers with a label-specific dot-based attention mechanism. We have extracted the embeddings from Common Crawl Glove (Global Vector). The architecture of the model is designed to calculate attention to words and their context …","url":["https://webthesis.biblio.polito.it/14400/","https://webthesis.biblio.polito.it/14400/1/tesi.pdf"]}
-{"year":"2020","title":"Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures","authors":["J Launay, I Poli, F Boniface, F Krzakala - arXiv preprint arXiv:2006.12878, 2020"],"snippet":"Page 1. Direct Feedback Alignment Scales to Modern Deep Learning Tasks and Architectures Julien Launay1,2 Iacopo Poli1 François Boniface1 Florent Krzakala1,2 1LightOn 2École Normale Supérieure {julien, iacopo, francois, florent}@lighton.ai Abstract …","url":["https://arxiv.org/pdf/2006.12878"]}
-{"year":"2020","title":"Discovering key topics from short, real-world medical inquiries via natural language processing and unsupervised learning","authors":["A Ziletti, C Berns, O Treichel, T Weber, J Liang… - arXiv preprint arXiv …, 2020"],"snippet":"… Table IIA1 presents a qualitative comparison of a standard embedding (en core web lg, trained on the Common Crawl) and a specialized biomedical embedding (scispaCy en core sci lg, trained also on PubMed). Specifically …","url":["https://arxiv.org/pdf/2012.04545"]}
-{"year":"2020","title":"Discovering Relational Intelligence in Online Social Networks","authors":["L Tan, T Pham, HK Ho, TS Kok - International Conference on Database and Expert …, 2020"],"snippet":"… 100 mil tweets. 283. \\(^\\text {a}\\)https://archive.ics.uci.edu/ml/datasets /bag+of+words. \\(^\\text {b}\\)http://commoncrawl.org/2014/07/april-2014-crawldata-available/. \\(^text {c}\\)https://developer.twitter.com/en/docs.html. \\(^\\text …","url":["https://link.springer.com/chapter/10.1007/978-3-030-59003-1_22"]}
-{"year":"2020","title":"Discovering web services in social web service repositories using deep variational autoencoders","authors":["I Lizarralde, C Mateos, A Zunino, TA Majchrzak… - Information Processing & …, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0306457319310878"]}
-{"year":"2020","title":"Disentangling semantic composition and semantic association in the left temporal lobe Abbreviated title: Semantic composition versus association","authors":["J Li, S Island, A Dhabi, L Pylkkänen"],"snippet":"… derived using the well-known GloVe word embeddings model (Pennington et al., 2014; freely available at https://nlp.stanford.edu/projects/glove/) trained on Common Crawl (https://commoncrawl.org/), which contains petabytes …","url":["https://www.biorxiv.org/content/10.1101/2020.08.17.254482v2.full.pdf"]}
-{"year":"2020","title":"Distractor Analysis and Selection for Multiple-Choice Cloze Questions for Second-Language Learners","authors":["L Gao, K Gimpel, A Jensson"],"snippet":"… form pair. For features that require embedding words, we use the 300-dimensional GloVe word embedPage 4. dings (Pennington et al., 2014) pretrained on the 42 billion token Common Crawl corpus. The GloVe embeddings …","url":["https://ttic.uchicago.edu/~kgimpel/papers/gao+etal.bea2020.pdf"]}
-{"year":"2020","title":"Distributed frameworks for approximate data analytics","authors":["G Hu - 2020"],"snippet":"… analytical queries can be expensive, eg, the Google book Ngrams dataset contains 2.2 TB of text data [17], and CommonCrawl corpus petabytes of web pages [18]. The above challenge is exacerbated when it is desirable to run different types of …","url":["https://rucore.libraries.rutgers.edu/rutgers-lib/65036/PDF/1/play/"]}
-{"year":"2020","title":"Distributed Training of Graph Convolutional Networks using Subgraph Approximation","authors":["A Angerd, K Balasubramanian, M Annavaram - arXiv preprint arXiv:2012.04930, 2020"],"snippet":"… The vertex label is the community a post belongs to. The features consist of an embedding of post information, created using GloVe CommonCrawl (Pennington et al., 2014). The first 20 days of posts are used for training, while the rest are used for testing and validation …","url":["https://arxiv.org/pdf/2012.04930"]}
-{"year":"2020","title":"Distributional and Lexical Exploration of Semantics of Derivational Morphology","authors":["UC Kunter, GN Özdemir, C Bozşahin"],"snippet":"… using Wikipedia datasets. The second one is presented in Grave et al. (2018), covering 157 languages including Turkish. Their models used Common Crawl and Wikipedia datasets and trained on fastText. The models were …","url":["http://www.academia.edu/download/63487208/Distributional_and_Lexical_Exploration_of_Semantics_of_DM20200531-40903-1x0rwv8.pdf"]}
-{"year":"2020","title":"Distributional Models in the Task of Hypernym Discovery","authors":["V Yadrintsev, A Ryzhova, I Sochenkov - Russian Conference on Artificial Intelligence, 2020"],"snippet":"… Most likely, the largest text corpus was used for the first model, which includes Wikipedia and Common Crawl (we do not know the exact volume of crawl-data for the Russian, but roughly 24 terabytes of plain text was used …","url":["https://link.springer.com/chapter/10.1007/978-3-030-59535-7_25"]}
-{"year":"2020","title":"Distributional semantic modeling: a revised technique to train term/word vector space models applying the ontology-related approach","authors":["O Palagin, V Velychko, K Malakhov, O Shchurov - arXiv preprint arXiv:2003.03350, 2020"],"snippet":"… Ac- cessed: 2020-03-03. [42] Firefly documentation. https://rorodata.github. io/firefly/. Accessed: 2020-03-03. [43] Common crawl. http://commoncrawl org/. Accessed: 2020-03-03. [44] Google dataset search. https://datasetsearch …","url":["https://arxiv.org/pdf/2003.03350"]}
-{"year":"2020","title":"Do Neural Language Models Show Preferences for Syntactic Formalisms?","authors":["A Kulmizev, V Ravishankar, M Abdou, J Nivre - arXiv preprint arXiv:2004.14096, 2020"],"snippet":"… Che et al. (2018). These models are trained on 20 million words randomly sampled from the concatenation of WikiDump and CommonCrawl datasets for 44 different languages, including our 13 languages. Each model features …","url":["https://arxiv.org/pdf/2004.14096"]}
-{"year":"2020","title":"Document Representations for Fast and Accurate Retrieval of Mathematical Information","authors":["V Novotný"],"snippet":"Page 1. Masaryk University Faculty of Informatics Document Representations for Fast and Accurate Retrieval of Mathematical Information Rigorous Thesis Vít Novotný Advisor: Doc. RNDr. Petr Sojka, Ph. D. Brno, Fall 2019 Signature …","url":["https://is.muni.cz/th/x86jd/thesis-with-papers.pdf"]}
-{"year":"2020","title":"Domain Name System Security and Privacy: A Contemporary Survey","authors":["A Khormali, J Park, H Alasmary, A Anwar, D Mohaisen - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Domain Name System Security and Privacy: A Contemporary Survey Aminollah Khormali, Jeman Park, Hisham Alasmary, Afsah Anwar, David Mohaisen University of Central Florida Abstract The domain name system …","url":["https://arxiv.org/pdf/2006.15277"]}
-{"year":"2020","title":"Domain Specific Complex Sentence (DCSC) Semantic Similarity Dataset","authors":["D Chandrasekaran, V Mago - arXiv preprint arXiv:2010.12637, 2020"],"snippet":"… trained. While BERT was trained on Book Corpus and Wikipedia corpus, RoBERTa model was trained on four different corpora namely Book Corpus, Common Crawl News dataset, OpenWebText dataset and the Stories dataset …","url":["https://arxiv.org/pdf/2010.12637"]}
-{"year":"2020","title":"Domain-Specific Meta-Embedding with Latent Semantic Structures","authors":["Q Liu, J Lu, G Zhang, T Shen, Z Zhang, H Huang - Information Sciences, 2020"],"snippet":"… For example, GloVe is trained on aggregated global word-word co-occurrence statistics from a corpus of over 840B tokens and fastText [2] pre-trained word representations for 157 languages on Common Crawl and the Wikipedia Corpora …","url":["https://www.sciencedirect.com/science/article/pii/S002002552031029X"]}
-{"year":"2020","title":"DOMINANCE STYLE AND VOCAL COMMUNICATION IN NON-HUMAN PRIMATES","authors":["ZC CHEN-KRAUS, C COYE10, M EMERY… - LANGUAGE of, 2020"],"snippet":"Page 441. DOMINANCE STYLE AND VOCAL COMMUNICATION IN NON-HUMAN PRIMATES K KATIE SLOCOMBE* 1, EITHNE KAVANAGH11,, SALLY STREET2, FELIX O. ANGWELA3, THORE J. BERGMAN4, MARYJKA …","url":["https://pure.mpg.de/rest/items/item_3190925/component/file_3219601/content#page=441"]}
-{"year":"2020","title":"Don't Stop Pretraining: Adapt Language Models to Domains and Tasks","authors":["S Gururangan, A Marasović, S Swayamdipta, K Lo… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Don't Stop Pretraining: Adapt Language Models to Domains and Tasks Suchin Gururangan† Ana Marasovic†♦ Swabha Swayamdipta†♦ Kyle Lo† Iz Beltagy† Doug Downey† Noah A. Smith†♦ †Allen Institute for Artificial …","url":["https://arxiv.org/pdf/2004.10964"]}
-{"year":"2020","title":"DRIVING INTENT EXPANSION VIA ANOMALY DETECTION IN A MODULAR CONVERSATIONAL SYSTEM","authors":["NR Mallinar, TK HO - US Patent App. 16/180,613, 2020"],"snippet":"… In various embodiments, the dataset builder 365 uses one or more of word2vec, the enwiki 2015 document vectorizer, ppdb paragram sentence embeddings, common-crawl uncased GloVe word embeddings, and enwiki …","url":["http://www.freepatentsonline.com/y2020/0142959.html"]}
-{"year":"2020","title":"Drug-Drug Interaction Classification Using Attention Based Neural Networks","authors":["D Zaikis, I Vlahavas - 11th Hellenic Conference on Artificial Intelligence, 2020"],"snippet":"… word in a given sentence. The large English statistical model was used, which is trained with GloVe vectors on the OntoNotes 5 Common Crawl corpus and has a POS syntax accuracy of 97.22 percent. The unique POS tags …","url":["https://dl.acm.org/doi/abs/10.1145/3411408.3411461"]}
-{"year":"2020","title":"Dual Conditional Cross Entropy Scores and LASER Similarity Scores for the WMT20 Parallel Corpus Filtering Shared Task","authors":["F Koerner, P Koehn"],"snippet":"… sentences. The Pashto language model was trained on a concatenation of the CommonCrawl and Wikipedia corpora, with the CommonCrawl oversampled by a factor of 64 to produce a dataset of 9,273,763 sentences. The …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.109.pdf"]}
-{"year":"2020","title":"Dynamic Data Selection and Weighting for Iterative Back-Translation","authors":["ZY Dou, A Anastasopoulos, G Neubig - arXiv preprint arXiv:2004.03672, 2020"],"snippet":"Page 1. Dynamic Data Selection and Weighting for Iterative Back-Translation Zi-Yi Dou, Antonios Anastasopoulos, Graham Neubig Language Technologies Institute, Carnegie Mellon University {zdou, aanastas, gneubig}@cs.cmu.edu Abstract …","url":["https://arxiv.org/pdf/2004.03672"]}
-{"year":"2020","title":"DynE: Dynamic Ensemble Decoding for Multi-Document Summarization","authors":["C Hokamp, DG Ghalandari, NT Pham, J Glover - arXiv preprint arXiv:2006.08748, 2020"],"snippet":"… Ghalandari et al. (2020) presented the WCEP dataset, which is a large-scale collection of clusters of news articles with a corresponding summary, constructed using the Wikipedia Current Events Portal, with additional articles gathered from CommonCrawl …","url":["https://arxiv.org/pdf/2006.08748"]}
-{"year":"2020","title":"EEGdenoiseNet: A benchmark dataset for deep learning solutions of EEG denoising","authors":["H Zhang, M Zhao, C Wei, D Mantini, Z Li, Q Liu - arXiv preprint arXiv:2009.11662, 2020"],"snippet":"Page 1. EEGdenoiseNet: A benchmark dataset for deep learning solutions of EEG denoising Haoming Zhang1,†, Mingqi Zhao1,2,†, Chen Wei1, Dante Mantini2,3, Zherui Li1, Quanying Liu1,∗ September 25, 2020 1 Department …","url":["https://arxiv.org/pdf/2009.11662"]}
-{"year":"2020","title":"Effect of Character and Word Features in Bidirectional LSTM-CRF for NER","authors":["C Ronran, S Lee - 2020 IEEE International Conference on Big Data and …, 2020"],"snippet":"… CRF), respectively, using public word embedding, character features and word features [6,4]. We explore existing word embeddings that is distinct from the previous studies including (1) Glove 300 embedding of 42B, 840B …","url":["https://ieeexplore.ieee.org/abstract/document/9070329/"]}
-{"year":"2020","title":"Efficient and High-Quality Neural Machine Translation with OpenNMT","authors":["G Klein, D Zhang, C Chouteau, JM Crego, J Senellart - Proceedings of the Fourth …, 2020"],"snippet":"… Europarl v9 1,838,568 Common Crawl corpus 2,399,123 News Commentary v14 338,285 Wiki Titles v1 1,305,141 Document-split Rapid 1,531,261 ParaCrawl v3 31,358,551 Total 38,770,929 news-crawl 2007-2018 …","url":["https://www.aclweb.org/anthology/2020.ngt-1.25.pdf"]}
-{"year":"2020","title":"Efficient strategies for hierarchical text classification: External knowledge and auxiliary tasks","authors":["KR Rojas, G Bustamante, MAS Cabezudo, A Oncevay - arXiv preprint arXiv …, 2020"],"snippet":"… of tokens in the input document. We use pre-trained word embeddings from Common Crawl (Grave et al., 2018) for the weights of this layer, and we do not fine-tune them during training time. Encoder: It is a bidirectional GRU …","url":["https://arxiv.org/pdf/2005.02473"]}
-{"year":"2020","title":"Efficient Transfer Learning for Quality Estimation with Bottleneck Adapter Layer","authors":["H Yang, M Wang, N Xie, Y Qin, Y Deng - Proceedings of the 22nd Annual Conference …, 2020"],"snippet":"… BPE is used for tokenizing, where 32000 tokens are reserved. We use UN corpus and Common Crawl parallel corpus with the size of 1https://github.com/pytorch/fairseq Page 5. Total Params Training Params …","url":["https://www.aclweb.org/anthology/2020.eamt-1.4.pdf"]}
-{"year":"2020","title":"Efficiently Reusing Old Models Across Languages via Transfer Learning","authors":["T Kocmi, O Bojar - Proceedings of the 22nd Annual Conference of the …, 2020"],"snippet":"… EN - Russian 12.6M News Commentary, Yandex, and UN Corpus WMT 2012 WMT 2018 EN - French 34.3M Commoncrawl, Europarl, Giga FREN, News commentary, UN corpus WMT 2013 WMT dis. 2015 Table 2: Corpora used for each language pair …","url":["https://www.aclweb.org/anthology/2020.eamt-1.3.pdf"]}
-{"year":"2020","title":"Embedding Compression with Isotropic Iterative Quantization","authors":["S Liao, J Chen, Y Wang, Q Qiu, B Yuan - arXiv preprint arXiv:2001.05314, 2020"],"snippet":"… We perform experiments with the GloVe embedding (Pennington et al. 2014) and the HDC embedding (Sun et al. 2015). The GloVe embedding is trained from 42B tokens of Common Crawl data. The HDC Table 1: Experiment …","url":["https://arxiv.org/pdf/2001.05314"]}
-{"year":"2020","title":"Embedding Compression with Right Triangle Similarity Transformations","authors":["H Song, D Zou, L Hu, J Yuan - International Conference on Artificial Neural Networks, 2020"],"snippet":"… model. 4.1 Experimental Setup. Pre-trained Continuous Embeddings. We conduct experiments on GloVe [16] and fasttext [1]. GloVe embeddings have been trained on 42B tokens of Common Crawl data with 400k words. Fasttext …","url":["https://link.springer.com/chapter/10.1007/978-3-030-61616-8_62"]}
-{"year":"2020","title":"EmoDet2: Emotion Detection in English Textual Dialogue using BERT and BiLSTM Models","authors":["H Al-Omari, MA Abdullah, S Shaikh - 2020 11th International Conference on …, 2020"],"snippet":"… Moreover, we have encoded the words in the conversation using Word2vec, Glove Wiki, and Glove Common Crawl packages … The hyperparameters as follow: Dropout = 0.4, the text in Word2Vec and Glove Wiki are lowered …","url":["https://ieeexplore.ieee.org/abstract/document/9078946/"]}
-{"year":"2020","title":"Emotion Aided Dialogue Act Classification for Task-Independent Conversations in a Multi-modal Framework","authors":["T Saha, D Gupta, S Saha, P Bhattacharyya - Cognitive Computation"],"snippet":"… To extract textual features, a convolutional neural network (CNN) [48]–based approach is used. Pretrained GloVe [49] embeddings trained on the CommonCrawl corpus of dimension 300 have been used to represent words as word vectors …","url":["https://link.springer.com/article/10.1007/s12559-019-09704-5"]}
-{"year":"2020","title":"Employing distributional semantics to organize task-focused vocabulary learning","authors":["HS Ponnusamy, D Meurers - arXiv preprint arXiv:2011.11115, 2020"],"snippet":"… graph, we start with a distributional semantic vector representation of each word, which we obtain from the pre-trained model of GloVe (Pennington et al., 2014) based on the co-occurrence statistics of the the words form a large …","url":["https://arxiv.org/pdf/2011.11115"]}
-{"year":"2020","title":"Empowering Architects and Designers: A Classification of What Functions to Accelerate in Storage","authors":["C Zou, AA Chien"],"snippet":"Page 1. Empowering Architects and Designers: A Classification of What Functions to Accelerate in Storage Chen Zou chenzou@uchicago.edu University of Chicago Andrew A. Chien achien@cs.uchicago.edu University of Chicago …","url":["https://newtraell.cs.uchicago.edu/files/tr_authentic/TR-2020-02.pdf"]}
-{"year":"2020","title":"End to end approach for i2b2 2012 challenge based on Cross-lingual models","authors":["EA Santamaría - 2020"],"snippet":"… Joshi et al., 2019). Unlike mBERT who has been trained on Wikipedia, XLM-RoBERT uses the CommonCrawl(Conneau et al., 2019a) corpus for its training. In this section we explain step by step our approach. First we adapt …","url":["https://addi.ehu.es/bitstream/handle/10810/48623/MAL-Edgar_Andres.pdf?sequence=1"]}
-{"year":"2020","title":"End-to-End Simultaneous Translation System for IWSLT2020 Using Modality Agnostic Meta-Learning","authors":["HJ Han, MA Zaidi, SR Indurthi, NK Lakumarapu, B Lee… - Proceedings of the 17th …, 2020"],"snippet":"… We evaluate our system on the MuST-C Dev set. Our parallel corpus of WMT19 consists of Europarl v9, ParaCrawl v3, Common Crawl, News Commentary v14, Wiki Titles v1 and Documentsplit Rapid for the German-English language pair …","url":["https://www.aclweb.org/anthology/2020.iwslt-1.5.pdf"]}
-{"year":"2020","title":"Energy-Based Models for Text","authors":["A Bakhtin, Y Deng, S Gross, M Ott, MA Ranzato… - arXiv preprint arXiv …, 2020"],"snippet":"… (2015); Kiros et al. (2015), which consists of fiction books in 16 different genres, totaling about half a billion words. • CCNews: We collect a de-duplicated subset of the English portion of the CommonCrawl news …","url":["https://arxiv.org/pdf/2004.10188"]}
-{"year":"2020","title":"English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too","authors":["J Phang, PM Htut, Y Pruksachatkun, H Liu, C Vania… - arXiv preprint arXiv …, 2020"],"snippet":"… 5XLM-R Large (Conneau et al., 2019) is a 550m-parameter variant of the RoBERTa masked language model (Liu et al., 2019b) trained on a cleaned version of CommonCrawl on 100 languages. 6Excluded in this draft due to implementation issues. Page 5 …","url":["https://arxiv.org/pdf/2005.13013"]}
-{"year":"2020","title":"Enhanced-RCNN: An Efficient Method for Learning Sentence Similarity","authors":["S Peng, H Cui, N Xie, S Li, J Zhang, X Li - Proceedings of The Web Conference 2020, 2020"],"snippet":"… Base model. Model parameter size time (s/batch) BERT-Base 102.2M 0.23 ± 0.20 Enhanced-RCNN 7.7M 0.02 ± 0.01 from the 840B Common Crawl corpus [21]. We set the hidden size as 192 for all BiGRU layers. Ant Financial …","url":["https://dl.acm.org/doi/pdf/10.1145/3366423.3379998"]}
-{"year":"2020","title":"Enhancing Word Embeddings with Knowledge Extracted from Lexical Resources","authors":["M Biesialska, B Rafieian, MR Costa-jussà - arXiv preprint arXiv:2005.10048, 2020"],"snippet":"… Dinu et al., 2015; Artetxe et al., 2017, 2018). Moreover, GloVe vectors for English were trained on Common Crawl (Pennington et al., 2014). Linguistic Constraints. To perform semantic specialization of word vector spaces, we …","url":["https://arxiv.org/pdf/2005.10048"]}
-{"year":"2020","title":"Entity-Switched Datasets: An Approach to Auditing the In-Domain Robustness of Named Entity Recognition Models","authors":["O Agarwal, Y Yang, BC Wallace, A Nenkova - arXiv preprint arXiv:2004.04123, 2020"],"snippet":"… al., 2019). For the first two, we used 300-d cased GloVe (Pennington et al., 2014) vectors trained on Common Crawl.7 For BERT, we use the public large8 uncased9 model and apply the default fine-tuning strategy. We use …","url":["https://arxiv.org/pdf/2004.04123"]}
-{"year":"2020","title":"Entrepreneurial Organizations and the Use of Strategic Silence","authors":["W Shi, M Weber - Proceedings of the 54th Hawaii International …"],"snippet":"… number of competing apps for a particular keyword), chart rankings (current ranking position for a keyword), difficulty (the popularity of apps including reviews and ratings) and traffic (eg, autosuggestion when typing in the store …","url":["https://scholarspace.manoa.hawaii.edu/bitstream/10125/71247/0506.pdf"]}
-{"year":"2020","title":"Establishing a New State-of-the-Art for French Named Entity Recognition","authors":["PJO Suárez, Y Dupont, B Muller, L Romary, B Sagot - LREC 2020-12th Language …, 2020"],"snippet":"… They use zero to three of the following vector representations: FastText non-contextual embeddings (Bojanowski et al., 2017), the FrELMo contextual language model ob- tained by training the ELMo architecture on the OSCAR …","url":["https://hal.inria.fr/hal-02617950/document"]}
-{"year":"2020","title":"Estimating educational outcomes from students' short texts on social media","authors":["I Smirnov - EPJ Data Science, 2020"],"snippet":"… We obtained significantly better results with a model that used word-embeddings (see Methods). We also find that embeddings trained on the VK corpus outperform models trained on the Wikipedia and Common Crawl corpora (Table 1). Page 6 …","url":["https://link.springer.com/content/pdf/10.1140/epjds/s13688-020-00245-8.pdf"]}
-{"year":"2020","title":"Estimating Mutual Information Between Dense Word Embeddings","authors":["V Zhelezniak, A Savkov, N Hammerla - Proceedings of the 58th Annual Meeting of …, 2020"],"snippet":"… Our focus here is on fastText vectors (Bojanowski et al., 2017) trained on Common Crawl (600B tokens), as previous literature suggests that among unsupervised vectors fastText yields the best performance for all tasks and …","url":["https://www.aclweb.org/anthology/2020.acl-main.741.pdf"]}
-{"year":"2020","title":"Estimating the influence of auxiliary tasks for multi-task learning of sequence tagging tasks","authors":["F Schröder, C Biemann"],"snippet":"Page 1. Estimating the influence of auxiliary tasks for multi-task learning of sequence tagging tasks Fynn Schröder Language Technology Group Universität Hamburg Hamburg, Germany fschroeder@informatik.uni-hamburg.de …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2020-schroeder-biemann-acl20-dataset-similarity.pdf"]}
-{"year":"2020","title":"Evaluating cross-lingual textual similarity on dictionary alignment problem","authors":["Y Sever, G Ercan - Language Resources and Evaluation, 2020"],"snippet":"… 2018) provides embeddings for 157 different languages trained on Wikipedia and Common Crawl Footnote 3 . For efficiency concerns, each embedding set of the 7 languages are pruned to the the most frequent \\(500\\times 10^3\\) words in each language …","url":["https://link.springer.com/article/10.1007/s10579-020-09498-1"]}
-{"year":"2020","title":"Evaluating German Transformer Language Models with Syntactic Agreement Tests","authors":["K Zaczynska, N Feldhus, R Schwarzenberg…"],"snippet":"… 1 The first model which we refer to as GBERTlarge is a community model provided by the Bavarian State Library.2 It was trained on multiple German corpora including a recent Wikipedia dump, EU Bookshop corpus …","url":["http://ceur-ws.org/Vol-2624/paper7.pdf"]}
-{"year":"2020","title":"Evaluating Multilingual BERT for Estonian","authors":["C Kittask, K Milintsevich, K Sirts - arXiv preprint arXiv:2010.00454, 2020"],"snippet":"… 1Corresponding Author: Claudia Kittask; E-mail: claudiakittask@gmail.com Page 2. and cross-lingual RoBERTa (XLM-RoBERTa) [3], which was trained on much larger CommonCrawl corpora and also includes 100 languages …","url":["https://arxiv.org/pdf/2010.00454"]}
-{"year":"2020","title":"Evaluating Sentence Representations for Biomedical Text: Methods and Experimental Results","authors":["NS Tawfik, MR Spruit - Journal of Biomedical Informatics, 2020"],"snippet":"… 3.2. Embedding Methods. GloVe We use the pre-trained embeddings consisting of 2.2 million vocabulary words available at https://nlp.stanford.edu/projects/glove/ which were trained on the Common Crawl (840B tokens) dataset …","url":["https://www.sciencedirect.com/science/article/pii/S1532046420300253"]}
-{"year":"2020","title":"Evaluating Word Embeddings on Low-Resource Languages","authors":["N Stringham, M Izbicki - Proceedings of the First Workshop on Evaluation and …, 2020"],"snippet":"… Grave et al. (2018) trained FastText embeddings on 157 languages using data from the Common Crawl project. But they were only able to explicitly evaluate 10 of these language models using the analogy task due to the …","url":["https://www.aclweb.org/anthology/2020.eval4nlp-1.17.pdf"]}
-{"year":"2020","title":"Evaluation of related news recommendations using document similarity methods","authors":["M Pranjic, V Podpecan, M Robnik-Šikonja, S Pollak"],"snippet":"… RoBERTa (Liu et al., 2019). It uses the sentence piece tokenizer and it is trained with the masked language model objective (MLM) on the CommonCrawl data in 100 languages, including Croatian. Similar to the mBERT, all …","url":["http://nl.ijs.si/jtdh20/pdf/JT-DH_2020_Pranjic-et-al_Evaluation-of-related-news-recommendations-using-document-similarity-methods.pdf"]}
-{"year":"2020","title":"Event Detection on Literature by Utilizing Word Embedding","authors":["J Chun, C Kim - International Conference on Database Systems for …, 2020"],"snippet":"… On the contrary, Neural-based methods have the limitation that they ignore semantic relationships in a text. 2.3 Facebook Pre-trained Word Vectors. We chose pre-trained word vectors published by Facebook, trained on …","url":["https://link.springer.com/chapter/10.1007/978-3-030-59413-8_21"]}
-{"year":"2020","title":"Evidence Integration for Multi-hop Reading Comprehension with Graph Neural Networks","authors":["L Song, Z Wang, M Yu, Y Zhang, R Florian, D Gildea - IEEE Transactions on …, 2020"],"snippet":"Page 1. 1041-4347 (c) 2020 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/9051845/"]}
-{"year":"2020","title":"Examining the rhetorical capacities of neural language models","authors":["Z Zhu, C Pan, M Abdalla, F Rudzicz - arXiv preprint arXiv:2010.00153, 2020"],"snippet":"… Non-contextualized word embeddings We consider two popular word embeddings here: • GloVe (Pennington et al., 2014) contains 2.2M vocabulary items and produces 300dimensional word vectors. The GloVe embedding …","url":["https://arxiv.org/pdf/2010.00153"]}
-{"year":"2020","title":"Experience Grounds Language","authors":["Y Bisk, A Holtzman, J Thomason, J Andreas, Y Bengio… - arXiv preprint arXiv …, 2020"],"snippet":"… (2013) trained on 1.6 billion tokens, while Pennington et al. (2014) scaled up to 840 billion tokens from Common Crawl. Recent approaches have made progress by substantially increasing the number of model parameters …","url":["https://arxiv.org/pdf/2004.10151"]}
-{"year":"2020","title":"Experiencers, Stimuli, or Targets: Which Semantic Roles Enable Machine Learning to Infer the Emotions?","authors":["L Oberländer, K Reich, R Klinger - arXiv preprint arXiv:2011.01599, 2020"],"snippet":"… 1For ET, 90% of the annotated experiencers are the authors of the tweets without corresponding span annotation. 2We use 42B tokens, pretrained on CommonCrawl (Pennington et al., 2014), https://nlp.stanford.edu …","url":["https://arxiv.org/pdf/2011.01599"]}
-{"year":"2020","title":"Experiments on Paraphrase Identification Using Quora Question Pairs Dataset","authors":["A Chandra, R Stefanus - arXiv preprint arXiv:2006.02648, 2020"],"snippet":"… matching result into a fix-length matching vector and continued to last layer of the model which is a fully connected layer. The paper use GloVe as a pretrained word vector from 840B Common Crawl corpus and apply it to Quora …","url":["https://arxiv.org/pdf/2006.02648"]}
-{"year":"2020","title":"Explicit Alignment Objectives for Multilingual Bidirectional Encoders","authors":["J Hu, M Johnson, O Firat, A Siddhant, G Neubig - arXiv preprint arXiv:2010.07972, 2020"],"snippet":"… Sentence Alignment Our first proposed objective encourages cross-lingual alignment of sentence 1 AMBER is trained on 26GB parallel data and 80GB monolingual Wikipedia data, while XLM-R-large is trained on 2.5TB …","url":["https://arxiv.org/pdf/2010.07972"]}
-{"year":"2020","title":"Explicit Sentence Compression for Neural Machine Translation","authors":["Z Li, R Wang, K Chen, M Utiyama, E Sumita, Z Zhang… - arXiv preprint arXiv …, 2019"],"snippet":"… for NMT evaluation. For the EN-DE translation task, 4.43 M bilingual sentence pairs from the WMT14 dataset were used as training data, including Common Crawl, News Commentary, and Europarl v7. The newstest2013 and …","url":["https://arxiv.org/pdf/1912.11980"]}
-{"year":"2020","title":"Exploiting Categorization of Online News for Profiling City Areas","authors":["A Bondielli, P Ducange, F Marcelloni - 2020 IEEE Conference on Evolving and …, 2020"],"snippet":"… FastText is created by Facebook and is based on Neural Networks. Pre-trained word vectors are available for 157 languages, trained on Common Crawl and Wikipedia. More specifically, we chose to use the pre-trained Italian model …","url":["https://ieeexplore.ieee.org/abstract/document/9122777/"]}
-{"year":"2020","title":"Exploiting Class Labels to Boost Performance on Embedding-based Text Classification","authors":["A Zubiaga - arXiv preprint arXiv:2006.02104, 2020"],"snippet":"… 4.2 Word Embedding Models & Classifiers We tested four word embedding models: (1) Google's Word2Vec model (gw2v), (2) a Twitter Word2Vec model5 (tw2v) [10], (3) GloVe embeddings trained from Common Crawl (cglove) …","url":["https://arxiv.org/pdf/2006.02104"]}
-{"year":"2020","title":"Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning","authors":["T Shen, Y Mao, P He, G Long, A Trischler, W Chen - arXiv preprint arXiv:2004.14224, 2020"],"snippet":"Page 1. EXPLOITING STRUCTURED KNOWLEDGE IN TEXT VIA GRAPH-GUIDED REPRESENTATION LEARNING Tao Shen∗ University of Technology Sydney tao.shen@student.uts.edu.au Yi Mao, Pengcheng …","url":["https://arxiv.org/pdf/2004.14224"]}
-{"year":"2020","title":"Exploring Different Methods for Solving Analogies with Portuguese Word Embeddings","authors":["T Sousa, H Gonçalo Oliveira, A Alves - 9th Symposium on Languages, Applications …, 2020"],"snippet":"… from several sources. Such sources include raw text (ie, an ensemble of Google News word2vec, Common Crawl GloVe, Open Subtitles fastText) combined with the ConceptNet semantic network with retrofitting. 1 https://github …","url":["https://drops.dagstuhl.de/opus/volltexte/2020/13022/pdf/OASIcs-SLATE-2020-9.pdf"]}
-{"year":"2020","title":"Exploring Event Extraction Across Languages","authors":["S Prabhu - 2020"],"snippet":"Page 1. Exploring Event Extraction Across Languages Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computational Linguistics by Research by Suhan Prabhu 201525118 suhan.prabhuk@research.iiit.ac.in …","url":["http://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.b481c850852a12a8.737568616e5f66696e616c5f7468657369732e706466.pdf"]}
-{"year":"2020","title":"Exploring Neural Network Approaches in Automatic Personality Recognition of Filipino Twitter Users","authors":["E Tighe, O Aran, C Cheng"],"snippet":"… FastText differs by learning character-grams, as opposed to word-grams. We utilize the embeddings trained on Common Crawl and Wikipedia data2 – specifically, the embeddings for English and Tagalog (both 300 dimensions) …","url":["https://www.researchgate.net/profile/Edward_Tighe/publication/343189230_Exploring_Neural_Network_Approaches_in_Automatic_Personality_Recognition_of_Filipino_Twitter_Users/links/5f1ae2aea6fdcc9626ad4c4d/Exploring-Neural-Network-Approaches-in-Automatic-Personality-Recognition-of-Filipino-Twitter-Users.pdf"]}
-{"year":"2020","title":"Exploring Swedish & English fastText Embeddings with the Transformer","authors":["TP Adewumi, F Liwicki, M Liwicki - arXiv preprint arXiv:2007.16007, 2020"],"snippet":"… We obtain better performance in both languages on the downstream task with far smaller training data, compared to recently released, common crawl versions and character n-grams appear useful for Swedish, a morphologically rich language …","url":["https://arxiv.org/pdf/2007.16007"]}
-{"year":"2020","title":"Exploring the Dominance of the English Language on the Websites of EU Countries","authors":["A Giannakoulopoulos, M Pergantis, N Konstantinou… - Future Internet, 2020"],"snippet":"… For this purpose, we used information obtained from Common Crawl, a “repository of web crawl data that is universally accessible and analyzable” [34]. Among the data Common Crawl offers is an index of every available webpage …","url":["https://www.mdpi.com/1999-5903/12/4/76/pdf"]}
-{"year":"2020","title":"Extended Overview of CLEF HIPE 2020: Named Entity Processing on Historical Newspapers","authors":["A Flückiger, S Clematide"],"snippet":"Page 1. Extended Overview of CLEF HIPE 2020: Named Entity Processing on Historical Newspapers Maud Ehrmann1[0000−0001−9900−2193], Matteo Romanello1[0000−0002− 1890−2577], Alex Flückiger2, and Simon Clematide2[0000−0003−1365−0662] …","url":["http://ceur-ws.org/Vol-2696/paper_255.pdf"]}
-{"year":"2020","title":"Extended study on using pretrained language models and YiSi-1 for machine translation evaluation","authors":["C Lo - Proceedings of the Fifth Conference on Machine …, 2020"],"snippet":"… The differencesbetweenXLM-RandBERTare1)XLM-Ris trained on the CommonCrawl corpus which is significantly larger than the Wikipedia training data used by BERT; 2) instead of a uniform data sampling rate used in BERT …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.99.pdf"]}
-{"year":"2020","title":"Extending Tables using a Web Table Corpus","authors":["S Sarabchi - 2020"],"snippet":"… Lehmberg et al. [12] gathered a web table corpus containing 233 million tables from the 2015 version of the CommonCrawl2, using a table extraction method similar to that of [11]. The table corpus … and 2https://commoncrawl.org/about …","url":["https://era.library.ualberta.ca/items/4f9f40b8-69ba-4c24-85b4-41f17517cc59/view/dfd3938b-a7d1-4b4c-85e0-4087c36d5713/Sarabchi_Saeed_202002_MSc.pdf"]}
-{"year":"2020","title":"Extracting Family History of Patients From Clinical Narratives: Exploring an End-to-End Solution With Deep Learning Models","authors":["X Yang, H Zhang, X He, J Bian, Y Wu - JMIR Medical Informatics, 2020"],"snippet":"… We screened 4 different word embeddings following a similar procedure reported in our previous study [46] and found that the Common Crawl embeddings—released by Facebook and trained using the fastText on the …","url":["https://medinform.jmir.org/2020/12/e22982/"]}
-{"year":"2020","title":"Extracting Training Data from Large Language Models","authors":["N Carlini, F Tramer, E Wallace, M Jagielski… - arXiv preprint arXiv …, 2020"],"snippet":"… In particular, we select samples from a subset of Common Crawl6 to feed as context to the model.7 6http://commoncrawl.org/ 7It is possible there is some intersection between these two datasets, effectively allowing this strategy to “cheat” …","url":["https://arxiv.org/pdf/2012.07805"]}
-{"year":"2020","title":"Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation","authors":["I Chung, B Kim, Y Choi, SJ Kwon, Y Jeon, B Park… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. arXiv:2009.07453v1 [cs.LG] 16 Sep 2020 Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation Insoo Chung∗ Byeongwook Kim∗ Yoonjung Choi Se Jung Kwon Yongkweon …","url":["https://arxiv.org/pdf/2009.07453"]}
-{"year":"2020","title":"Facebook AI's WMT20 News Translation Task Submission","authors":["PJ Chen, A Lee, C Wang, N Goyal, A Fan… - arXiv preprint arXiv …, 2020"],"snippet":"… we use all the available monolingual data, eg NewsCrawl + CommonCrawl + Wikipedia dumps for Tamil, and CommonCrawl for Inuktitut … unconstrained track, we use Tamil monolingual data and Tamil-English mined bitext data …","url":["https://arxiv.org/pdf/2011.08298"]}
-{"year":"2020","title":"Factors affecting sentence similarity and paraphrasing identification","authors":["M Alian, A Awajan - International Journal of Speech Technology, 2020"],"snippet":"… Grave et al. (2018) contributed in a pre-trained word vector representation for 157 languages including Arabic. The word vectors have been trained on Wikipedia and the Common Crawl corpus using an extension of the FastText model with subword information …","url":["https://link.springer.com/article/10.1007/s10772-020-09753-4"]}
-{"year":"2020","title":"Fairness in AI-based Recruitment and Career Pathway Optimization","authors":["DF Mujtaba - 2020"],"snippet":"Page 1. FAIRNESS IN AI-BASED RECRUITMENT AND CAREER PATHWAY OPTIMIZATION By Dena Freshta Mujtaba A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of …","url":["http://search.proquest.com/openview/f2938ed72cda2c3b656a0db1b2be7320/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2020","title":"Fake News Data Collection and Classification: Iterative Query Selection for Opaque Search Engines with Pseudo Relevance Feedback","authors":["A Elyashar, M Reuben, R Puzis - arXiv preprint arXiv:2012.12498, 2020"],"snippet":"Page 1. FAKE NEWS DATA COLLECTION AND CLASSIFICATION: ITERATIVE QUERY SELECTION FOR OPAQUE SEARCH ENGINES WITH PSEUDO RELEVANCE FEEDBACK APREPRINT Aviad Elyashar, Maor Reuben …","url":["https://arxiv.org/pdf/2012.12498"]}
-{"year":"2020","title":"Fake News Detection","authors":["IP Marín, D Arroyo - Conference on Complex, Intelligent, and Software …, 2020"],"snippet":"… 4. https://spacy.io/ [Last accessed 26 Jan 2020]. 5. en_core_web_lg, pre-trained English statistical models. English multi-task CNN trained on OntoNotes, with GloVe vectors trained on Common Crawl. 6. https …","url":["https://link.springer.com/chapter/10.1007/978-3-030-57805-3_22"]}
-{"year":"2020","title":"Fake news spreader detection using neural tweet aggregation","authors":["O Bakhteev, A Ogaltsov, P Ostroukhov"],"snippet":"… As a preprocessing step we lowercased tweets and removed stop-words and punctuation. We did not use any special preprocessing. For the word embeddings we used fastText [1] trained on Common Crawl and Wikipedia with dimension set to 100 …","url":["https://pan.webis.de/downloads/publications/papers/bakhteev_2020.pdf"]}
-{"year":"2020","title":"Fake News Spreader Identification in Twitter using Ensemble Modeling","authors":["A Hashemi, MR Zarei, MR Moosavi, M Taheri"],"snippet":"… Page 4. The sources used in the English model for training data are OntoNotes 51 and GloVe Common Crawl2 and the Spanish model utilizes UD Spanish AnCora v2.53, WikiNER4, OSCAR (Common Crawl)5 and Wikipedia …","url":["https://pan.webis.de/downloads/publications/papers/hashemi_2020.pdf"]}
-{"year":"2020","title":"Fashion-IQ 2020 Challenge 2nd Place Team's Solution","authors":["M Shin, Y Cho, S Hong - arXiv preprint arXiv:2007.06404, 2020"],"snippet":"… For training the LSTM and the GRU from scratch, we initialize the word embedding with the concatenation of three GloVe vectors2 learned from Wikipedia, Twitter, and Common Crawl that results in 900-dimensional input …","url":["https://arxiv.org/pdf/2007.06404"]}
-{"year":"2020","title":"Fast entity linking in noisy text environments","authors":["SM Shah, MD Conover, PN Skomoroch, MT Hayes… - US Patent 10,733,383, 2020"],"snippet":"… entry). In some embodiments, the candidate dictionary is determined by using the hyperlinks on a Wikipedia page, or a Common Crawl page to identify surface forms (the hyperlink anchor text) that point to a specific page. Each …","url":["http://www.freepatentsonline.com/10733383.html"]}
-{"year":"2020","title":"Fast Indexes for Gapped Pattern Matching","authors":["M Cáceres, SJ Puglisi, B Zhukova - International Conference on Current Trends in …, 2020"],"snippet":"… Open image in new window Fig. 2. Fig. 2. Time to search a 2GiB subset of the Common Crawl web collection (commoncrawl.org). for 20 VLG patterns (\\(k=2\\), \\(delta _i,\\varDelta _i = \\langle 100,110\\rangle \\)), composed of very …","url":["https://link.springer.com/chapter/10.1007/978-3-030-38919-2_40"]}
-{"year":"2020","title":"FinBERT: A Pre-trained Financial Language Representation Model for Financial Text Mining","authors":["Z Liu, D Huang, K Huang, Z Li, J Zhao"],"snippet":"… sizes, totaling over 61 GB text: • English Wikipedia1 and BooksCorpus (Zhu et al., 2015), which are the original training data used to train BERT (totaling 13GB, 3.31B words); • FinancialWeb (totaling 24GB, 6.38B words), which …","url":["https://www.ijcai.org/Proceedings/2020/0622.pdf"]}
-{"year":"2020","title":"Finding of asymmetric relation between words","authors":["M Muraoka, T Nasukawa, KMA Salam - US Patent App. 16/287,326, 2020"],"snippet":"US20200272696A1 - Finding of asymmetric relation between words - Google Patents. Finding of asymmetric relation between words. Download PDF Info. Publication number US20200272696A1. US20200272696A1 US16/287,326 …","url":["https://patents.google.com/patent/US20200272696A1/en"]}
-{"year":"2020","title":"Finding the needle in the haystack: Fine-tuning transformers to classify protest events in a sea ofnews articles, with Bayesian uncertainty measures","authors":["C Ghai - 2020"],"snippet":"Page 1. Finding the needle in the haystack: Fine-tuning transformers to classify protest events in a sea of news articles, with Bayesian uncertainty measures Chris Ghai Master's Thesis, Spring 2020 Page 2. This master's thesis …","url":["https://www.duo.uio.no/bitstream/handle/10852/79984/1/chris_ghai_thesis.pdf"]}
-{"year":"2020","title":"Findings of the 2020 conference on machine translation (wmt20)","authors":["L Barrault, M Biesialska, O Bojar, MR Costa-jussà… - Proceedings of the Fifth …, 2020"],"snippet":"… Distinct words – 76,013 – 6,165 178,453 85,189 Common Crawl Parallel Corpus German ↔ English Czech ↔ English Russian ↔ English French ↔ German … Common Crawl Language Model Data English German Czech Russian Polish Sent …","url":["https://www.aclweb.org/anthology/2020.wmt-1.1.pdf"]}
-{"year":"2020","title":"Findings of the WMT 2020 Biomedical Translation Shared Task: Basque, Italian and Russian as New Additional Languages","authors":["R Bawden, G Di Nunzio, C Grozea, I Unanue, A Yepes… - 5th Conference on Machine …, 2020"],"snippet":"Page 1. HAL Id: hal-02986356 https://hal.inria.fr/hal-02986356 Submitted on 2 Nov 2020 HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not …","url":["https://hal.inria.fr/hal-02986356/document"]}
-{"year":"2020","title":"Findings of the WMT 2020 shared task on parallel corpus filtering and alignment","authors":["P Koehn, V Chaudhary, A El-Kishky, N Goyal, PJ Chen… - Proceedings of the Fifth …, 2020"],"snippet":"… Noisy parallel documents and parallel sentences were sourced from the CCAligned2 dataset (El- Kishky et al., 2020a), a massive collection of cross-lingual web documents covering over 8k language pairs aligned from …","url":["https://www.aclweb.org/anthology/2020.wmt-1.78.pdf"]}
-{"year":"2020","title":"Fine-Grained Argument Unit Recognition and Classification","authors":["D Trautmann, J Daxenberger, C Stab, H Schütze…"],"snippet":"… Table 1). This also increases comparability with related work. The topics are general enough to have good coverage in Common Crawl … 4http://commoncrawl.org/2016/02/ february-2016-crawlarchive-now-available/ 5https://www.elastic.co/products/elasticsearch …","url":["https://www.researchgate.net/profile/Dietrich_Trautmann/publication/332590723_Robust_Argument_Unit_Recognition_and_Classification/links/5e32b02ca6fdccd96576e059/Robust-Argument-Unit-Recognition-and-Classification.pdf"]}
-{"year":"2020","title":"Fine-grained entity type classification using GRU with self-attention","authors":["K Dhrisya, G Remya, A Mohan - International Journal of Information Technology, 2020"],"snippet":"… The dictionary for the proposed model is built with GLoVe vectors of 300 dimensions. It is a pre-trained word embedding created by utilizing common Crawl 840B. These vectors on various corpora can be downloaded from Stanford GLoVe Website. Parameter settings …","url":["https://link.springer.com/article/10.1007/s41870-020-00499-5"]}
-{"year":"2020","title":"FLERT: Document-Level Features for Named Entity Recognition","authors":["S Schweter, A Akbik - arXiv preprint arXiv:2011.06993, 2020"],"snippet":"… Conneau et al. (2019). We use the xlm-roberta-large model in our experiments, trained on 2.5TB of data from a cleaned Common Crawl corpus (Wenzek et al., 2020) for 100 different languages Embeddings (+WE). For each setup …","url":["https://arxiv.org/pdf/2011.06993"]}
-{"year":"2020","title":"Forum Duplicate Question Detection by Domain Adaptive Semantic Matching","authors":["Z Xu, H Yuan - IEEE Access, 2020"],"snippet":"… B. MODEL IMPLEMENTATION The word embedding was initialized with 300-dimensional GloVe [33] vectors which are pretrained in the 840B Common Crawl corpus. The Embedding was set to be trainable. The …","url":["https://ieeexplore.ieee.org/iel7/6287639/8948470/09043551.pdf"]}
-{"year":"2020","title":"Four dimensions characterizing comprehensive trait judgments of faces","authors":["C Lin, U Keles, R Adolphs - 2020"],"snippet":"… and text classi cation using a neural network provided within the FastText library40; this neural network had been trained on Common Crawl data of 600 billion words to predict the identity of a word given a context. We then applied …","url":["https://www.researchsquare.com/article/rs-41215/latest.pdf"]}
-{"year":"2020","title":"French Contextualized Word-Embeddings with a sip of CaBeRnet: a New French Balanced Reference Corpus","authors":["M Fabre, PJO Suárez, B Sagot, ÉV de la Clergerie - CMLC-8-8th Workshop on the …, 2020","M Popa-Fabre, PJO Suárez, B Sagot… - Proceedings of the 8th …, 2020"],"snippet":"… al., 2019), we decided to include in our comparison a corpus of French text extracted from Common Crawl8. We … 8More information available at https://commoncrawl … OSCAR gathers a set of monolingual text extracted …","url":["https://hal.inria.fr/hal-02678358/document","https://www.aclweb.org/anthology/2020.cmlc-1.3.pdf"]}
-{"year":"2020","title":"Frequency-dependent Regularization in Constituent Ordering Preferences","authors":["Z Liu, E Morgan"],"snippet":"… a total of around 9 billion tokens. This corpus consists of web page data from both Common Crawl and Wikipedia and is automatically parsed with UDPipe (Straka & Straková, 2017). Within this corpus, each token is represented …","url":["https://www.researchgate.net/profile/Zoey_Liu2/publication/341712949_Frequency-dependent_Regularization_in_Constituent_Ordering_Preferences/links/5ecffdb292851c9c5e65d021/Frequency-dependent-Regularization-in-Constituent-Ordering-Preferences.pdf"]}
-{"year":"2020","title":"From Chest X-Rays to Radiology Reports: A Multimodal Machine Learning Approach","authors":["S Singh, S Karimi, K Ho-Shon, L Hamey - 2019 Digital Image Computing: Techniques …, 2019"],"snippet":"… Also, on the text side, we use the Glove [30] word embeddings having a 300-dimensional embedding vector for each word, and have been trained on a generic text corpus named Common Crawl having 42B tokens, 1.9M vocab …","url":["https://ieeexplore.ieee.org/abstract/document/8945819/"]}
-{"year":"2020","title":"From Dataset Recycling to Multi-Property Extraction and Beyond","authors":["T Dwojak, M Pietruszka, Ł Borchmann, J Chłędowski… - arXiv preprint arXiv …, 2020"],"snippet":"… T5. Recently proposed T5 model (Raffel et al., 2020) is a Transformer model pretrained on a cleaned version of CommonCrawl. T5 is famous for achieving excellent performance on the SuperGLUE benchmark (Wang et al., 2019) …","url":["https://arxiv.org/pdf/2011.03228"]}
-{"year":"2020","title":"From Hero to Z\\'eroe: A Benchmark of Low-Level Adversarial Attacks","authors":["S Eger, Y Benz - arXiv preprint arXiv:2010.05648, 2020"],"snippet":"… The reason may be that our noises are not always natural, in the sense of having high support in large datasets such as CommonCrawl or Wikipedia, but they are still within the limits of cognitive abilities of ordinary humans …","url":["https://arxiv.org/pdf/2010.05648"]}
-{"year":"2020","title":"From Pixel to Patch: Synthesize Context-aware Features for Zero-shot Semantic Segmentation","authors":["Z Gu, S Zhou, L Niu, Z Zhao, L Zhang - arXiv preprint arXiv:2009.12232, 2020"],"snippet":"Page 1. 1 From Pixel to Patch: Synthesize Context-aware Features for Zero-shot Semantic Segmentation Zhangxuan Gu, Siyuan Zhou, Li Niu*, Zihan Zhao, Liqing Zhang* Abstract—Zero-shot learning has been actively studied …","url":["https://arxiv.org/pdf/2009.12232"]}
-{"year":"2020","title":"From Syntactic Structure to Semantic Relationship: Hypernym Extraction from Definitions by Recurrent Neural Networks Using the Part of Speech Information","authors":["Y Tan, X Wang, T Jia - International Semantic Web Conference, 2020"],"snippet":"… In recent years, much research pay attention to extracting hypernyms from larger data resources via the high precise of pattern-based methods. [25] extract hypernymy relations from the CommonCrawl web corpus using lexico-syntactic patterns …","url":["https://link.springer.com/chapter/10.1007/978-3-030-62419-4_30"]}
-{"year":"2020","title":"From Web Crawl to Clean Register-Annotated Corpora","authors":["V Laippala, S Rönnqvist, S Hellström, J Luotolahti… - … of the 12th Web as Corpus …, 2020"],"snippet":"… crawl or extracting data from existing crawl-based datasets, such as Common Crawl1. As … CommonCrawl is a free and openly available web crawl maintained by the CommonCrawl … Lately the Common Crawl dataset has …","url":["https://www.aclweb.org/anthology/2020.wac-1.3.pdf"]}
-{"year":"2020","title":"From Zero to Hero: On the Limitations of Zero-Shot Cross-Lingual Transfer with Multilingual Transformers","authors":["A Lauscher, V Ravishankar, I Vulić, G Glavaš - arXiv preprint arXiv:2005.00633, 2020"],"snippet":"… It is trained on the CommonCrawl-100 data (Wenzek et al., 2019) of 100 languages … Interestingly, for both high7For XLM-R, we take the reported sizes of languagespecific portions of CommonCrawl-100 from Conneau et al …","url":["https://arxiv.org/pdf/2005.00633"]}
-{"year":"2020","title":"From Zero to Hero: On the Limitations of Zero-Shot Language Transfer with Multilingual Transformers","authors":["A Lauscher, V Ravishankar, I Vulić, G Glavaš - … of the 2020 Conference on Empirical …, 2020"],"snippet":"… sampling. XLM on RoBERTa (XLM-R). XLM-R (Conneau et al., 2020) is an instance of RoBERTa, robustly trained on a large multilingual CommonCrawl-100 (CC-100) corpus (Wenzek et al., 2019) covering 100 languages …","url":["https://www.aclweb.org/anthology/2020.emnlp-main.363.pdf"]}
-{"year":"2020","title":"Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing","authors":["Z Dai, G Lai, Y Yang, QV Le - arXiv preprint arXiv:2006.03236, 2020"],"snippet":"… ablation studies. 5 Page 6. • Large scale: Pretraining models for 500K steps with batch size 8K on the five datasets used by XLNet [3] and ELECTRA [5] (Wikipedia + Book Corpus + ClueWeb + Gigaword + Common Crawl). We will …","url":["https://arxiv.org/pdf/2006.03236"]}
-{"year":"2020","title":"Gated Semantic Difference Based Sentence Semantic Equivalence Identification","authors":["X Liu, Q Chen, X Wu, Y Hua, J Chen, D Li, B Tang… - IEEE/ACM Transactions on …, 2020"],"snippet":"… The word embeddings for the quora corpus are 300dimensional GloVe word vectors pre-trained from the 840B Common Crawl corpus [45] and for the LCQMC are 300-dimensional word vectors pre-trained from the Chinese 5[Online] …","url":["https://ieeexplore.ieee.org/abstract/document/9222233/"]}
-{"year":"2020","title":"Gender Bias in Multilingual Embeddings and Cross-Lingual Transfer","authors":["J Zhao, S Mukherjee, S Hosseini, KW Chang… - arXiv preprint arXiv …, 2020"],"snippet":"… is an OCCUPATION-TITLE” where name is recognized in each language by using the corresponding Named Entity Recognition model from spaCy.5 To control for the same time period for datasets across languages …","url":["https://arxiv.org/pdf/2005.00699"]}
-{"year":"2020","title":"Gender Bias in Multilingual Embeddings","authors":["J Zhao, S Mukherjee, S Hosseini, KW Chang…"],"snippet":"… an OCCUPATION-TITLE” where name is recognized in each language by using the corresponding Named Entity Recognition model from spaCy.5 To control for the same time period for datasets across languages …","url":["https://www.researchgate.net/profile/Subhabrata_Mukherjee/publication/340660062_Gender_Bias_in_Multilingual_Embeddings/links/5e97428692851c2f52a6200a/Gender-Bias-in-Multilingual-Embeddings.pdf"]}
-{"year":"2020","title":"Gender Detection on Social Networks using Ensemble Deep Learning","authors":["K Kowsari, M Heidarysafa, T Odukoya, P Potter… - arXiv preprint arXiv …, 2020"],"snippet":"… 25d, 50d, 100d, and 200d vectors. This word embedding is trained over even bigger corpora, including Wikipedia and Common Crawl content. The objective function is as follows: f(wi − wj, ˜wk) = Pik Pjk (2) where wi is refer to …","url":["https://arxiv.org/pdf/2004.06518"]}
-{"year":"2020","title":"Gender stereotype reinforcement: Measuring the gender bias conveyed by ranking algorithms","authors":["A Fabris, A Purpura, G Silvello, GA Susto - Information Processing & Management, 2020"],"snippet":"… Corrado, Dean, 2013). Most frequently, they are learnt from large text corpora available online (such as Wikipedia, Google News and Common Crawl, capturing semantic relationships of words based on their usage. Recent work …","url":["https://arxiv.org/pdf/2009.01334"]}
-{"year":"2020","title":"Gender stereotypes are reflected in the distributional structure of 25 languages","authors":["M Lewis, G Lupyan - Nature Human Behaviour, 2020"],"snippet":"Cultural stereotypes such as the idea that men are more suited for paid work and women are more suited for taking care of the home and family, may contribute to gender imbalances in science, technology, engineering and …","url":["https://www.nature.com/articles/s41562-020-0918-6"]}
-{"year":"2020","title":"Generalisation of Cyberbullying Detection","authors":["K Richard, L Marc-André - arXiv preprint arXiv:2009.01046, 2020","MA Larochelle, R Khoury"],"snippet":"… We use FastText pre-trained on Common Crawl data featuring 300 dimensions and 2 million word vectors with subword information6 to convert the words into vector representations, of which we concatenate a 60-dimensional binary …","url":["https://arxiv.org/pdf/2009.01046","https://web.ntpu.edu.tw/~myday/doc/ASONAM2020/ASONAM2020_Proceedings/pdf/papers/047_034_296.pdf"]}
-{"year":"2020","title":"Generalize Sentence Representation with Self-Inference","authors":["KC Yang, HY Kao"],"snippet":"… Our model is trained with the phrases in the parse trees and tested on the whole sentence. Experimental Settings We initialize word embeddings using the pretrained FastText common-crawl vectors (Mikolov et al. 2018) and freeze the weights during training …","url":["https://www.aaai.org/Papers/AAAI/2020GB/AAAI-YangKC.7098.pdf"]}
-{"year":"2020","title":"Generating Categories for Sets of Entities","authors":["S Zhang, K Balog, J Callan - arXiv preprint arXiv:2008.08428, 2020"],"snippet":"… entity linking for tables and table schema to predicate matching. Ritze et al. [31] propose an iterative method for matching tables to DBpedia. They develop a manually annotated dataset for matching between a Web table corpus …","url":["https://arxiv.org/pdf/2008.08428"]}
-{"year":"2020","title":"Generating Diverse Conversation Responses by Creating and Ranking Multiple Candidates","authors":["YP Ruan, ZH Ling, X Zhu, Q Liu, JC Gu - Computer Speech & Language, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0885230820300048"]}
-{"year":"2020","title":"Generating Fact Checking Briefs","authors":["A Fan, A Piktus, F Petroni, G Wenzek, M Saeidi… - Proceedings of the 2020 …, 2020"],"snippet":"… We take the top search hit as the evidence and retrieve the text from CommonCrawl4. Finally, the generated question and retrieved evidence document is provided to the question answering model to generate an answer. 4.1 Question Generation …","url":["https://www.aclweb.org/anthology/2020.emnlp-main.580.pdf"]}
-{"year":"2020","title":"Generating fake websites: WikiGen","authors":["M Longland - 2020"],"snippet":"… [2015]. This is a relatively small vector file. An alternative considered was the Common Crawl (840B tokens) vectors from Stanford NLP's GloVe [Pennington et al., 2014] but memory issues meant the smaller file was used instead …","url":["https://pdfs.semanticscholar.org/0776/aece84f01a6f593d1748657bf2ec4dec49b4.pdf"]}
-{"year":"2020","title":"Generating Keyword Lists Related to Topics Represented by an Array of Topic Records, for Use in Targeting Online Advertisements and Other Uses","authors":["L Palaic, MH Gross, SA Schriber - US Patent App. 16/803,214, 2020"],"snippet":"… For data gathering purposes, a custom heuristic can be used that operates on a Common Crawl Corpus. Documents gathered from a Common Crawl process might be automatically annotated with appropriate topics tags so …","url":["https://patents.google.com/patent/US20200273069A1/en"]}
-{"year":"2020","title":"Generating Personalized Product Descriptions from User Reviews","authors":["G Elad, K Radinsky, B Kimelfeld - 2019"],"snippet":"Page 1. Generating Personalized Product Descriptions from User Reviews Guy Elad Technion - Computer Science Department - M.Sc. Thesis MSC-2019-25 - 2019 Page 2. Technion - Computer Science Department …","url":["http://www.cs.technion.ac.il/users/wwwb/cgi-bin/tr-get.cgi/2019/MSC/MSC-2019-25.pdf"]}
-{"year":"2020","title":"Generating Query Suggestions for Cross-language and Cross-terminology Health Information Retrieval","authors":["PM Santos, C Teixeira Lopes - Advances in Information Retrieval: 42nd European …, 2020"],"snippet":"… The English collection is provided by the Consumer Health Search Task in the 2018 edition of the CLEF eHealth Lab2. This task uses a set of 50 English queries and a document corpus with 5,535,120 web pages acquired from a CommonCrawl dump …","url":["https://link.springer.com/content/pdf/10.1007/978-3-030-45442-5_43.pdf"]}
-{"year":"2020","title":"Generating Representative Headlines for News Stories","authors":["X Gu, Y Mao, J Han, J Liu, H Yu, Y Wu, C Yu, D Finnie… - arXiv preprint arXiv …, 2020"],"snippet":"… By fine-tuning the model on human-curated labels, we can combine the two sources of supervision and further improve performance. 6One can use CommonCrawl to fetch web articles. Page 5. Generating Representative Headlines for News Stories …","url":["https://arxiv.org/pdf/2001.09386"]}
-{"year":"2020","title":"Generative Language Modeling for Automated Theorem Proving","authors":["S Polu, I Sutskever - arXiv preprint arXiv:2009.03393, 2020"],"snippet":"… We pre-train our models on both GPT-3's post-processed version of CommonCrawl as well as a more reasoning-focused mix of Github, arXiv and Math StackExchange. 7 … 5.3 Pre-training Models are pre-trained on …","url":["https://arxiv.org/pdf/2009.03393"]}
-{"year":"2020","title":"Generative Models are Unsupervised Predictors of Page Quality: A Colossal-Scale Study","authors":["D Bahri, Y Tay, C Zheng, D Metzler, C Brunk… - arXiv preprint arXiv …, 2020"],"snippet":"… 3.1 Datasets This section describes the datasets used in our experiments. • Web500M. The core corpora used in our experiments consists of a random sample of 500 million English web documents obtained from the Common Crawl1. • GPT-2-Output …","url":["https://arxiv.org/pdf/2008.13533"]}
-{"year":"2020","title":"Geographically-Balanced Gigaword Corpora for 50 Language Varieties","authors":["J Dunn, B Adams - Proceedings of The 12th Language Resources and …, 2020"],"snippet":"… 3. Collecting Geo-Referenced Documents The data for this paper comes from the Common Crawl,2 as processed in the Corpus of Global Language Use (henceforth, CGLU). This project includes the Common Crawl data from …","url":["https://www.aclweb.org/anthology/2020.lrec-1.308.pdf"]}
-{"year":"2020","title":"Geoparsing the historical Gazetteers of Scotland: accurately computing location in mass digitised texts","authors":["R Filgueira, C Grover, M Terras, B Alex - Proceedings of the 8th Workshop on …, 2020"],"snippet":"… Small size model (11MB). • en core web md: English multi-task CNN trained on OntoNotes, with GloVe vectors trained on Common Crawl … en core web lg: English multi-task CNN trained on OntoNotes, with GloVe vectors trained on Common Crawl …","url":["https://www.aclweb.org/anthology/2020.cmlc-1.4.pdf"]}
-{"year":"2020","title":"GeoVectors: a Linked Open Corpus of OpenStreetMap Embeddings","authors":["N Tempelmeier, S Gottschalk, E Demidova - 2020"],"snippet":"… As most of the OSM keys are in English, we chose the 300-dimensional English word vectors trained on the Common Crawl and Wikipedia [5]. Encoding: To encode an OSM entity o, we utilise the individual word em …","url":["https://openreview.net/pdf?id=EibPtOjZUn"]}
-{"year":"2020","title":"German's Next Language Model","authors":["B Chan, S Schweter, T Möller - arXiv preprint arXiv:2010.10906, 2020"],"snippet":"… The XLM-RoBERTa model is trained on 2.5TB of data from a cleaned Common Crawl corpus (Wenzek et al., 2020) for 100 different languages … OSCAR (Ortiz Suárez et al., 2019) is a set of monolingual corpora extracted from Common Crawl …","url":["https://arxiv.org/pdf/2010.10906"]}
-{"year":"2020","title":"Getting Closer to AI Complete Question Answering: A Set of Prerequisite Real Tasks","authors":["AROKM Downey, A Rumshisky"],"snippet":"… Similarity-based approaches. The first baseline represents a given text, a question, and each of the choices as the average of 300-dimensional CommonCrawl FastText word embeddings (Bojanowski et al. 2016) of its constituent words …","url":["https://www.aaai.org/Papers/AAAI/2020GB/AAAI-RogersA.7778.pdf"]}
-{"year":"2020","title":"Getting Passive Aggressive About False Positives: Patching Deployed Malware Detectors","authors":["E Raff, B Filar, J Holt - arXiv preprint arXiv:2010.12080, 2020"],"snippet":"… We base our testing and results on a representative sample of industry data. Our corpus consisted of 1,101,407 Microsoft Office documents that contained macros. Similar to [33] data was collected from Common Crawl (CC) [34] and VirusTotal [35] …","url":["https://arxiv.org/pdf/2010.12080"]}
-{"year":"2020","title":"Getting Structured Data from the Internet","authors":["BDP Scale, JM Patel"],"snippet":"… WARC file format ..... 278 Common crawl index ..... 282 … 331 Processing parquet files for a common crawl index ..... 334 …","url":["https://link.springer.com/content/pdf/10.1007/978-1-4842-6576-5.pdf"]}
-{"year":"2020","title":"Give your Text Representation Models some Love: the Case for Basque","authors":["R Agerri, IS Vicente, JA Campos, A Barrena, X Saralegi… - arXiv preprint arXiv …, 2020"],"snippet":"… Common Crawl word vectors (FastText-officialcommon-crawl) were trained on Common Crawl and Wikipedia using CBOW with position-weights … train our systems to perform the following comparisons: (i) FastText official models …","url":["https://arxiv.org/pdf/2004.00033"]}
-{"year":"2020","title":"GLEAKE: Global and Local Embedding Automatic Keyphrase Extraction","authors":["JR Asl, JM Banda - arXiv preprint arXiv:2005.09740, 2020"],"snippet":"… doc2vec_news_dbow AP News glove.6B Wikipedia + Gigaword GloVe 50-300 [28] glove.twitter.27B Twitter 25-200 glove.840B Common Crawl 300 TABLE 1 DIFFERENT PRE-TRAINED EMBEDDINGS USED BY GLEAKE Page 5. 5 …","url":["https://arxiv.org/pdf/2005.09740"]}
-{"year":"2020","title":"Global Under-Resourced MEedia Translation (GoURMET)","authors":["MAAS BBC, JW BBC, B Haddow, AM Barone…"],"snippet":"Page 1. GoURMET H2020–825299 D5.3 Initial Integration Report Global Under-Resourced MEedia Translation (GoURMET) H2020 Research and Innovation Action Number: 825299 D5.3 – Initial Integration Report Nature Report Work Package WP5 …","url":["https://gourmet-project.eu/wp-content/uploads/2020/07/GoURMET_D5_3_Initial_Integration_Report.pdf"]}
-{"year":"2020","title":"Going Back in Time to Find What Existed on the Web and How much has been Preserved: How much of Palestinian Web has been Archived?","authors":["T Sammar, H Khalilia - مؤتمرات الآداب والعلوم الانسانية والطبيعية, 2020"],"snippet":"‎… References 1. Common crawl url index. url (http://index.commoncrawl.org/). 2. International internet preservation consortium (iipc).http://www.netpreserve.org. 3. Internet archive (https://archive.org/). 4. Internet archive wayback machine. url (https://archive.org/web/) …","url":["http://proceedings.sriweb.org/akn/index.php/art/article/viewFile/410/466"]}
-{"year":"2020","title":"Goku's Participation in WAT 2020","authors":["D Wang, O Htun - Proceedings of the 7th Workshop on Asian Translation, 2020"],"snippet":"… Secondly, we fine-tuned on the JPO patent corpus using the mBART auto-encoder model (Liu et al., 2020), which has been pre-trained on largescale monolingual CommonCrawl (CC) corpus in 25 languages using the BART objective (Lewis et al., 2020) …","url":["https://www.aclweb.org/anthology/2020.wat-1.16.pdf"]}
-{"year":"2020","title":"GoodReads Book Recommendation Service","authors":["Y Tian, V Bai, Z Doganata"],"snippet":"… Common Crawl: https://commoncrawl.org/ Models: ● Howard, Jeremy and Ruder, Sebastian. \"Universal Language Model Fine-tuning for Text Classification.\" Paper presented at the meeting of the ACL, 2018. ● Conneau …","url":["http://tianyijun.com/files/GoodReads_Recommendation.pdf"]}
-{"year":"2020","title":"GottBERT: a pure German Language Model","authors":["R Scheible, F Thomczyk, P Tippmann, V Jaravine… - arXiv preprint arXiv …, 2020"],"snippet":"… dbmz BERT used as source data a German Wikipedia dump, EU Bookshop corpus, Open Subtitles, CommonCrawl, ParaCrawl and News Crawl which … than mBERT, the multilingual XLM-RoBERTa (Conneau et al., 2019) was …","url":["https://arxiv.org/pdf/2012.02110"]}
-{"year":"2020","title":"GPT-3 AI language tool calls for cautious optimism","authors":["Oxford Analytica - Emerald Expert Briefings"],"snippet":"… The training process leveraged this by exposing GPT-3 to historical sweeps of the internet, known as 'crawls'. One substantial component was the Common Crawl dataset, a multilingual capture of almost 1 trillion words …","url":["https://www.emerald.com/insight/content/doi/10.1108/OXAN-DB256373/full/html"]}
-{"year":"2020","title":"GPT-3 Creative Fiction","authors":["G Branwen - 2020"],"snippet":"… For GPT-2, I saw finetuning as doing 2 things: Fixing ignorance: missing domain knowledge. GPT-2 didn't know many things about most things—it was just a handful (1.5 billion) of parameters trained briefly on …","url":["https://www.gwern.net/GPT-3"]}
-{"year":"2020","title":"Grammatical Error Correction in Low Error Density Domains: A New Benchmark and Analyses","authors":["S Flachs, O Lacroix, H Yannakoudakis, M Rei… - arXiv preprint arXiv …, 2020"],"snippet":"… matical errors. The source texts are randomly se- lected from the first 18 dumps of the CommonCrawl4 dataset and represent a wide range of data seen online such as blogs, magazines, corporate or educational websites. These …","url":["https://arxiv.org/pdf/2010.07574"]}
-{"year":"2020","title":"Graph Attention Network with Memory Fusion for Aspect-level Sentiment Analysis","authors":["L Yuan, J Wang, LC Yu, X Zhang - Proceedings of the 1st Conference of the Asia …, 2020"],"snippet":"Page 1. Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, pages 27–36 December 4 - 7, 2020 …","url":["https://www.aclweb.org/anthology/2020.aacl-main.4.pdf"]}
-{"year":"2020","title":"Graph Policy Network for Transferable Active Learning on Graphs","authors":["S Hu, Z Xiong, M Qu, X Yuan, MA Côté, Z Liu, J Tang - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Graph Policy Network for Transferable Active Learning on Graphs Shengding Hu Tsinghua University hsd16@mails.tsinghua.edu.cn Zheng Xiong Tsinghua University harryfootball@163.com Meng Qu MILA meng.qu@umontreal.ca …","url":["https://arxiv.org/pdf/2006.13463"]}
-{"year":"2020","title":"Graphical User Interface Auto-Completion with Element Constraints","authors":["L Brückner - 2020"],"snippet":"Page 1. Aalto University School of Science Master's Programme in ICT Innovation Lukas Brückner Graphical User Interface Auto-Completion with Element Constraints Master's Thesis Espoo, September 25, 2020 Supervisor: Prof …","url":["https://aaltodoc.aalto.fi/bitstream/handle/123456789/47385/master_Br%C3%BCckner_Lukas_2020.pdf?sequence=1"]}
-{"year":"2020","title":"GraphWalker: An I/O-Efficient and Resource-Friendly Graph Analytic System for Fast and Scalable Random Walks","authors":["R Wang, Y Li, H Xie, Y Xu, JCS Lui"],"snippet":"Page 1. GraphWalker: An I/O-Efficient and Resource-Friendly Graph Analytic System for Fast and Scalable Random Walks Rui Wang1, Yongkun Li1, Hong Xie2, Yinlong Xu1, John CS Lui3 1University of Science and Technology …","url":["https://www.cse.cuhk.edu.hk/~cslui/PUBLICATION/ATC2020.pdf"]}
-{"year":"2020","title":"GREEK-BERT: The Greeks visiting Sesame Street","authors":["J Koutsikakis, I Chalkidis, P Malakasiotis… - arXiv preprint arXiv …, 2020"],"snippet":"… and (c) the Greek part of OSCAR [25], a clean version of Common Crawl.5 Accents and other diacritics were removed, and all words were … 5https://commoncrawl.org 6https://github.com/google-research/bert 7The …","url":["https://arxiv.org/pdf/2008.12014"]}
-{"year":"2020","title":"Grounded Compositional Outputs for Adaptive Language Modeling","authors":["N Pappas, P Mulcaire, NA Smith - arXiv preprint arXiv:2009.11523, 2020"],"snippet":"Page 1. Grounded Compositional Outputs for Adaptive Language Modeling Nikolaos Pappas♣ Phoebe Mulcaire♣ Noah A. Smith♣♦ ♣Paul G. Allen School of Computer Science & Engineering, University of Washington ♦Allen …","url":["https://arxiv.org/pdf/2009.11523"]}
-{"year":"2020","title":"Guided Generation of Cause and Effect","authors":["Z Li, X Ding, T Liu, JE Hu, B Van Durme"],"snippet":"… 3629 Page 2. Processed Common Crawl Corpus Causal Patterns Based Matching and Filtering … Thus we harvest a large causal dataset from the preprocessed large-scale English Common Crawl corpus (5.14 TB) [Buck et al., 2014] …","url":["https://www.ijcai.org/Proceedings/2020/0502.pdf"]}
-{"year":"2020","title":"Harbsafe-162. A Domain-Specific Data Set for the Intrinsic Evaluation of Semantic Representations for Terminological Data","authors":["S Arndt, D Schnäpp - arXiv preprint arXiv:2005.14576, 2020"],"snippet":"Page 1. Harbsafe-162 – A Domain-Specific Data Set for the Intrinsic Evaluation of Semantic Representations for Terminological Data Susanne Arndt, MA∗ Technische Universität Braunschweig Dieter Schnäpp, MA∗∗ Technische Universität Braunschweig …","url":["https://arxiv.org/pdf/2005.14576"]}
-{"year":"2020","title":"Hard-Coded Gaussian Attention for Neural Machine Translation","authors":["W You, S Sun, M Iyyer - arXiv preprint arXiv:2005.00742, 2020"],"snippet":"… 10As the full WMT14 En→Fr is too large for us to feasibly train on, we instead follow Akoury et al. (2019) and train on just the Europarl / Common Crawl subset, while evaluating using the full dev/test sets. 11https://github.com/dojoteef/synst Page 5 …","url":["https://arxiv.org/pdf/2005.00742"]}
-{"year":"2020","title":"Harnessing Multilinguality in Unsupervised Machine Translation for Rare Languages","authors":["X Garcia, A Siddhant, O Firat, AP Parikh - arXiv preprint arXiv:2009.11201, 2020"],"snippet":"… In contrast, for an actual low-resource language, Gujarati, WMT only provides 500 thousand lines of monolingual data (in news domain) and an additional 3.7 million lines of monolingual data from Common Crawl (noisy, generaldomain) …","url":["https://arxiv.org/pdf/2009.11201"]}
-{"year":"2020","title":"HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection","authors":["B Mathew, P Saha, SM Yimam, C Biemann, P Goyal… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection* Binny Mathew1†, Punyajoy Saha1†, Seid Muhie Yimam2 Chris Biemann2, Pawan Goyal1, Animesh Mukherjee1 1 Indian Institute of Technology …","url":["https://arxiv.org/pdf/2012.10289"]}
-{"year":"2020","title":"HCA: Hierarchical Compare Aggregate model for question retrieval in community question answering","authors":["MS Zahedi, M Rahgozar, RA Zoroofi - Information Processing & Management, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S030645732030813X"]}
-{"year":"2020","title":"Hidden in Plain Sight: Building a Global Sustainable Development Data Catalogue","authors":["J Hodson, A Spezzatti - ICT Analysis and Applications, 2020"],"snippet":"… We iteratively re-train our model using 300-dimensional word-embedding features trained on the CommonCrawl web-scale data set 7 with the GLobal VEctors for Word Representation (GloVe) procedure (see [7]). Table 2 shows …","url":["https://link.springer.com/content/pdf/10.1007/978-981-15-8354-4.pdf#page=795"]}
-{"year":"2020","title":"Hierarchical models vs. transfer learning for document-level sentiment classification","authors":["J Barnes, V Ravishankar, L Øvrelid, E Velldal - arXiv preprint arXiv:2002.08131, 2020"],"snippet":"… Universal Language Model Fine-Tuning (ULMFIT): We use the AWD-LSTM architecture (Merity et al., 2018) and pretrain on Wikipedia data (or Common Crawl in the case of Norwegian) taken from the CONLL 2017 shared task (Zeman et al., 2017) …","url":["https://arxiv.org/pdf/2002.08131"]}
-{"year":"2020","title":"Hierarchical Multimodal Attention for End-to-End Audio-Visual Scene-Aware Dialogue Response Generation","authors":["H Le, D Sahoo, NF Chen, SCH Hoi - Computer Speech & Language, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0885230820300280"]}
-{"year":"2020","title":"High Accuracy Phishing Detection Based on Convolutional Neural Networks","authors":["SY Yerima, MK Alzaylaee - 2020"],"snippet":"… Their approach first encodes the URL strings using one-hot encoding and then inputs each encoded character vector into the LSTM neurons for training and testing. Their method achieved an accuracy of 0.935 on the Common …","url":["https://dora.dmu.ac.uk/bitstream/handle/2086/19450/HAPD-CNN-paper-accepted-version.pdf?sequence=1&isAllowed=y"]}
-{"year":"2020","title":"HitAnomaly: Hierarchical Transformers for Anomaly Detection in System Log","authors":["S Huang, Y Liu, C Fung, R He, Y Zhao, H Yang, Z Luan - IEEE Transactions on …, 2020"],"snippet":"… matrix. Finally, we obtain the word vector of 'terminating' as [16, 2, 11]. LogRobust [10] leverages off-the-shelf word vectors, which were pre-trained on Common Crawl Corpus dataset using the Fast-Text [20] algorithm. We initialize …","url":["https://ieeexplore.ieee.org/abstract/document/9244088/"]}
-{"year":"2020","title":"How “BERTology” Changed the State-of-the-Art also for Italian NLP","authors":["F Tamburini - Proceedings of the Seventh Italian Conference on …, 2020"],"snippet":"… Page 2. billions of tokens. Also for GilBERTo it is available only the uncased model. • UmBERTo4: the more recent model de- veloped explicitly for Italian, as far as we know, is UmBERTo ('Musixmatch/umbertocommoncrawl-cased-v1' – umC) …","url":["http://ceur-ws.org/Vol-2769/paper_79.pdf"]}
-{"year":"2020","title":"How Furiously Can Colourless Green Ideas Sleep? Sentence Acceptability in Context","authors":["JH Lau, CS Armendariz, S Lappin, M Purver, C Shu - arXiv preprint arXiv:2004.00881, 2020"],"snippet":"… BERTUCS Transformer Bidir. 340M Uncased 13GB WordPiece Wikipedia, BookCorpus XLNET Transformer Hybrid 340M Cased 126GB SentenceWikipedia, BookCorpus, Giga5 Piece ClueWeb, Common Crawl Table 1: Language models and their configurations …","url":["https://arxiv.org/pdf/2004.00881"]}
-{"year":"2020","title":"How Human is Machine Translationese? Comparing Human and Machine Translations of Text and Speech","authors":["J van Genabith, E Teich","Y Bizzoni, TS Juzek, C España-Bonet, KD Chowdhury… - Proceedings of the 17th …, 2020"],"snippet":"… German translation and interpreting are both from English. lines de tokens en tokens Ct Cs CommonCrawl 2,212,292 49,870,179 54,140,396 MultiUN 108,387 4,494,608 4,924,596 NewsCommentary 324,388 8,316,081 46,222,416 …","url":["http://www.sfb1102.uni-saarland.de/wp/wp-content/uploads/2020/06/IWSLT-b1-B7-final2020.pdf","https://www.aclweb.org/anthology/2020.iwslt-1.34.pdf"]}
-{"year":"2020","title":"How Language Shapes Prejudice Against Women: An Examination Across 45 World Languages","authors":["D DeFranza, H Mishra, A Mishra - 2020"],"snippet":"… context in which it occurs. Using text data from Wikipedia and the Common Crawl project … discussing gender issues. Wikipedia and a corpus of web crawl data from over five billion web pages, known as the Common Crawl, serve as our data source …","url":["https://psyarxiv.com/mrbcf/download?format=pdf"]}
-{"year":"2020","title":"How Many Pages? Paper Length Prediction from the Metadata","authors":["E Çano, O Bojar - arXiv preprint arXiv:2010.15924, 2020"],"snippet":"… We used static word embeddings of 300 dimensions from three sources: the 6 billion tokens collection of Common Crawl4 trained with Glove [23], the 840 billion tokens collection of Common Crawl trained with Glove, and …","url":["https://arxiv.org/pdf/2010.15924"]}
-{"year":"2020","title":"How Much Self-attention Do We Need? Trading Attention for Feed-forward Layers","authors":["K Irie, A Gerstenberger, R Schlüter, H Ney - ICASSP, Barcelona, Spain, 2020"],"snippet":"… to 6 (in contrast to what we typically observe eg, on LibriSpeech [28]): this is in fact due to some overlap between the common crawl training subset … Then we fine-tune the model on the TED-LIUM 2 transcriptions (2 M words) …","url":["https://www-i6.informatik.rwth-aachen.de/publications/download/1126/Irie-ICASSP-2020.pdf"]}
-{"year":"2020","title":"How Should Markup Tags Be Translated?","authors":["G Hanneman, G Dinu, AI Amazon"],"snippet":"… especially large or noisy data sets. For EN–DE, we begin with the training data released by the WMT 2020 news task, ignoring the Common Crawl and Paracrawl corpora and heavily filtering WikiMatrix. Our EN–FR training data …","url":["https://assets.amazon.science/fa/f2/640de7fd483a8c385db7a0b5c7cd/how-should-markup-tags-be-translated.pdf"]}
-{"year":"2020","title":"Human-in-the-Loop AI for Analysis of Free Response Facial Expression Label Sets","authors":["C Butler, H Oster, J Togelius - Proceedings of the 20th ACM International Conference …, 2020"],"snippet":"… 1. GloVe, 300-dimensional vectors trained on Common Crawl [33]: distributional model that learns word vectors by examining word co- occurrences within a text corpus with logbilinear regression, global matrix factorization and local context window methods …","url":["https://dl.acm.org/doi/abs/10.1145/3383652.3423892"]}
-{"year":"2020","title":"Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning","authors":["R Schuster, T Schuster, Y Meri, V Shmatikov - arXiv preprint arXiv:2001.04935, 2020"],"snippet":"Page 1. Humpty Dumpty: Controlling Word Meanings via Corpus Poisoning* Roei Schuster Tel Aviv University † roeischuster@mail.tau.ac.il Tal Schuster CSAIL, MIT tals@csail.mit.edu Yoav Meri † 111yoav@gmail.com Vitaly …","url":["https://arxiv.org/pdf/2001.04935"]}
-{"year":"2020","title":"Hungarian layer: A novel interpretable neural layer for paraphrase identification","authors":["H Xiao - Neural Networks, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0893608020302653"]}
-{"year":"2020","title":"HW-TSC's Participation in the WMT 2020 News Translation Shared Task","authors":["D Wei, H Shang, Z Wu, Z Yu, L Li, J Guo, M Wang…"],"snippet":"… monolingual text from Common Crawl and news crawl 2018 for Km and En, respectively. 2.1.3 Ps/En Similar to Km/En, we also use the Para Crawl v5.1 (1M), Khmer and Pashto parallel data (0.03M) as bitext and select …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.31.pdf"]}
-{"year":"2020","title":"Hybrid Feature Model for Emotion Recognition in Arabic Text","authors":["N Alswaidan, MEB Menai - IEEE Access, 2020"],"snippet":"… 5https://github.com/minimaxir/char-embeddings 6https://unicode.org/emoji/ charts/full-emoji-list.html • FastText [22]: 300-dimensional word vectors trained on Common Crawl7 using CBOW with position weights … 7https://commoncrawl …","url":["https://ieeexplore.ieee.org/iel7/6287639/8948470/09007420.pdf"]}
-{"year":"2020","title":"HyCoNN: Hybrid Cooperative Neural Networks for Personalized News Discussion Recommendation","authors":["J Risch, V Künstler, R Krestel"],"snippet":"… For DeepCoNN and also HyCoNN, we use 300-dimensional fastText word embeddings, which were pre-trained on the English-language Common Crawl dataset [25]. The resulting embeddings function as input to a convolutional layer that consists of n neurons …","url":["https://hpi.de/fileadmin/user_upload/fachgebiete/naumann/people/risch/risch2020hyconn.pdf"]}
-{"year":"2020","title":"Identifying Cognates in English-Dutch and French-Dutch by means of Orthographic Information and Cross-lingual Word Embeddings","authors":["E Lefever, S Labat, P Singh - the 12th Conference on Language Resources and …, 2020"],"snippet":"… The former approach was improved in the following way. Firstly, standard fastText word embeddings, which were pretrained on Common Crawl and Wikipedia and generated with the standard skip-gram model as proposed by Bo- janowski et al …","url":["https://biblio.ugent.be/publication/8662200/file/8662201"]}
-{"year":"2020","title":"Identifying Phished Website Using Multilayer Perceptron","authors":["A Dev, V Jain - Advances in Distributed Computing and Machine …"],"snippet":"… Phishing Webpage Source: PhishTank, OpenPhish. Legitimate Webpage Source: Alexa, Common Crawl. The main process in the phishing webpage is to work on its features and how effectively it is handling the dataset. Each …","url":["https://link.springer.com/chapter/10.1007/978-981-15-4218-3_37"]}
-{"year":"2020","title":"Identifying Sensitive URLs at Web-Scale","authors":["M Srdjan, I Costas, S Georgios, N Laoutaris - 2020","S Matic, C Iordanou, G Smaragdakis, N Laoutaris - studies"],"snippet":"… We then use our classifier to search for sensitive URLs in a corpus of 1 Billion URLs collected by the Common Crawl project. We identify more than 155 millions sensitive URLs in more than 4 million domains … Automated …","url":["http://eprints.networks.imdea.org/2187/1/imc20.pdf","http://laoutaris.info/wp-content/uploads/2020/09/imc2020.pdf"]}
-{"year":"2020","title":"Identifying Tasks from Mobile App Usage Patterns","authors":["Y Tian, K Zhou, M Lalmas, D Pelleg - Proceedings of the 43rd International ACM …, 2020"],"snippet":"Page 1. Identifying Tasks from Mobile App Usage Patterns Yuan Tian University of Nottingham Nottingham, UK yuan.tian@nottingham.ac.uk Ke Zhou University of Nottingham Nottingham, UK ke.zhou@nottingham.ac …","url":["https://dl.acm.org/doi/abs/10.1145/3397271.3401441"]}
-{"year":"2020","title":"Igbo-English Machine Translation: An Evaluation Benchmark","authors":["I Ezeani, P Rayson, I Onyenwe, C Uchechukwu… - arXiv preprint arXiv …, 2020"],"snippet":"… Page 2. Published as a conference paper at ICLR 2020 texts (eg Wikipedia, CommonCrawl, local government materials, local TV/Radio stations etc). Phase 2: Translation and correction In this phase, the 10,000 sentence pairs …","url":["https://arxiv.org/pdf/2004.00648"]}
-{"year":"2020","title":"IIU: Specialized Architecture for Inverted Index Search","authors":["J Heo, J Won, Y Lee, S Bharuka, J Jang, TJ Ham…"],"snippet":"Page 1. IIU: Specialized Architecture for Inverted Index Search Jun Heo∗ Jaeyeon Won∗ Yejin Lee∗ Shivam Bharuka†§ Jaeyoung Jang‡ Tae Jun Ham∗ Jae W. Lee∗ ∗Seoul National University, †Facebook, Inc., ‡Sungkyunkwan University …","url":["https://www.cs.princeton.edu/~tae/iiu_asplos2020.pdf"]}
-{"year":"2020","title":"Imitation Attacks and Defenses for Black-box Machine Translation Systems","authors":["E Wallace, M Stern, D Song - arXiv preprint arXiv:2004.15015, 2020"],"snippet":"… For English→German, we query the source side of the WMT14 training set (≈ 4.5M sentences).3 For Nepali→English, we query the Nepali Language Wikipedia (≈ 100,000 sentences) and approximately two million sentences from Nepali common crawl …","url":["https://arxiv.org/pdf/2004.15015"]}
-{"year":"2020","title":"Impact of News on the Commodity Market: Dataset and Results","authors":["A Sinha, T Khandait - arXiv preprint arXiv:2009.04202, 2020"],"snippet":"… The GloVe pre-trained word-embeddings are known to capture the meaning of a word through a high dimensional vector [22]. For this research, we used the 300-dimensional vectors which were trained on 840 billion tokens through the common crawl …","url":["https://arxiv.org/pdf/2009.04202"]}
-{"year":"2020","title":"Impact of sentence length on the readability of web for screen reader users","authors":["BB Kadayat, E Eika - International Conference on Human-Computer …, 2020"],"snippet":"… They used MapReduce for real-time calculation of the readability of more than a billion webpages. The datasets called Common Crawl included 61 million domain-names, 92 million PDF documents, and seven million Word documents …","url":["https://link.springer.com/chapter/10.1007/978-3-030-49282-3_18"]}
-{"year":"2020","title":"Improved method of word embedding for efficient analysis of human sentiments","authors":["S Sagnika, BSP Mishra, SK Meher - Multimedia Tools and Applications, 2020"],"snippet":"… Designed by Pennington [23] in 2014, it creates a word vector space by training on word-word co-occurrence counts. The models are trained on Wikipedia dumps, Gigaword 5 and Common Crawl texts, and apply …","url":["https://link.springer.com/article/10.1007/s11042-020-09632-9"]}
-{"year":"2020","title":"Improving Indonesian Text Classification Using Multilingual Language Model","authors":["IF Putra, A Purwarianti - arXiv preprint arXiv:2009.05713, 2020"],"snippet":"… The XLM-R Large also has substantially more parameters and was trained on a larger balanced dataset from the CommonCrawl corpus that contains 100 languages. The XLM-R variant that we use in the experiment is …","url":["https://arxiv.org/pdf/2009.05713"]}
-{"year":"2020","title":"IMPROVING KNOWLEDGE ACCESSIBILITY ON THE WEB","authors":["R Yu"],"snippet":"Page 1. IMPROVING KNOWLEDGE ACCESSIBILITY ON THE WEB – from Knowledge Base Augmentation to Search as Learning Inaugural dissertation for the attainment of the title of doctor in the Faculty of Mathematics and …","url":["https://docserv.uni-duesseldorf.de/servlets/DerivateServlet/Derivate-56199"]}
-{"year":"2020","title":"Improving Low Compute Language Modeling with In-Domain Embedding Initialisation","authors":["C Welch, R Mihalcea, JK Kummerfeld - arXiv preprint arXiv:2009.14109, 2020"],"snippet":"… We see that the value of additional data depends on the domain. Gigaword is also news text and is able to improve performance. The larger GloVe datasets use Wikipedia and CommonCrawl data, which is a poorer match and so does not improve performance …","url":["https://arxiv.org/pdf/2009.14109"]}
-{"year":"2020","title":"Improving Network Security through Collaborative Sharing","authors":["CS Ardi - 2020"],"snippet":"Page 1. IMPROVING NETWORK SECURITY THROUGH COLLABORATIVE SHARING by Calvin Satiawan Ardi A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA …","url":["http://search.proquest.com/openview/9de70dfceaa27a03d073c17f5f071579/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2020","title":"Improving Personal Health Mention Detection on Twitter Using Permutation Based Word Representation Learning","authors":["PI Khan, I Razzak, A Dengel, S Ahmed - International Conference on Neural …, 2020"],"snippet":"… In: Invited Talk at the SIGIR 2012 Workshop on Open-Source Information Retrieval (2012)Google Scholar. 24. Common CrawlCommon crawl corpus (2019). http://commoncrawl.org. Copyright information. © Springer Nature …","url":["https://link.springer.com/chapter/10.1007/978-3-030-63830-6_65"]}
-{"year":"2020","title":"Improving Ranking in Document based Search Systems","authors":["RRK Menon, J Kaartik, ETK Nambiar, AK TK, A Kumar - 2020 4th International …, 2020"],"snippet":"… The pre-trained word embedding models used were: 1. Fasttext i. – Wiki News 1M 16B Tokens ii. – Common Crawl 2M 600B Tokens 2. GloVe 2.2M 840B Tokens B. Evaluation Metrics The standard metrics include Precision, Recall, and F1 score …","url":["https://ieeexplore.ieee.org/abstract/document/9143047/"]}
-{"year":"2020","title":"Increasing Accessibility of Electronic Theses and Dissertations (ETDs) Through Chapter-level Classification","authors":["PM Jude - 2020"],"snippet":"Page 1. Increasing Accessibility of Electronic Theses and Dissertations (ETDs) Through Chapter-level Classification Palakh Mignonne Jude Thesis submitted to the Faculty of the Virginia Polytechnic Institute and State University …","url":["https://vtechworks.lib.vt.edu/bitstream/handle/10919/99294/Jude_P_T_2020.pdf?sequence=1"]}
-{"year":"2020","title":"INDEXING OF BIG TEXT DATA AND SEARCHING IN THE INDEXED DATA","authors":["BD KOZÁK"],"snippet":"… enhanced documents. Input data In [14, 8], the input data was CommonCrawl and Wikipedia. The English wikipedia … 8 Page 15. CommonCrawl3is a project that maintains an open repository of web crawl data. For the practical part of …","url":["https://dspace.vutbr.cz/bitstream/handle/11012/192492/final-thesis.pdf?sequence=3"]}
-{"year":"2020","title":"Indic-Transformers: An Analysis of Transformer Language Models for Indian Languages","authors":["K Jain, A Deshpande, K Shridhar, F Laumann, A Dash - arXiv preprint arXiv …, 2020"],"snippet":"… The Open Super-large Crawled ALMAnaCH coRpus (OSCAR) dataset [48] is a filtered version of the CommonCrawl dataset and has monolingual corpora for 166 languages. Prior to training, we normalize the OSCAR dataset for …","url":["https://arxiv.org/pdf/2011.02323"]}
-{"year":"2020","title":"IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Language Models for Indian Languages","authors":["D Kakwani, A Kunchukuttan, S Golla, A Bhattacharyya…"],"snippet":"… The OSCAR project (Ortiz Suarez et al., 2019), a recent processing of CommonCrawl, also contains much less data for most Indian languages than our crawls. The CCNet () and C4 () projects also provide tools to …","url":["https://indicnlp.ai4bharat.org/papers/arxiv2020_indicnlp_corpus.pdf"]}
-{"year":"2020","title":"IndoNLU: Benchmark and Resources for Evaluating Indonesian Natural Language Understanding","authors":["B Wilie, K Vincentio, GI Winata, S Cahyawijaya, X Li… - arXiv preprint arXiv …, 2020"],"snippet":"… Page 5. Dataset # Words # Sentences Size Style Source OSCAR (Ortiz Suárez et al., 2019) 2,279,761,186 148,698,472 14.9 GB mixed OSCAR CoNLLu Common Crawl (Ginter et al., 2017) 905,920,488 77,715,412 6.1 GB mixed LINDAT/CLARIAH-CZ …","url":["https://arxiv.org/pdf/2009.05387"]}
-{"year":"2020","title":"Inducing Language-Agnostic Multilingual Representations","authors":["W Zhao, S Eger, J Bjerva, I Augenstein - arXiv preprint arXiv:2008.09112, 2020"],"snippet":"… XLM-R Contextualized word embeddings (Conneau et al., 2019) are pre-trained on the CommonCrawl corpora of 100 languages, which contain more monolingual data than Wikipedia corpora, with 1) a vocabulary size …","url":["https://arxiv.org/pdf/2008.09112"]}
-{"year":"2020","title":"Inductive Learning on Commonsense Knowledge Graph Completion","authors":["B Wang, G Wang, J Huang, J You, J Leskovec… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Inductive Learning on Commonsense Knowledge Graph Completion Bin Wang1, Guangtao Wang2, Jing Huang2, Jiaxuan You3, Jure Leskovec3, C.-C. Jay Kuo1 1 University of Southern California 2 JD AI Research …","url":["https://arxiv.org/pdf/2009.09263"]}
-{"year":"2020","title":"Inexpensive Domain Adaptation of Pretrained Language Models: A Case Study on Biomedical Named Entity Recognition","authors":["N Poerner, U Waltinger, H Schütze - arXiv preprint arXiv:2004.03354, 2020"],"snippet":"… 1 Introduction Pretrained Language Models such as BERT (De- vlin et al., 2019) have spearheaded advances on many NLP tasks. Usually, PTLMs are pretrained on unlabeled general-domain and/or mixed-domain text, such …","url":["https://arxiv.org/pdf/2004.03354"]}
-{"year":"2020","title":"Inexpensive Domain Adaptation of Pretrained Language Models: Case Studies on Biomedical NER and Covid-19 QA","authors":["N Poerner, U Waltinger, H Schütze"],"snippet":"… Pretrained Language Models (PTLMs) such as BERT (Devlin et al., 2019) have spearheaded ad- vances on many NLP tasks. Usually, PTLMs are pretrained on unlabeled general-domain and/or mixed-domain text, such …","url":["https://web.iiit.ac.in/~rizwan.ali/papers/828.pdf"]}
-{"year":"2020","title":"Infosys Machine Translation System for WMT20 Similar Language Translation Task","authors":["K Rathinasamy, A Singh, B Sivasambagupta… - Proceedings of WMT, 2020"],"snippet":"… data. 2.2.2 Synthetic data CommonCrawl n-grams raw monolingual files are processed1 to remove sentences with invalid characters, strip leading and trailing whitespaces, and remove duplicate sentences. 3 System Overview …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.52.pdf"]}
-{"year":"2020","title":"iNLTK: Natural Language Toolkit for Indic Languages","authors":["G Arora - arXiv preprint arXiv:2009.12534, 2020"],"snippet":"… iNLTK results were compared against results reported in (Kunchukuttan et al., 2020) for pre-trained embeddings released by the FastText project trained on Wikipedia (FT-W) (Bo- janowski et al., 2016), Wiki+CommonCrawl …","url":["https://arxiv.org/pdf/2009.12534"]}
-{"year":"2020","title":"INSET: Sentence Infilling with INter-SEntential Transformer","authors":["Y Huang, Y Zhang, O Elachqar, Y Cheng - Proceedings of the 58th Annual Meeting of …, 2020"],"snippet":"… For the effectiveness of human evaluation, we use the simplest strategy to mask sentences. The Recipe dataset is obtained from (https: //commoncrawl.org), where the metadata is formatted according to Schema.org (https:// schema.org/Recipe) …","url":["https://www.aclweb.org/anthology/2020.acl-main.226.pdf"]}
-{"year":"2020","title":"Integrating Geospatial Data and Social Media in Bidirectional Long-Short Term Memory Models to Capture Human Nature Interactions","authors":["A Larkin, P Hystad - The Computer Journal, 2020"],"snippet":"… language processing [32]. Tweet texts were transformed into word vector arrays using the Stanford GloVe (Global Vectors for Word Representation) Common Crawl dictionary (https://nlp.stanford.edu/projects/glove/). The GloVe …","url":["https://academic.oup.com/comjnl/advance-article-abstract/doi/10.1093/comjnl/bxaa094/5893915"]}
-{"year":"2020","title":"Intelligent phishing detection scheme using deep learning algorithms","authors":["MA Adebowale, KT Lwin, MA Hossain - Journal of Enterprise Information …, 2020"],"snippet":"… Half of the data set consisted of phishing sites from PhishTank, which is a site that is used as phishing URL depository, and half of the data set was comprised of legitimate sites from Common Crawl, a corpus of web crawl data …","url":["https://www.emerald.com/insight/content/doi/10.1108/JEIM-01-2020-0036/full/html"]}
-{"year":"2020","title":"Intermediate Training of BERT for Product Matching","authors":["R Peeters, C Bizer, G Glavaš - small"],"snippet":"… uct Corpus for Large-Scale Product Matching [26]. These datasets are derived from schema.org annotations from thousands of webshops extracted from the Common Crawl. Relying on schema.org annotations of product identifiers …","url":["http://data.dws.informatik.uni-mannheim.de/largescaleproductcorpus/data/v2/papers/DI2KG2020_Peeters.pdf"]}
-{"year":"2020","title":"Interpretability Analysis for Named Entity Recognition to Understand System Predictions and How They Can Improve","authors":["O Agarwal, Y Yang, BC Wallace, A Nenkova - arXiv preprint arXiv:2004.04564, 2020"],"snippet":"… representations are concatenated. We use 300 dimensional cased GloVe (Pennington et al., 2014) vectors trained on Common Crawl.2 We use the IO labeling scheme and evaluate the systems via micro-F1, at the token level. We use …","url":["https://arxiv.org/pdf/2004.04564"]}
-{"year":"2020","title":"Interpretable & Time-Budget-Constrained Contextualization for Re-Ranking","authors":["S Hofstätter, M Zlabinger, A Hanbury - arXiv preprint arXiv:2002.01854, 2020"],"snippet":"… The first section contains the traditional baselines; the second contains the neural re-ranking baselines; in the third section we report the results of our TK model with three 6 42B CommonCrawl lower-cased: https://nlp.stanford.edu/projects/glove/ Page 5 …","url":["https://arxiv.org/pdf/2002.01854"]}
-{"year":"2020","title":"Introduction to Cloud Computing and Amazon Web Services (AWS)","authors":["JM Patel - Getting Structured Data from the Internet, 2020"],"snippet":"… 5 examples. IAM and S3 sections are necessary for Chapters 6 and 7 since we will be using data compiled by a nonprofit called common crawl which is only publicly available on S3 through AWS open registry. You will have …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-6576-5_3"]}
-{"year":"2020","title":"Introduction to Common Crawl Datasets","authors":["JM Patel - Getting Structured Data from the Internet, 2020"],"snippet":"The Common Crawl Foundation (https://commoncrawl.org/) is a 501(c)(3) nonprofit involved in providing open access web crawl data going back to over eight years. They perform monthly web crawls which cover over 25 billion pages for each month. This …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-6576-5_6"]}
-{"year":"2020","title":"Introduction to Web Scraping","authors":["JM Patel - Getting Structured Data from the Internet, 2020"],"snippet":"… We will introduce natural language processing algorithms in Chapter 4, and we will put them into action in Chapters 6 and 7 on a Common Crawl dataset. The next step is loading the cleaned data from the preceding step into an appropriate database …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-6576-5_1"]}
-{"year":"2020","title":"Is Everything Fine, Grandma? Acoustic and Linguistic Modeling for Robust Elderly Speech Emotion Recognition","authors":["G Sogancıoglu, O Verkholyak, H Kaya, D Fedotov… - INTERSPEECH, Shanghai …, 2020","G Soğancıoğlu, O Verkholyak, H Kaya, D Fedotov… - arXiv preprint arXiv …, 2020"],"snippet":"… We use pre-trained 100-dimensional English and German word embeddings [23], which are trained on Common Crawl2, and finetune the pretrained model on our dataset … 1https://cloud.google.com/translate 2http://commoncrawl.org/ Page 3. cording to its POS …","url":["https://arxiv.org/pdf/2009.03432","https://indico2.conference4me.psnc.pl/event/35/contributions/3140/attachments/1218/1261/Wed-SS-1-4-12.pdf"]}
-{"year":"2020","title":"Is language modeling enough? Evaluating effective embedding combinations","authors":["R Schneider, T Oberhauser, P Grundmann, FA Gers… - 2020"],"snippet":"… 2.1. Universal Text Embeddings Recently, researchers explore universal text embeddings trained on extensive Web corpora, such as the Common Crawl6 (Mikolov et al., 2018; Radford et al., 2019), the billion … 5https …","url":["https://eprints.soton.ac.uk/438613/1/LREC20_LM_TM_27_1_.pdf"]}
-{"year":"2020","title":"Is MAP Decoding All You Need? The Inadequacy of the Mode in Neural Machine Translation","authors":["B Eikema, W Aziz - arXiv preprint arXiv:2005.10283, 2020"],"snippet":"… For English-Nepali we also use a translated version of the Penn Treebank4 and for English-Sinhala we additionally use Open Subtitles (Lison et al., 2018). We use a filtered crawl of Wikipedia and Common Crawl released in Guzmán et al …","url":["https://arxiv.org/pdf/2005.10283"]}
-{"year":"2020","title":"Is Wikipedia succeeding in reducing gender bias? Assessing changes in gender bias in Wikipedia using word embeddings","authors":["KG Schmahl, TJ Viering, S Makrodimitris, AN Jahfari… - Proceedings of the Fourth …, 2020"],"snippet":"… These categories have shown significant bias towards male or female words in embeddings from Google News corpora [Mikolov et al., 2013a], Google Books [Jones et al., 2020], as well as a 'Common Crawl' corpus [Caliskan et al., 2017] …","url":["https://www.aclweb.org/anthology/2020.nlpcss-1.11.pdf"]}
-{"year":"2020","title":"It's the Best Only When It Fits You Most: Finding Related Models for Serving Based on Dynamic Locality Sensitive Hashing","authors":["L Zhou, Z Wang, A Das, J Zou - arXiv preprint arXiv:2010.09474, 2020"],"snippet":"… BAIR CORD-19 LSUN Bedroom iNaturalist (iNat) 2017 ImageNet OpenImagesV4 Wikipedia 1 Billion Word Benchmark CommonCrawl Multillingual Wikipedia Natural Questions 3 15 3 3 8 10 9 7 2 5 58 3 5 2 5 2 CelebA HQ iMet Collection 2019 …","url":["https://arxiv.org/pdf/2010.09474"]}
-{"year":"2020","title":"Italian Transformers Under the Linguistic Lens","authors":["A Miaschip, G Sartim, D Brunato, F Dell'Orletta… - Proceedings of the Seventh …, 2020"],"snippet":"… For instance, we can notice that, for both the probing models, features related to the distribution of syntactic relations (SyntacticDep) are better predicted by GePpeTto, while GilBERTo and UmBERTo-Commoncrawl are the best …","url":["http://ceur-ws.org/Vol-2769/paper_56.pdf"]}
-{"year":"2020","title":"JASS: Japanese-specific Sequence to Sequence Pre-training for Neural Machine Translation","authors":["Z Mao, F Cromieres, R Dabre, H Song, S Kurohashi - arXiv preprint arXiv:2005.03361, 2020"],"snippet":"… Mono Ja Common Crawl 22M En News Crawl 22M Ru News Crawl 22M … 5.1.2. Monolingual data We use monolingual data containing 22M Japanese, 22M English and 22M Russian sentences randomly sub-sampled from Common Crawl dataset and News crawl4 dataset …","url":["https://arxiv.org/pdf/2005.03361"]}
-{"year":"2020","title":"Joint Multiclass Debiasing of Word Embeddings","authors":["R Popović, F Lemmerich, M Strohmaier - arXiv preprint arXiv:2003.11520, 2020"],"snippet":"… As in previous studies [7], evaluation was done on three pretrained Word Embedding models with vector dimension of 300: FastText2(English we- bcrawl and Wikipedia, 2 million words), GloVe3(Common Crawl, Wikipedia …","url":["https://arxiv.org/pdf/2003.11520"]}
-{"year":"2020","title":"Joint translation and unit conversion for end-to-end localization","authors":["G Dinu, P Mathur, M Federico, S Lauly, Y Al-Onaizan - arXiv preprint arXiv …, 2020","GDPMMFSL YaserAl-Onaizan, AWS Amazon"],"snippet":"… Europarl (Koehn, 2005) and news commentary data from WMT En→De shared task 2019 totalling 2.2 million sentences.2 Standard translation test sets do not have, however, enough examples of unit conversions and in fact corpora …","url":["https://arxiv.org/pdf/2004.05219","https://assets.amazon.science/b2/a7/e1ada6104b3587401b30ccc8637a/joint-translation-and-unit-conversion-for-end-to-end-localization.pdf"]}
-{"year":"2020","title":"KBPearl: a knowledge base population system supported by joint entity and relation linking","authors":["X Lin, H Li, H Xin, Z Li, L Chen - Proceedings of the VLDB Endowment, 2020"],"snippet":"Page 1. KBPearl: A Knowledge Base Population System Supported by Joint Entity and Relation Linking Xueling Lin, Haoyang Li, Hao Xin, Zijian Li, Lei Chen Department of Computer Science and Engineering The Hong Kong …","url":["https://dl.acm.org/doi/pdf/10.14778/3384345.3384352"]}
-{"year":"2020","title":"Keeping Models Consistent between Pretraining and Translation for Low-Resource Neural Machine Translation","authors":["W Zhang, X Li, Y Yang, R Dong, G Luo - Future Internet, 2020"],"snippet":"Recently, the pretraining of models has been successfully applied to unsupervised and semi-supervised neural machine translation. A cross-lingual language model uses a pretrained masked language model to initialize the …","url":["https://www.mdpi.com/1999-5903/12/12/215/pdf"]}
-{"year":"2020","title":"Kernel compositional embedding and its application in linguistic structured data classification","authors":["H Ganji, MM Ebadzadeh, S Khadivi - Knowledge-Based Systems, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0950705120300460"]}
-{"year":"2020","title":"Key Phrase Classification in Complex Assignments","authors":["M Ravikiran - arXiv preprint arXiv:2003.07019, 2020"],"snippet":"… Corpus and English Wikipedia used in BERT was found to be useful for training. The additional data included Common Crawl News dataset (76 GB), Web text corpus (38 GB) and Stories from Common Crawl (31 GB). This coupled …","url":["https://arxiv.org/pdf/2003.07019"]}
-{"year":"2020","title":"Keynote speaker","authors":["M Benjamin"],"snippet":"Skip to content …","url":["https://asling.org/tc42/"]}
-{"year":"2020","title":"Keyphrase Extraction as Sequence Labeling Using Contextualized Embeddings","authors":["D Sahrawat, D Mahata, H Zhang, M Kulkarni, A Sharma… - Advances in Information …, 2020"],"snippet":"… We also use 300 dimensional fixed embeddings from Glove [20], Word2Vec [19], and FastText [13] (common-crawl, wiki-news). We also compare the proposed architecture against four popular baselines …","url":["https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7148038/"]}
-{"year":"2020","title":"KGvec2go--Knowledge Graph Embeddings as a Service","authors":["J Portisch, M Hladik, H Paulheim - arXiv preprint arXiv:2003.05809, 2020"],"snippet":"… knowledge graphs. 4.3. WebIsALOD The WebIsA database (Seitner et al., 2016) is a data set which consists of hypernymy relations ex- tracted from the Common Crawl8, a downloadable copy of the Web. The extraction was …","url":["https://arxiv.org/pdf/2003.05809"]}
-{"year":"2020","title":"KIT's IWSLT 2020 SLT Translation System","authors":["NQ Pham, F Schneider, TN Nguyen, TL Ha, TS Nguyen… - Proceedings of the 17th …, 2020"],"snippet":"… Table 2: Text Training Data Dataset Sentences TED Talks (TED) 220K Europarl (EPPS) 2.2MK CommonCrawl 2.1M Rapid 1.21M ParaCrawl 25.1M OpenSubtitles 12.6M WikiTitle 423K Back-translated News 26M Page 2. 56 3 Simultaneous Speech Translation …","url":["https://www.aclweb.org/anthology/2020.iwslt-1.4.pdf"]}
-{"year":"2020","title":"KLEJ: Comprehensive Benchmark for Polish Language Understanding","authors":["P Rybak, R Mroczkowski, J Tracz, I Gawlik - arXiv preprint arXiv:2005.00630, 2020"],"snippet":"… word vectors. To evaluate their impact on KLEJ tasks, we initialize word embeddings with fastText (Bojanowski et al., 2016) trained on Common Crawl and Wikipedia for Polish language (Grave et al., 2018). 4.1.3 ELMo ELMo …","url":["https://arxiv.org/pdf/2005.00630"]}
-{"year":"2020","title":"KLUMSy@ KIPoS: Experiments on Part-of-Speech Tagging of Spoken Italian","authors":["T Proisl, G Lapesa"],"snippet":"… The PAISÀ corpus of Italian texts from the web (Lyding et al., 2014),5 the text of the Italian Wikimedia dumps,6 ie Wiki(pedia|books|news|versity|voyage), as ex- tracted by Wikipedia Extractor,7 and the Italian subset of OSCAR …","url":["http://ceur-ws.org/Vol-2765/paper140.pdf"]}
-{"year":"2020","title":"Knowledge Augmented Aspect Category Detection for Aspect-based Sentiment Analysis","authors":["K Martinen - 2019"],"snippet":"Page 1. MASTERTHESIS Knowledge Augmented Aspect Category Detection for Aspect-based Sentiment Analysis Kai Martinen 01.12.2019 University of Hamburg MIN-Faculty Department of Computer Science Language Technologies …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2019-ma-martinen.pdf"]}
-{"year":"2020","title":"Knowledge Efficient Deep Learning for Natural Language Processing","authors":["H Wang - arXiv preprint arXiv:2008.12878, 2020"],"snippet":"Page 1. Knowledge Efficient Deep Learning for Natural Language Processing by Hai Wang A thesis submitted in partial fulfillment for the degree of Doctor of Philosophy in Computer Science at the Toyota Technological Institute …","url":["https://arxiv.org/pdf/2008.12878"]}
-{"year":"2020","title":"Knowledge Graphs Evolution and Preservation--A Technical Report from ISWS 2019","authors":["N Abbas, K Alghamdi, M Alinam, F Alloatti, G Amaral… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Knowledge Graphs Evolution and Preservation A Technical Report from ISWS 2019 December 23, 2020 Bertinoro, Italy arXiv:2012.11936v1 [cs.AI] 22 Dec 2020 Page 2. Authors Main Editors Valentina Anita Carriero …","url":["https://arxiv.org/pdf/2012.11936"]}
-{"year":"2020","title":"KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding","authors":["J Ham, YJ Choe, K Park, I Choi, H Soh - arXiv preprint arXiv:2004.03289, 2020"],"snippet":"… 20 days). We also use XLM-R (Conneau and Lample, 2019), a publicly available cross-lingual language model that was pre-trained on 2.5TB of Common Crawl corpora in 100 languages including Korean (54GB). Note that …","url":["https://arxiv.org/pdf/2004.03289"]}
-{"year":"2020","title":"LAMBERT: Layout-Aware language Modeling using BERT for information extraction","authors":["Ł Garncarek, R Powalski, T Stanisławek, B Topolski… - arXiv preprint arXiv …, 2020"],"snippet":"… Dataset pages EDGAR 119 088 RVL-CDIP 90 054 Common Crawl 389 469 cTDaR 782 private 151 074 Total 750 467 Table 1: Sizes of training datasets … Common Crawl PDFs This is a dataset produced by downloading PDF …","url":["https://arxiv.org/pdf/2002.08087"]}
-{"year":"2020","title":"Language model domain adaptation for automatic speech recognition","authors":["A Prasad, P Motlicek, A Nanchen - 2020"],"snippet":"… By exploring and exploiting various datasets like Common Crawl, Europarl, news and TEDLIUM and by experimenting different techniques in training a model, we achieve the goal of adapting a general purpose LM to a domain like talks …","url":["https://infoscience.epfl.ch/record/275402"]}
-{"year":"2020","title":"Language Models and Word Sense Disambiguation: An Overview and Analysis","authors":["D Loureiro, K Rezaee, MT Pilehvar… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Language Models and Word Sense Disambiguation: An Overview and Analysis Daniel Loureiro∗ LIAAD - INESC TEC Department of Computer Science - FCUP University of Porto, Portugal Kiamehr Rezaee∗ Department …","url":["https://arxiv.org/pdf/2008.11608"]}
-{"year":"2020","title":"Language Models are Few-Shot Learners","authors":["TB Brown, B Mann, N Ryder, M Subbiah, J Kaplan… - arXiv preprint arXiv …, 2020"],"snippet":"… of our held-out validation set as an accurate measure of overfitting, and (3) we also added known high-quality reference corpora to the training mix to augment CommonCrawl and increase its diversity. Details of the first two …","url":["https://arxiv.org/pdf/2005.14165"]}
-{"year":"2020","title":"Language Models are Open Knowledge Graphs","authors":["C Wang, X Liu, D Song - arXiv preprint arXiv:2010.11967, 2020"],"snippet":"… In fact, these pre-trained LMs automatically acquire factual knowledge from large-scale corpora (eg, BookCorpus (Zhu et al., 2015), Common Crawl (Brown et al., 2020)) via pre-training. The learned knowledge in pre-trained LMs is the key to the current success …","url":["https://arxiv.org/pdf/2010.11967"]}
-{"year":"2020","title":"Language Models not just for Pre-training: Fast Online Neural Noisy Channel Modeling","authors":["S Bhosale, K Yee, S Edunov, M Auli - arXiv preprint arXiv:2011.07164, 2020"],"snippet":"… Big architecture. The model is trained on de-duplicated Romanian CommonCrawl data consisting of 623M sentences or 21.7B words after normalization and tokenization (Conneau et al., 2019; Wenzek et al., 2020). The German …","url":["https://arxiv.org/pdf/2011.07164"]}
-{"year":"2020","title":"Language-agnostic BERT Sentence Embedding","authors":["F Feng, Y Yang, D Cer, N Arivazhagan, W Wang - arXiv preprint arXiv:2007.01852, 2020"],"snippet":"… The sentences are filtered using a sentence 1https://commoncrawl.org/ 2https://www.wikipedia.org/ 3Long lines are usually JavaScript or attempts at SEO … Finally, we pretrain on common crawl which is much larger, albeit …","url":["https://arxiv.org/pdf/2007.01852"]}
-{"year":"2020","title":"Large Scale Knowledge Graph Based Synthetic Corpus Generation for Knowledge-Enhanced Language Model Pre-training","authors":["O Agarwal, H Ge, S Shakeri, R Al-Rfou - arXiv preprint arXiv:2010.12688, 2020"],"snippet":"… 3We use only one annotator at the moment but are expanding this evaluation to multiple annotators. Page 7. such as Wikipedia or common crawl. KGs are a rich source of factual information that can serve as additional succint informatopm …","url":["https://arxiv.org/pdf/2010.12688"]}
-{"year":"2020","title":"Large-Scale Analysis of HTTP Response Headers","authors":["C Leyers, J Paytosh, N Worthy - 2020"],"snippet":"… The data come from the Common Crawl's monthly web crawls that collect responses from what we can consider to be the entire internet … The data come from the Common Crawl's monthly web crawls that collect responses …","url":["https://digitalcommons.winthrop.edu/source/SOURCE_2020/allpresentationsandperformances/101/"]}
-{"year":"2020","title":"Latte-Mix: Measuring Sentence Semantic Similarity with Latent Categorical Mixtures","authors":["M Li, H Bai, L Tan, K Xiong, J Lin - arXiv preprint arXiv:2010.11351, 2020"],"snippet":"Page 1. Latte-Mix: Measuring Sentence Semantic Similarity with Latent Categorical Mixtures Minghan Li*1, 2 , He Bai1, 3 , Luchen Tan1 , Kun Xiong1 , Ming Li1, 3 , Jimmy Lin1, 3 1RSVP.ai, 2University of Toronto, 3David R. Cheriton …","url":["https://arxiv.org/pdf/2010.11351"]}
-{"year":"2020","title":"LEAPME: Learning-based Property Matching with Embeddings","authors":["D Ayala Hernández, IC Hernández Salmerón… - ArXiv. org, arXiv …, 2020","D Ayala, I Hernández, D Ruiz, E Rahm - arXiv preprint arXiv:2010.01951, 2020"],"snippet":"… To compute embeddings, we use the pre-trained GloVe approach [43]1, specifically for the uncased Common Crawl corpus that includes 300-dimensional vectors for 1.9 million words, promising a good coverage …","url":["https://arxiv.org/pdf/2010.01951","https://idus.us.es/bitstream/handle/11441/105071/1/LEAPME%20Learning%20based%20Property%20Matching%20with%20Embeddings.pdf?sequence=1"]}
-{"year":"2020","title":"Learning Accurate Integer Transformer Machine-Translation Models","authors":["E Wu - arXiv preprint arXiv:2001.00926, 2020"],"snippet":"… sor2Tensor v1.12 English-to-German translation task (translate_ende_wmt32k_packed). This dataset has 4.6 million sentence pairs drawn from three WMT18 [Bojar et al., 2018a] parallel corpora: News Commentary V13, Europarl V7, and Common Crawl …","url":["https://arxiv.org/pdf/2001.00926"]}
-{"year":"2020","title":"Learning and Evaluating Emotion Lexicons for 91 Languages","authors":["S Buechel, S Rücker, U Hahn - arXiv preprint arXiv:2005.05672, 2020"],"snippet":"… We use the fastText embedding models from Grave et al. (2018) trained for 157 languages on the respective WIKIPEDIA and the respective part of COMMONCRAWL. These resources not only greatly facilitate our work …","url":["https://arxiv.org/pdf/2005.05672"]}
-{"year":"2020","title":"Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games","authors":["A Adhikari, X Yuan, MA Côté, M Zelinka, MA Rondeau… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Learning Dynamic Knowledge Graphs to Generalize on Text-Based Games Ashutosh Adhikari * 1 Xingdi Yuan * 2 Marc-Alexandre Côté * 2 Mikuláš Zelinka 3 Marc-Antoine Rondeau 2 Romain Laroche 2 Pascal Poupart …","url":["https://arxiv.org/pdf/2002.09127"]}
-{"year":"2020","title":"Learning Engineering Properties with Bag-of-Tricks. For the Automated Evaluation of a Piping Design","authors":["WC Tan, KH Chua, CB Yan, IM Chen - 2020 IEEE 16th International Conference on …, 2020"],"snippet":"… and T. Mikolov, “Learning word vectors for 157 languages,” in Proceedings of the International Conference on Language Resources and Evaluation (LREC 2018), 2018. [28] [Online]. Available: https://commoncrawl.org/ 1280","url":["https://ieeexplore.ieee.org/abstract/document/9217001/"]}
-{"year":"2020","title":"LEARNING FROM MULTIMODAL WEB DATA","authors":["JM Hessel - 2020"],"snippet":"… (2018); Roemmele et al. (2011); De Marneffe et al. (2019); Clark et al. (2019). 7https://commoncrawl.org/ 5 Page 22. model; they achieve high performance on several video understanding tasks (eg, retrieval), and …","url":["https://jmhessel.com/files/2020/phd_thesis.pdf"]}
-{"year":"2020","title":"Learning Geometric Word Meta-Embeddings","authors":["P Jawanpuria, NTV Dev, A Kunchukuttan, B Mishra - arXiv preprint arXiv:2004.09219, 2020"],"snippet":"… GloVe (Pennington et al., 2014): has 1 917 494 word embeddings trained on 42B tokens of web data from the common crawl. • fastText (Bojanowski et al., 2017): has 2 000 000 word embeddings trained on common crawl …","url":["https://arxiv.org/pdf/2004.09219"]}
-{"year":"2020","title":"Learning hierarchical relationships for object-goal navigation","authors":["Y Qiu, A Pal, HI Christensen"],"snippet":"Page 1. Learning hierarchical relationships for object-goal navigation Yiding Qiu ∗ UC San Diego yiqiu@eng.ucsd.edu Anwesan Pal ∗ UC San Diego a2pal@eng.ucsd.edu Henrik I. Christensen UC San Diego hichristensen@eng.ucsd.edu …","url":["https://www.researchgate.net/profile/Anwesan_Pal/publication/346061932_Learning_hierarchical_relationships_for_object-goal_navigation/links/5fb9b05fa6fdcc6cc659d1b2/Learning-hierarchical-relationships-for-object-goal-navigation.pdf"]}
-{"year":"2020","title":"Learning to Evaluate Translation Beyond English: BLEURT Submissions to the WMT Metrics 2020 Shared Task","authors":["T Sellam, A Pu, HW Chung, S Gehrmann, Q Tan… - arXiv preprint arXiv …, 2020"],"snippet":"… Details of MBERT-WMT pre-training We trained MBERT-WMT model with an MLM loss (Devlin et al., 2019), using a combination of public datasets: Wikipedia, the WMT 2019 News Crawl (Barrault et al.), the C4 variant of Com …","url":["https://arxiv.org/pdf/2010.04297"]}
-{"year":"2020","title":"Learning to Segment Actions from Observation and Narration","authors":["D Fried, JB Alayrac, P Blunsom, C Dyer, S Clark… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Learning to Segment Actions from Observation and Narration Daniel Fried‡ Jean-Baptiste Alayrac† Phil Blunsom† Chris Dyer† Stephen Clark† Aida Nematzadeh† †DeepMind, London, UK ‡Computer Science Division, UC Berkeley …","url":["https://arxiv.org/pdf/2005.03684"]}
-{"year":"2020","title":"Learning to summarize from human feedback","authors":["N Stiennon, L Ouyang, J Wu, DM Ziegler, R Lowe… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Learning to summarize from human feedback Nisan Stiennon∗ Long Ouyang∗ Jeff Wu∗ Daniel M. Ziegler∗ Ryan Lowe∗ Chelsea Voss∗ Alec Radford Dario Amodei Paul Christiano∗ OpenAI Abstract As language …","url":["https://arxiv.org/pdf/2009.01325"]}
-{"year":"2020","title":"Learning unbiased zero-shot semantic segmentation networks via transductive transfer","authors":["H Liu, Y Wang, J Zhao, G Yang, F Lv - arXiv preprint arXiv:2007.00515, 2020"],"snippet":"… IV. EXPERIMENTS Following [7], we use the concatenation of two different word vectors, ie word2vec trained on Google News [12] and fastText trained on Common Crawl [12], to construct the semantic space shared by source and target classes …","url":["https://arxiv.org/pdf/2007.00515"]}
-{"year":"2020","title":"Learning User Representations for Open Vocabulary Image Hashtag Prediction","authors":["T Durand - Proceedings of the IEEE/CVF Conference on Computer …, 2020"],"snippet":"… We train our model using ADAM [26] during 20 epochs with a start learning rate 5e-5. We use ResNet-50 [22] as the ConvNet and GloVe embeddings [34] as pre-trained word em- beddings. GloVe was trained on Common …","url":["http://openaccess.thecvf.com/content_CVPR_2020/papers/Durand_Learning_User_Representations_for_Open_Vocabulary_Image_Hashtag_Prediction_CVPR_2020_paper.pdf"]}
-{"year":"2020","title":"Learning Word and Sub-word Vectors for Amharic (Less Resourced Language)","authors":["A Eshetu, G Teshome, T Abebe"],"snippet":"… The large text collection from Wikipedia and common crawl are commonly used data source to train and learn word vectors (Al-Rfou et al., 2013; Bojanowski et al … (2014) released GloVe models trained on Wikipedia …","url":["https://www.academia.edu/download/64390049/39IJAERS-08202035-Learning.pdf"]}
-{"year":"2020","title":"Leveraging ParsBERT and Pretrained mT5 for Persian Abstractive Text Summarization","authors":["M Farahani, M Gharachorloo, M Manthouri - arXiv preprint arXiv:2012.11204, 2020"],"snippet":"… T5, on the other hand, is a unified Seq2Seq framework that employs Text-to- Text format to address NLP text-based problems. A multilingual variation of the T5 model is called mT5 [16] that covers 101 different …","url":["https://arxiv.org/pdf/2012.11204"]}
-{"year":"2020","title":"Leveraging Structured Metadata for Improving Question Answering on the Web","authors":["X Du, A Hassan, A Fourney, R Sim, P Bennett… - … of the 1st Conference of the …, 2020"],"snippet":"… website content. The Web Data Commons project (Mühleisen and Bizer, 2012) estimates that 0.9 billion HTML pages out of the 2.5 billion pages (37.1%) in the Common Crawl web corpus1 contain structured metadata. Figure …","url":["https://www.aclweb.org/anthology/2020.aacl-main.55.pdf"]}
-{"year":"2020","title":"LIG-Health at Adhoc and Spoken IR Consumer Health Search: expanding queries using UMLS and FastText.","authors":["P Mulhem, GG Saez, A Mannion, D Schwab, J Frej - Conference and Labs of the …, 2020"],"snippet":"… The FastText embedding vector of a word is the sum of the vectors of its component ngrams. We used the pre-trained word vectors for English language, trained on Common Crawl and Wikipedia using FastText. The features of the model used are as follows; …","url":["http://www.dei.unipd.it/~ferro/CLEF-WN-Drafts/CLEF2020/paper_129.pdf"]}
-{"year":"2020","title":"LIMSI@ WMT 2020","authors":["SA Rauf, JC Rosales, I Paris, PM Quang, S Paris…"],"snippet":"… Domain Corpus sents. words words (en) (de) web Paracrawl 50,875 978 919 economy Tilde EESC 2,858 61 58 news Commoncrawl 2,399 51 47 Tilde rapid 940 20 19 News commentary 361 8 8 tourism Tilde tourism 7 …","url":["http://statmt.org/wmt20/pdf/2020.wmt-1.86.pdf"]}
-{"year":"2020","title":"Linguistic Structure Guided Context Modeling for Referring Image Segmentation","authors":["F Zhang, J Han","T Hui, S Liu, S Huang, G Li, S Yu, F Zhang, J Han"],"snippet":"… rate. CNN is fixed during training. We use batch size 1 and stop training after 700K iterations. GloVe word embeddings [30] pretrained on Common Crawl with 840B tokens are used to replace randomly initialized ones. For fair …","url":["http://colalab.org/media/paper/Linguistic_Structure_Guided_Context_Modeling_for_Referring_Image_Segmentation.pdf","https://link.springer.com/content/pdf/10.1007/978-3-030-58607-2_4.pdf"]}
-{"year":"2020","title":"Linguistically-aware Attention for Reducing the Semantic-Gap in Vision-Language Tasks","authors":["G KV, A Nambiar, KS Srinivas, A Mittal - arXiv preprint arXiv:2008.08012, 2020"],"snippet":"… The pre-trained word-to-vector networks such as Glove [29] and Bert [30] are inexpensive and rich in making linguistic correlations (since they are already trained on a large textual corpus such as Common Crawl and Wikipedia2014) …","url":["https://arxiv.org/pdf/2008.08012"]}
-{"year":"2020","title":"LNMap: Departures from Isomorphic Assumption in Bilingual Lexicon Induction Through Non-Linear Mapping in Latent Space","authors":["T Mohiuddin, MS Bari, S Joty - arXiv preprint arXiv:2004.13889, 2020"],"snippet":"… English, Italian, and German em- beddings were trained on WacKy crawling corpora using CBOW (Mikolov et al., 2013b), while Spanish and Finnish embeddings were trained on WMT News Crawl and Common Crawl, respectively. 4.2 Baseline Methods …","url":["https://arxiv.org/pdf/2004.13889"]}
-{"year":"2020","title":"Localizing Open-Ontology QA Semantic Parsers in a Day Using Machine Translation","authors":["M Moradshahi, G Campagna, SJ Semnani, S Xu… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Localizing Open-Ontology QA Semantic Parsers in a Day Using Machine Translation Mehrad Moradshahi Giovanni Campagna Sina J. Semnani Silei Xu Monica S. Lam Computer Science Department Stanford University …","url":["https://arxiv.org/pdf/2010.05106"]}
-{"year":"2020","title":"Localizing Q&A Semantic Parsers for Any Language in a Day","authors":["M Moradshahi, G Campagna, S Semnani, S Xu, M Lam - Proceedings of the 2020 …, 2020"],"snippet":"Page 1. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pages 5970–5983, November 16–20, 2020. c 2020 Association for Computational Linguistics 5970 Localizing Open-Ontology …","url":["https://www.aclweb.org/anthology/2020.emnlp-main.481.pdf"]}
-{"year":"2020","title":"Locally Constructing Product Taxonomies from Scratch Using Representation Learning","authors":["M Kejriwal, RK Selvam, CC Ni, N Torzec"],"snippet":"… The WDC schema.org project, which relies on the webpages in the Common Crawl, is able to automatically extract schema.org data from webpages due to its unique syntax and make it available as a dataset in Resource Description Framework (RDF) …","url":["https://web.ntpu.edu.tw/~myday/doc/ASONAM2020/ASONAM2020_Proceedings/pdf/papers/080_098_507.pdf"]}
-{"year":"2020","title":"LOREM: Language-consistent Open Relation Extraction from Unstructured Text","authors":["T Harting, S Mesbah, C Lofi"],"snippet":"… Since these sentences are automatically tagged, we do expect a higher noise level than in the manually tagged test sets. For the language-individual model, we use FastText word em- beddings [11] which are trained on Common Crawl and Wikipedia dataset …","url":["https://pure.tudelft.nl/portal/files/69221720/2020_WWW_LOREM.pdf"]}
-{"year":"2020","title":"Lost in Embedding Space: Explaining Cross-Lingual Task Performance with Eigenvalue Divergence","authors":["H Dubossarsky, I Vulić, R Reichart, A Korhonen - arXiv preprint arXiv:2001.11136, 2020"],"snippet":"… We prefer Wikipedia as the main embedding training corpus over the larger Common Crawl corpus, because the text in Wikipedia is much cleaner or even hand-curated, and adheres to the rules of standard language (Grave et al., 2018) …","url":["https://arxiv.org/pdf/2001.11136"]}
-{"year":"2020","title":"Low-Resource Knowledge-Grounded Dialogue Generation","authors":["X Zhao, W Wu, C Tao, C Xu, D Zhao, R Yan - arXiv preprint arXiv:2002.10348, 2020"],"snippet":"Page 1. Published as a conference paper at ICLR 2020 LOW-RESOURCE KNOWLEDGE-GROUNDED DIALOGUE GENERATION Xueliang Zhao1,2, Wei Wu3, Chongyang Tao1, Can Xu3, Dongyan Zhao1,2, Rui Yan1,2,4∗ 1Wangxuan …","url":["https://arxiv.org/pdf/2002.10348"]}
-{"year":"2020","title":"Low-Resource Text Classification via Cross-lingual Language Model Fine-tuning","authors":["X Li, Z Li, J Sheng, W Slamu"],"snippet":"… XLM - R shows the possibility of training one model for many languages while not sacrificing per-language performance. It is trained on 2.5TB of CommonCrawl data, in 100 languages and uses a large vocabulary size of CCL 2020 …","url":["http://www.cips-cl.org/static/anthology/CCL-2020/CCL-20-092.pdf"]}
-{"year":"2020","title":"LREC 2020 Workshop Language Resources and Evaluation Conference 11–16 May 2020","authors":["M Kupietz, H Lungen, I Pisetta"],"snippet":"Page 1. LREC 2020 Workshop Language Resources and Evaluation Conference 11–16 May 2020 8th Workshop on Challenges in the Management of Large Corpora (CMLC-8) PROCEEDINGS Editors: Piotr Ba´nski, Adrien Barbaresi, Simon Clematide …","url":["https://ids-pub.bsz-bw.de/files/9811/Banski_Barbaresi_Clematide_Kupietz_Luengen_Pisetta_Proceedings_LREC_2020.pdf"]}
-{"year":"2020","title":"Machine Bias and Fundamental Rights","authors":["D Amilevičius - Smart Technologies and Fundamental Rights, 2020"],"snippet":"Jump to Content Jump to Main Navigation. English; 中文; français; Deutsch. Access via: Google Googlebot - Web Crawler SEO. Login to my Brill account Create Brill Account. Publications. Subjects. African Studies American Studies …","url":["https://brill.com/view/book/edcoll/9789004437876/BP000019.xml"]}
-{"year":"2020","title":"Machine Translation for English–Inuktitut with Segmentation, Data Acquisition and Pre-Training","authors":["C Roest, L Edman, G Minnema, K Kelly, J Spenader… - Proceedings of the Fifth …, 2020"],"snippet":"… 2), we train XLM models with the News Crawl data for English and Common Crawl data for Inuktitut, as specified in Table 2. We also use Hansards and Newsdevtrain oversampled 5 times for parallel data. We try both tagging …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.29.pdf"]}
-{"year":"2020","title":"Machine Translation in Natural Language Processing by Implementing Artificial Neural Network Modelling Techniques: An Analysis","authors":["FA Khan, A Abubakar - International Journal on Perceptive and Cognitive …, 2020"],"snippet":"… The experiment for the proposed model has followed with BERT, to BookCorpus [35] and Wikipedia for English as an initializing point for pretraining. Similarly, other text includes, Giga5 (16Gb) ClueWeb 2012-B and Common Crawl respectively …","url":["https://journals.iium.edu.my/kict/index.php/IJPCC/article/download/134/96"]}
-{"year":"2020","title":"Machine Translation Reference-less Evaluation using YiSi-2 with Bilingual Mappings of Massive Multilingual Language Model","authors":["C Lo, S Larkin - Proceedings of the Fifth Conference on Machine …, 2020"],"snippet":"… The differencesbetweenXLM-RandBERTare1)XLM-Ris trained on the CommonCrawl corpus which is significantly larger than the Wikipedia training data used by BERT; 2) instead of a uniform data sampling rate used in BERT …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.100.pdf"]}
-{"year":"2020","title":"Machine Translation System Selection from Bandit Feedback","authors":["J Naradowsky, X Zhang, K Duh - arXiv preprint arXiv:2002.09646, 2020"],"snippet":"… Specifically, we in- clude OpenSubtitles2018 [Lison and Tiedemann, 2016] and WMT 2017 [Bojar et al., 2017], which contains data from eg parliamentary proceedings (Europarl, UN), political/economic news, and web-crawled parallel corpus (Common Crawl) …","url":["https://arxiv.org/pdf/2002.09646"]}
-{"year":"2020","title":"MAD-X: An Adapter-based Framework for Multi-task Cross-lingual Transfer","authors":["J Pfeiffer, I Vulić, I Gurevych, S Ruder - arXiv preprint arXiv:2005.00052, 2020"],"snippet":"… It is a Transformer-based model pretrained for one hundred languages on large cleaned Common Crawl corpora (Wenzek et al., 2019). For efficiency purposes, we use the XLM-R Base configuration as the basis for all of our experiments …","url":["https://arxiv.org/pdf/2005.00052"]}
-{"year":"2020","title":"Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation","authors":["N Reimers, I Gurevych - arXiv preprint arXiv:2004.09813, 2020"],"snippet":"Page 1. Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation Nils Reimers and Iryna Gurevych Ubiquitous Knowledge Processing Lab (UKP-TUDA) Department of Computer Science …","url":["https://arxiv.org/pdf/2004.09813"]}
-{"year":"2020","title":"MantisTable SE: an Efficient Approach for the Semantic Table Interpretation","authors":["M Cremaschi, R Avogadro, A Barazzetti, D Chieregato - Semantic Web Challenge on …, 2020"],"snippet":"… Web Tables: The WebTables system [1] extracts 14.1 billion HTML tables and finds 154 million are high-quality tables (1.1%); – Web Tables: Lehmberg et al. [5] extract 233 million content tables from Common Crawl 2015 (2.25 …","url":["http://ceur-ws.org/Vol-2775/paper8.pdf"]}
-{"year":"2020","title":"Mapping crime descriptions to law articles using deep learning","authors":["M Vink, N Netten, MS Bargh, S van den Braak… - Proceedings of the 13th …, 2020"],"snippet":"… This is a popular word embedding created by Facebook and available in many languages. The FastText embeddings are trained on Wikipedia texts and the data from the common crawl project. The word embeddings have a vector size of 300 …","url":["https://dl.acm.org/doi/abs/10.1145/3428502.3428507"]}
-{"year":"2020","title":"Mapping Languages: The Corpus of Global Language Use","authors":["J Dunn"],"snippet":"… language) and 156 countries (again with over 1 million words from each country), all distilled from Common Crawl web data … region: (i) the number of sites indexed by the Common Crawl; (ii) the population's degree of access …","url":["https://publicdata.canterbury.ac.nz/Research/Geocorpus/Documentation/!Paper.Corpus_of_Global_Language_Use.pdf"]}
-{"year":"2020","title":"Mapping the market for remanufacturing: An application of “Big Data” analytics","authors":["JQF Netoa, M Dutordoira - International Journal of Production Economics, 2020"],"snippet":"… The vectors are created with Global Vectors for Word Representation (GloVe), one of the most well-known word embedding methods (Pennington et al., 2014), and are based on a data set obtained from Common Crawl, a nonprofit …","url":["https://www.sciencedirect.com/science/article/pii/S092552732030181X"]}
-{"year":"2020","title":"MASK: A flexible framework to facilitate de-identification of clinical texts","authors":["N Milosevic, G Kalappa, H Dadafarin, M Azimaee… - arXiv preprint arXiv …, 2020"],"snippet":"… The first of these ap- proaches, used GLoVe (Global Vector) word embeddings [14]. We used GLoVe embeddings trained on common crawl data containing 840 billion tokens, 2.2 million unique tokens in vocabulary, and 300dimensional vectors …","url":["https://arxiv.org/pdf/2005.11687"]}
-{"year":"2020","title":"Masked ELMo: An evolution of ELMo towards fully contextual RNN language models","authors":["G Senay, E Salin - arXiv preprint arXiv:2010.04302, 2020"],"snippet":"… It should be noted that ELMo 5.5B is trained on a larger corpus than ELMo and Masked ELMo (Wikipedia: 1.9B and the common crawl from WMT 2008-2012: 3.6B). Moreover, a BERT baseline (BERT*) trained on the same …","url":["https://arxiv.org/pdf/2010.04302"]}
-{"year":"2020","title":"Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of Yorùbá and Twi","authors":["J Alabi, K Amponsah-Kaakyire, D Adelani… - Proceedings of The 12th …, 2020"],"snippet":"… The resource par excellence is Wikipedia2, an online encyclopedia currently available in 307 languages3. Other initiatives such as Common Crawl4 or the Jehovahs Witnesses site5 are also repositories for multilingual …","url":["https://www.aclweb.org/anthology/2020.lrec-1.335.pdf"]}
-{"year":"2020","title":"Massively Multilingual Document Alignment with Cross-lingual Sentence-Mover's Distance","authors":["A El-Kishky, F Guzmán - arXiv preprint arXiv:2002.00761, 2020"],"snippet":"… selected for evaluation. Baseline Methods. For comparison, we implemented two existing and intuitive document scoring baselines previously evaluated on this URL-Aligned CommonCrawl dataset [11]. The first method dubbed …","url":["https://arxiv.org/pdf/2002.00761"]}
-{"year":"2020","title":"Master Thesis: Developing a Cross-Lingual Named Entity Recognition Model","authors":["J Podolak, P Zeinert - 2020"],"snippet":"Page 1. Master Thesis: Developing a Cross-Lingual Named Entity Recognition Model Jowita Podolak1, Philine Zeinert2 1jopo@itu.dk 2phze@itu.dk June 1, 2020 Course Code: KISPECI1SE Page 2. Abstract To build a Cross …","url":["https://www.derczynski.com/itu/docs/xling-ner_jopo_phze.pdf"]}
-{"year":"2020","title":"Matching Job Applicants to Free Text Job Ads Using Semantic Networks and Natural Language Inference","authors":["A Thun - 2020"],"snippet":"Page 1. IN DEGREE PROJECT COMPUTER SCIENCE AND ENGINEERING, SECOND CYCLE, 30 CREDITS , STOCKHOLM SWEDEN 2020 Matching Job Applicants to Free Text Job Ads Using Semantic Networks and Natural Language Inference ANTON THUN …","url":["https://www.diva-portal.org/smash/get/diva2:1467916/FULLTEXT01.pdf"]}
-{"year":"2020","title":"MDD@ AMI: Vanilla Classifiers for Misogyny Identification","authors":["S El Abassi, S Nisioi - Proceedings of Sixth Evaluation Campaign of Natural …, 2020"],"snippet":"… CBOW embeddings pre-trained on Wikipedia and OSCAR (Common Crawl)3. The second run is trained on English glove em- beddings that surprisingly contain the representation of more than half of our Italian …","url":["http://ceur-ws.org/Vol-2765/paper149.pdf"]}
-{"year":"2020","title":"MEASURING DIVERGENT THINKING ORIGINALITY WITH HUMAN RATERS AND TEXT-MINING MODELS: A PSYCHOMETRIC COMPARISON OF METHODS","authors":["D Dumasa, P Organisciaka, M Dohertyb"],"snippet":"Page 1. Running Head: MEASURING ORIGINALITY 1 MEASURING DIVERGENT THINKING ORIGINALITY WITH HUMAN RATERS AND TEXT-MINING MODELS: A PSYCHOMETRIC COMPARISON OF METHODS …","url":["https://www.researchgate.net/profile/Denis_Dumas/publication/339364072_Measuring_Divergent_Thinking_Originality_with_Human_Raters_and_Text-Mining_Models_A_Psychometric_Comparison_of_Methods/links/5e4d686892851c7f7f46b607/Measuring-Divergent-Thinking-Originality-with-Human-Raters-and-Text-Mining-Models-A-Psychometric-Comparison-of-Methods.pdf"]}
-{"year":"2020","title":"Measuring prominence of scientific work in online news as a proxy for impact","authors":["J Ravenscroft, A Clare, M Liakata - arXiv preprint arXiv:2007.14454, 2020"],"snippet":"… In our task we employ pre-trained GloVe4 feature embeddings trained on the Common Crawl dataset5, a multi-petabyte archive of content scraped from the world wide web containing 42 billion tokens and a vocabulary 1.9 million words …","url":["https://arxiv.org/pdf/2007.14454"]}
-{"year":"2020","title":"Media-Analytics. org: A Resource to Research Language Usage by News Media Outlets","authors":["D Rozado - ITM Web of Conferences, 2020"],"snippet":"… news media outlets. News articles textual content are available in outlet-specific domains and Internet cache repositories such as the Internet Archive Wayback Machine, Google Cache and Common Crawl. Articles' headlines …","url":["https://www.itm-conferences.org/articles/itmconf/pdf/2020/03/itmconf_ictessh2020_03004.pdf"]}
-{"year":"2020","title":"Membership Inference Attacks on Sequence-to-Sequence Models: Is My Data In Your Machine Translation System?","authors":["S Hisamoto, M Post, K Duh"],"snippet":"… Page 3. CommonCrawl subcorpus … We now describe how Carol prepares the data for Alice and Bob. First, Carol se- lects 4 subcorpora for the training data of Al- ice, namely CommonCrawl, Europarl v7, News Commentary v13, and Rapid 2016 …","url":["http://www.cs.jhu.edu/~kevinduh/t/membership-inference.pdf"]}
-{"year":"2020","title":"Meta-Learning for Few-Shot NMT Adaptation","authors":["A Sharaf, H Hassan, H Daumé III - arXiv preprint arXiv:2004.02745, 2020"],"snippet":"… In all cases, the baseline machine translation system is a neural English to German (En-De) transformer model (Vaswani et al., 2017), initially trained on 5.2M sentences filtered from the the standard parallel data …","url":["https://arxiv.org/pdf/2004.02745"]}
-{"year":"2020","title":"Method and apparatus for improved automatic subtitle segmentation using an artificial neural network model","authors":["P WILKEN, E Matusov - US Patent App. 16/876,780, 2020"],"snippet":"… These data included all other publicly available training data, including ParaCrawl, CommonCrawl, EUbookshop, JRCAcquis, EMEA, and other corpora from the OPUS collection … This may be done to avoid oversampling …","url":["https://patentimages.storage.googleapis.com/d1/56/2b/7b6e0c087c851d/US20200364402A1.pdf"]}
-{"year":"2020","title":"Method and system for interactive keyword optimization for opaque search engines","authors":["R Puzis, A ELYASHAR, M REUBEN - US Patent App. 16/840,538, 2020"],"snippet":"… 2018]. The model was trained on Common Crawl (http://commoncrawl.org/) and Wikipedia (https://www.wikipedia.org/) using fastText library (https://fasttext.cc/). For the distance measure, the simple Euclidean distance was used …","url":["https://patents.google.com/patent/US20200327120A1/en"]}
-{"year":"2020","title":"Method for automatically generating a wrapper for extracting web data, and a computer system","authors":["G Gottlob, E SALLINGER, R FAYZRAKHMANOV… - US Patent App. 16/630,485, 2020"],"snippet":"US20200167393A1 - Method for automatically generating a wrapper for extracting web data, and a computer system - Google Patents. Method for automatically generating a wrapper for extracting web data, and a computer system. Download PDF Info …","url":["https://patents.google.com/patent/US20200167393A1/en"]}
-{"year":"2020","title":"Methods for morphology learning in low (er)-resource scenarios","authors":["T Bergmanis - 2020"],"snippet":"Page 1. This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (eg PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following terms and conditions of use: This work …","url":["https://era.ed.ac.uk/bitstream/handle/1842/37115/Bergmanis2020_Redacted.pdf?sequence=3&isAllowed=y"]}
-{"year":"2020","title":"Metrics and tools for exploring toxicity in social media","authors":["PMFN da Silva - 2020"],"snippet":"Page 1. FACULDADE DE ENGENHARIA DA UNIVERSIDADE DO PORTO Metrics and tools for exploring toxicity in social media Pedro Silva Mestrado Integrado em Engenharia Informática e Computação Supervisor: Sérgio …","url":["https://repositorio-aberto.up.pt/bitstream/10216/128545/2/412412.pdf"]}
-{"year":"2020","title":"Mis-shapes, Mistakes, Misfits: An Analysis of Domain Classification Services","authors":["P Vallina, V Le Pochat, Á Feal, M Paraschiv, J Gamba…"],"snippet":"… service. Their popularity is further reflected by the fact that 47% of the 4.4M domains are indexed in the Chrome User Experience Report [71] and 0.5% by Common Crawl [72], both generated between August and October 2019 …","url":["https://lepoch.at/files/domain-classification-imc20.pdf"]}
-{"year":"2020","title":"Mitigating Bias in Deep Nets with Knowledge Bases: the Case of Natural Language Understanding for Robots","authors":["M Mensio, E Bastianelli, I Tiddi, G Rizzo"],"snippet":"… The connections in green represent highway connections be- tween the first and the third layer. over the Common Crawl resource3 … For this reason, it can intrinsically provide an ex- planation for the model behavior, as it summarizes a much 3http://commoncrawl.org …","url":["http://ceur-ws.org/Vol-2600/paper20.pdf"]}
-{"year":"2020","title":"Mitigating Gender Bias in Machine Learning Data Sets","authors":["S Leavy, G Meaney, K Wade, D Greene - arXiv preprint arXiv:2005.06898, 2020"],"snippet":"… evaluation of system accuracy and learned associations in machine learning technologies that underlie many search and recommendation systems [9]. Implicit Association Tests (IATs) were found to be effective in uncovering …","url":["https://arxiv.org/pdf/2005.06898"]}
-{"year":"2020","title":"Modeling Recurring Concepts in Single-label and Multi-label Streams","authors":["Z Ahmadi"],"snippet":"Page 1. Modeling Recurring Concepts in Single-label and Multi-label Streams A thesis submitted for the degree of DN at the Department of Physics, Mathematics and Computer Science at the Johannes …","url":["https://publications.ub.uni-mainz.de/theses/volltexte/2019/100003220/pdf/100003220.pdf"]}
-{"year":"2020","title":"Modeling remotely collected speech data: Applications for psychiatry","authors":["TB Holmlund - 2020"],"snippet":"… To base the analysis on a corpus with a wide variety of animal-word sources, we used a set of pretrained word vectors calculated from approximately 42 billion tokens from the entire internet, courtesy of the Common Crawl project (Pennington et al., 2014) …","url":["https://munin.uit.no/bitstream/handle/10037/17098/paper_III.pdf?sequence=8"]}
-{"year":"2020","title":"Modeling the Music Genre Perception across Language-Bound Cultures","authors":["EV Epure, G Salha, M Moussallam, R Hennequin - arXiv preprint arXiv:2010.06325, 2020"],"snippet":"… representations as described next. Multilingual Static Word Embeddings. The classical word embeddings we study are the multilingual fastText word vectors trained on Wikipedia and Common Crawl (Grave et al., 2018). The model is an …","url":["https://arxiv.org/pdf/2010.06325"]}
-{"year":"2020","title":"Modeling Word Formation in English–German Neural Machine Translation","authors":["M Weller-Di Marco, A Fraser - Proceedings of the 58th Annual Meeting of the …, 2020"],"snippet":"… We compare four training settings: small (248,730 sentences: newscommentary), large2M (1,956,444 sentences: Europarl + news-commentary), large4M (4,116,215 sentences: Europarl + news-commentary + …","url":["https://www.aclweb.org/anthology/2020.acl-main.389.pdf"]}
-{"year":"2020","title":"Moral Concerns are Differentially Observable in Language","authors":["B Kennedy, M Atari, AM Davani, J Hoover, A Omrani… - 2020"],"snippet":"… lexical semantic relatedness. We compute text representations by averaging GloVe word embedding vectors (Pennington et al., 2014) which were trained on text from the Common Crawl3. In 2 https://github.com/lda-project/lda …","url":["https://psyarxiv.com/uqmty/download?format=pdf"]}
-{"year":"2020","title":"Moral Framing and Ideological Bias of News","authors":["K Lerman - … : 12th International Conference, SocInfo 2020, Pisa …","N Mokhberian, A Abeliuk, P Cummings, K Lerman - arXiv preprint arXiv:2009.12979, 2020"],"snippet":"… then and V the m− denote semantic to axis set corresponding to this MF dimension is: Am= mean (V m+)− mean (V m−)(1) For the computations of this part, the embeddings of words are obtained from the pretrained GloVe …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=6tIBEAAAQBAJ&oi=fnd&pg=PA206&dq=commoncrawl&ots=3yMGfdMsr5&sig=MyXXhdRNotNI087l9_nvaNHNjhI","https://arxiv.org/pdf/2009.12979"]}
-{"year":"2020","title":"Morphological and pseudomorphological effects in English visual word processing: How much can we attribute the statistical structure of the language?","authors":["P Stevens, D Plaut"],"snippet":"… Real-valued 300dimensional semantic vectors generated from the Common Crawl internet text corpus were converted to 200-dimensional binary vectors using a binary multidimensional scaling algorithm (Rohde, 2002) …","url":["https://cognitivesciencesociety.org/cogsci20/papers/0399/0399.pdf"]}
-{"year":"2020","title":"Morphological Skip-Gram: Using morphological knowledge to improve word representation","authors":["F Santos, H Macedo, T Bispo, C Zanchetting - arXiv preprint arXiv:2007.10055, 2020"],"snippet":"… Keeping the quality of word embeddings and decreasing training time is very important because usually, a corpus to training embeddings is composed of 1B tokens. For example, the Common Crawl corpora contain 820B tokens …","url":["https://arxiv.org/pdf/2007.10055"]}
-{"year":"2020","title":"mT5: A massively multilingual pre-trained text-to-text transformer","authors":["A Roberts, A Barua, A Siddhant, C Raffel, L Xue… - 2021","L Xue, N Constant, A Roberts, M Kale, R Al-Rfou… - arXiv preprint arXiv …, 2020"],"snippet":"… In this paper, we in- troduce mT5, a multilingual variant of T5 that was pre-trained on a new Common Crawl-based dataset covering 101 languages … mC4 comprises natural text in 101 languages drawn from the public Common Crawl web scrape …","url":["https://arxiv.org/pdf/2010.11934","https://research.google/pubs/pub50316/"]}
-{"year":"2020","title":"Multi-Label Sentiment Analysis on 100 Languages with Dynamic Weighting for Label Imbalance","authors":["SF Yilmaz, EB Kaynak, A Koç, H Dibeklioğlu, SS Kozat - arXiv preprint arXiv …, 2020"],"snippet":"… 2, we use XLM-RoBERTa pretrained tokenizer and pretrained model [17]. XLM-RoBERTa is pretrained on CommonCrawl corpora of 100 different languages. We first tokenize the input sentence si into subword units via …","url":["https://arxiv.org/pdf/2008.11573"]}
-{"year":"2020","title":"Multi-model transfer and optimization for cloze task","authors":["J Tang, L Ling, C Ma, H Zhang, J Huang - … on Artificial Intelligence and Robotics 2020, 2020"],"snippet":"… Transformer Enc. PLM ≈ BERT WikiEn+BookCorpus+Giga5 +ClueWeb+Common Crawl RoBERTa Transformer Enc. MLM 355M BookCorpus+CCNews +OpenWebText+STORIES XLM-R Transformer Enc. MLM 550M CommonCrawl ALBERT Transformer Enc …","url":["https://www.spiedigitallibrary.org/conference-proceedings-of-spie/11574/115740T/Multi-model-transfer-and-optimization-for-cloze-task/10.1117/12.2579412.short"]}
-{"year":"2020","title":"Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity","authors":["I Vulić, S Baker, EM Ponti, U Petti, I Leviant, K Wing… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Multi-SimLex: A Large-Scale Evaluation of Multilingual and Cross-Lingual Lexical Semantic Similarity https://multisimlex.com/ Ivan Vulic ∗♠ LTL, University of Cambridge Simon Baker ∗♠ LTL, University of Cambridge …","url":["https://arxiv.org/pdf/2003.04866"]}
-{"year":"2020","title":"Multilingual AMR-to-Text Generation","authors":["A Fan, C Gardent - Proceedings of the 2020 Conference on Empirical …, 2020"],"snippet":"… 4.1 Data Pretraining For encoder pretraining on silver AMR, we take thirty million sentences from the English portion of CCNET 2 (Wenzek et al., 2019), a cleaned version of Common Crawl (an open source version of the web) …","url":["https://www.aclweb.org/anthology/2020.emnlp-main.231.pdf"]}
-{"year":"2020","title":"Multilingual Denoising Pre-training for Neural Machine Translation","authors":["Y Liu, J Gu, N Goyal, X Li, S Edunov, M Ghazvininejad… - arXiv preprint arXiv …, 2020"],"snippet":"… 2 Multilingual Denoising Pre-training We use a large-scale common crawl (CC) corpus (§2.1) to pre-train BART models (§2.2). Our ex- periments in the later sections involve finetuning a range of models pre-trained on different subsets of the CC languages §2.3) …","url":["https://arxiv.org/pdf/2001.08210"]}
-{"year":"2020","title":"Multilingual Dependency Parsing from Universal Dependencies to Sesame Street","authors":["J Nivre - International Conference on Text, Speech, and …, 2020"],"snippet":"… pre-trained models provided by Che et al. [3], who train ELMo on 20 million words randomly sampled from raw WikiDump and Common Crawl datasets for 44 languages. For BERT, we employ the pretrained multilingual cased …","url":["https://link.springer.com/chapter/10.1007/978-3-030-58323-1_2"]}
-{"year":"2020","title":"Multilingual Factual Knowledge Retrieval from Pretrained Language Models","authors":["Z Jiang, A Anastasopoulos, J Araki, H Ding, G Neubig - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models Zhengbao Jiang†, Antonios Anastasopoulos♣,∗, Jun Araki‡, Haibo Ding‡, Graham Neubig† †Languages Technologies Institute …","url":["https://arxiv.org/pdf/2010.06189"]}
-{"year":"2020","title":"Multilingual Legal Information Retrieval System for Mapping Recitals and Normative Provisions","authors":["AK JOHN - Legal Knowledge and Information Systems: JURIX …, 2020"],"snippet":"… cc/docs/en/crawl-vectors. html): pre-trained on Common Crawl and Wikipedia. We used the word-average method, which divides the sum of the word embeddings in a legal norm by the norm length. The embedding di- mension size was set to 128 …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=fy4NEAAAQBAJ&oi=fnd&pg=PA123&dq=commoncrawl&ots=BUOuNY0sH2&sig=nWyRhj_URXdbdS30qkO5Z2kfHcY"]}
-{"year":"2020","title":"Multilingual Probing Tasks for Word Representations","authors":["G Gül Şahin, C Vania, I Kuznetsov, I Gurevych - Computational Linguistics"],"snippet":"Page 1. Computational Linguistics Just Accepted MS. https://doi.org/10.1162/ COLI_a_00376 © Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license LINSPECTOR Multilingual Probing Tasks for Word Representations …","url":["https://www.mitpressjournals.org/doi/pdf/10.1162/COLI_a_00376"]}
-{"year":"2020","title":"Multilingual Stance Detection in Tweets: The Catalonia Independence Corpus","authors":["E Zotova, R Agerri, M Nuñez, G Rigau - … of The 12th Language Resources and …, 2020"],"snippet":"… Initial experimentation showed that the Common Crawl5 models performed better for our particular task. The Common Crawl models are trained using a Continuous Bag-of-Words (CBOW) architecture with position-weights and …","url":["https://www.aclweb.org/anthology/2020.lrec-1.171.pdf"]}
-{"year":"2020","title":"Multilingual Stance Detection: The Catalonia Independence Corpus","authors":["E Zotova, R Agerri, M Nuñez, G Rigau - arXiv preprint arXiv:2004.00050, 2020"],"snippet":"… task. The Common Crawl models are trained using a Continuous Bag-of-Words (CBOW) architecture with position-weights and 300 di- mensions on a vocabulary of 2M words … information. 5http://commoncrawl.org/ Page 4. 3.5 …","url":["https://arxiv.org/pdf/2004.00050"]}
-{"year":"2020","title":"Multilingual Translation with Extensible Multilingual Pretraining and Finetuning","authors":["Y Tang, C Tran, X Li, PJ Chen, N Goyal, V Chaudhary… - arXiv preprint arXiv …, 2020"],"snippet":"… challenging to train from scratch. In contrast, monolingual data exists even for low resource languages, particularly in resources such as Wikipedia or Commoncrawl, a version of the web. Thus, leveraging this monolingual …","url":["https://arxiv.org/pdf/2008.00401"]}
-{"year":"2020","title":"Multilingual Unsupervised Sentence Simplification","authors":["L Martin, A Fan, É de la Clergerie, A Bordes, B Sagot - arXiv preprint arXiv …, 2020"],"snippet":"… We mine a large quantity of paraphrases from the Common Crawl using libraries such as LASER (Artetxe et al., 2018) and faiss (Johnson et al … CCNET is an extraction of Common Crawl,2 an open source snapshot of the web …","url":["https://arxiv.org/pdf/2005.00352"]}
-{"year":"2020","title":"Multilingual Zero-shot Constituency Parsing","authors":["T Kim, S Lee - arXiv preprint arXiv:2004.13805, 2020"],"snippet":"Page 1. Multilingual Zero-shot Constituency Parsing Taeuk Kim and Sang-goo Lee Department of Computer Science and Engineering Seoul National University, Seoul, Korea {taeuk,sglee}@europa.snu.ac.kr Abstract Zero-shot …","url":["https://arxiv.org/pdf/2004.13805"]}
-{"year":"2020","title":"MultiMix: A Robust Data Augmentation Strategy for Cross-Lingual NLP","authors":["MS Bari, MT Mohiuddin, S Joty - arXiv preprint arXiv:2004.13240, 2020"],"snippet":"… samples around each selected sample. XLM-R is a multilingual LM that is trained on massive multilingual corpora (2.5 TB of refined Common-Crawl data in 100 languages) with a masked LM (MLM) objective. We chose XLM-R …","url":["https://arxiv.org/pdf/2004.13240"]}
-{"year":"2020","title":"Multiple Knowledge GraphDB (MKGDB)","authors":["S Faralli, P Velardi, F Yusifli - Proceedings of The 12th Language Resources and …, 2020"],"snippet":"… Crawl11 Web corpus. 7https://www.objectivity.com/products/ thingspan/ thingspanfeatures/ 8https://titan.thinkaurelius.com/ 9https://neo4j.com/ 10the Neo4j platform provides an interface for the development and inclusion of …","url":["https://www.aclweb.org/anthology/2020.lrec-1.283.pdf"]}
-{"year":"2020","title":"Multiscale System for Alzheimer's Dementia Recognition through Spontaneous Speech","authors":["E Edwards, C Dognin, B Bollepalli, M Singh…"],"snippet":"… Deep Random Forest Setting: We extract features using three pre-trained embeddings: Word2Vec (CBOW) with subword information [29] (pre-trained on Common Crawl), GloVe [30] pre-trained on Common Crawl and Sent2Vec …","url":["https://indico2.conference4me.psnc.pl/event/35/contributions/3302/attachments/1227/1271/Wed-SS-1-6-9.pdf"]}
-{"year":"2020","title":"MuSe 2020 Challenge and Workshop: Multimodal Sentiment Analysis, Emotion-target Engagement and Trustworthiness Detection in Real-life Media: Emotional Car …","authors":["L Stappen, A Baird, G Rizos, P Tzirakis, X Du, F Hafner… - Proceedings of the 1st …, 2020"],"snippet":"… 4.3 Language FastText [5] is a library for efficient learning of word embeddings. It is based on the skipgram model where a vector representation is associated to each character n-gram. The model is trained on the English Common Crawl corpus (600B tokens) …","url":["https://dl.acm.org/doi/abs/10.1145/3423327.3423673"]}
-{"year":"2020","title":"MuSe 2020--The First International Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop","authors":["L Stappen, A Baird, G Rizos, P Tzirakis, X Du, F Hafner… - arXiv preprint arXiv …, 2020"],"snippet":"… 4.3 Language FastText [5] is a library for efficient learning of word embeddings. It is based on the skipgram model where a vector representation is associated to each character n-gram. The model is trained on the English Common Crawl corpus (600B tokens) …","url":["https://arxiv.org/pdf/2004.14858"]}
-{"year":"2020","title":"MWPD2020: Semantic Web Challenge on Mining the Web of HTML-embedded Product Data","authors":["Z Zhang, C Bizer, R Peeters, A Primpeli"],"snippet":"Page 1. MWPD2020: Semantic Web Challenge on Mining the Web of HTML-embedded Product Data Ziqi Zhang1[0000−0002−8587−8618], Christian Bizer2[0000−0003−2367−0237], Ralph Peeters2[0000−0003 …","url":["http://ceur-ws.org/Vol-2720/paper1.pdf"]}
-{"year":"2020","title":"Névszói kötőhangzók variabilitásának korpuszalapú vizsgálata Corpus-based analysis of the variability of linking vowels in nouns and adjectives","authors":["R Péter, L Dániel"],"snippet":"… 3.1 Corpus The corpus on which we conducted our measurements is the prepublished version of the Webcorpus 2 (Nemeskey, 2020). It is based on the Common Crawl webcorpus, which is a collection of pages …","url":["https://hlt.bme.hu/media/pdf/thesis_levai_ma.pdf"]}
-{"year":"2020","title":"Named Entity Recognition for Code-Mixed Indian Corpus using Meta Embedding","authors":["R Priyadharshini, BR Chakravarthi, M Vegupatti… - 2020 6th International …, 2020"],"snippet":"… IV. EXPERIMENT We use FastText word embedding trained from Common Crawl and Wikipedia [30] for English and Hindi-Devanagari script (native script for Hindi). We also add the English Twitter GloVe word embeddings since the NER data is from Twitter …","url":["https://ieeexplore.ieee.org/abstract/document/9074379/"]}
-{"year":"2020","title":"Naming unrelated words reliably predicts creativity","authors":["JA Olson, J Nahas, D Chmoulevitch, ME Webb - PsyArXiv. December, 2020"],"snippet":"… We trained the GloVe model with the Common Crawl corpus, which contains the text of billions of web pages … We chose the GloVe algorithm and the Common Crawl corpus; this combination correlates best with …","url":["https://psyarxiv.com/qvg8b/download/?format=pdf"]}
-{"year":"2020","title":"Narrative Origin Classification of Israeli-Palestinian Conflict Texts","authors":["J Wei, E Santos Jr - The Thirty-Third International Flairs Conference, 2020"],"snippet":"… For training and testing, we converted text inputs into nu- merical representations using 300-dimensional distributed embeddings pre-trained on the Common Crawl database with the GloVe method (Pennington, Socher, and Manning 2014) …","url":["https://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS20/paper/download/18443/17596"]}
-{"year":"2020","title":"Natural Language Correction-Thesis Proposal","authors":["J Náplava"],"snippet":"… considered. This table displays top 15 languages with worst results on dictionary baseline. a new pipeline utilizing both clean data from Wikipedia and also not that clean data from general web (utilizing CommonCrawl corpus). The …","url":["http://ufal.mff.cuni.cz/~zabokrtsky/pgs/thesis_proposal/jakub-naplava-proposal.pdf"]}
-{"year":"2020","title":"Natural Language Generation using Transformer Network in an Open-domain Setting","authors":["AAM Gopinath, P Bhattacharyya","D Varshney, A Ekbal, GP Nagaraja, M Tiwari… - International Conference on …, 2020"],"snippet":"… The embeddings used in our model are trained on Common Crawl dataset with 840B tokens and 2.2M vocab. We use 300-dimensional sized vectors. 3.3 Baseline Models We formulate our task of response generation as a machine translation problem …","url":["https://link.springer.com/chapter/10.1007/978-3-030-51310-8_8","https://www.researchgate.net/profile/Deeksha-Varshney/publication/342238636_Natural_Language_Generation_Using_Transformer_Network_in_an_Open-Domain_Setting/links/60432b74299bf1e0785aff2f/Natural-Language-Generation-Using-Transformer-Network-in-an-Open-Domain-Setting.pdf"]}
-{"year":"2020","title":"Natural Language Processing (NLP) and Text Analytics","authors":["JM Patel - Getting Structured Data from the Internet, 2020"],"snippet":"In the preceding chapters, we have solely relied on the structure of the HTML documents themselves to scrape information from them, and that is a powerful method to extract information.","url":["https://link.springer.com/chapter/10.1007/978-1-4842-6576-5_4"]}
-{"year":"2020","title":"Natural Language Processing Model for Managing Maintenance Requests in Buildings","authors":["Y Bouabdallaoui, Z Lafhaj, P Yim, L Ducoulombier… - Buildings, 2020"],"snippet":"… In order to overcome the limited corpus of vocabulary in our dataset, a pre-trained word embedding was used. It is based on the FastText model [44] and trained on a large corpus of French vocabulary from Wikipedia and Common Crawl [45] …","url":["https://www.mdpi.com/2075-5309/10/9/160/pdf"]}
-{"year":"2020","title":"Natural Language Transfer Learning for Physiological Textual Similarity","authors":["V Awatramani, P Gupta - 2020 10th International Conference on Cloud …, 2020"],"snippet":"… Moreover, RoBERTa is trained over 160 GB of text that includes English Wikipedia and BooksCorporus used earlier in BERT and additionally, CommonCrawl News (CC-NEWS) dataset consisting of 63 million articles …","url":["https://ieeexplore.ieee.org/abstract/document/9058216/"]}
-{"year":"2020","title":"Naver Labs Europe's Participation in the Robustness, Chat, and Biomedical Tasks at WMT 2020","authors":["A Bérard, V Nikoulina, I Calapodescu, J Philip - … of the Fifth Conference on Machine …, 2020"],"snippet":"… Corpus Sents Docs Paracrawl 33.9M – Rapid2019 965k 48.3k Europarl 1.75M 6.7k Commoncrawl 1.97M – Wikimatrix 5.68M – Wikititles … of large monolingual English and German datasets (100M lines in total per language …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.57.pdf"]}
-{"year":"2020","title":"Nearest Neighbor Machine Translation","authors":["U Khandelwal, A Fan, D Jurafsky, L Zettlemoyer… - arXiv preprint arXiv …, 2020"],"snippet":"… The parallel sentences are mined from cleaned monolingual commoncrawl data created using the ccNet pipeline (Wenzek et al., 2019) … with only the kNN distribution (λ = 1) with beam size 1, retrieving k = 8 neighbors from …","url":["https://arxiv.org/pdf/2010.00710"]}
-{"year":"2020","title":"NestMSA: a new multiple sequence alignment algorithm","authors":["M Kayed, AA Elngar - The Journal of Supercomputing, 2020"],"snippet":"Multiple sequence alignment (MSA) is a core problem in many applications. Various optimization algorithms such as genetic algorithm and particle swarm opti.","url":["https://link.springer.com/article/10.1007/s11227-020-03206-0"]}
-{"year":"2020","title":"Neural Aspect-based Text Generation","authors":["H Hayashi - 2020"],"snippet":"Page 1. November 25, 2020 DRAFT Thesis Proposal Neural Aspect-based Text Generation Hiroaki Hayashi November 25, 2020 Language Technologies Institute School of Computer Science Carnegie Mellon University Pittsburgh, PA 15123 Thesis Committee …","url":["https://hiroakih.me/thesis_proposal.pdf"]}
-{"year":"2020","title":"Neural Databases","authors":["J Thorne, M Yazdani, M Saeidi, F Silvestri, S Riedel… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Neural Databases James Thorne University of Cambridge Facebook AI jt719@cam.ac.uk Majid Yazdani Facebook AI myazdani@fb.com Marzieh Saeidi Facebook AI marzieh@fb.com Fabrizio Silvestri Facebook AI fsilvestri@fb.com …","url":["https://arxiv.org/pdf/2010.06973"]}
-{"year":"2020","title":"NEURAL MACHINE TRANSLATION WITH UNIVERSAL VISUAL REPRESENTATION","authors":["Z Li, H Zhao"],"snippet":"… We used newsdev2016 as the dev set and newstest2016 as the test set. 2) For the EN-DE translation task, 4.43M bilingual sentence pairs of the WMT14 dataset were used as training data, including Common Crawl, News Commentary, and Europarl v7 …","url":["https://www.researchgate.net/profile/Zhuosheng_Zhang4/publication/339375656_Neural_Machine_Translation_with_Universal_Visual_Representation/links/5e4e27a4299bf1cdb938db20/Neural-Machine-Translation-with-Universal-Visual-Representation.pdf"]}
-{"year":"2020","title":"Neural Simultaneous Speech Translation Using Alignment-Based Chunking","authors":["P Wilken, T Alkhouli, E Matusov, P Golik - arXiv preprint arXiv:2005.14489, 2020"],"snippet":"Page 1. arXiv:2005.14489v1 [cs.CL] 29 May 2020 Neural Simultaneous Speech Translation Using Alignment-Based Chunking Patrick Wilken, Tamer Alkhouli, Evgeny Matusov, Pavel Golik Applications Technology (AppTek), Aachen …","url":["https://arxiv.org/pdf/2005.14489"]}
-{"year":"2020","title":"Neural Text Segmentation and Its Application to Sentiment Analysis","authors":["J Li, B Chiu, S Shang, L Shao - IEEE Transactions on Knowledge and Data …, 2020"],"snippet":"Page 1. 1041-4347 (c) 2020 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/9051834/"]}
-{"year":"2020","title":"Neural Word Embeddings for Sentiment Analysis","authors":["B Naderalvojoud - 2020"],"snippet":"Page 1. 1 Page 2. NEURAL WORD EMBEDDINGS FOR SENTIMENT ANALYSIS DUYGU ANAL˙IZ˙I˙IC¸˙IN S˙IN˙IRSEL S¨OZC¨UK¨OZ YERLES¸˙IKLER˙I BEHZAD NADERALVOJOUD PROF. DR. EBRU SEZER Supervisor Submitted to …","url":["http://www.openaccess.hacettepe.edu.tr:8080/xmlui/bitstream/handle/11655/22784/10350958.pdf?sequence=1"]}
-{"year":"2020","title":"NewB: 200,000+ Sentences for Political Bias Detection","authors":["J Wei - arXiv preprint arXiv:2006.03051, 2020"],"snippet":"… When inputting sentences into the model, we tokenize each sentence at the word-level and convert each word into a vector using 300dimensional distributed embeddings trained on the Common Crawl database with the GloVe method (Pennington et al., 2014) …","url":["https://arxiv.org/pdf/2006.03051"]}
-{"year":"2020","title":"News topic classification as a first step towards diverse news recommendation","authors":["O De Clercq, L De Bruyne, V Hoste - Computational Linguistics in the Netherlands …, 2020"],"snippet":"… The RobBERT model was trained on the Dutch part of the 39GB OSCAR corpus, a part of the Common Crawl corpus (Suárez et al. 2019). As sub-word token input, BERTje uses WordPiece, whereas RobBERT uses byte-level Byte Pair Encoding (BPE) …","url":["https://www.clinjournal.org/clinj/article/download/103/92"]}
-{"year":"2020","title":"NLNDE at CANTEMIST: Neural Sequence Labeling and Parsing Approaches for Clinical Concept Extraction","authors":["L Lange, X Dai, H Adel, J Strötgen - arXiv preprint arXiv:2010.12322, 2020"],"snippet":"… In particular, we use pre-trained fastText embeddings [22] that were trained on articles from Wikipedia and the Common Crawl, as well as domain-speci c fastText embeddings [23] that were pretrained on articles of the Spanish …","url":["https://arxiv.org/pdf/2010.12322"]}
-{"year":"2020","title":"NLP North at WNUT-2020 Task 2: Pre-training versus Ensembling for Detection of Informative COVID-19 English Tweets","authors":["AG Møller, R van der Goot, B Plank - Proceedings of the 6th Workshop on Noisy …, 2020"],"snippet":"… twitter. ArXiv, abs/2005.07503. Sebastian Nagel. 2016. https://commoncrawl org/2016/10/news-dataset-available/. Dat Quoc Nguyen, Thanh Vu, Afshin Rahimi, Mai Hoang Dao, Linh The Nguyen, and Long Doan. 2020. WNUT …","url":["http://www.robvandergoot.com/doc/wnut2020.pdf"]}
-{"year":"2020","title":"No computation without representation: Avoiding data and algorithm biases through diversity","authors":["C Kuhlman, L Jackson, R Chunara - arXiv preprint arXiv:2002.11836, 2020"],"snippet":"… Page 3. Dataset Description Sensitive Attribute race gender age other Adult: US Census income data [36]. [43, 57, 72, 77] [2, 3, 25, 27, 43, 57, 64, 77] [57] [2, 57] Common Crawl: Occupation biographies [42]. [34] Comm …","url":["https://arxiv.org/pdf/2002.11836"]}
-{"year":"2020","title":"Noise Pollution in Hospital Readmission Prediction: Long Document Classification with Reinforcement Learning","authors":["L Xu, J Hogan, RE Patzer, JD Choi - arXiv preprint arXiv:2005.01259, 2020"],"snippet":"… Averaged Word Embedding For the averaged word embedding encoder (AWE; Section 4.2), em- beddings generated by FastText trained on the Common Crawl and the English Wikipedia with the 300 dimension is …","url":["https://arxiv.org/pdf/2005.01259"]}
-{"year":"2020","title":"Not All Swear Words Are Used Equal: Attention over Word n-grams for Abusive Language Identification","authors":["HJ Jarquín-Vásquez, M Montes-y-Gómez… - Mexican Conference on …, 2020","L Villasenor-Pineda - Pattern Recognition: 12th Mexican Conference, MCPR …"],"snippet":"… On the other hand, for word representation we used pre-trained fastText embeddings [3], trained with subword information on Common Crawl. Table 2. Proposed attention-based deep neural network hyperparameters. Layer …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=UO_rDwAAQBAJ&oi=fnd&pg=PA282&dq=commoncrawl&ots=4BGirDzhwW&sig=0HRX8HVtoXlgmfN76pD6wgHh1_c","https://link.springer.com/chapter/10.1007/978-3-030-49076-8_27"]}
-{"year":"2020","title":"NOTICE TO BORROWERS","authors":["C Li"],"snippet":"Page 1. DISTRIBUTION AGREEMENT In presenting this thesis as a partial fulfillment of the requirements for an advanced degree from Emory University, I agree that the Library of the University shall make it available for inspection …","url":["https://franklicm.github.io/files/thesis_final.pdf"]}
-{"year":"2020","title":"Novel Entity Discovery from Web Tables","authors":["S Zhang, E Meij, K Balog, R Reinanda - arXiv preprint arXiv:2002.00206, 2020"],"snippet":"Page 1. Novel Entity Discovery from Web Tables Shuo Zhang Bloomberg London, United Kingdom szhang611@bloomberg.net Edgar Meij Bloomberg London, United Kingdom emeij@bloomberg.net Krisztian Balog University …","url":["https://arxiv.org/pdf/2002.00206"]}
-{"year":"2020","title":"Novel Opinion mining System for Movie Reviews","authors":["AH AbdulHafiz - International Journal of Intelligent Systems and …, 2020"],"snippet":"… We have adopted the Word2Vec feature representation, the CSG in particular, in our work. It has a pre-trained word vector for the English language trained on 1 million common crawl and Wikipedia documents. Word2vec is a two-layer neural net …","url":["https://151.80.211.128/IJISAE/article/download/1090/621"]}
-{"year":"2020","title":"NRC Systems for the 2020 Inuktitut–English News Translation Task","authors":["R Knowles, D Stewart, S Larkin, P Littell - Proceedings of the Fifth Conference on …, 2020"],"snippet":"… org/wmt20/translation-task.html Page 3. 157 Wiki Titles or Common Crawl Inuktitut data.9 We incorporated the news portion of the development data in training our models to alleviate the domain mismatch issue (Section 5.1). 4 Preprocessing and Postprocessing …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.13.pdf"]}
-{"year":"2020","title":"NUIG-DSI at the WebNLG+ challenge: Leveraging Transfer Learning for RDF-to-text generation","authors":["N Pasricha, M Arcan, P Buitelaar - Proceedings of the 3rd WebNLG Workshop on …, 2020"],"snippet":"… middle) and reference lexicalisation (bottom). (Vaswani et al., 2017) and is pre-trained using un- supervised learning on a large corpus of unlabeled data obtained from the Web using the Common Crawl project. It is trained using …","url":["https://webnlg-challenge.loria.fr/files/2020.webnlg-papers.15.pdf"]}
-{"year":"2020","title":"ODArchive–Creating an Archive for Structured Data from Open Data Portals","authors":["T Weber, J Mitöhner"],"snippet":"… We deem this project particularly useful as a resource for experiments on real-world structured data: to name an example, while large corpora of tabular data from Web tables have been made available via CommonCrawl [6], the …","url":["https://aic.ai.wu.ac.at/~polleres/publications/webe-etal-2020ISWC.pdf"]}
-{"year":"2020","title":"On Finding Similar Verses from the Holy Quran using Word Embeddings","authors":["S Saeed, S Haider, Q Rajput - 2020 International Conference on Emerging Trends in …, 2020"],"snippet":"… It is an English multitask Convolution Neural Network (CNN)[4] trained on OntoNotes[14], with GloVe[11] vectors trained on Common Crawl[3]. It contains 685,000 keys, 20,000 unique words and each word …","url":["https://ieeexplore.ieee.org/abstract/document/9080691/"]}
-{"year":"2020","title":"On Multilingual Word Embeddings & their applications in machine translation","authors":["N Jain"],"snippet":"… crosslingual signals. The hard/challenging dataset comprise of English-Italian, English-German, English-Finnish and English-Spanish pairs. These embeddings are trained on Wacky crawling corpora/common crawl corpora. We notice …","url":["https://naman-ntc.github.io/data/Seminar.pdf"]}
-{"year":"2020","title":"On revealing shared conceptualization among open datasets","authors":["M Bogdanović, N Veljković, MF Gligorijević, D Puflović… - Journal of Web Semantics, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S1570826820300573"]}
-{"year":"2020","title":"On the comparability of Pre-trained Language Models","authors":["M Aßenmacher, C Heumann - arXiv preprint arXiv:2001.00781, 2020"],"snippet":"… Wikipedia data sets are available in the Tensorflow Datasets-module3. CommonCrawl Among other resources, Yang et al. (2019) used data from CommonCrawl … CommonCrawl https://commoncrawl.org/ Unclear Fully available XLNet ClueWeb 2012-B Callan et al …","url":["https://arxiv.org/pdf/2001.00781"]}
-{"year":"2020","title":"On the diminishing return of labeling clinical reports","authors":["JB Lamare, T Olatunji, L Yao - arXiv preprint arXiv:2010.14587, 2020"],"snippet":"… linear classifiers. Recent NLP ad- vance pushes the envelop much further by leveraging web-scale data – for instance, the Common Crawl project 1 that produces 20TB of textual data from the Internet each month. To cope …","url":["https://arxiv.org/pdf/2010.14587"]}
-{"year":"2020","title":"On the Effectiveness of Behavior-Based Ransomware Detection","authors":["J Han, Z Lin, DE Porter - International Conference on Security and Privacy in …, 2020"],"snippet":"… To measure whether partial encryption is effective at withholding user data, we collected 200 different PDF documents from the web using Common Crawl Document Download [4]. We choose PDF documents with a minimum of 10 pages …","url":["https://link.springer.com/chapter/10.1007/978-3-030-63095-9_7"]}
-{"year":"2020","title":"On the evaluation of retrofitting for supervised short-text classification","authors":["K GHAZI, A TCHECHMEDJIEV, S HARISPE…"],"snippet":"… we considered the 300-dimensional word vectors: (i) Paragram [16], learned from the text content in the paraphrase database PPDB, (ii) Glove [22] learned from Wikipedia and Common Crawl data, (iii) MUSE, a fastText embedding …","url":["http://ceur-ws.org/Vol-2708/donlp2.pdf"]}
-{"year":"2020","title":"On the impact of publicly available news and information transfer to financial markets","authors":["M Jazbec, B Pásztor, F Faltings, N Antulov-Fantulin… - arXiv preprint arXiv …, 2020"],"snippet":"… To address ihttps://commoncrawl.org iiDetailed statistics about the Common Crawl can found here: https://commoncrawl.github.io/cc-crawl-statistics iiiWe omitted the domain www.nbonews.com. While the most frequently occurring …","url":["https://arxiv.org/pdf/2010.12002"]}
-{"year":"2020","title":"On the importance of pre-training data volume for compact language models","authors":["V Micheli, M D'Hoffschmidt, F Fleuret - arXiv preprint arXiv:2010.03813, 2020"],"snippet":"… OSCAR 2 (Ortiz Suárez et al., 2019) is a large-scale multilingual open source collection of corpora ob- tained by language classification and filtering of the Common Crawl corpus 3. The whole French part amounts to 138 GB …","url":["https://arxiv.org/pdf/2010.03813"]}
-{"year":"2020","title":"On the Language Neutrality of Pre-trained Multilingual Representations","authors":["J Libovický, R Rosa, A Fraser - arXiv preprint arXiv:2004.05160, 2020"],"snippet":"… XLM-RoBERTa. Conneau et al. (2019) claim that the original mBERT is under-trained and train a similar model on a larger dataset that consists of two terabytes of plain text extracted from CommonCrawl (Wenzek et al., 2019) …","url":["https://arxiv.org/pdf/2004.05160"]}
-{"year":"2020","title":"On the Persistence of Persistent Identifiers of the Scholarly Web","authors":["M Klein, L Balakireva - arXiv preprint arXiv:2004.03011, 2020"],"snippet":"… These findings were confirmed in a large scale study by Thompson and Jian [16] based on two samples of the web taken from Common Crawl6 datasets … Thompson, HS, Tong, J.: Can common crawl reliably track persistent identifier (PID) use over time …","url":["https://arxiv.org/pdf/2004.03011"]}
-{"year":"2020","title":"On the synthesis of metadata tags for HTML files","authors":["P Jiménez, JC Roldán, FO Gallego, R Corchuelo - Software: Practice and Experience"],"snippet":"… Recently, an analysis of the 32.04 million domains in the November 2019 Common Crawl has revealed that only 11.92 million domains provide metadata tags,1 which clearly argues for a method that helps software agents deal with the documents provided by the remaining …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/spe.2886"]}
-{"year":"2020","title":"On using Product-Specific Schema. org from Web Data Commons: An Empirical Set of Best Practices","authors":["R Kiran Selvam, M Kejriwal - arXiv e-prints, 2020","RK Selvam, M Kejriwal - arXiv preprint arXiv:2007.13829, 2020"],"snippet":"… on e-commerce websites. The Web Data Commons (WDC) project has extracted schema.org data at scale from webpages in the Common Crawl and made it available as an RDF 'knowledge graph' at scale. The portion of this …","url":["https://arxiv.org/pdf/2007.13829","https://ui.adsabs.harvard.edu/abs/2020arXiv200713829K/abstract"]}
-{"year":"2020","title":"On-The-Fly Information Retrieval Augmentation for Language Models","authors":["H Wang, D McAllester - Proceedings of the First Joint Workshop on Narrative …, 2020"],"snippet":"… News etc. For language modelling we use the NY Times portion because it is written by native English speakers. Since GPT 2.0 is trained on Common Crawl which contains news collections started from 2008. To avoid testing …","url":["https://www.aclweb.org/anthology/2020.nuse-1.14.pdf"]}
-{"year":"2020","title":"One Belt, One Road, One Sentiment? A Hybrid Approach to Gauging Public Opinions on the New Silk Road Initiative","authors":["JK Chandra, E Cambria, A Nanetti"],"snippet":"… ABSA. We used the Common Crawl GloVe version [44], a pre-trained 300-dimension vector representation database of 840 billion tokens and 2.2 million vocabulary, to convert our preprocessed tweets into word embeddings …","url":["https://sentic.net/one-belt-one-road-one-sentiment.pdf"]}
-{"year":"2020","title":"Open Information Extraction as Additional Source for Kazakh Ontology Generation","authors":["N Khairova, S Petrasova, O Mamyrbayev, K Mukhsina - Asian Conference on …, 2020"],"snippet":"… also for many others. For example, an experiment was conducted in [19] for assessing the adequacy of measuring the factual density of 50 randomly selected Spanish documents in the CommonCrawl corpus. In a recent study …","url":["https://link.springer.com/chapter/10.1007/978-3-030-41964-6_8"]}
-{"year":"2020","title":"Open Intent Extraction from Natural Language Interactions","authors":["N Vedula, N Lipka, P Maneriker, S Parthasarathy - Proceedings of The Web …, 2020"],"snippet":"… 2A commercial Customer Relationship Management (CRM) software. Implementation: We use the 300-dimensional GloVe embeddings [50] pre-trained on the Common Crawl dataset3, and character embeddings as per Ma et al [42] …","url":["https://dl.acm.org/doi/pdf/10.1145/3366423.3380268"]}
-{"year":"2020","title":"Open science-based framework to reveal open data publishing: an experience from using Common Crawl","authors":["A Correa, I Fernandes - ELPUB 24rd edition of the International Conference on …, 2020"],"snippet":"The publishing of open data is considered a key element for civic participation paving the way to the 'public value', a term which underpins the social contribution. A result of that can be seen through the popularity of data portals published all around …","url":["https://hal.archives-ouvertes.fr/hal-02544245/document"]}
-{"year":"2020","title":"Open source speech recognition on edge devices","authors":["R Peinl, B Rizk, R Szabad - 2020 10th International Conference on Advanced …, 2020"],"snippet":"… To make the comparison as fair as possible we used the KenLM 6-gram language model for all ASR models except DS2, which came with its own word-level language model trained on CommonCrawl (en-00) from the Common Crawl Corpus7 …","url":["https://ieeexplore.ieee.org/abstract/document/9208978/"]}
-{"year":"2020","title":"Open-Domain Question Answering Goes Conversational via Question Rewriting","authors":["R Anantha, S Vakulenko, Z Tu, S Longpre, S Pulman… - arXiv preprint arXiv …, 2020"],"snippet":"… relevant pages with randomly sampled web pages that constitute 1% of the Common Crawl dataset identified … Wayback Machine and 9.9M random web pages from the Common Crawl dataset … 3 https://commoncrawl.org/2019 …","url":["https://arxiv.org/pdf/2010.04898"]}
-{"year":"2020","title":"Optimal Subarchitecture Extraction For BERT","authors":["A de Wynter, DJ Perry - arXiv preprint arXiv:2010.10499, 2020"],"snippet":"… In order to have a sufficiently diverse dataset to pre-train Bort, we combined corpora obtained from Wikipedia7, Wiktionary8, OpenWebText (Gokaslan and Cohen, 2019), UrbanDictionary9, One Billion Words (Chelba et al., 2014) …","url":["https://arxiv.org/pdf/2010.10499"]}
-{"year":"2020","title":"Optimizing Distributed Computing Systems via Machine Learning","authors":["H Wang - 2020"],"snippet":"Page 1. Optimizing Distributed Computing Systems via Machine Learning by Hao Wang A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Electrical …","url":["https://tspace.library.utoronto.ca/bitstream/1807/103710/1/Wang_Hao_202011_PhD_thesis.pdf"]}
-{"year":"2020","title":"OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddings","authors":["S Dev, T Li, JM Phillips, V Srikumar - arXiv preprint arXiv:2007.00049, 2020"],"snippet":"… Our code for reproducing experiments will be released upon publication. Debiasing contextualized embeddings. The operations above are described for a noncontextualized embedding; we use one of the largest such …","url":["https://arxiv.org/pdf/2007.00049"]}
-{"year":"2020","title":"Out-of-the-Box and into the Ditch? Multilingual Evaluation of Generic Text Extraction Tools","authors":["A Barbaresi, G Lejeune - Proceedings of the 12th Web as Corpus Workshop, 2020"],"snippet":"… Recently, approaches using the CommonCrawl1 have flourished as they allow for faster download and processing by skipping (or more precisely outsourcing) the crawling phase (Habernal et al., 2016; Schäfer, 2016) … 1https://commoncrawl.org …","url":["https://www.aclweb.org/anthology/2020.wac-1.2.pdf"]}
-{"year":"2020","title":"Overview of the CLEF eHealth 2020 task 2: consumer health search with ad hoc and spoken queries","authors":["L Goeuriot, Z Liu, G Pasi, GG Saez, M Viviani, C Xu - … Notes of Conference and Labs of …, 2020"],"snippet":"… 2.1 Documents The 2018 CLEF eHealth Consumer Health Search document collection was used in this year's IR challenge. As detailed in [17], this collection consists of web pages acquired from the CommonCrawl. An …","url":["http://www.dei.unipd.it/~ferro/CLEF-WN-Drafts/CLEF2020/paper_260.pdf"]}
-{"year":"2020","title":"Overview of the CLEF eHealth Evaluation Lab 2020","authors":["C Xu - … IR Meets Multilinguality, Multimodality, and Interaction …"],"snippet":"… Task 2. The 2018 CLEF eHealth Consumer Health Search document collection was used in this year's IR challenge. As detailed in [14], this collection consists of web pages acquired from the CommonCrawl. An initial list of websites was identified for acquisition …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=IxP9DwAAQBAJ&oi=fnd&pg=PA255&dq=commoncrawl&ots=BCbV87DfTS&sig=y0JIuiOfa-DKv4aFVa2ZXlCYBic"]}
-{"year":"2020","title":"Overview of the seventh Dialog System Technology Challenge: DSTC7","authors":["LF D'Haro, K Yoshino, C Hori, TK Marks… - Computer Speech & …, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0885230820300012"]}
-{"year":"2020","title":"Overview of the Transformer-based Models for NLP Tasks","authors":["A Gillioz, J Casas, E Mugellini, O Abou Khaled"],"snippet":"… they contain. The tokenization is done with SentencePiece [15]. In a few cases, for example, in [16], the authors only used a subset of those datasets (eg Stories [17] is a subset of CommonCrawl dataset). IV. BENCHMARKS …","url":["https://annals-csis.org/Volume_21/drp/pdf/20.pdf"]}
-{"year":"2020","title":"Overview of Touché 2020: Argument Retrieval","authors":["A Bondarenko, M Fröbe, M Beloucif, L Gienapp… - Working Notes Papers of the …, 2020","H Wachsmuth, M Potthast, M Hagen - … IR Meets Multilinguality, Multimodality, and Interaction …","Y Ajjour, A Panchenko, C Biemann, B Stein… - Experimental IR Meets …"],"snippet":"… Stab et al.[26] retrieve documents from the Common Crawl 3 and then use a topic-dependent neural network to extract arguments from the retrieved documents … This method is shown to outperform several 3 http://commoncrawl. org. Page 398 …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=IxP9DwAAQBAJ&oi=fnd&pg=PA384&dq=commoncrawl&ots=BCbV87DfTS&sig=590FLiaMF0QksqxDhusBxoZQuK4","https://link.springer.com/content/pdf/10.1007/978-3-030-58219-7.pdf#page=395","https://webis.de/downloads/publications/papers/stein_2020v.pdf"]}
-{"year":"2020","title":"ParaCrawl: Web-Scale Acquisition of Parallel Corpora","authors":["M Banón, P Chen, B Haddow, K Heafield, H Hoang…"],"snippet":"… In an ex- ploratory study, only 5% of a collection of web pages with useful content were found in CommonCrawl. This may have improved with recent more extensive crawls by CommonCrawl but there is still a strong argument for targeted crawling. 4 Crawling …","url":["https://www.neural.mt/papers/edinburgh/paracrawl.pdf"]}
-{"year":"2020","title":"Parallelograms revisited: Exploring the limitations of vector space models for simple analogies","authors":["JC Peterson, D Chen, TL Griffiths - Cognition, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0010027720302596"]}
-{"year":"2020","title":"Pedro Javier Ortiz Suárez1, 3 [0000− 0003− 0343− 8852], Yoann Dupont2","authors":["G Lejeune, T Tian"],"snippet":"… For the fixed word embeddings we used the Common Crawl-based FastText embeddings [10] originally trained by Facebook as opposed to the embeddings provided by the HIPE shared task, as we obtained better dev …","url":["http://ceur-ws.org/Vol-2696/paper_203.pdf"]}
-{"year":"2020","title":"Persistent metadata catalog","authors":["GS Mcpherson, Y Mikhaylyuta, TD Baker, RJ Cole - US Patent 10,853,356, 2020"],"snippet":"… sources. In one embodiment metadata catalog service 120 may host metadata for a collection of data sets that are available in the public domain, such as the 1000 genome, NASA NEX, and the Common Crawl Corpus data sets …","url":["https://www.freepatentsonline.com/10853356.html"]}
-{"year":"2020","title":"Phishing Detection Using Machine Learning Technique","authors":["J Rashid, T Mahmood, MW Nisar, T Nazir - 2020 First International Conference of …, 2020"],"snippet":"… and June 2017. In particular, we selected 5000 phishing web pages, and all web pages are more stable, especially based on URLs. The fish tank is based entirely on the Alexa URL and Common Crawl archives. B. Step 2 Vocabulary …","url":["https://ieeexplore.ieee.org/abstract/document/9283771/"]}
-{"year":"2020","title":"PhishingLine: Hybrid Phishing Classifier with Logo Detection","authors":["K Vohra - 2020"],"snippet":"… 29 5.5 Web Capture . . . . . 30 5.5.1 WARC . . . . . 30 5.5.2 Common Crawl . . . . . 30 5.6 Client Server Architecture . . . . . 30 5.6.1 TCP …","url":["https://www.ka.beer/pdf/project.pdf"]}
-{"year":"2020","title":"Phonemer at WNUT-2020 Task 2: Sequence Classification Using COVID Twitter BERT and Bagging Ensemble Technique based on Plurality Voting","authors":["A Wadhawan - arXiv preprint arXiv:2010.00294, 2020"],"snippet":"… Table 2. 4.2 System Settings For training the CNN, LSTM and BiLSTMs, word vectors for english language pre-trained on Common Crawl2 and Wikipedia3 are downloaded4 and used using FastText5 library. These word vectors …","url":["https://arxiv.org/pdf/2010.00294"]}
-{"year":"2020","title":"Photo Stream Question Answer","authors":["W Zhang, S Tang, Y Cao, J Xiao, S Pu, F Wu, Y Zhuang - Proceedings of the 28th …, 2020"],"snippet":"Page 1. Photo Stream Question Answer Wenqiao Zhang Zhejiang University wenqiaozhang@zju.edu.cn Siliang Tang* Zhejiang Universety siliang@zju.edu.cn Yanpeng Cao,Jun Xiao Zhejiang University caoyp,junx@zju.edu.cn …","url":["https://dl.acm.org/doi/abs/10.1145/3394171.3413745"]}
-{"year":"2020","title":"PMap: Ensemble Pre-training Models for Product Matching","authors":["N Kertkeidkachorn, R Ichise"],"snippet":"… In this section, we explain the pre-train models and how to fine-tune them. 5 http://webdatacommons.org/largescaleproductcorpus/v2/index. html 6 http://webdatacommons.org/structureddata/ 7 https://commoncrawl …","url":["http://ceur-ws.org/Vol-2720/paper2.pdf"]}
-{"year":"2020","title":"PoKED: A Semi-Supervised System for Word Sense Disambiguation","authors":["F Wei"],"snippet":"Page 1. PoKED: A Semi-Supervised System for Word Sense Disambiguation Feng Wei 1 Abstract In this paper, we propose a semi-supervised neural system, named Position-wise Orthogonal Knowledge-Enhanced Disambiguator …","url":["https://proceedings.icml.cc/static/paper_files/icml/2020/1929-Paper.pdf"]}
-{"year":"2020","title":"Practical Data Science for Information Professionals","authors":["D Stuart - 2020"],"snippet":"Page 1. Practical Data Science for Information Professionals Page 2. Every purchase of a Facet book helps to fund CILIP's advocacy, awareness and accreditation programmes for information professionals. Page 3. Practical Data …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=2TjzDwAAQBAJ&oi=fnd&pg=PP3&dq=commoncrawl&ots=kN5yF0ztQ5&sig=n_c9XhBzAQWnpO6G9vyAev9qRJY"]}
-{"year":"2020","title":"Pragmatic Aspects of Discourse Production for the Automatic Identification of Alzheimer's Disease","authors":["A Pompili, A Abad, DM de Matos, IP Martins - IEEE Journal of Selected Topics in …, 2020"],"snippet":"… For this purpose, we rely on a pre-trained model of word vector representations containing 2 million word vectors, in 300 dimensions, trained with fastText on Common Crawl [42]. In the process of converting a sentence into its vector …","url":["https://ieeexplore.ieee.org/abstract/document/8963723/"]}
-{"year":"2020","title":"Pre-indexing Pruning Strategies","authors":["S Altin, R Baeza-Yates, BB Cambazoglu - International Symposium on String …, 2020"],"snippet":"… 4 Experimental Setup. 4.1 Document Collection. As web document collection, we mostly use the open source web collection provided by Common Crawl, CC, in November 2017 … 5 Experimental Results. 5.1 Common Crawl and BM25 …","url":["https://link.springer.com/chapter/10.1007/978-3-030-59212-7_13"]}
-{"year":"2020","title":"Pre-trained Models for Natural Language Processing: A Survey","authors":["X Qiu, T Sun, Y Xu, Y Shao, N Dai, X Huang - arXiv preprint arXiv:2003.08271, 2020"],"snippet":"Page 1. .Invited Review . Pre-trained Models for Natural Language Processing: A Survey Xipeng Qiu*, Tianxiang Sun, Yige Xu, Yunfan Shao, Ning Dai & Xuanjing Huang School of Computer Science, Fudan University, Shanghai …","url":["https://arxiv.org/pdf/2003.08271"]}
-{"year":"2020","title":"Pre-training Polish Transformer-based Language Models at Scale","authors":["S Dadas, M Perełkiewicz, R Poświata - arXiv preprint arXiv:2006.04229, 2020"],"snippet":"… the size of the training corpus. 2) We proposed a method for collecting and pre-processing the data from the Common Crawl database to obtain clean, high-quality text corpora. 3) We conducted a comprehensive evaluation …","url":["https://arxiv.org/pdf/2006.04229"]}
-{"year":"2020","title":"Pre-training via Leveraging Assisting Languages and Data Selection for Neural Machine Translation","authors":["H Song, R Dabre, Z Mao, F Cheng, S Kurohashi… - arXiv preprint arXiv …, 2020"],"snippet":"… Additionally, we used Common Crawl4 monolingual corpora for pre-training … We filled the CurrentDistribution line by line in Common Crawl file if the ratio of the length of current line had been less than the ratio of this length in target length distribution …","url":["https://arxiv.org/pdf/2001.08353"]}
-{"year":"2020","title":"Pre-training via Leveraging Assisting Languages for Neural Machine Translation","authors":["H Song, R Dabre, Z Mao, F Cheng, S Kurohashi…"],"snippet":"… We used Common Crawl3 monolingual corpora for pre-training … We created a shared sub-word vocabulary us- ing Japanese and English data from ASPEC mixing with Japanese, English, Chinese and French data from Common Crawl …","url":["https://shyyhs.github.io/files/ACL2020SRW_Song_paper.pdf"]}
-{"year":"2020","title":"Predicting Consumers' Brand Sentiment Using Text Analysis on Reddit","authors":["P Cen"],"snippet":"… with a F-score of 86.25 for NER tasks. The en_core_web_md model is an English multi-task CNN trained on OntoNotes, with GloVe vectors trained on Common Crawl For NER tasks, it assigns various labels to identified entities, such as “CARDINAL,” “ORG,” …","url":["https://repository.upenn.edu/cgi/viewcontent.cgi?article=1097&context=joseph_wharton_scholars"]}
-{"year":"2020","title":"Predicting Themes within Complex Unstructured Texts: A Case Study on Safeguarding Reports","authors":["A Edwards, D Rogers, J Camacho-Collados… - arXiv preprint arXiv …, 2020"],"snippet":"… Pre-trained word embeddings We leverage two pre-trained 300-dimensional word embedding models: Word2vec (Mikolov et al., 2013) trained on Google news dataset and fastText (Bojanowski et al., 2017) trained with subword information on Common Crawl …","url":["https://arxiv.org/pdf/2010.14584"]}
-{"year":"2020","title":"Predicting Twitter Engagement With Deep Language Models","authors":["M Volkovs, Z Cheng, M Ravaut, H Yang, K Shen…"],"snippet":"… text comprehension tasks. The majority of published language models are pre-trained on large text corpora such as Wikipedia or CommonCrawl, that typically contain longer and properly worded pieces of text. Tweets on the …","url":["http://www.cs.toronto.edu/~mvolkovs/recsys2020_challenge.pdf"]}
-{"year":"2020","title":"Prior Guided Feature Enrichment Network for Few-Shot Segmentation","authors":["Z Tian, H Zhao, M Shu, Z Yang, R Li, J Jia - IEEE Annals of the History of Computing, 2020"],"snippet":"… Therefore the prior is not,applicable and we only verify FEM on the baseline with,VGG-16 backbone in the zero-shot setting.,Structural Change,Embeddings of Word2Vec [24] and,FastText [22] are trained …","url":["https://www.computer.org/csdl/journal/tp/5555/01/09154595/1lZzPRFhQqY"]}
-{"year":"2020","title":"Privacy at Scale: Introducing the PrivaSeer Corpus of Web Privacy Policies","authors":["M Srinath, S Wilson, CL Giles - arXiv preprint arXiv:2004.11131, 2020"],"snippet":"… As a consequence, 2https://commoncrawl.org/ Page 3 … Thus, we selected those URLs which had the word “privacy” or the words “data” and “protection” from the Common Crawl URL archive. We were able to extract 3.9 million URLs that fit this selection criterion …","url":["https://arxiv.org/pdf/2004.11131"]}
-{"year":"2020","title":"Privacy Policies over Time: Curation andAnalysis of a Million-Document Dataset","authors":["R Amos, G Acar, E Lucherini, M Kshirsagar… - arXiv preprint arXiv …, 2020"],"snippet":"… app privacy policy URLs [23]. Concurrent to this work, Srinath et al. contribute PrivaSeer, a dataset of over 1 million English privacy policies extracted from May 2019 Common Crawl data [14]. Our work advances this area of …","url":["https://arxiv.org/pdf/2008.09159"]}
-{"year":"2020","title":"Privacy-Preserving Passive DNS","authors":["P Papadopoulos, N Pitropakis, WJ Buchanan, O Lo… - Computers, 2020"],"snippet":"… These sources include but are not limited to Public Blacklists, the Alexa ranking, the Common Crawl project, and various Top Level Domain (TLD) zone files. This system's output is a refined dataset that can be …","url":["https://www.mdpi.com/2073-431X/9/3/64/pdf"]}
-{"year":"2020","title":"Privacy-Preserving Visual Content Tagging using Graph Transformer Networks","authors":["XS Vu, DT Le, C Edlund, L Jiang, HD Nguyen"],"snippet":"… that local knowledge can be derived from data observations including label semantics or multimedia content se- mantics (eg, optical character recognition); whereas, global knowledge can be drawn from publicly available corpora …","url":["https://people.cs.umu.se/sonvx/files/ACMMM2020_SGTN_CAMREADY_1.pdf"]}
-{"year":"2020","title":"Probing Task-Oriented Dialogue Representation from Language Models","authors":["CS Wu, C Xiong - arXiv preprint arXiv:2010.13912, 2020"],"snippet":"… is to maximize left-to-right generation likelihood. To ensure diverse and nearly unlimited text sources, they use Common Crawl to obtain 8M documents as its training data. Budzianowski and Vulic (2019) trained GPT2 on task …","url":["https://arxiv.org/pdf/2010.13912"]}
-{"year":"2020","title":"Probing Tasks for Noised Back-Translation","authors":["N Spring - 2020"],"snippet":"Page 1. Bachelor's thesis presented to the Faculty of Arts and Social Sciences of the University of Zurich for the degree of Bachelor of Arts UZH Probing Tasks for Noised Back-Translation Author: Nicolas Spring Student …","url":["https://www.cl.uzh.ch/dam/jcr:34ea0877-26f8-405b-88a5-1191536986db/spring_ba_probing_tasks.pdf"]}
-{"year":"2020","title":"Probing Text Models for Common Ground with Visual Representations","authors":["G Ilharco, R Zellers, A Farhadi, H Hajishirzi - arXiv preprint arXiv:2005.00619, 2020"],"snippet":"… GloVe embeddings (Pennington et al., 2014). For such, we use embeddings trained on 840 billion tokens of web data from Common Crawl, with dL = 300 and a vocabulary size of 2.2 million2. Models trained on text and images …","url":["https://arxiv.org/pdf/2005.00619"]}
-{"year":"2020","title":"Programming in Natural Language with fuSE: Synthesizing Methods from Spoken Utterances Using Deep Natural Language Understanding","authors":["S Weigelt, V Steurer, T Hey, WF Tichy - Proceedings of the 58th Annual Meeting of …, 2020"],"snippet":"… on the Common Crawl dataset4 by Facebook Research (Mikolov et al., 3Note that we do not discuss the influence of varying epoch numbers, since we used early stopping, ie the training stops when the validation loss stops …","url":["https://www.aclweb.org/anthology/2020.acl-main.395.pdf"]}
-{"year":"2020","title":"Projecting Heterogeneous Annotations for Named Entity Recognition","authors":["R Agerri, G Rigau","R Agerri, G Rigau - Proceedings of the Iberian Languages Evaluation …, 2020"],"snippet":"… Page 3. of Common Crawl text … The biggest update that XLM-Roberta offers is a significantly increased amount of training data, 2.5TB of Common Crawl clean data [6]. As for BERT, in this paper we use the base version of XLM-RoBERTa …","url":["http://ceur-ws.org/Vol-2664/capitel_paper2.pdf","https://ragerri.github.io/files/ixaera-capitel2020.pdf"]}
-{"year":"2020","title":"Projecting named entity recognizers from resource-rich to resource-poor languages without annotated or parallel corpora","authors":["J Hou"],"snippet":"Page 1. Projecting named entity recognizers from resource-rich to resourcepoor languages without annotated or parallel corpora Hou, Jue Helsinki October 20, 2019 UNIVERSITY OF HELSINKI Department of Computer …","url":["https://helda.helsinki.fi/bitstream/handle/10138/310012/Jue_Hou-Master_s_Thesis-v2.1.pdf?sequence=2&isAllowed=y"]}
-{"year":"2020","title":"PTT5: Pretraining and validating the T5 model on Brazilian Portuguese data","authors":["D Carmo, M Piau, I Campiotti, R Nogueira, R Lotufo - arXiv preprint arXiv:2008.09144, 2020"],"snippet":"… The original T5 vocabulary uses the SentencePiece library [7] using English, German, French, and Romanian web pages from Common Crawl.1 We use a similar procedure to create our Portuguese vocabulary: we train …","url":["https://arxiv.org/pdf/2008.09144"]}
-{"year":"2020","title":"PublishInCovid19 at the FinSBD-2 Task: Sentence and List Extraction in Noisy PDF Text Using a Hybrid Deep Learning and Rule-Based Approach","authors":["J Singh - Proceedings of the Second Workshop on Financial …, 2020"],"snippet":"… For the pretrained word embeddings, we use GloVE 6 which are trained on large Common Crawl dataset and can effectively represent 84 billion cased tokens. To train the BERT for our task, we fine-tune a pre-trained model, namely bert-base-cased …","url":["https://www.aclweb.org/anthology/2020.finnlp-1.pdf#page=63"]}
-{"year":"2020","title":"Punctuation Prediction in Spontaneous Conversations: Can We Mitigate ASR Errors with Retrofitted Word Embeddings?","authors":["Ł Augustyniak, P Szymanski, M Morzy, P Zelasko… - arXiv preprint arXiv …, 2020"],"snippet":"… In this work, we use pre-trained GloVe embeddings trained on the Common Crawl dataset consisting of 2.6 billion textual documents … In our case, the punctuation in conversational transcripts is substantially different from the …","url":["https://arxiv.org/pdf/2004.05985"]}
-{"year":"2020","title":"PyChain: A Fully Parallelized PyTorch Implementation of LF-MMI for End-to-End ASR","authors":["Y Shao, Y Wang, D Povey, S Khudanpur - arXiv preprint arXiv:2005.09824, 2020"],"snippet":"… We hope that our experience with PYCHAIN will inspire other efforts to build next-generation hybrid ASR tools. 812k hours AM train set and common crawl LM. 9Data augmentation and pre-trained on LibriSpeech …","url":["https://arxiv.org/pdf/2005.09824"]}
-{"year":"2020","title":"Quality and Relevance Metrics for Selection of Multimodal Pretraining Data","authors":["R Rao, S Rao, E Nouri, D Dey, A Celikyilmaz, B Dolan - Proceedings of the IEEE/CVF …, 2020"],"snippet":"… The GloVe vectors used are pretrained on 840 billion tokens from Common Crawl. Let o ∈ Oi be the set of objects de- tected by the RCNN for a given image i, w ∈ d be the set 0 100 200 300 400 500 ConceptualCaptions Ngram …","url":["http://openaccess.thecvf.com/content_CVPRW_2020/papers/w56/Rao_Quality_and_Relevance_Metrics_for_Selection_of_Multimodal_Pretraining_Data_CVPRW_2020_paper.pdf"]}
-{"year":"2020","title":"Quality Estimation for Machine Translation with Multi-granularity Interaction⋆","authors":["K Tian, J Zhang"],"snippet":"… (7) 4 Experiments 4.1 Dataset The bilingual parallel corpus that we use for pre-trained multilingual BERT is officially released by the WMT17 Shared Task: Machine Translation of News1, in- cluding Europarl v7, Common Crawl …","url":["http://sc.cipsc.org.cn/mt/conference/2020/papers/T20-1005.pdf"]}
-{"year":"2020","title":"Quality Evaluation","authors":["JM Gomez-Perez, R Denaux, A Garcia-Silva - A Practical Guide to Hybrid Natural …, 2020"],"snippet":"… Besides the embeddings trained by us, we also include, as part of our study, several pre-trained embeddings, notably the GloVe embeddings for CommonCrawl— code glove_840B provided by Stanford11 —fastText …","url":["https://link.springer.com/chapter/10.1007/978-3-030-44830-1_7"]}
-{"year":"2020","title":"Query focused abstractive summarization using BERTSUM model","authors":["DM Abdullah - 2020"],"snippet":"… Conneau et al. (2019) have introduced a multilingual masked language model from Facebook AI. This model has been trained on 2.5 TB of newly created clean CommonCrawl (Wenzek et al., 2019) data in 100 languages. The model has shown state-of-the-art results …","url":["https://opus.uleth.ca/bitstream/handle/10133/5760/ABDULLAH_DEEN_MOHAMMAD_MSC_2020.pdf?sequence=1"]}
-{"year":"2020","title":"Question Answering for Comparative Questions with GPT-2","authors":["B Sievers"],"snippet":"… https://www.microsoft.com/en-us/research/blog/ turing-nlg-a-17-billion-parameter-languagemodel-by-microsoft/, accessed: 6.3.2020 3. Bevendorff, J., Stein, B., Hagen, M., Potthast, M.: Elastic chatnoir: search engine for the clueweb and the common crawl …","url":["http://ceur-ws.org/Vol-2696/paper_213.pdf"]}
-{"year":"2020","title":"Question Answering When Knowledge Bases are Incomplete","authors":["C Pradel, D Sileo, Á Rodrigo, A Peñas, E Agirre - International Conference of the …, 2020","E Agirre - … IR Meets Multilinguality, Multimodality, and Interaction …"],"snippet":"… with bag of word embeddings. We use FastText CommonCrawl word embeddings [10] 4 and a max pooling to produce the continuous bag of word representations of table columns and the question text. The column bag of words …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=IxP9DwAAQBAJ&oi=fnd&pg=PA43&dq=commoncrawl&ots=BCbV87DfTS&sig=kVIo_AYLn9xgMPpxB-rDuk1jzEg","https://link.springer.com/chapter/10.1007/978-3-030-58219-7_4"]}
-{"year":"2020","title":"Question Type Classification Methods Comparison","authors":["T Seidakhmetov - arXiv preprint arXiv:2001.00571, 2020"],"snippet":"… The GLoVe vectors were pre-trained using 840 billion tokens from Common Crawl, and each token is mapped into a 300-dimensional vector [3]. Xembeddings = GloveEmbedding( Xword) ∈ RNxDword where Dword is a number of dimensions of a word vector …","url":["https://arxiv.org/pdf/2001.00571"]}
-{"year":"2020","title":"Questioning the Use of Bilingual Lexicon Induction as an Evaluation Task for Bilingual Word Embeddings","authors":["B Marie, A Fujita"],"snippet":"… gual word embeddings. In fact, this corpus was significantly smaller than the Wikipedia corpora for all the other languages, and than the Finnish Common Crawl corpus used to train Finnish Vecmap-emb. Another finding is …","url":["https://www.anlp.jp/proceedings/annual_meeting/2020/pdf_dir/P5-14.pdf"]}
-{"year":"2020","title":"REALTOXICITYPROMPTS: Evaluating Neural Toxic Degeneration in Language Models","authors":["S Gehman, S Gururangan, M Sap, Y Choi, NA Smith - arXiv preprint arXiv …, 2020","SGS Gururangan, MSY Choi, NA Smith"],"snippet":"… GPT-2 (specifically, GPT-2-small; Radford et al., 2019), is a similarly sized model pretrained on OPENAI-WT, which contains 40GB of English web text and is described in §6.7 GPT-3 (Brown et al., 2020) is pretrained on a mix …","url":["https://arxiv.org/pdf/2009.11462","https://homes.cs.washington.edu/~msap/pdfs/gehman2020realtoxicityprompts.pdf"]}
-{"year":"2020","title":"Recent Trends in the Use of Deep Learning Models for Grammar Error Handling","authors":["M Naghshnejad, T Joshi, VN Nair - arXiv preprint arXiv:2009.02358, 2020"],"snippet":"Page 1. 1 Recent Trends in the Use of Deep Learning Models for Grammar Error Handling Mina Naghshnejad1, Tarun Joshi, and Vijayan N. Nair Corporate Model Risk, Wells Fargo2 Abstract Grammar error handling (GEH) is …","url":["https://arxiv.org/pdf/2009.02358"]}
-{"year":"2020","title":"Recipes for Adapting Pre-trained Monolingual and Multilingual Models to Machine Translation","authors":["AC Stickland, X Li, M Ghazvininejad - arXiv preprint arXiv:2004.14911, 2020"],"snippet":"Page 1. Recipes for Adapting Pre-trained Monolingual and Multilingual Models to Machine Translation Asa Cooper Stickland♣ Xian Li♠ ♣ University of Edinburgh, ♠ Facebook AI a.cooper.stickland@ed.ac.uk, {xianl,ghazvini}@fb.com Marjan Ghazvininejad♠ Abstract …","url":["https://arxiv.org/pdf/2004.14911"]}
-{"year":"2020","title":"ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning","authors":["W Yu, Z Jiang, Y Dong, J Feng - arXiv preprint arXiv:2002.04326, 2020"],"snippet":"Page 1. Published as a conference paper at ICLR 2020 RECLOR: AREADING COMPREHENSION DATASET REQUIRING LOGICAL REASONING Weihao Yu∗, Zihang Jiang∗, Yanfei Dong & Jiashi Feng National University …","url":["https://arxiv.org/pdf/2002.04326"]}
-{"year":"2020","title":"Recognai's Working Notes for CANTEMIST-NER Track","authors":["DC Fidalgo, D Vila-Suero, FA Montes - … of the Iberian Languages Evaluation Forum …, 2020"],"snippet":"… light-weight solution regarding the pretrained component. For this reason we chose the pretrained Spanish word vectors provided by FastText[4]. These vectors encompass 2 million words that were trained on Common Crawl4 …","url":["http://ceur-ws.org/Vol-2664/cantemist_paper4.pdf"]}
-{"year":"2020","title":"Reducing Language Biases in Visual Question Answering with Visually-Grounded Question Encoder","authors":["G KV, A Mittal - arXiv preprint arXiv:2007.06198, 2020"],"snippet":"Page 1. Reducing Language Biases in Visual Question Answering with Visually-Grounded Question Encoder Gouthaman KV and Anurag Mittal Indian Institute of Technology Madras, India {gkv,amittal}@cse.iitm.ac.in Abstract …","url":["https://arxiv.org/pdf/2007.06198"]}
-{"year":"2020","title":"Referring Image Segmentation via Cross-Modal Progressive Comprehension","authors":["S Huang, T Hui, S Liu, G Li, Y Wei, J Han, L Liu, B Li - … of the IEEE/CVF Conference on …, 2020"],"snippet":"Page 1. Referring Image Segmentation via Cross-Modal Progressive Comprehension Shaofei Huang1,2∗ Tianrui Hui1,2∗ Si Liu3† Guanbin Li4 Yunchao Wei5 Jizhong Han1,2 Luoqi Liu6 Bo Li3 1 Institute of Information Engineering …","url":["http://openaccess.thecvf.com/content_CVPR_2020/papers/Huang_Referring_Image_Segmentation_via_Cross-Modal_Progressive_Comprehension_CVPR_2020_paper.pdf"]}
-{"year":"2020","title":"Refinement of Unsupervised Cross-Lingual Word Embeddings","authors":["M Biesialska, MR Costa-jussà - arXiv preprint arXiv:2002.09213, 2020"],"snippet":"… Finnish. Monolingual embeddings of 300 di- mensions were created using Word2Vec3 [18] and were trained on WMT News Crawl (Spanish), WacKy crawling corpora (English, German), and Common Crawl (Finnish). To evaluate …","url":["https://arxiv.org/pdf/2002.09213"]}
-{"year":"2020","title":"ReINTEL: A Multimodal Data Challenge for Responsible Information Identification on Social Network Sites","authors":["DT Le, XS Vu, ND To, HQ Nguyen, TT Nguyen, L Le… - arXiv preprint arXiv …, 2020"],"snippet":"… Word2VecVN (Vu, 2016) x Trained on 7GB texts of Vietnamese news FastText (Vietnamese version) (Joulin et al., 2016) x Trained on Vietnamese texts of the CommonCrawl corpus ETNLP (Vu et al., 2019) x Trained on 1GB texts of Vietnamese Wikipedia …","url":["https://arxiv.org/pdf/2012.08895"]}
-{"year":"2020","title":"Related Tasks can Share! A Multi-task Framework for Affective language","authors":["KS Deep, MS Akhtar, A Ekbal, P Bhattacharyya - arXiv preprint arXiv:2002.02154, 2020"],"snippet":"… 3. Character-level embeddings2: Character-level embeddings are trained over common crawl glove corpus providing 300 dimensional vectors for each character (used in case if word is not present in other two embeddings) …","url":["https://arxiv.org/pdf/2002.02154"]}
-{"year":"2020","title":"Relational and Fine-Grained Argument Mining","authors":["D Trautmann, M Fromm, V Tresp, T Seidl, H Schütze - Datenbank-Spektrum, 2020"],"snippet":"… Crowdworkers had the task of selecting argumentative spans for a given set of topics and topic related sentences. The sentences were from textual data extracted from Common Crawl Footnote 6 for a predefined list of eight …","url":["https://link.springer.com/article/10.1007/s13222-020-00341-z"]}
-{"year":"2020","title":"Relational Databases and SQL Language","authors":["JM Patel - Getting Structured Data from the Internet, 2020"],"snippet":"… itself. We are mainly discussing PostgreSQL here so that you can scale up to 64 TB if you decide to index large portions of common crawl datasets for creating a backlinks and news database in Chapters 6 and 7, respectively …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-6576-5_5"]}
-{"year":"2020","title":"Representation learning for input classification via topic sparse autoencoder and entity embedding","authors":["D Li, J Zhang, P Li - US Patent App. 16/691,554, 2020"],"snippet":"US20200184339A1 - Representation learning for input classification via topic sparse autoencoder and entity embedding - Google Patents. Representation learning for input classification via topic sparse autoencoder and entity embedding. Download PDF Info …","url":["https://patents.google.com/patent/US20200184339A1/en"]}
-{"year":"2020","title":"Reproducible Extraction of Cross-lingual Topics (rectr)","authors":["CH Chan, J Zeng, H Wessler, M Jungblut, K Welbers… - … Methods and Measures, 2020"],"snippet":"… 17 Researchers at Facebook Research created these aligned word embeddings by first training fastText word embeddings (Bojanowski et al., 2017) using Wikipedia and Common Crawl articles of each individual …","url":["https://www.tandfonline.com/doi/abs/10.1080/19312458.2020.1812555"]}
-{"year":"2020","title":"Research Challenges in Designing Differentially Private Text Generation Mechanisms","authors":["O Feyisetan, A Aggarwal, Z Xu, N Teissier - arXiv preprint arXiv:2012.05403, 2020"],"snippet":"… A natural way to “bias” an exponential mechanism without changing its privacy properties is to modulate it with a public “prior” µ(z). For example, such a prior can be constructed over a publicly available corpus such as Wikipedia or Common Crawl …","url":["https://arxiv.org/pdf/2012.05403"]}
-{"year":"2020","title":"Residual Energy-Based Models for Text Generation","authors":["Y Deng, A Bakhtin, M Ott, A Szlam, MA Ranzato - arXiv preprint arXiv:2004.11714, 2020"],"snippet":"… Page 6. Published as a conference paper at ICLR 2020 genres, totaling about half a billion words. The latter is a de-duplicated subset of the English portion of the CommonCrawl news dataset (Nagel, 2016), which totals around 16 Billion words …","url":["https://arxiv.org/pdf/2004.11714"]}
-{"year":"2020","title":"Rethinking embedding coupling in pre-trained language models","authors":["HW Chung, T Févry, H Tsai, M Johnson, S Ruder - arXiv preprint arXiv:2010.12821, 2020"],"snippet":"Page 1. Preprint. Under review. RETHINKING EMBEDDING COUPLING IN PRE-TRAINED LANGUAGE MODELS Hyung Won Chung∗† Google Research hwchung@google.com Thibault Févry∗† thibaultfevry@gmail …","url":["https://arxiv.org/pdf/2010.12821"]}
-{"year":"2020","title":"Rethinking Evaluation in ASR: Are Our Models Robust Enough?","authors":["T Likhomanenko, Q Xu, V Pratap, P Tomasello, J Kahn… - arXiv preprint arXiv …, 2020"],"snippet":"… only; for TL – both train transcriptions and provided LM data. We also train a 4-gram LM on Common Crawl (CC) data with 200k top words and pruning of all 3,4-grams appearing once. Perplexity of all LMs is shown in Table 2 …","url":["https://arxiv.org/pdf/2010.11745"]}
-{"year":"2020","title":"Retrieving Comparative Arguments using Deep Pre-trained Language Models and NLU","authors":["V Chekalina, A Panchenko"],"snippet":"… ChatNoir is an Elasticsearch-based5 engine providing access to nearly 3 billion web pages from ClueWeb and Common Crawl corpora … ACM. 2. J. Bevendorff, B. Stein, M. Hagen, and M. Potthast. Elastic ChatNoir: Search …","url":["http://ceur-ws.org/Vol-2696/paper_210.pdf"]}
-{"year":"2020","title":"Reusing a Pretrained Language Model on Languages with Limited Corpora for Unsupervised NMT","authors":["A Chronopoulou, D Stojanovski, A Fraser - arXiv preprint arXiv:2009.07610, 2020"],"snippet":"… We use 68M En sentences from NewsCrawl, 2.4M Mk and 4M Sq, both from CommonCrawl and Wikipedia … Second, in En- De, we use high-quality corpora for both languages (NewsCrawl), whereas Mk and Sq are trained on low-quality CommonCrawl data …","url":["https://arxiv.org/pdf/2009.07610"]}
-{"year":"2020","title":"Review of the Recent Techniques for Learning Commonsense Knowledge applied to the Winograd Schema Challenge","authors":["A Koleva"],"snippet":"… 4 A Combined Approach Prakash et al. [2], to the best of our knowledge, are the first ones to combine methods from KRR with methods from ML such as language models. They propose a framework in which four different …","url":["http://ecai2020.eu/papers/1513_paper.pdf"]}
-{"year":"2020","title":"Review rating prediction framework using deep learning","authors":["BH Ahmed, AS Ghabayen - Journal of Ambient Intelligence and Humanized …, 2020"],"snippet":"… word representation) embedding. There are several Glove embeddings from different sources, such as Twitter, Wikipedia or the common crawl. We utilized we utilize the Glove embedding trained by (Pennington et al. 2014) on …","url":["https://link.springer.com/article/10.1007/s12652-020-01807-4"]}
-{"year":"2020","title":"Revisiting Round-Trip Translation for Quality Estimation","authors":["J Moon, H Cho, EL Park - arXiv preprint arXiv:2004.13937, 2020"],"snippet":"Page 1. Revisiting Round-Trip Translation for Quality Estimation Jihyung Moon Naver Papago Hyunchang Cho Naver Papago {jihyung.moon, hyunchang.cho, lucypark}@navercorp.com Eunjeong L. Park Naver Papago Abstract …","url":["https://arxiv.org/pdf/2004.13937"]}
-{"year":"2020","title":"RobBERT: a Dutch RoBERTa-based Language Model","authors":["P Delobelle, T Winters, B Berendt - arXiv preprint arXiv:2001.06286, 2020"],"snippet":"… 3.1 Data We pre-trained our model on the Dutch section of the OSCAR corpus, a large multilingual corpus which was obtained by language classification in the Common Crawl corpus (Ortiz Suárez et al., 2019). This Dutch corpus …","url":["https://arxiv.org/pdf/2001.06286"]}
-{"year":"2020","title":"Robust Cross-lingual Embeddings from Parallel Sentences","authors":["A Sabet, P Gupta, JB Cordonnier, R West, M Jaggi - arXiv preprint arXiv:1912.12481, 2019"],"snippet":"… MUSE 0.38 0.30 0.74 0.64 RCSLS 0.38 0.30 0.74 0.64 FASTTEXTCommon Crawl 0.49 0.32 0.75 0.57 BIVEC 0.40 0.36 0.70 0.60 … We also include FASTTEXT monolingual vectors trained on CommonCrawl data (Grave et …","url":["https://arxiv.org/pdf/1912.12481"]}
-{"year":"2020","title":"Robust Prediction of Punctuation and Truecasing for Medical ASR","authors":["M Sunkara, S Ronanki, K Dixit, S Bodapati, K Kirchhoff - Proceedings of the First …, 2020","MSSRK Dixit, SBK Kirchhoff - ACL 2020, 2020"],"snippet":"… But just like any other model, these Language Models are biased by their training data. In particular, they are typically trained on data that is easily available in large quantities on the internet eg Wikipedia, CommonCrawl etc …","url":["https://www.aclweb.org/anthology/2020.nlpmc-1.8.pdf","https://www.aclweb.org/anthology/2020.nlpmc-1.pdf#page=65"]}
-{"year":"2020","title":"Robust Prediction of Punctuation and Truecasingfor Medical ASR","authors":["M Sunkara, S Ronanki, K Dixit, S Bodapati, K Kirchhoff - arXiv preprint arXiv …, 2020"],"snippet":"… But just like any other model, these Language Models are biased by their training data. In particular, they are typically trained on data that is easily available in large quantities on the internet eg Wikipedia, CommonCrawl etc …","url":["https://arxiv.org/pdf/2007.02025"]}
-{"year":"2020","title":"Russian-English Bidirectional Machine Translation System","authors":["A Xv, W Chao - Ariel"],"snippet":"… For the monolingual data we use English and Russian Newscrawl as well as a filtered part of Commoncrawl in Russian … Russian is relatively smaller than that of English, we have to augment the Newscrawl data for Russian …","url":["http://statmt.org/wmt20/pdf/2020.wmt-1.35.pdf"]}
-{"year":"2020","title":"Samsung R&D Institute Poland submission to WMT20 News Translation Task","authors":["M Krubinski, M Chochowski, B Boczek, M Koszowski… - Proceedings of the Fifth …, 2020"],"snippet":"… Pretraining a complete encoder-decoder model allows for later direct fine-tuning on the translation ob- jective, with parallel corpora. In our experiment, we sampled 250M sentences from CommonCrawl for Czech, English and Polish (ie 750M in total) …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.16.pdf"]}
-{"year":"2020","title":"SandiDoc at CLEF 2020-Consumer Health Search: AdHoc IR Task","authors":["S Seneviratne, E Daskalaki, M Zakir - Conference and Labs of the Evaluation (CLEF) …, 2020"],"snippet":"… respectively. 2 Resources 2.1 Dataset The document collection used in the document retrieval task was acquired by the common crawl dump of 2018-19. This included web pages of the formats such as HTML, XHTML, XML. The …","url":["http://www.dei.unipd.it/~ferro/CLEF-WN-Drafts/CLEF2020/paper_160.pdf"]}
-{"year":"2020","title":"SardiStance@ EVALITA2020: Overview of the Task on Stance Detection in Italian Tweets","authors":["AT Cignarella, M Lai, C Bosco, V Patti, P Rosso - … of the 7th Evaluation Campaign of …, 2020"],"snippet":"… In particular, they trained three classifiers based respectively on SENTIPOLC 2016 (Barbieri et al., 2016) for sentiment analysis classification, on HaSpeeDe 2018 (Bosco et al., 2018) 4https://huggingface.co/Musixmatch/ umberto-commoncrawl-cased-v1 …","url":["http://ceur-ws.org/Vol-2765/paper159.pdf"]}
-{"year":"2020","title":"SberQuAD–Russian Reading Comprehension Dataset: Description and Analysis","authors":["P Braslavski - … IR Meets Multilinguality, Multimodality, and Interaction …"],"snippet":"… We tokenized text using spaCy. 12 To initialize the embedding layer for BiDAF, DocQA, DrQA, and R-Net we use Russian casesensitive fastText embeddings trained on Common Crawl and Wikipedia. 13 This initialization is used for both questions and paragraphs …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=IxP9DwAAQBAJ&oi=fnd&pg=PA3&dq=commoncrawl&ots=BCbV87DfTS&sig=E3mWPymZbBAvDLn8azUpJimpaMs"]}
-{"year":"2020","title":"Scalable Cross Lingual Pivots to Model Pronoun Gender for Translation","authors":["K Webster, E Pitler - arXiv preprint arXiv:2006.08881, 2020"],"snippet":"… glish was most recently contested at WMT'132 (Bojaretal., 2013), which offered participants 14,980,513 sentence pairs from Eu- roparl3 (Habash et al., 2017), Common Crawl (Smith et al., 2013), the United Nations cor …","url":["https://arxiv.org/pdf/2006.08881"]}
-{"year":"2020","title":"Scalable, Multi-Constraint, Complex-Objective Graph Partitioning","authors":["GM Slota, C Root, K Devine, K Madduri… - IEEE Transactions on …, 2020"],"snippet":"Page 1. Scalable, Multi-Constraint, Complex-Objective Graph Partitioning GeorgeM.Slota ,CameronRoot,KarenDevine ,KameshMadduri , and Sivasankaran Rajamanickam Abstract—We introduce XTRAPULP, a distributed-memory …","url":["https://ieeexplore.ieee.org/abstract/document/9115834/"]}
-{"year":"2020","title":"Scaling Laws for Neural Language Models","authors":["J Kaplan, S McCandlish, T Henighan, TB Brown… - arXiv preprint arXiv …, 2020","OEIAY Need"],"snippet":"01/23/20 - We study empirical scaling laws for language model performance on the cross-entropy loss. The loss scales as a power-law with mode...","url":["https://arxiv.org/pdf/2001.08361","https://deepai.org/publication/scaling-laws-for-neural-language-models"]}
-{"year":"2020","title":"Scientific Question Answering with AAN","authors":["K Mueller"],"snippet":"… have easy to understand language as well as little background knowledge required. They then used web data provided by Common Crawl to find supporting web documents from which to draw information and construct …","url":["https://zoo.cs.yale.edu/classes/cs290/19-20a/mueller.keaton.kim6/Keaton_Mueller_CPSC290_Final_Report.pdf"]}
-{"year":"2020","title":"Scones: Towards Conversational Authoring of Sketches","authors":["F Huang, D Ha, E Schoop, J Canny"],"snippet":"… detail in Section 4.1. For each text token t, we use a 300-dimensional GLoVe vector trained on 42B tokens from the Common Crawl dataset [22] to semantically represent these words in the instructions. To train the Transformer …","url":["http://people.eecs.berkeley.edu/~eschoop/docs/scones.pdf"]}
-{"year":"2020","title":"Scoring Dimension-Level Job Performance From Narrative Comments: Validity and Generalizability When Using Natural Language Processing","authors":["AB Speer - Organizational Research Methods, 2020"],"snippet":"Performance appraisal narratives are qualitative descriptions of employee job performance. This data source has seen increased research attention due to the ability to efficiently derive insights u...","url":["https://journals.sagepub.com/doi/abs/10.1177/1094428120930815"]}
-{"year":"2020","title":"SDRS: A new lossless dimensionality reduction for text corpora","authors":["IV de Mendizabal, V Basto-Fernandes, E Ezpeleta… - Information Processing & …, 2020"],"snippet":"… Clueweb 12, Web (html) pages, English, unknown, 870M. Common Crawl Data, Web (html) pages, multilingual, 100% spam, 9 Billion in 2014 and increasing. YouTube Comments Dataset, Youtube comments, multilingual, 7% spam, 6M …","url":["https://www.sciencedirect.com/science/article/pii/S0306457319314694"]}
-{"year":"2020","title":"Searching the Web for Cross-lingual Parallel Data","authors":["A El-Kishky, P Koehn, H Schwenk - Proceedings of the 43rd International ACM SIGIR …, 2020"],"snippet":"… and Tokenization – CommonCrawl Preprocessing Code • Open-source Code for Generating Cross-lingual Datasets – Code for Generating High-quality Monolingual Data from CommonCrawl – Code for Generating …","url":["https://dl.acm.org/doi/abs/10.1145/3397271.3401417"]}
-{"year":"2020","title":"SEDAR: a Large Scale French-English Financial Domain Parallel Corpus","authors":["A Ghaddar, P Langlais - Proceedings of The 12th Language Resources and …, 2020"],"snippet":"… It contains 40.8M sentence pairs extracted from five datasets that cover various domains: EUROPARL V7 (Koehn, 2005), UNITED NATIONS CORPUS (Eisele and Chen, 2010), COMMON CRAWL CORPUS, NEWS COMMENTARY, and 109 FRENCH-ENGLISH corpus …","url":["https://www.aclweb.org/anthology/2020.lrec-1.442.pdf"]}
-{"year":"2020","title":"Seeking Meaning: Examining a Cross-situational Solution to Learn Action Verbs Using Human Simulation Paradigm","authors":["Y Zhang, A Amatuni, E Cain, C Yu"],"snippet":"… of words in a given corpus. We used the GloVe model pretrained on 840B tokens of Common Crawl text to create semantic distance measures (Pennington, Socher & Manning, 2014). We discovered that both semantic knowledge …","url":["https://cognitivesciencesociety.org/cogsci20/papers/0705/0705.pdf"]}
-{"year":"2020","title":"Self-training Improves Pre-training for Natural Language Understanding","authors":["J Du, E Grave, B Gunel, V Chaudhary, O Celebi, M Auli… - arXiv preprint arXiv …, 2020"],"snippet":"… As a large-scale external bank of unannotated sentences, we extract and filter text from CommonCrawl 1 (Wenzek et al., 2019) … CommonCrawl data contains a wide variety of domains and text styles which makes it a good general-purpose corpus …","url":["https://arxiv.org/pdf/2010.02194"]}
-{"year":"2020","title":"Semantic image retrieval","authors":["T Berg, PN Belhumeur - US Patent 10,769,502, 2020","T Berg, PN Belhumeur - US Patent App. 16/999,616, 2020"],"snippet":"… GloVe. Common Crawl is a public repository of web crawl data (eg, blogs, news, and comments) available on the internet in the commoncrawl.org domain, the entire contents of which is hereby incorporated by reference. GloVe …","url":["https://patents.google.com/patent/US20200380320A1/en","https://www.freepatentsonline.com/10769502.html"]}
-{"year":"2020","title":"Semantic Matching: Dynamic Composition of Matcher Ensembles for Ontology Alignment","authors":["A Vennesland - 2020"],"snippet":"Page 1. ISBN 978-82-326-4842-9 (printed ver.) ISBN 978-82-326-4843- 6 (electronic ver.) ISSN 1503-8181 Doctoral theses at NTNU, 2020:247 Audun Vennesland Semantic Matching Dynamic Composition of Matcher …","url":["https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/handle/11250/2674337/Audun%20Vennesland_PhD.pdf?sequence=1"]}
-{"year":"2020","title":"Semantic Networks for Engineering Design: A Survey","authors":["J Han, S Sarica, F Shi, J Luo - arXiv preprint arXiv:2012.07060, 2020"],"snippet":"… relations No Pre-trained word2vec (Mikolov et al., 2013) Unsupervised Google News Cosine similarity No Pre-trained GloVe (Pennington et al., 2014) Unsupervised Wikipedia, Gigaword, Common Crawl Cosine similarity No B-Link …","url":["https://arxiv.org/pdf/2012.07060"]}
-{"year":"2020","title":"Semantic Norm Extrapolation is a Missing Data Problem","authors":["B Snefjella, I Blank - 2020"],"snippet":"Page 1. DRAFT Running head: SEMANTIC NORM EXTRAPOLATION 1 Semantic Norm Extrapolation is a Missing Data Problem Bryor Snefjella & Idan Blank University of California, Los Angeles Department of Psychology Author Note …","url":["https://psyarxiv.com/y2gav/download?format=pdf"]}
-{"year":"2020","title":"Semantic Recommendations of Books Using Recurrent Neural Networks","authors":["M Nitu, S Ruseti, M Dascalu, S Tomescu - Ludic, Co-design and Tools Supporting Smart …"],"snippet":"… We conducted the experiments using pre-trained FastText embeddings for Romanian language. The embedding model consists of 2 million word vectors trained on Common Crawl and Wikipedia (approx. 600 billion tokens). Page 239. 240 M. Nitu et al. Fig …","url":["https://link.springer.com/content/pdf/10.1007/978-981-15-7383-5.pdf#page=234"]}
-{"year":"2020","title":"Semantic-Based Algorithm for Scoring Alternative Uses Tests (AUT)","authors":["C Stevenson"],"snippet":"… Page 6. Each response was mapped to a word vector in 300 dimensions using a fastText pretrained model for Dutch. This model was trained on Wikipedia and Common Crawl data, using CBOW model with character …","url":["http://modelingcreativity.org/blog/wp-content/uploads/2020/07/Tsai_Y_BDS_Thesis_report_11695986_PML.pdf"]}
-{"year":"2020","title":"Semantical Search Term Clustering for Performance Prediction","authors":["R Coenders"],"snippet":"Page 1. Eindhoven University of Technology MASTER Semantical search term clustering for performance prediction Coenders, R. Award date: 2019 Link to publication Disclaimer This document contains a student thesis (bachelor's …","url":["https://research.tue.nl/files/139495213/Thesis_RikCoenders_Aug2019.pdf"]}
-{"year":"2020","title":"Semi-autonomous methodology to validate and update customer needs database through text data analytics","authors":["AM Bigorra, O Isaksson, M Karlberg - International Journal of Information …, 2020"],"snippet":"… Two different pre-trained word vectors based on 1 and 2 million English words from Wikipedia and Common Crawl are considered and they are referred along the rest of the presented paper as emb1 and emb2, respectively 3 …","url":["https://www.sciencedirect.com/science/article/pii/S0268401219300817"]}
-{"year":"2020","title":"SemSeq: A Regime for Training Widely-Applicable Word-Sequence Encoders","authors":["H Tsuyuki, TY Ogawa, HTB Kobayashi - … : 16th International Conference of the Pacific …, 2020"]}
-{"year":"2020","title":"Sense Inventories for Arabic Texts","authors":["M Alian, A Awajan"],"snippet":"… E. Fasttext pre-trained embeddings Arabic Fasttext embeddings are provided by Grave et al. [16]. These embeddings are resulted from training on Wikipedia and Common Crawl corpus. They have used an extension of the Fasttext model with subword information …","url":["https://www.researchgate.net/profile/Marwah_Alian/publication/346785930_Sense_Inventories_for_Arabic_Texts/links/5fd0a6a745851568d14da099/Sense-Inventories-for-Arabic-Texts.pdf"]}
-{"year":"2020","title":"Sentence Matching with Deep Self-attention and Co-attention Features","authors":["Z Wang, D Yan - 2020","Z Wang, D Yan - … Conference on Knowledge Science, Engineering and …, 2021"],"snippet":"… 4.1 Implementation Details. In our experiments, word embedding vectors are initialized with 300d GloVe vectors pre-trained from the 840B Common Crawl corpus. Embeddings of out of the vocabulary of GloVe is initialized …","url":["https://link.springer.com/chapter/10.1007/978-3-030-82147-0_45","https://openreview.net/pdf?id=EEV7-ruXM5H"]}
-{"year":"2020","title":"Sentence-Embedding and Similarity via Hybrid Bidirectional-LSTM and CNN Utilizing Weighted-Pooling Attention","authors":["D HUANG, A AHMED, SY ARAFAT, KI RASHID… - IEICE TRANSACTIONS on …, 2020"],"snippet":"… bag-of-words architecture. • A GloVe is a 300-dimensional word embedding model learned on aggregated global word co-occurrence statistics from Common Crawl (840 billion to- kens) [32]. 4.2 Datasets The datasets are concisely …","url":["https://www.jstage.jst.go.jp/article/transinf/E103.D/10/E103.D_2018EDP7410/_pdf"]}
-{"year":"2020","title":"Sentiment Analysis Approach Based on Combination of Word Embedding Techniques","authors":["I Kaibi, H Satori - Embedded Systems and Artificial Intelligence, 2020"],"snippet":"… The fastText pre-trained word vectors is a high-quality word representation for 157 languages, two sources of data are used to train fastText pre-trained models: the free online encyclopedia Wikipedia and data from the common crawl project …","url":["https://link.springer.com/chapter/10.1007/978-981-15-0947-6_76"]}
-{"year":"2020","title":"Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology: Using Natural Language Processing and Deep Learning for Decision Aid","authors":["C Zuheros, E Martínez-Cámara, E Herrera-Viedma… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. arXiv:2008.00032v1 [cs.CL] 31 Jul 2020 Sentiment Analysis based Multi-person Multi-criteria Decision Making Methodology: Using Natural Language Processing and Deep Learning for Decision Aid Cristina Zuheros1 …","url":["https://arxiv.org/pdf/2008.00032"]}
-{"year":"2020","title":"Sentiment analysis for customer relationship management: an incremental learning approach","authors":["N Capuano, L Greco, P Ritrovato, M Vento - Applied Intelligence, 2020"],"snippet":"… text corpora. In particular, Universal Dependencies and WikiNER corpora [31] were used for Italian, while OntoNotes [32] and Common Crawl Footnote 3 corpora were used for English. The classification model. Once the WEs …","url":["https://link.springer.com/article/10.1007/s10489-020-01984-x"]}
-{"year":"2020","title":"Sentiment Analysis for Hinglish Code-mixed Tweets by means of Cross-lingual Word Embeddings","authors":["P Singh, E Lefever - LREC 2020–4th Workshop on Computational …, 2020"],"snippet":"… This can probably be attributed to the quality of the monolingual embeddings, since the English embeddings were trained on the vast Common Crawl data while the Code-Mixed embeddings were trained on a little more than 100,000 scraped tweets …","url":["https://biblio.ugent.be/publication/8662137/file/8662140"]}
-{"year":"2020","title":"Sentiment Aware Word Embeddings Using Refinement and Senti-Contextualized Learning Approach","authors":["B Naderalvojoud, EA Sezer - Neurocomputing, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0925231220304811"]}
-{"year":"2020","title":"Sentiment detection with FedMD: Federated Learning via Model Distillation","authors":["PTG Momcheva"],"snippet":"… value due to the nature of tweets - they are short, have little context and contain misspelled and shortened words, all of which stands in general contrast to the GloVe training data and logic, which was based on structured …","url":["http://ceur-ws.org/Vol-2656/paper24.pdf"]}
-{"year":"2020","title":"Seq2Seq Models for Recommending Short Text Conversations","authors":["J Torres, C Vaca, L Terán, CL Abad - Expert Systems with Applications, 2020"],"snippet":"… to a lower-dimensional representation ( w ∈ R d ). For the initialization of the word embeddings, we use the pre-trained vectors provided by Mikolov, Grave, Bojanowski, Puhrsch, and Joulin (2018), which consist of 2 …","url":["https://www.sciencedirect.com/science/article/pii/S0957417420300956"]}
-{"year":"2020","title":"Sequential Latent Knowledge Selection for Knowledge-Grounded Dialogue","authors":["B Kim, J Ahn, G Kim - arXiv preprint arXiv:2002.07510, 2020"],"snippet":"Page 1. Published as a conference paper at ICLR 2020 SEQUENTIAL LATENT KNOWLEDGE SELECTION FOR KNOWLEDGE-GROUNDED DIALOGUE Byeongchang Kim Jaewoo Ahn Gunhee Kim Department of Computer …","url":["https://arxiv.org/pdf/2002.07510"]}
-{"year":"2020","title":"Sequential Neural Networks for Noetic End-to-End Response Selection","authors":["Q Chen, W Wang - Computer Speech & Language, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S088523082030005X"]}
-{"year":"2020","title":"Sequential Transfer Learning for Event Detection and Key Sentence Extraction","authors":["A Ollagnier, H Williams"],"snippet":"… Training is performed on the base version trained on cased text. XLNet [22] 12-layer, 768-hidden, 12-heads 110M parameters Pre-trained models are based on English texts from Wikipedia, BooksCorpus, Giga5, ClueWeb, and Common Crawl …","url":["https://www.researchgate.net/profile/Ollagnier_Anais/publication/344440133_Sequential_Transfer_Learning_for_Event_Detection_and_Key_Sentence_Extraction/links/5f75ad1a299bf1b53e0397ce/Sequential-Transfer-Learning-for-Event-Detection-and-Key-Sentence-Extraction.pdf"]}
-{"year":"2020","title":"Shopify in Germany: An analysis of a Canadian e-commerce platform's marketing strategy and activities in an international market.","authors":["K Howe-Patterson, I Schuiling"],"snippet":"Page 1. Available at: http://hdl.handle.net/2078.1/thesis:25661 [Downloaded 2020/09/25 at 09:14:22 ] \"Shopify in Germany: An analysis of a Canadian e-commerce platform's marketing strategy and activities in an international …","url":["https://dial.uclouvain.be/downloader/downloader.php?pid=thesis%3A25661&datastream=PDF_01&cover=cover-mem"]}
-{"year":"2020","title":"Sidecar: Augmenting Word Embedding Models with Expert Knowledge","authors":["M Lemay, D Shapiro, MK MacPherson, K Yee… - Future of Information and …, 2020"],"snippet":"… spaCy's en_core_web_lg GloVe model 8 , trained on Common Crawl 9. Facebook's crawl-300d-2M fastText model 10 , also trained on Common Crawl. All three models produce vectors of size 300. To generate vectors for the …","url":["https://link.springer.com/chapter/10.1007/978-3-030-39442-4_39"]}
-{"year":"2020","title":"Sights, titles and tags: mining a worldwide photo database for sightseeing","authors":["A Luberg, J Pindis, T Tammet"],"snippet":"… Explosion AI spaCy pretrained model [7]. We use a medium sized web code model. The model is based on Common Crawl and OntoNotes 5 [22] sources … Facebook fastText pretrained model [8]. The model is pretrained on Common Crawl and Wikipedia data …","url":["http://wims2020.sigappfr.org/wp-content/uploads/2020/06/WIMS'20/p149-Luberg.pdf"]}
-{"year":"2020","title":"SimAlign: High Quality Word Alignments without Parallel Training Data using Static and Contextualized Embeddings","authors":["MJ Sabet, P Dufter, H Schütze - arXiv preprint arXiv:2004.08728, 2020"],"snippet":"… In addition, we use XLM-RoBERTa base (Conneau et al., 2019), which is pretrained on 100 languages on CommonCrawl data. We denote alignments obtained using the embeddings from the i-th layer by XLM-R[i] …","url":["https://arxiv.org/pdf/2004.08728"]}
-{"year":"2020","title":"Similarity judgment within and across categories: A comprehensive model comparison","authors":["R Richie, S Bhatia - 2020"],"snippet":"… Google News 100B 300 None Magnitude Librarya fastText 600B Common Crawl FastText with Continuous Bag of Words (CBOW) … GloVe 840B Common Crawl GloVe Common Crawl 840B 300 None Magnitude Library Glove 840B Common Crawl, Paragram …","url":["https://psyarxiv.com/5pa9r/download"]}
-{"year":"2020","title":"Simulation Induces Durable, Extensive Changes to Self-knowledge","authors":["J Rubin-McGregor, Z Zhao, D Tamir - PsyArXiv. December, 2020"],"snippet":"Page 1. SIMULATION CHANGES SELF-KNOWLEDGE 1 1 2 3 4 5 6 Simulation Induces Durable, Extensive Changes to Self-Knowledge 7 Jordan Rubin-McGregora, Zidong Zhaoa, and Diana Tamira 8 aDepartment of …","url":["https://psyarxiv.com/m2wgk/download/?format=pdf"]}
-{"year":"2020","title":"SINAI at eHealth-KD Challenge 2020: Combining Word Embeddings for Named Entity Recognition in Spanish Medical Records","authors":["P López-Úbedaa, JM Perea-Ortegab…"],"snippet":"… we have used two specific pre-trained word embeddings: BETO [28], which follows a BERT model trained on a big Spanish corpus, and XLM-RoBERTa [29], which were generated by using a large multilingual language model …","url":["http://ceur-ws.org/Vol-2664/eHealth-KD_paper7.pdf"]}
-{"year":"2020","title":"Siva at WNUT-2020 Task 2: Fine-tuning Transformer Neural Networks for Identification of Informative Covid-19 Tweets","authors":["S Sai - Proceedings of the Sixth Workshop on Noisy User …, 2020"],"snippet":"… The base version of RoBERTa has 125M parameters, and the large version has 355M parameters. XLM-RoBERTa XLM-RoBERTa(Conneau et al., 2019) is a multilingual model trained on 2.5 TB data from CommonCrawl. This …","url":["https://www.aclweb.org/anthology/2020.wnut-1.45.pdf"]}
-{"year":"2020","title":"SJTU-NICT's Supervised and Unsupervised Neural Machine Translation Systems for the WMT20 News Translation Task","authors":["Z Li, H Zhao, R Wang, K Chen, M Utiyama, E Sumita - arXiv preprint arXiv …, 2020"],"snippet":"… In the supervised PL→EN translation direction, we based on the XLM framework to pre-train a Polish language model using common crawl and news crawl monolingual data, and proposed the XLM enhanced NMT model …","url":["https://arxiv.org/pdf/2010.05122"]}
-{"year":"2020","title":"SMAN: Stacked Multi-Modal Attention Network for Cross-Modal Image-Text Retrieval","authors":["BR Loss"],"snippet":"Page 1. warwick.ac.uk/lib-publications Manuscript version: Author's Accepted Manuscript The version presented in WRAP is the author's accepted manuscript and may differ from the published version or Version of Record. Persistent …","url":["https://pdfs.semanticscholar.org/7588/90bef9a1a85a25a1f6831a58f00a462476af.pdf"]}
-{"year":"2020","title":"SML: Semantic Meta-learning for Few-shot Semantic Segmentation","authors":["AK Pambala, T Dutta, S Biswas - arXiv preprint arXiv:2009.06680, 2020"],"snippet":"… Word2vec (Mikolov et al. 2013) is trained on Google News dataset (Wang, Ye, and Gupta 2018) which contains 3-million words; (2) FastText (Joulin et al. 2016) is trained on Common-Crawl dataset (Mikolov et al. 2018). We use these …","url":["https://arxiv.org/pdf/2009.06680"]}
-{"year":"2020","title":"SNK@ DANKMEMES: Leveraging Pretrained Embeddings for Multimodal Meme Detection","authors":["S Fiorucci - Proceedings of Seventh Evaluation Campaign of …, 2020"],"snippet":"… et al., 2018). Word embeddings are trained on Common Crawl and Wikipedia, using CBOW with positionweights, in dimension 300, with character n-grams of length 5, a window of size 5 and 10 negatives. We calculated the …","url":["http://ceur-ws.org/Vol-2765/paper121.pdf"]}
-{"year":"2020","title":"Social biases in word embeddings and their relation to human cognition","authors":["A Caliskan, M Lewis - 2020"],"snippet":"… state-of-the-art word embeddings is the vast amount of training data available. GloVe is trained on 840 billion tokens and more than 2 million unique words of Common Crawl data which is a crawl of the entire world wide web. Similarly, Word2vec is trained on a …","url":["https://psyarxiv.com/d84kg/download?format=pdf"]}
-{"year":"2020","title":"Social Media Attributions in the Context of Water Crisis","authors":["R Sarkar, H Sarkar, S Mahinder, AR KhudaBukhsh - arXiv preprint arXiv:2001.01697, 2020"],"snippet":"… used embedding in this preprocessing step. We used the 300 dimensional GloVe model trained on 840 billion tokens of the CommonCrawl corpus, having a vocabulary size of 2.2 million. While calculating the embedding of …","url":["https://arxiv.org/pdf/2001.01697"]}
-{"year":"2020","title":"Sociolinguistic Properties of Word Embeddings","authors":["A Arseniev-Koehler, JG Foster - SocArXiv. August, 2020"],"snippet":"… These studies use large, commonly available pre-trained embeddings or their training corpora, such as Google News, web data (Common Crawl), and Google Books … They replicated results using a pretrained model on Common Crawl data …","url":["https://osf.io/b8kud/download"]}
-{"year":"2020","title":"Software for creating and analyzing semantic representations","authors":["FÅ Nielsen, LK Hansen - Statistical Semantics, 2020"],"snippet":"… This package provides models for the tagger, parser, named-entity recognizer and distributional semantic vectors trained on OntoNotes Release 5 and the Common Crawl dataset … 10 K–50 K. 300. 29 languages. GloVe. Common …","url":["https://link.springer.com/chapter/10.1007/978-3-030-37250-7_3"]}
-{"year":"2020","title":"Spoken words as biomarkers: using machine learning to gain insight into communication as a predictor of anxiety","authors":["G Demiris, KL Corey Magan, D Parker Oliver… - Journal of the American …, 2020"],"snippet":"… The validity of using cosine distance in an embedding space to measure text similarity depends largely on how well the embedding space represents the semantic concepts present in the text. In our case, the word embeddings …","url":["https://academic.oup.com/jamia/advance-article-abstract/doi/10.1093/jamia/ocaa049/5831105"]}
-{"year":"2020","title":"SPONTANEOUS STEREOTYPE CONTENT: MEASUREMENT AIMING TOWARD THEORETICAL INTEGRATION AND DISCOVERY","authors":["G Nicolas Ferreira - 2020","GN Ferreira - 2020"],"snippet":"Page 1. SPONTANEOUS STEREOTYPE CONTENT: MEASUREMENT AIMING TOWARD THEORETICAL INTEGRATION AND DISCOVERY GANDALF NICOLAS FERREIRA A DISSERTATION PRESENTED TO THE FACULTY OF PRINCETON UNIVERSITY IN …","url":["http://search.proquest.com/openview/41d33da8e87d459690442733f719668f/1?pq-origsite=gscholar&cbl=18750&diss=y","https://dataspace.princeton.edu/bitstream/88435/dsp01zp38wg55d/1/NicolasFerreira_princeton_0181D_13366.pdf"]}
-{"year":"2020","title":"Stanza: A Python Natural Language Processing Toolkit for Many Human Languages","authors":["P Qi, Y Zhang, Y Zhang, J Bolton, CD Manning - arXiv preprint arXiv:2003.07082, 2020"],"snippet":"… For the character-level language models in the NER component, we pretrained them on a mix of the Common Crawl and Wikipedia dumps, and the news corpora released by the WMT19 Shared Task (Barrault et al., 2019), with …","url":["https://arxiv.org/pdf/2003.07082"]}
-{"year":"2020","title":"STIL--Simultaneous Slot Filling, Translation, Intent Classification, and Language Identification: Initial Results using mBART on MultiATIS++","authors":["JGM FitzGerald - arXiv preprint arXiv:2010.00760, 2020"],"snippet":"… The mBART.cc25 model was trained on 25 languages for 500k steps using a 1.4 TB corpus of scraped website data taken from Common Crawl (Wenzek et al., 2019). The model was trained to reconstruct masked tokens and to rearrange scrambled sentences …","url":["https://arxiv.org/pdf/2010.00760"]}
-{"year":"2020","title":"STILTool: A Semantic Table Interpretation evaLuation Tool","authors":["E Jimenez-Ruiz, A Maurino - The Semantic Web: ESWC 2020 Satellite Events …","M Cremaschi, A Siano, R Avogadro, E Jimenez-Ruiz…"],"snippet":"… In order to size the spread of tabular data, 2.5 M tables have been identified within the Common Crawl repository1 [3]. The current snapshot of Wikipedia contains more than 3.23 M tables from more than 520k Wikipedia articles …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=C0UIEAAAQBAJ&oi=fnd&pg=PA61&dq=commoncrawl&ots=OcUKD8orbe&sig=5EUZjTQOLRGuwqaWXWRmrck1S50","https://preprints.2020.eswc-conferences.org/posters_demos/paper_293.pdf"]}
-{"year":"2020","title":"Structured deep neural network with low complexity","authors":["S Liao - 2020"],"snippet":"Page 1. STRUCTURED DEEP NEURAL NETWORK WITH LOW COMPLEXITY By SIYU LIAO A dissertation submitted to the School of Graduate Studies Rutgers, The State University of New Jersey in partial fulfillment of the …","url":["https://rucore.libraries.rutgers.edu/rutgers-lib/64996/PDF/1/"]}
-{"year":"2020","title":"Study and Creation of Datasets for Comparative Questions Classification","authors":["S Stahlhacke"],"snippet":"… The data used by the system is a preprocessed version of the Common Crawl Text Corpus8, which crawled from the world wide web … Which one is better suited for me, Xbox One or PS4? 8https://commoncrawl.org/ 4 Page 11. CHAPTER 1. INTRODUCTION …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2020-ma-stahlhacke.pdf"]}
-{"year":"2020","title":"Studying the Evolution of Greek Words via Word Embeddings","authors":["V Barzokas, E Papagiannopoulou, G Tsoumakas - 11th Hellenic Conference on …, 2020"],"snippet":"… Despite the limited size of the Greek corpus compared to Common Crawl and Wikipedia used for the pre-trained fastText embeddings, we didn't detect any notable difference in the quality of our models in comparison with the pre-trained one …","url":["https://dl.acm.org/doi/abs/10.1145/3411408.3411425"]}
-{"year":"2020","title":"Substance over Style: Document-Level Targeted Content Transfer","authors":["A Hegel, S Rao, A Celikyilmaz, B Dolan - arXiv preprint arXiv:2010.08618, 2020"],"snippet":"Page 1. Substance over Style: Document-Level Targeted Content Transfer Allison Hegel1∗ Sudha Rao2 Asli Celikyilmaz2 Bill Dolan2 1Lexion, Seattle, WA, USA 2Microsoft Research, Redmond, WA, USA allison@lexion.ai {sudhra,aslicel,billdol}@microsoft.com Abstract …","url":["https://arxiv.org/pdf/2010.08618"]}
-{"year":"2020","title":"Subword Segmentation and a Single Bridge Language Affect Zero-Shot Neural Machine Translation","authors":["A Rios, M Müller, R Sennrich - arXiv preprint arXiv:2011.01703, 2020","AR Gonzales, M Müller, R Sennrich - Proceedings of the Fifth Conference on …, 2020"],"snippet":"… Page 3. 530 corpora training dev test Language Pairs with English: de↔en Commoncrawl, Europarl-v9, Wikititles-v1 5M 250 2000 cs↔en Europarl-v9, CzEng1.7 5M 250 2000 fr↔en Commoncrawl, Europarl-v7 …","url":["https://arxiv.org/pdf/2011.01703","https://www.aclweb.org/anthology/2020.wmt-1.64.pdf"]}
-{"year":"2020","title":"Suggesting Citations for Wikidata Claims based on Wikipedia's External References","authors":["P Curotto, A Hogan"],"snippet":"… Offline: Given that some Wikidata items do not have an associated Wikipedia article, that many Wikipedia articles have few references, etc., it would be interesting to develop a broader corpus with more documents from the Web, perhaps from the Common Crawl …","url":["http://aidanhogan.com/docs/wikidata-references.pdf"]}
-{"year":"2020","title":"Supervised Understanding of Word Embeddings","authors":["HZ Yerebakan, P Bhatia, Y Shinagawa"],"snippet":"… In our experiments, we have used scikit-learn linear logistic regression model with a positive class weight of 2 to enhance the effect of positive words. We have used top 250k words of Fasttext Common Crawl word …","url":["https://rcqa-ws.github.io/papers/paper8.pdf"]}
-{"year":"2020","title":"Surface pattern-enhanced relation extraction with global constraints","authors":["H Jiang, JT Liu, S Zhang, D Yang, Y Xiao, W Wang - Knowledge and Information …, 2020"],"snippet":"Relation extraction is one of the most important tasks in information extraction. The traditional works either use sentences or surface patterns (ie, the.","url":["https://link.springer.com/article/10.1007/s10115-020-01502-y"]}
-{"year":"2020","title":"Survey on RNN and CRF models for de-identification of medical free text","authors":["JL Leevy, TM Khoshgoftaar, F Villanustre - Journal of Big Data, 2020"],"snippet":"The increasing reliance on electronic health record (EHR) in areas such as medical research should be addressed by using ample safeguards for patient privacy. These records often tend to be big data, and given that a significant …","url":["https://journalofbigdata.springeropen.com/articles/10.1186/s40537-020-00351-4"]}
-{"year":"2020","title":"SYMPTOM EXTRACTION FROM ATRIAL FIBRILLATION PATIENT CLINICAL NOTES USING DEEP LEARNING","authors":["TET van Putten"],"snippet":"Page 1. Eindhoven University of Technology MASTER Symptom extraction from atrial fibrillation patient clinical notes using deep learning van Putten, TE Award date: 2020 Link to publication Disclaimer This document contains …","url":["https://pure.tue.nl/ws/portalfiles/portal/163432620/Master_Thesis_Tim_van_Putten.pdf"]}
-{"year":"2020","title":"Syntax Role for Neural Semantic Role Labeling","authors":["Z Li, H Zhao, S He, J Cai - arXiv preprint arXiv:2009.05737, 2020"],"snippet":"Page 1. Syntax Role for Neural Semantic Role Labeling Zuchao Li Shanghai Jiao Tong University Department of Computer Science and Engineering charlee@sjtu. edu.cn Hai Zhao∗ Shanghai Jiao Tong University Department …","url":["https://arxiv.org/pdf/2009.05737"]}
-{"year":"2020","title":"System and method for model derivation for entity prediction","authors":["FI Wyss, A Ganapathiraju, P Buduguppa - US Patent App. 16/677,989, 2020"],"snippet":"… The dense representation can be used to capture the contextual information. For an NER system, the information can be encoded in the form of “world knowledge' by using a corpus such as the Wikipedia corpus or Google's common crawl data …","url":["https://patents.google.com/patent/US20200151248A1/en"]}
-{"year":"2020","title":"Systematic Mapping on Embedded Semantic Markup Validated with Data Mining Techniques","authors":["R Navarrete, C Montenegro, L Recalde - … Conference on Applied Human Factors and …, 2020"],"snippet":"… Markup format: microdata, rdfa, jsonld. Approach of the Research: ads, commerce, commoncrawl, crawl, deploy, education, egovernment, entity, error, extract, extraction, fix, government, learning, lod, mistake, owl, pld, plds, rdf, video, wdc, webdatacommons …","url":["https://link.springer.com/chapter/10.1007/978-3-030-51328-3_53"]}
-{"year":"2020","title":"SYSTEMS AND METHODS FOR LEARNING USER REPRESENTATIONS FOR OPEN VOCABULARY DATA SETS","authors":["T Durand, G Mori - US Patent App. 16/826,215, 2020"],"snippet":"Systems and methods adapted for training a machine learning model to predict data labels are described. The approach includes receiving a first data set comprising first data objects and associated fi.","url":["https://www.freepatentsonline.com/y2020/0302340.html"]}
-{"year":"2020","title":"TabEAno: Table to Knowledge Graph Entity Annotation","authors":["P Nguyen, N Kertkeidkachorn, R Ichise, H Takeda - arXiv preprint arXiv:2010.01829, 2020"],"snippet":"… Note that, tables in this study refer to relational vertical tables. A 3 Open Data Vision: https://opendatabarometer.org 4 Common Crawl: http://commoncrawl.org/ arXiv:2010.01829v1 [cs.AI] 5 Oct 2020 Page 2. 2 Phuc Nguyen et al …","url":["https://arxiv.org/pdf/2010.01829"]}
-{"year":"2020","title":"TaBERT: Pretraining for Joint Understanding of Textual and Tabular Data","authors":["P Yin, G Neubig, W Yih, S Riedel - arXiv preprint arXiv:2005.08314, 2020"],"snippet":"… Page 5. interesting avenue for future work. Specifically, we collect tables and their surrounding NL text from English Wikipedia and the WDC WebTable Corpus (Lehmberg et al., 2016), a large-scale table collection from CommonCrawl …","url":["https://arxiv.org/pdf/2005.08314"]}
-{"year":"2020","title":"Tagging Reading Comprehension Materials with Document Extraction Attention Networks","authors":["B Sun, Y Zhu, R Xiao, Y Xiao, YG Wei - IEEE Transactions on Learning …, 2020"],"snippet":"Page 1. 1939-1382 (c) 2020 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/9079601/"]}
-{"year":"2020","title":"Tagging with Weak Labels. Paper presented at AAAI Conference on","authors":["E Simpson, J Pfeiffer, I Gurevych"],"snippet":"… For FAMULUS, we use 300-dimensional German fastText embeddings (Grave et al. 2018), and for NER and PICO we use 300-dimensional English GloVe 3 embeddings trained on 840 billion tokens from Common Crawl. To …","url":["https://research-information.bris.ac.uk/files/225055068/AAAI_Low_Resource_Sequence_Tagging_with_Weak_Labels.pdf"]}
-{"year":"2020","title":"Tailored retrieval of health information from the web for facilitating communication and empowerment of elderly people","authors":["M Alfano, B Lenzitti, D Taibi, M Helfert - 2020"],"snippet":"… contain all Microformat, Microdata and RDFa (Resource Description Framework in Attributes) data extracted from the open repository of Web crawl data named Common Crawl (CC)9 … 8 http://webdatacommons.org/ 9 …","url":["http://doras.dcu.ie/24469/2/ICT4AWE_2020_40_CR.pdf"]}
-{"year":"2020","title":"Target driven visual navigation exploiting object relationships","authors":["Y Qiu, A Pal, HI Christensen - arXiv preprint arXiv:2003.06749, 2020"],"snippet":"… For the word embeddings, we used the 300-D GloVe vectors pretrained on 840 billion tokens of Common Crawl [49]. The A3C model is based on [50], and the model hyperparameters used were: learning rate …","url":["https://arxiv.org/pdf/2003.06749"]}
-{"year":"2020","title":"Targeted Poisoning Attacks on Black-Box Neural Machine Translation","authors":["C Xu, J Wang, Y Tang, F Guzman, BIP Rubinstein… - arXiv preprint arXiv …, 2020"],"snippet":"… 3We find that the crawling services commonly used for parallel data collection, eg, Common Crawl (commoncrawl.org), are also fetching news articles from self-publishing sources like blogs (eg, with a subdomain of blogspot.com) …","url":["https://arxiv.org/pdf/2011.00675"]}
-{"year":"2020","title":"Tell and guess: cooperative learning for natural image caption generation with hierarchical refined attention","authors":["W Zhang, S Tang, J Su, J Xiao, Y Zhuang - Multimedia Tools and Applications, 2020"],"snippet":"… Implementation details. We use Tensorflow to implement our model and its variants. Given a textual caption, we employ the word2vec model (ie, GloVe word embedding [22] ) which is pre-trained on the Common Crawl dataset [25] …","url":["https://link.springer.com/article/10.1007/s11042-020-08832-7"]}
-{"year":"2020","title":"Tell Me Why You Feel That Way: Processing Compositional Dependency for Tree-LSTM Aspect Sentiment Triplet Extraction (TASTE)","authors":["A Sutherland, S Bensch, T Hellström, S Magg… - International Conference on …, 2020"],"snippet":"… aligned}$$. (6). $$\\begin{aligned}&{h}_{j} = o_j \\odot tanh(c_j). \\end{aligned}$$. (7). Words in a sentence are represented as Word Embeddings from the pre-trained Common-Crawl 840 B data 2 before they are fed to the DTLSTM. To …","url":["https://link.springer.com/chapter/10.1007/978-3-030-61609-0_52"]}
-{"year":"2020","title":"Tencent AI Lab machine translation systems for the WMT20 chat translation task","authors":["L Wang, Z Tu, X Wang, L Ding, L Ding, S Shi - Proceedings of the Fifth Conference on …, 2020"],"snippet":"… Out-of-domain Parallel Data The participants are allowed to use all the training data in the News shared task.4 Thus, we combine six corpora including Euporal, ParaCrawl, CommonCrawl, TildeRapid, NewsCommentary and WikiMatrix …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.60.pdf"]}
-{"year":"2020","title":"Testing pre-trained Transformer models for Lithuanian news clustering","authors":["L Stankevičius, M Lukoševičius - arXiv preprint arXiv:2004.03461, 2020"],"snippet":"… Specifically, we will use well known baselines – multilingual BERT and recently published XLM-R, trained on more than two terabytes of filtered CommonCrawl data. We chose clustering task to also try to advance the field of data mining …","url":["https://arxiv.org/pdf/2004.03461"]}
-{"year":"2020","title":"Text as data: a machine learning-based approach to measuring uncertainty","authors":["R Nyman, P Ormerod - arXiv preprint arXiv:2006.06457, 2020"],"snippet":"… The authors assemble a very large corpus of words from various sources. We use the one described on the GloVe website as Common Crawl (glove.42B.300d.zip). A co-occurrence matrix is constructed, which describes …","url":["https://arxiv.org/pdf/2006.06457"]}
-{"year":"2020","title":"Text Classification: Exploiting the Social Network","authors":["SBM Alkhereyf"],"snippet":"Page 1. Text Classification: Exploiting the Social Network Sakhar Alkhereyf Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy under the Executive Committee of the Graduate School of …","url":["https://academiccommons.columbia.edu/doi/10.7916/d8-t2jv-sb09/download"]}
-{"year":"2020","title":"Text mining-based construction site accident classification using hybrid supervised machine learning","authors":["MY Cheng, D Kusoemo, RA Gosno - Automation in Construction, 2020"],"snippet":"… There are various pre-trained databases in the GloVe website that is open for public, such as Wikipedia database consists of 6 billion words and 100 dimension, Common Crawl database consists of 42 billion words and 300 …","url":["https://www.sciencedirect.com/science/article/pii/S092658051931341X"]}
-{"year":"2020","title":"Text-based classification of interviews for mental health--juxtaposing the state of the art","authors":["JV Wouts - arXiv preprint arXiv:2008.01543, 2020"],"snippet":"… Model name Pretrain corpus Tokenizer type Acc Sentiment analysis belabBERT Common Crawl Dutch (non-shuffled) BytePairEncoding 95.92∗ % RobBERT Common Crawl Dutch (shuffled) BytePairEncoding 94.42 …","url":["https://arxiv.org/pdf/2008.01543"]}
-{"year":"2020","title":"TextSETTR: Label-Free Text Style Extraction and Tunable Targeted Restyling","authors":["P Riley, N Constant, M Guo, G Kumar, D Uthus… - arXiv preprint arXiv …, 2020"],"snippet":"… Furthermore, we demonstrate that a single model trained on unlabeled Common Crawl data is capable of transferring along multiple dimensions including dialect, emotiveness, formality, politeness, and sentiment. 1 INTRODUCTION …","url":["https://arxiv.org/pdf/2010.03802"]}
-{"year":"2020","title":"TF-CR: Weighting Embeddings for Text Classification","authors":["A Zubiaga - arXiv preprint arXiv:2012.06606, 2020"],"snippet":"… Page 6. • cglove: GloVe embeddings trained from Common Crawl. • wglove: GloVe embeddings trained from Wikipedia.6 We use two different classifiers for these experiments, SVM and Logistic Regression, which are known …","url":["https://arxiv.org/pdf/2012.06606"]}
-{"year":"2020","title":"The 2019 BBN Cross-lingual Information Retrieval System","authors":["DK Le Zhang, W Hartmann, M Srivastava, L Tarlin… - LREC 2020 Language Resources …","L Zhang, D Karakos, W Hartmann, M Srivastava… - Proceedings of the …, 2020"],"snippet":"… 4.1. Training Data The primary data source for constructing MT models is parallel data from the build language pack, augmented with a variety of web data, such as CommonCrawl2 and open parallel corpus (Tiedemann …","url":["http://www.lrec-conf.org/proceedings/lrec2020/workshops/CLSSTS2020/CLSSTS-2020.pdf#page=49","https://www.aclweb.org/anthology/2020.clssts-1.8.pdf"]}
-{"year":"2020","title":"The 2020 bilingual, bi-directional webnlg+ shared task overview and evaluation results (webnlg+ 2020)","authors":["TC Ferreira, C Gardent, C van der Lee, N Ilinykh… - Proceedings of the 3rd …, 2020"],"snippet":"… 3.3 Mono-task, Bilingual Approaches cuni-ufal. The mBART model (Liu et al., 2020) is pre-trained for multilingual denoising on the large-scale multilingual CC25 corpus extracted from Common Crawl, which contains …","url":["https://webnlg-challenge.loria.fr/files/2020.webnlg-papers.7.pdf"]}
-{"year":"2020","title":"THE ABILITY OF WORD EMBEDDINGS TO CAPTURE WORD SIMILARITIES","authors":["M Toshevska, F Stojanovska, J Kalajdjieski"],"snippet":"… architectures [25]. In our experiments, we have used pre-trained models both trained with subword information on Wikipedia 2017 (16B tokens) and trained with subword information on Common Crawl (600B tokens)4. 2https …","url":["http://www.academia.edu/download/63915170/120200714-10552-nn915u.pdf"]}
-{"year":"2020","title":"The ADAPT Centre's neural MT systems for the WAT 2020 document-level translation task","authors":["W Jooste, R Haque, A Way - 2020"],"snippet":"… Finally, source-language monolingual data with n-grams similar to that of the documents in the test set was mined from the Common Crawl Corpus6 to be used as a source-side original synthetic corpus (SOSC) for fine-tuning the NMT model parameters …","url":["http://doras.dcu.ie/25205/1/WAT_2020.pdf"]}
-{"year":"2020","title":"The afrl wmt20 news-translation systems","authors":["J Gwinnup, T Anderson - Proceedings of the Fifth Conference on Machine …, 2020"],"snippet":"… Page 2. 207 corpus unfiltered lines filtered lines percent remain commoncrawl 723,256 655,069 90.57% newscommentaryv15 319,242 286,947 89.88% yandex 1,000,000 901,318 90.13 … 2013. Dirt cheap webscale parallel text from the common crawl …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.20.pdf"]}
-{"year":"2020","title":"The Art of Reproducible Machine Learning","authors":["V Novotný - RASLAN 2020 Recent Advances in Slavonic Natural …, 2020"],"snippet":"… We then use the initializations to reproduce 14 the results of Mikolov et al.(2018)[19, Table 2] us- ing the subword cbow model of Bojanowski et al.(2017)[2] and the 2017 English Wikipedia 15 training corpus (4% of the …","url":["https://nlp.fi.muni.cz/raslan/raslan20.pdf#page=63"]}
-{"year":"2020","title":"The birth of Romanian BERT","authors":["SD Dumitrescu, AM Avram, S Pyysalo - arXiv preprint arXiv:2009.08712, 2020"],"snippet":"… In total, the OPUS corpus contains around 4GB of Romanian text. OSCAR OSCAR (Ortiz Suárez et al., 2019), or Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language …","url":["https://arxiv.org/pdf/2009.08712"]}
-{"year":"2020","title":"The Case For Alternative Web Archival Formats To Expedite The Data-To-Insight Cycle","authors":["X Wang, Z Xie - arXiv preprint arXiv:2003.14046, 2020"],"snippet":"… Large-scale, comprehensive web archiving initiatives include the Internet Archive [8], the Common Crawl [16], and many programs at national libraries and archives. These … 5.2 Data We chose to use Common Crawl's web …","url":["https://arxiv.org/pdf/2003.14046"]}
-{"year":"2020","title":"The Challenge of Diacritics in Yoruba Embeddings","authors":["TP Adewumi, F Liwicki, M Liwicki - arXiv preprint arXiv:2011.07605, 2020"],"snippet":"… (2018) are tabulated: Wiki, U_Wiki, C3 & CC, representing embeddings from the cleaned Wikipedia dump, its undiacritized (normalized) version, the diacritized data from Alabi et al. (2020) and the Common Crawl embedding by Grave et al. (2018), respectively …","url":["https://arxiv.org/pdf/2011.07605"]}
-{"year":"2020","title":"The Danish Gigaword Project","authors":["L Strømberg-Derczynski, R Baglini, MH Christiansen… - arXiv preprint arXiv …, 2020"],"snippet":"… Similarly, other huge monolithic datasets such as the Common Crawl Danish data suffer from large amounts of non-Danish content, possibly due to the pervasive confusion between Danish and Norwegian Bokmål … Common …","url":["https://arxiv.org/pdf/2005.03521"]}
-{"year":"2020","title":"The ELTE. DH Pilot Corpus–Creating a Handcrafted Gigaword Web Corpus with Metadata","authors":["B Indig, Á Knap, Z Sárközi-Lindner, M Timári, G Palkó - … of the 12th Web as Corpus …, 2020"],"snippet":"… Nowadays, large corpora are utilising the Common Crawl archive like the OSCAR corpus (Ortiz Suárez et al., 2019) with 5.16 billion (2.33 … All of these corpora – except the ones based on Common Crawl – have the same …","url":["https://www.aclweb.org/anthology/2020.wac-1.5.pdf"]}
-{"year":"2020","title":"The Emergence, Advancement and Future of Textual Answer Triggering","authors":["KN Acheampong, W Tian, EB Sifah… - Science and Information …, 2020"],"snippet":"… A similar observation is realized (\\(A_1 \\approx 0.8986\\); \\(A_2 \\approx 0.7352\\); difference in margin \\(\\approx 0.1634 \\)) when the model the 300-dimensional word vectors trained on Common Crawl with GloVe from spaCy is used …","url":["https://link.springer.com/chapter/10.1007/978-3-030-52246-9_50"]}
-{"year":"2020","title":"The Geometry of Distributed Representations for Better Alignment, Attenuated Bias, and Improved Interpretability","authors":["S Dev - arXiv preprint arXiv:2011.12465, 2020"],"snippet":"… 39 5 RMSE variation with word frequency in (a) GloVe Wiki to GloVe Common Crawl and (b) word2vec to GloVe evaluated for Wiki dataset. All words were used for tests in lower case as listed in the table. . . . . 40 …","url":["https://arxiv.org/pdf/2011.12465"]}
-{"year":"2020","title":"The NiuTrans Machine Translation Systems for WMT20","authors":["Y Zhang, Z Wang, R Cao, B Wei, W Shan, S Zhou… - Proceedings of the Fifth …, 2020"],"snippet":"… mentary, Common Crawl , TED Talks 4 Japanese monolingual data corpus about 1.7 billion. After the data filter, 12 million parallel data was left and 11 million selected by the neural language model was used as training data …","url":["https://www.aclweb.org/anthology/2020.wmt-1.37.pdf"]}
-{"year":"2020","title":"The POLAR Framework: Polar Opposites Enable Interpretability of Pre-Trained Word Embeddings","authors":["B Mathew, S Sikdar, F Lemmerich, M Strohmaier - arXiv preprint arXiv:2001.09876, 2020"],"snippet":"… (2) GloVe embeddings [27]3 trained on Web data from Common Crawl … 3We used the Common Crawl embeddings with 42B tokens: https://nlp. stanford.edu/ projects/glove/ 4The datasets are available here: https://github …","url":["https://arxiv.org/pdf/2001.09876"]}
-{"year":"2020","title":"The POLUSA Dataset: 0.9 M Political News Articles Balanced by Time and Outlet Popularity","authors":["L Gebhard, F Hamborg - arXiv preprint arXiv:2005.14024, 2020"],"snippet":"… RoBERTa: A Robustly Optimized BERT Pretraining Ap- proach. arXiv: 1907.11692 [cs] [6] Sebastian Nagel. 2016. Common Crawl – News Dataset Available. Retrieved May 8, 2020 from https://commoncrawl.org/2016/10 …","url":["https://arxiv.org/pdf/2005.14024"]}
-{"year":"2020","title":"The presence of occupational structure in online texts based on word embedding NLP models","authors":["Z Kmetty, J Koltai, T Rudas - arXiv preprint arXiv:2005.08612, 2020"],"snippet":"… We used three pre-trained vector spaces in the analysis. The first vector model we used was trained on the English language texts of the Common Crawl (CC) corpus1, a huge web archive … 2016) 1 http://commoncrawl.org 2 …","url":["https://arxiv.org/pdf/2005.08612"]}
-{"year":"2020","title":"The role of affective meaning, semantic associates, and orthographic neighbours in modulating the N400 in single words","authors":["F Blomberg, M Roll, J Frid, M Lindgren, M Horne - The Mental Lexicon, 2020"],"snippet":"… of fastText compared to other popular implementations (such as Word2Vec and Glove) is that it already has a model for Swedish trained on millions of words taken from the Swedish version of the free online encyclopedia …","url":["https://www.jbe-platform.com/content/journals/10.1075/ml.19021.blo"]}
-{"year":"2020","title":"The Two-Pass Softmax Algorithm","authors":["M Dukhan, A Ablavatski - arXiv preprint arXiv:2001.04438, 2020"],"snippet":"Page 1. The Two-Pass Softmax Algorithm Marat Dukhan ∗1,2 and Artsiom Ablavatski1 1Google Research 2Georgia Institute of Technology Abstract The softmax (also called softargmax) function is widely used in machine learning …","url":["https://arxiv.org/pdf/2001.04438"]}
-{"year":"2020","title":"The University of Edinburgh's English-Tamil and English-Inuktitut Submissions to the WMT20 News Translation Task","authors":["R Bawden, A Birch, R Dobreva, A Oncevay… - 5th Conference on Machine …, 2020"],"snippet":"… The only additional monolingual Inuktitut data was 163k sentences of common-crawl data, which we backtranslated for the English→Inuktitut system … Synthetic (from en Europarl) en-iu 650k Synthetic (from en News …","url":["https://hal.archives-ouvertes.fr/hal-02981153/document"]}
-{"year":"2020","title":"The University of Edinburgh's submission to the German-to-English and English-to-German Tracks in the WMT 2020 News Translation and Zero-shot Translation …","authors":["U Germann - 2020"],"snippet":"… High-quality parallel data Europarl ca. 1.79 M Rapid ca. 1.45 M News Commentary ca. 0.35 M Crawled parallel data ParaCrawl 5.1 ca. 34.37 M CommonCrawl ca. 2.40 M WikiMatrix ca. 6.22 M WikiTitles ca. 1.38 M Monolingual crawled news data German ca …","url":["http://statmt.org/wmt20/pdf/2020.wmt-1.18.pdf"]}
-{"year":"2020","title":"The University of Helsinki and Aalto University submissions to the WMT 2020 news and lowresource translation tasks","authors":["Y Scherrer, SA Grönroos, S Virpioja - the Fifth Conference on Machine Translation, 2020"],"snippet":"… NewsDiscuss 2019 2 000 000 1 000 000 CommonCrawl 80 244 80 244 … In terms of monolingual Inuktitut data, besides the unaligned NH data, the organizers only provided a CommonCrawl dump. This corpus was again backtranslated to English and filtered …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.134.pdf"]}
-{"year":"2020","title":"The University of Helsinki submission to the IWSLT2020 Offline Speech Translation Task","authors":["R Vázquez, M Aulamo, U Sulubacak, J Tiedemann - The 17th International …, 2020"],"snippet":"… filter out noisy translations. OpenSubtitles2018, which consists of subtitle translations, and corpora gathered by crawling the internet, Common Crawl and ParaCrawl, are especially likely to contain noisy data. For filtering the …","url":["https://tuhat.helsinki.fi/ws/files/137272405/uni_helsinki_submission_iwslt_2020.pdf"]}
-{"year":"2020","title":"The Unreasonable Effectiveness of Machine Learning in Moldavian versus Romanian Dialect Identification","authors":["M Găman, RT Ionescu - arXiv preprint arXiv:2007.15700, 2020"],"snippet":"… We note that these representations are learned from Romanian corpora, such as the corpus for contemporary Romanian language (CoRoLa) (Mititelu, Tufis, and Irimia 2018; Pais and Tufis 2018), Common Crawl (CC) and Wikipedia (Grave et al …","url":["https://arxiv.org/pdf/2007.15700"]}
-{"year":"2020","title":"The Voice and Speech Processing within Language Technology Applications: Perspective of the Russian Data Protection Law","authors":["I Ilin"],"snippet":"… of collecting, systematizing and annotating language data are various language datasets such as Open Subtitles43, the Common Crawl da- taset44, the … 43 Available at: https://www.opensubtitles.org/ru (accessed: 18.05.2020) …","url":["https://www.researchgate.net/profile/Ilya_Ilin/publication/345237982_The_Voice_and_Speech_Processing_within_Language_Technology_Application_Perspective_of_the_Russian_Data_Protection_Law/links/5fa11750458515b7cfb5ce68/The-Voice-and-Speech-Processing-within-Language-Technology-Application-Perspective-of-the-Russian-Data-Protection-Law.pdf"]}
-{"year":"2020","title":"The Volctrans Machine Translation System for WMT20","authors":["L Wu, X Pan, Z Lin, Y Zhu, M Wang, L Li - arXiv preprint arXiv:2010.14806, 2020"],"snippet":"… We use all parallel data available: Eu- roparl v10, ParaCrawl v5.1, Common Crawl corpus, News Commentary v15, Wiki Titles v2, Tilde Rapid corpus and WikiMatrix corpus … Each part contains 10M common crawl sentences and 3M Newscrawl sentences …","url":["https://arxiv.org/pdf/2010.14806"]}
-{"year":"2020","title":"TheNorth@ HaSpeeDe 2: BERT-based Language Model Fine-tuning for Italian Hate Speech Detection","authors":["E Lavergne, R Saini, G Kovács, K Murphy"],"snippet":"… ERT. AlBERTo was pretrained on TWITA, that is a collection of Italian tweets (Polignano et al., 2019b). UmBERTo was pretrained on Commoncrawl ITA exploiting OSCAR Italian large corpus (Parisi et al., 2020). Finally, PoliBERT …","url":["http://ceur-ws.org/Vol-2765/paper135.pdf"]}
-{"year":"2020","title":"This is a post-peer-review, pre-copyedit version of an article in press in Motivation and Emotion. The final authenticated version is available online at: http://dx. doi. org …","authors":["JS Pang, H Ring"],"snippet":"… datasets. Based on these experiments we decided to use Facebook's FastText subword embeddings of 300 dimensions trained on Common Crawl (600 billion tokens).5 This is the set of pre-trained vectors that we …","url":["http://www.academia.edu/download/63571037/Pang_Ring-2020-Automating_implicit_motive_coding-ME_AAM.pdf"]}
-{"year":"2020","title":"This is a post-peer-review, pre-copyedit version of an article in press in Motivation and Emotion. The final authenticated version will be available online at: http://dx. doi …","authors":["JS Pang, H Ring"],"snippet":"… datasets. Based on these experiments we decided to use Facebook's FastText subword embeddings of 300 dimensions trained on Common Crawl (600 billion tokens).5 This is the set of pre-trained vectors that we …","url":["https://osf.io/b7d96/download"]}
-{"year":"2020","title":"Tight Integrated End-to-End Training for Cascaded Speech Translation","authors":["P Bahar, T Bieschke, R Schlüter, H Ney - arXiv preprint arXiv:2011.12167, 2020"],"snippet":"… For MT training on En→De, we utilize the parallel data allowed for the IWSLT 2020. After filtering the noisy corpora, namely ParaCrawl, CommonCrawl, Rapid and OpenSubtitles2018, we end up with almost 27M bilingual text sentences …","url":["https://arxiv.org/pdf/2011.12167"]}
-{"year":"2020","title":"Tilde at WMT 2020: News Task Systems","authors":["R Krišlauks, M Pinnis - arXiv preprint arXiv:2010.15423, 2020"],"snippet":"… translation. In order to make use of the Polish CommonCrawl corpus, we scored sentences using the in-domain language models and selected top-scoring sentences as additional monolingual data for back-translation. Many …","url":["https://arxiv.org/pdf/2010.15423"]}
-{"year":"2020","title":"Tired of Topic Models? Clusters of Pretrained Word Embeddings Make for Fast and Good Topics too!","authors":["S Sia, A Dalmia, SJ Mielke - arXiv preprint arXiv:2004.14914, 2020"],"snippet":"… 0.177 FastText 2B (Wikipedia) -0.561 -0.657 -0.419 0.225 0.142 0.196 -0.382 -0.187 0.212 0.235 0.240 0.253 Glove 840B (Common Crawl) -0.436 -0.111 -0.299 0.182 0.213 0.155 -0.043 0.179 0.233 0.219 0.237 0.240 BERT …","url":["https://arxiv.org/pdf/2004.14914"]}
-{"year":"2020","title":"To BERT or Not to BERT: Comparing Task-specific and Task-agnostic Semi-Supervised Approaches for Sequence Tagging","authors":["K Bhattacharjee, M Ballesteros, R Anubhai, S Muresan… - arXiv preprint arXiv …, 2020","KBMBR Anubhai, S Muresan, JMFLY Al, OA AI"],"snippet":"… Cloze (Baevski et al., 2019) and BERT-MRC+DSC (Li et al., 2019) are SOTA baselines for CONLL-2003 and CONLL-2012, respectively, for this task. Baevski et al. (2019) also use subsampled Common Crawl and News Crawl …","url":["https://arxiv.org/pdf/2010.14042","https://assets.amazon.science/79/37/7a3f91804693baaaadc5062a9821/to-bert-or-not-to-bert-comparing-task-specific-and-task-agnostic-semi-supervised-approaches-for-sequence-tagging.pdf"]}
-{"year":"2020","title":"Tohoku-AIP-NTT at WMT 2020 News Translation Task","authors":["S Kiyono, T Ito, R Konno, M Morishita, J Suzuki - … of the Fifth Conference on Machine …, 2020"],"snippet":"… 2.2 Monolingual Corpus The origins of the monolingual corpus in our system are the Europarl, NewsCommentary, and en- tire NewsCrawl (2008-2019) corpora for English and German, and the Europarl …","url":["http://www.statmt.org/wmt20/pdf/2020.wmt-1.12.pdf"]}
-{"year":"2020","title":"Topics in Sequence-to-Sequence Learning for Natural Language Processing","authors":["R Aharoni"],"snippet":"Page 1. Topics in Sequence-to-Sequence Learning for Natural Language Processing Roee Aharoni Ph.D. Thesis Submitted to the Senate of Bar-Ilan University Ramat Gan, Israel May 2020 Page 2. This work was …","url":["http://www.roeeaharoni.com/Phd_Thesis.pdf"]}
-{"year":"2020","title":"Touché: First Shared Task on Argument Retrieval","authors":["A Bondarenko, M Hagen, M Potthast, H Wachsmuth…"],"snippet":"… Systems. pp. 44–52 (2012) 2. Bevendorff, J., Stein, B., Hagen, M., Potthast, M.: Elastic ChatNoir: Search Engine for the ClueWeb and the Common Crawl. In: Proceedings of the 40th European Conference on IR Research (ECIR). pp …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2020-bondarenkoetal-ecir-touche.pdf"]}
-{"year":"2020","title":"Toward building recommender systems for the circular economy: Exploring the perils of the European Waste Catalogue","authors":["G van Capelleveen, C Amrit, H Zijm, DM Yazan, A Abdi - Journal of Environmental …"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0301479720313554"]}
-{"year":"2020","title":"Towards Context-Aware Opinion Summarization for Monitoring Social Impact of News","authors":["A Ramón-Hernández, A Simón-Cuevas, MMG Lorenzo… - Information, 2020"],"snippet":"… Specifically, those vectors are generated by using the word2vec pre-trained model included in the es_core_news_md model of the spaCy library, which includes 300-dimensional vectors trained using FastText CBOW on Wikipedia …","url":["https://www.mdpi.com/2078-2489/11/11/535/pdf"]}
-{"year":"2020","title":"Towards countering hate speech against journalists on social media","authors":["P Charitidis, S Doropoulos, S Vologiannidis… - Online Social Networks and …, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S2468696420300124"]}
-{"year":"2020","title":"Towards Effective Utilization of Pretrained Language Models—Knowledge Distillation from BERT","authors":["L Liu - 2020"],"snippet":"… For non-contextual embeddings, there are multiple pre-trained word vectors, such as word2vec trained on Google News, GloVe [60] trained on Wikipedia/Gigaword/Common Crawl, and fastText[67] trained on Wikipedia/Common Crawl …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/16225/Liu_Linqing.pdf?sequence=3"]}
-{"year":"2020","title":"Towards Efficient and Reproducible Natural Language Processing","authors":["J Dodge - 2020"],"snippet":"… multiple epochs is standard). For example, the July 2019 Common Crawl contains 242 TB of uncompressed data,8 so even storing the data is expensive … 7https://opensource.google.com/projects/open-images-dataset …","url":["https://www.lti.cs.cmu.edu/sites/default/files/dodge%2C%20jesse%20-%20May%202020.pdf"]}
-{"year":"2020","title":"Towards Generalized Neural Semantic Parsing","authors":["P Yin - 2020"],"snippet":"Page 1. April 27, 2020 DRAFT Thesis Proposal Towards Generalized Neural Semantic Parsing Pengcheng Yin April 27, 2020 Language Technologies Institute School of Computer Science Carnegie Mellon University Pittsburgh, PA 15123 Thesis Committee …","url":["http://pcyin.me/thesis_proposal.pdf"]}
-{"year":"2020","title":"Towards IP-based Geolocation via Fine-grained and Stable Webcam Landmarks","authors":["Z Wang, Q Li, J Song, H Wang, L Sun - Proceedings of The Web Conference 2020, 2020"],"snippet":"Page 1. Towards IP-based Geolocation via Fine-grained and Stable Webcam Landmarks Zhihao Wang Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security, University of Chinese Academy …","url":["https://dl.acm.org/doi/pdf/10.1145/3366423.3380216"]}
-{"year":"2020","title":"Towards Orthographic and Grammatical Clinical Text Correction: a First Approach","authors":["S Lima López - 2020"],"snippet":"… Their application to GEC is based on the idea that correct sequences are bound to have a higher probability score than incorrect ones. They are very dependent on the data that is used to build them, and so large corpora …","url":["https://addi.ehu.es/bitstream/handle/10810/48624/MAL-Salvador_Lima.pdf?sequence=1"]}
-{"year":"2020","title":"Towards Useful Word Embeddings","authors":["V Novotný, M Štefánik, D Lupták, P Sojka"],"snippet":"… The size of our dataset is only 4% of the Common Crawl dataset used by Mikolov et al … We will also train our word vector models using larger corpora such as Common Crawl to enable meaningful comparison to sota results. Acknowledgments …","url":["https://www.fi.muni.cz/usr/sojka/papers/raslan-2020-novotny-stefanik-luptak-sojka.pdf"]}
-{"year":"2020","title":"Towards Visual Dialog for Radiology","authors":["O Kovaleva, C Shivade, S Kashyap, K Kanjaria, J Wu… - Proceedings of the 19th …, 2020"],"snippet":"… the models, (b) domain-independent GloVe Common Crawl embeddings (Pennington et al., 2014), and (c) domain-specific fastText embeddings trained by (Romanov and Shivade, 2018). The latter are initialized with GloVe …","url":["https://www.aclweb.org/anthology/2020.bionlp-1.6.pdf"]}
-{"year":"2020","title":"Traceability Support for Multi-Lingual Software Projects","authors":["Y Liu, J Lin, J Cleland-Huang - arXiv preprint arXiv:2006.16940, 2020"],"snippet":"Page 1. Traceability Support for Multi-Lingual Software Projects Yalin Liu, Jinfeng Lin, Jane Cleland-Huang University of Notre Dame Notre Dame, IN yliu26@nd.edu, jlin6@nd.edu,JaneHuang@nd.edu ABSTRACT Software …","url":["https://arxiv.org/pdf/2006.16940"]}
-{"year":"2020","title":"Tracing the emergence of gendered language in childhood","authors":["B Prystawski, E Grant, A Nematzadeh, SWS Lee…"],"snippet":"… We used three commonly-used sets of pre-trained word em- beddings: the word2vec embeddings trained on the Google News corpus (Mikolov et al., 2013a), the GloVe embeddings trained on the Common Crawl corpus, and …","url":["https://cognitivesciencesociety.org/cogsci20/papers/0190/0190.pdf"]}
-{"year":"2020","title":"Train Hard, Finetune Easy: Multilingual Denoising for RDF-to-Text Generation","authors":["Z Kasner, O Dušek - Proceedings of the 3rd WebNLG Workshop on Natural …, 2020"],"snippet":"… al., 2019). Adopting BART's objective and architecture, mBART (Liu et al., 2020) is pre-trained on the large-scale CC25 corpus extracted from Common Crawl, which contains data in 25 languages (Wenzek et al., 2020). The …","url":["https://webnlg-challenge.loria.fr/files/2020.webnlg-papers.20.pdf"]}
-{"year":"2020","title":"Transformer based Deep Intelligent Contextual Embedding for Twitter sentiment analysis","authors":["U Naseem, I Razzak, K Musial, M Imran - Future Generation Computer Systems, 2020"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0167739X2030306X"]}
-{"year":"2020","title":"Transforming machine translation: a deep learning system reaches news translation quality comparable to human professionals","authors":["M Popel, M Tomkova, J Tomek, Ł Kaiser, J Uszkoreit… - Nature Communications, 2020"],"snippet":"The quality of human translation was long thought to be unattainable for computer translation systems. In this study, we present a deep-learning system, CUBBITT, which challenges this view. In a context-aware blind evaluation …","url":["https://www.nature.com/articles/s41467-020-18073-9"]}
-{"year":"2020","title":"Translation Artifacts in Cross-lingual Transfer Learning","authors":["M Artetxe, G Labaka, E Agirre - arXiv preprint arXiv:2004.04721, 2020"],"snippet":"… We first collect the premises from a filtered version of CommonCrawl (Buck et al., 2014), taking a subset of 5 websites that represent a diverse set of genres: a newspaper, an economy forum, a celebrity magazine, a literature blog, and a consumer magazine …","url":["https://arxiv.org/pdf/2004.04721"]}
-{"year":"2020","title":"Translation System and Method","authors":["N Bertoldi, D Caroselli, MA Farajian, M Federico… - US Patent App. 16/118,273, 2020"],"snippet":"US20200073947A1 - Translation System and Method - Google Patents. Translation System and Method. Download PDF Info. Publication number US20200073947A1. US20200073947A1 US16/118,273 US201816118273A US2020073947A1 …","url":["https://patents.google.com/patent/US20200073947A1/en"]}
-{"year":"2020","title":"TransQuest: Translation Quality Estimation with Cross-lingual Transformers","authors":["T Ranasinghe, C Orasan, R Mitkov - arXiv preprint arXiv:2011.01536, 2020"],"snippet":"… to acquire. Instead, XLM-R trains RoBERTa(Liu et al., 2019) on a huge, multilingual dataset at an enormous scale: unlabelled text in 104 languages is extracted from CommonCrawl datasets, totalling 2.5TB of text. It is trained …","url":["https://arxiv.org/pdf/2011.01536"]}
-{"year":"2020","title":"Triclustering in Big Data Setting","authors":["D Egurnov, DI Ignatov, D Tochilkin - arXiv preprint arXiv:2010.12933, 2020"],"snippet":"Page 1. Triclustering in Big Data Setting Dmitry Egurnov, Dmitry I. Ignatov, and Dmitry Tochilkin Abstract In this paper, we describe versions of triclustering algorithms adapted for efficient calculations in distributed environments …","url":["https://arxiv.org/pdf/2010.12933"]}
-{"year":"2020","title":"Triple E-Effective Ensembling of Embeddings and Language Models for NER of Historical German.","authors":["S Schweter, L März"],"snippet":"… We use the FastText embeddings trained on Wikipedia (FastText Wiki) and Common Crawl (FastText CC) in a ”classic” word embeddings manner, that means we do not use subwords … BPE MultiBPEmb Wikipedia < 7000 …","url":["http://ceur-ws.org/Vol-2696/paper_173.pdf"]}
-{"year":"2020","title":"TULIP: A Five-Star Table and List-from Machine-Readable to Machine-Understandable Systems","authors":["J Nandakwang, P Chongstitvatana - Linked Open Data-Applications, Trends and …, 2020"],"snippet":"Currently, Linked Data is increasing at a rapid rate as the growth of the Web. Aside from new information that has been created exclusively as Semantic Web-ready, part of them comes from the transformation of existing structural …","url":["https://www.intechopen.com/online-first/tulip-a-five-star-table-and-list-from-machine-readable-to-machine-understandable-systems"]}
-{"year":"2020","title":"TweetBERT: A Pretrained Language Representation Model for Twitter Text Analysis","authors":["MMA Qudar, V Mago - arXiv preprint arXiv:2010.11091, 2020"],"snippet":"… It has been pre-trained on an extremely large, five different types of corpora: BookCorpus, English Wikipedia, CC-News (collected from CommonCrawl News) dataset, OpenWebText, a WebText corpus [23], and Stories, a dataset containing story-like content [23] …","url":["https://arxiv.org/pdf/2010.11091"]}
-{"year":"2020","title":"Two-Level Transformer and Auxiliary Coherence Modeling for Improved Text Segmentation","authors":["G Glavaš, S Somasundaran - arXiv preprint arXiv:2001.00891, 2020"],"snippet":"… In all our experiments we use 300dimensional monolingual FASTTEXT word embeddings pretrained on the Common Crawl corpora of respective languages: EN, CS, FI, and TR.9 We induce a cross-lingual word embedding …","url":["https://arxiv.org/pdf/2001.00891"]}
-{"year":"2020","title":"UHH-LT & LT2 at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detection","authors":["G Wiedemann, SM Yimam, C Biemann - arXiv preprint arXiv:2004.11493, 2020"],"snippet":"… languages at once (Conneau et al., 2019). The model itself is equivalent to RoBERTa, but the training data consists of texts from more than 100 languages filtered from the CommonCrawl1 dataset. ALBERT – A Lite BERT for Self …","url":["https://arxiv.org/pdf/2004.11493"]}
-{"year":"2020","title":"Uncertainty-Aware Machine Support for Paper Reviewing on the Interspeech 2019 Submission Corpus","authors":["L Stappen, G Rizos, M Hasan, T Hain, BW Schuller"],"snippet":"… compressed to 300 dimensions. FastText and GloVe are based on the Common Crawl (1.9 M unique words, 840 B tokens) and Word2Vec on the GoogleNews (3 M unique words, 100 B total) dataset. We additionally experimented …","url":["https://indico2.conference4me.psnc.pl/event/35/contributions/3133/attachments/305/328/Tue-1-9-1.pdf"]}
-{"year":"2020","title":"Underlying Cause of Death Identification from Death Certificates using Reverse Coding to Text and a NLP Based Deep Learning Approach","authors":["V Della Mea, MH Popescu, K Roitero - Informatics in Medicine Unlocked, 2020"],"snippet":"… XLM-R (a variation of XLM), trained on one hundred languages using more than two terabytes of filtered CommonCrawl data, outperformed multilingual BERT (mBERT) on a variety of cross-lingual benchmarks [5]. 3.3.4. XLNet …","url":["https://www.sciencedirect.com/science/article/pii/S2352914820306067"]}
-{"year":"2020","title":"Understanding phishers' strategies of mimicking uniform resource locators to leverage phishing attacks: A machine learning approach","authors":["JS Tharani, NAG Arachchilage - arXiv preprint arXiv:2007.00489, 2020"],"snippet":"… webpage data downloaded from PhishTank2, OpenPhish3 and Legitimate ones are downloaded from Alexa4 and Common Crawl5 According … (4) 4 https://www.alexa.com/topsites/category/Computers/Internet/OntheW eb/W …","url":["https://arxiv.org/pdf/2007.00489"]}
-{"year":"2020","title":"Understanding Word Embeddings and Language Models","authors":["JM Gomez-Perez, R Denaux, A Garcia-Silva - A Practical Guide to Hybrid Natural …, 2020"],"snippet":"… 1) pre-trained contextualized word embeddings (ELMo), (2) pre-trained context-independent word embeddings learnt from Common Crawl (fastText), Twitter … Another version of this classifier using in addition fastText embeddings …","url":["https://link.springer.com/chapter/10.1007/978-3-030-44830-1_3"]}
-{"year":"2020","title":"UniBO@ KIPoS: Fine-tuning the Italian “BERTology” for PoS-tagging Spoken Data","authors":["F Tamburini"],"snippet":"… project. Also for GilBERTo it is available only the uncased model. • UmBERTo4: the more recent model de- veloped explicitly for Italian, as far as we know, is UmBERTo ('Musixmatch/umbertocommoncrawl-cased-v1' – umC). As …","url":["http://ceur-ws.org/Vol-2765/paper94.pdf"]}
-{"year":"2020","title":"UninaStudents@ SardiStance: Stance Detection in Italian Tweets-Task A","authors":["M Moraca, G Sabella, S Morra - Proceedings of the 7th Evaluation Campaign of …, 2020"],"snippet":"… As Master students, we approached these NLP topics for the first time. Therefore, we are aware 5https://huggingface.co/Musixmatch/umbertocommoncrawl-cased-v1 that our results are not at the state of the art in the field. However …","url":["http://ceur-ws.org/Vol-2765/paper146.pdf"]}
-{"year":"2020","title":"Unit Test Case Generation with Transformers","authors":["M Tufano, D Drain, A Svyatkovskiy, SK Deng… - arXiv preprint arXiv …, 2020"],"snippet":"… It has been pre-trained on the Common Crawl dataset [32] constituting nearly a trillion words, an expanded version of the WebText [33] dataset, two internet-based books corpora (Books1 and Books2), and English-language Wikipedia …","url":["https://arxiv.org/pdf/2009.05617"]}
-{"year":"2020","title":"Uniting Plain Language, Cognitive Fluency, and Believability","authors":["SI Johnson - 2020"],"snippet":"… considering at least four linguistic features (Romanyshyn, 2018). Similar to Randall (2019), Romanyshyn (2018) considers the frequency of a word using Common Crawl, a large corpus of web content. Taking this approach one step further, she lemmatizes the 1 …","url":["http://search.proquest.com/openview/9b0f9b3644e2372cabfc4aedb4849573/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2020","title":"UNITOR@ Sardistance2020: Combining Transformer-based Architectures and Transfer Learning for Robust Stance Detection","authors":["S Giorgioni, M Politi, S Salman, D Croce, R Basili - … of the 7th Evaluation Campaign of …, 2020"],"snippet":"… with <negativo>3. 2https://huggingface.co/Musixmatch/ umberto-commoncrawlcased-v1 3We discarded the few available messages with mixed po- larity, to simplify the final classification task. Irony Detection. We speculate …","url":["http://ceur-ws.org/Vol-2765/paper99.pdf"]}
-{"year":"2020","title":"Unsupervised Cross-Lingual Part-of-Speech Tagging for Truly Low-Resource Scenarios","authors":["R Eskander, S Muresan, M Collins - Proceedings of the 2020 Conference on …, 2020"],"snippet":"… essential when the domain of the training data is different from the one of the pre-trained em- beddings, which is the case in our learning setup, where we use the Bible data for training, while the XLM-R model is trained on text …","url":["https://www.aclweb.org/anthology/2020.emnlp-main.391.pdf"]}
-{"year":"2020","title":"Unsupervised Cross-lingual Representation Learning for Speech Recognition","authors":["A Conneau, A Baevski, R Collobert, A Mohamed… - arXiv preprint arXiv …, 2020"],"snippet":"… For comparison with [29] only, we train 4-gram n-gram language models on CommonCrawl data [25, 50] for Assamese (140MiB of text data), Swahili (2GiB), Tamil (4.8GiB) and Lao (763MiB); for this experiment only we report word error rate (WER). 3.2 Training details …","url":["https://arxiv.org/pdf/2006.13979"]}
-{"year":"2020","title":"Unsupervised Domain Clusters in Pretrained Language Models","authors":["R Aharoni, Y Goldberg - arXiv preprint arXiv:2004.02105, 2020"],"snippet":"… exact requirements from such data with respect to all the aforementioned aspects. On top of that, domain labels are usually unavailable – eg in large-scale web-crawled data like Common Crawl1 which was recently used to …","url":["https://arxiv.org/pdf/2004.02105"]}
-{"year":"2020","title":"Unsupervised Evaluation of Human Translation Quality","authors":["Y Zhou, D Bollegala - 2019"],"snippet":"… publicly available monolingual word embeddings. Specifically, we first use the monolingual word embeddings, which are trained on Wikipedia and Common Crawl using fastText (Grave et al., 2018). Because our dataset contains …","url":["https://pdfs.semanticscholar.org/2735/60e715ee0dfaae2dee75fbb7484f811816d2.pdf"]}
-{"year":"2020","title":"Unsupervised Label Refinement Improves Dataless Text Classification","authors":["Z Chu, K Stratos, K Gimpel - arXiv preprint arXiv:2012.04194, 2020"],"snippet":"… We use the 300 dimensional GloVe vectors7 trained on Common Crawl.8 We experiment with two distance functions when using GloVe: cosine and L2 … 7http://nlp.stanford.edu/ data/glove.840B.300d.zip 8https://commoncrawl.org/ ROBERTA Dual Encoder …","url":["https://arxiv.org/pdf/2012.04194"]}
-{"year":"2020","title":"Unsupervised Question Decomposition for Question Answering","authors":["E Perez, P Lewis, W Yih, K Cho, D Kiela"],"snippet":"… Specifically, by leveraging >10M questions from Common Crawl, we learn to map from the distribution of multi-hop questions to the distribution of single-hop subquestions … We retrieve candidates from a corpus of 10M simple …","url":["https://rcqa-ws.github.io/papers/paper9.pdf"]}
-{"year":"2020","title":"UPB at GermEval-2020 Task 3: Assessing Summaries for German Texts using BERTScore and Sentence-BERT","authors":["A Paraschiv"],"snippet":"… bert-base-german-europeana-uc 2 Uncased Europeana newspapers bert-base-germanuc2 Uncased Wikipedia, Subtitles, News, Commoncrawl literary-german-bert3 Uncased German Fiction Literature bert-adapted-german-press4 Uncased Newspapers …","url":["http://ceur-ws.org/Vol-2624/germeval-task3-paper2.pdf"]}
-{"year":"2020","title":"Upgrading the Newsroom: An Automated Image Selection System for News Articles","authors":["F Liu, R Lebret, D Orel, P Sordet, K Aberer - arXiv preprint arXiv:2004.11449, 2020"],"snippet":"Page 1. 1 Upgrading the Newsroom: An Automated Image Selection System for News Articles FANGYU LIU∗, Language Technology Lab (LTL), University of Cambridge, United Kingdom RÉMI LEBRET, Distributed Information …","url":["https://arxiv.org/pdf/2004.11449"]}
-{"year":"2020","title":"UR NLP@ HaSpeeDe 2 at EVALITA 2020: Towards Robust Hate Speech Detection with Contextual Embeddings","authors":["J Hoffmann, U Kruschwitz"],"snippet":"… XLM-R is based on XLM and RoBERTa. It is trained on data covering 100 languages in a very large (2TB) CommonCrawl. Transformer document embeddings are obtained from (the large version of) XLM-R. In addition Page 3 …","url":["http://ceur-ws.org/Vol-2765/paper105.pdf"]}
-{"year":"2020","title":"Urban Dictionary Embeddings for Slang NLP Applications","authors":["S Wilson, W Magdy, B McGillivray, K Garimella… - Proceedings of The 12th …, 2020"],"snippet":"… with the goal of producing generally applicable word embeddings, many popular pre-trained word embeddings have been fit to large and diverse corpora of text from the web such as the Common Crawl.3 In … 2 http://smash …","url":["https://www.aclweb.org/anthology/2020.lrec-1.586.pdf"]}
-{"year":"2020","title":"URL-based Phishing Attack Detection by Convolutional Neural Networks","authors":["J Nowak, M Korytkowski, P Najgebauer, M Wozniak…"],"snippet":"… The database downloaded during the article writing contained 10,604 records. To obtain legitimate websites, the second part of the training dataset was downloaded from the Common Crawl Foundation (http://commoncrawl.org/) …","url":["http://ajiips.com.au/papers/V15.2/v15n2_64-71.pdf"]}
-{"year":"2020","title":"Using Natural Language Preprocessing Architecture (NLPA) for Big Data Text Sources","authors":["M Novo-Lourés, R Pavón, R Laza, D Ruano-Ordas… - Scientific Programming, 2020"],"snippet":"Journals; Publish with us; Publishing partnerships; About us; Blog. Scientific Programming. +Journal Menu. PDF. Journal overview. For authorsFor reviewersFor editorsTable of Contents Special Issues.","url":["https://www.hindawi.com/journals/sp/2020/2390941/"]}
-{"year":"2020","title":"Using Natural Language Processing to Identify Similar Patent Documents","authors":["J Navrozidis, H Jansson - LU-CS-EX, 2020"],"snippet":"Page 1. MASTER'S THESIS 2020 Using Natural Language Processing to Identify Similar Patent Documents Hannes Jansson, Jakob Navrozidis ISSN 1650-2884 LU-CS-EX: 2020-05 DEPARTMENT OF COMPUTER …","url":["https://lup.lub.lu.se/student-papers/record/9008699/file/9026407.pdf"]}
-{"year":"2020","title":"Using Probabilistic Soft Logic to Improve Information Extraction in the Legal Domain","authors":["B Kirsch, S Giesselbach, T Schmude, M Völkening…"],"snippet":"… spaCy Classifier: This architecture is based on a CNN with mean pooling and a final feed-forward layer. The network is fed with pretrained word embeddings trained on the German Wikipedia and the German common crawl (Ortiz Suárez et al., 2019).9 …","url":["http://ceur-ws.org/Vol-2738/LWDA2020_paper_29.pdf"]}
-{"year":"2020","title":"Using Publisher Partisanship for Partisan News Detection","authors":["CL Yeh"],"snippet":"Page 1. Using Publisher Partisanship for Partisan News Detection A Comparison of Performance between Annotation Levels Chia-Lun Yeh Page 2. Using Publisher Partisanship for Partisan News Detection A …","url":["https://pdfs.semanticscholar.org/604f/233a21249d44085e41e7415ed9741fc69d5e.pdf"]}
-{"year":"2020","title":"Using Sentences as Semantic Representations in Large Scale Zero-Shot Learning","authors":["YL Cacheux, HL Borgne, M Crucianu - arXiv preprint arXiv:2010.02959, 2020"],"snippet":"… For the same reason, we used FastText and Glove models pre-trained on Common Crawl We used a 300-dimension version for all three … Fasttext: https://fasttext.cc/docs/en/englishvectors.html (version trained on Common Crawl with 600B tokens, no subword information) …","url":["https://arxiv.org/pdf/2010.02959"]}
-{"year":"2020","title":"Using Word Embeddings to Learn a Better Food Ontology. Front","authors":["J Youn, T Naravane, I Tagkopoulos - Artif. Intell, 2020"],"snippet":"… W ikinews W ikipedia 2017 + UMBC webbase + s tatmt.org 0.313 2.98 Crawl Common Crawl 0 .317 3.00 Word2vec (Mikolov …","url":["https://pdfs.semanticscholar.org/1c47/eb747f27eab42bc8e9e9ded83dd784eadf4c.pdf"]}
-{"year":"2020","title":"ValNorm: A New Word Embedding Intrinsic Evaluation Method Reveals Valence Biases are Consistent Across Languages and Over Decades","authors":["A Toney, A Caliskan - arXiv preprint arXiv:2006.03950, 2020"],"snippet":"… We choose six widely used pre-trained word embedding sets, listed in Table 2, to compare ValNorm's performance on different algorithms (GloVe, fastText, word2vec) and training corpora (Common Crawl, Wikipedia, OpenSubtitles …","url":["https://arxiv.org/pdf/2006.03950"]}
-{"year":"2020","title":"Vandalism Detection in Crowdsourced Knowledge Bases","authors":["S Heindorf - 2019"],"snippet":"… Manual OpenStreetMap, Uniprot, WordNet, MusicBrainz, IMDb Wikipedia, WikiHow, YouTube Wikia/FANDOM, StackExchange, Quora, Yahoo Answers DBpedia, YAGO, NELL dblp, BabelNet Internet Archive, Common Crawl NASA …","url":["https://pdfs.semanticscholar.org/e70f/b288ceb09fc244554a274f31cd1217663027.pdf"]}
-{"year":"2020","title":"Variational Transformers for Diverse Response Generation","authors":["Z Lin, GI Winata, P Xu, Z Liu, P Fung - arXiv preprint arXiv:2003.12738, 2020"],"snippet":"… embeddings. The first is EMBFT (Liu et al., 2016) that calculates the average of word embeddings in a sentence using FastText (Mikolov et al., 2018) which is trained with Common Crawl and Wikipedia data. We use FastText …","url":["https://arxiv.org/pdf/2003.12738"]}
-{"year":"2020","title":"VECO: Variable Encoder-decoder Pre-training for Cross-lingual Understanding and Generation","authors":["F Luo, W Wang, J Liu, Y Liu, B Bi, S Huang, F Huang… - arXiv preprint arXiv …, 2020"],"snippet":"… We adopt the same 250K vocabulary that is also used by XLM-R (Conneau et al., 2019) and mBART (Liu et al., 2020b). Pre-Training Datasets For monolingual training datasets, we reconstruct Common-Crawl Corpus used in XLM-R (Conneau et al., 2019) …","url":["https://arxiv.org/pdf/2010.16046"]}
-{"year":"2020","title":"Video Question Answering on Screencast Tutorials","authors":["W Zhao, S Kim, N Xu, H Jin"],"snippet":"… visual cues, and graph embeddings. All the models have the word embeddings initialized with the 300-dimensional pretrained fastText [Bojanowski et al., 2017] vectors on Common Crawl dataset. The convolutional layer in …","url":["https://www.ijcai.org/Proceedings/2020/0148.pdf"]}
-{"year":"2020","title":"Visual and Textual Deep Feature Fusion for Document Image Classification","authors":["S Bakkali, Z Ming, M Coustaty, M Rusinol - Proceedings of the IEEE/CVF Conference …, 2020"],"snippet":"… FastText algorithm we used was pretrained on 2 million word vectors trained on Common Crawl (600B tokens), and uses 1,999,996 word vectors. Bert: Bert [11] is a contextualized bidirectional word embedding based on the transformer architecture …","url":["http://openaccess.thecvf.com/content_CVPRW_2020/papers/w34/Bakkali_Visual_and_Textual_Deep_Feature_Fusion_for_Document_Image_Classification_CVPRW_2020_paper.pdf"]}
-{"year":"2020","title":"Visual Relations Augmented Cross-modal Retrieval","authors":["Y Guo, J Chen, H Zhang, YG Jiang - … of the 2020 International Conference on …, 2020"],"snippet":"… vector with the corresponding visual feature. The label embedding vector is obtained with a learnable embedding layer initialized by GloVe [25] that pre-trained on the Common-Crawl dataset. Given a set of object categories …","url":["https://dl.acm.org/doi/pdf/10.1145/3372278.3390709"]}
-{"year":"2020","title":"Visualizing and Interpreting RNN Models in URL-based Phishing Detection","authors":["T Feng, C Yue - Proceedings of the 25th ACM Symposium on Access …, 2020"],"snippet":"… The legitimate URLs came from the Common Crawl (www.commoncrawl.org) open web searching database, while the phishing URLs came from the popular PhishTank (www.phishtank.com) phishing website repository. In …","url":["https://dl.acm.org/doi/pdf/10.1145/3381991.3395602"]}
-{"year":"2020","title":"Wat zei je? Detecting Out-of-Distribution Translations with Variational Transformers","authors":["TZ Xiao, AN Gomez, Y Gal - arXiv preprint arXiv:2006.08344, 2020"],"snippet":"… The following datasets were used in our experiments: • WMT EN ↔ DE: The training set for translation tasks between English (EN) and German (DE) composed of news-commentary-v13 with 284k sentences pairs, wmt13 …","url":["https://arxiv.org/pdf/2006.08344"]}
-{"year":"2020","title":"Weakly-Supervised Multi-Level Attentional Reconstruction Network for Grounding Textual Queries in Videos","authors":["Y Song, J Wang, L Ma, Z Yu, J Yu - arXiv preprint arXiv:2003.07048, 2020"],"snippet":"… For each second we uniformly sample 16 frames as input to C3D, and obtain a 4096-dimentional visual feature from fc6 layer. Each word from the query is represented by GloVe [22] word embedding vector pre-trained on Common Crawl …","url":["https://arxiv.org/pdf/2003.07048"]}
-{"year":"2020","title":"Web Crawl Processing on Big Data Scale","authors":["JM Patel - Getting Structured Data from the Internet, 2020"],"snippet":"… We got this domain ranks file and column names from the common crawl blog post (https://commoncrawl.org/2020/02/host-and-domain-level-webgraphs-novdecjan-2019-2020/); they publish new domain ranks about four …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-6576-5_7"]}
-{"year":"2020","title":"Web Table Extraction, Retrieval, and Augmentation: A Survey","authors":["S Zhang, K Balog - ACM Transactions on Intelligent Systems and …, 2020"],"snippet":"… Table corpora Type #tables Source WDC 2012 Web Table Corpus Web tables 147M Web crawl (Common Crawl) WDC 2015 Web Table Corpus Web tables 233M Web crawl (Common Crawl) Dresden Web Tables Corpus …","url":["https://dl.acm.org/doi/abs/10.1145/3372117"]}
-{"year":"2020","title":"Webis at TREC 2019: Decision Track","authors":["A Bondarenko, M Fröbe, V Kasturia, M Völske, B Stein…"],"snippet":"… In Proceedings of SIGIR 2017. 1419–1420. [2] Janek Bevendor , Benno Stein, Ma hias Hagen, and Martin Po hast. 2018. Elastic ChatNoir: Search Engine for the ClueWeb and the Common Crawl. In Proceedings of ECIR 2018. 820–824 …","url":["https://trec.nist.gov/pubs/trec28/papers/Webis.D.pdf"]}
-{"year":"2020","title":"Webis at TREC 2020: Health Misinformation Track","authors":["A Bondarenko, M Fröbe, S Günther, M Hagen… - 2020","J Bevendor, A Bondarenko, M Fröbe, S Günther…"],"snippet":"… During retrieval, we used ChatNoirs existing weighting scheme for the two Common Crawl snapshots, which combines BM25 scores of multiple elds … we relax the precondition of documents' 1We have indexed a 2015 and …","url":["https://webis.de/downloads/publications/papers/stein_2020zb.pdf","https://webis.de/downloads/publications/slides/stein_2020zb.pdf"]}
-{"year":"2020","title":"Webly Supervised Semantic Embeddings for Large Scale Zero-Shot Learning","authors":["YL Cacheux, A Popescu, HL Borgne - arXiv preprint arXiv:2008.02880, 2020"],"snippet":"… prototypes. These embeddings are extracted from generic large scale text collections such as Wikipedia [21,34] or Common Crawl [6,33] … use. For GloVe on ImageNet, the model pretrained on Common Crawl has the best performance …","url":["https://arxiv.org/pdf/2008.02880"]}
-{"year":"2020","title":"WeChat Neural Machine Translation Systems for WMT20","authors":["F Meng, J Yan, Y Liu, Y Gao, X Zeng, Q Zeng, P Li… - arXiv preprint arXiv …, 2020"],"snippet":"… Commentary, Common Crawl and Gigaword corpus. The English monolingual data includes News crawl, News discussions, Europarl v10, News Commentary, Common Crawl, Wiki dumps and the Gigaword corpus. After …","url":["https://arxiv.org/pdf/2010.00247"]}
-{"year":"2020","title":"WEFE: The Word Embeddings Fairness Evaluation Framework","authors":["P Badilla, F Bravo-Marquez, J Pérez"],"snippet":"… The following are the pre-trained em- bedding models that we consider: 1) conceptnet, 2) fasttextwikipedia, 3) glove-twitter, 4) glove-wikipedia, 5) lexveccommoncrawl, 6) word2vec-googlenews, and 7) word2vecgender-hard …","url":["https://felipebravom.com/publications/ijcai2020.pdf"]}
-{"year":"2020","title":"WEmbSim: A Simple yet Effective Metric for Image Captioning","authors":["N Sharif, L White, M Bennamoun, W Liu, SAA Shah - arXiv preprint arXiv:2012.13137, 2020"],"snippet":"… Page 5. TABLE I T - . Name Source Dims Corpus Corpus Size Vocabulary Size GloVE 840B [12] 300 Common Crawl 8.4 · 1011 2 · 106 Word2vec [6] 300 Google News (100B) 1.0 · 1011 3 · 106 FastText [13] 300 Wikipedia 4.0 · 109 3 · 106 …","url":["https://arxiv.org/pdf/2012.13137"]}
-{"year":"2020","title":"What determines the order of adjectives in English? Comparing efficiency-based theories using dependency treebanks","authors":["R Futrell, W Dyer, G Scontras - Proceedings of the 58th Annual Meeting of the …, 2020"],"snippet":"… sklearn.cluster.KMeans applied to a pretrained set of 1.9 million 300-dimension GloVe vectors2 generated from the Common Crawl corpus … Table 1a shows the accuracies of our predictors in predicting held-out …","url":["https://www.aclweb.org/anthology/2020.acl-main.181.pdf"]}
-{"year":"2020","title":"What Sparks Joy: The AffectVec Emotion Database","authors":["S Raji, G de Melo - Proceedings of The Web Conference 2020, 2020"],"snippet":"… We consider the cosine similarity of word– emotion pairs in word2vec trained on the Google News corpus [18], GloVe [26] trained on Twitter (200-dim.) and CommonCrawl (840B, 300-dim.), as well as the counterfitted vectors by Mrksic et al. [24]. Results …","url":["https://dl.acm.org/doi/pdf/10.1145/3366423.3380068"]}
-{"year":"2020","title":"What the [MASK]? Making Sense of Language-Specific BERT Models","authors":["D Nozza, F Bianchi, D Hovy - arXiv preprint arXiv:2003.02912, 2020"],"snippet":"… OSCAR (Open Super-large Crawled Almanach coRpus) (Or- tiz Suárez et al., 2019) is a huge multilingual corpus obtained by filtering the Common Crawl corpus, which is a parallel multilingual corpus comprised of crawled documents from the internet …","url":["https://arxiv.org/pdf/2003.02912"]}
-{"year":"2020","title":"When and Why is Unsupervised Neural Machine Translation Useless?","authors":["Y Kim, M Graça, H Ney - arXiv preprint arXiv:2004.10581, 2020","YKM Graça, H Ney - 22nd Annual Conference of the European Association …"],"snippet":"… However, for low-resource language pairs, it is difficult to match the data domain of both sides on a large scale. For example, our monolingual data for Kazakh is mostly from Wikipedia and Common Crawl, while the English data is solely from News Crawl …","url":["https://arxiv.org/pdf/2004.10581","https://www.aclweb.org/anthology/2020.eamt-1.pdf#page=55"]}
-{"year":"2020","title":"When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models","authors":["B Muller, A Anastasopoulos, B Sagot, D Seddah - arXiv preprint arXiv:2010.12858, 2020"],"snippet":"… al., 2019). OSCAR is a corpus extracted from a Common Crawl Web snapshot.3 It provides a significant 2Also see the discussion in Section §3.2 on the script distributions in mBERT. 3http://commoncrawl.org/ Language (iso …","url":["https://arxiv.org/pdf/2010.12858"]}
-{"year":"2020","title":"When do Word Embeddings Accurately Reflect Surveys on our Beliefs About People?","authors":["K Joseph, JH Morgan - arXiv preprint arXiv:2004.12043, 2020"],"snippet":"Page 1. When do Word Embeddings Accurately Reflect Surveys on our Beliefs about People? Kenneth Joseph Computer Science and Engineering University at Buffalo Buffalo, NY, 14226 kjoseph@buffalo.edu Jonathan H. Morgan …","url":["https://arxiv.org/pdf/2004.12043"]}
-{"year":"2020","title":"When Does Unsupervised Machine Translation Work?","authors":["K Marchisio, K Duh, P Koehn - arXiv preprint arXiv:2004.05516, 2020"],"snippet":"… “News crawl” (News) and “Common Crawl” (CC) settings determine whether the system can flexibly handle diverse datasets. Specifics of the datasets used are described in subsequent subsections … UN = United Nations …","url":["https://arxiv.org/pdf/2004.05516"]}
-{"year":"2020","title":"Which* BERT? A Survey Organizing Contextualized Encoders","authors":["P Xia, S Wu, B Van Durme - arXiv preprint arXiv:2010.00854, 2020"],"snippet":"… Raffel et al. (2019) curate a 745GB subset of Common Crawl (CC),10 which starkly contrasts with the 13GB used in BERT … 9https://sites.google.com/ view/ sustainlp2020/shared-task 10https://commoncrawl.org/ scrapes publicly …","url":["https://arxiv.org/pdf/2010.00854"]}
-{"year":"2020","title":"Who is asking? humans and machines experience","authors":["M Klein, L Balakireva, H Shankar"],"snippet":"… licenses/by/4.0/). Similarly, the motivation behind the recent study by Thompson and Jian [14] based on two Common Crawl samples of the web was to quantify the use of HTTP DOIs versus URLs of landing pages. They found …","url":["https://osf.io/pgxc3/download"]}
-{"year":"2020","title":"Why are events important and how to compute them in geospatial research?","authors":["M Yuan"],"snippet":"… GPT-3 is a gigantic neural network with 175 billion input parameters and 96 layers of transformer decoders, each of which has 1.8 billion parameters, and is pre-trained with 45TB (499 billion tokens) compressed data from five …","url":["https://www.josis.org/index.php/josis/article/viewFile/723/300"]}
-{"year":"2020","title":"Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity","authors":["T Isbister, M Sahlgren - arXiv preprint arXiv:2009.03116, 2020"],"snippet":"… et al., 2018). We use the CBOW model that has been trained on Common Crawl and Wikipedia.6 As with Word2Vec, the vectors for sentences are obtained by averaging the embedding vector for each word. BERT: Deep Transformer …","url":["https://arxiv.org/pdf/2009.03116"]}
-{"year":"2020","title":"Why Overfitting Isn't Always Bad: Retrofitting Cross-Lingual Word Embeddings to Dictionaries","authors":["M Zhang, Y Fujinuma, MJ Paul, J Boyd-Graber"],"snippet":"… We align English embeddings with six target languages: German (DE), Spanish (ES), French (FR), Italian (IT), Japanese (JA), and Chinese (ZH). We use 300-dimensional fastText vectors trained on Wikipedia and Common Crawl (Grave et al., 2018) …","url":["http://users.umiacs.umd.edu/~mozhi/pdf/retrofit.pdf"]}
-{"year":"2020","title":"Wide range screening of algorithmic bias in word embedding models using large sentiment lexicons reveals underreported bias types","authors":["D Rozado - PLOS ONE, 2020"],"snippet":"… This work systematically analyzed 3 popular word embeddings methods: Word2vec (Skip-gram) [4], Glove [9] and FastText [10], externally pretrained on a wide array of corpora such as Google News, Wikipedia, Twitter or Common Crawl …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231189"]}
-{"year":"2020","title":"WikiAsp: A Dataset for Multi-domain Aspect-based Summarization","authors":["H Hayashi, P Budania, P Wang, C Ackerson… - arXiv preprint arXiv …, 2020"],"snippet":"… sections of Wikipedia from referenced web pages. Following the WikiSum data generation script,3 we first crawled cited references covered by CommonCrawl for each Wikipedia article. We then recover all the sections4 of …","url":["https://arxiv.org/pdf/2011.07832"]}
-{"year":"2020","title":"Will it Unblend?","authors":["Y Pinter, CL Jacobs, J Eisenstein - arXiv preprint arXiv:2009.09123, 2020"],"snippet":"Page 1. Will it Unblend? Yuval Pinter School of Interactive Computing Georgia Institute of Technology Atlanta, GA, USA uvp@gatech.edu Cassandra L. Jacobs Department of Psychology University of Wisconsin Madison, WI, USA cjacobs2@wisc.edu …","url":["https://arxiv.org/pdf/2009.09123"]}
-{"year":"2020","title":"Word associations and the distance properties of context-aware word embeddings","authors":["MA Rodriguez, P Merlo - Proceedings of the 24th Conference on Computational …, 2020"],"snippet":"… However, in this work, we used the pre-trained FASTTEXT embeddings provided by the official site of FASTTEXT, that we expressly do not modify.3 The embeddings are trained on 600-billion tokens from …","url":["https://www.aclweb.org/anthology/2020.conll-1.30.pdf"]}
-{"year":"2020","title":"Word Embedding Evaluation for Sinhala","authors":["D Lakmal, S Ranathunga, S Peramuna, I Herath - Proceedings of The 12th Language …, 2020"],"snippet":"… Common Crawl can be considered as a precious starting point for building a cleaned large corpus for … Common Crawl monthly dataset only contains 0.007% of content in Sinhala4, however, this amount is still … 4https …","url":["https://www.aclweb.org/anthology/2020.lrec-1.231.pdf"]}
-{"year":"2020","title":"WORD EMBEDDINGS IN ROMANIAN FOR THE RETAIL BANKING DOMAIN","authors":["I RAICU, N BOITOUT, R BOLOGA, MG STURZA"],"snippet":"… In addition, Facebook released a year later another version of FastText pre-trained word embeddings, trained on Common Crawl and Wikipedia [4]. Another pre-trained word embeddings in Romanian can be found at …","url":["https://www.researchgate.net/profile/Irina_Raicu2/publication/341553193_WORD_EMBEDDINGS_IN_ROMANIAN_FOR_THE_RETAIL_BANKING_DOMAIN/links/5ec6d768a6fdcc90d68c8596/WORD-EMBEDDINGS-IN-ROMANIAN-FOR-THE-RETAIL-BANKING-DOMAIN.pdf"]}
-{"year":"2020","title":"Word Embeddings Inherently Recover the Conceptual Organization of the Human Mind","authors":["V Swift - arXiv preprint arXiv:2002.10284, 2020"],"snippet":"… Sub-word information was incorporated on the basis of n-grams (length = 5), with a window size of 5 and 10 negatives, and a step size of .05. The English model was trained on a Common Crawl corpus comprised of English text from 2.96 billion webpages …","url":["https://arxiv.org/pdf/2002.10284"]}
-{"year":"2020","title":"Word meaning in minds and machines","authors":["BM Lake, GL Murphy - arXiv preprint arXiv:2008.01766, 2020"],"snippet":"… is illustrated in Figure 1A. CBOW has been trained on tremendous corpora; for instance, in this article, we analyze a large-scale CBOW model trained on the Common Crawl corpus of 630 billion words. CBOW learns a word …","url":["https://arxiv.org/pdf/2008.01766"]}
-{"year":"2020","title":"Word Representations for Named Entity Recognition","authors":["R Agerri"],"snippet":"… Transformers: Bertin (Gigaword+Wikipedia), XLM-RoBERTa (Common Crawl) and mBERT (Wikipedia + books) • Project annotations (various strategies) Page 54 … BETO (various sources) – XLM-RoBERTa (Common Crawl 2.5TB) – mBERT (Wikipedia + books) …","url":["https://cit-ai.net/archive/CitAI_Seminar_11Nov20_Agerri.pdf"]}
-{"year":"2020","title":"Word Representations for Neural Network Based Myanmar Text-to-Speech System","authors":["AM Hlaing, WP Pa"],"snippet":"… In [21], the size of word vectors is small, and it contains about 55K entries for Myanmar language and can be downloaded from the link [23]. In [22], the word vectors are trained on Common Crawl and Wikipedia using fastText …","url":["http://www.inass.org/2020/2020043023.pdf"]}
-{"year":"2020","title":"Word Rotator's Distance","authors":["S Yokoi, R Takahashi, R Akama, J Suzuki, K Inui - Proceedings of the 2020 …, 2020"],"snippet":"Page 1. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pages 2944–2960, November 16–20, 2020. c 2020 Association for Computational Linguistics 2944 Word Rotator's Distance …","url":["https://www.aclweb.org/anthology/2020.emnlp-main.236.pdf"]}
-{"year":"2020","title":"Word Rotator's Distance: Decomposing Vectors Gives Better Representations","authors":["S Yokoi, R Takahashi, R Akama, J Suzuki, K Inui - arXiv preprint arXiv:2004.15003, 2020"],"snippet":"Page 1. Word Rotator's Distance: Decomposing Vectors Gives Better Representations Sho Yokoi1 Ryo Takahashi1,2 Reina Akama1,2 Jun Suzuki1,2 Kentaro Inui1,2 1 Tohoku University 2 RIKEN {yokoi, ryo.t, reina.a, jun.suzuki, inui}@ecei.tohoku.ac.jp Abstract …","url":["https://arxiv.org/pdf/2004.15003"]}
-{"year":"2020","title":"Word Sense Disambiguation for 158 Languages using Word Embeddings Only","authors":["V Logacheva, D Teslenko, A Shelmanov, S Remus… - arXiv preprint arXiv …, 2020"],"snippet":"… The contributions of our work are the following: 1The full list languages is available at fasttext.cc and includes English and 157 other languages for which embeddings were trained on a combination of Wikipedia and CommonCrawl texts …","url":["https://arxiv.org/pdf/2003.06651"]}
-{"year":"2020","title":"Word2Sent: A new learning sentiment‐embedding model with low dimension for sentence level sentiment classification","authors":["M Kasri, M Birjali, A Beni‐Hssane - Concurrency and Computation: Practice and …"],"snippet":"Abstract Word embedding models become an increasingly important method that embeds words into a high dimensional space. These models have been widely utilized to extract semantic and syntactic feat...","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.6149"]}
-{"year":"2020","title":"Words Matter: Gender, Jobs and Applicant Behavior in India","authors":["S Chaturvedi, K Mahajan, Z Siddique - 2020"],"snippet":"… Pennington et al., 2014). The 300 dimensional pretrained word vectors have been obtained by training the algorithm on web data from common crawl, and comprise 2.2 million unique words. Cosine similarity between any …","url":["https://www.dse.univr.it/documenti/Seminario/documenti/documenti102498.pdf"]}
-{"year":"2020","title":"Words, constructions and corpora: Network representations of constructional semantics for Mandarin space particles","authors":["ACH Chen - Corpus Linguistics and Linguistic Theory, 2020"],"snippet":"Jump to Content Jump to Main Navigation Publications. Subjects. Architecture and Design Arts Asian and Pacific Studies Business and Economics Chemistry Classical and Ancient Near Eastern Studies Computer Sciences Cultural …","url":["https://www.degruyter.com/view/journals/cllt/ahead-of-print/article-10.1515-cllt-2020-0012/article-10.1515-cllt-2020-0012.xml"]}
-{"year":"2020","title":"Wrestling with Complexity in Computational Social Science: Theory, Estimation and Representation","authors":["S de Marchi - The SAGE Handbook of Research Methods in Political …, 2020"]}
-{"year":"2020","title":"WT5?! Training Text-to-Text Models to Explain their Predictions","authors":["S Narang, C Raffel, K Lee, A Roberts, N Fiedel… - arXiv preprint arXiv …, 2020"],"snippet":"… 1997; Ruder, 2017). In Raffel et al. (2019), this framework was used to pre-train Transformer (Vaswani et al., 2017) models on a large collection of unlabeled text drawn from the Common Crawl web scrape. We use the result …","url":["https://arxiv.org/pdf/2004.14546"]}
-{"year":"2020","title":"X-FACTR: Multilingual Factual Knowledge Retrieval from Pretrained Language Models","authors":["Z Jiang, A Anastasopoulos, J Araki, H Ding, G Neubig - Proceedings of the 2020 …, 2020"],"snippet":"Page 1. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, pages 5943–5959, November 16–20, 2020. c 2020 Association for Computational Linguistics 5943 X-FACTR: Multilingual …","url":["https://www.aclweb.org/anthology/2020.emnlp-main.479.pdf"]}
-{"year":"2020","title":"XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation","authors":["Y Liang, N Duan, Y Gong, N Wu, F Guo, W Qi, M Gong… - arXiv preprint arXiv …, 2020"],"snippet":"… 2.1.2 Large Corpus (LC) Multilingual Corpus Following Wenzek et al. (2019), we construct a clean version of Common Crawl (CC)3 as the multilingual corpus … 2https://github.com/ attardi/wikiextractor. 3https://commoncrawl.org/. available in English …","url":["https://arxiv.org/pdf/2004.01401"]}
-{"year":"2020","title":"Xiaomi's Submissions for IWSLT 2020 Open Domain Translation Task","authors":["Y Sun, M Guo, X Li, J Cui, B Wang - Proceedings of the 17th International Conference …, 2020"],"snippet":"… And for unconstrained submission, we choose the largescale amounts of Commoncrawl Chinese10 and Japanese11 dataset as additional monolingual data for training LMs and executing BT to enhance our NMT systems …","url":["https://www.aclweb.org/anthology/2020.iwslt-1.18.pdf"]}
-{"year":"2020","title":"YNU OXZ@ HaSpeeDe 2 and AMI: XLM-RoBERTa with Ordered Neurons LSTM for classification task at EVALITA 2020","authors":["X Ou, H Li - Proceedings of Sixth Evaluation Campaign of Natural …, 2020"],"snippet":"… scale multi-language pre-training model. It can be un- derstood as a combination of XLM and RoBER- Ta. It is trained on 2.5 TB of newly created clean CommonCrawl data in 100 languages. Because the training of the model …","url":["http://ceur-ws.org/Vol-2765/paper93.pdf"]}
-{"year":"2020","title":"Zero Shot Domain Generalization","authors":["U Maniyar, AA Deshmukh, U Dogan… - arXiv preprint arXiv …, 2020"],"snippet":"… Thus using semantic space helps us in the visual classification task. We use word embeddings of classes - in particular, simple GloVe embeddings [28] trained on Common Crawl corpus - as the semantic space in this work …","url":["https://arxiv.org/pdf/2008.07443"]}
-{"year":"2020","title":"Zero-shot semantic segmentation using relation network","authors":["Y Zhang - 2020"],"snippet":"Page 1. University of Jyväskylä Faculty of Information Technology Yindong Zhang Zero-shot Semantic Segmentation using Relation Network Master's thesis of information technology May 28, 2020 Page 2. i Author: Yindong …","url":["https://jyx.jyu.fi/bitstream/handle/123456789/69720/1/URN%3ANBN%3Afi%3Ajyu-202006043976.pdf"]}
-{"year":"2021","title":"'I'm just feeling like it'. On the relationship between the use of the progressive and sentiment polarity in Italian","authors":["L Viola"],"snippet":"… art transformer-based machine learning model for emotion and sentiment classification in Italian which employs the Italian BERT model UmBERTo trained on Commoncrawl ITA (Parisi, Francia, and Magnani [2020] 2021). For …","url":["https://www.uib.no/sites/w3.uib.no/files/attachments/viola.pdf"]}
-{"year":"2021","title":"4. Unlocking value from AI in financial services: strategic and organizational tradeoffs vs. media narratives","authors":["G Lanzolla, S Santoni, C Tucci - Artificial Intelligence for Sustainable Value Creation, 2021"],"snippet":"Page 87. 4. Unlocking value from AI in financial services: strategic and organizational tradeoffs vs. media narratives Gianvito Lanzolla, Simone Santoni and Christopher Tucci 1. INTRODUCTION In 1955, McCarthy wrote that …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=_9BCEAAAQBAJ&oi=fnd&pg=PA70&dq=commoncrawl&ots=Z-4LjY9D6U&sig=BHpJ4i9Wq18ZWZDIWoGm5BnHqSY"]}
-{"year":"2021","title":"6 Data Collection and Representation for Similar Languages, Varieties and Dialects","authors":["T Samardžic, N Ljubešic - Similar Languages, Varieties, and Dialects: A …, 2021"],"snippet":"… Page 146. Data Collection and Representation for Similar Languages 127 Another project that should be mentioned in this brief overview is the CommonCrawl, a project performing crawls over the whole internet for textual data since 2013 with regular data updates …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=hhA5EAAAQBAJ&oi=fnd&pg=PA121&dq=commoncrawl&ots=2XimIiF4W6&sig=XlIzLoiwAxuodhBmJeC_iS9BSeg"]}
-{"year":"2021","title":"\" Short is the Road that Leads from Fear to Hate\": Fear Speech in Indian WhatsApp Groups","authors":["P Saha, B Mathew, K Garimella, A Mukherjee - arXiv preprint arXiv:2102.03870, 2021"],"snippet":"Page 1. “Short is the Road that Leads from Fear to Hate”: Fear Speech in Indian WhatsApp Groups Punyajoy Saha punyajoys@iitkgp.ac.in Indian Institute of Technology Kharagpur, West Bengal, India Binny Mathew binnymathew …","url":["https://arxiv.org/pdf/2102.03870"]}
-{"year":"2021","title":"A common framework for quantifying the learnability of nouns and verbs","authors":["Y Zhou, D Yurovsky - Proceedings of the Annual Meeting of the Cognitive …, 2021"],"snippet":"… We used pre-trained 300-dimensional semantic vectors derived from the the Common Crawl corpus composed of 840 billion tokens and 2.2 million words. For our analysis, we considered only the words that corresponded to the relevant 434 images. Procedure …","url":["https://escholarship.org/content/qt8dn6k82j/qt8dn6k82j.pdf"]}
-{"year":"2021","title":"A Comparative Study on Word Embeddings in Deep Learning for Text Classification","authors":["C Wang, P Nulty, D Lillis"],"snippet":"… 3https://nlp.stanford.edu/projects/glove/ 4https://commoncrawl.org/ 5https://fasttext.cc/ 6https://allennlp.org/elmo 7We additionally experimented from the fourth-to-last (-4) layer to the last layer … 300s refers to the GloVe …","url":["https://lill.is/pubs/Wang2020a.pdf"]}
-{"year":"2021","title":"A Comparison Framework for Product Matching Algorithms","authors":["J Foxcroft - 2021"],"snippet":"Page 1. A Comparison Framework for Product Matching Algorithms by Jeremy Foxcroft A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science Guelph, Ontario, Canada …","url":["https://atrium.lib.uoguelph.ca/xmlui/bitstream/handle/10214/26375/Foxcroft_Jeremy_202109_Msc.pdf?sequence=3"]}
-{"year":"2021","title":"A Comparison of Approaches to Document-level Machine Translation","authors":["Z Ma, S Edunov, M Auli - arXiv preprint arXiv:2101.11040, 2021"],"snippet":"… WMT17 English-German (en-de). For this benchmark, we follow the setup of Müller et al. (2018) whose training data includes the Europarl, Common Crawl, News Commentary and Rapid corpora, totaling nearly 6M sentence pairs …","url":["https://arxiv.org/pdf/2101.11040"]}
-{"year":"2021","title":"A Comprehensive Assessment of Dialog Evaluation Metrics","authors":["YT Yeh, M Eskenazi, S Mehri - arXiv preprint arXiv:2106.03706, 2021"],"snippet":"… RoBERTa, which is employed in USR (Mehri and Eskenazi, 2020b), improves the training techniques in BERT and trains the model on a much larger corpus which includes the CommonCrawl News dataset (Mackenzie et al., 2020) and text ex- tracted from Reddit …","url":["https://arxiv.org/pdf/2106.03706"]}
-{"year":"2021","title":"A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search","authors":["M Wang, X Xu, Q Yue, Y Wang - arXiv preprint arXiv:2101.12631, 2021"],"snippet":"Page 1. A Comprehensive Survey and Experimental Comparison of Graph-Based Approximate Nearest Neighbor Search Mengzhao Wang1, Xiaoliang Xu1, Qiang Yue1, Yuxiang Wang1,∗ 1Hangzhou Dianzi University …","url":["https://arxiv.org/pdf/2101.12631"]}
-{"year":"2021","title":"A Comprehensive Survey of Grammatical Error Correction","authors":["Y Wang, Y Wang, K Dang, J Liu, Z Liu - ACM Transactions on Intelligent Systems and …, 2021"],"snippet":"Grammatical error correction (GEC) is an important application aspect of natural language processing techniques, and GEC system is a kind of very important intelligent system that has long been explored both in academic and industrial …","url":["https://dl.acm.org/doi/abs/10.1145/3474840"]}
-{"year":"2021","title":"A Computational Framework for Slang Generation","authors":["Z Sun, R Zemel, Y Xu - arXiv preprint arXiv:2102.01826, 2021"],"snippet":"… To compare with and compute the baseline em- bedding methods M for definition sentences, we used 300-dimensional fastText embeddings (Bo- janowski et al., 2017) pre-trained with subword information on 600 billion …","url":["https://arxiv.org/pdf/2102.01826"]}
-{"year":"2021","title":"A coral-reef approach to extract information from HTML tables","authors":["P Jiménez Aguirre, JC Roldán Salvador… - Applied Soft Computing …, 2022","P Jiménez, JC Roldán, R Corchuelo - Applied Soft Computing, 2021"],"snippet":"… Unfortunately, a recent analysis of the 32.04 million domains in the November 2019 Common Crawl has revealed that only 11.92 million domains provide such semantic hints [10], which argues for a method to deal with the remaining 20.12 …","url":["https://idus.us.es/bitstream/handle/11441/131990/1/1-s2.0-S1568494621009029-main.pdf?sequence=1","https://www.sciencedirect.com/science/article/pii/S1568494621009029"]}
-{"year":"2021","title":"A COVID-19 news coverage mood map of Europe","authors":["F Robertson, J Lagus, K Kajava - Proceedings of the EACL Hackashop on News …, 2021"],"snippet":"… Newscrawl is a web crawl provided by the Common Crawl organisation which is updated more frequently and contains only data from news websites2. In order to keep the size of the corpus manageable and the extraction …","url":["https://www.aclweb.org/anthology/2021.hackashop-1.15.pdf"]}
-{"year":"2021","title":"A data quality approach to the identification of discrimination risk in automated decision making systems","authors":["A Vetrò, M Torchiano, M Mecati - Government Information Quarterly, 2021"],"snippet":"… Similarly, a scientific experiment on the search engine Common Crawl (De-Arteaga et al., 2019) revealed an unequal treatment due to gender imbalance in the input data (almost 400,000 biographies): authors compared …","url":["https://www.sciencedirect.com/science/article/pii/S0740624X21000551"]}
-{"year":"2021","title":"A data-centric review of deep transfer learning with applications to text data","authors":["S Bashath, N Perera, S Tripathi, K Manjang, M Dehmer… - Information Sciences, 2021"],"snippet":"Abstract In recent years, many applications are using various forms of deep learning models. Such methods are usually based on traditional learning paradigms requiring the consistency of properties among the feature spaces of the training and …","url":["https://www.sciencedirect.com/science/article/pii/S002002552101183X"]}
-{"year":"2021","title":"A deep learning-based bilingual Hindi and Punjabi named entity recognition system using enhanced word embeddings","authors":["A Goyal, V Gupta, M Kumar - Knowledge-Based Systems, 2021"],"snippet":"… Initially, we collect Facebook’s pre-trained FastText embeddings which are trained on Wikipedia and common crawl data with 300 dimensions for our Hindi and Punjabi datasets. But after experiments, we find many of the words in our dataset are …","url":["https://www.sciencedirect.com/science/article/pii/S0950705121008637"]}
-{"year":"2021","title":"A Framework for Generating Extractive Summary from Multiple Malayalam Documents","authors":["K Manju, S David Peter, SM Idicula - Information, 2021"],"snippet":"… Semantically similar words are mapped to nearby points in the vector space. In this work the vectorization of the terms in the document are performed using the pretrained word embedding model FastText for Malayalam, trained on Common Crawl and Wikipedia …","url":["https://www.mdpi.com/2078-2489/12/1/41/pdf"]}
-{"year":"2021","title":"A Framework for Quality Assessment of Semantic Annotations of Tabular Data","authors":["R Avogadro, M Cremaschi, E Jiménez-Ruiz, A Rula - International Semantic Web …, 2021"],"snippet":"… 1 Introduction. Much information is conveyed within tables. A prominent example is the large set of relational databases or tabular data present on the Web. To size the spread of tabular data, 2.5M tables have been …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88361-4_31"]}
-{"year":"2021","title":"A Fusion Approach for Paper Submission Recommendation System","authors":["ST Huynh, N Dang, PT Huynh, DH Nguyen, BT Nguyen - International Conference on …, 2021"],"snippet":"… Finally, we use crawl-300d-2M 3 as the pre-train embedding matrix, which has 600 billion tokens and 2 million word vectors trained on Common Crawl. It can make using crawl-300d-2M more efficiently in vectorization. As depicted in Fig …","url":["https://link.springer.com/chapter/10.1007/978-3-030-79463-7_7"]}
-{"year":"2021","title":"A General Language Assistant as a Laboratory for Alignment","authors":["A Askell, Y Bai, A Chen, D Drain, D Ganguli… - arXiv preprint arXiv …, 2021"],"snippet":"… For language model pre-training, these models are trained for 400B tokens on a distribution consisting mostly of filtered common crawl … The natural language dataset was composed of 55% heavily filtered common crawl data (220B tokens), 32 …","url":["https://arxiv.org/pdf/2112.00861"]}
-{"year":"2021","title":"A Heuristic-driven Ensemble Framework for COVID-19 Fake News Detection","authors":["SD Das, A Basak, S Dutta - arXiv preprint arXiv:2101.03545, 2021"],"snippet":"… of model-specific special tokens. Each model also has its corresponding vocabulary associated with its tokenizer, trained on a large corpus data like GLUE, wikitext-103, CommonCrawl data etc. During training, each model …","url":["https://arxiv.org/pdf/2101.03545"]}
-{"year":"2021","title":"A Heuristic-driven Uncertainty based Ensemble Framework for Fake News Detection in Tweets and News Articles","authors":["SD Das, A Basak, S Dutta - arXiv preprint arXiv:2104.01791, 2021"],"snippet":"… Each model also has its corresponding vocabulary associated with its tokenizer, trained on a large corpus data like GLUE, wikitext-103, CommonCrawl data etc. During training, each model applies the tokenization …","url":["https://arxiv.org/pdf/2104.01791"]}
-{"year":"2021","title":"A Human Being Wrote This Law","authors":["AB Cyphert"],"snippet":"… GPT-3 had an impressively large data training set: it was trained on the Common Crawl dataset, a nearly trillion-word dataset,22 which includes everything from traditional news sites like the New York Times to sites like Reddit.The Common …","url":["https://lawreview.law.ucdavis.edu/issues/55/1/articles/files/55-1_Cyphert.pdf"]}
-{"year":"2021","title":"A Literature Survey of Recent Advances in Chatbots","authors":["G Caldarini, S Jaf, K McGarry - 2021"],"snippet":"… This led to the development of pretrained systems such as BERT (Bidirectional Encoder Representations from transformers) [46] and GPT (Generative Pre-trained Transformer), which were trained with huge language datasets, such as Wikipedia …","url":["https://www.preprints.org/manuscript/202112.0265/download/final_file"]}
-{"year":"2021","title":"A Mechanism for Producing Aligned Latent Spaces with Autoencoders","authors":["S Jain, A Radhakrishnan, C Uhler - arXiv preprint arXiv:2106.15456, 2021"],"snippet":"… 6.1 Alignment of GloVe Embeddings In this section, we apply our theory to align semantic/syntactic directions in GloVe word embeddings [21]. We use 300 dimensional GloVe vectors that were trained on Common Crawl with 840 billion tokens …","url":["https://arxiv.org/pdf/2106.15456"]}
-{"year":"2021","title":"A Multi-Platform Analysis of Political News Discussion and Sharing on Web Communities","authors":["Y Wang, S Zannettou, J Blackburn, B Bradlyn… - arXiv preprint arXiv …, 2021"],"snippet":"… supported types of entities). The model re- lies on Convolutional Neural Networks (CNNs), trained on the OntoNotes dataset [90], as well as Glove vectors [62] trained on the Common Crawl dataset [17]. 2.3 News Stories Identification …","url":["https://arxiv.org/pdf/2103.03631"]}
-{"year":"2021","title":"A Multi-Task Learning Model for Multidimensional Relevance Assessment","authors":["DGP Putri, M Viviani, G Pasi - International Conference of the Cross-Language …, 2021"],"snippet":"… 6 In particular, we focused on the ad-hoc retrieval subtask. The data consist of Web pages crawled by means of CommonCrawl, 7 related to the health-related domain. The data collections consider 50 topics/queries and associated documents …","url":["https://link.springer.com/chapter/10.1007/978-3-030-85251-1_9"]}
-{"year":"2021","title":"A Multifactorial Approach to Crosslinguistic Constituent Orderings","authors":["Z Liu"],"snippet":"… The data for training these LMs was taken from the raw data of the CoNLL 2017 Shared Task on multilingual parsing (Ginter et al. 2017), which contains texts from Common Crawl and Wikipedia. The architecture of the LM was the same for every language …","url":["https://www.researchgate.net/profile/Zoey-Liu/publication/354204297_A_Multifactorial_Approach_to_Crosslinguistic_Constituent_Orderings/links/612c0095c69a4e487967c628/A-Multifactorial-Approach-to-Crosslinguistic-Constituent-Orderings.pdf"]}
-{"year":"2021","title":"A Multitask Framework to Detect Depression, Sentiment and Multi-label Emotion from Suicide Notes","authors":["S Ghosh, A Ekbal, P Bhattacharyya - Cognitive Computation, 2021"],"snippet":"The significant rise in suicides is a major cause of concern in public health domain. Depression plays a major role in increasing suicide ideation among th.","url":["https://link.springer.com/article/10.1007/s12559-021-09828-7"]}
-{"year":"2021","title":"A Novel Corpus of Discourse Structure in Humans and Computers","authors":["B Hemmatian, S Feucht, R Avram, A Wey, M Garg… - arXiv preprint arXiv …, 2021"],"snippet":"We present a novel corpus of 445 humanand computer-generated documents, comprising about 27,000 clauses, annotated for semantic clause types and coherence relations that allow for nuanced comparison of artificial and natural …","url":["https://arxiv.org/pdf/2111.05940"]}
-{"year":"2021","title":"A novel fusion-based deep learning model for sentiment analysis of COVID-19 tweets","authors":["ME Basiri, S Nemati, M Abdar, S Asadi, UR Acharrya - Knowledge-Based Systems, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0950705121005049"]}
-{"year":"2021","title":"A NOVEL TRILINGUAL DATASET FOR CRISIS NEWS CATEGORIZATION ACROSS LANGUAGES","authors":["K Kajava - 2021"],"snippet":"… Use Common Crawl instead • “the goal of democratizing access to web information by producing and maintaining an open repository of web crawl data that is universally accessible and analyzable” (https://commoncrawl.org/about/, accessed June 1 2021) …","url":["https://blogs.helsinki.fi/language-technology/files/2021/06/LT-Seminar-2021-06-03-Kaisla-Kajava.pdf"]}
-{"year":"2021","title":"A Primer on Pretrained Multilingual Language Models","authors":["S Doddapaneni, G Ramesh, A Kunchukuttan, P Kumar… - arXiv preprint arXiv …, 2021"],"snippet":"… and they differ in the architecture (eg, number of layers, parameters, etc), objective functions used for training (eg, monolingual masked language modeling objective, translation language modeling objective, etc), data used …","url":["https://arxiv.org/pdf/2107.00676"]}
-{"year":"2021","title":"A Probing Task on Linguistic Properties of Korean Sentence Embedding","authors":["A Ahn, BI Ko, D Lee, G Han, M Shin, J Nam - Annual Conference on Human and …, 2021"],"snippet":"Abstract 본 연구는 한국어 문장 임베딩 (embedding) 에 담겨진 언어적 속성을 평가 하기 위한 프로빙 태스크 (Probing Task) 를 소개한다. 프로빙 태스크는 임베딩 으로부터 문장의 표층적, 통사적, 의미적 속성을 구분하는 문제로 영어, 폴란드어 …","url":["https://www.koreascience.or.kr/article/CFKO202130060614813.pdf"]}
-{"year":"2021","title":"A Residual Network Architecture for Hindi NER using Fasttext and BERT embedding layers","authors":["R Shelke, S Vanjale"],"snippet":"… It provides word embedding for Hindi (and 157 other languages) and is based on the CBOW (Continuous Bag-of-Words) model. The CBOW model learns by predicting the current word based on its context, and it was trained on Common Crawl and Wikipedia …","url":["https://www.novyimir.net/gallery/nmrj%202867f.pdf"]}
-{"year":"2021","title":"A Review of Bangla Natural Language Processing Tasks and the Utility of Transformer Models","authors":["F Alam, A Hasan, T Alam, A Khan, J Tajrin, N Khan… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. A Review of Bangla Natural Language Processing Tasks and the Utility of Transformer Models FIROJ ALAM, Qatar Computing Research Institute, HBKU, Qatar MD. ARID HASAN, Cognitive Insight Limited, Bangladesh …","url":["https://arxiv.org/pdf/2107.03844"]}
-{"year":"2021","title":"A Review of Public Datasets in Question Answering Research","authors":["BB Cambazoglu, M Sanderson, F Scholer, B Croft"],"snippet":"… matching the question. The sentences are selected based on their tf-idf similarity to the question. The underlying web page collection contains pages from the July 2018 archive of the Common Crawl web repository. Task. Given a …","url":["http://www.sigir.org/wp-content/uploads/2020/12/p07.pdf"]}
-{"year":"2021","title":"A Semi-supervised Multi-task Learning Approach to Classify Customer Contact Intents","authors":["L Dong, MC Spencer, A Biagi"],"snippet":"… We note that this ALBERT model is trained as a multiclass classification with only positive cases. 3.2.2 SS MT D/TAPT ALBERT The pretrained language models are mostly trained on well-known corpora, such as Wikipedia, Common Crawl, BookCorpus, Reddit, etc …","url":["https://assets.amazon.science/79/22/d9237534448293405083a73b896d/a-semi-supervised-multi-task-learning-approach-to-classify-customer-contact-intents.pdf"]}
-{"year":"2021","title":"A Short Survey of LSTM Models for De-identification of Medical Free Text","authors":["JL Leevy, TM Khoshgoftaar - 2020 IEEE 6th International Conference on …, 2020"],"snippet":"… The training set was obtained from the 2014 i2b2 challenge, while the test set came from the University of Florida (UF) Health Integrated Data Repository 5. Word embeddings were sourced from GoogleNews [54] …","url":["https://ieeexplore.ieee.org/abstract/document/9319017/"]}
-{"year":"2021","title":"A Simple Post-Processing Technique for Improving Readability Assessment of Texts using Word Mover's Distance","authors":["JM Imperial, E Ong - arXiv preprint arXiv:2103.07277, 2021"],"snippet":"… technique described in Section 4. For the word embeddings of English, German, and Filipino needed for the technique, we downloaded the resources from the fastText website5. The word embeddings in various …","url":["https://arxiv.org/pdf/2103.07277"]}
-{"year":"2021","title":"A Simple Recipe for Multilingual Grammatical Error Correction","authors":["S Rothe, J Mallinson, E Malmi, S Krause, A Severyn - arXiv preprint arXiv:2106.03830, 2021"],"snippet":"… 2.1 mT5 Pre-training mT5 has been pre-trained on mC4 corpus, a subset of Common Crawl, covering 101 languages and composed of about 50 billion documents. For details on mC4, we refer the reader to the original paper (Xue et al., 2020) …","url":["https://arxiv.org/pdf/2106.03830"]}
-{"year":"2021","title":"A Spontaneous Stereotype Content Model: Taxonomy, Properties, and Prediction.","authors":["G Nicolas, X Bai, ST Fiske"],"snippet":"… model trained on the Common Crawl (600 billion words obtained from various internet sources) … the Common Crawl (600 billion words), a Glove model trained using around 840 billion words from the Common Crawl (Pennington, Socher, & Manning, 2014; …","url":["https://www.nicolaslab.org/publication/sscm/SSCM.pdf"]}
-{"year":"2021","title":"A Study of Analogical Density in Various Corpora at Various Granularity","authors":["R Fam, Y Lepage - Information, 2021"],"snippet":"In this paper, we inspect the theoretical problem of counting the number of analogies between sentences contained in a text. Based on this, we measure the analogical density of the text. We focus on analogy at the sentence level …","url":["https://www.mdpi.com/2078-2489/12/8/314/pdf"]}
-{"year":"2021","title":"A Study of Analogical Density in Various Corpora at Various Granularity. Information 2021, 12, 314","authors":["R Fam, Y Lepage - 2021"],"snippet":"… Table 4 shows the statistics of Multi30K corpus. • CommonCrawl (available at: commoncrawl.org accessed on 20 September 2020) is a crawled web archive and dataset … Table 5 shows the statistics on the CommonCrawl corpus …","url":["https://search.proquest.com/openview/208b192bc36d7c71728c73989c304dea/1?pq-origsite=gscholar&cbl=2032384"]}
-{"year":"2021","title":"A study on performance improvement considering the balance between corpus in Neural Machine Translation","authors":["C Park, K Park, H Moon, S Eo, H Lim - Journal of the Korea Convergence Society, 2021"],"snippet":"… 1. Concept of Corpus Weight Balance GPT3도 Common Crawl, WebText2, Books1, Books2, Wikipedia 등의 데이터를 합쳐 모델을 훈련하 게 된다. 그러나 말뭉치 간의 ��성 및 특징(어투, 문체, 도메인 등)이 다름에도 하나의 데이터로 …","url":["https://www.koreascience.or.kr/article/JAKO202116954598769.pdf"]}
-{"year":"2021","title":"A Survey of COVID-19 Misinformation: Datasets, Detection Techniques and Open Issues","authors":["AR Ullah, A Das, A Das, MA Kabir, K Shu - arXiv preprint arXiv:2110.00737, 2021"],"snippet":"Page 1. A Survey of COVID-19 Misinformation: Datasets, Detection Techniques and Open Issues AR Sana Ullaha, Anupam Dasa, Anik Dasb, Muhammad Ashad Kabirc,∗, Kai Shud aDepartment of Computer Science and Engineering …","url":["https://arxiv.org/pdf/2110.00737"]}
-{"year":"2021","title":"A Survey of Machine Learning-Based Solutions for Phishing Website Detection","authors":["L Tang, QH Mahmoud - Machine Learning and Knowledge Extraction, 2021"],"snippet":"With the development of the Internet, network security has aroused people's attention. It can be said that a secure network environment is a basis for the rapid and sound development of the Internet. Phishing is an essential class …","url":["https://www.mdpi.com/2504-4990/3/3/34/pdf"]}
-{"year":"2021","title":"A Survey of Recent Abstract Summarization Techniques","authors":["D Puspitaningrum - Proceedings of Sixth International Congress on …, 2021"],"snippet":"… For C4, taken from Common Crawl scrape from April 2019 and applied some cleansing filters, it results in a very clean 750GB text dataset of large pre-training datasets, more extensive than other pre-training datasets. 3.2 Pegasus-XSum (Pegasus) …","url":["https://hal.archives-ouvertes.fr/hal-03216381/document"]}
-{"year":"2021","title":"A Survey on Bias in Deep NLP","authors":["I Garrido-Muñoz, A Montejo-Ráez, F Martínez-Santiago… - 2021"],"snippet":"… 2016 [26] Gender Word2Vec, GloVe GoogleNews corpus (w2vNEWS), Common Crawl English Analogies/Cosine Similarity Vector Space Manipulation After - 2017 [10] Gender, Ethnicity GloVe, Word2Vec Common …","url":["https://www.preprints.org/manuscript/202103.0049/download/final_file"]}
-{"year":"2021","title":"A Survey on Data Augmentation for Text Classification","authors":["M Bayer, MA Kaufhold, C Reuter - arXiv preprint arXiv:2107.03158, 2021"],"snippet":"… CNN+LSTM/GRU HON RSN-1 RSN-2 Word2Vec Hate Speech FastText Wikipedia GoogleNews W2V GloVe Common Crawl GloVe Common Crawl GloVe Common Crawl -22.7 (Macro F1) +1.0 -3.3 +0.3 -0.2 0 [44] 1. Method …","url":["https://arxiv.org/pdf/2107.03158"]}
-{"year":"2021","title":"A Survey on Low-Resource Neural Machine Translation","authors":["R Wang, X Tan, R Luo, T Qin, TY Liu - arXiv preprint arXiv:2107.04239, 2021"],"snippet":"Page 1. A Survey on Low-Resource Neural Machine Translation Rui Wang, Xu Tan, Renqian Luo, Tao Qin and Tie-Yan Liu Microsoft Research Asia {ruiwa, xuta, t-reluo, taoqin, tyliu}@microsoft.com Abstract Neural approaches …","url":["https://arxiv.org/pdf/2107.04239"]}
-{"year":"2021","title":"A Survey On Neural Word Embeddings","authors":["E Sezerer, S Tekir - arXiv preprint arXiv:2110.01804, 2021"],"snippet":"… ivLBL/vLBL [95] 2013 100-600 Wiki LBL Performance - NCE [47] GloVe [109] 2014 300 Wiki, Gigaword, Commoncrawl LBL+coocurence Matrix Training - - DEPS [69] 2014 300 Wiki CBOW Training Stanford tagger[129] …","url":["https://arxiv.org/pdf/2110.01804"]}
-{"year":"2021","title":"A Survey on Statistical Approaches for Abstractive Summarization of Low Resource Language Documents","authors":["P Deshpande, S Jahirabadkar - Smart Trends in Computing and Communications, 2022"],"snippet":"… German Wiki data is used as real data and synthetic data is a common crawl data. Synthetic data is used to increase size of data. Three settings are considered for generation of summaries: (1) Transformer model using real data for training. …","url":["https://link.springer.com/chapter/10.1007/978-981-16-4016-2_69"]}
-{"year":"2021","title":"A Synthetic FACS Framework for Expanding Facial Expression Lexicons","authors":["C Butler - 2021"],"snippet":"Page 1. A Synthetic FACS Framework for Expanding Facial Expression Lexicons DISSERTATION Submitted in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY (Computer Science) at the …","url":["https://search.proquest.com/openview/ebf5a87df8275e6fc6fac0b1c0b21b44/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"A system for proactive risk assessment of application changes in cloud operations","authors":["R Batta, L Shwartz, M Nidd, AP Azad, H Kumar - 2021 IEEE 14th International …, 2021"],"snippet":"Abstract Change is one of the biggest contributors to service outages. With more enterprises migrating their applications to cloud and using automated build and deployment the volume and rate of changes has significantly increased. Furthermore …","url":["https://www.computer.org/csdl/proceedings-article/cloud/2021/006000a112/1ymJ4TXNxUA"]}
-{"year":"2021","title":"A Systematic Investigation of Commonsense Understanding in Large Language Models","authors":["XL Li, A Kuncoro, CM d'Autume, P Blunsom… - arXiv preprint arXiv …, 2021"],"snippet":"… 2019), we train our models using the cleaned version of Common Crawl corpus (C4), around 800 GB of data. Our largest model, with 32 transformer layers and 7 billion parameters, has a similar number of parameters to the open-sourced GPT-J model (Wang …","url":["https://arxiv.org/pdf/2111.00607"]}
-{"year":"2021","title":"A systems-wide understanding of the human olfactory percept chemical space","authors":["J Kowalewski, B Huynh, A Ray - Chemical Senses, 2021"],"snippet":"… 2015; spaCy, 2016), and a convolutional neural network previously trained on GloVe Common Crawl (Pennington, Socher, & Manning, 2014) and OntoNotes 5. The training set is comprised of more than 1 million English …","url":["https://academic.oup.com/chemse/advance-article-abstract/doi/10.1093/chemse/bjab007/6153471"]}
-{"year":"2021","title":"A Targeted Attack on Black-Box Neural Machine Translation with Parallel Data Poisoning","authors":["C Xu, J Wang, Y Tang, F Guzmán, BIP Rubinstein… - Proceedings of the Web …, 2021"],"snippet":"… 3https://commoncrawl.org/ 4We assume that these poisoned web pages are archived and to be used for parallel data extraction. This assumption is realistic as we find that the crawling services commonly used for parallel …","url":["https://dl.acm.org/doi/abs/10.1145/3442381.3450034"]}
-{"year":"2021","title":"A unified approach to sentence segmentation of punctuated text in many languages","authors":["R Wicks, M Post"],"snippet":"Page 1. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, pages 3995–4007 August 1–6, 2021 …","url":["https://aclanthology.org/2021.acl-long.309.pdf"]}
-{"year":"2021","title":"A word embedding-based approach to cross-lingual topic modeling","authors":["CH Chang, SY Hwang - Knowledge and Information Systems, 2021"],"snippet":"The cross-lingual topic analysis aims at extracting latent topics from corpora of different languages. Early approaches rely on high-cost multilingual reso.","url":["https://link.springer.com/article/10.1007/s10115-021-01555-7"]}
-{"year":"2021","title":"ABC: Attention with Bounded-memory Control","authors":["H Peng, J Kasai, N Pappas, D Yogatama, Z Wu, L Kong… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Under review as a conference paper at ICLR 2022 ABC: ATTENTION WITH BOUNDED-MEMORY CONTROL Hao Peng♠ Jungo Kasai♠ Nikolaos Pappas♠ Dani Yogatama♣ Zhaofeng Wu♦∗ Lingpeng Kong♦ Roy Schwartz …","url":["https://arxiv.org/pdf/2110.02488"]}
-{"year":"2021","title":"Abuse is Contextual, What about NLP? The Role of Context in Abusive Language Annotation and Detection","authors":["S Menini, AP Aprosio, S Tonelli - arXiv preprint arXiv:2103.14916, 2021"],"snippet":"… In particular, all vectors are extracted starting from the pre-trained embeddings obtained from the Common Crawl corpus.5 Since SVM takes in input sentence embeddings, we convert the context and the current tweet …","url":["https://arxiv.org/pdf/2103.14916"]}
-{"year":"2021","title":"Accelerated execution via eager-release of dependencies in task-based workflows","authors":["H Elshazly, F Lordan, J Ejarque, RM Badia - The International Journal of High …, 2021"],"snippet":"Task-based programming models offer a flexible way to express the unstructured parallelism patterns of nowadays complex applications. This expressive capability is required to achieve maximum possi...","url":["https://journals.sagepub.com/doi/abs/10.1177/1094342021997558"]}
-{"year":"2021","title":"Accelerating Text Communication via Abbreviated Sentence Input","authors":["J Adhikary, J Berger, K Vertanen"],"snippet":"… For our out-of-domain training set, we used one billion words of web text from Common Crawl1. We only … As shown in Table 1, random sentences from Common Crawl averaged 30 words. The cross-entropy 1https://commoncrawl …","url":["https://aclanthology.org/2021.acl-long.514.pdf"]}
-{"year":"2021","title":"Accurate Word Representations with Universal Visual Guidance","authors":["Z Zhang, H Yu, H Zhao, R Wang, M Utiyama - arXiv preprint arXiv:2012.15086, 2020"],"snippet":"… WMT'14 EN-DE 4.43M bilingual sentence pairs of the WMT14 dataset were used as training data, including Common Crawl, News Commentary, and Europarl v7. The newstest2013 and newstest2014 datasets were …","url":["https://arxiv.org/pdf/2012.15086"]}
-{"year":"2021","title":"Acquiring and Harnessing Verb Knowledge for Multilingual Natural Language Processing","authors":["O Majewska - 2021"],"snippet":"Advances in representation learning have enabled natural language processing models to derive non-negligible linguistic information directly from text corpora in an unsupervised fashion. However, this signal is underused in downstream tasks …","url":["https://www.repository.cam.ac.uk/bitstream/handle/1810/329292/Majewska_PhDThesis_final.pdf?sequence=4"]}
-{"year":"2021","title":"Active Learning for Argument Mining: A Practical Approach","authors":["N Solmsdorf, D Trautmann, H Schütze - arXiv preprint arXiv:2109.13611, 2021"],"snippet":"… easily discernible argumentative statements. The corpus contains 1,000 sentences per topic, ie, in total 8,000 instances, which were tapped from a Common Crawl snapshot and in- dexed with Elasticsearch. The time-consuming …","url":["https://arxiv.org/pdf/2109.13611"]}
-{"year":"2021","title":"Adapting Neural Machine Translation for Automatic Post-Editing","authors":["A Sharma, P Gupta, A Nelakanti"],"snippet":"… reference as the output. 3.2 Pre-training on domain-specific data FAIR's WMT'19 NMT model was trained on Newscrawl and Commoncrawl datasets while the source of this year's APE data is Wikipedia. To fix the domain mismatch …","url":["https://assets.amazon.science/dc/df/5443c00541a9b6257f6110c5bb86/adapting-neural-machine-translation-for-automatic-post-editing.pdf"]}
-{"year":"2021","title":"Adaptive Ranking Relevant Source Files for Bug Reports Using Genetic Algorithm","authors":["H Fujita, H Perez-Meana - 2021"],"snippet":"Abstract. Precisely locating buggy files for a given bug report is a cumbersome and time-consuming task, particularly in a large-scale project with thousands of source files and bug reports. An efficient bug localization module is desirable to improve the …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=GYxJEAAAQBAJ&oi=fnd&pg=PA430&dq=commoncrawl&ots=IRy65Bdasc&sig=WyEQAu3sL155gzwLW6pjIX4mCwQ"]}
-{"year":"2021","title":"ADEPT: An Adjective-Dependent Plausibility Task","authors":["A Emami, I Porada, A Olteanu, K Suleman, A Trischler…"],"snippet":"… 4 Dataset To construct ADEPT, we scrape text samples from English Wikipedia and Common Crawl, extracting adjectival modifier-noun pairs that occur with high frequency … We extracted 10 million pairs from English …","url":["https://aclanthology.org/2021.acl-long.553.pdf"]}
-{"year":"2021","title":"ADPBC: Arabic Dependency Parsing Based Corpora for Information Extraction","authors":["S Mohamed, M Hussien, HM Mousa - 2021"],"snippet":"… Sch. Econ. Res. Pap. No. WP BRP., 2018. [27] A. Panchenko, E. Ruppert, S. Faralli, SP Ponzetto, and C. Biemann, “Building a web-scale dependency-parsed corpus from common crawl,” Lr. 2018 - 11th Int. Conf. Lang. Resour. Eval., pp. 1816–1823, 2019 …","url":["http://www.mecs-press.org/ijitcs/ijitcs-v13-n1/IJITCS-V13-N1-4.pdf"]}
-{"year":"2021","title":"Advances and Trends in Artificial Intelligence. From Theory to Practice: 34th International Conference on Industrial, Engineering and Other Applications of Applied …","authors":["H Fujita"],"snippet":"Page 1. Hamido Fujita Ali Selamat Jerry Chun-Wei Lin Moonis Ali (Eds.) Advances and Trends in Artificial Intelligence From Theory to Practice 34th International Conference on Industrial, Engineering and Other Applications …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=ihg5EAAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=fSoeFLOj--&sig=NR8xQHWDWjlGUhvSgV52wEaaT6Y"]}
-{"year":"2021","title":"Aggressive and Offensive Language Identification in Hindi, Bangla, and English: A Comparative Study","authors":["R Kumar, B Lahiri, AK Ojha - SN Computer Science, 2021"],"snippet":"In the present paper, we carry out a comparative study between offensive and aggressive language and attempt to understand their inter-relationship. To car.","url":["https://link.springer.com/article/10.1007/s42979-020-00414-6"]}
-{"year":"2021","title":"AlephBERT: A Hebrew Large Pre-Trained Language Model to Start-off your Hebrew NLP Application With","authors":["A Seker, E Bandel, D Bareket, I Brusilovsky… - arXiv preprint arXiv …, 2021"],"snippet":"… Oscar: A deduplicated Hebrew portion of the OSCAR corpus, which is “extracted from Common Crawl via language classification, filtering and cleaning” (Ortiz Suárez et al., 2020). • Twitter: Texts of Hebrew tweets collected between 2014-09-28 and 2018-03-07 …","url":["https://arxiv.org/pdf/2104.04052"]}
-{"year":"2021","title":"Alignment of Language Agents","authors":["Z Kenton, T Everitt, L Weidinger, I Gabriel, V Mikulik… - arXiv preprint arXiv …, 2021","ZKTEL Weidinger, IGVMG Irving"],"snippet":"… Large scale unlabeled datasets are collected from the web, such as the CommonCrawl dataset (Raffel et al., 2019). Input data and labels are created by chopping a sentence into … Brown et al. (2020) attempt to im- prove …","url":["https://ar5iv.labs.arxiv.org/html/2103.14659","https://arxiv.org/pdf/2103.14659"]}
-{"year":"2021","title":"All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training","authors":["I Nassar, S Herath, E Abbasnejad, W Buntine, G Haffari - arXiv preprint arXiv …, 2021"],"snippet":"… A detailed description of such relations and examples thereof can be found in the ConceptNet documentation8. On the other hand, GloVe and word2vec are two prominent sets of word embeddings, the former is trained on 840 …","url":["https://arxiv.org/pdf/2104.05248"]}
-{"year":"2021","title":"All NLP Tasks Are Generation Tasks: A General Pretraining Framework","authors":["Z Du, Y Qian, X Liu, M Ding, J Qiu, Z Yang, J Tang - arXiv preprint arXiv:2103.10360, 2021"],"snippet":"Page 1. All NLP Tasks Are Generation Tasks: A General Pretraining Framework Zhengxiao Du *12 Yujie Qian * 3 Xiao Liu 1 2 Ming Ding 1 2 Jiezhong Qiu 1 2 Zhilin Yang 4 2 Jie Tang 1 2 Abstract There have been various types …","url":["https://arxiv.org/pdf/2103.10360"]}
-{"year":"2021","title":"Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training","authors":["B Zheng, L Dong, S Huang, S Singhal, W Che, T Liu… - arXiv preprint arXiv …, 2021"],"snippet":"… are learned on the reconstructed CommonCrawl corpus (Chi et al., 2021b; Conneau et al., 2020) using SentencePiece (Kudo and Richardson, 2018) with the unigram language model (Kudo, 2018). The unigram distributions …","url":["https://arxiv.org/pdf/2109.07306"]}
-{"year":"2021","title":"ALX: Large Scale Matrix Factorization on TPUs","authors":["H Mehta, S Rendle, W Krichene, L Zhang - arXiv preprint arXiv:2112.02194, 2021"],"snippet":"We present ALX, an open-source library for distributed matrix factorization using Alternating Least Squares, written in JAX. Our design allows for efficient use of the TPU architecture and scales well to matrix factorization problems of O(B) rows/columns …","url":["https://arxiv.org/pdf/2112.02194"]}
-{"year":"2021","title":"AMMUS: A Survey of Transformer-based Pretrained Models in Natural Language Processing","authors":["KS Kalyan, A Rajasekharan, S Sangeetha - arXiv preprint arXiv:2108.05542, 2021"],"snippet":"… mT6 [91], XLM-E [89] CC-Aligned [108] Parallel corpus of 292 million non-English common crawl document pairs and 100 million English common crawl document pairs. XLM-E [89] Dakshina [109] Parallel corpus containing 10K sentences for 12 In- dian languages …","url":["https://arxiv.org/pdf/2108.05542"]}
-{"year":"2021","title":"An Alignment-Based Approach to Semi-Supervised Bilingual Lexicon Induction with Small Parallel Corpora","authors":["K Marchisio, C Xiong, P Koehn"],"snippet":"… learning. 6 Experimental Settings Language Corpus # of words English WaCky, BNC, Wikipedia 2.8 B Italian itWac 1.6 B German SdeWaC 0.9 B Spanish News Crawl 2007-2012 386 M Finnish Common Crawl 2016 2.8 B Table …","url":["https://aclanthology.org/2021.mtsummit-research.24.pdf"]}
-{"year":"2021","title":"An analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neuron nets","authors":["AG Sboeva, SG Sboevac, IA Moloshnikova…"],"snippet":"Page 1. An analysis of full-size Russian complexly NER labelled corpus of Internet user reviews on the drugs based on deep learning and language neuron nets AG Sboeva,b,, SG Sboevac, IA Moloshnikova, AV Gryaznova, RB …","url":["https://sagteam.ru/papers/med-corpus/4.pdf"]}
-{"year":"2021","title":"An Effective Deep Learning Approach for Extractive Text Summarization","authors":["MT Luu, TH Le, MT Hoang"],"snippet":"Page 1. An Effective Deep Learning Approach for Extractive Text Summarization Minh-Tuan Luu PhD. Student, School of Information and Communication Technology, Hanoi University of Science and Technology, No.1 Dai Co …","url":["http://www.ijcse.com/docs/INDJCSE21-12-02-141.pdf"]}
-{"year":"2021","title":"An embedding method for unseen words considering contextual information and morphological information","authors":["MS Won, YS Choi, S Kim, CW Na, JH Lee - Proceedings of the 36th Annual ACM …, 2021"],"snippet":"… Random embeddings are assigned for OOv words. Glove is implemented by using preǦtrained 300Ǧdimensional Glove embedding, which is trained on Common Crawl with 840B word tokens. Random embeddings are assigned for OOv words …","url":["https://dl.acm.org/doi/abs/10.1145/3412841.3441982"]}
-{"year":"2021","title":"An empirical evaluation of text representation schemes to filter the social media stream","authors":["S Modha, P Majumder, T Mandl - Journal of Experimental & Theoretical Artificial …, 2021"],"snippet":"… Glove pre-trained model available with different embed size and trained on the common crawl, Twitter. We have used the Glove pre-trained model with a vocabulary size of 2.2 million and trained on the common crawl. fastText …","url":["https://www.tandfonline.com/doi/full/10.1080/0952813X.2021.1907792"]}
-{"year":"2021","title":"An Empirical Exploration in Quality Filtering of Text Data","authors":["L Gao - arXiv preprint arXiv:2109.00698, 2021"],"snippet":"… (2020), with a Paretodistribution thresholded filtering method and a shallow CommonCrawl-WebText classfier … (2020) has been made public, we instead use the same type of fasttext (Joulin et al., 2017) classifier between unfiltered …","url":["https://arxiv.org/pdf/2109.00698"]}
-{"year":"2021","title":"An Empirical Study on Task-Oriented Dialogue Translation","authors":["S Liu - ICASSP 2021-2021 IEEE International Conference on …, 2021"],"snippet":"… consistent). We valid them with SENT-BASE model on En⇒De task. data in WMT20 news domain, which consists of CommonCrawl and NewsCommentary. We conduct data selection to select similar amount of sentences …","url":["https://ieeexplore.ieee.org/abstract/document/9413521/"]}
-{"year":"2021","title":"An End-to-end Point of Interest (POI) Conflation Framework","authors":["R Low, ZD Tekler, L Cheah - arXiv preprint arXiv:2109.06073, 2021"],"snippet":"… words that did not appear in the training data [63]. For this study, the fastText model was pre-trained on 2 million word vectors with subword information from commoncrawl.org. The second advantage of using the fastText library to …","url":["https://arxiv.org/pdf/2109.06073"]}
-{"year":"2021","title":"An evaluation dataset for depression detection in Arabic social media","authors":["S Elimam, M Bougeussa - International Journal of Knowledge Engineering and …, 2021"],"snippet":"Studying depression in Arabic social media has been neglected compared to other languages and the traditional way of dealing with depression (face-to-face medical diagnose) is not enough as the number of people that suffer from depression in …","url":["https://www.inderscienceonline.com/doi/abs/10.1504/IJKEDM.2021.119888"]}
-{"year":"2021","title":"An Explainable Multi-Modal Hierarchical Attention Model for Developing Phishing Threat Intelligence","authors":["Y Chai, Y Zhou, W Li, Y Jiang - IEEE Transactions on Dependable and Secure …, 2021"],"snippet":"Phishing website attack, as one of the most persistent forms of cyber threats, evolves and remains a major cyber threat. Various detection methods (eg, lookup systems, fraud cue-based methods) have been proposed to identify phishing websites. The …","url":["https://ieeexplore.ieee.org/abstract/document/9568704/"]}
-{"year":"2021","title":"An Exploration of Alignment Concepts to Bridge the Gap between Phrase-based and Neural Machine Translation","authors":["JT Peter"],"snippet":"Page 1. An Exploration of Alignment Concepts to Bridge the Gap between Phrase-based and Neural Machine Translation Von der Fakultät für Mathematik, Informatik und Naturwissenschaften der RWTH Aachen University zur …","url":["https://www-i6.informatik.rwth-aachen.de/publications/download/1175/PeterJan-Thorsten--ExplorationofAlignmentConceptstoBridgetheGapbetweenPhrase-basedNeuralMachineTranslation--2020.pdf"]}
-{"year":"2021","title":"An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformers","authors":["T Ranasinghe, C Orasan, R Mitkov - arXiv preprint arXiv:2106.00143, 2021"],"snippet":"… Our architecture relies on the XLM-R transformer model (Conneau et al., 2020) to derive the representations of the input sentences. XLM-R has been trained on a large-scale multilingual dataset in 104 languages, totalling …","url":["https://arxiv.org/pdf/2106.00143"]}
-{"year":"2021","title":"An Exploratory Study on Utilising the Web of Linked Data for Product Data Mining","authors":["Z Zhang, X Song - arXiv preprint arXiv:2109.01411, 2021"],"snippet":"… The Web Data Commons3 (WDC) project extracts such structured data from the CommonCrawl4 as RDF n-quads5, and release them on … to create a very large training dataset for product entity linking using semantic markup data …","url":["https://arxiv.org/pdf/2109.01411"]}
-{"year":"2021","title":"An extended analysis of the persistence of persistent identifiers of the scholarly web","authors":["M Klein, L Balakireva - International Journal on Digital Libraries, 2021"],"snippet":"… These findings were confirmed in a large-scale study by Thompson and Jian [22] based on two samples of the web taken from Common Crawl Footnote 3 datasets. The authors were motivated to quantify the use of HTTP DOIs versus URLs of …","url":["https://link.springer.com/article/10.1007/s00799-021-00315-w"]}
-{"year":"2021","title":"An Intrinsic and Extrinsic Evaluation of Learned COVID-19 Concepts using Open-Source Word Embedding Sources","authors":["S Parikh, A Davoudi, S Yu, C Giraldo, E Schriver… - medRxiv"],"snippet":"… 8] and GloVe [9] on large corpora of texts including domain-independent texts (eg, internet web pages like Wikipedia and CommonCrawl; social media … Standard GloVe Embeddings Paper Vectors [9] Common Crawl Token 10 …","url":["https://www.medrxiv.org/content/medrxiv/early/2021/01/04/2020.12.29.20249005.full.pdf"]}
-{"year":"2021","title":"An Investigation towards Differentially Private Sequence Tagging in a Federated Framework","authors":["A Jana, C Biemann"],"snippet":"… 2The hyperparameter settings to train those models are as follows: epochs- 10, batch size - 32, learning rate - 0.15, optimizer - Stochastic gradient descent (SGD) Common Crawl corpus) from spaCy library3, the dimension of which is 300 …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2021-janabiemann-privnlp-fed.pdf"]}
-{"year":"2021","title":"An Overview on Evaluation Labs and Open Issues in Health-related Credible Information Retrieval","authors":["R Upadhyay, G Pasi, M Viviani - 2021"],"snippet":"… The 2020 Track used a dataset provided by Common Crawl, in particular related to different news collected in the first four months of 2020.4 On … 2https://trec-health-misinfo.github.io/2019.html 3https://lemurproject.org …","url":["http://52.178.216.184/paper31.pdf"]}
-{"year":"2021","title":"Analysis and Evaluation of Language Models for Word Sense Disambiguation","authors":["D Loureiro, K Rezaee, MT Pilehvar… - Computational Linguistics, 2021"],"snippet":"Page 1. Analysis and Evaluation of Language Models for Word Sense Disambiguation Daniel Loureiro∗ LIAAD - INESC TEC Department of Computer Science - FCUP University of Porto, Portugal dloureiro@fc.up.pt Kiamehr …","url":["https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli_a_00405/1900170/coli_a_00405.pdf"]}
-{"year":"2021","title":"Analysis of Machine Learning and Deep Learning Frameworks for Opinion Mining on Drug Reviews","authors":["F Youbi, N Settouti - The Computer Journal, 2021"],"snippet":"… More precisely, GloVe consists of collecting word co- occurrence statistics in a form of a word co-occurrence matrix, in which its developers have provided pre-embed millions of English tokens obtained from Wikipedia data and common crawl data …","url":["https://academic.oup.com/comjnl/advance-article-abstract/doi/10.1093/comjnl/bxab084/6311550"]}
-{"year":"2021","title":"Analyzing Hyperonyms of Stack Overflow Posts","authors":["L Tóth, L Vidács"],"snippet":"… They applied a similar lexico-syntactic pattern-based mining on the dataset obtained from CommonCrawl [17] using a slightly different grammar for NP identification and, therefore, a slightly different set of patterns. Despite the differences …","url":["https://www.researchgate.net/profile/Laszlo-Toth-12/publication/356192289_Analyzing_Hyperonyms_of_Stack_Overflow_Posts/links/61910421d7d1af224bea68e9/Analyzing-Hyperonyms-of-Stack-Overflow-Posts.pdf"]}
-{"year":"2021","title":"Analyzing Multimodal Language via Acoustic-and Visual-LSTM with Channel-aware Temporal Convolution Network","authors":["S Mai, S Xing, H Hu - IEEE/ACM Transactions on Audio, Speech, and …, 2021"],"snippet":"Page 1. 2329-9290 (c) 2021 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/9387606/"]}
-{"year":"2021","title":"Analyzing the Forgetting Problem in Pretrain-Finetuning of Open-domain Dialogue Response Models","authors":["T He, J Liu, K Cho, M Ott, B Liu, J Glass, F Peng - … of the 16th Conference of the …, 2021"],"snippet":"… 4.1 Datasets For pretraining, we use the large-scale CCNEWS data (Bakhtin et al., 2019) which is a de-duplicated subset of the English portion of the CommonCrawl news dataset1 … We tune the 1 http://commoncrawl.org/2016/10/ news-dataset-available Page 5. 1125 …","url":["https://www.aclweb.org/anthology/2021.eacl-main.95.pdf"]}
-{"year":"2021","title":"Analyzing transfer learning impact in biomedical cross-lingual named entity recognition and normalization","authors":["RM Rivera-Zavala, P Martínez - BMC Bioinformatics, 2021"],"snippet":"… The FastText-2M [52] pre-trained English word embedding model trained with subword information on Common Crawl using the FastText implementation. Finally, the PubMed and PMC [53] pre-trained English word embedding model, trained on a …","url":["https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04247-9"]}
-{"year":"2021","title":"Annotation of Fine-Grained Geographical Entities in German Texts","authors":["J Moreno-Schneider, M Plakidis, G Rehm - 3rd Conference on Language, Data and …, 2021"],"snippet":"… The SpaCy models are trained on Ontonotes 5 and Common Crawl (English; en_core_web_md) and WikiNER and TIGER (German; de_core_news_md). The Stanford models are trained on the CoNLL 2003 data [18]. BERT-NER is trained on WikiNER [11] …","url":["https://drops.dagstuhl.de/opus/volltexte/2021/14547/pdf/OASIcs-LDK-2021-11.pdf"]}
-{"year":"2021","title":"Answering questions about insurance supervision with a Neural Machine Translator","authors":["J Glowienke - 2021"],"snippet":"… Conneau et al. [3] pre-train a model based on the RoBERTa architecture to create crosslingual representations. The XLM-R model is pre-trained on a common crawl dataset of 100 languages using the masked multi-lingual language model ap- proach …","url":["https://dke.maastrichtuniversity.nl/jan.niehues/wp-content/uploads/2021/08/Glowienke-Master-thesis.pdf"]}
-{"year":"2021","title":"Anticipating Attention: On the Predictability of News Headline Tests","authors":["N Hagar, N Diakopoulos, B DeWilde - Digital Journalism, 2021"],"snippet":"… These embeddings contain 300 dimensions and were trained on English language text from the OntoNotes 5.0 and GloVe Common Crawl corpora. For each headline, we computed the average embedding vector across all tokens. …","url":["https://www.tandfonline.com/doi/abs/10.1080/21670811.2021.1984266"]}
-{"year":"2021","title":"Applying and Understanding an Advanced, Novel Deep Learning Approach: A Covid 19, Text Based, Emotions Analysis Study","authors":["J Choudrie, S Patil, K Kotecha, N Matta, I Pappas - Information Systems Frontiers, 2021"],"snippet":"The pandemic COVID 19 has altered individuals' daily lives across the globe. It has led to preventive measures such as physical distancing to be impo.","url":["https://link.springer.com/article/10.1007/s10796-021-10152-6"]}
-{"year":"2021","title":"Applying Deep Learning Techniques for Sentiment Analysis to Assess Sustainable Transport","authors":["A Serna Nocedal, A Soroa Echave, R Agerri Gascón - 2021","A Serna, A Soroa, R Agerri - Sustainability, 2021"],"snippet":"… Thus, the multilingual version of BERT [25] was trained for 104 languages. More recently, XLM-RoBERTa [21] distributes a multilingual model which contains 100 languages trained on 2.5 TB of filtered Common Crawl text. To …","url":["https://addi.ehu.eus/bitstream/handle/10810/50497/sustainability-13-02397-v2.pdf?sequence=1&isAllowed=y","https://www.mdpi.com/2071-1050/13/4/2397/pdf"]}
-{"year":"2021","title":"Applying Deep Learning Techniques for Sentiment Analysis to Assess Sustainable Transport. Sustainability 2021, 13, 2397","authors":["A Serna, A Soroa, R Agerri - 2021"],"snippet":"… Thus, the multilingual version of BERT [25] was trained for 104 languages. More recently, XLM-RoBERTa [21] distributes a multilingual model which contains 100 languages trained on 2.5 TB of filtered Common Crawl text. To …","url":["https://search.proquest.com/openview/b1ea0637935ea567d5fd68853527c980/1?pq-origsite=gscholar&cbl=2032327"]}
-{"year":"2021","title":"AR-LSAT: Investigating Analytical Reasoning of Text","authors":["W Zhong, S Wang, D Tang, Z Xu, D Guo, J Wang, J Yin… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. AR-LSAT: Investigating Analytical Reasoning of Text Wanjun Zhong1∗, Siyuan Wang3∗, Duyu Tang2, Zenan Xu1∗, Daya Guo1∗ Jiahai Wang1, Jian Yin1, Ming Zhou4 and Nan Duan2 1 The School of Data and Computer Science, Sun Yat-sen University …","url":["https://arxiv.org/pdf/2104.06598"]}
-{"year":"2021","title":"Arabic Offensive Language Detection in Social Media","authors":["F Husain - 2021"],"snippet":"Page 1. ARABIC OFFENSIVE LANGUAGE DETECTION IN SOCIAL MEDIA by Fatemah Ali Husain A Dissertation Submitted to the Graduate Faculty of George Mason University in Partial Fulfillment of The Requirements for the …","url":["https://search.proquest.com/openview/aefe47a620c621b1c7ed7f95196cf6ba/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"AraCOVID19-SSD: Arabic COVID-19 Sentiment and Sarcasm Detection Dataset","authors":["MS Hadj Ameur - Revue de l'Information Scientifique et Technique, 2023","MSH Ameur, H Aliane - arXiv preprint arXiv:2110.01948, 2021"],"snippet":"… Multilingual BERT (mBERT)6: A BERT-based model [17] pretrained on the first 104 major Wikipedia languages7. • XLM-Roberta 8: A large multi-lingual language model, trained on 2.5TB of filtered Common Crawl data [19]. 4.2.2 Bag-of-Words Models …","url":["https://arxiv.org/pdf/2110.01948","https://www.asjp.cerist.dz/index.php/en/downArticle/134/27/1/220363"]}
-{"year":"2021","title":"AraStance: A Multi-Country and Multi-Domain Dataset of Arabic Stance Detection for Fact Checking","authors":["T Alhindi, A Alabdulkarim, A Alshehri, M Abdul-Mageed… - arXiv preprint arXiv …, 2021"],"snippet":"… AraStance and Khoja. This indicates the suitability of the pretraining data of ARBERT that includes Books, Gi- gawords and Common Crawl data primarily from MSA but also a small amount of Egyptian Arabic. Since half of …","url":["https://arxiv.org/pdf/2104.13559"]}
-{"year":"2021","title":"ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic","authors":["M Abdul-Mageed, AR Elmadany, EMB Nagoudi - arXiv preprint arXiv:2101.01785, 2020"],"snippet":"… mBERT (Devlin et al., 2019) and XLM-R (Conneau et al., 2020) use a small Arabic text collection from Wikipedia (153M tokens) and CommonCrawl (2.9B … XLM-R (Conneau et al., 2020) is trained on Common Crawl data, hence …","url":["https://arxiv.org/pdf/2101.01785"]}
-{"year":"2021","title":"Are Multilingual Models Effective in Code-Switching?","authors":["GI Winata, S Cahyawijaya, Z Liu, Z Lin, A Madotto… - arXiv preprint arXiv …, 2021"],"snippet":"… switching tasks. 2.2.2 XLM-RoBERTa XLM-RoBERTa (XLM-R) (Conneau et al., 2020) is a multilingual language model that is pre-trained on 100 languages using more than two terabytes of filtered CommonCrawl data. Thanks to …","url":["https://arxiv.org/pdf/2103.13309"]}
-{"year":"2021","title":"Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? A Comprehensive Assessment for Catalan","authors":["J Armengol-Estapé, CP Carrino, C Rodriguez-Penagos… - arXiv preprint arXiv …, 2021"],"snippet":"… Catalan Government; (2) the Catalan Open Subtitles, a collection of translated movie subtitles (Tiedemann, 2012); (3) the non-shuffled version of the Catalan part of the OSCAR corpus (Suárez et al., 2019), a collection …","url":["https://arxiv.org/pdf/2107.07903"]}
-{"year":"2021","title":"Are You Really Complaining? A Multi-task Framework for Complaint Identification, Emotion, and Sentiment Classification","authors":["A Singh, S Saha - International Conference on Document Analysis and …, 2021"],"snippet":"… For deep learning baseline (MT\\(_{\\mathrm{GloVe}}\\)) we also used pre-trained GloVe 13 [16] word embedding which is trained on Common Crawl (840 billion tokens) corpus to get the word embedding representations. 4.4 Results and Discussion …","url":["https://link.springer.com/chapter/10.1007/978-3-030-86331-9_46"]}
-{"year":"2021","title":"ARMAN: Pre-training with Semantically Selecting and Reordering of Sentences for Persian Abstractive Summarization","authors":["A Salemi, E Kebriaei, GN Minaei, A Shakery - arXiv preprint arXiv:2109.04098, 2021"],"snippet":"… This corpus contains around 2.8M articles and 1.4B words in all of the articles. CC100 (Conneau et al., 2020; Wenzek et al., 2020) is a monolingual dataset for 100+ languages constructed from Commoncrawl snapshots. This …","url":["https://arxiv.org/pdf/2109.04098"]}
-{"year":"2021","title":"As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation","authors":["J Wang, C Xu, F Guzman, A El-Kishky, BIP Rubinstein… - arXiv preprint arXiv …, 2021"],"snippet":"… Our testing framework facilitates constructing test instances for new domains in the following steps: 1. Obtain a large corpus of text that contains numbers (eg,CommonCrawl); 2. Check if there is a number in the output translation; …","url":["https://arxiv.org/pdf/2107.08357"]}
-{"year":"2021","title":"Aspect-based Sentiment Analysis with Graph Convolution over Syntactic Dependencies","authors":["A Zunic, P Corcoran, I Spasic","A Žunić, P Corcoran, I Spasić - Artificial Intelligence in Medicine, 2021"],"snippet":"… individual sentences into dependency graphs. Individual words representing vertices in such graphs were mapped onto their embeddings, which were pretrained 160 on web data from Common Crawl using the GloVe method [31]. Each input …","url":["https://www.researchgate.net/profile/Irena-Spasic/publication/353775596_Aspect-based_Sentiment_Analysis_with_Graph_Convolution_over_Syntactic_Dependencies/links/61112fae169a1a0103ea3e67/Aspect-based-Sentiment-Analysis-with-Graph-Convolution-over-Syntactic-Dependencies.pdf","https://www.sciencedirect.com/science/article/pii/S0933365721001317"]}
-{"year":"2021","title":"ASR4REAL: An extended benchmark for speech models","authors":["M Riviere, J Copet, G Synnaeve - arXiv preprint arXiv:2110.08583, 2021"],"snippet":"… even a language model trained on a dataset as big as Common Crawl does not seem to have significant positive effect which reiterates … For all of theses models we used the a 4-gram LM trained on Common Crawl with the decoding parameters …","url":["https://arxiv.org/pdf/2110.08583"]}
-{"year":"2021","title":"Assessing reasoning and world knowledge of large language models using questionized counterfactual conditionals","authors":["J Frohberg, F Binder - 2021"],"snippet":"Page 1. Assessing reasoning and world knowledge of large language models using questionized counterfactual conditionals Jörg Frohberg apergo UG Leipzig, Germany j.frohberg@apergo.ai Frank Binder Institute for Applied …","url":["https://openreview.net/pdf?id=i9XYDrUJYyP"]}
-{"year":"2021","title":"Assessing the Extent and Types of Hate Speech in Fringe Communities: A Case Study of Alt-Right Communities on 8chan, 4chan, and Reddit","authors":["D Rieger, AS Kümpel, M Wich, T Kiening, G Groh - Social Media+ Society, 2021"],"snippet":"… For this article, the fastText word vectors pre-trained on the English Common Crawl dataset were used because it is trained on web data and thus an appropriate basis (Mikolov, Grave, Bojanowski, Puhrsch, & Joulin, 2019). …","url":["https://journals.sagepub.com/doi/pdf/10.1177/20563051211052906"]}
-{"year":"2021","title":"AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Models","authors":["HT Madabushi, E Gow-Smith, C Scarton… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Models Harish Tayyar Madabushi, Edward Gow-Smith, Carolina Scarton and Aline Villavicencio Department …","url":["https://arxiv.org/pdf/2109.04413"]}
-{"year":"2021","title":"Attention-based model for predicting question relatedness on Stack Overflow","authors":["J Pei, Z Qin, Y Cong, J Guan - arXiv preprint arXiv:2103.10763, 2021"],"snippet":"… released by Stanford [22]. This word embeddings pre-trained in the Common Crawl corpus, which contains a large amount of data irrelevant to software engineering, may lead to ambiguous results [18]. Therefore, we hope that …","url":["https://arxiv.org/pdf/2103.10763"]}
-{"year":"2021","title":"Attention: there is an inconsistency between android permissions and application metadata!","authors":["H Alecakir, B Can, S Sen - International Journal of Information Security"],"snippet":"Since mobile applications make our lives easier, there is a large number of mobile applications customized for our needs in the application markets. While.","url":["https://link.springer.com/article/10.1007/s10207-020-00536-1"]}
-{"year":"2021","title":"Attentive Excitation and Aggregation for Bilingual Referring Image Segmentation","authors":["Q Zhou, T Hui, R Wang, H Hu, S Liu - ACM Transactions on Intelligent Systems and …, 2021"],"snippet":"… For English expression, we use GloVe1 pretrained on Common Crawl to embed each word into a 300-d vector. For Chinese expression, existing tools … GloVe word embeddings [34] pretrained on Common Crawl 840B …","url":["https://dl.acm.org/doi/abs/10.1145/3446345"]}
-{"year":"2021","title":"Augmenting Poetry Composition with Verse by Verse","authors":["D Uthus, M Voitovich, RJ Mical - arXiv preprint arXiv:2103.17205, 2021"],"snippet":"… TextSETTR was shown to yield better results in transforming sentiment while preserving fluency (important aspects for our work). As described in the TextSETTR paper, we use the model that had been fine-tuned on English Common Crawl data …","url":["https://arxiv.org/pdf/2103.17205"]}
-{"year":"2021","title":"Augmenting semantic lexicons using word embeddings and transfer learning","authors":["T Alshaabi, C Van Oort, M Fudolig, MV Arnold… - arXiv preprint arXiv …, 2021"],"snippet":"… words. We then pass the token embeddings to a 300dimensional embedding layer. We initialize the embedding layer with weights trained with subword information on Common Crawl and Wikipedia using FastText [59]. In …","url":["https://arxiv.org/pdf/2109.09010"]}
-{"year":"2021","title":"AUGVIC: Exploiting BiText Vicinity for Low-Resource NMT","authors":["T Mohiuddin, MS Bari, S Joty - arXiv preprint arXiv:2106.05141, 2021"],"snippet":"… localization guide, respectively. For some languages, the amount of specific domain monolingual data is limited, where we added additional monolingual data of that language from Common Crawl. Following previous work …","url":["https://arxiv.org/pdf/2106.05141"]}
-{"year":"2021","title":"Authorship Weightage Algorithm for Academic publications: A new calculation and ACES webserver for determining expertise","authors":["WL Wu, O Tan, KF Chan, NB Ong, D Gunasegaran… - Methods and Protocols, 2021"],"snippet":"… the back-end server. These word vectors were trained on Common Crawl (https://commoncrawl.org (last accessed on 28 April 2021)) using fastText [17], and are used to map the processed query to its corresponding values …","url":["https://www.mdpi.com/2409-9279/4/2/41/pdf"]}
-{"year":"2021","title":"Automated Change Detection in Privacy Policies","authors":["A Adhikari - 2020"],"snippet":"Page 1. University of Denver Digital Commons @ DU Electronic Theses and Dissertations Graduate Studies 2020 Automated Change Detection in Privacy Policies Andrick Adhikari Follow this and additional works at: https://digitalcommons.du.edu/etd …","url":["https://digitalcommons.du.edu/cgi/viewcontent.cgi?article=2702&context=etd"]}
-{"year":"2021","title":"Automated essay scoring: A review of the field","authors":["P Lagakis, S Demetriadis - … International Conference on Computer, Information and …, 2021"],"snippet":"… Transformer models make use of those huge datasets of existing general text data, such as Wikipedia Corpus and Common Crawl, to pretrain multilayer neural networks with context-sensitive meaning of, and relations between, words, such as …","url":["https://ieeexplore.ieee.org/abstract/document/9618476/"]}
-{"year":"2021","title":"Automated Grading of Exam Responses: An Extensive Classification Benchmark","authors":["A Farazouli, Z Lee, P Papapetrou, U Fors - … Science: 24th International Conference, DS 2021 …","J Ljungman, V Lislevand, J Pavlopoulos, A Farazouli… - International Conference on …, 2021"],"snippet":"… This method proves that training BERT with alternative design choices and with more data, including the CommonCrawl News dataset, … training XLM-R on one hundred languages using CommonCrawl data2, in contrast to previous works such …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=IydHEAAAQBAJ&oi=fnd&pg=PA3&dq=commoncrawl&ots=QIe2sENq0_&sig=LQ1NnDlylvNDV4-vNPAiGJEMZd4","https://link.springer.com/chapter/10.1007/978-3-030-88942-5_1"]}
-{"year":"2021","title":"Automated identification of bias inducing words in news articles using linguistic and context-oriented features","authors":["T Spinde, L Rudnitckaia, J Mitrović, F Hamborg… - Information Processing & …, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0306457321000157"]}
-{"year":"2021","title":"Automated methods for Question-Answering in Icelandic","authors":["V Snæbjarnarson"],"snippet":"… The source of the data is the open internet, made accessible to those with relatively modest computing resources and disk storage through the targeted use of the Common Crawl datasets that comprise petabytes of data. Prior work has focused on the …","url":["https://vesteinn.is/thesis_150921.pdf"]}
-{"year":"2021","title":"Automatic Detection of Fake","authors":["BM Bažík"],"snippet":"… For the data, they created the RealNews dataset, a large corpus of news articles from Common Crawl1. Fake News Detection Using Deep Learning Techniques [11] compared Logistic Regression (LR), Naive Bayes (NB) …","url":["https://is.muni.cz/th/hk1px/Martin_Bazik_master_thesis.pdf"]}
-{"year":"2021","title":"Automatic Difficulty Classification of Arabic Sentences","authors":["N Khallaf, S Sharoff - arXiv preprint arXiv:2103.04386, 2021"],"snippet":"… corpus (Common Crawl and Wikipedia for ArabicBERT vs Common Crawl XML-R vs Wikipedia for BERT, AraBert and UCS) used to train the Arabic … The corpus will be classified on the ba- sis of how difficult the sentences are …","url":["https://arxiv.org/pdf/2103.04386"]}
-{"year":"2021","title":"Automatic Fully-Contextualized Recommendation Extraction from Radiology Reports","authors":["J Steinkamp, C Chambers, D Lalevic, T Cook - Journal of Digital Imaging, 2021"],"snippet":"… We evaluated a simple long short-term memory (LSTM) architecture [12] on the task. We used a combination of custom-trained fastText vectors, trained on our institution's entire repository of radiology reports, with Global …","url":["https://link.springer.com/article/10.1007/s10278-021-00423-8"]}
-{"year":"2021","title":"Automatic Generic Web Information Extraction at Scale","authors":["M Aljabary - 2021"],"snippet":"Page 1. 1 Page 2. 2 Automatic Generic Web Information Extraction at Scale Master Thesis Computer Science, Data Science and Technology University of Twente. Enschede, The Netherlands An attempt to bring some structure …","url":["http://essay.utwente.nl/86153/1/Aljabary_MA_EEMCS.pdf"]}
-{"year":"2021","title":"Automatic Sexism Detection with Multilingual Transformer Models","authors":["S Mina, B Jaqueline, L Daria, S Djordje, K Armin… - arXiv preprint arXiv …, 2021"],"snippet":"… XLM-R is a multilingual model trained on 100 languages, similar to mBERT. Unlike the latter, XLM-R is not trained on Wikipedia data but on monolingual CommonCrawl data. The model shows improved cross-lingual language …","url":["https://arxiv.org/pdf/2106.04908"]}
-{"year":"2021","title":"Automatic Stress Detection from Facial Videos","authors":["EM de Oca - 2021"],"snippet":"… , leading to the development of pretrained systems such as BERT(Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer), which were trained with large language datasets, such as Wikipedia …","url":["https://www.eduardomontesdeoca.com/s/ADSS-Project.pdf"]}
-{"year":"2021","title":"Automatically Detecting Cyberbullying Comments on Online Game Forums","authors":["HHP Vo, HT Tran, ST Luu - arXiv preprint arXiv:2106.01598, 2021"],"snippet":"… on Wikipedia and Gigaword corpora. The fastText 3 is trained on Common Crawl and Wikipedia datasets using CBOW with position-weight in 300 dimensions with 5-grams features. D. Traditional machine learning models Logistic …","url":["https://arxiv.org/pdf/2106.01598"]}
-{"year":"2021","title":"Autonomous Writing Futures","authors":["AH Duin, I Pedersen - Writing Futures: Collaborative, Algorithmic …, 2021"],"snippet":"… GPT-3 is 175 billion parameters. GPT-3 is trained on the Common Crawl data set, a corpus of almost a trillion words of texts scraped from the Web. “The dataset and model size are about two orders of magnitude larger than those used for GPT-2,” the authors write …","url":["https://link.springer.com/chapter/10.1007/978-3-030-70928-0_4"]}
-{"year":"2021","title":"Auxiliary Bi-Level Graph Representation for Cross-Modal Image-Text Retrieval","authors":["X Zhong, Z Yang, M Ye, W Huang, J Yuan, CW Lin - 2021 IEEE International …, 2021"],"snippet":"… The scene graph features Soi and Srij are transformed by a learnable embedding layer which is initialized by GloVe [18] pre-trained on the Common-Crawl dataset, and maps Ioi and Irij into a vector of same dimension: Soi = WoIoi , Srij = WrIrij , (1) …","url":["https://ieeexplore.ieee.org/abstract/document/9428380/"]}
-{"year":"2021","title":"Auxiliary Learning for Relation Extraction","authors":["S Lyu, J Cheng, X Wu, L Cui, H Chen, C Miao - IEEE Transactions on Emerging …, 2020"],"snippet":"… 7https://catalog.ldc.upenn.edu/LDC2018T24 8http://semeval2.fbk.eu/semeval2. php?location=data 9Following previous work, we choose GloVe word vectors with 300 dimensions (Common Crawl) https://nlp.stanford.edu/projects/glove …","url":["https://ieeexplore.ieee.org/abstract/document/9296307/"]}
-{"year":"2021","title":"Background Knowledge in Schema Matching: Strategy vs. Data","authors":["J Portisch, M Hladik, H Paulheim - arXiv preprint arXiv:2107.00001, 2021"],"snippet":"… used. WebIsALOD is a large hypernymy graph based on the WebIsA database [37]. The latter is a dataset which consists of hypernymy relations extracted from the Common Crawl, a large set of crawled Web pages. The extraction …","url":["https://arxiv.org/pdf/2107.00001"]}
-{"year":"2021","title":"Bambara Language Dataset for Sentiment Analysis","authors":["M Diallo, C Fourati, H Haddad - arXiv preprint arXiv:2108.02524, 2021"],"snippet":"… In this paper, we present the first common-crawl-based Bambara dialectal dataset dedicated for Sentiment Analysis, available freely for Natural Language Processing research purposes … Bambara V1 dataset represents …","url":["https://arxiv.org/pdf/2108.02524"]}
-{"year":"2021","title":"Bandits Don't Follow Rules: Balancing Multi-Facet Machine Translation with Multi-Armed Bandits","authors":["J Kreutzer, D Vilar, A Sokolov - arXiv preprint arXiv:2110.06997, 2021"],"snippet":"Training data for machine translation (MT) is often sourced from a multitude of large corpora that are multi-faceted in nature, eg containing contents from multiple domains or different levels of quality or complexity. Naturally, these facets do not …","url":["https://arxiv.org/pdf/2110.06997"]}
-{"year":"2021","title":"BARTpho: Pre-trained Sequence-to-Sequence Models for Vietnamese","authors":["NL Tran, DM Le, DQ Nguyen - arXiv preprint arXiv:2109.09701, 2021"],"snippet":"… rization. Here, mBART is pre-trained on a Common Crawl dataset of 25 languages, which contains 137 GB of syllablelevel Vietnamese texts. We employ the single-document summarization dataset VNDS (Nguyen et al. 2019 …","url":["https://arxiv.org/pdf/2109.09701"]}
-{"year":"2021","title":"belabBERT: a Dutch RoBERTa-based language model applied to psychiatric classification","authors":["J Wouts, J de Boer, A Voppel, S Brederoo… - arXiv preprint arXiv …, 2021"],"snippet":"… 3.1.1. Pre-training For the pre-training of belabBERT we used the OSCAR corpus which consists of a set of monolingual corpora extracted from Common Crawl snapshots … belabBERT Common Crawl Dutch (non-shuffled) BytePairEncoding 95.92 ∗ …","url":["https://arxiv.org/pdf/2106.01091"]}
-{"year":"2021","title":"Benchmarking Differential Privacy and Federated Learning for BERT Models","authors":["P Basu, TS Roy, R Naidu, Z Muftuoglu, S Singh… - arXiv preprint arXiv …, 2021"],"snippet":"… It uses 160 GB of text for pre-training, including 16GB of Books Corpus and English Wikipedia used in BERT. The additional data included CommonCrawl News dataset, Web text corpus and Stories from Common Crawl. For …","url":["https://arxiv.org/pdf/2106.13973"]}
-{"year":"2021","title":"BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation","authors":["H Xu, B Van Durme, K Murray - arXiv preprint arXiv:2109.04588, 2021"],"snippet":"… on 145G German text data portion of OSCAR (Or- tiz Suárez et al., 2020), a huge multilingual corpus extracted from Common Crawl … Vaswani et al., 2017) masked language model trained on 100 languages, using more than …","url":["https://arxiv.org/pdf/2109.04588"]}
-{"year":"2021","title":"BERT: A Review of Applications in Natural Language Processing and Understanding","authors":["MV Koroteev - arXiv preprint arXiv:2103.11943, 2021"],"snippet":"Page 1. BERT: A Review of Applications in Natural Language Processing and Understanding Koroteev MV, Financial University under the government of the Russian Federation, Moscow, Russia mvkoroteev@fa.ru Abstract: In …","url":["https://arxiv.org/pdf/2103.11943"]}
-{"year":"2021","title":"Bertinho: Galician BERT Representations","authors":["D Vilares, M Garcia, C Gómez-Rodríguez - arXiv preprint arXiv:2103.13799, 2021"],"snippet":"Page 1. Bertinho: Galician BERT Representations Bertinho: Representaciones BERT para el gallego David Vilares,1 Marcos Garcia,2 Carlos Gómez-Rodr´ıguez 1 1Universidade da Coru˜na, CITIC, Galicia, Spain 2CiTIUS, Universidade …","url":["https://arxiv.org/pdf/2103.13799"]}
-{"year":"2021","title":"Better Neural Machine Translation by Extracting Linguistic Information from BERT","authors":["HS Shavarani, A Sarkar - arXiv preprint arXiv:2104.02831, 2021"],"snippet":"… clack, clack.”). 9Europarl+CommonCrawl+NewsCommentary https://www.statmt. org/wmt14/translation-task.html, please note that in the later years this training set remained the same, but ParaCrawl data was added to it. We …","url":["https://arxiv.org/pdf/2104.02831"]}
-{"year":"2021","title":"Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation","authors":["E Briakou, M Carpuat - arXiv preprint arXiv:2105.15087, 2021"],"snippet":"Page 1. Beyond Noise: Mitigating the Impact of Fine-grained Semantic Divergences on Neural Machine Translation Eleftheria Briakou and Marine Carpuat Department of Computer Science University of Maryland College Park …","url":["https://arxiv.org/pdf/2105.15087"]}
-{"year":"2021","title":"Beyond the English Web: Zero-Shot Cross-Lingual and Lightweight Monolingual Classification of Registers","authors":["L Repo, V Skantsi, S Rönnqvist, S Hellström… - arXiv preprint arXiv …, 2021"],"snippet":"… FreCORE and SweCORE are random samples of the 2017 CoNLL datasets (Ginter et al., 2017) originally drawn from Common Crawl … XLM-R is trained on 2.5TB of filtered Common Crawl (Wenzek et al., 2020) data comprising …","url":["https://arxiv.org/pdf/2102.07396"]}
-{"year":"2021","title":"Bias Silhouette Analysis: Towards Assessing the Quality of Bias Metrics for Word Embedding Models","authors":["M Spliethöver, H Wachsmuth"],"snippet":"… Word Embedding Models. As biased and unbiased models, we use GloVe CommonCrawl [Pennington et al., 2014] trained on 840 billion English tokens and the English ConceptNet Numberbatch 19.08 [Speer et al., 2017] (referred to as NBatch below), respectively …","url":["https://www.ijcai.org/proceedings/2021/0077.pdf"]}
-{"year":"2021","title":"Bidirectional Language Modeling: A Systematic Literature Review","authors":["M Shah Jahan, HU Khan, S Akbar, M Umar Farooq… - Scientific Programming, 2021"],"snippet":"Page 1. Review Article Bidirectional Language Modeling: A Systematic Literature Review Muhammad Shah Jahan ,1 Habib Ullah Khan ,2 Shahzad Akbar ,3 Muhammad Umar Farooq ,1 Sarah Gul ,4 and Anam Amjad 1 1Department …","url":["https://www.hindawi.com/journals/sp/2021/6641832/"]}
-{"year":"2021","title":"Bilingual Lexical Induction for Sinhala-English using Cross Lingual Embedding Spaces","authors":["A Liyanage, S Ranathunga, S Jayasena - 2021 Moratuwa Engineering Research …, 2021"],"snippet":"… Using pre-trained fastText embeddings trained on Wikipedia and Common crawl data using two different evaluation dictionaries as a preliminary experiment to identify the performance of embeddings created from non-comparable corpora …","url":["https://ieeexplore.ieee.org/abstract/document/9525667/"]}
-{"year":"2021","title":"Bilingual Lexicon Induction via Unsupervised Bitext Construction and Word Alignment","authors":["H Shi, L Zettlemoyer, SI Wang - arXiv preprint arXiv:2101.00148"],"snippet":"Page 1. Bilingual Lexicon Induction via Unsupervised Bitext Construction and Word Alignment Haoyue Shi ∗ TTI-Chicago freda@ttic.edu Luke Zettlemoyer University of Washington Facebook AI Research lsz@fb.com …","url":["https://arxiv.org/pdf/2101.00148"]}
-{"year":"2021","title":"BitextEdit: Automatic Bitext Editing for Improved Low-Resource Machine Translation","authors":["E Briakou, SI Wang, L Zettlemoyer, M Ghazvininejad - arXiv preprint arXiv …, 2021"],"snippet":"Mined bitexts can contain imperfect translations that yield unreliable training signals for Neural Machine Translation (NMT). While filtering such pairs out is known to improve final model quality, we argue that it is suboptimal in low-resource conditions …","url":["https://arxiv.org/pdf/2111.06787"]}
-{"year":"2021","title":"Blank spots, critical information needs and local journalism fund-ing","authors":["S Bisiani"],"snippet":"Abstract A global business model crisis in journalism, fuelled by loss in advertising revenue, challenges the survival of local news production. In Sweden, it has led to the closure of several newspapers across the country, and the concentration of …","url":["http://compscjournalism.org/projects/simona/projects/Master_Thesis_Simona_Bisiani.pdf"]}
-{"year":"2021","title":"Book genre and author's gender recognition based on titles","authors":["A Pawłowski, E Herden, T Walkowiak - … and Text: Data, models, information and …, 2021"],"snippet":""}
-{"year":"2021","title":"BOSS: Bandwidth-Optimized Search Accelerator for Storage-Class Memory","authors":["J Heo, SY Lee, S Min, Y Park, SJ Jung, TJ Ham…"],"snippet":"Page 1. BOSS: Bandwidth-Optimized Search Accelerator for Storage-Class Memory Jun Heo, Seung Yul Lee, Sunhong Min, Yeonhong Park, Sung Jun Jung, Tae Jun Ham, Jae W. Lee Seoul National University {j.heo, triomphant1 …","url":["https://conferences.computer.org/iscapub/pdfs/ISCA2021-4ghucdBnCWYB7ES2Pe4YdT/333300a279/333300a279.pdf"]}
-{"year":"2021","title":"Bottom-Up Shift and Reasoning for Referring Image Segmentation","authors":["S Yang, M Xia, G Li, HY Zhou, Y Yu - Proceedings of the IEEE/CVF Conference on …, 2021"],"snippet":"Page 1. Bottom-Up Shift and Reasoning for Referring Image Segmentation Sibei Yang1∗† Meng Xia2∗ Guanbin Li2 Hong-Yu Zhou3 Yizhou Yu3,4† 1ShanghaiTech University 2Sun Yat-sen University 3The University of Hong Kong 4Deepwise AI Lab Abstract …","url":["https://openaccess.thecvf.com/content/CVPR2021/papers/Yang_Bottom-Up_Shift_and_Reasoning_for_Referring_Image_Segmentation_CVPR_2021_paper.pdf"]}
-{"year":"2021","title":"bradleypallen/keras-quora-question-pairs","authors":["ONDJF Mar, AMJJA Sep, OSMTW Thu, F Sat"],"snippet":"… Model, Source of Word Embeddings, Accuracy. \"BiMPM model\" [5], GloVe Common Crawl (840B tokens, 300D), 0.88 … \"Decomposable attention\" [6], \"Quora's text corpus\", 0.86. \"LDC\" [5], GloVe Common Crawl (840B tokens, 300D), 0.86 …","url":["https://giters.com/bradleypallen/keras-quora-question-pairs?amp=1"]}
-{"year":"2021","title":"Building a File Observatory for Secure Parser Development","authors":["T Allison, W Burke, C Mattmann, A Mensikova…"],"snippet":"… 3196–3200. [Online]. Available: http://www.lrec-conf.org/proceedings/lrec2012/pdf/534 Paper.pdf [10] “Common Crawl,” https://commoncrawl.org. [11] P. Wyatt, “Stressful PDF corpus grows!” https://www.pdfa.org/ stressful-pdf-corpus-grows/, November 2020.","url":["https://langsec.org/spw21/papers/Allison_LangSec21.pdf"]}
-{"year":"2021","title":"Building a Question and Answer System for News Domain","authors":["S Basu, A Gaddala, P Chetan, G Tiwari, N Darapaneni… - arXiv preprint arXiv …, 2021"],"snippet":"… We have used two approaches for building the Embedding Layers for the models 3. GloVe Embedding: we used the 300 Dimension Common Crawl for the English language 4. Universal Sentence Encoder: we used the 512 …","url":["https://arxiv.org/pdf/2105.05744"]}
-{"year":"2021","title":"Building Accountable Natural Language Processing Models: on Social Bias Detection and Mitigation","authors":["J Zhao - 2021"],"snippet":"Natural Language Processing (NLP) plays an important role in many applications, including resume filtering, text analysis, and information retrieval. Despite the remarkable accuracy enabled by the advances of machine learning methods, recent …","url":["https://escholarship.org/content/qt0441n1tt/qt0441n1tt.pdf"]}
-{"year":"2021","title":"But how robust is RoBERTa actually?: A Benchmark of SOTA Transformer Networks for Sexual Harassment Detection on Twitter","authors":["P Basu, TS Roy, A Singhal - 2021 Fifth International Conference on I-SMAC (IoT in …, 2021"],"snippet":"Harassment, which is of sexual/physical in nature, is defined as any unwanted sexual misconduct, including the unwarranted and ill-suited promise of benefit in exchange for sexual indulgence. It also includes a span of actions from verbal …","url":["https://ieeexplore.ieee.org/abstract/document/9640861/"]}
-{"year":"2021","title":"Can I Take Your Subdomain? Exploring Same-Site Attacks in the Modern Web","authors":["MSMTL Veronese, SCM Maffei"],"snippet":"Page 1. Can I Take Your Subdomain? Exploring Same-Site Attacks in the Modern Web Marco Squarcina1 Mauro Tempesta1 Lorenzo Veronese1 Stefano Calzavara2 Matteo Maffei1 1 TU Wien 2 Università Ca' Foscari Venezia & OWASP …","url":["https://minimalblue.com/data/papers/USENIX21_can_i_take_your_subdomain.pdf"]}
-{"year":"2021","title":"Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color","authors":["M Abdou, A Kulmizev, D Hershcovich, S Frank… - arXiv preprint arXiv …, 2021"],"snippet":"… Word-type FastText embeddings trained on Common Crawl (Bojanowski et al., 2017) … These S contexts are either randomly sampled from common crawl (RC), or deterministically generated to allow for control over contextual variation (CC) …","url":["https://arxiv.org/pdf/2109.06129"]}
-{"year":"2021","title":"Can Small and Synthetic Benchmarks Drive Modeling Innovation? A Retrospective Study of Question Answering Modeling Approaches","authors":["NF Liu, T Lee, R Jia, P Liang - arXiv preprint arXiv:2102.01065, 2021"],"snippet":"Page 1. Can Small and Synthetic Benchmarks Drive Modeling Innovation? A Retrospective Study of Question Answering Modeling Approaches Nelson F. Liu Tony Lee Robin Jia Percy Liang Computer Science Department, Stanford …","url":["https://arxiv.org/pdf/2102.01065"]}
-{"year":"2021","title":"CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervision","authors":["Z Li, X Ding, K Liao, T Liu, B Qin - arXiv preprint arXiv:2107.09852, 2021"],"snippet":"… ambiguity and precise causal patterns to extract word level causeeffect pairs from the preprocessed English Common Crawl corpus (5.14 … (2016) for creating a causal lexical knowledge base, we reproduce a variant of their …","url":["https://arxiv.org/pdf/2107.09852"]}
-{"year":"2021","title":"CCQA: A New Web-Scale Question Answering Dataset for Model Pre-Training","authors":["P Huber, A Aghajanyan, B Oğuz, D Okhonko, W Yih… - arXiv preprint arXiv …, 2021"],"snippet":"… Consequently, we propose a novel QA dataset based on the Common Crawl project in this paper. Using the readily available schema.org annotation, we extract around 130 million multilingual question-answer pairs, including about 60 million …","url":["https://arxiv.org/pdf/2110.07731"]}
-{"year":"2021","title":"CDA: a Cost Efficient Content-based Multilingual Web Document Aligner","authors":["T Vu, AA AI, A Moschitti - 2021"],"snippet":"… CommonCrawl Sextet Previous datasets share the same domains that are heavily biased toward French content (see Table 3). We leverage a monthly crawl from CommonCrawl, specifically … Table 4: Parallel English tokens …","url":["https://assets.amazon.science/01/69/5f786b844c08a079eda7e6437c16/cda-a-cost-efficient-content-based-multilingual-web-document-aligner.pdf"]}
-{"year":"2021","title":"Censorship of Online Encyclopedias: Implications for NLP Models","authors":["E Yang, ME Roberts - arXiv preprint arXiv:2101.09294, 2021"],"snippet":"… Word embeddings are also useful because they can be pre-trained on large corpuses of text like Wikipedia or Common Crawl, and these pre-trained embeddings can then be used as an initial layer in applications that may have less training data …","url":["https://arxiv.org/pdf/2101.09294"]}
-{"year":"2021","title":"Challenges for cognitive decoding using deep learning methods","authors":["AW Thomas, C Ré, RA Poldrack - arXiv preprint arXiv:2108.06896, 2021"],"snippet":"… learning in 251 the target domain. Transfer learning has been especially successful in CV and NLP, where large 252 publicly available datasets exist (eg, [72,73] and http://www.commoncrawl.org). Here, DL 253 models are first …","url":["https://arxiv.org/pdf/2108.06896"]}
-{"year":"2021","title":"Changing the World by Changing the Data","authors":["A Rogers - arXiv preprint arXiv:2105.13947, 2021"],"snippet":"… The use of uncontrolled samples (like the Common-Crawl-based corpora) would have to be justified by arguing either that the above types of bias can be safely ignored, or that the benefits outweigh the risks. 2.2.3 Might not be the best approach …","url":["https://arxiv.org/pdf/2105.13947"]}
-{"year":"2021","title":"Characterizing and addressing the issue of oversmoothing in neural autoregressive sequence modeling","authors":["I Kulikov, M Eremeev, K Cho - arXiv preprint arXiv:2112.08914, 2021"],"snippet":"… We use the subset of WMT’19 training set consisting of news commentary v12 and common crawl resulting in slightly more than 1M and 2M training sentence pairs for Ru→En and De↔En pairs, respectively. We fine-tuned single model checkpoints …","url":["https://arxiv.org/pdf/2112.08914"]}
-{"year":"2021","title":"Characterizing Network Infrastructure Using the Domain Name System","authors":["P Kintis - 2020"],"snippet":"Page 1. CHARACTERIZING NETWORK INFRASTRUCTURE USING THE DOMAIN NAME SYSTEM A Dissertation Presented to The Academic Faculty By Panagiotis Kintis In Partial Fulfillment of the Requirements for the Degree …","url":["https://smartech.gatech.edu/bitstream/handle/1853/64165/KINTIS-DISSERTATION-2020.pdf"]}
-{"year":"2021","title":"Charformer: Fast Character Transformers via Gradient-based Subword Tokenization","authors":["Y Tay, VQ Tran, S Ruder, J Gupta, HW Chung, D Bahri… - arXiv preprint arXiv …, 2021"],"snippet":"… In addition, we compare to the byte-level models from §3.1, which we pre-train on multilingual data. Setup We pre-train CHARFORMER as well as the Byte-level T5 and Byte-level T5+LASC baselines on multilingual …","url":["https://arxiv.org/pdf/2106.12672"]}
-{"year":"2021","title":"ChineseBERT: Chinese Pretraining Enhanced by Glyph and Pinyin Information","authors":["Z Sun, X Li, X Sun, Y Meng, X Ao, Q He, F Wu, J Li - arXiv preprint arXiv:2106.16038, 2021"],"snippet":"… We collected our pretraining data from CommonCrawl5. After pre-processing (such as removing the data with too much … ERNIE BERT-wwm MacBERT ChineseBERT Data Source Heterogeneous Wikipedia Heterogeneous …","url":["https://arxiv.org/pdf/2106.16038"]}
-{"year":"2021","title":"Claim Detection in Biomedical Twitter Posts","authors":["A Wührl, R Klinger - arXiv preprint arXiv:2104.11639, 2021"],"snippet":"… The first three models (NB, LG, BiLSTM) use 50-dimensional FastText (Bojanowski et al., 2017) embeddings trained on the Common Crawl corpus (600 billion tokens) as input6. NB. We use a (Gaussian) naive Bayes with …","url":["https://arxiv.org/pdf/2104.11639"]}
-{"year":"2021","title":"Classification of Emotions Based on Text and Qualitative Variables","authors":["J Dobša, D Šebalj, D Bužić"],"snippet":"… Experiments were done both with Common Crawl GloVe pretrained vectors with the dimensionality of 300, and without pretrained vectors. Fifteen percent of learning samples were used for validation. We constructed six neural networks models: CNN …","url":["https://www.researchgate.net/profile/Jasminka-Dobsa/publication/355461190_Classification_of_Emotions_Based_on_Text_and_Qualitative_Variables/links/61716c97750da711ac647d77/Classification-of-Emotions-Based-on-Text-and-Qualitative-Variables.pdf"]}
-{"year":"2021","title":"Classification of Horror Stories from Reddit","authors":["D Zhou, C Kim, S Gatiganti"],"snippet":"… We further hypothesize that performance would still increase a little if we used the larger pre-trained vectors such as Common Crawl or Twitter sets, but they come with increased download sizes (>1 GB) and increased training time …","url":["http://cs229.stanford.edu/proj2021spr/report2/82008167.pdf"]}
-{"year":"2021","title":"Classification of Texts Using a Vocabulary of Synonyms","authors":["A Giliazova - 2021 14th International Conference Management of …, 2021"],"snippet":"… This is a Transformer-based masked language model trained on one hundred languages, including Russian language, using more than two terabytes of filtered CommonCrawl data. The XLM-R model significantly outperforms multilingual BERT (mBERT) …","url":["https://ieeexplore.ieee.org/abstract/document/9600131/"]}
-{"year":"2021","title":"CLASSIFICATION OF TWEETS USING MULTIPLE THRESHOLDS WITH SELF-CORRECTION AND WEIGHTED CONDITIONAL","authors":["TN Ahmad - 2020"],"snippet":"Page 1. CLASSIFICATION OF TWEETS USING MULTIPLE THRESHOLDS WITH SELF-CORRECTION AND WEIGHTED CONDITIONAL PROBABILITIES A thesis submitted to The University of Manchester for the degree of Doctor of Philosophy …","url":["https://www.research.manchester.ac.uk/portal/files/188959099/FULL_TEXT.PDF"]}
-{"year":"2021","title":"Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications","authors":["S Sun, A El-Kishky, V Chaudhary, J Cross, F Guzmán… - arXiv preprint arXiv …, 2021"],"snippet":"… Current state of the art QE systems (Fomicheva et al., 2020b; Ranasinghe et al., 2020a; Sun et al., 2020). are built on XLM-R (Conneau et al., 2019), a contextualized language model pre-trained on more than 2 terabytes of …","url":["https://arxiv.org/pdf/2109.08627"]}
-{"year":"2021","title":"Classifying Fake and Real Neurally Generated News","authors":["A Govindaraju, J Griffith - 2021 Swedish Workshop on Data Science (SweDS), 2021"],"snippet":"… In order to train and test the model, 3 datasets have been created: One containing real news extracted from a common crawl; the second comprises a neural fake news dataset generated using language modelling techniques; the third comprises a …","url":["https://ieeexplore.ieee.org/abstract/document/9638268/"]}
-{"year":"2021","title":"CLEF eHealth Evaluation Lab 2021","authors":["L Kelly, LA Alemany, N Brew-Sam, V Cotik, D Filippo…"],"snippet":"… This collection consists of Web pages acquired from Common Crawl,14 which is augmented with additional pages collected from a number of known reliable health Websites and other known unreliable health Websites [9]. The topics …","url":["https://www.researchgate.net/profile/Marco-Viviani/publication/350569762_CLEF_eHealth_Evaluation_Lab_2021/links/6073f32e92851c8a7bbea835/CLEF-eHealth-Evaluation-Lab-2021.pdf"]}
-{"year":"2021","title":"Click This, Not That: Extending Web Authentication with Deception","authors":["T Barron, J So, N Nikiforakis - Proceedings of the 2021 ACM Asia Conference on …, 2021"],"snippet":"… after creation. References. 2020. Common Crawl. https://commoncrawl.org/the-data/ get-started/Google Scholar Google Scholar; 2020. Mouseflow: Session Replay, Heatmaps, Funnels, Forms & User Feedback. https://mouseflow …","url":["https://dl.acm.org/doi/abs/10.1145/3433210.3453088"]}
-{"year":"2021","title":"ClimateBert: A Pretrained Language Model for Climate-Related Text","authors":["N Webersinke, M Kraus, JA Bingler, M Leippold - arXiv preprint arXiv:2110.12010, 2021"],"snippet":"… 2019), and a subset of CommonCrawl that is said to resemble the storylike style of WINOGRAD schemas (Trinh and Le, 2019). While these sources are valuable to build a model working on general language, it has been shown that domain-specific …","url":["https://arxiv.org/pdf/2110.12010"]}
-{"year":"2021","title":"CLIP2StyleGAN: Unsupervised Extraction of StyleGAN Edit Directions","authors":["R Abdal, P Zhu, J Femiani, NJ Mitra, P Wonka - arXiv preprint arXiv:2112.05219, 2021"],"snippet":"… The CLIP image encoder [34] is trained on the common-crawl dataset, an internet-scale set of images that encompasses a broad range of visual concepts. However, a typical high-quality GAN would be trained on a more specific set of images, for example …","url":["https://arxiv.org/pdf/2112.05219"]}
-{"year":"2021","title":"Cluster analysis of agricultural household production of self-employed","authors":["AV Plotnikov - IOP Conference Series: Earth and Environmental …, 2021"],"snippet":"… To train this model, we used a sample of Russian-language documents from the CommonCrawl dump, balanced by geography, compiled by Jonathan Dunn and Ben Adams; the corpus Size is 2.1 billion words. Page 5. AGRITECH-IV-2020 IOP Conf …","url":["https://iopscience.iop.org/article/10.1088/1755-1315/677/2/022080/pdf"]}
-{"year":"2021","title":"Cluster-Based Antiphishing (CAP) Model for Smart Phones","authors":["M Faisal, S Abed - Scientific Programming"],"snippet":"… latest techniques tested on UCI datasets. 4.4.2. Dataset Taken from Mendeley. Source Phishing web page: Phish Tank, Legitimate web page source: Alexa, Common Crawl (1) Dataset Information. In this scenario, the dataset …","url":["https://www.hindawi.com/journals/sp/2021/9957323/"]}
-{"year":"2021","title":"Code-Mixing on Sesame Street: Dawn of the Adversarial Polyglots","authors":["S Tan, S Joty - arXiv preprint arXiv:2103.09593, 2021"],"snippet":"… However, the latter trend is replicated for BUMBLEBEE if we remove this constraint (Table 14 in Appendix G). A possible explanation is that XLM-R and Unicoder were trained on monolingual CommonCrawl (CC) data, while …","url":["https://arxiv.org/pdf/2103.09593"]}
-{"year":"2021","title":"CoDesc: A Large Code–Description Parallel Dataset","authors":["M Hasan, T Muttaqueen, A Al Ishtiaq, KS Mehrab…"],"snippet":"… 9052–9065, Online. Association for Computational Linguistics. CommonCrawl Common crawl. https:// commoncrawl.org/. Accessed: 2021-01-31. Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 …","url":["http://masumhasan.net/files/CoDesc.pdf"]}
-{"year":"2021","title":"Combining Natural Language Processing and Machine Learning for Profiling and Fake News Detection","authors":["A Bondielli"],"snippet":"Page 1. PHD PROGRAM IN SMART COMPUTING DIPARTIMENTO DI INGEGNERIA DELL'INFORMAZIONE (DINFO) Combining Natural Language Processing and Machine Learning for Profiling and Fake News Detection Alessandro Bondielli …","url":["https://flore.unifi.it/bitstream/2158/1244287/1/PhDThesis_AlessandroBondielli.pdf"]}
-{"year":"2021","title":"Combining Pre-trained Word Embeddings and Linguistic Features for Sequential Metaphor Identification","authors":["R Mao, C Lin, F Guerin - arXiv preprint arXiv:2104.03285, 2021"],"snippet":"… For instance, GloVe was trained on Common Crawl2, from billions of web pages (840 billion tokens); ELMo was trained on WMT 2011 News Crawl data3 (800 million tokens); BERT was trained on Wikipedia4 (2.5 billion tokens) …","url":["https://arxiv.org/pdf/2104.03285"]}
-{"year":"2021","title":"Combining word embeddings as a tool for subject identification","authors":["A Hamm - Wissensaustauschworkshop\" Maschinelles Lernen VII\", 2021"],"snippet":"This talk shows ungoing work aiming at finding subject matter relations between text documents and word clouds. A number of increasingly successful semantic word embedding procedures - learning semantic relations from contextual distributions …","url":["https://elib.dlr.de/147623/1/Combining%20word%20embeddings.pdf"]}
-{"year":"2021","title":"Comparative Analysis of Bengali Stop Word Detection Using Different Approaches","authors":["RJ Rupa, JF Sohana, M Rahman - … on Automation, Control and Mechatronics for …, 2021"],"snippet":"… In this paper, the pretrained Bengali FastText CBOW model is utilized to produce word vectors trained on the common crawl and Wikipedia [27] and both logistic regression and support vector machine classifiers acquire a performance score of 86%. TABLE XII …","url":["https://ieeexplore.ieee.org/abstract/document/9528279/"]}
-{"year":"2021","title":"Comparative Analysis of Different Transformer Based Architectures Used in Sentiment Analysis","authors":["K Pipalia, R Bhadja, M Shukla - 2020 9th International Conference System Modeling …, 2020"],"snippet":"… Distill BERT Base:66 BookCorpus wiki BERT Distillation T5 Base:220 large:770 Colossal Clean Crawled Corpus (C4) Text Infilling XLNet Base:~110 Large:~340 BookCorpus Wiki, Giga5 ClueWeb, Common Crawl …","url":["https://ieeexplore.ieee.org/abstract/document/9337081/"]}
-{"year":"2021","title":"Comparing Apples and Oranges: Human and Computer Clustered Affinity Diagrams Under the Microscope","authors":["P Borlinghaus, S Huber - 26th International Conference on Intelligent User …, 2021"],"snippet":"… training corpora WSD no OOV LSI [9] − NMF [18] − LDA [5] − GloVe [26] Wiki word2vec [22] Google News corpus doc2vec [17] 900k sentences from qualitative survey ◦ fastText [6] Common Crawl, Wiki • … FastText was trained on Common Crawl and Wikipedia corpus …","url":["https://dl.acm.org/doi/abs/10.1145/3397481.3450674"]}
-{"year":"2021","title":"Comparing Contextualised Embeddings for Predicting the (Graded) Effect of Context in Word Similarity","authors":["JM Albers - 2021"],"snippet":"… As data set XLM-RoBERTa uses CommonCrawl instead of Wikipedia, which provides limited scale for low resource languages. 4 Page 5 … The CommonCrawl data set is designed to be more diverse than other data sets, which mainly use Wikipedia and books …","url":["https://dspace.library.uu.nl/bitstream/handle/1874/406113/6400507_JorisAlbers_Thesis.pdf?sequence=1"]}
-{"year":"2021","title":"Comparing Encoder-Decoder Architectures for Neural Machine Translation: A Challenge Set Approach","authors":["C Doan - 2021"],"snippet":"Machine translation (MT) as a field of research has known significant advances in recent years, with the increased interest for neural machine translation (NMT). By combining deep learning with translation, researchers have been able to deliver …","url":["https://ruor.uottawa.ca/bitstream/10393/42936/1/Doan_Coraline_2021_thesis.pdf"]}
-{"year":"2021","title":"Comparing general and specialized word embeddings for biomedical named entity recognition","authors":["RE Ramos-Vargas, I Román-Godínez, S Torres-Ramos - PeerJ Computer Science, 2021"],"snippet":"… 01-14 Received 2020-11-05 Academic Editor Susan Gauch Subject Areas Bioinformatics, Artificial Intelligence, Computational Linguistics Keywords Word embeddings, BioNER, BiLSTM-CRF, DrugBank, MedLine, Pyysalo …","url":["https://peerj.com/articles/cs-384/"]}
-{"year":"2021","title":"Comparing the Performance of NLP Toolkits and Evaluation measures in Legal Tech","authors":["MZ Khan, J Mitrovic, JMPDM Granitzer - 2021"],"snippet":"Page 1. Lehrstuhl für Data Science Comparing the Performance of NLP Toolkits and Evaluation measures in Legal Tech Masterarbeit von Muhammad Zohaib Khan Supervised By: Prof. Dr. Jelena Mitrovic 1. Prüfer 2. Prüfer …","url":["https://www.academia.edu/download/65887417/Deep_Neural_Language_Modelling_in_Law.pdf"]}
-{"year":"2021","title":"Comparing Traditional and Neural Approaches for Detecting Health-Related Misinformation","authors":["D Elsweiler - … IR Meets Multilinguality, Multimodality, and Interaction …","M Fernández-Pichel, DE Losada, JC Pichel…"],"snippet":"… Table 1 reports the main statistics of the resulting datasets. We also tested classifiers for the task of distinguishing between useful documents for non-expert end users (ie, trustworthy and readable) and non-useful …","url":["http://persoal.citius.usc.es/jcpichel/docs/2021_CLEF_MFernandezPichel.pdf","https://books.google.de/books?hl=en&lr=lang_en&id=p9FCEAAAQBAJ&oi=fnd&pg=PA78&dq=commoncrawl&ots=eNycpv3vEv&sig=v7CAPFEmV26pL2Lhj2R2t581gZ0"]}
-{"year":"2021","title":"Comparison of Czech Transformers on Text Classification Tasks","authors":["J Lehečka, J Švec - arXiv preprint arXiv:2107.10042, 2021"],"snippet":"… Researchers from Facebook have published multilingual XLM-RoBERTa model [3] pre-trained on one hundred languages (including Czech), using more than two terabytes of filtered Common Crawl data … 2. 1https …","url":["https://arxiv.org/pdf/2107.10042"]}
-{"year":"2021","title":"Compilation and Validation of a Large Fake News Dataset in Hungarian","authors":["M Gencsi, Z Bodó, A Szenkovits - 2021 IEEE 19th International Symposium on …, 2021"],"snippet":"… The huBERT model was trained on the Hungarian subset of the Common Crawl and a snapshot of the Hungarian Wikipedia, while the multilingual model was trained on the top 104 languages with the largest Wikipedias, among them also …","url":["https://ieeexplore.ieee.org/abstract/document/9582484/"]}
-{"year":"2021","title":"Comprehensive analysis of embeddings and pre-training in NLP","authors":["JK Tripathy, SC Sethuraman, MV Cruz, A Namburu… - Computer Science Review, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S1574013721000733"]}
-{"year":"2021","title":"Comprehensive Evaluation of Word Embeddings for Highly Inflectional Language","authors":["P Drozda, K Sopyla, J Lewalski - International Conference on Computational …, 2021"],"snippet":"… The obtained results showed that in terms of accuracy the Facebook fasttext model learned on the Common Crawl collection should be considered the best model under assumptions of experimental session. Keywords. Word …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88113-9_48"]}
-{"year":"2021","title":"Comprehensive Multi-Modal Interactions for Referring Image Segmentation","authors":["K Jain, V Gandhi - arXiv preprint arXiv:2104.10412, 2021"],"snippet":"… 576. At 448 × 448 resolution, H = W = 14 and at 576 × 576 resolution, H = W = 18. We use GLoVe embeddings [17] pre-trained on Common Crawl 840B tokens to initialize word embedding for words in the expressions. The …","url":["https://arxiv.org/pdf/2104.10412"]}
-{"year":"2021","title":"Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation","authors":["M Deng, B Tan, Z Liu, EP Xing, Z Hu - arXiv preprint arXiv:2109.06379, 2021"],"snippet":"Page 1. Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation Mingkai Deng1∗, Bowen Tan1∗, Zhengzhong Liu1,2, Eric P. Xing1,2,3, Zhiting Hu4 1Carnegie Mellon University …","url":["https://arxiv.org/pdf/2109.06379"]}
-{"year":"2021","title":"Computational analysis and synthesis of song lyrics","authors":["P Březinová - 2021"],"snippet":"… It uses CMUdict for phonetic transcription, analyzes CommonCrawl8 web data repository for forced rhymes, Google Books Ngrams (Weiss [2015]) for building language model, and WordNet 3.0 (Pearson et al. [2005]) for semantic relations …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/147665/120397406.pdf?sequence=1"]}
-{"year":"2021","title":"Computational Challenges for Artificial Intelligence and Machine Learning in Environmental Research","authors":["M Werner, G Dax, M Laass - INFORMATIK 2020, 2021"],"snippet":"… This includes news streams, social media messages, human-curated knowledge such as OpenStreetMap and Wikipedia, opinionated data sources such as blog posts from certain platforms, or blind web scale data collections such as common crawl …","url":["https://dl.gi.de/bitstream/handle/20.500.12116/34809/C21-1.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"Computational filling of curatorial gaps in a fine arts exhibition","authors":["A Flexer"],"snippet":"… Please note that we translate all keywords from German to English for this paper. We use the German fasttext5 word em- bedding, which has been trained on about 3 million words from the Wikipediaand 19 million words …","url":["https://computationalcreativity.net/iccc21/wp-content/uploads/2021/09/ICCC_2021_paper_75reduced.pdf"]}
-{"year":"2021","title":"Computational methods to understand the association between emojis and emotions","authors":["AAM Shoeb - 2021"],"snippet":"Page 1. © 2021 Abu Awal Md Shoeb ALL RIGHTS RESERVED Page 2. COMPUTATIONAL METHODS TO UNDERSTAND THE ASSOCIATION BETWEEN EMOJIS AND EMOTIONS By ABU AWAL MD SHOEB A dissertation submitted to the School of Graduate Studies …","url":["https://rucore.libraries.rutgers.edu/rutgers-lib/65975/PDF/1/"]}
-{"year":"2021","title":"Computer Science Review","authors":["JK Tripathy, SC Sethuraman, MV Cruz, V Vijayakumar - 2021"],"snippet":"abstract The amount of data and computing power has drastically increased over the last decade, which leads to the development of several new fronts in the field of Natural Language Processing (NLP). In addition to that, the entanglement of …","url":["https://www.researchgate.net/profile/Mangalraj-Poobalasubramanian/publication/355132427_Comprehensive_analysis_of_embeddings_and_pre-training_in_NLP/links/6164f98e1eb5da761e836888/Comprehensive-analysis-of-embeddings-and-pre-training-in-NLP.pdf"]}
-{"year":"2021","title":"CoMSum and SIBERT: A Dataset and Neural Model for Query-Based Multi-document Summarization","authors":["S Kulkarni, S Chammas, W Zhu, F Sha, E Ie - International Conference on Document …, 2021"],"snippet":"… We use the cleaned Common Crawl (CC) corpus [32] to source relevant web documents that are diverse and multi-faceted for generating Natural Questions (NQ) (long-form) answers [21]. Figure 1 illustrates the overall procedure …","url":["https://link.springer.com/chapter/10.1007/978-3-030-86331-9_6"]}
-{"year":"2021","title":"Concept-Based Label Embedding via Dynamic Routing for Hierarchical Text Classification","authors":["X Wang, L Zhao, B Liu, T Chen, F Zhang, D Wang"],"snippet":"… Hyper-parameters are tuned on a validation set by grid search. We take Stanford's publicly available GloVe 300-dimensional embeddings trained on 42 billion tokens from Common Crawl (Pennington et al., 2014) as initialization for word em- beddings …","url":["https://aclanthology.org/2021.acl-long.388.pdf"]}
-{"year":"2021","title":"Confused by Path: Analysis of Path Confusion Based Attacks","authors":["SA Mirheidari - 2020"],"snippet":"… 93 iii Page 10. Page 11. List of Tables 4.1 Sample Grouped Web pages. . . . . 29 4.2 Narrowing down the Common Crawl to the candidate set used in our analysis (from left to right). . . . 36 4.3 Vulnerable pages and sites in the candidate set …","url":["https://iris.unitn.it/retrieve/handle/11572/280512/382175/phd_unitn_Seyed%20Ali_Mirheidari.pdf"]}
-{"year":"2021","title":"ConRPG: Paraphrase Generation using Contexts as Regularizer","authors":["Y Meng, X Ao, Q He, X Sun, Q Han, F Wu, J Li - arXiv preprint arXiv:2109.00363, 2021"],"snippet":"… We implement the above models, ie p(−→ci|c<i,c>i), p(←−ci|c<i,c>i), p(c<i|ci,c>i), p(c>i|c<i,ci) based on the SEQ2SEQ structure on a subset of CommonCrawl containing 10 billion tokens in total. We use Transformers …","url":["https://arxiv.org/pdf/2109.00363"]}
-{"year":"2021","title":"Consumer Health Search at CLEF eHealth 2021","authors":["L Goeuriot, G Pasi, H Suominen, E Bassani… - CLEF 2021 Evaluation Labs …, 2021"],"snippet":"… The task generated a new representative web corpus including web pages acquired from a 2021 CommonCrawl and social media content from Twitter and Reddit, along with a new collection of 55 manually generated layperson …","url":["http://ceur-ws.org/Vol-2936/paper-62.pdf"]}
-{"year":"2021","title":"Contingency of semantic generalization on episodic specificity varies across development","authors":["CT Ngo, SL Benear, H Popal, IR Olson, NS Newcombe - Current Biology, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0960982221004619"]}
-{"year":"2021","title":"Contrastive finetuning of generative language models for informal premise selection","authors":["JM Han, T Xu, S Polu, A Neelakantan, A Radford"],"snippet":"… contrastive training. • GPT-3 style pretraining. The model is pretrained for 300B tokens on the same data (a mix of filtered CommonCrawl, WebText, books, and Wikipedia) as GPT-3 [2]. • WebMath pretraining. Starting from the …","url":["http://aitp-conference.org/2021/abstract/paper_21.pdf"]}
-{"year":"2021","title":"Control Prefixes for Text Generation","authors":["J Clive, K Cao, M Rei - arXiv preprint arXiv:2110.08329, 2021"],"snippet":"Prompt learning methods adapt pre-trained language models to downstream applications by using a task-specific prompt together with the input. Most of the current work on prompt learning in text generation relies on a shared dataset-level …","url":["https://arxiv.org/pdf/2110.08329"]}
-{"year":"2021","title":"Conversations Powered by Cross-Lingual Knowledge","authors":["W Sun, C Meng, Q Meng, Z Ren, P Ren, Z Chen… - 2021"],"snippet":"Page 1. Conversations Powered by Cross-Lingual Knowledge Weiwei Sun1* Chuan Meng1* Qi Meng2 Zhaochun Ren1† Pengjie Ren1† Zhumin Chen1 Maarten de Rijke3,4 1Shandong University, Qingdao, China 2Microsoft …","url":["https://staff.fnwi.uva.nl/m.derijke/wp-content/papercite-data/pdf/sun-2021-conversations.pdf"]}
-{"year":"2021","title":"CopyCat: Near-Duplicates within and between the ClueWeb and the Common Crawl","authors":["M Fröbe, J Bevendorff, L Gienapp, M Völske, B Stein… - 2021"],"snippet":"The amount of near-duplicates in web crawls like the ClueWeb or Common Crawl demands from their users either to develop a preprocessing pipeline for deduplication, which is costly both computationally and in person hours, or accepting …","url":["https://webis.de/downloads/publications/papers/froebe_2021.pdf"]}
-{"year":"2021","title":"Corpulyzer: A Novel Framework for Building Low Resource Language Corpora","authors":["B Tahir, MA Mehmood - IEEE Access"],"snippet":"… Leveraging dataset from Common Crawl Corpus (CCC), first, we prepare a list of seed URLs by filtering the Urdu language webpages … INDEX TERMS Common crawl, web crawling, text corpus, corpus analysis, regional languages corpora …","url":["https://ieeexplore.ieee.org/iel7/6287639/9312710/09316706.pdf"]}
-{"year":"2021","title":"Corpus and Baseline Model for Domain-Specific Entity Recognition in German","authors":["S Torge, W Hahn, R Jäkel, WE Nagel - 2020 6th IEEE Congress on Information …, 2021"],"snippet":"… Deepset AI4 FastText Wikipedia 100 Deepset AI GloVe Wikipedia 300 FastText [26] FastText Wikipedia, 300 Common Crawl Kyubyong5 Word2Vec Wikipedia 300 SB Tweets s[27] FastText 50 Mio Tweets 100 SB Tweets l[27] FastText 50 Mio Tweets 300 …","url":["https://ieeexplore.ieee.org/abstract/document/9357189/"]}
-{"year":"2021","title":"COVIDSenti: A Large-Scale Benchmark Twitter Data Set for COVID-19 Sentiment Analysis","authors":["P BALAJI","U Naseem, I Razzak, M Khushi, PW Eklund, J Kim - IEEE Transactions on …, 2021"],"snippet":"… Similarly, for word embeddings, pretrained Word2Vec, GloVe, and fastText embeddings trained on Common Crawl and Wikipedia are used and have 300D vectors. In addition, we used hybrid models, such as hybrid ranking (HyRank) and …","url":["https://ieeexplore.ieee.org/abstract/document/9340540/","https://sist.sathyabama.ac.in/sist_naac/documents/1.3.4/1822-b.tech-it-batchno-359.pdf"]}
-{"year":"2021","title":"CRASS: A Novel Data Set and Benchmark to Test Counterfactual Reasoning of Large Language Models","authors":["J Frohberg, F Binder - arXiv preprint arXiv:2112.11941, 2021"],"snippet":"We introduce the CRASS (counterfactual reasoning assessment) data set and benchmark utilizing questionized counterfactual conditionals as a novel and powerful tool to evaluate large language models. We present the data set design …","url":["https://arxiv.org/pdf/2112.11941"]}
-{"year":"2021","title":"Creation, Enrichment and Application of Knowledge Graphs","authors":["S Gottschalk - 2021"],"snippet":"Page 1. CREATION, ENRICHMENT AND APPLICATION OF KNOWLEDGE GRAPHS Von der Fakultät für Elektrotechnik und Informatik der Gottfried Wilhelm Leibniz Universität Hannover zur Erlangung des Grades DOKTOR …","url":["https://www.repo.uni-hannover.de/bitstream/handle/123456789/11125/phd_thesis_gottschalk.pdf?sequence=1"]}
-{"year":"2021","title":"CrisisBench: Benchmarking Crisis-related Social Media Datasets for Humanitarian Information Processing","authors":["F Alam, H Sajjad, M Imran, F Ofli - 2021"],"snippet":"… 2017). fastText: For the fastText (Joulin et al. 2017), we used pretrained embeddings trained on Common Crawl, which is re- leased by fastText for English. Transformer models: Pre-trained models have achieved …","url":["https://mimran.me/papers/CrisisBench_Benchmarking_Crisis_related_Social_Media_Datasets_ICWSM21.pdf"]}
-{"year":"2021","title":"Cross-Domain Transfer of Generative Explanations Using Text-to-Text Models","authors":["KF Erliksson, A Arpteg, M Matskin, AH Payberah - International Conference on …, 2021"],"snippet":"… An analysis of BERT'S attention. In: ACL Blackbox NLP Workshop (2019)Google Scholar. 7. Common Crawl. https://www.commoncrawl.org. 8. Danilevsky, M., et al.: A survey of the state of explainable AI for natural language processing …","url":["https://link.springer.com/chapter/10.1007/978-3-030-80599-9_8"]}
-{"year":"2021","title":"Cross-language Information Retrieval","authors":["P Galuščáková, DW Oard, S Nair - arXiv preprint arXiv:2111.05988, 2021"],"snippet":"Two key assumptions shape the usual view of ranked retrieval: (1) that the searcher can choose words for their query that might appear in the documents that they wish to see, and (2) that ranking retrieved documents will suffice because the searcher …","url":["https://arxiv.org/pdf/2111.05988"]}
-{"year":"2021","title":"Cross-Language Learning for Entity Matching","authors":["R Peeters, C Bizer - arXiv preprint arXiv:2110.03338, 2021"],"snippet":"… We further use a German BERT model pre-trained on a di- verse set of German data ('bert-base-german-dbmdz-uncased'), including the German Wikipedia, parts of the Common Crawl, and EU Bookshop corpus, which …","url":["https://arxiv.org/pdf/2110.03338"]}
-{"year":"2021","title":"Cross-lingual Capsule Network for Hate Speech Detection in Social Media","authors":["A Jiang, A Zubiaga - arXiv preprint arXiv:2108.03089, 2021"],"snippet":"… mBERT. Multilingual BERT6 (mBERT) is a variant of BERT [14] that was trained on 104 languages of Wikipedia; XLM-R. XLM-RoBERTa is a scaled cross-lingual sentence en- coder across 100 languages from Common Crawl [11]; …","url":["https://arxiv.org/pdf/2108.03089"]}
-{"year":"2021","title":"Cross-lingual Fine-tuning for Abstractive Arabic Text Summarization","authors":["M Kahla, ZG Yang, A Novák - 2021"],"snippet":"… We only kept ar- ticles from the “Main/Top Stories” section, and filtered out all articles where either the main article text or the lead was too short or missing and items where the text is shorter than 4 times the 2https://www …","url":["http://nlpg.itk.ppke.hu/sites/default/files/publications/RANLP2021_Cross_lingual_fine_tuning_for_Abstractive_Arabic_Text_Summarization.pdf"]}
-{"year":"2021","title":"Cross-lingual Hate Speech Detection using Transformer Models","authors":["T Tiţa, A Zubiaga - arXiv preprint arXiv:2111.00981, 2021"],"snippet":"Hate speech detection within a cross-lingual setting represents a paramount area of interest for all medium and large-scale online platforms. Failing to properly address this issue on a global scale has already led over time to morally questionable real-life …","url":["https://arxiv.org/pdf/2111.00981"]}
-{"year":"2021","title":"Cross-lingual Language Model Pretraining for Retrieval","authors":["P Yu, H Fei, P Li - Proceedings of the Web Conference 2021, 2021"],"snippet":"… (MLM) and next sentence prediction (NSP) objectives [13] on the top 102 languages with the largest Wikipedia dumps. (v) XLM-R. We use the public checkpoint9 [8]. It was originally pretrained with the MLM objective on the CommonCrawl corpus in 100 languages …","url":["https://dl.acm.org/doi/abs/10.1145/3442381.3449830"]}
-{"year":"2021","title":"Cross-Lingual Text Classification of Transliterated Hindi and Malayalam","authors":["J Krishnan, A Anastasopoulos, H Purohit, H Rangwala - arXiv preprint arXiv …, 2021"],"snippet":"… The improvement produced by our model is due to the fact that the pre-trained models have likely not seen that many transliterations in these languages. mBERT is trained using data from Wikipedia, while XLM-R uses Common Crawl …","url":["https://arxiv.org/pdf/2108.13620"]}
-{"year":"2021","title":"Cross-lingual Transfer for Text Classification with Dictionary-based Heterogeneous Graph","authors":["N Chairatanakul, N Sriwatanasakdi… - arXiv preprint arXiv …, 2021"],"snippet":"… FastText (Bojanowski et al., 2017): a taskindependent word embedding trained on Wikipedia and Common Crawl only of a target language. • RCSLS (Joulin et al., 2018): a CLWE trained on Wikipedia. We used public FastText4 version …","url":["https://arxiv.org/pdf/2109.04400"]}
-{"year":"2021","title":"Cross-lingual transfer of abstractive summarizer to less-resource language","authors":["A Žagar, M Robnik-Šikonja - Journal of Intelligent Information Systems, 2021"],"snippet":"Automatic text summarization extracts important information from texts and presents the information in the form of a summary. Abstractive summarization app.","url":["https://link.springer.com/article/10.1007/s10844-021-00663-8"]}
-{"year":"2021","title":"Cross-lingual Transferring of Pre-trained Contextualized Language Models","authors":["Z Li, K Parnow, H Zhao, Z Zhang, R Wang, M Utiyama… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. ARXIV, DECEMBER 2020 1 Cross-lingual Transferring of Pre-trained Contextualized Language Models Zuchao Li, Kevin Parnow, Hai Zhao, Zhuosheng Zhang, Rui Wang, Masao Utiyama, and Eiichiro Sumita Abstract …","url":["https://arxiv.org/pdf/2107.12627"]}
-{"year":"2021","title":"Cross-Lingual Word Embedding Refinement by $\\ell_ {1} $ Norm Optimisation","authors":["X Peng, C Lin, M Stevenson - arXiv preprint arXiv:2104.04916, 2021"],"snippet":"… Tibetan family). News-Embs (Artetxe et al., 2018a): embeddings trained on a multilingual News text collection, ie, Page 5. the WaCKy Crawl of {EN, DE, IT}, the Common Crawl of FI, and the WMT News Crawl of ES. News-Embs …","url":["https://arxiv.org/pdf/2104.04916"]}
-{"year":"2021","title":"Cross-Lingual Word Embedding Refinement by ℓ1 Norm Optimisation Norm Optimisation","authors":["X Peng, C Lin, M Stevenson - Proceedings of the 2021 Conference of the North …, 2021"],"snippet":"… family). News-Embs (Artetxe et al., 2018a): embeddings trained on a multilingual News text collection, ie, Page 5. 2694 the WaCKy Crawl of {EN, DE, IT}, the Common Crawl of FI, and the WMT News Crawl of ES. News-Embs …","url":["https://www.aclweb.org/anthology/2021.naacl-main.214.pdf"]}
-{"year":"2021","title":"Cross-lingual word embedding refinement by ℓ1 norm optimisation","authors":["X Peng, C Lin, M Stevenson - arXiv, 2021"],"snippet":"… Tibetan family). News-Embs (Artetxe et al., 2018a): embeddings trained on a multilingual News text collection, ie, Page 6. the WaCKy Crawl of {EN, DE, IT}, the Common Crawl of FI, and the WMT News Crawl of ES. News-Embs …","url":["https://eprints.whiterose.ac.uk/173333/1/2104.04916v1.pdf"]}
-{"year":"2021","title":"Cross-Modal Progressive Comprehension for Referring Segmentation","authors":["S Liu, T Hui, S Huang, Y Wei, B Li, G Li - IEEE Transactions on Pattern Analysis and …, 2021"],"snippet":"Page 1. 0162-8828 (c) 2021 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/9430750/"]}
-{"year":"2021","title":"CTNet: Conversational Transformer Network for Emotion Recognition","authors":["Z Lian, B Liu, J Tao - IEEE/ACM Transactions on Audio, Speech, and …, 2021"],"snippet":"… utterances. Specifically, we convert transcripts into the concatenation of vectors of the constituent words. These vectors are the public available word vectors trained on the Common Crawl and Wikipedia datasets [44]. Totally …","url":["https://ieeexplore.ieee.org/abstract/document/9316758/"]}
-{"year":"2021","title":"CUNI systems for WMT21: Terminology translation Shared Task","authors":["J Jon, M Novák, JP Aires, D Variš, O Bojar - arXiv preprint arXiv:2109.09350, 2021"],"snippet":"… 3.1 Data We used all English-French corpora allowed by the organizers, aside from Paracrawl (with the exception of one model, which is marked). Namely this means Europarl v10, Common Crawl, UN Parallel Corpus …","url":["https://arxiv.org/pdf/2109.09350"]}
-{"year":"2021","title":"Current Advances in Neural Networks","authors":["V Gallego, DR Insua - 2021"],"snippet":"Abstract This article reviews current advances and developments in neural networks. This requires recalling some of the earlier work in the field. We emphasize Bayesian approaches and their benefits compared to more standard maximum likelihood …","url":["https://www.annualreviews.org/doi/abs/10.1146/annurev-statistics-040220-112019"]}
-{"year":"2021","title":"Data Augmentation for Speech Recognition in Maltese: A Low-Resource Perspective","authors":["C Mena, A DeMarco, C Borg, L van der Plas, A Gatt - arXiv preprint arXiv:2111.07793, 2021"],"snippet":"Developing speech technologies is a challenge for low-resource languages for which both annotated and raw speech data is sparse. Maltese is one such language. Recent years have seen an increased interest in the computational processing of …","url":["https://arxiv.org/pdf/2111.07793"]}
-{"year":"2021","title":"Data augmentation impact on domain-specific text summarization","authors":["A LAIFA, C CRUZ, L Gautier"],"snippet":"… Association for Computational Linguistics, Seattle / Virtual, United States (2020) 4. Lin C., Text Summarization Branches Out, 74–81. Association for Computational Linguistics, Barcelona, Spain (2004) 5. Common Crawl Foundation, https://commoncrawl.org/","url":["https://www.researchgate.net/profile/Abdelghani-Laifa/publication/351935366_Data_augmentation_impact_on_domain-specific_text_summarization/links/60b0b492458515bfb0ac029e/Data-augmentation-impact-on-domain-specific-text-summarization.pdf"]}
-{"year":"2021","title":"Data Efficient Deep Learning Models for Text Classification","authors":["R Garreta"],"snippet":"Page 1. Universidad de la República PEDECIBA Informática Master Thesis Data Efficient Deep Learning Models for Text Classification Author: Raúl Garreta Supervisors …","url":["https://www.fing.edu.uy/inco/grupos/pln/publicaciones/tesis_garreta.pdf"]}
-{"year":"2021","title":"Data Filtering using Cross-Lingual Word Embeddings","authors":["C Herold, J Rosendahl, J Vanvinckenroye, H Ney - … of the 2021 Conference of the …, 2021"],"snippet":"… The De→En training data consists of the corpora Commoncrawl, Europarl, Rapid and ParaCrawl from the WMT 2019 news translation task2. We use the czeng 1.7 corpus3 from the WMT 2018 news translation task for En→Cs …","url":["https://www.aclweb.org/anthology/2021.naacl-main.15.pdf"]}
-{"year":"2021","title":"Data science with Vadalog: Knowledge Graphs with machine learning and reasoning in practice","authors":["L Bellomarini, RR Fayzrakhmanov, G Gottlob… - Future Generation …, 2021"],"snippet":"… Such resources originate from data streams collected from internal systems (eg, Enterprise Resource Planning, Workflow Management, and Supply Chain Management) and external resources (eg, news, social media feeds and the Common Crawl 1 ). …","url":["https://www.sciencedirect.com/science/article/pii/S0167739X21004179"]}
-{"year":"2021","title":"Dataset for Identification of Homophobia and Transophobia in Multilingual YouTube Comments","authors":["BR Chakravarthi, R Priyadharshini, R Ponnusamy… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Abstract The increased proliferation of abusive content on social media platforms has a negative impact on online users. The dread, dislike, discomfort, or mistrust of lesbian, gay, transgender or bisexual persons is de- fined as homophobia/transphobia …","url":["https://arxiv.org/pdf/2109.00227"]}
-{"year":"2021","title":"DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing","authors":["P He, J Gao, W Chen - arXiv preprint arXiv:2111.09543, 2021"],"snippet":"This paper presents a new pre-trained language model, DeBERTaV3, which improves the original DeBERTa model by replacing mask language modeling (MLM) with replaced token detection (RTD), a more sample-efficient pre-training task. Our …","url":["https://arxiv.org/pdf/2111.09543"]}
-{"year":"2021","title":"Debiasing Multilingual Word Embeddings: A Case Study of Three Indian Languages","authors":["S Bansal, V Garimella, A Suhane, A Mukherjee - arXiv preprint arXiv:2107.10181, 2021"],"snippet":"… We do not plan to release non-anonymized bios-data since it is already available for download from the commoncrawl portal. Page 4 … One of the main challenges here is the absence of appropriate datasets (bios) in Indic languages on Common Crawl dumps …","url":["https://arxiv.org/pdf/2107.10181"]}
-{"year":"2021","title":"Decentralised Privacy: A Distributed Ledger Approach","authors":["P Papadopoulos, N Pitropakis, WJ Buchanan - … , and Devices; Hussain, CM, Di Sia, P …, 2021"],"snippet":"Our world due to the technological progress became fast-paced and is constantly evolving, thus changing every single day. Consequently, the most valuable asset on earth is not gold or oil anymore but data. Big data companies try to take advantage …","url":["https://link.springer.com/content/pdf/10.1007/978-3-030-58675-1_58-1.pdf"]}
-{"year":"2021","title":"Deciphering Speech: a Zero-Resource Approach to Cross-Lingual Transfer in ASR","authors":["O Klejch, E Wallington, P Bell - arXiv preprint arXiv:2111.06799, 2021"],"snippet":"… To prevent this issue we always used a language model trained on CommonCrawl data when deciphering and later re-decoding the training data. The CommonCrawl language models were trained on approximately 100M tokens and …","url":["https://arxiv.org/pdf/2111.06799"]}
-{"year":"2021","title":"Deduplicating Training Data Makes Language Models Better","authors":["K Lee, D Ippolito, A Nystrom, C Zhang, D Eck… - arXiv preprint arXiv …, 2021"],"snippet":"… models trained on CommonCrawl in- clude GPT-3 (Brown et al., 2020) with the addition of book datasets, GROVER (Zellers et al., 2019) on a restricted subset filtered to news domains called RealNews, and T5 (Raffel et al., 2020) …","url":["https://arxiv.org/pdf/2107.06499"]}
-{"year":"2021","title":"Deep artificial neural networks reveal a distributed cortical network encoding propositional sentence-level meaning","authors":["AJ Anderson, D Kiela, JR Binder, L Fernandino… - Journal of Neuroscience, 2021"],"snippet":"… represents individual words as 300-dimensional floating point vectors derived by factorizing a word co- 286 occurrence matrix (vocabulary size is 2.2 million words and co-occurrences were measured across 840 287 billion tokens …","url":["https://www.jneurosci.org/content/early/2021/03/22/JNEUROSCI.1152-20.2021.abstract"]}
-{"year":"2021","title":"Deep contextualized text representation and learning for fake news detection","authors":["M Samadi, M Mousavian, S Momtazi - Information Processing & Management, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0306457321002077"]}
-{"year":"2021","title":"Deep Learning and Computational Chemistry","authors":["T James, D Hristozov - Artificial Intelligence in Drug Design, 2022"],"snippet":"… For example, ImageNet contains approximately 1.2 million labeled images [99] and Common Crawl, which contributes the bulk of the training data for GPT-3, nearly one trillion words [100]. The initial training phase for AlphaGo likewise utilized a set …","url":["https://link.springer.com/protocol/10.1007/978-1-0716-1787-8_5"]}
-{"year":"2021","title":"Deep Learning for Blocking in Entity Matching: A Design Space Exploration","authors":["H Li, N Tang, M Ouzzani, Y Govind, D Paulsen, G Fung…"],"snippet":"… Popular word-level embeddings such as word2vec [52] and GloVe [67] and characterlevel embeddings such as fastText [9] often come with pre-trained embeddings that are trained on a large generic external corpus such as Wikipedia, Common Crawl or PubMed …","url":["http://da.qcri.org/ntang/pubs/deepblocker.pdf"]}
-{"year":"2021","title":"Deep learning for sentence clustering in essay grading support","authors":["LH Chang, I Rastas, S Pyysalo, F Ginter - arXiv preprint arXiv:2104.11556, 2021"],"snippet":"… [16] and refer readers to this paper for further details of the embeddings. These embedding were induced using the implementation of the skip-gram algorithm [22] in the word2vec software package on Finnish Common Crawl data …","url":["https://arxiv.org/pdf/2104.11556"]}
-{"year":"2021","title":"Deep Learning Transformer Architecture for Named Entity Recognition on Low Resourced Languages: State of the art results","authors":["R Hanslo - arXiv preprint arXiv:2111.00830, 2021"],"snippet":"… model trained on 100 languages uses 2.5 TB of CommonCrawl (CC) data [2]. From the 100 languages used by the XLM-R multilingual masked language model, it is noted that Afrikaans (af) and isiXhosa (xh) are included in the pre-training. …","url":["https://arxiv.org/pdf/2111.00830"]}
-{"year":"2021","title":"Deep Learning With Anaphora Resolution for the Detection of Tweeters With Depression: Algorithm Development and Validation Study","authors":["A Wongkoblap, MA Vadillo, V Curcin - JMIR Mental Health, 2021"],"snippet":"Background: Mental health problems are widely recognized as a major public health challenge worldwide. This concern highlights the need to develop effective tools for detecting mental health disorders in the population. Social …","url":["https://mental.jmir.org/2021/8/e19824/"]}
-{"year":"2021","title":"Deep Learning-based Sentiment Analysis of Facebook Data: The Case of Turkish Users","authors":["Ö Çoban, SA Özel, A İnan - The Computer Journal, 2021"],"snippet":"Abstract. Sentiment analysis (SA) is an essential task for many domains where it is crucial to know users' public opinion about events, products, brands, politi.","url":["https://academic.oup.com/comjnl/advance-article-abstract/doi/10.1093/comjnl/bxaa172/6095851"]}
-{"year":"2021","title":"DeepEva: A Deep Neural Network Architecture for Assessing Sentence Complexity in Italian and English Languages","authors":["GL Bosco, G Pilato, D Schicchi - Array, 2021","GL Boscoa, G Pilato, D Schicchic"],"snippet":"Abstract Automatic Text Complexity Evaluation (ATE) is a research field that aims at creating new methodologies to make autonomous the process of the text complexity evaluation, that is the study of the text-linguistic features (eg, lexical, syntactical …","url":["https://iris.unipa.it/retrieve/handle/10447/524419/1257448/1-s2.0-S2590005621000424-main.pdf","https://www.sciencedirect.com/science/article/pii/S2590005621000424"]}
-{"year":"2021","title":"Delving into Deep Imbalanced Regression","authors":["Y Yang, K Zha, YC Chen, H Wang, D Katabi - arXiv preprint arXiv:2102.09554, 2021"],"snippet":"Page 1. Delving into Deep Imbalanced Regression Yuzhe Yang 1 Kaiwen Zha 1 Ying-Cong Chen 1 Hao Wang 2 Dina Katabi 1 Abstract Real-world data often exhibit imbalanced distributions, where certain target values …","url":["https://arxiv.org/pdf/2102.09554"]}
-{"year":"2021","title":"Democratic Backsliding and Media Responses to Government Repression: Machine Learning Evidence from Tanzania","authors":["FS Adiguzel, D Romero, E Wibbels"],"snippet":"… Using the list of international, regional and national domains, we first check GDELT and the Internet Archive for available links, pull the available web pages from the Common Crawl and from the websites directly. We then initialize Scrapy …","url":["https://mlp.trinity.duke.edu/assets/Tanzania_ML4P.pdf"]}
-{"year":"2021","title":"Dense Events Grounding in Video","authors":["P Bao, Q Zheng, Y Mu - 2021"],"snippet":"… 2015) as previous methods to extract C3D video features on both datasets. And we use Glove (Jeffrey Pennington and Manning 2014) word embeddings pretrained on Common Crawl to represent each word in the sentences …","url":["http://www.muyadong.com/paper/3254_PeijunB.pdf"]}
-{"year":"2021","title":"Depression Detection of Twitter Posters using Deep Learning with Anaphora Resolution","authors":["A Wongkoblap, MNR District"],"snippet":"… occurrent words as vectors [26]. GloVe was trained on several textual datasets eg, Wikipedia and common crawl (a copy of web content), and supported 50, 100, 200, and 300 dimensional vectors. Anaphora resolution is another …","url":["https://kclpure.kcl.ac.uk/portal/files/150024721/Journal_V2_270121_submitted.pdf"]}
-{"year":"2021","title":"DESCGEN: A Distantly Supervised Datasetfor Generating Abstractive Entity Descriptions","authors":["W Shi, M Joshi, L Zettlemoyer - arXiv preprint arXiv:2106.05365, 2021"],"snippet":"… We further parse the HTML texts of the web pages and extract contents as source documents. Real News To expand the collection of source documents, we extract entity mentions in RealNews (Zellers et al., 2019) …","url":["https://arxiv.org/pdf/2106.05365"]}
-{"year":"2021","title":"Design, analysis and implementation of advanced methodologies to measure the socio-economic impact of personal data in large online services","authors":["J González Cabañas - 2021"],"snippet":"The web ecosystem is enormous, and overall it is sustained by an intangible attribute that mainly supports the majority of free services: the exploitation of personal information. Over the years, concerns on how services use personal data …","url":["https://e-archivo.uc3m.es/bitstream/handle/10016/33628/tesis_jose_gonzalez_caba%C3%B1as_2021.pdf?sequence=1"]}
-{"year":"2021","title":"Detecting Anatomical and Functional Connectivity Relations in Biomedical Literature via Language Representation Models","authors":["IB Ozyurt, J Menke, A Bandrowski, M Martone - … of the Second Workshop on Scholarly …, 2021"],"snippet":"… For word embeddings we have used 300 dimensional Common Crawl (840B tokens) trained GloVe (Pennington et al., 2014) vectors. The de- pendency parse trees for the input sentences were generated via Stanford CoreNLP (Manning et al., 2014) package …","url":["https://www.aclweb.org/anthology/2021.sdp-1.4.pdf"]}
-{"year":"2021","title":"Detecting Discrete Emotions in Text Using Neural Networks","authors":["SA Seyeditabari - 2020"],"snippet":"Page 1. DETECTING DISCRETE EMOTIONS IN TEXT USING NEURAL NETWORKS by Seyed Armin Seyeditabari A dissertation submitted to the faculty of The University of North Carolina at Charlotte in partial fulfillment of the …","url":["https://search.proquest.com/openview/474e6c4af557600c03e4c198c711cf47/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"Detecting ethnicity-targeted hate speech in Russian social media texts","authors":["E Pronoza, P Panicheva, O Koltsova, P Rosso - Information Processing & …, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0306457321001606"]}
-{"year":"2021","title":"Detecting formal thought disorder by deep contextualized word representations","authors":["J Sarzynska-Wawer, A Wawer, A Pawlak… - Psychiatry Research, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0165178121004315"]}
-{"year":"2021","title":"Detecting Hate Speech on Social Media Using Deep Learning Techniques","authors":["DO Idris, EO Akinola, S Olalekan"],"snippet":"… A FastText pre-trained model was obtained from Facebook's FastText website which contained 2 million word vectors with 300 dimensions trained with subword information on Common Crawl (consisting of a total of 600 billion tokens) …","url":["http://journals.ui.edu.ng/index.php/uijslictr/article/download/86/68"]}
-{"year":"2021","title":"Detecting Online Risks and Supportive Interaction in Instant Messenger Conversations using Czech Transformers","authors":["O Sotolář, J Plhák, M Tkaczyk, M Lebedíková… - RASLAN 2021 Recent …, 2021"],"snippet":"We present a comparison of state-of-the-art models for text classification of Online Risks and Supportive Interaction in anonymized Instant Messenger conversations held in Czech. We compare the transformer models Czert, RobeCzech, and FERNET-C5 …","url":["https://nlp.fi.muni.cz/raslan/raslan21.pdf#page=27"]}
-{"year":"2021","title":"Detecting Phishing Sites--An Overview","authors":["P Kalaharsha, BM Mehtre - arXiv preprint arXiv:2103.12739, 2021"],"snippet":"… Some of the common sources of datasets are shown below in Table 1. Alexa and Common crawl contains names of the legitimate sites which are likely to be used for phishing [62][63] … 2 Common-Crawl [63] 940 million URLs 2.8 billion webpages …","url":["https://arxiv.org/pdf/2103.12739"]}
-{"year":"2021","title":"Detecting the target of sarcasm is hard: Really??","authors":["P Parameswaran, A Trotman, V Liesaputra, D Eyers - Information Processing & …, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0306457321000972"]}
-{"year":"2021","title":"Detection and Morphological Analysis of Novel Russian Loanwords","authors":["Y Spektor - 2021"],"snippet":"… is compiled. The first dataset is the CC-100 Russian dataset (Conneau et al., 2020, Wenzek et al., 2020), which includes Common Crawl2 data from January 2018 to February 2019. A second … 3. 2 https://commoncrawl.org/ Page 16. 6 …","url":["https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=5665&context=gc_etds"]}
-{"year":"2021","title":"Detection of phishing attacks using probabilistic neural network with a novel training algorithm for reduced Gaussian kernels and optimal smoothing parameter …","authors":["S Priya, S Selvakumar - International Journal of Ad Hoc and Ubiquitous …, 2021"],"snippet":"Page 1. Int. J. Ad Hoc and Ubiquitous Computing, Vol. 36, No. 2, 2021 67 Detection of phishing attacks using probabilistic neural network with a novel training algorithm for reduced Gaussian kernels and optimal …","url":["https://www.inderscienceonline.com/doi/abs/10.1504/IJAHUC.2021.113381"]}
-{"year":"2021","title":"Detection of Phishing Websites from URLs by using Classification Techniques on WEKA","authors":["B Geyik, K Erensoy, E Kocyigit - 2021 6th International Conference on Inventive …, 2021"],"snippet":"… We get the dataset from [21]. In this dataset, legitimate sites are collected from common-crawl and Alexa while phishing sites are collected from Phishtank. After some pre-processing steps 122,055 values 85,220 with …","url":["https://ieeexplore.ieee.org/abstract/document/9358642/"]}
-{"year":"2021","title":"Development and Evaluation of Novel Ophthalmology Domain-Specific Neural Word Embeddings to Predict Visual Prognosis","authors":["S Wang, B Tseng, T Hernandez-Boussard - International Journal of Medical …, 2021"],"snippet":"… entity recognition, sentence classification, relation extraction, and other general natural language processing tasks,[8] and general domain GloVe (Global Vectors for Word Representation), pre-trained on large corpora of general …","url":["https://www.sciencedirect.com/science/article/pii/S1386505621000903"]}
-{"year":"2021","title":"Development of a language model and opinion extraction for text analysis of online platforms","authors":["A Qudar, M Md - 2021"],"snippet":"Page 1. Lakehead University Knowledge Commons,http://knowledgecommons. lakeheadu.ca Electronic Theses and Dissertations Electronic Theses and Dissertations from 2009 2021 Development of a language model and opinion …","url":["https://knowledgecommons.lakeheadu.ca/bitstream/handle/2453/4822/QudarM2021m-1a.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"DFKI SLT at GermEval 2021: Multilingual Pre-training and Data Augmentation for the Classification of Toxicity in Social Media Comments","authors":["R Calizzano, M Ostendorff, G Rehm"],"snippet":"… It was trained on the Common Crawl corpus in 100 languages using masked language modeling. We choose XLM-RoBERTa instead of Multilingual BERT5 because XLM-RoBERTa outperforms Multilingual BERT on a variety of cross-lingual benchmarks …","url":["https://netlibrary.aau.at/obvukloa/periodical/titleinfo/6435231/full.pdf"]}
-{"year":"2021","title":"Dictionary-based Debiasing of Pre-trained Word Embeddings","authors":["M Kaneko, D Bollegala - arXiv preprint arXiv:2101.09525, 2021"],"snippet":"… 3M words learned from Google News corpus (Mikolov et al., 2013a)), GloVe4 (300dimensional embeddings for ca. 2.1M words learned from the Common Crawl (Pennington et al., 2014)), and fastText5 (300-dimensional embeddings for ca …","url":["https://arxiv.org/pdf/2101.09525"]}
-{"year":"2021","title":"Different Keystrokes for Different Folks: Visualizing Crowdworker Querying Behavior","authors":["R Benham, J Mackenzie, JS Culpepper, A Moffat - 2021"],"snippet":"… In this paper, we present the Common Crawl News Query Ex- plorer, 1 which enables information retrieval practitioners to ob- serve and compare human query formulation a posteriori … Common Crawl News Query Explorer …","url":["https://jmmackenzie.io/pdf/bm+21-chiir.pdf"]}
-{"year":"2021","title":"Difficulty-as-improvement: The courage to keep going in the face of life's difficulties","authors":["V Yan, D Oyserman, G Kiper, M Atari - 2021"],"snippet":"… Our computational linguistic analyses of the “Common Crawl” corpus suggest that when people talk about difficulty they also talk about importance, impossibility, and improvement (Study 1). Studies 2-14 (total N = 2,378) use our brief difficulty-as-improvement …","url":["https://psyarxiv.com/f7epj/download?format=pdf"]}
-{"year":"2021","title":"Digital humanities and web archives: Possible new paths for combining datasets","authors":["N Brügger - International Journal of Digital Humanities, 2021"],"snippet":"… Only a limited number of web archives are open to the wider public, most notably the US based Internet Archive, but also the Portuguese, the Croatian, the Australian, and the Icelandic web archives, and open collections such …","url":["https://link.springer.com/article/10.1007/s42803-021-00038-z"]}
-{"year":"2021","title":"Discovering prerequisite relations from educational documents through word embeddings","authors":["F Gasparetti - Future Generation Computer Systems, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0167739X21003290"]}
-{"year":"2021","title":"Discovering Representation Sprachbund For Multilingual Pre-Training","authors":["Y Fan, Y Liang, A Muzio, H Hassan, H Li, M Zhou… - arXiv preprint arXiv …, 2021"],"snippet":"… We use Wikipedia1 corpora (100 languages are included, total size 101GB) and a clean version of Common Crawl (CC)2 (89 languages are included, total size 2500GB) following Liang et al. (2020). 108 languages are included in our multilingual corpora …","url":["https://arxiv.org/pdf/2109.00271"]}
-{"year":"2021","title":"Discovering X Degrees of Keyword Separation in a Fine Arts Collection","authors":["A Flexer"],"snippet":"… Please note that we translate all keywords from German to English for this paper. We use the German fasttext word embedding, which has been trained on about 3 million words from the Wikipediaand 19 million words from …","url":["https://www.researchgate.net/profile/Arthur-Flexer/publication/350721506_Discovering_X_Degrees_of_Keyword_Separation_in_a_Fine_Arts_Collection/links/606e9f15a6fdcc5f778cad52/Discovering-X-Degrees-of-Keyword-Separation-in-a-Fine-Arts-Collection.pdf"]}
-{"year":"2021","title":"Discrete and Soft Prompting for Multilingual Models","authors":["M Zhao, H Schütze - arXiv preprint arXiv:2109.03630, 2021"],"snippet":"… Setup. We conduct all experiments using the pretrained XLM-RoBERTa-base model (Conneau et al., 2020) containing 270M parameters trained on 2.5 TB CommonCrawl data in 100 languages. We use PyTorch (Paszke et al., 2019) and the Hugprompt …","url":["https://arxiv.org/pdf/2109.03630"]}
-{"year":"2021","title":"Discrete Cosine Transform as Universal Sentence Encoder","authors":["N Almarwani, M Diab - arXiv preprint arXiv:2106.00934, 2021"],"snippet":"… Specifically, we used a sample of 1 million parallel sentences from WMT'13 common-crawl data; this subset is the same one used in (Aldarmaki and Diab, 2019).4 To assess efficacy of the DCT models for the cross …","url":["https://arxiv.org/pdf/2106.00934"]}
-{"year":"2021","title":"Discriminative Reranking for Neural Machine Translation","authors":["A Lee, M Auli, MA Ranzato"],"snippet":"… We follow the steps in Ng et al. (2019) for data preprocessing, including sentence deduplication, language identification filtering on all bitext and monolingual data (Joulin et al., 2017) and in- domain filtering (Moore …","url":["https://aclanthology.org/2021.acl-long.563.pdf"]}
-{"year":"2021","title":"Dissociating Semantic and Phonemic Search Strategies in the Phonemic Verbal Fluency Task in early Dementia","authors":["H Lindsay, P Mueller, N Linz, R Zeghari, MM Mina… - Proceedings of the Seventh …, 2021"],"snippet":"… To obtain semantic word embeddings, the pretrained French fastText model is used. This model is trained on Common Crawl and Wikipedia corpora using the continuous bag of words (CBOW) algorithm with a negative sampling loss function …","url":["https://www.aclweb.org/anthology/2021.clpsych-1.4.pdf"]}
-{"year":"2021","title":"DistilBERT-based Argumentation Retrieval for Answering Comparative Questions","authors":["A Alhamzeh, M Bouhaouel, E Egyed-Zsigmond… - Working Notes of CLEF, 2021"],"snippet":"… doi:10.1007/ 978-3-030-22948-1\\_5. [16] J. Bevendorff, B. Stein, M. Hagen, M. Potthast, Elastic ChatNoir: Search Engine for the ClueWeb and the Common Crawl, in: L. Azzopardi, A. Hanbury, G. Pasi, B. Piwowarski (Eds.), Advances in Information Retrieval …","url":["http://ceur-ws.org/Vol-2936/paper-209.pdf"]}
-{"year":"2021","title":"DISTRIBUTIONAL INVESTIGATION OF SOME FREQUENT TURKISH DERIVATIONAL AFFIXES FOR EXPLORING THEIR SEMANTICS","authors":["GN Özdemir - 2021"],"snippet":"Page 1. DISTRIBUTIONAL INVESTIGATION OF SOME FREQUENT TURKISH DERIVATIONAL AFFIXES FOR EXPLORING THEIR SEMANTICS A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF INFORMATICS OF THE …","url":["https://open.metu.edu.tr/bitstream/handle/11511/91631/gizemnur_ozdemir_tez.pdf"]}
-{"year":"2021","title":"Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP","authors":["T Bansal, K Gunasekaran, T Wang, T Munkhdalai… - arXiv preprint arXiv …, 2021"],"snippet":"… This performance drops even further (≈ 10%; r2c4) when the tasks are sampled from a different domain (common crawl) than the training domain … Figure 2 further shows that, for the Cluster tasks, constructing tasks from more diverse domain such …","url":["https://arxiv.org/pdf/2111.01322"]}
-{"year":"2021","title":"DLJUST at SemEval-2021 Task 7: Hahackathon: Linking Humor and Offense","authors":["H Al-Omari, R Duwairi"],"snippet":"… Training the model on larger data set significantly improves the model performance using BookCurpus, English Wikipedia, CC-news with 63 million English news articles, OpenWebText, and Stories; which is a subset of CommonCrawl data …","url":["https://aclanthology.org/2021.semeval-1.155.pdf"]}
-{"year":"2021","title":"Do Images really do the Talking? Analysing the significance of Images in Tamil Troll meme classification","authors":["SU Hegde, A Hande, R Priyadharshini, S Thavareesan… - arXiv preprint arXiv …, 2021"],"snippet":"… To address data imbalance during pretraining, the low-resource data are up- sampled while the high-resourceful data are downsampled to smoothen the data. The model is pretrained from scratch using the Wikipedia2, Common …","url":["https://arxiv.org/pdf/2108.03886"]}
-{"year":"2021","title":"Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing","authors":["RH Maudslay, R Cotterell - Proceedings of the 2021 Conference of the North …, 2021"],"snippet":"Page 1. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 124–131 June 6–11, 2021. ©2021 Association for Computational Linguistics 124 …","url":["https://www.aclweb.org/anthology/2021.naacl-main.11.pdf"]}
-{"year":"2021","title":"DOCmT5: Document-Level Pretraining of Multilingual Language Models","authors":["CH Lee, A Siddhant, V Ratnakar, M Johnson - arXiv preprint arXiv:2112.08709, 2021"],"snippet":"In this paper, we introduce DOCmT5, a multilingual sequence-to-sequence language model pre-trained with large scale parallel documents. While previous approaches have focused on leveraging sentence-level parallel data, we try to build …","url":["https://arxiv.org/pdf/2112.08709"]}
-{"year":"2021","title":"Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus","authors":["J Dodge, M Sap, A Marasovic, W Agnew, G Ilharco…"],"snippet":"… In addition to C4.EN, we host the “uncleaned” version (C4.EN.NOCLEAN), which is the snapshot of Common Crawl identified as … 5https://github.com/ allenai/c4- documentation/discussions 6https://commoncrawl.org/, where …","url":["https://homes.cs.washington.edu/~msap/pdfs/dodge2021documentingC4.pdf"]}
-{"year":"2021","title":"Documenting the English Colossal Clean Crawled Corpus","authors":["J Dodge, M Sap, A Marasovic, W Agnew, G Ilharco… - arXiv preprint arXiv …, 2021"],"snippet":"… been established. In this work we provide the first documentation for the Colossal Clean Crawled Corpus (C4; Raffel et al., 2020), a dataset created by applying a set of filters to a single snapshot of Common Crawl. We begin …","url":["https://arxiv.org/pdf/2104.08758"]}
-{"year":"2021","title":"Does Robustness Improve Fairness? Approaching Fairness with Word Substitution Robustness Methods for Text Classification","authors":["Y Pruksachatkun, S Krishna, J Dhamala, R Gupta… - arXiv preprint arXiv …, 2021"],"snippet":"… We take 97,320 examples from the public leaderboard as the test set. • Bias in Bios (De-Arteaga et al., 2019) 3 is a dataset for occupation classification derived from Common Crawl corpus. It consists of 178,619 train and 91,917 test examples …","url":["https://arxiv.org/pdf/2106.10826"]}
-{"year":"2021","title":"Does semantics aid syntax? An empirical study on named entity recognition and classification","authors":["X Zhong, E Cambria, A Hussain - Neural Computing and Applications, 2021"],"snippet":"Many researchers jointly model multiple linguistic tasks (eg, joint modeling of named entity recognition and named entity classification and joint modeli.","url":["https://link.springer.com/article/10.1007/s00521-021-05949-0"]}
-{"year":"2021","title":"Domain-specific Taxonomy Enrichment based on Meta-Embeddings","authors":["M Tikhomirov, NV Loukachevitch - 2021"],"snippet":"In this paper we study the use of meta-embeddings approaches, which combine several source embeddings, for the taxonomy class prediction of new terms. We test the proposed approach in the informationsecurity domain in the task of enriching the …","url":["http://ceur-ws.org/Vol-3036/paper23.pdf"]}
-{"year":"2021","title":"Don't Stop at the Top: Using Certificate Transparency Logs to Extend Domain Lists for Web Security Studies","authors":["F Marquardt, C Schmidt - 2020 IEEE 45th Conference on Local Computer …, 2020"],"snippet":"… They propose a system that collects massive amounts of records from various data sources, including data from top lists, blacklists, the Common Crawl project and DNS zone files. From these data sources, they were able to extract 199,110,841 unique domain names …","url":["https://ieeexplore.ieee.org/abstract/document/9314793/"]}
-{"year":"2021","title":"DRo: A data-scarce mechanism to revolutionize the performance of DL-based Security Systems","authors":["M Sewak, SK Sahay, H Rathore - 2021 IEEE 46th Conference on Local Computer …, 2021"],"snippet":"… For pre-training a Transformer based TL language models like the OpenAI's GPT-3 [7] or the Google's BERT [5], billions to even trillions of (web) common-crawl documents could be easily and inexpensively made available …","url":["https://ieeexplore.ieee.org/abstract/document/9524929/"]}
-{"year":"2021","title":"DS-TOD: Efficient Domain Specialization for Task Oriented Dialog","authors":["CC Hung, A Lauscher, SP Ponzetto, G Glavaš - arXiv preprint arXiv:2110.08395, 2021"],"snippet":"Recent work has shown that self-supervised dialog-specific pretraining on large conversational datasets yields substantial gains over traditional language modeling (LM) pretraining in downstream task-oriented dialog (TOD). These approaches, however …","url":["https://arxiv.org/pdf/2110.08395"]}
-{"year":"2021","title":"DSGPT: Domain-Specific Generative Pre-Training of Transformers for Text Generation in E-commerce Title and Review Summarization","authors":["X Zhang, Y Jiang, Y Shang, Z Cheng, C Zhang, X Fan… - Proceedings of the 44th …, 2021"],"snippet":"… powerful. Pre-training a language model from a general corpus such as Wikipedia or the Common Crawl requires tremendous time and resource commitment, and can be wasteful if the downstream tasks are limited in variety …","url":["https://dl.acm.org/doi/pdf/10.1145/3404835.3463037"]}
-{"year":"2021","title":"Dual-Objective Fine-Tuning of BERT for Entity Matching","authors":["R Peeters, C Bizer"],"snippet":"… WDC LSPC datasets: We use the training and test sets from the WDC Product Data Corpus for Large-scale Product Matching (WDC LSPC)1 [27] for the evaluation. The datasets were built by ex- tracting product offers from the Common Crawl …","url":["https://www.uni-mannheim.de/media/Einrichtungen/dws/Files_Research/Web-based_Systems/pub/Peeters-Bizer-Dual-Objective-Fine-Tuning-VLDB2021-preprint.pdf"]}
-{"year":"2021","title":"Dual-State Capsule Networks for Text Classification","authors":["P Demotte, S Ranathunga - arXiv preprint arXiv:2109.04762, 2021"],"snippet":"Page 1. Dual-State Capsule Networks for Text Classification Piyumal Demotte, Surangika Ranathunga Department of Computer Science and Engineering, University of Moratuwa Katubedda 10400, Sri Lanka {piyumalanthony.16,surangika}@cse.mrt.ac.lk Abstract …","url":["https://arxiv.org/pdf/2109.04762"]}
-{"year":"2021","title":"DuRecDial 2.0: A Bilingual Parallel Corpus for Conversational Recommendation","authors":["Z Liu, H Wang, ZY Niu, H Wu, W Che - arXiv preprint arXiv:2109.08877, 2021"],"snippet":"Page 1. DuRecDial 2.0: A Bilingual Parallel Corpus for Conversational Recommendation Zeming Liu1∗, Haifeng Wang2, Zheng-Yu Niu2, Hua Wu2, Wanxiang Che1† 1Research Center for Social Computing and Information …","url":["https://arxiv.org/pdf/2109.08877"]}
-{"year":"2021","title":"Dynamic Knowledge Capitalization in Big Data Context: Monte Carlo Tree Search Based Reinforcement Learning","authors":["B Hirchoua, B Ouhbi, B Frikh - The International Conference on Artificial Intelligence …, 2021"],"snippet":"… 1. Fig. 1. Sub-trees examples alongside their local rewards. In order to demonstrate the effectiveness and efficiency of the proposed approach, a Common Crawl big data set is used for evaluation. Texts in this collection …","url":["https://link.springer.com/chapter/10.1007/978-3-030-76346-6_64"]}
-{"year":"2021","title":"Dynamic Tuning and Weighting of Meta-learning for NMT Domain Adaptation","authors":["Z Song, Z Ma, K Qi, G Liu - International Conference on Artificial Neural Networks, 2021"],"snippet":"… 4 Experiments. 4.1 Datasets. Experiments are conducted on English-German parallel datasets. We use 6.4M sentence pairs to get a pre-trained model. The training data are sampled from CommonCrawl, Europarl, NewsCommentary, Wikititles and Rapid2019 …","url":["https://link.springer.com/chapter/10.1007/978-3-030-86383-8_46"]}
-{"year":"2021","title":"Easy-to-use combination of POS and BERT model for domain-specific and misspelled terms","authors":["A Benamar, M Bothua, C Grouin, A Vilnat"],"snippet":"… – Oscar [19] is a set of monolingual corpora extracted from Common Crawl. It was selected using a classification model for each language following the approach of [6] based on FastText [12]. The classifier was previously pretrained on Wikipedia …","url":["http://ceur-ws.org/Vol-3015/paper132.pdf"]}
-{"year":"2021","title":"Echo chambers revisited: The (overwhelming) sharing of in-group politicians, pundits and media on Twitter","authors":["M Wojcieszak, A Casas, X Yu, J Nagler, JA Tucker - 2021"],"snippet":"Page 1. DRAFT Echo chambers revisited: The (overwhelming) sharing of in-group politicians, pundits and media on Twitter Magdalena Wojcieszak a,b , Andreu Casas c , Xudong Yu a , Jonathan Nagler d , and Joshua A. Tucker d …","url":["https://osf.io/xwc79/download?format=pdf"]}
-{"year":"2021","title":"ECKPN: Explicit Class Knowledge Propagation Network for Transductive Few-shot Learning","authors":["C Chen, X Yang, C Xu, X Huang, Z Ma - Proceedings of the IEEE/CVF Conference on …, 2021"],"snippet":"… Specifically, we first leverage the GloVe (pretrained on a large text corpora with self-supervised constraint) [33] to obtain the d1-dimensional semantic embeddings of class labels. The Common Crawl version of the GloVe is …","url":["https://openaccess.thecvf.com/content/CVPR2021/papers/Chen_ECKPN_Explicit_Class_Knowledge_Propagation_Network_for_Transductive_Few-Shot_Learning_CVPR_2021_paper.pdf"]}
-{"year":"2021","title":"EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoising","authors":["H Zhang, M Zhao, C Wei, D Mantini, Z Li, Q Liu - Journal of Neural Engineering, 2021"],"snippet":"Page 1. Journal of Neural Engineering ACCEPTED MANUSCRIPT • OPEN ACCESS EEGdenoiseNet: A benchmark dataset for end-to-end deep learning solutions of EEG denoising To cite this article before publication: Haoming Zhang et al 2021 J. Neural Eng …","url":["https://iopscience.iop.org/article/10.1088/1741-2552/ac2bf8/pdf"]}
-{"year":"2021","title":"Effective Seed-Guided Topic Labeling for Dataless Hierarchical Short Text Classification","authors":["Y Yang, H Wang, J Zhu, W Shi"],"snippet":"… We set the number of iterations to 8 as our model achieves competitive performance since then. For word embeddings, we employ the widely used GloVe Common Crawl6 [21], which contains 840B tokens, 2.2M vocab and 300d vectors …","url":["https://link.springer.com/content/pdf/10.1007/978-3-030-74296-6_21.pdf"]}
-{"year":"2021","title":"Efficiency and Scalability of Large Search Architectures","authors":["M Siedlaczek - 2021"],"snippet":"Page 1. Page 2. 4/21/2021 04/25/2021 Page 3. iii Micro lm or other copies of this dissertation are obtainable from UMI Dissertation Publishing ProQuest CSA 789 E. Eisenhower Parkway PO Box 1346 Ann Arbor, MI 48106-1346 Page 4. iv V ��","url":["https://search.proquest.com/openview/eac3a8ad7dcc3c4ed49f8beb9d39dfce/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"Efficient Large Scale Language Modeling with Mixtures of Experts","authors":["M Artetxe, S Bhosale, N Goyal, T Mihaylov, M Ott… - arXiv preprint arXiv …, 2021"],"snippet":"Mixture of Experts layers (MoEs) enable efficient scaling of language models through conditional computation. This paper presents a detailed empirical study of how autoregressive MoE language models scale in comparison with dense models …","url":["https://arxiv.org/pdf/2112.10684"]}
-{"year":"2021","title":"Efficient Passage Retrieval with Hashing for Open-domain Question Answering","authors":["I Yamada, A Asai, H Hajishirzi - arXiv preprint arXiv:2106.00882, 2021"],"snippet":"… the index of a common knowledge source (eg, Wikipedia) requires dozens of gigabytes.1 A reduction in the index size is critical for real-world QA that requires large knowledge sources such as scientific databases (eg, PubMed) …","url":["https://arxiv.org/pdf/2106.00882"]}
-{"year":"2021","title":"Emerging trends: A gentle introduction to fine-tuning","authors":["KW Church, Z Chen, Y Ma - Natural Language Engineering, 2021"],"snippet":"The previous Emerging Trends article (Church et al., 2021. Natural Language Engineering 27(5), 631–645.) introduced deep nets to poets. Poets is an imperfect metaphor, intended as a gesture toward inclusion. The future for deep nets will …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C31D429D0928351D6A6692F8ECD1E7ED/S1351324921000322a.pdf/emerging_trends_a_gentle_introduction_to_finetuning.pdf"]}
-{"year":"2021","title":"Emotionally informed hate speech detection: a multi-target perspective","authors":["P Chiril, EW Pamungkas, F Benamara, V Moriceau… - Cognitive Computation, 2021"],"snippet":"Hate Speech and harassment are widespread in online communication, due to users' freedom and anonymity and the lack of regulation provided by social me.","url":["https://link.springer.com/article/10.1007/s12559-021-09862-5"]}
-{"year":"2021","title":"Empirical Best Practices On Using Product-Specific Schema. org","authors":["M Kejriwal, RK Selvam, CC Ni, N Torzec - Proceedings of the AAAI Conference on …, 2021"],"snippet":"… Keywords: E-commerce, Schema.org, Best Practices, Web Data Commons, Common Crawl, Markup, Big Data Abstract. Schema.org has experienced high growth in recent years. Structured descriptions of products embedded …","url":["https://ojs.aaai.org/index.php/AAAI/article/view/17816"]}
-{"year":"2021","title":"Empirical Regularization for Synthetic Sentence Pairs in Unsupervised Neural Machine Translation","authors":["X Ai, B Fang - 2021"],"snippet":"Page 1. Empirical Regularization for Synthetic Sentence Pairs in Unsupervised Neural Machine Translation Xi Ai, Bin Fang Chongqing University barid.x.ai@gmail.com, fb@cqu.edu.cn Abstract UNMT tackles …","url":["https://www.aaai.org/AAAI21Papers/AAAI-520.AiXi.pdf"]}
-{"year":"2021","title":"End-to-End Multimodal Clinical Depression Recognition using Deep Neural Networks: A comparative Analysis","authors":["M Muzammel, H Salam, A Othmani - Computer Methods and Programs in …, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0169260721005071"]}
-{"year":"2021","title":"Energy-saving Cross-layer Optimization of Big Data Transfer Based on Historical Log Analysis","authors":["L Rodolph, MD Nine, L Di Tacchio, T Kosar - arXiv preprint arXiv:2104.01192, 2021"],"snippet":"… These include: (1) the small file size dataset consisting of 20,000 HTML files derived from the common crawl project [2]; (2) the medium file size dataset consisting of 5,000 image files derived from Flickr [4]; (3) the large …","url":["https://arxiv.org/pdf/2104.01192"]}
-{"year":"2021","title":"Engineering Knowledge Graph from Patent Database","authors":["L Siddharth, L Blessing, KL Wood, J Luo - arXiv preprint arXiv:2106.06739, 2021"],"snippet":"… pdf Page 25. embedding models that were trained on Google News, Wikipedia, gigaword, and Common Crawl as the original data sources. The entries in Table 2 that mention these models are the resultant semantic networks …","url":["https://arxiv.org/pdf/2106.06739"]}
-{"year":"2021","title":"Engineering Practical Lempel-Ziv Tries","authors":["D Arroyuelo, R Cánovas, J Fischer, D Köppl, M Löbel…"],"snippet":"Page 1. Engineering Practical Lempel-Ziv Tries ∗ Diego Arroyuelo1,2 Rodrigo Cánovas3 Johannes Fischer4 Dominik Köppl5 Marvin Löbel4 Gonzalo Navarro 1,6 Rajeev Raman7 1 Millennium Institute for Foundational Research on Data (IMFD), Chile …","url":["https://users.dcc.uchile.cl/~gnavarro/ps/jea21.pdf"]}
-{"year":"2021","title":"ENHANCED REPRESENTATIONS AND EFFICIENT ANALYSIS OF SYNTACTIC DEPENDENCIES WITHIN AND BEYOND TREE STRUCTURES","authors":["T Shi - 2021"],"snippet":"Page 1. ENHANCED REPRESENTATIONS AND EFFICIENT ANALYSIS OF SYNTACTIC DEPENDENCIES WITHIN AND BEYOND TREE STRUCTURES A Dissertation Presented to the Faculty of the Graduate School of Cornell University …","url":["http://www.cs.cornell.edu/~tianze/papers/thesis.pdf"]}
-{"year":"2021","title":"Enhanced sentiment extraction architecture for social media content analysis using capsule networks","authors":["P Demotte, K Wijegunarathna, D Meedeniya, I Perera - Multimedia Tools and …, 2021"],"snippet":"Recent research has produced efficient algorithms based on deep learning for text-based analytics. Such architectures could be readily applied to text-base.","url":["https://link.springer.com/article/10.1007/s11042-021-11471-1"]}
-{"year":"2021","title":"Enhancing Context Through Contrast","authors":["K Ambilduke, A Shetye, D Bagade, R Bhagwatkar…"],"snippet":"Neural machine translation benefits from semantically rich representations. Considerable progress in learning such representations has been achieved by language modelling and mutual information maximization objectives using …","url":["https://preregister.science/papers_21neurips/18_paper.pdf"]}
-{"year":"2021","title":"Enhancing Cross-lingual Semantic Annotations using Deep Network Sentence Embeddings","authors":["YC Lin, P Hoffmann, E Rahm - 2021"],"snippet":"… RoBERTa. XLM- R uses only MLM as training objective as RoBERTa (ie no TLM) but with multilingual corpus. It is trained on even larger dataset (the CommonCrawl corpus (Wenzek et al., 2019), 2.5 TB) and in 100 languages. XLM …","url":["https://dbs.uni-leipzig.de/file/HEALTHINF21_YCLIN.pdf"]}
-{"year":"2021","title":"Enhancing Viewing Experience of Generated Visual Storylines for Promotional Videos","authors":["C Liu, H Yu, Z Shen, I Dixon, Y Yu, Z Gao, P Wang… - 2021 IEEE International …, 2021"],"snippet":"… ResNet50. Both models are trained on the DeepFashion dataset [21] until convergence2. Word embeddings are obtained from the pre-trained model on the 840B Common Crawl dataset. λi is set to 0.5. α, β, αc and βc are set to 0.4 …","url":["https://ieeexplore.ieee.org/abstract/document/9428292/"]}
-{"year":"2021","title":"Ensembling of Distilled Models from Multi-task Teachers for Constrained Resource Language Pairs","authors":["A Hendy, EA Gad, M Abdelghaffar, JS ElMosalami… - arXiv preprint arXiv …, 2021"],"snippet":"… all the available monolingual data, eg NewsCrawl + CommonCrawl + Extended CommonCrawl for Hausa, and Extended CommonCrawl for both Xhosa and Zulu. For relatively … In addition to the NewsCrawl monolingual subset, we add a …","url":["https://arxiv.org/pdf/2111.13284"]}
-{"year":"2021","title":"Enterprise Data Integration: On Extracting Data from HTML Tables","authors":["JC Roldán Salvador - 2020"],"snippet":"… layer is used. The authors learnt the network using 3 567 tables from 200 web sites, and evaluated the results on 60 678 ta- bles from 300 web sites; the documents were selected from the April 2016 Common Crawl. They also …","url":["https://idus.us.es/bitstream/handle/11441/105486/1/Rold%C3%A1n%20Salvador%2C%20Carlos%20tesis.pdf?sequence=1"]}
-{"year":"2021","title":"ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation","authors":["Y Sun, S Wang, S Feng, S Ding, C Pang, J Shang, J Liu… - arXiv preprint arXiv …, 2021"],"snippet":"… However, these large-scale pre-trained language models with hundreds of billions of parameters are trained on plain texts. For example, the 175-billion-parameter GPT-3 is trained on a corpus with 570GB filtered texts from Common Crawl …","url":["https://arxiv.org/pdf/2107.02137"]}
-{"year":"2021","title":"ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora","authors":["X Ouyang, S Wang, C Pang, Y Sun, H Tian, H Wu… - arXiv preprint arXiv …, 2020"],"snippet":"… XLM-R (Conneau et al., 2019) studies the effects of models when trained on a large scale corpus. It used 2.5T data extracted from Common Crawl (Wenzek et al., 2019) that involves 100 languages for MMLM training. Results …","url":["https://arxiv.org/pdf/2012.15674"]}
-{"year":"2021","title":"Error Analysis of using BART for Multi-Document Summarization: A Study for English and German Language","authors":["T Johner, A Jana, C Biemann"],"snippet":"… For instance, single-document summarization of text in German language was done by Parida and Motlicek (2019) who utilized transformer models for abstractive summarization on two datasets — SwissText 20191 and …","url":["https://www.researchgate.net/profile/Abhik-Jana/publication/351548608_Error_Analysis_of_using_BART_for_Multi-Document_Summarization_A_Study_for_English_and_German_Language/links/609cfb0c299bf1259ed0452e/Error-Analysis-of-using-BART-for-Multi-Document-Summarization-A-Study-for-English-and-German-Language.pdf"]}
-{"year":"2021","title":"Error identification for machine translation with metric embedding and attention","authors":["R Rubino, A Fujita, B Marie - Proceedings of the 2nd Workshop on Evaluation and …, 2021"],"snippet":"Abstract Quality Estimation (QE) for Machine Translation has been shown to reach relatively high accuracy in predicting sentence-level scores, relying on pretrained contextual embeddings and human-produced quality scores. However, the lack of …","url":["https://aclanthology.org/2021.eval4nlp-1.15.pdf"]}
-{"year":"2021","title":"ESPnet-ST IWSLT 2021 Offline Speech Translation System","authors":["H Inaguma, B Yan, S Dalmia, P Gu, J Shi, K Duh… - arXiv preprint arXiv …, 2021"],"snippet":"… Must-C - 0.68M Must-C v2 0.74M ST-TED (cleaned) 0.40M Europarl 1.82M Commoncrawl 2.39M Paracrawl 34.37M NewsCommentary 0.37M WikiTitles 1.38M RAPID 1.63M WikiMatrix 1.57M Table 1: Corpus statistics data was …","url":["https://arxiv.org/pdf/2107.00636"]}
-{"year":"2021","title":"Est-ce que vous compute? Code-switching, cultural identity, and AI","authors":["A Falbo, T LaCroix - arXiv preprint arXiv:2112.08256, 2021"],"snippet":"… of the Common Crawl dataset, resulting in approximately 14 billion tokens (though they do not provide details of how the Common Crawl … is predominantly English: around 45% of HTML pages in the Common Crawl dataset have English as their …","url":["https://arxiv.org/pdf/2112.08256"]}
-{"year":"2021","title":"Establishing Trustworthiness Through Algorithmic Approaches to Qualitative Research","authors":["H Nguyen, J Ahn, A Belgrave, J Lee, L Cawelti, HE Kim… - International Conference on …, 2021","HE Kim, Y Prado, R Santagata, A Villavicencio - … 2020, Malibu, CA, USA, February 1-3 …, 2021"],"snippet":"… The model contains 300 dimensional word vectors that were trained on a vocabulary of 2 million words from web page data (Common Crawl dataset; GloVe, [21]). We then worked to cluster words together using the …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=k90XEAAAQBAJ&oi=fnd&pg=PA47&dq=commoncrawl&ots=6DvGd4cN1o&sig=FHX30JOd7Xl7m8NWbE-QfeuJbks","https://link.springer.com/chapter/10.1007/978-3-030-67788-6_4"]}
-{"year":"2021","title":"Estimating the Effects of Text Genre, Image Resolution and Algorithmic Complexity needed for Sinhala Optical Character Recognition","authors":["I Anuradha, C Liyanage, R Weerasinghe - International Journal on Advances in ICT …, 2021"],"snippet":"… 2) 5million+ sentences in Sinhala common crawler: In 2019, Guzman [16] presented two monolingual corpora for Sinhala. Those were a combination of 155k+ sentences of filtered Sinhala Wikipedia and 5178k+ sentences of Sinhala common crawl …","url":["https://icter.sljol.info/articles/10.4038/icter.v14i3.7231/galley/5596/download/"]}
-{"year":"2021","title":"Estimation of Imageability Ratings of English Words Using Neural Networks","authors":["VV Bochkarev, AV Savinkov, AV Shevlyakova - Mexican International Conference on …, 2021"],"snippet":"… (a set of CommonCrawl vectors). The values of the correlation coefficients obtained in [6] are shown in the last row of the table. We chose the best values from those given in [6] that were obtained also using the fastText vectors trained on the …","url":["https://link.springer.com/chapter/10.1007/978-3-030-89820-5_5"]}
-{"year":"2021","title":"Evaluating and Explaining Natural Language Generation with GenX","authors":["K Duskin, S Sharma, JY Yun, E Saldanha, D Arendt - … on Data Science with Human in …, 2021"],"snippet":"… While we demonstrated utility on datasets with tens of thousands of text examples, the nearest neighbor approach used would become intractable on massive text corpora such as CommonCrawl 7. This limits GenX to …","url":["https://www.aclweb.org/anthology/2021.dash-1.12.pdf"]}
-{"year":"2021","title":"Evaluating Contextualized Language Models for Hungarian","authors":["J Ács, D Lévai, D Nemeskey, A Kornai"],"snippet":"… It was trained on Webcorpus 2.0 (Nemeskey, 2020), 9- billion-token corpus compiled from the Hungarian subset of Common Crawl3. Its string identifier in Huggingface Transformers is … XLMRoBERTa was trained on 2TB of …","url":["https://hlt.bme.hu/media/pdf/huBERT_eval.pdf"]}
-{"year":"2021","title":"Evaluating Document Coherence Modelling","authors":["A Shen, M Mistica, B Salehi, H Li, T Baldwin, J Qi - arXiv preprint arXiv:2103.10133, 2021"],"snippet":"Page 1. arXiv:2103.10133v1 [cs.CL] 18 Mar 2021 Evaluating Document Coherence Modelling Aili Shen ♣ , Meladel Mistica ♣ , Bahar Salehi ♣ , Hang Li ♢ , Timothy Baldwin ♣ , Jianzhong Qi ♣ ♣ The University of Melbourne …","url":["https://arxiv.org/pdf/2103.10133"]}
-{"year":"2021","title":"Evaluating Off-the-Shelf Machine Listening and Natural Language Models for Automated Audio Captioning","authors":["B Weck, X Favory, K Drossos, X Serra - arXiv preprint arXiv:2110.07410, 2021"],"snippet":"… We use the publicly available model trained with subword information on the Common Crawl corpus, which contains 600B tokens and is significantly larger than the corpora used for the Glove and word2vec model [38]. We employ BERT as our …","url":["https://arxiv.org/pdf/2110.07410"]}
-{"year":"2021","title":"Evaluating Sequence-to-Sequence Modelling for Dialogue State Tracking","authors":["M Tuli, S Agrawal"],"snippet":"… 3.2.1 Word embeddings. We use GloVe [21] pretrained word embeddings, as done in [9]. We use the GloVe-840B-300D embeddings: 300-dimensional embeddings trained on 840B tokens from Common Crawl. 3.2.2 Models …","url":["https://www.mathieutuli.com/docs/nmt_for_dst.pdf"]}
-{"year":"2021","title":"Evaluating the Evaluation Metrics for Style Transfer: A Case Study in Multilingual Formality Transfer","authors":["E Briakou, S Agrawal, J Tetreault, M Carpuat - arXiv preprint arXiv:2110.10668, 2021"],"snippet":"While the field of style transfer (ST) has been growing rapidly, it has been hampered by a lack of standardized practices for automatic evaluation. In this paper, we evaluate leading ST automatic metrics on the oft-researched task of formality style …","url":["https://arxiv.org/pdf/2110.10668"]}
-{"year":"2021","title":"Evaluating the Text-to-SQL Capabilities of Large Language Models","authors":["MVAEX TS","N Rajkumar, R Li, D Bahdanau - arXiv preprint arXiv:2204.00498, 2022"],"snippet":"We perform an empirical evaluation of Text-to-SQL capabilities of the Codex language model. We find that, without any finetuning, Codex is a strong baseline on the Spider benchmark; we also analyze the failure modes of Codex in this setting …","url":["https://arxiv.org/pdf/2204.00498","https://openreview.net/pdf?id=lYli-bAuK54"]}
-{"year":"2021","title":"Evaluating the textbugger NLP Attack on","authors":["S Eicher"],"snippet":"… 1 Introduction The ubiquity of deep learning models which learn from their user-base, like social recommenders or CAPTCHA[4], or other relatively unsupervised datasets, like the Common Crawl, in practice has given rise …","url":["http://cs229.stanford.edu/proj2021spr/report2/82526938.pdf"]}
-{"year":"2021","title":"Evaluating Word Embeddings with Categorical Modularity","authors":["S Casacuberta, K Halevy, DE Blasi - arXiv preprint arXiv:2106.00877, 2021"],"snippet":"… these embeddings. FastText. Monolingual embeddings for 157 languages trained on Common Crawl and Wikipedia that use CBOW with position-weights and character n-grams (Bojanowski et al., 2017). MUSE. Cross-lingual …","url":["https://arxiv.org/pdf/2106.00877"]}
-{"year":"2021","title":"Evaluation and Interpretation of Word Embeddings","authors":["J Kuchár"],"snippet":"… 2.3.1 Facebook's Wikipedia and Common Crawl FastText Word Embeddings for 157 languages Produced by Grave et al. [8], the Facebook's Wikipedia and Common Crawl fastText word embeddings may be the most-used and …","url":["https://is.muni.cz/th/eycxc/Evaluation_and_interpretation_of_word_embeddings_Archive.pdf"]}
-{"year":"2021","title":"Evaluation of contextual embeddings on less-resourced languages","authors":["M Ulčar, A Žagar, CS Armendariz, A Repar, S Pollak… - arXiv preprint arXiv …, 2021"],"snippet":"… The ELMoForManyLangs project (EFML) [Che et al., 2018] trained ELMo models for several languages but used relatively small datasets of 20 million words randomly sampled from the raw text released by the CONLL 2017 …","url":["https://arxiv.org/pdf/2107.10614"]}
-{"year":"2021","title":"Evaluation of Neural Network Transformer Models for Named-Entity Recognition on Low-Resourced Languages","authors":["R Hanslo - 2021"],"snippet":"… LANGUAGE MODEL ARCHITECTURE XLM-Roberta (XLM-R) is a transformer-based multilingual masked language model [2]. This language model trained on 100 languages uses 2.5 TB of CommonCrawl (CC) data …","url":["https://annals-csis.org/proceedings/2021/pliks/7.pdf"]}
-{"year":"2021","title":"Evaluation of Sentence Representations in Semantic Text Similarity Tasks","authors":["N Balzar Ekenbäck - 2021"],"snippet":"… 5. Transformer based encoder, using RoBERTa. For the baseline representation, word embeddings trained on common crawl data was used.[30] A few different approaches were used to construct the sentence vector representation …","url":["https://www.diva-portal.org/smash/get/diva2:1535961/FULLTEXT01.pdf"]}
-{"year":"2021","title":"Evaluation of Split-and-Rephrase Output of the Knowledge Extraction Tool in the Intelligent Tutoring System","authors":["A Grubišić, B Žitko, A Gašpar, D Vasić, A Dodaj - Expert Systems with Applications, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0957417421012562"]}
-{"year":"2021","title":"Everything Is All It Takes: A Multipronged Strategy for Zero-Shot Cross-Lingual Information Extraction","authors":["M Yarmohammadi, S Wu, M Marone, H Xu, S Ebner… - arXiv preprint arXiv …, 2021"],"snippet":"… We focus on the coarsest “Abstract” level, where the goal is to identify events and their agents and patients. The documents come from the news-specific portion of Common Crawl … We use the same Common Crawl corpus as XLM-R for pretraining …","url":["https://arxiv.org/pdf/2109.06798"]}
-{"year":"2021","title":"Evolution of diversity and dominance of companies in online activity","authors":["PX McCarthy, X Gong, S Eghbal, DS Falster, MA Rizoiu - Plos one, 2021"],"snippet":"… We compile the linkage record over time of online websites towards domains using Common Crawl (https://commoncrawl.org/). Common Crawl is the largest open index of the web and which has been shown to represent over …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0249993"]}
-{"year":"2021","title":"Evolution of Gaussian Process kernels for machine translation post-editing effort estimation","authors":["I Roman, R Santana, A Mendiburu, JA Lozano - Annals of Mathematics and Artificial …, 2021"],"snippet":"Page 1. Annals of Mathematics and Artificial Intelligence https://doi.org/10.1007/s10472021-09751-5 Evolution of Gaussian Process kernels for machine translation post-editing effort estimation Ibai Roman1 ·Roberto Santana1 ·Alexander Mendiburu1 ·Jose A. Lozano1 …","url":["https://link.springer.com/article/10.1007/s10472-021-09751-5"]}
-{"year":"2021","title":"Examination Committee.","authors":["S Colcher - 2021"],"snippet":"… evaluates the model on a German Wiki data 9 using data extracted from Common Crawl 10 as synthetic summaries … it delivers a good value on aiding the overall performance assessment. 9https://www.swisstext.org/ 10http://commoncrawl.org/ Page 18 …","url":["https://www.maxwell.vrac.puc-rio.br/53550/53550.PDF"]}
-{"year":"2021","title":"Examining Media Bias in the 2020 Democratic Primary","authors":["D Färber - 2021"],"snippet":"Page 1. Examining Media Bias in the 2020 Democratic Primary by Extraction of Entity-Relationships from News Articles Master Thesis submitted by Daniel Färber at University of Konstanz Faculty of Politics, Law and Economics …","url":["https://www.researchgate.net/profile/Daniel-Faerber/publication/354219152_Examining_Media_Bias_in_the_2020_Democratic_Primary_by_Extraction_of_Entity-Relationships_from_News_Articles/links/612cd83f2b40ec7d8bd2405b/Examining-Media-Bias-in-the-2020-Democratic-Primary-by-Extraction-of-Entity-Relationships-from-News-Articles.pdf"]}
-{"year":"2021","title":"Examining the Effects of Preprocessing on the Detection of Offensive Language in German Tweets","authors":["S Reimann, D Dakota"],"snippet":"… dings. We ultimately settled on on the default 300 dimensional fastText German embeddings (Grave et al., 2018), trained on the German CommonCrawl and Wikpedia, as they yielded the most stable performance. We also …","url":["https://konvens2021.phil.hhu.de/wp-content/uploads/2021/09/2021.KONVENS-1.14.pdf"]}
-{"year":"2021","title":"Executive function & semantic memory impairments in Alzheimer's disease—investigating the decline of executive function and semantic memory in Alzheimer's …","authors":["JM Tröger - 2021"],"snippet":"Alzheimer’s Disease (AD) has a huge impact on an ever-aging society in highly developed industrialized countries such as the EU member states: according to the World Alzheimer’s Association the number one risk factor for AD is age. AD patients …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/31994/1/Troeger-Executive_Function_vs._Semantic_Memory_in_AD-v3.4.pdf"]}
-{"year":"2021","title":"Experience and prediction: a metric of hardness for a novel litmus test","authors":["N Isaak, L Michael - Journal of Logic and Computation, 2021"],"snippet":"Abstract. In the past decade, the Winograd schema challenge (WSC) has become a central aspect of the research community as a novel litmus test. Consequently, th.","url":["https://academic.oup.com/logcom/advance-article-abstract/doi/10.1093/logcom/exab005/6129485"]}
-{"year":"2021","title":"Experience Report: Deep Learning-based System Log Analysis for Anomaly Detection","authors":["Z Chen, J Liu, W Gu, Y Su, MR Lyu - arXiv preprint arXiv:2107.05908, 2021"],"snippet":"Page 1. Experience Report: Deep Learning-based System Log Analysis for Anomaly Detection Zhuangbin Chen, Jinyang Liu, Wenwei Gu The Chinese University of Hong Kong Hong Kong, China {zbchen,jyliu,wwgu}@cse.cuhk.edu.hk …","url":["https://arxiv.org/pdf/2107.05908"]}
-{"year":"2021","title":"Experimental Evaluation of Deep Learning models for Marathi Text Classification","authors":["A Kulkarni, M Mandhane, M Likhitkar, G Kshirsagar… - arXiv preprint arXiv …, 2021"],"snippet":"… It was created by processing January-December 2018 Commoncrawl snapshots … OSCAR: Open Super-large Crawled AL- MAnaCH coRpus (OSCAR) is obtained by filtering and language classifying the Common Crawl corpus (Suárezetal., 2019) …","url":["https://arxiv.org/pdf/2101.04899"]}
-{"year":"2021","title":"Experiments with adversarial attacks on text genres","authors":["M Lepekhin, S Sharoff - arXiv preprint arXiv:2107.02246, 2021"],"snippet":"… It has the same architecture, but uses bigger and more genre diverse corpora and an updated pre-training procedure. In addition, XLM-RoBERTa is a multilingual model trained on Common Crawl data in comparison to multilingual BERT only trained on Wikipedia …","url":["https://arxiv.org/pdf/2107.02246"]}
-{"year":"2021","title":"ExpertRank: A Multi-level Coarse-grained Expert-based Listwise Ranking Loss","authors":["Z Chen, C Eickhoff - arXiv preprint arXiv:2107.13752, 2021"],"snippet":"… For KNRM, ConvKNRM and MatchPyramid, GloVe word embeddings with 300 dimensions [25], trained on the Common Crawl dataset2, are used for vocabulary initialization … 1https://www.tensor ow.org/ 2https://commoncrawl …","url":["https://arxiv.org/pdf/2107.13752"]}
-{"year":"2021","title":"Explainable Prediction of Text Complexity: The Missing Preliminaries for Text Simplification","authors":["C Gârbacea, M Guo, S Carton, Q Mei"],"snippet":"… all positions without data corruption. We use the 12 layer XLNeT base pre-trained model on the English Wikipedia, the Books corpus (similar to BERT), Giga5, ClueWeb 2012-B, and Common Crawl. 4.1.2 Evaluation Metric We …","url":["https://aclanthology.org/2021.acl-long.88.pdf"]}
-{"year":"2021","title":"Exploiting Linguistic Information from Nepali Transcripts for Early Detection of Alzheimer's Disease using Natural Language Processing and Machine Learning …","authors":["S Adhikari, S Thapa, U Naseem, P Singh, H Huo… - International Journal of …, 2021"],"snippet":"Alzheimer's disease (AD) is considered as progressing brain disease, which can be slowed down with the early detection and proper treatment by identifying the early symptoms. Language change serves as an early sign that a patient's cognitive …","url":["https://www.sciencedirect.com/science/article/pii/S1071581921001798"]}
-{"year":"2021","title":"Exploiting semantic similarity models to automate transfer credit assessment in academic mobility","authors":["D Chandrasekaran - 2021"],"snippet":"Page 1. Exploiting semantic similarity models to automate transfer credit assessment in academic mobility by Dhivya Chandrasekaran A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science in the …","url":["https://lurepository.lakeheadu.ca/bitstream/handle/2453/4779/ChandrasekaranD2021m-1a.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"Exploring Conditional Text Generation for Aspect-Based Sentiment Analysis","authors":["SUS Chebolu, F Dernoncourt, N Lipka, T Solorio - arXiv preprint arXiv:2110.02334, 2021"],"snippet":"… (2019). The encoder utilizes a denoising goal similar to BERT, while the decoder tries to recreate the original sequence (autoencoder) token by token using the preceding (uncorrupted) tokens and the encoder output. T5 uses common crawl web extracted text …","url":["https://arxiv.org/pdf/2110.02334"]}
-{"year":"2021","title":"Exploring deep learning methods for recognizing rare diseases and their clinical manifestations from texts","authors":["I Segura-Bedmar, D Camino-Perdonas… - arXiv preprint arXiv …, 2021"],"snippet":"… The model contains word embeddings of di- mension 300 for 3 million words. • GloVe [54], a pre-trained word embedding model trained using Common Crawl, an open repository of web crawl data. The model contains …","url":["https://arxiv.org/pdf/2109.00343"]}
-{"year":"2021","title":"Exploring intrinsic information content models for addressing the issues of traditional semantic measures to evaluate verb similarity","authors":["MKS Prasad, P Sharma - Computer Speech & Language, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0885230821000838"]}
-{"year":"2021","title":"Exploring Monolingual Data for Neural Machine Translation with Knowledge Distillation","authors":["AF Aji, K Heafield - arXiv preprint arXiv:2012.15455, 2020"],"snippet":"… Out- of-domain back-translation data (CommonCrawl– mixed, Open Subtitle–conversation) damages the performance, however … Though, CommonCrawl or Opensub1 conversational monolingual data is still better than not us- ing any monolingual data at all …","url":["https://arxiv.org/pdf/2012.15455"]}
-{"year":"2021","title":"Exploring Pre-Trained Transformers and Bilingual Transfer Learning for Arabic Coreference Resolution","authors":["B Min - Proceedings of the Fourth Workshop on Computational …, 2021"],"snippet":"Abstract In this paper, we develop bilingual transfer learning approaches to improve Arabic coreference resolution by leveraging additional English annotation via bilingual or multilingual pre-trained transformers. We show that bilingual transfer …","url":["https://aclanthology.org/2021.crac-1.10.pdf"]}
-{"year":"2021","title":"Exploring the Possibilities of Applying Transfer Learning Methods for Natural Language Processing in Software Development","authors":["W Ding"],"snippet":"Page 1. DEPARTMENT OF INFORMATICS TECHNISCHE UNIVERSITÄT MÜNCHEN Master's Thesis in Informatics: Data Engineering and Analytics Exploring the Possibilities of Applying Transfer Learning Methods for Natural …","url":["https://wwwmatthes.in.tum.de/file/1d56vodcuu5ou/Sebis-Public-Website/-/Master-Thesis-Wei-Ding/Masterthesis_WeiDing.pdf"]}
-{"year":"2021","title":"Exploring the Predictive Power of News and Neural Machine Learning Models for Economic Forecasting","authors":["V Bitetta, I Bordino, A Ferretti, F Gullo, G Ponti… - Mining Data for Financial …"],"snippet":"… rule-based procedure that builds on the linguistic features of the spaCy Python library 5 . The NLP pipeline relies on the en_core_web_lg model of spaCy 6 , an English multi-task Convolutional Neural Network trained on OntoNotes …","url":["https://europepmc.org/article/pmc/pmc7808169"]}
-{"year":"2021","title":"Exploring Transformers in Emotion Recognition: a comparison of BERT, DistillBERT, RoBERTa, XLNet and ELECTRA","authors":["D Cortiz - arXiv preprint arXiv:2104.02041, 2021"],"snippet":"… tokens but in random order. XLNet was trained with over 130 GB of textual data. In addition to BERT's two datasets, they included three more corpora: Giga5, ClueWeb, and Common Crawl. XLNet outperformed BERT on 20 …","url":["https://arxiv.org/pdf/2104.02041"]}
-{"year":"2021","title":"Exploring Unsupervised Pretraining Objectives for Machine Translation","authors":["C Baziotis, I Titov, A Birch, B Haddow - arXiv preprint arXiv:2106.05634, 2021"],"snippet":"… (2019). The (pretraining) monolingual data contain 5M sentences from Common Crawl and Wikipedia per language, while the parallel data are approximately 600K sentences from the Bible, Open Subtitles, GNOME/KDE/Ubuntu, and Paracrawl …","url":["https://arxiv.org/pdf/2106.05634"]}
-{"year":"2021","title":"Exploring Zero-shot Cross-lingual Aspect-based Sentiment Analysis using Pre-trained Multilingual Language Models","authors":["KTK Phan, DN Hao, D Van Thin, NLT Nguyen - 2021 International Conference on …, 2021"],"snippet":"… The mBERT model is trained on the Wikipedia data of 104 languages, while the XLM-R model is trained on the CommonCrawl data in 100 … In detail, the XLM-R model is trained on the combination of Common Crawl with Wikipedia data, while …","url":["https://ieeexplore.ieee.org/abstract/document/9585242/"]}
-{"year":"2021","title":"Exploring Zero-Shot Emotion Recognition in Speech Using Semantic-Embedding Prototypes","authors":["X Xu, J Deng, N Cummins, Z Zhang, L Zhao… - IEEE Transactions on …, 2021"],"snippet":"Page 1. 1520-9210 (c) 2021 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/9449953/"]}
-{"year":"2021","title":"Exposure of occupations to technologies of the fourth industrial revolution","authors":["B Meindl, MR Frank, J Mendonça - arXiv preprint arXiv:2110.13317, 2021"],"snippet":"… The common crawl corpus comprises texts from various sources available on the web, and therefore the embeddings represent various aspects of language. However, the structure and words used in patent data are more technical than standard …","url":["https://arxiv.org/pdf/2110.13317"]}
-{"year":"2021","title":"EXPRESS: Attribute Sentiment Scoring with Online Text Reviews: Accounting for Language Structure and Missing Attributes","authors":["I Chakraborty, M Kim, K Sudhir - Journal of Marketing Research, 2021"],"snippet":"Page 1. Peer Review Version Attribute Sentiment Scoring with Online Text Reviews: Accounting for Language Structure and Missing Attributes Journal: Journal of Marketing Research Manuscript ID JMR.19.0192.R3 Manuscript …","url":["https://journals.sagepub.com/doi/abs/10.1177/00222437211052500"]}
-{"year":"2021","title":"Extending Neural Temporal Tagging Systems with External Knowledge","authors":["M Pömsl"],"snippet":"Page 1. Extending Neural Temporal Tagging Systems with External Knowledge Martin Pömsl Dr. phil. Tobias Thelen Institute of Cognitive Science, Osnabrück M. Sc. Luzian Hahn Fraunhofer Institute for Integrated Circuits, Erlangen Osnabrück University …","url":["https://mpoemsl.github.io/documents/bachelor_thesis_mpoemsl.pdf"]}
-{"year":"2021","title":"Extracting ESG data from business documents","authors":["J Van Der Elst, S Nijssen"],"snippet":"… Common Crawl (Want to use our data? – Common Crawl 2021) for example is an open repository of web crawl data consisting of web page data, metadata extracts and text extracts. It is obtained by scraping web pages and ignoring HTML markup …","url":["https://dial.uclouvain.be/downloader/downloader.php?pid=thesis%3A30732&datastream=PDF_01&cover=cover-mem"]}
-{"year":"2021","title":"Extraction and Analysis of Stories: Natural Language Processing for Software Engineering.","authors":["H Guo - 2021"],"snippet":"Page 1. ABSTRACT GUO, HUI. Extraction and Analysis of Stories: Natural Language Processing for Software Engineering. (Under the direction of Dr. Munindar P. Singh.) Modern software systems are deployed in sociotechnical …","url":["https://repository.lib.ncsu.edu/bitstream/handle/1840.20/38875/etd.pdf?sequence=1"]}
-{"year":"2021","title":"Extremely low-resource neural machine translation for Asian languages","authors":["R Rubino, B Marie, R Dabre, A Fujita, M Utiyama… - Machine Translation, 2021"],"snippet":"This paper presents a set of effective approaches to handle extremely low-resource language pairs for self-attention based neural machine translation (NMT).","url":["https://link.springer.com/article/10.1007/s10590-020-09258-6"]}
-{"year":"2021","title":"Facebook AI WMT21 News Translation Task Submission","authors":["C Tran, S Bhosale, J Cross, P Koehn, S Edunov, A Fan - arXiv preprint arXiv …, 2021"],"snippet":"… For each language, we train an n-gram language model (Heafield, 2011) on all available news-domain data (Newscrawl) and a n-gram language model on a similarly sized sample from general-domain data (Commoncrawl) …","url":["https://arxiv.org/pdf/2108.03265"]}
-{"year":"2021","title":"Fact-Checking of Claims from the English Wikipedia Using Evidence in the Wild","authors":["A Sathe - 2021"],"snippet":"… architectures. These advancements enable taking advantage of vast amounts of unsupervised text data obtained using the internet, via sources such as Wikipedia and Common Crawl. Using these large corpora, researchers have demonstrated …","url":["https://scholarship.richmond.edu/cgi/viewcontent.cgi?article=2562&context=honors-theses"]}
-{"year":"2021","title":"Factorising Meaning and Form for Intent-Preserving Paraphrasing","authors":["T Hosking, M Lapata - arXiv preprint arXiv:2105.15053, 2021"],"snippet":"… English. Although this system was trained on high volumes of data (including Common Crawl), the training data contains relatively few questions, and we would not expect it to perform well in the domain under consideration …","url":["https://arxiv.org/pdf/2105.15053"]}
-{"year":"2021","title":"Fast and Compact Set Intersection through Recursive Universe Partitioning","authors":["GE Pibiri"],"snippet":"… CCNews is a dataset of news freely available from CommonCrawl; precisely, it consists of the news appeared from 09/01/16 to 30/03/18. Identifiers were assigned to documents according to the lexicographic order of their URLs …","url":["http://pages.di.unipi.it/pibiri/papers/DCC21.pdf"]}
-{"year":"2021","title":"Fast Extraction of Word Embedding from Q-contexts","authors":["J Kong, W Li, Z Liu, B Liao, J Qiu, CY Hsieh, Y Cai… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Fast Extraction of Word Embedding from Q-contexts Junsheng Kong ∗† School of Software Engineering, South China University of Technology China sescut_kongjunsheng@mail.scut.edu.cn Weizhao Li ∗† School …","url":["https://arxiv.org/pdf/2109.07084"]}
-{"year":"2021","title":"FAST: A carefully sampled and cognitively motivated dataset for distributional semantic evaluation","authors":["S Evert, G Lapesa"],"snippet":"… Embeddings: word2vec (Mikolov et al., 2013) trained on 100G tokens of Google News data,10 GloVe (Pennington et al., 2014) trained on 6G to- kens of wikipedia + newspapers or 42G tokens of Common Crawl (CC) Web …","url":["https://files.de-1.osf.io/v1/resources/cd8ar/providers/osfstorage/613cdcae079a0a027601be5b?action=download&direct&version=1"]}
-{"year":"2021","title":"Faster Re-translation Using Non-Autoregressive Model For Simultaneous Neural Machine Translation","authors":["H Han, S Indurthi, MA Zaidi, NK Lakumarapu, B Lee… - arXiv preprint arXiv …, 2020"],"snippet":"… We choose the best system based on the MuST-C dev set and report the results on the MuST-C tst-COMMON test set. The WMT19 dataset further consists of Europarl v9, ParaCrawl v3, Common Crawl, News Commentary …","url":["https://arxiv.org/pdf/2012.14681"]}
-{"year":"2021","title":"fastText-based methods for Emotion Identification in Russian Internet Discourse","authors":["A Babii, M Kazyulina, A Malafeev - 13th ACM Web Science Conference 2021, 2021"],"snippet":"… 0.8. The only exception is the model based on the GRU architecture and pre-trained on the Common Crawl. That … 0.81. The lowest performance was shown by the CNN model pre-trained on the Common Crawl embeddings. We …","url":["https://dl.acm.org/doi/abs/10.1145/3447535.3462499"]}
-{"year":"2021","title":"FEEL-IT: Emotion and Sentiment Classification for the Italian Language","authors":["F Bianchi, D Nozza, D Hovy - Proceedings of the Eleventh Workshop on …, 2021"],"snippet":"… In this paper, we use the Italian BERT model UmBERTo trained on Commoncrawl ITA.4 As the first experimental condition, we fine-tune the UmBERTo model for the task of emotion classification with the considered training data (UmBERTo-FT) …","url":["https://www.aclweb.org/anthology/2021.wassa-1.8.pdf"]}
-{"year":"2021","title":"Felix Hamborg, Philipp Meschenmoser, Moritz Schubotz","authors":["P Scharpf, B Gipp - Wahrheit und Fake im postfaktisch-digitalen Zeitalter"],"snippet":"… These filter criteria are passed to news-please, which subsequently searches for relevant news articles in the Common Crawl News … 2 News-please currently accesses the raw archive provided by the Common Crawl project. To speed up the …","url":["https://link.springer.com/content/pdf/10.1007/978-3-658-32957-0.pdf#page=164"]}
-{"year":"2021","title":"Feminist Curation of Text for Data-centric AI","authors":["M Bartl, S Leavy"],"snippet":"Abstract Language models are becoming increasingly central to artificial intelligence through their use in online search, recommendation engines and language generation technologies. However, concepts of gender can be deeply embedded in …","url":["https://datacentricai.org/papers/79_CameraReady_DCAI_Workshop_NeurIPS_2021_final.pdf"]}
-{"year":"2021","title":"Few-shot Learning with Multilingual Language Models","authors":["XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen… - arXiv preprint arXiv …, 2021"],"snippet":"… Our models are trained on a static multilingual corpus extracted from CommonCrawl, with English text comprising 32.6% of the total number … As such we also note the potential difference in genres between CommonCrawl and the genres used in GPT-3 …","url":["https://arxiv.org/pdf/2112.10668"]}
-{"year":"2021","title":"FH-SWF SG at GermEval 2021: Using Transformer-Based Language Models to Identify Toxic, Engaging, & Fact-Claiming Comments","authors":["C Gawron, S Schmidt - arXiv preprint arXiv:2109.02966, 2021"],"snippet":"… Philipp Reissel and Philip May have published both a German ELECTRA model (Reissel and May, 2020) and a “German colossal, cleaned Common Crawl corpus” (GC4) (Reissel and May, 2021) with about 540 GB of German …","url":["https://arxiv.org/pdf/2109.02966"]}
-{"year":"2021","title":"Findings of the WMT 2021 Biomedical Translation Shared Task: Summaries of Animal Experiments as New Test Set","authors":["L Yeganova, D Wiemann, M Neves, F Vezzani, A Siu… - Sixth Conference on …, 2021"],"snippet":"In the sixth edition of the WMT Biomedical Task, we addressed a total of eight language pairs, namely English/German, English/French, English/Spanish, English/Portuguese, English/Chinese, English/Russian, English/Italian, and English/Basque. Further, our …","url":["https://hal.archives-ouvertes.fr/hal-03435096/document"]}
-{"year":"2021","title":"Fine and Coarse Granular Argument Classification before Clustering","authors":["L Dumani, T Wiesenfeldt, R Schenkel - Proceedings of the 30th ACM International …, 2021"],"snippet":"… This dataset consists of eight topics each with 1,000 usergenerated sentences originating from the Common Crawl archive.A key difference to our dataset, besides presumably different appearing frames as well as topics being used as queries, is …","url":["https://dl.acm.org/doi/abs/10.1145/3459637.3482431"]}
-{"year":"2021","title":"Fine-tuning Distributional Semantic Models for Closely-Related Languages","authors":["K Bhatia, D Aggarwal, A Vaidya - Proceedings of the Eighth Workshop on NLP for …, 2021"],"snippet":"… We further compare our fine-tuned models with two pre-trained word embedding models, namely fastText (FT-WC), trained on Common Crawl and Wikipedia (Grave et al., 2018) and IndicFastText (I- FT) (Kakwani et al., 2020) …","url":["https://www.aclweb.org/anthology/2021.vardial-1.7.pdf"]}
-{"year":"2021","title":"FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs","authors":["J Portisch, M Hladik, H Paulheim - arXiv preprint arXiv:2103.01576, 2021"],"snippet":"… DBpedia [10] – but instead on the whole Web: The dataset consists of hypernymy relations extracted from the Common Crawl5, a … 3see https://www.wikidata.org/wiki/Q1881843 4see https://query.wikidata.org …","url":["https://arxiv.org/pdf/2103.01576"]}
-{"year":"2021","title":"Focused Attention Improves Document-Grounded Generation","authors":["S Prabhumoye, K Hashimoto, Y Zhou, AW Black… - arXiv preprint arXiv …, 2021"],"snippet":"… 4.1 Wikipedia Update Generation This task involves generating an update for Wikipedia context given a news article (Prabhumoye et al., 2019). The dataset was collected by parsing Wikipedia articles and Common Crawl for news articles …","url":["https://arxiv.org/pdf/2104.12714"]}
-{"year":"2021","title":"FoodChem: A food-chemical relation extraction model","authors":["G Cenikj, BK Seljak, T Eftimov - arXiv preprint arXiv:2110.02019, 2021"],"snippet":"… Apart from the datasets used for pre-training the original BERT model, 3 additional sources are involved in the pre-training of RoBERTa: the OpenWebText corpus [32], the Stories subset from the Common Crawl dataset [33] and the CommonCrawl News dataset [34] …","url":["https://arxiv.org/pdf/2110.02019"]}
-{"year":"2021","title":"Four dimensions characterize attributions from faces using a representative set of English trait words","authors":["C Lin, U Keles, R Adolphs - Nature Communications, 2021"],"snippet":"People readily (but often inaccurately) attribute traits to others based on faces. While the details of attributions depend on the language available to describe social traits, psychological theories argue that two or three dimensions (such …","url":["https://www.nature.com/articles/s41467-021-25500-y"]}
-{"year":"2021","title":"From Argument Search to Argumentative Dialogue: A Topic-independent Approach to Argument Acquisition for Dialogue Systems","authors":["N Rach, C Schindler, I Feustel, J Daxenberger…"],"snippet":"… query. The engine utilizes a web crawl from the year 2016 based on CommonCrawl 2 to retrieve relevant documents and subsequently classify sentences in the documents as either pro, con or no argument (Stab et al., 2018) …","url":["https://sigdial.org/sites/default/files/workshops/conference22/Proceedings/pdf/2021.sigdial-1.39.pdf"]}
-{"year":"2021","title":"From OpenAPI Fragments to API Pattern Primitives and Design Smells","authors":["S Serbout, C Pautasso, U Zdun, O Zimmermann - 2021"],"snippet":"In the past few years, the OpenAPI Specification (OAS) has emerged as a standard description language for accurately modeling Web APIs. Today, thousands of OpenAPI descriptions can be found by mining open source repositories. In this paper …","url":["http://eprints.cs.univie.ac.at/7145/1/main.pdf"]}
-{"year":"2021","title":"gaBERT--an Irish Language Model","authors":["J Barry, J Wagner, L Cassidy, A Cowap, T Lynn… - arXiv preprint arXiv …, 2021"],"snippet":"… texts, and official documents. OSCAR The unshuffled Irish portion of the OS- CAR Corpus (Ortiz Suárez et al., 2019) which is a collection of documents from CommonCrawl and sorted by language ID. ParaCrawl The Irish portion …","url":["https://arxiv.org/pdf/2107.12930"]}
-{"year":"2021","title":"Gaze-based Multimodal Meaning Recovery for Noisy/Complex Environments","authors":["Ö Alaçam, G Malhotra, E Ruppert, C Biemann - Proceedings of the 2021 International …, 2021"],"snippet":"… In addition, we also utilized xlm-roberta-base masked language model, which is a large multi-lingual language model, trained on 2.5 TB of filtered CommonCrawl data [8]. Unlike multilingual BERT and RoBERTa, XLM-RoBERTa can infer the language of …","url":["https://dl.acm.org/doi/abs/10.1145/3462244.3481002"]}
-{"year":"2021","title":"Gender Bias in English and German Children's Literature: A Computational Analysis Using Word Embeddings","authors":["D Geißler - 2021"],"snippet":"Page 1. Gender Bias in English and German Children's Literature: A Computational Analysis Using Word Embeddings MASTER THESIS Dominique Geißler Master Interaction Technology Faculty of Electrical Engineering, Mathematics …","url":["http://essay.utwente.nl/88570/1/Geissler_MA_EEMCS.pdf"]}
-{"year":"2021","title":"Gender Stereotypes in Natural Language: Word Embeddings Show Robust Consistency Across Child and Adult Language Corpora of More Than 65 Million Words","authors":["TES Charlesworth, V Yang, TC Mann, B Kurdi… - Psychological Science, 2020"],"snippet":"… In this case, lemmatization is particularly helpful because the target corpora are smaller than other natural-language corpora, such as the Common Crawl corpus (which we use for validation as described below) with more than 600 billion word tokens (Mikolov, Grave …","url":["https://journals.sagepub.com/doi/abs/10.1177/0956797620963619"]}
-{"year":"2021","title":"Generalization of cyberbullying traces","authors":["MA Larochelle - 2020"],"snippet":"Page 1. © Marc-André Larochelle, 2020 Generalization of Cyberbullying Traces Mémoire Marc-André Larochelle Maîtrise en informatique - avec mémoire Maître ès sciences (M. Sc.) Québec, Canada Page 2. Generalization of Cyberbullying Traces Mémoire …","url":["https://corpus.ulaval.ca/jspui/bitstream/20.500.11794/67899/1/36823.pdf"]}
-{"year":"2021","title":"Generalized zero-shot object recognition withoutclass-attribute relations","authors":["M Er - 2021"],"snippet":"Page 1. GENERALIZED ZERO-SHOT OBJECT RECOGNITION WITHOUT CLASS-ATTRIBUTE RELATIONS A THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST …","url":["https://open.metu.edu.tr/bitstream/handle/11511/89793/12626239.pdf"]}
-{"year":"2021","title":"Generating Sense Inventories for Ambiguous Arabic Words","authors":["M Alian, A Awajan"],"snippet":"… 4.3. Fasttext Pre-Trained Embeddings Arabic Fasttext embeddings are provided by Grave et al. [12]. These embeddings result from training on Wikipedia and Common Crawl corpus. They use an extension of the Fasttext model with subword information …","url":["https://www.researchgate.net/profile/Marwah-Alian/publication/351762403_Generating_Sense_Inventories_for_Ambiguous_Arabic_Words/links/60b9d6f192851cb13d7442ab/Generating-Sense-Inventories-for-Ambiguous-Arabic-Words.pdf"]}
-{"year":"2021","title":"Generative Adversarial Networks based on Mixed-Attentions for Citation Intent Classification in Scientific Publications","authors":["YS Wang, CY Chen, LH Lee - Proceedings of the 33rd Conference on Computational …, 2021"],"snippet":"Abstract We propose the mixed-attention-based Generative Adversarial Network (named maGAN), and apply it for citation intent classification in scientific publication. We select domain-specific training data, propose a mixed-attention mechanism, and …","url":["https://aclanthology.org/2021.rocling-1.36.pdf"]}
-{"year":"2021","title":"Generative Chatbot Framework for Cybergrooming Prevention","authors":["P Wang - 2021"],"snippet":"Cybergrooming refers to the crime of establishing personal close relationships with potential victims, commonly teens, for the purpose of sexual exploitation or abuse via online social media platforms. Cybergrooming has been recognized as a serious …","url":["https://vtechworks.lib.vt.edu/bitstream/handle/10919/107136/Wang_P_T_2021.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"Generative Question Answering in a Low-Resource Setting","authors":["L Isotalo"],"snippet":"… While the monolingual T5 was pre-trained on the C4 data set which consists of 750GB of English text from Common Crawl, mT5 has been pre-trained on the data likewise collected from Common Crawl but in over 100 languages …","url":["https://dke.maastrichtuniversity.nl/jan.niehues/wp-content/uploads/2021/07/Isotalo-Thesis.pdf"]}
-{"year":"2021","title":"Generic Key Value Extractions from Emails","authors":["R Gupta - International Conference on Big Data Analytics, 2020"],"snippet":"… sentences. Authors of [14] describe a machine learning-based model trained on common-crawl data with multi-task optimizations to represent each keyword phrase using a 500-dimension vector of real numbers. Cosine similarity …","url":["https://link.springer.com/chapter/10.1007/978-3-030-66665-1_13"]}
-{"year":"2021","title":"GenSumm: A Joint Framework for Multi-task Tweet Classification and Summarization using Sentiment Analysis and Generative Modelling","authors":["D Bansal, R Grover, N Saini, S Saha - IEEE Transactions on Affective Computing, 2021"],"snippet":"Social media platforms like Twitter act as a medium for communication among people, government agencies, NGOs, and other relief providing agencies in widespread humanitarian havoc during a disaster outbreak when other …","url":["https://ieeexplore.ieee.org/abstract/document/9629222/"]}
-{"year":"2021","title":"Geoscience Language Processing for Exploration","authors":["H Denli, HA Chughtai, B Hughes, R Gistri, P Xu - Abu Dhabi International Petroleum …, 2021"],"snippet":"Deep learning has recently been providing step-change capabilities, particularly using transformer models, for natural language processing applications such as question answering, query-based summarization, and language translation for …","url":["https://onepetro.org/SPEADIP/proceedings-abstract/21ADIP/3-21ADIP/D031S102R003/474196"]}
-{"year":"2021","title":"GeoVectors: A Linked Open Corpus of OpenStreetMap Embeddings on World Scale","authors":["N Tempelmeier, S Gottschalk, E Demidova - arXiv preprint arXiv:2108.13092, 2021"],"snippet":"… them. Training: Pre-trained word vectors are available at the fastText website6. As most of the OSM keys are in English, we chose the 300dimensional English word vectors trained on the Common Crawl, and Wikipedia [10] …","url":["https://arxiv.org/pdf/2108.13092"]}
-{"year":"2021","title":"German Speech Recognition System using DeepSpeech","authors":["J Xu, K Matta, S Islam, A Nürnberger - … of the 4th International Conference on Natural …, 2020"],"snippet":"… In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 4774–4778. [5] Common crawl 2020. Language model. http://commoncrawl org/. [6] DeepSpeech Deutsch 2020. German dataset of Mozilla Common voice …","url":["https://dl.acm.org/doi/abs/10.1145/3443279.3443313"]}
-{"year":"2021","title":"GFST: Gender-Filtered Self-Training for More Accurate Gender in Translation","authors":["PK Choubey, A Currey, P Mathur, G Dinu…"],"snippet":"Page 1. GFST: Gender-Filtered Self-Training for More Accurate Gender in Translation Prafulla Kumar Choubey∗† Texas A&M University prafulla.choubey@tamu.edu Anna Currey∗, Prashant Mathur, Georgiana Dinu Amazon …","url":["https://assets.amazon.science/db/c9/8f55d40b417ebc2266c4fb81d90f/gfst-gender-filtered-self-training-for-more-accurate-gender-in-translation.pdf"]}
-{"year":"2021","title":"GitTables: A Large-Scale Corpus of Relational Tables","authors":["M Hulsebos, Ç Demiralp, P Groth - 2021","MHS Computing, ÇDS Computing"],"snippet":"… We use the character-level n-gram FastText model pretrained on the Common Crawl corpus. We experimented with contextual models like BERT [13] and the Universal Sentence Encoder [8] , but found that these models yield worse or at best …","url":["https://ar5iv.labs.arxiv.org/pdf/2106.07258.pdf","https://openreview.net/pdf?id=yYQuqGcxFvb"]}
-{"year":"2021","title":"Going Full-TILT Boogie on Document Understanding with Text-Image-Layout Transformer","authors":["R Powalski, Ł Borchmann, D Jurkiewicz, T Dwojak… - arXiv preprint arXiv …, 2021"],"snippet":"… Library ∗ , and PDF files from Common Crawl. Then, a T5-like masked language model pretraining objective is used, but in a salient span masking scheme, ie, named entities are preferred rather than random tokens [47,15] …","url":["https://arxiv.org/pdf/2102.09550"]}
-{"year":"2021","title":"Golos: Russian Dataset for Speech Research","authors":["N Karpov, A Denisenko, F Minkin - arXiv preprint arXiv:2106.10161, 2021"],"snippet":"… language. Additionally, we built a 3-gram language model on the open Common Crawl dataset and merged it with the train set transcriptions. Using … 8. 7https:// commoncrawl.org 8https://github.com/sberdevices/golos Page 5. 8 …","url":["https://arxiv.org/pdf/2106.10161"]}
-{"year":"2021","title":"Governments and the Net: Defense, Control, and Trust in the Fifth Domain","authors":["L Kawerau - 2021"],"snippet":"… The by far largest data source is the Common Crawl archive. Every four weeks, Common Crawl generates a new dataset that contains content and metadata of billions of webpages based on following the links on a large sample of websites …","url":["http://kops.uni-konstanz.de/bitstream/handle/123456789/55972/Kawerau_2-176y1g4fs6pvh0.pdf?sequence=5&isAllowed=y"]}
-{"year":"2021","title":"GPT Perdetry Test: Generating new meanings for new words","authors":["N Malkin, S Lanka, P Goel, S Rao, N Jojic - Proceedings of the 2021 Conference of …, 2021"],"snippet":"… Most of the words were known by none of them. 36 of the 74 words do not appear in the top 2 million words of the Common Crawl corpus, according to the GloVe embedding matrix (Pennington et al., 2014), and the median rank of the other words is 656565 …","url":["https://www.aclweb.org/anthology/2021.naacl-main.439.pdf"]}
-{"year":"2021","title":"GPT3-to-plan: Extracting plans from text using GPT-3","authors":["A Olmo, S Sreedharan, S Kambhampati - arXiv preprint arXiv:2106.07131, 2021"],"snippet":"… 2020) is the latest version of the GPT models developed by OpenAI1. A 175 billion parameter autoregressive language model with 96 layers trained on a 560GB+ web corpora (Common Crawl2 and WebText2 (Gokaslan …","url":["https://arxiv.org/pdf/2106.07131"]}
-{"year":"2021","title":"Grammar Index by Induced Suffix Sorting","authors":["H Bannai, M Takeda - String Processing and Information Retrieval: 28th …","T Akagi, D Köppl, Y Nakashima, S Inenaga, H Bannai… - arXiv preprint arXiv …, 2021"],"snippet":"… Sizes are in megabytes [MB]. Dataset commoncrawl dna einstein. de Input size GCIS-nep GCIS-uni ESP-index FM-index r-index 221. 180 220. 119 138 … com/nicolaprezza/r-index, respectively. To save space, we renamed …","url":["https://arxiv.org/pdf/2105.13744","https://books.google.de/books?hl=en&lr=lang_en&id=gEdFEAAAQBAJ&oi=fnd&pg=PA85&dq=commoncrawl&ots=0CKdrg1l4k&sig=X0BiUyMEx7vsbj3O2GcRTMn6Cms"]}
-{"year":"2021","title":"Graph-based KB and Text Fusion Interaction Network for Open Domain Question Answering","authors":["Y Ding, Y Rao, F Yang - 2021 International Joint Conference on Neural …, 2021"],"snippet":"… C. Implementation Details Through our experiments, the 300-dimension GloVe embedding trained on the Common Crawl corpus is used to initialize the word embedding. The hidden dimension of LSTM and the dimension of entity embedding are both 100 …","url":["https://ieeexplore.ieee.org/abstract/document/9534439/"]}
-{"year":"2021","title":"Grounding Linguistic Commands to Navigable Regions","authors":["N Rufus, K Jain, UKR Nair, V Gandhi, KM Krishna - 2021"],"snippet":"… Input images are resized to 448 × 448 spatial resolution. We use 300d GloVe embeddings pre-trained on Common Crawl 840B tokens [22]. The maximum length of commands is set to T = 40 and for both visual and linguistic features, channel dimension C = 512 …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/inproceedings.pdf.8b947b8b2836d208.49524f5332315f313135365f46492e706466.pdf"]}
-{"year":"2021","title":"H2oloo at TREC 2020: When all you got is a hammer... Deep Learning, Health Misinformation, and Precision Medicine","authors":["R Pradeep, X Ma, X Zhang, H Cui, R Xu, R Nogueira… - Corpus"],"snippet":"… ranking. We adopt all the default settings. We index all the news articles found in the CommonCrawl News crawl from January 1st, 2020 to April 30th, 2020. At inference time, we retrieve the top-k0 (=1000) documents per query …","url":["https://trec.nist.gov/pubs/trec29/papers/h2oloo.DL.HM.PM.pdf"]}
-{"year":"2021","title":"HAHA at EmoEvalEs 2021: Sentiment Analysis in Spanish Tweets with Cross-lingual Model","authors":["K Li - Proceedings of the Iberian Languages Evaluation …, 2021"],"snippet":"… It is a large multi-lingual language model, trained on 2.5TB of filtered Common Crawl data … Because the XLM-RoBERTa model increases the number of languages and the number of training data sets, it uses more …","url":["http://ceur-ws.org/Vol-2943/emoeval_paper5.pdf"]}
-{"year":"2021","title":"Harmonized System Code Classification Using Transfer Learning with Pre-Trained Weights","authors":["K Pain - 2021"],"snippet":"Page 1. HARMONIZED SYSTEM CODE CLASSIFICATION USING TRANSFER LEARNING WITH PRE-TRAINED WEIGHTS by Koustav Pain (Tukai) Submitted in partial fulfillment of the requirements for the degree of Master of Computer Science at …","url":["https://dalspace.library.dal.ca/bitstream/handle/10222/80672/KoustavPain2021.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"Hate Speech Detection based on Sentiment Knowledge Sharing","authors":["X Zhou, Y Yang, X Fan, G Ren, Y Song, Y Diao, L Yang…"],"snippet":"… To compare with previous works, We report results of DV using the standard Accuracy and weighted F1. In our experiments, for the input layer, all word vectors are initialized by Glove Common Crawl Embeddings (840B Token), and the dimension is 300 …","url":["https://aclanthology.org/2021.acl-long.556.pdf"]}
-{"year":"2021","title":"HDRS: Hindi Dialogue Restaurant Search Corpus for Dialogue State Tracking in Task-Oriented Environment","authors":["S Malviya, R Mishra, SK Barnwal, US Tiwary - IEEE/ACM Transactions on Audio …, 2021"],"snippet":"Page 1. 2329-9290 (c) 2021 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/9376978/"]}
-{"year":"2021","title":"HerBERT: Efficiently Pretrained Transformer-based Language Model for Polish","authors":["R Mroczkowski, P Rybak, A Wróblewska, I Gawlik - … of the 8th Workshop on Balto …, 2021"],"snippet":"… CCNet (Wenzek et al., 2020) is a clean monolingual corpus extracted from Common Crawl6 dataset of crawled websites … The first one did not use pretrained embeddings while the latter utilized fastText (Bo- janowski …","url":["https://www.aclweb.org/anthology/2021.bsnlp-1.1.pdf"]}
-{"year":"2021","title":"Hierarchical Ranking for Answer Selection","authors":["H Gao, M Hu, R Cheng, T Gao - arXiv preprint arXiv:2102.00677, 2021"],"snippet":"Page 1. Hierarchical Ranking for Answer Selection Hang Gao, Mengting Hu, Renhong Cheng, Tiegang Gao Nankai University knimet@mail.nankai. edu.cn Abstract Answer selection is a task to choose the positive answers …","url":["https://arxiv.org/pdf/2102.00677"]}
-{"year":"2021","title":"HIGH PERFORMANCE DOCUMENT STORE IMPLEMENTATION IN RUST","authors":["I Aggarwal - 2021"],"snippet":"Databases are a core part of any application which requires persistence of data. The performance of applications involving the use of database systems is directly proportional to how fast their database read-write operations are. The aim of this …","url":["https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=2044&context=etd_projects"]}
-{"year":"2021","title":"HISTOGRAM OF TASK UNCERTAINTY","authors":["QL SCHEDULER, MT LEARNING"],"snippet":"… 2014) word embedding (300d version on 840B Common Crawl data), and Xavier initialization for the parameters. The mini-batch size is set to 16, including samples of the same task. Other than these, we follow the training procedure for (Søgaard …","url":["https://openreview.net/pdf?id=sHUFhv03qX_"]}
-{"year":"2021","title":"HmBlogs: A big general Persian corpus","authors":["HM Khansari, M Shamsfard - arXiv preprint arXiv:2111.02362, 2021"],"snippet":"… The main part of PRT is obtained from the Persian section of the Common Crawl project (Common Crawl, nd). Common Crawl is a web crawl project that crawls and collects resources available on the web in any language, including some in Persian …","url":["https://arxiv.org/pdf/2111.02362"]}
-{"year":"2021","title":"HONEST: Measuring hurtful sentence completion in language models","authors":["D Nozza, F Bianchi, D Hovy - Proceedings of the 2021 Conference of the North …, 2021"],"snippet":"Page 1. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 2398–2406 June 6–11, 2021. ©2021 Association for Computational Linguistics 2398 …","url":["https://www.aclweb.org/anthology/2021.naacl-main.191.pdf"]}
-{"year":"2021","title":"Hope Speech detection in under-resourced Kannada language","authors":["A Hande, R Priyadharshini, A Sampath, KP Thamburaj… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Advances in Computational Intelligence manuscript No. (will be inserted by the editor) Hope Speech detection in under-resourced Kannada language Adeep Hande · Ruba Priyadharshini · Anbukkarasi Sampath · Kingston …","url":["https://arxiv.org/pdf/2108.04616"]}
-{"year":"2021","title":"How do blind people know that blue is cold? Distributional semantics encode color-adjective associations","authors":["J van Paridon, Q Liu, G Lupyan - PsyArXiv. February, 2021"],"snippet":"… trained on. Using the projection method, we computed color associations in embeddings trained on four different text corpora: The Common Crawl and Wikipedia (Grave, Bojanowski, Gupta, Joulin, & Page 2. Mikolov, 2018 …","url":["https://psyarxiv.com/vyxpq/download/?format=pdf"]}
-{"year":"2021","title":"How Do Simple Transformations of Text and Image Features Impact Cosine-Based Semantic Match?","authors":["G Collell, MF Moens - ECIR (1), 2021"],"snippet":"… 1. Word-level features: – GloVe6 [40]: We use 300-d vectors pre-trained on the Common Crawl corpus with 840B tokens and a 2.2M-word vocabulary. – word2vec (w2v) [37]: We use the skip-gram 300-d embeddings trained on Wikipedia …","url":["https://www.researchgate.net/profile/Guillem-Collell/publication/350427435_How_Do_Simple_Transformations_of_Text_and_Image_Features_Impact_Cosine-Based_Semantic_Match/links/60851cdd907dcf667bc0b6a8/How-Do-Simple-Transformations-of-Text-and-Image-Features-Impact-Cosine-Based-Semantic-Match.pdf"]}
-{"year":"2021","title":"How far can we get with one GPU in 100 hours? CoAStaL at MultiIndicMT Shared Task","authors":["R Aralikatte, HRM Bello, M de Lhoneux, D Hershcovich…"],"snippet":"… translation task. It is pre-trained on publicly available corpora from Wikipedia and Common Crawl. It … tion task. This model is pre-trained on mC4, a multilingual version of the Common Crawl consisting of text from 101 languages. It …","url":["https://aclanthology.org/2021.wat-1.24.pdf"]}
-{"year":"2021","title":"How good BERT based models are in sentiment analysis of Croatian tweets: comparison of four multilingual BERTs","authors":["M Ptiček"],"snippet":"… It is pre-trained on texts on 100 different languages and more than two terabytes of data filtered from CommonCrawl data. As stated by the authors “XLM-RoBERTa (XLM-R) outperforms mBERT on cross-lingual classification by up to 23% accuracy on low-resource …","url":["http://archive.ceciis.foi.hr/app/public/conferences/2021/Proceedings/IS/IS1.pdf"]}
-{"year":"2021","title":"How Great is the Great Firewall? Measuring China's DNS Censorship","authors":["NP Hoang, AA Niaki, J Dalek, J Knockel, P Lin… - arXiv preprint arXiv …, 2021"],"snippet":"… nsarchive.gwu.edu, cs.colorado.edu) are censored but their SLDs (eg, mit.edu, gwu.edu, colorado.edu) are not. We complement our test list by including domains from the Citizen Lab test lists (CLTL) [13], the Tranco list [66], and the Common Crawl project [14] …","url":["https://arxiv.org/pdf/2106.02167"]}
-{"year":"2021","title":"How much is a cow like a meow? A novel database of human judgements of","authors":["K Wegner-Clemens, GL Malcolm, S Shomstein - Psychological Science"],"snippet":"… This model was trained on a total of 650 billion words including Wikipedia from June 2017, two news corpuses (statmt.org news, UMBC news), and corpuses derived from a wide range of websites (Gigagword, Common Crawl). The words …","url":["https://psyarxiv.com/7h82c/download/?format=pdf"]}
-{"year":"2021","title":"How to Adapt Your Pretrained Multilingual Model to 1600 Languages","authors":["A Ebrahimi, K Kann - arXiv preprint arXiv:2106.02124, 2021"],"snippet":"… 2018) who present embeddings for 157 languages trained on additional data from Common Crawl … the larger vocabulary of 250k subwords created using SentencePiece tokenization (Kudo and Richardson, 2018) and the …","url":["https://arxiv.org/pdf/2106.02124"]}
-{"year":"2021","title":"How Viable is Password Cracking in Digital Forensic Investigation? Analyzing the Guessability of over 3.9 Billion Real-World Accounts","authors":["A Kanta, S Coray, I Coisel, M Scanlon - Forensic Science International: Digital …, 2021"],"snippet":"… GloVe [34] was used to automate this process with its Common Crawl 42B 300d, a pre-trained model in English for GloVe15 … This is because they do not have a representation in the Common Crawl and therefore cannot be compared to the categories …","url":["https://www.forensicsandsecurity.com/papers/PasswordCracking3BillionAccounts.pdf"]}
-{"year":"2021","title":"How Vulnerable Are Automatic Fake News Detection Methods to Adversarial Attacks?","authors":["C Koenders, J Filla, N Schneider, V Woloszyn - arXiv preprint arXiv:2107.07970, 2021"],"snippet":"Page 1. How Vulnerable Are Automatic Fake News Detection Methods to Adversarial Attacks? Camille Koenders Technische Universität Berlin camille.koenders@gmail.com Johannes Filla Technische Universität Berlin johannesfilla@gmx.de …","url":["https://arxiv.org/pdf/2107.07970"]}
-{"year":"2021","title":"HowSumm: A Multi-Document Summarization Dataset Derived from WikiHow Articles","authors":["O Boni, G Feigenblat, G Lev, M Shmueli-Scheuer… - arXiv preprint arXiv …, 2021"],"snippet":"… a corpus. They es- tablish this approach by extracting answers that are Wikipedia paragraphs from Google Natural Questions (Kwiatkowski et al., 2019) and documents from Common Crawl (Raffel et al., 2020) corpus. In some …","url":["https://arxiv.org/pdf/2110.03179"]}
-{"year":"2021","title":"HTLM: Hyper-Text Pre-Training and Prompting of Language Models","authors":["A Aghajanyan, D Okhonko, M Lewis, M Joshi, H Xu… - arXiv preprint arXiv …, 2021"],"snippet":"… Hyper-text, such as the HTML found in the Common Crawl1, has a number of advantages for pretraining over plain text … Our HyperText Language Model (HTLM) is trained on 23TB of simplified HTML which we automatically extract …","url":["https://arxiv.org/pdf/2107.06955"]}
-{"year":"2021","title":"HULTIG-C: NLP Corpus and Services in the Cloud","authors":["S Pais, J Cordeiro, M Jamil - 2021"],"snippet":"… [11] presented a Multilingual Web Corpus in over 50 languages with over 10 billion tokens licensed under the Creative Commons license. The texts that made up the corpus were extracted from Common Crawl, with around 2 billion crawled URLs ��","url":["https://www.researchsquare.com/article/rs-696114/latest.pdf"]}
-{"year":"2021","title":"HumAID: Human-Annotated Disaster Incidents Data from Twitter","authors":["F Alam, U Qazi, M Imran, F Ofli - arXiv preprint arXiv:2104.03090, 2021"],"snippet":"Page 1. HumAID: Human-Annotated Disaster Incidents Data from Twitter with Deep Learning Benchmarks Firoj Alam, Umair Qazi, Muhammad Imran, Ferda Ofli Qatar Computing Research Institute, HBKU, Qatar {fialam,uqazi,mimran,fofli}@hbku.edu.qa …","url":["https://arxiv.org/pdf/2104.03090"]}
-{"year":"2021","title":"Human and Transformer-Based Prosodic Phrasing in Two Speech Genres","authors":["J Volín, M Řezáčková, J Matouřek - International Conference on Speech and …, 2021"],"snippet":"… We worked with the pre-trained Text-to-Text TransferTransformer (T5) model [18] and used the ability of weights pre-training from a huge amount of unlabeled text in the language [4, 18] – for this task we used Czech …","url":["https://link.springer.com/chapter/10.1007/978-3-030-87802-3_68"]}
-{"year":"2021","title":"Human-Centered Financial Summarization","authors":["T PASSALI - 2021"],"snippet":"Page 1. ARISTOTLE UNIVERSITY OF THESSALONIKI MASTER'S THESIS Human-Centered Financial Summarization Author: Tatiana PASSALI Supervisor: Dr. Grigorios TSOUMAKAS A thesis submitted in fulfillment of …","url":["http://ikee.lib.auth.gr/record/329076/files/GRI-2021-30128.pdf"]}
-{"year":"2021","title":"Hybrid approach to detecting symptoms of depression in social media entries","authors":["A Wołk, K Chlasta, P Holas - arXiv preprint arXiv:2106.10485, 2021"],"snippet":"… 2004). To conduct the experiments, we trained our model on the data from the Common Crawl (Bevendorff et al. 2018) project. As the CommonCrawl corpus is very polluted, an algorithmic division into sentences, data de-duplication, and cleaning was necessary …","url":["https://arxiv.org/pdf/2106.10485"]}
-{"year":"2021","title":"I Wish I Would Have Loved This One, But I Didn't--A Multilingual Dataset for Counterfactual Detection in Product Reviews","authors":["J O'Neill, P Rozenshtein, R Kiryo, M Kubota… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. arXiv:2104.06893v1 [cs.CL] 14 Apr 2021 I Wish I Would Have Loved This One, But I Didn't – A Multilingual Dataset for Counterfactual Detection in Product Reviews James O'Neill‡,∗∗Polina Rozenshtein†,∗ Ryuichi …","url":["https://arxiv.org/pdf/2104.06893"]}
-{"year":"2021","title":"IBM MNLP IE at CASE 2021 task 1: Multi-granular and multilingual event detection on protest news","authors":["P Awasthy, J Ni, K Barker, R Florian - Proceedings of the 4th Workshop on …, 2021"],"snippet":"… Hence we decided to use XLM-R as the text encoder. We use HuggingFace's pytorch im- plementation of transformers (Wolf et al., 2019). XLM-R was pre-trained with unlabeled Wikipedia text and the CommonCrawl Corpus of 100 languages …","url":["https://aclanthology.org/2021.case-1.18.pdf"]}
-{"year":"2021","title":"iCompass at NLP4IF-2021–Fighting the COVID-19 Infodemic","authors":["W Henia, O Rjab, H Haddad, C Fourati - Proceedings of the Fourth Workshop on NLP …, 2021"],"snippet":"… Page 3. 117 3.4 Arabic ALBERT Arabic ALBERT2 by (KUIS-AI-Lab) models were pretrained on 4.4 Billion words: Arabic version of OSCAR (unshuffled version of the corpus) filtered from Common Crawl and Recent dump of Arabic Wikipedia …","url":["https://www.aclweb.org/anthology/2021.nlp4if-1.17.pdf"]}
-{"year":"2021","title":"Identification of Biased Terms in News Articles by Comparison of Outlet-specific Word Embeddings","authors":["T Spinde, L Rudnitckaia, F Hamborg"],"snippet":"… We scraped articles from both news outlets, published in the last decade, from 2010 to 2020, from Common Crawl [4]. For preprocessing, we use Genism simple preprocessing and generate n-grams. 3.4 Linear mapping between vector spaces …","url":["https://www.researchgate.net/profile/Timo_Spinde2/publication/348303058_Identification_of_Biased_Terms_in_News_Articles_by_Comparison_of_Outlet-specific_Word_Embeddings/links/5ff70425a6fdccdcb837e519/Identification-of-Biased-Terms-in-News-Articles-by-Comparison-of-Outlet-specific-Word-Embeddings.pdf"]}
-{"year":"2021","title":"Identification of Toxic, Engaging, and Fact-Claiming Comments","authors":["J Risch, A Stoll, L Wilms, M Wiegand - 2021"],"snippet":"Page 1. Proceedings of the GermEval 2021 Workshop on the Identification of Toxic, Engaging, and Fact-Claiming Comments 17th Conference on Natural Language Processing KONVENS 2021 Heinrich Heine University Düsseldorf …","url":["https://netlibrary.aau.at/obvukloa/content/titleinfo/6435190/full.pdf"]}
-{"year":"2021","title":"Identifying communicative functions in discourse with content types","authors":["T Caselli, R Sprugnoli, G Moretti - Language Resources and Evaluation, 2021"],"snippet":"Texts are not monolithic entities but rather coherent collections of micro illocutionary acts which help to convey a unitary message of content and purpose.","url":["https://link.springer.com/article/10.1007/s10579-021-09554-4"]}
-{"year":"2021","title":"Idiomatic Expression Identification using Semantic Compatibility","authors":["Z Zeng, S Bhat - arXiv preprint arXiv:2110.10064, 2021"],"snippet":"Idiomatic expressions are an integral part of natural language and constantly being added to a language. Owing to their non-compositionality and their ability to take on a figurative or literal meaning depending on the sentential context, they have been a …","url":["https://arxiv.org/pdf/2110.10064"]}
-{"year":"2021","title":"IIITT@ DravidianLangTech-EACL2021: Transfer Learning for Offensive Language Detection in Dravidian Languages","authors":["K Yasaswini, K Puranik, A Hande, R Priyadharshini… - Proceedings of the First …, 2021"],"snippet":"… 4.3 XLM-RoBERTa XLM-RoBERTa (Conneau et al., 2020) is a large multi-lingual language model, trained on 2.5TB of cleaned CommonCrawl data in 100 languages. It can be recognized as a union of XLM (Lample …","url":["https://www.aclweb.org/anthology/2021.dravidianlangtech-1.25.pdf"]}
-{"year":"2021","title":"IIITT@ LT-EDI-EACL2021-Hope Speech Detection: There is always hope in Transformers","authors":["K Puranik, A Hande, R Priyadharshini, S Thavareesan… - arXiv preprint arXiv …, 2021"],"snippet":"… It's trained on over 2TB of filtered CommonCrawl data in 100 different languages. It was an update to the XLM-100 model (Lample and Conneau, 2019) but with in- creased training data … Wikipedia, Common Crawl7, PMINDIA8 and Dakshina9 datasets …","url":["https://arxiv.org/pdf/2104.09066"]}
-{"year":"2021","title":"Image Emotion Recognition Using Visual and Semantic Features Reflecting Emotional and Similar Objects","authors":["T YAMAMOTO, S TAKEUCHI, A NAKAZAWA - IEICE TRANSACTIONS on Information …, 2021"],"snippet":"… GloVe has been used for sentiment analysis [40]; therefore, we use GloVe as the method for obtaining the word vector. It has a 300-dimensional word embedding weight pre-trained by Common Crawl (840 billion tokens), which is publicly available [41] …","url":["https://www.jstage.jst.go.jp/article/transinf/E104.D/10/E104.D_2020EDP7218/_pdf"]}
-{"year":"2021","title":"Impacts of Homophone Normalization on Semantic Models for Amharic","authors":["TD Belay, E Kombolcha, AA Ayele, G Gelaye…"],"snippet":"… embedding representation. The only available pretrained static word embedding for Amharic text is the fastText model, which is trained from Wikipedia and web data scraped in the common crawl project [19]. This embedding …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2021-belayetal-ict4da-amharicnorm.pdf"]}
-{"year":"2021","title":"Implicit social cognition: A brief (and gentle) introduction","authors":["B Kurdi, MR Banaji - PsyArXiv. January, 2021"],"snippet":"… individual-level implicit attitudes toward ten social categories indexed using the IAT are closely aligned with societal-level semantic associations derived from the vast Common Crawl corpus via so- called word embeddings …","url":["https://psyarxiv.com/a4pjy/download/?format=pdf"]}
-{"year":"2021","title":"Implicitly Abusive Comparisons–A New Dataset and Linguistic Analysis","authors":["M Wiegand, M Geulig, J Ruppenhofer - Proceedings of the 16th Conference of the …, 2021"],"snippet":"… A comparison was represented by the embedding vector of the word in that comparison whose similarity was highest to the centroid. As embeddings we chose the fastText emeddings (Joulin et al., 2017) induced on Common Crawl.8 Emotions (EMO) …","url":["https://www.aclweb.org/anthology/2021.eacl-main.27.pdf"]}
-{"year":"2021","title":"Improved Automated Classification of Sentences in Data Science Exercises","authors":["AM Angelone, A Galassi, P Vittorini - … in Methodologies and intelligent Systems for …, 2021"],"snippet":"… In our setting, fastText embeddings are vectors of 300 dimensions, BERT embeddings are vectors of 768 dimensions. As for fastText, we adopted the precomputed Italian language model 1 , trained on Common Crawl and Wikipedia …","url":["https://link.springer.com/chapter/10.1007/978-3-030-86618-1_2"]}
-{"year":"2021","title":"Improved Word Representations Via Summed Target and Context Embeddings","authors":["N Fulda, N Robinson"],"snippet":"… The word2vec and word2vec-PLUS scores here were trained on the corpus of scraped ar- ticles since it resembles the Common Crawl data used to train GloVe [9] more closely than the other, more specialized corpora we explored …","url":["https://dragn.ai/wp-content/uploads/2021/01/sami2021_39_Nancy-Fulda.pdf"]}
-{"year":"2021","title":"Improving Hierarchical Product Classification using Domain-specific Language Modelling","authors":["A Brinkmann, C Bizer - 2021"],"snippet":"… Afterwards, we investigate whether it is possible to improve the performance of the transformer models by performing additional self-supervised pre-training using different corpora of product offers, which were extracted from the Common Crawl …","url":["https://www.uni-mannheim.de/media/Einrichtungen/dws/Files_Research/Web-based_Systems/pub/Brinkmann-Bizer-Improving_Hierarchical_Product_Classification_using_domain_specific_laguage_modelling-PKG4Ecommerce2021.pdf"]}
-{"year":"2021","title":"Improving Large-scale Language Models and Resources for Filipino","authors":["JCB Cruz, C Cheng - arXiv preprint arXiv:2111.06053, 2021"],"snippet":"… 2019) is a massive dataset obtained from language identification and filtering of the Common Crawl dataset. We use the deduplicated version of the Filipino (Tagalog) portion of OSCAR and add it to our pretraining corpus. …","url":["https://arxiv.org/pdf/2111.06053"]}
-{"year":"2021","title":"Improving Multilingual Models for the Swedish Language: Exploring CrossLingual Transferability and Stereotypical Biases","authors":["S Katsarou - 2021"],"snippet":"… To acquire the natural text needed for pretraining purposes, the authors used common crawl [21]. Common crawl is a non commercial … To justify the choice of Common Crawl the authors say that it is a publicly available repository, allowing any …","url":["https://www.diva-portal.org/smash/get/diva2:1618310/FULLTEXT01.pdf"]}
-{"year":"2021","title":"Improving question answering for event-focused questions in temporal collections of news articles","authors":["J Wang, A Jatowt, M Färber, M Yoshikawa - Information Retrieval Journal"],"snippet":"Temporal collections of news articles (or news archives) contain numerous accurate and time-aligned articles, which offer immense value to our society, hel.","url":["https://link.springer.com/article/10.1007/s10791-020-09387-9"]}
-{"year":"2021","title":"Improving Sentiment Classification for Arabic Short Text Using Deep Learning Approaches","authors":["A Alwehaibi - 2021"],"snippet":"Page 1. Improving Sentiment Classification for Arabic Short Text Using Deep Learning Approaches Ali Alwehaibi North Carolina A&T State University A dissertation submitted to the graduate faculty in partial fulfillment of the requirements for the degree of …","url":["https://search.proquest.com/openview/615ff8051266a66aec4a923d0faafa78/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"Improving the Lexical Ability of Pretrained Language Models for Unsupervised Neural Machine Translation","authors":["A Chronopoulou, D Stojanovski, A Fraser - arXiv preprint arXiv:2103.10531, 2021"],"snippet":"… We use 3K randomly sampled sentences of SETIMES (Tiedemann, 2012) as validation/test sets. We also use 68M En sentences from NewsCrawl. For Sq and Mk we use all the CommonCrawl corpora from Ortiz Suárez et …","url":["https://arxiv.org/pdf/2103.10531"]}
-{"year":"2021","title":"in the Language Technology (LT) group","authors":["T Fischer, C Biemann, SM Yimam"],"snippet":"… The model is trained on the colossal and cleaned version of common crawl (C4) as well as HugeNews which consists of 1.5B news articles from the web. Unsurprisingly, this method achieves state-of-the-art results on many summarization datasets …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2021-ma-timfischer.pdf"]}
-{"year":"2021","title":"indicnlp@ kgp at DravidianLangTech-EACL2021: Offensive Language Identification in Dravidian Languages","authors":["K Kedia, A Nandy - arXiv preprint arXiv:2102.07150, 2021"],"snippet":"… use the bert-base-multilingual-cased model, mBERT trained on cased text in 104 languages from large Wikipedia articles, and the xlm-roberta-base model, XLM-R (Conneau et al., 2020) trained on 100 languages, using …","url":["https://arxiv.org/pdf/2102.07150"]}
-{"year":"2021","title":"IndoNLG: Benchmark and Resources for Evaluating Indonesian Natural Language Generation","authors":["S Cahyawijaya, GI Winata, B Wilie, K Vincentio, X Li… - arXiv preprint arXiv …, 2021"],"snippet":"… Wiki Javanese1 6,015,961 231,571 53.2 MB formal Wikipedia CC-100 Sundanese 13,761,754 433,086 107.6 MB mixed Common Crawl CC-100 Javanese 20,560,458 690,517 161.9 MB mixed Common Crawl TOTAL 3,626,283,931 276,838,931 23.79 GB …","url":["https://arxiv.org/pdf/2104.08200"]}
-{"year":"2021","title":"Information Extraction from Semi-Structured Websites","authors":["C Lockard - 2021"],"snippet":"… Note the log scale of the x-axis. . . . . 42 3.4 Extraction precision vs. number of extractions on the CommonCrawl dataset at various confidence thresholds; the orange bar indicates a 0.75 threshold yielding 1.25millionextractionsat90%precision. . . . . 47 …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/47422/Lockard_washington_0250E_22994.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"Information Retrieval Model for Social Media Applications","authors":["S Bhandari - 2021"],"snippet":"… 2019 IEEE International Conference on Healthcare Informatics (ICHI), pp. 1–3, 2019. [17] S. Nagel, “Cc-news.” https://commoncrawl.org/2016/10/news-datasetavailable/, 2016. [18] M. Heidari and JH Jones, “Using bert to extract …","url":["http://129.174.21.13/bitstream/handle/1920/11956/bhandari_social-media-ml.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"Information retrieval versus deep learning approaches for generating traceability links in bilingual projects","authors":["J Lin, Y Liu, J Cleland-Huang - Empirical Software Engineering, 2022"],"snippet":"Abstract Software traceability links are established between diverse artifacts of the software development process in order to support tasks such as compliance analysis, safety assurance, and requirements validation. However, practice has shown that it …","url":["https://link.springer.com/article/10.1007/s10664-021-10050-0"]}
-{"year":"2021","title":"INFOTEC-LaBD at PAN@ CLEF21: Profiling Hate Speech Spreaders on Twitter through Emotion-based Representations","authors":["H Cabrera, S Miranda-Jiménez, ES Tellez - CLEF, 2021"],"snippet":"… 26] for mapping Tweets to semantic space. In particular, we use the model pre-trained on 600 billion tokens on Common Crawl for the English task and the one from [27] to tackle the Spanish task. We use the NRC Lexicon [12 …","url":["http://ceur-ws.org/Vol-2936/paper-159.pdf"]}
-{"year":"2021","title":"Infusing Future Information into Monotonic Attention Through Language Models","authors":["MA Zaidi, S Indurthi, B Lee, NK Lakumarapu, S Kim - arXiv preprint arXiv:2109.03121, 2021"],"snippet":"Page 1. Infusing Future Information into Monotonic Attention Through Language Models Mohd Abbas Zaidi∗, Sathish Indurthi∗†, Beomseok Lee Nikhil Kumar Lakumarapu, Sangha Kim NLP Lab, Samsung Research, Seoul, South …","url":["https://arxiv.org/pdf/2109.03121"]}
-{"year":"2021","title":"Input Augmentation Improves Constrained Beam Search for Neural Machine Translation: NTT at WAT 2021","authors":["K Chousa, M Morishita - arXiv preprint arXiv:2106.05450, 2021"],"snippet":"… We also used CommonCrawl provided by the WMT 2020 news shared task (Barrault et al., 2020) as additional monolingual data. For CommonCrawl data, we chose the ten million English and Japanese sentences that are similar …","url":["https://arxiv.org/pdf/2106.05450"]}
-{"year":"2021","title":"Integrated Training for Sequence-to-Sequence Models Using Non-Autoregressive Transformer","authors":["E Tokarchuk, J Rosendahl, W Wang, P Petrushkov…"],"snippet":"… Figure 2: Different variants of the encoder-decoder model integration through the connection interface. 5.1 Data Training data for French→German includes Eu- roparl corpus version 7 (Koehn, 2005), CommonCrawl2 corpus and the newstest2008-2010 …","url":["https://www-i6.informatik.rwth-aachen.de/publications/download/1194/TokarchukEvgeniiaRosendahlJanWangWeiyuePetrushkovPavelLancewickiTomerKhadiviShahramNeyHermann--IntegratedTrainingforSequence-to-SequenceModelsUsingNon-AutoregressiveTransformer--2021.pdf"]}
-{"year":"2021","title":"Intelligent Arabic-Based Healthcare Assistant","authors":["T Wael, A Hesham, M Youssef, O Adel, H Hesham… - 2021 3rd Novel Intelligent …, 2021"],"snippet":"… It was pre-trained on ∼8.2 billion words from the Arabic version of OSCAR (unshuffled version of the corpus) - filtered from Common Crawl [6], the recent dump of Arabic Wikipedia, and other Arabic resources, which sum up to ∼95GB of text. The corpus …","url":["https://ieeexplore.ieee.org/abstract/document/9600526/"]}
-{"year":"2021","title":"Intelligent Document Validation","authors":["E de Souza Pais - 2021"],"snippet":"Abstract Processes in organizations over the past few years have been increasingly automated. In order to make them more efficient and practical. However, one area in which manual work is still common is document analysis. In this area, due to the …","url":["https://estudogeral.uc.pt/retrieve/217107/Eduardo%20de%20Sousa%20Pais.pdf"]}
-{"year":"2021","title":"Intelligent Methods for Accurately Detecting Phishing Websites","authors":["M Al-kasassbeh, ABUZ AL MAHA"],"snippet":"… A. Data set The data set used in this paper is offered by [19] is composed of 5000 phishing websites and 5000 legitimate websites. Phishing websites are collected from PhishTank and OpenPhish, while legitimate websites are collected from Alexa and Common Crawl …","url":["https://www.academia.edu/download/65538093/200207223.pdf"]}
-{"year":"2021","title":"Interactive Clustering of Cooking Recipe Instructions: Towards the Automatic Detection of Events Involving Kitchen Devices","authors":["F Ventirozos, M Jacobo-Romero, S Clinch… - 2021 IEEE 15th …, 2021"],"snippet":"… Based on these synonym sets, we enriched our list by adding similar words based on GloVe word embedding vectors [17], which were pre-trained on the Common Crawl corpus1 … 1https://commoncrawl.org/ 342 Page 3. Figure …","url":["https://ieeexplore.ieee.org/abstract/document/9364446/"]}
-{"year":"2021","title":"Interactive query expansion for professional search applications","authors":["T Russell-Rose, P Gooch, U Kruschwitz - arXiv preprint arXiv:2106.13528, 2021"],"snippet":"… The DBpedia data set describes 4.58 million entities, out of which 4.22 million are classified in a consistent ontology. 2. WebISA (Seitner et al., 2016) is a publicly available database containing hypernymy relations extracted from the CommonCrawl web corpus …","url":["https://arxiv.org/pdf/2106.13528"]}
-{"year":"2021","title":"Internet-Augmented Dialogue Generation","authors":["M Komeili, K Shuster, J Weston - arXiv preprint arXiv:2107.07566, 2021"],"snippet":"… First, we store and utilize the Common Crawl dump of the internet from Wenzek et al … DPR+FAISS-based models We trained DPR+FAISS-based models using either the WoW or WizInt training datasets, and using either …","url":["https://arxiv.org/pdf/2107.07566"]}
-{"year":"2021","title":"Interpretability in Word Sense Disambiguation using Tsetlin Machine","authors":["RK Yadav, L Jiao, OC Granmo, M Goodwin - 2021"],"snippet":"… FastText-Base (FTX- B), FastText-CommonCrawl (FTX-C), 1 neural network (NN) BERT base, and our proposed TM. FTX- B is a fast text linear classifier without pre-trained embeddings and FTX-C is a fast text linear classifier with …","url":["https://www.scitepress.org/Papers/2021/103821/103821.pdf"]}
-{"year":"2021","title":"Interpretable bias mitigation for textual data: Reducing gender bias in patient notes while maintaining classification performance","authors":["JR Minot, N Cheney, M Maier, DC Elbers, CM Danforth… - arXiv preprint arXiv …, 2021"],"snippet":"… and resulting word embeddings. For instance, general purpose language models are often trained on Wikipedia and the Common Crawl collection of web pages (eg, BERT [27], RoBERTa [28]). Training language models on …","url":["https://arxiv.org/pdf/2103.05841"]}
-{"year":"2021","title":"Interpreting and Controlling Linguistic Features in Neural Networks' Representations","authors":["T Limisiewicz"],"snippet":"Abstract In recent years, Neural Networks proved their usefulness in computing and processing vector representations to solve various NLP tasks. The key objective of the thesis is to provide a better explanation of the neural network’s representation of …","url":["https://ufal.mff.cuni.cz/~zabokrtsky/pgs/thesis_proposal/tomasz-limisiewicz-proposal.pdf"]}
-{"year":"2021","title":"Introducing A large Tunisian Arabizi Dialectal Dataset for Sentiment Analysis","authors":["C Fourati, H Haddad, A Messaoudi, M BenHajhmida… - Proceedings of the Sixth …, 2021"],"snippet":"… In this pa- per, we introduce a large common-crawl-based Tunisian Arabizi dialectal dataset dedicated for Sentiment Analysis … Hence, our contributions can be summarized as: the first re- lease of a Tunizi large-scale Common-Crawl-based Page 3. 228 …","url":["https://www.aclweb.org/anthology/2021.wanlp-1.25.pdf"]}
-{"year":"2021","title":"Introducing huBERT","authors":["ND Márk"],"snippet":"… Abstract This paper introduces the huBERT family of models. The flagship is the eponymous BERT Base model trained on the new Hungarian Webcorpus 2.0, a 9-billion-token corpus of Web text collected from the Common Crawl …","url":["https://hlt.bme.hu/media/pdf/huBERT.pdf"]}
-{"year":"2021","title":"Introduction: digital humanities and the use of web archives","authors":["K Teszelszky - 2021"],"snippet":"… Also, an ever-increasing amount of data is selected, archived, and presented worldwide in web collections by organizations like the Internet Archive, Common Crawl, national libraries, and other academic research and digital heritage …","url":["https://link.springer.com/article/10.1007/s42803-021-00040-5"]}
-{"year":"2021","title":"Investigating Depression Semantics on Reddit","authors":["S Agarwal, P Singh, J Shah, N Sanjeev - International Conference on Neural …, 2021"],"snippet":"Major depression is a challenging issue affecting individuals and those of the people around them. This paper investigates the Reddit comments for the automated identification of comments being indicative of depressive behaviour. We …","url":["https://link.springer.com/chapter/10.1007/978-3-030-92310-5_75"]}
-{"year":"2021","title":"Investigating Hostile Post Detection in Hindi","authors":["V Bhatnagar, P Kumar, P Bhattacharyya - Neurocomputing, 2021"],"snippet":"… Wiki + CC : Pretrained Embeddings trained on Wikipedia and Common Crawl Wiki : Pretrained Embeddings trained on Wikipedia TEAP : … Wikipedia pretrained word vectors 25 and Wikipedia + Common Crawl pretrained word vectors 26 for …","url":["https://www.sciencedirect.com/science/article/pii/S0925231221018099"]}
-{"year":"2021","title":"Investigating Monolingual and Multilingual BERTModels for Vietnamese Aspect Category Detection","authors":["D Van Thin, LS Le, VX Hoang, NLT Nguyen - arXiv preprint arXiv:2103.09519, 2021"],"snippet":"… Besides, there are many variants of BERT models which are published for Vietnamese language and multi-lingual model as cross-lingual language model (XLM-R) [10] or multilingual BERT [9]. These models are pre-trained …","url":["https://arxiv.org/pdf/2103.09519"]}
-{"year":"2021","title":"Investigation of different decoding algorithms for the automatic generation of alternative language patterns in German to English translation","authors":["M Zanon"],"snippet":"… Crawled Corpus (C4) to pretrain the model on. They base this data set on the text data from April 2019 of the Common Crawl archive, which provides web extracted text by scraping about 20TB of text from HTML files each month …","url":["https://users.informatik.haw-hamburg.de/~schumann/BachelorArbeitMelinaZanon.pdf"]}
-{"year":"2021","title":"Is Domain Adaptation Worth Your Investment? Comparing BERT and FinBERT on Financial Tasks","authors":["B Peng, E Chersoni, YY Hsu, CR Huang - Proceedings of the Third Workshop on …, 2021"],"snippet":"… The first-generation Transformers were mainly trained on general corpora, such as Wikipedia or Common Crawl. However, considering domain adaptations, many researchers have later injected domain-specific knowledge in such architectures …","url":["https://aclanthology.org/2021.econlp-1.5.pdf"]}
-{"year":"2021","title":"Is the Number of Trainable Parameters All That Actually Matters?","authors":["A Chatelain, A Djeghri, D Hesslow, J Launay, I Poli - arXiv preprint arXiv:2109.11928, 2021"],"snippet":"… Architecture details for the four model sizes considered are available in the supplementary. The model is trained on French data obtained using a Common Crawl dump filtered by CCNet [23]. We use byte-level byte-pair encoding, with a vocabulary of 50,262 tokens …","url":["https://arxiv.org/pdf/2109.11928"]}
-{"year":"2021","title":"isiZulu Word Embeddings","authors":["S Dlamini, E Jembere, A Pillay, B van Niekerk - 2021 Conference on Information …, 2021"],"snippet":"… TABLE 1: THE MODELS TO BE COMPARED ALONG WITH DETAILS OF THE CORPORA THEY WERE TRAINED ON. Model Corpus Corpus Size Vocabulary Word2Vec Google News 6 billion 1 million GloVe Common …","url":["https://ieeexplore.ieee.org/abstract/document/9395011/"]}
-{"year":"2021","title":"JABER: Junior Arabic BERt","authors":["A Ghaddar, Y Wu, A Rashid, K Bibi, M Rezagholizadeh… - arXiv preprint arXiv …, 2021"],"snippet":"… 2020) is a 12 layer BERT model trained on 95GB of common crawl, news, and Wikipedia Arabic data. AraBERT (Antoun et al.… • Common Crawl (CC) This data was downloaded from 10 shards of monthly Common Crawl 3 covering March to …","url":["https://arxiv.org/pdf/2112.04329"]}
-{"year":"2021","title":"Jigsaw: Large Language Models meet Program Synthesis","authors":["N Jain, S Vaidyanath, A Iyer, N Natarajan… - arXiv preprint arXiv …, 2021"],"snippet":"Large pre-trained language models such as GPT-3, Codex, and Google's language model are now capable of generating code from natural language specifications of programmer intent. We view these developments with a mixture of optimism and …","url":["https://arxiv.org/pdf/2112.02969"]}
-{"year":"2021","title":"JMIR Mental Health","authors":["A Wongkoblap, M Vadillo, V Curcin, C Rauschenberg… - Mental Health"],"snippet":"… occurrent words as vectors [25]. GloVe was trained on several textual data sets, such as Wikipedia and common crawl (a copy of web content), and supported 50D, 100D, 200D, and 300D vectors. Anaphora resolution is another …","url":["https://mental.jmir.org/2021/8/PDF"]}
-{"year":"2021","title":"Joint Open Knowledge Base Canonicalization and Linking","authors":["Y Liu, W Shen, Y Wang, J Wang, Z Yang, X Yuan - Proceedings of the 2021 …, 2021"],"snippet":"… 1 − Simemb (si,sj ) if xij = 0 For instance, the score ofSimemb (“Barack Obama”, “President Obama”) is 0.873 using fastText [17] embeddings trained on Common Crawl via MindSpore Framework1, which indicates these two NPs are likely to refer to the same entity …","url":["https://dl.acm.org/doi/abs/10.1145/3448016.3452776"]}
-{"year":"2021","title":"Joint source–target encoding with pervasive attention","authors":["M Elbayad, L Besacier, J Verbeek - Machine Translation, 2021"],"snippet":"The pervasive attention model is a sequence-to-sequence model that addresses the issue of source–target interaction in encoder–decoder models by jointly encoding the two sequences with a two-dimensional convolutional neural network. We …","url":["https://link.springer.com/article/10.1007/s10590-021-09289-7"]}
-{"year":"2021","title":"Juris2vec: Building Word Embeddings from Philippine Jurisprudence","authors":["E Peramo, C Cheng, M Cordel - … International Conference on Artificial Intelligence in …, 2021"],"snippet":"… utilized a 2010 Wikipedia dump with 1 billion tokens; a 2014 Wikipedia dump with 1.6 billion tokens; Gigaword 5 which has 4.3 billion tokens; the combination Gigaword5 + Wikipedia2014, which has 6 billion tokens; and …","url":["https://ieeexplore.ieee.org/abstract/document/9415251/"]}
-{"year":"2021","title":"Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts","authors":["A Baheti, M Sap, A Ritter, M Riedl - arXiv preprint arXiv:2108.11830, 2021"],"snippet":"… For example, OpenAI's GPT-3 (Brown et al., 2020) is a 175 billion parameter neural network, trained on a 570GB subset CommonCrawl that is capable of engaging in impressive open-domain di- alogues with a user, when …","url":["https://arxiv.org/pdf/2108.11830"]}
-{"year":"2021","title":"Just What do You Think You're Doing, Dave?'A Checklist for Responsible Data Use in NLP","authors":["A Rogers, T Baldwin, K Leins - arXiv preprint arXiv:2109.06598, 2021"],"snippet":"Page 1. 'Just What do You Think You're Doing, Dave?' ∗ A Checklist for Responsible Data Use in NLP Anna Rogers Center for Social Data Science University of Copenhagen Denmark arogers@sodas.ku.dk Timothy Baldwin …","url":["https://arxiv.org/pdf/2109.06598"]}
-{"year":"2021","title":"KAN: Knowledge-Augmented Networks for Few-Shot Learning","authors":["Z Zhu, X Lin - ICASSP 2021-2021 IEEE International Conference on …, 2021"],"snippet":"… 3.3. Hyperparameters For the knowledge graph, to represent the initial semantic features of nodes, we use the GloVe model [23] which is the Common Crawl version trained on 840B tokens. The dimension of the semantic features is 300 …","url":["https://ieeexplore.ieee.org/abstract/document/9413612/"]}
-{"year":"2021","title":"KazNERD: Kazakh Named Entity Recognition Dataset","authors":["R Yeshpanov, Y Khassanov, HA Varol - arXiv preprint arXiv:2111.13419, 2021"],"snippet":"We present the development of a dataset for Kazakh named entity recognition. The dataset was built as there is a clear need for publicly available annotated corpora in Kazakh, as well as annotation guidelines containing straightforward--but rigorous--rules …","url":["https://arxiv.org/pdf/2111.13419"]}
-{"year":"2021","title":"KI2TE: Knowledge-Infused InterpreTable Embeddings for COVID-19 Misinformation Detection","authors":["W Shiao, EE Papalexakis"],"snippet":"… After cleaning, we were left with around 20K fake news articles. 3.4.3 Real News Dataset. We used the list from the BS Detector Chrome extension3 to pick the reputable sites. We then collected ar- ticles from all of the matching …","url":["https://www.cs.ucr.edu/~epapalex/papers/Knod2021_paper_7.pdf"]}
-{"year":"2021","title":"KIT's IWSLT 2021 Offline Speech Translation System","authors":["TN Nguyen, TS Nguyen, C Huber, M Awiszus… - Proceedings of the 18th …, 2021"],"snippet":"… On the other hand, Page 2. 126 Table 2: Text Training Data Dataset Sentences TED Talks (TED) 220K Europarl (EPPS) 2.2MK CommonCrawl 2.1M Rapid 1.21M ParaCrawl 25.1M OpenSubtitles 12.6M WikiTitle 423K Back-translated News 26M …","url":["https://aclanthology.org/2021.iwslt-1.13.pdf"]}
-{"year":"2021","title":"Knowledge Graphs for Analyzing and Searching Legal Data","authors":["K Sabrina, P Axel - 2021"],"snippet":"Page 1. Titel der Dissertation: Knowledge Graphs for Analyzing and Searching Legal Data Dissertation zur Erlangung des akademischen Grades eines Doktors der Sozialund Wirtschaftswissenschaften an der Wirtschaftsuniversität Wien eingereicht bei …","url":["https://aic.ai.wu.ac.at/~polleres/supervised_theses/Erwin_Filtz_PhD_2021.pdf"]}
-{"year":"2021","title":"Knowledge-driven Answer Generation for Conversational Search","authors":["M Leite, R Ferreira, D Semedo, J Magalhães - arXiv preprint arXiv:2104.06892, 2021"],"snippet":"… This model is pre-trained on the large C4 cor- 5 Page 6. pus, which was derived from Common Crawl1. A masked language modelling objective is used, where the model is trained to predict corrupted randomly sampled tokens of varying sizes. 5. Evaluation 5.1 …","url":["https://arxiv.org/pdf/2104.06892"]}
-{"year":"2021","title":"Knowledge-enhanced neural grammar Induction","authors":["B Li - 2021"],"snippet":"… become the dominant approach. Thanks to the Transformer's superior capability of parallelism, PLMs can be efficiently trained on enormous raw text (eg, common crawl of the internet) containing billions of tokens. Surprisingly, although PLMs contain no …","url":["https://era.ed.ac.uk/bitstream/handle/1842/37896/BowenLi_2021.pdf?sequence=1"]}
-{"year":"2021","title":"Label Imputation for Homograph Disambiguation: Theoretical and Practical Approaches","authors":["JM Seale - 2021"],"snippet":"Page 1. City University of New York (CUNY) CUNY Academic Works Dissertations, Theses, and Capstone Projects CUNY Graduate Center 9-2021 Label Imputation for Homograph Disambiguation: Theoretical and Practical Approaches Jennifer M. Seale …","url":["https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=5591&context=gc_etds"]}
-{"year":"2021","title":"Label-Descriptive Patterns and their Application to Characterizing Classification Errors","authors":["M Hedderich, J Fischer, D Klakow, J Vreeken - arXiv preprint arXiv:2110.09599, 2021"],"snippet":"State-of-the-art deep learning methods achieve human-like performance on many tasks, but make errors nevertheless. Characterizing these errors in easily interpretable terms gives insight into whether a model is prone to making systematic …","url":["https://arxiv.org/pdf/2110.09599"]}
-{"year":"2021","title":"LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs","authors":["C Schuhmann, R Vencu, R Beaumont, R Kaczmarczyk… - arXiv preprint arXiv …, 2021"],"snippet":"… To create image-text pairs, we parse through WAT files from Common Crawl and parse out all HTML IMG tags containing an alt-text attribute. We download the raw images from the parsed URLs with asynchronous requests using Trio and Asks libraries. …","url":["https://arxiv.org/pdf/2111.02114"]}
-{"year":"2021","title":"LAMBERT: Layout-Aware Language Modeling for Information Extraction","authors":["Ł Garncarek, R Powalski, T Stanisławek, B Topolski…"],"snippet":"… tuning, respectively. The training was performed on a collection of PDFs extracted from Common Crawl containing a variety of documents (we randomly selected up to 10 documents from any single domain). The documents …","url":["https://www.researchgate.net/profile/Lukasz-Garncarek/publication/339374440_LAMBERT_Layout-Aware_language_Modeling_for_information_extraction/links/605c2fdda6fdccbfea04b14a/LAMBERT-Layout-Aware-language-Modeling-for-information-extraction.pdf"]}
-{"year":"2021","title":"Language Embeddings for Typology and Cross-lingual Transfer Learning","authors":["D Yu, T He, K Sagae - arXiv preprint arXiv:2106.02082, 2021"],"snippet":"… lang_emb represents language embeddings from our proposed denoising autoencoder trained with language specific MUSE embeddings, using CommonCrawl text. Eng. lang_emb represents language embeddings trained …","url":["https://arxiv.org/pdf/2106.02082"]}
-{"year":"2021","title":"Language Models are not Models of Language","authors":["C Veres - arXiv preprint arXiv:2112.07055, 2021"],"snippet":"… Also mentioned is the Common Crawl web content where \"... difficulty of cleaning and filtering the Common Crawl data ...\" which has low … Common Crawl data also contains duplicate lines which often signals highly repetitive \"boilerplate text\", which …","url":["https://arxiv.org/pdf/2112.07055"]}
-{"year":"2021","title":"Language Models have a Moral Dimension","authors":["P Schramowski, C Turan, N Andersen, C Rothkopf… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Language Models have a Moral Dimension Patrick Schramowski, Cigdem Turan, Nico Andersen, Constantin Rothkopf & Kristian Kersting Abstract Artificial writing is permeating our lives due to recent advances in large …","url":["https://arxiv.org/pdf/2103.11790"]}
-{"year":"2021","title":"Language Representation Models: An Overview","authors":["T Schomacker, M Tropmann-Frick - Entropy, 2021"],"snippet":"… Since C4 is based on the common crawl project, it not only contains book-like or article-like texts but a much wider variety of English texts. Despite its colossal size [11], p. 7, ensured that, by their used techniques, C4 only consists of reasonably clean …","url":["https://www.mdpi.com/1099-4300/23/11/1422/pdf"]}
-{"year":"2021","title":"Language representations for computational argumentation","authors":["A Lauscher - 2021"],"snippet":"… CA Computational Argumentation. – , , , CBOW Continuous Bag of Words. – , , , CC Citation Contexts. CC- CommonCrawl- . , CCC Citation Context Identi cation. – CL Computational Linguistics. , , , , CLWE Cross-lingual Word Embe","url":["https://madoc.bib.uni-mannheim.de/60201/1/dissertation_lauscher.pdf"]}
-{"year":"2021","title":"Language Transfer for Identifying Diagnostic Paragraphs in Clinical","authors":["L Di Liello, O Uryupina, A Moschitti - 2021"],"snippet":"This paper aims at uncovering the structure of clinical documents, in particular, identifying paragraphs describing “diagnosis” or “procedures”. We present transformer-based architectures for approaching this task in a monolingual setting (English) …","url":["http://ceur-ws.org/Vol-3033/paper56.pdf"]}
-{"year":"2021","title":"LaoPLM: Pre-trained Language Models for Lao","authors":["N Lin, Y Fu, Z Yang, S Jiang - arXiv preprint arXiv:2110.05896, 2021"],"snippet":"… On the one hand, we utilize all the Lao data from the OSCAR corpus9, a humongous multilingual corpus whose texts all come from the Common Crawl corpus10. Suárez et al. [23] proposes the goclassy architecture to perform language …","url":["https://arxiv.org/pdf/2110.05896"]}
-{"year":"2021","title":"Large Margin Training Improves Language Models for ASR","authors":["J Wang, J Huang, KW Church - ICASSP 2021-2021 IEEE International Conference on …, 2021"],"snippet":"… on enWiki+bookcorpus. We thus adopt the published model and skip the pretraining phase. On the other hand, GPT, as a realization of transformer decoder model, is pretrained on a larger corpus, common crawl. For a fair …","url":["https://ieeexplore.ieee.org/abstract/document/9414724/"]}
-{"year":"2021","title":"Large-Scale Contextualised Language Modelling for Norwegian","authors":["A Kutuzov, J Barnes, E Velldal, L Øvrelid, S Oepen - arXiv preprint arXiv:2104.06546, 2021"],"snippet":"… models for Bokmål and Nynorsk). However, these models were trained on very modestly sized corpora of 20 million words for each language (randomly sampled from Wikipedia dumps and Common Crawl data). In a parallel effort …","url":["https://arxiv.org/pdf/2104.06546"]}
-{"year":"2021","title":"Large-Scale Self-and Semi-Supervised Learning for Speech Translation","authors":["C Wang, A Wu, J Pino, A Baevski, M Auli, A Conneau - arXiv preprint arXiv …, 2021"],"snippet":"… We also make use of monolingual text data in the target language to further improve translation quality. Specifically, we train a language model (LM) on part of the CommonCrawl data3 that is in similar domains as CoVoST …","url":["https://arxiv.org/pdf/2104.06678"]}
-{"year":"2021","title":"LARO: Language Agnostic Sentence Representations from finetuned RoBERTa⋆","authors":["AS Salvado - Language"],"snippet":"… The training resulted in the model approximating the meaning and syntax of all languages in the training data. The dataset which XLM-Roberta was trained on consists of 2.5TB CommonCrawl Data. The architecture of …","url":["https://users.informatik.haw-hamburg.de/~ubicomp/projekte/master2021-proj/soblechero.pdf"]}
-{"year":"2021","title":"LaTr: Layout-Aware Transformer for Scene-Text VQA","authors":["AF Biten, R Litman, Y Xie, S Appalaraju, R Manmatha - arXiv preprint arXiv …, 2021"],"snippet":"We propose a novel multimodal architecture for Scene Text Visual Question Answering (STVQA), named Layout-Aware Transformer (LaTr). The task of STVQA requires models to reason over different modalities. Thus, we first investigate the …","url":["https://arxiv.org/pdf/2112.12494"]}
-{"year":"2021","title":"LATS: Low-Resource Abstractive Text Summarization","authors":["CB van Yperen, F Frasincar, K Gruber - 2021"],"snippet":"… texts from 350 million Web pages. The dataset is based on the Common Crawl Web archive which is publicly available and contains scraped HTML files from which the markup has been removed. The HTML files have been …","url":["https://thesis.eur.nl/pub/56900/MSc_Thesis_27042021_CvanYperen.pdf"]}
-{"year":"2021","title":"Learned Construction Grammars Converge Across Registers Given Increased Exposure","authors":["J Dunn, HT Madabushi - arXiv preprint arXiv:2110.05663, 2021"],"snippet":"This paper measures the impact of increased exposure on whether learned construction grammars converge onto shared representations when trained on data from different registers. Register influences the frequency of constructions, with …","url":["https://arxiv.org/pdf/2110.05663"]}
-{"year":"2021","title":"Learning adaptive representations for entity recognition in the biomedical domain","authors":["I Lauriola, F Aiolli, A Lavelli, F Rinaldi - Journal of Biomedical Semantics, 2021"],"snippet":"Named Entity Recognition is a common task in Natural Language Processing applications, whose purpose is to recognize named entities in textual documents. Several systems exist to solve this task in the biomedical domain …","url":["https://jbiomedsem.biomedcentral.com/articles/10.1186/s13326-021-00238-0"]}
-{"year":"2021","title":"Learning Mathematical Properties of Integers","authors":["M Ryskina, K Knight - arXiv preprint arXiv:2109.07230, 2021"],"snippet":"… Ours OEIS 14M 133,004 GloVe–840B–300D Common Crawl 840B 64,729 … (2019), we choose three embedding models pre-trained on English text corpora: • GloVe–840B–300D: 300-dimensional GloVe vectors trained …","url":["https://arxiv.org/pdf/2109.07230"]}
-{"year":"2021","title":"Learning policy scheduling for text augmentation","authors":["S Li, X Ao, F Pan, Q He - Neural Networks, 2021"],"snippet":"Abstract When training deep learning models, data augmentation is an important technique to improve the performance and alleviate overfitting. In natural language processing (NLP), existing augmentation methods often use fixed strategies …","url":["https://www.sciencedirect.com/science/article/pii/S0893608021003907"]}
-{"year":"2021","title":"Learning Sense-Specific Static Embeddings using Contextualised Word Embeddings as a Proxy","authors":["D Bollegala, Y Zhou - Proceedings of the 35th Pacific Asia Conference on …, 2021","Y Zhou, D Bollegala - arXiv preprint arXiv:2110.02204, 2021"],"snippet":"… context t . 3 Experiments 3.1 Experimental Setup In our experiments, we use the pretained GloVe3 em- beddings (Common Crawl with 840B tokens and 2.2M vocabulary) as the static word embeddings g(u) with p = 300. We use …","url":["https://aclanthology.org/2021.paclic-1.2.pdf","https://arxiv.org/pdf/2110.02204"]}
-{"year":"2021","title":"Learning Sentiment Sentence Representation with Multiview Attention Model","authors":["Y Zhang, J Wang, X Zhang - Information Sciences, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0020025521005041"]}
-{"year":"2021","title":"Learning Structured Neural Semantic Parsers","authors":["P Yin - 2021"],"snippet":"Page 1. Learning Structured Neural Semantic Parsers Pengcheng Yin CMU LTI 21 014 August 16, 2021 Language Technologies Institute School of Computer Science Carnegie Mellon University 5000 Forbes Ave., Pittsburgh, PA 15123 www.lti.cs.cmu.edu …","url":["https://www.lti.cs.cmu.edu/sites/default/files/yin%2C%20pengcheng%20-%20Thesis.pdf"]}
-{"year":"2021","title":"Learning to Lemmatize in the Word Representation Space","authors":["J Lagus, A Klami - NoDaLiDa 2021, 2021"],"snippet":"… Data We validate the approach on Finnish language, using pretrained embeddings provided by the fastText library (Bojanowski et al., 2016). The embeddings were trained on Common Crawl and Wikipedia corpora and have dimensionality of d= 300 …","url":["https://ep.liu.se/ecp/178/ecp2021178.pdf#page=265"]}
-{"year":"2021","title":"Learning to rank for Consumer Health Search","authors":["H Yang, X Liu, B Zheng, G Yang - CLEF 2021 Evaluation Labs and Workshop: Online …, 2021"],"snippet":"… Totally, the collection consists of over 5 million medical webpages from selected domains acquired from the CommonCrawl and other resources [4]. 3.3. Topics Totally 55 topics are used in the CLEF 2021 CHS task, and they are based on realistic search scenarios …","url":["http://ceur-ws.org/Vol-2936/paper-71.pdf"]}
-{"year":"2021","title":"Learning To Retrieve Prompts for In-Context Learning","authors":["O Rubin, J Herzig, J Berant - arXiv preprint arXiv:2112.08633, 2021"],"snippet":"In-context learning is a recent paradigm in natural language understanding, where a large pre-trained language model (LM) observes a test instance and a few training examples as its input, and directly decodes the output without any update to its …","url":["https://arxiv.org/pdf/2112.08633"]}
-{"year":"2021","title":"Leveraging Longitudinal Data for Personalized Prediction and Word Representations","authors":["C Welch - 2021"],"snippet":"Page 1. Leveraging Longitudinal Data for Personalized Prediction and Word Representations by Charles Welch A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Computer …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/167971/cfwelch_1.pdf?sequence=1"]}
-{"year":"2021","title":"Leveraging Transformers for Hate Speech Detection in Conversational Code-Mixed Tweets","authors":["ZM Farooqi, S Ghosh, RR Shah - arXiv preprint arXiv:2112.09986, 2021"],"snippet":"… • XLM-Roberta (XLM-R) [42] is a transformer-based masked language model pretrained on Common Crawl data having about 100 languages. It was proposed by Facebook and happened to be one of the best-performing transformer models for …","url":["https://arxiv.org/pdf/2112.09986"]}
-{"year":"2021","title":"Lexicon Development for COVID-19-related Concepts Using Open-source Word Embedding Sources: An Intrinsic and Extrinsic Evaluation","authors":["S Parikh, A Davoudi, S Yu, C Giraldo, E Schriver… - JMIR Medical Informatics, 2021"],"snippet":"Background: Scientists are developing new computational methods and prediction models to better clinically understand COVID-19 prevalence, treatment efficacy, and patient outcomes. These efforts could be improved by leveraging …","url":["https://medinform.jmir.org/2021/2/e21679"]}
-{"year":"2021","title":"Light gradient boosting machine-based phishing webpage detection model using phisher website features of mimic URLs","authors":["E Oram, PB Dash, B Naik, J Nayak, S Vimal, SK Nataraj - Pattern Recognition Letters, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0167865521003445"]}
-{"year":"2021","title":"LILE: Look In-Depth before Looking Elsewhere--A Dual Attention Network using Transformers for Cross-Modal Information Retrieval in Histopathology Archives","authors":["D Maleki, H Tizhoosh - 2021"],"snippet":"The volume of available data has grown dramatically in recent years in many applications. Furthermore, the age of networks that used multiple modalities separately has practically ended. Therefore, enabling bidirectional cross-modality …","url":["https://openreview.net/pdf?id=ZmsElUaQ0Xm"]}
-{"year":"2021","title":"Limitations of Knowledge Distillation for Zero-shot Transfer Learning","authors":["S Soltan, AA AI, H Khan, W Hamza"],"snippet":"… However, they focused on distillation during pretraining and evaluate their model only on XNLI from XTREME benchmarks. Since they used common crawl data for pretraining and a different architecture, their models are not directly comparable to ours. 3 Method …","url":["https://assets.amazon.science/3b/46/17df4724436d850c46fcb41b1569/limitations-of-knowledge-distillation-for-zero-shot-transfer-learning.pdf"]}
-{"year":"2021","title":"LIMSI@ MLIA","authors":["SA Rauf, F Yvon - 2020"],"snippet":"… In addition, we used the Cochrane bilingual parallel corpus [4]3 and the Taus Corona Crisis corpus.4. For out-of-domain corpus, we used the parallel corpora provided by the WMT14 campaign, which included Gigafr-en …","url":["http://eval.covid19-mlia.eu/meetings/round1/report/20210114-limsi.pdf"]}
-{"year":"2021","title":"Lingua Custodia's participation at the WMT 2021 Machine Translation using Terminologies shared task","authors":["M Ailem, J Liu, R Qader - arXiv preprint arXiv:2111.02120, 2021"],"snippet":"This paper describes Lingua Custodia's submission to the WMT21 shared task on machine translation using terminologies. We consider three directions, namely English to French, Russian, and Chinese. We rely on a Transformer-based …","url":["https://arxiv.org/pdf/2111.02120"]}
-{"year":"2021","title":"Linking place records using multi-view encoders","authors":["V Cousseau, L Barbosa - Neural Computing and Applications, 2021"],"snippet":"… For address embeddings, we utilized case-sensitive embeddings trained with the FastText model [4] on top of a Wikipedia and Common Crawl corpus [22]. The reasoning behind the different embedding sources for names and …","url":["https://link.springer.com/article/10.1007/s00521-021-05932-9"]}
-{"year":"2021","title":"LIORI at SemEval-2021 Task 2: Span Prediction and Binary Classification approaches to Word-in-Context Disambiguation","authors":["A Davletov, N Arefyev, D Gordeev, A Rey - Proceedings of the Fifteenth Workshop on …, 2021"],"snippet":"… tokens. XLM-R was trained on a cleaned two-terabyte CommonCrawl Corpus in 100 languages. A new promising approach to language task modelling is treating any natural language task as a question answering problem …","url":["https://aclanthology.org/2021.semeval-1.103.pdf"]}
-{"year":"2021","title":"LISN@ WMT 2021","authors":["J Xu, SA Rauf, MQ Pham, F Yvon - 6th Conference on Statistical Machine Translation, 2021"],"snippet":"This paper describes LISN's submissions to two shared tasks at WMT'21. For the biomedical translation task, we have developed resource-heavy systems for the English-French language pair, using both out-ofdomain and in-domain corpora. The …","url":["https://hal.archives-ouvertes.fr/hal-03430610/document"]}
-{"year":"2021","title":"LMMS Reloaded: Transformer-based Sense Embeddings for Disambiguation and Beyond","authors":["D Loureiro, AM Jorge, J Camacho-Collados - arXiv preprint arXiv:2105.12449, 2021"],"snippet":"Page 1. LMMS Reloaded: Transformer-based Sense Embeddings for Disambiguation and Beyond Daniel Loureiroa,∗, Alıpio Mário Jorgea, Jose Camacho-Colladosb aLIAAD - INESC TEC, Dept. of Computer Science, FCUP …","url":["https://arxiv.org/pdf/2105.12449"]}
-{"year":"2021","title":"LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking","authors":["H Jiang, S Gurajada, Q Lu, S Neelam, L Popa, P Sen… - arXiv preprint arXiv …, 2021"],"snippet":"… We also employ a suite of pretrained or custom trained neural language models to compute the similarity of mi and eij. Pre-trained Embedding Models. These include SpaCy's semantic similarity6 function that uses Glove …","url":["https://arxiv.org/pdf/2106.09795"]}
-{"year":"2021","title":"Log Parsing and Template Extraction Using Neueral Sequence-To-Sequence Models","authors":["K Pawlikowski - 2021"],"snippet":"Abstract System log messages are produced by software systems as their code executes. The contents of these log messages vary across systems and are defined by the software developers of the system. Log messages can be captured and …","url":["https://search.proquest.com/openview/6e178e5359e69ed4aa85193bc726d8ac/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"Looking for Semantic Similarity: What a Vector Space Model of Semantics Can Tell Us About Attention in Real-world Scenes","authors":["TR Hayes, JM Henderson - 2021"],"snippet":"… ing the semantic vectors from Word2vec (Mikolov, Chen, Corrado, & Dean, 2013) and GloVe 1.2 (Pennington, Socher, & Manning, 2014) that learn how words are associated with each other from large text corpora (ie, Google …","url":["https://osf.io/wsyz9/download?format=pdf"]}
-{"year":"2021","title":"Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models","authors":["R Wolfe, A Caliskan - arXiv preprint arXiv:2110.00672, 2021"],"snippet":"Page 1. Low Frequency Names Exhibit Bias and Overfitting in Contextualizing Language Models Robert Wolfe University of Washington rwolfe3@uw.edu Aylin Caliskan University of Washington aylin@uw.edu Abstract We use …","url":["https://arxiv.org/pdf/2110.00672"]}
-{"year":"2021","title":"LSI_UNED at CLEF eHealth2021: Exploring the effects of transfer learning in negation detection and entity recognition in clinical texts","authors":["H Fabregat, A Duque, L Araujo, J Martinez-Romo - CLEF eHealth, 2021"],"snippet":"… Word embeddings: Two different pre-trained word embeddings from different sources are used for text representation. On the one hand, we use general domain Spanish 100dimensional word embeddings in …","url":["http://ceur-ws.org/Vol-2936/paper-65.pdf"]}
-{"year":"2021","title":"M6: A Chinese Multimodal Pretrainer","authors":["J Lin, R Men, A Yang, C Zhou, M Ding, Y Zhang… - arXiv preprint arXiv …, 2021"],"snippet":"… Xu et al. [45] released a 100GB corpus named CLUECorpus2020, which is re- trieved from the multilingual Common Crawl dataset … Forum discussion Plain-text - 8.7 39.0 223.1 - 18.0 Common Crawl Plain-text - 40.3 108.7 370.7 - 83.3 …","url":["https://arxiv.org/pdf/2103.00823"]}
-{"year":"2021","title":"M6: Multi-Modality-to-Multi-Modality Multitask Mega-transformer for Unified Pretraining","authors":["J Lin, R Men, A Yang, C Zhou, Y Zhang, P Wang… - 2021"],"snippet":"… Xu et al. [45] released a 100𝐺𝐵 corpus named CLUECorpus2020, which is retrieved from the multilingual Common Crawl dataset … Forum discussion Plain-text - 8.7 39.0 223.1 - 18.0 Common Crawl Plain-text - 40.3 108.7 370.7 - 83.3 …","url":["https://keg.cs.tsinghua.edu.cn/jietang/publications/KDD21-Lin-et-al-M6.pdf"]}
-{"year":"2021","title":"Machine Habitus: Toward a Sociology of Algorithms","authors":["M Airoldi - 2021"]}
-{"year":"2021","title":"Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset","authors":["V Agarwal, A Manjunatha, JA Smith, AV Gribok… - 2021"],"snippet":"Page 1. INL/EXT-21-61984 Revision 0 Industry Funding Opportunity Announcement Award Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset March …","url":["https://www.osti.gov/servlets/purl/1770866"]}
-{"year":"2021","title":"Machine Learning and Security Studies","authors":["S Dorsey - 2020"],"snippet":"Page 1. Machine Learning and Security Studies by Spencer Dorsey Department of Political Science Duke University Date: Approved: Scott de Marchi, Advisor Peter Feaver, Advisor Laia Balcells Erik Wibbels Dissertation submitted …","url":["https://dukespace.lib.duke.edu/dspace/bitstream/handle/10161/22158/Dorsey_duke_0066D_15915.pdf?sequence=1"]}
-{"year":"2021","title":"Machine learning for financial transaction classification across companies using character-level word embeddings of text fields","authors":["RK Jørgensen, C Igel - Intelligent Systems in Accounting, Finance and …"],"snippet":"Abstract An important initial step in accounting is mapping financial transfers to the corresponding accounts. We devised machine-learning-based systems that automate this process. They use word em...","url":["https://onlinelibrary.wiley.com/doi/full/10.1002/isaf.1500"]}
-{"year":"2021","title":"Machine Learning Meets Natural Language Processing--The story so far","authors":["NI Galanis, P Vafiadis, KG Mirzaev, GA Papakostas - arXiv preprint arXiv:2104.10213, 2021"],"snippet":"… in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 4938–4947, 2020. 42. “Common Crawl”, Accessed: Mar. 24, 2021.[Online]. Available: https://commoncrawl.org/ 43. “Kaggle”, Accessed: Mar. 24, 2021.[Online] …","url":["https://arxiv.org/pdf/2104.10213"]}
-{"year":"2021","title":"Machine Learning with Applications","authors":["N Kanakaris, N Giarelis, I Siachos, N Karacapilidis","NK Corrêa, S Falk, S Fatimah, A Sen, N De Oliveira","S Casola, I Lauriola, A Lavelli"],"snippet":"This paper employs techniques and algorithms from the fields of natural language processing, graph representation learning and word embeddings to assist project managers in the task of personnel selection. To do so, our approach initially …","url":["https://www.researchgate.net/profile/Nicholas-Correa-2/publication/380496051_TeenyTinyLlama_Open-source_tiny_language_models_trained_in_Brazilian_Portuguese/links/66474976479366623af3b128/TeenyTinyLlama-Open-source-tiny-language-models-trained-in-Brazilian-Portuguese.pdf","https://www.researchgate.net/profile/Nikos-Kanakaris/publication/356403657_Making_personnel_selection_smarter_through_word_embeddings_A_graph-based_approach/links/61a4ac35d7d1af224b2be56e/Making-personnel-selection-smarter-through-word-embeddings-A-graph-based-approach.pdf","https://www.researchgate.net/profile/Silvia-Casola/publication/361083726_Pre-trained_transformers_an_empirical_comparison/links/62a3370f55273755ebe1d59b/Pre-trained-transformers-an-empirical-comparison.pdf"]}
-{"year":"2021","title":"Machine Translation Customization via Automatic Training Data Selection from the Web","authors":["T Vu, A Moschitti"],"snippet":"… 5 Fig. 1: Customization process of MT Systems Corpus Sent. (MM) News Commentary v13 0.3 Rapid (press releases) 1.3 Common Crawl 1.9 Europarl v7 2.4 ParaCrawl (Zipporah) 40.6 ParaCrawl (BiCleaner) 27.7 …","url":["https://assets.amazon.science/ed/9f/3bc994bc4be7bc53449bda397d83/machine-translation-customization-via-automatic-training-data-selection-from-the-web.pdf"]}
-{"year":"2021","title":"Majority Voting with Bidirectional Pre-translation Improves Bitext Retrieval","authors":["A Jones, DT Wijaya - arXiv preprint arXiv:2103.06369, 2021"],"snippet":"Page 1. Majority Voting with Bidirectional Pre-translation Improves Bitext Retrieval Alex Jones Dartmouth College alexander.g.jones.23@dartmouth.edu Derry Tanti Wijaya Boston University wijaya@bu.edu Abstract Obtaining …","url":["https://arxiv.org/pdf/2103.06369"]}
-{"year":"2021","title":"Making personnel selection smarter through word embeddings: A graph-based approach","authors":["N Kanakaris, N Giarelis, I Siachos, N Karacapilidis - Machine Learning with …, 2021"],"snippet":"… GoogleNews using Word2Vec and Common Crawl using GloVe are some of the most favored public pre-trained word embeddings. For an in-depth analysis as far as the differences and use-cases of various pre-trained word embeddings are …","url":["https://www.sciencedirect.com/science/article/pii/S2666827021001079"]}
-{"year":"2021","title":"Maps Search Misspelling Detection Leveraging Domain-Augmented Contextual Representations","authors":["Y Li - arXiv preprint arXiv:2108.06842, 2021"],"snippet":"… The second two models are trained with 42B Glove (Common Crawl) vectors, with embedding dimension 300, hidden state di- mension 50 and the same vocabulary. Our motivation of using a Page 4. KDD WIT '21, Aug …","url":["https://arxiv.org/pdf/2108.06842"]}
-{"year":"2021","title":"Marked Attribute Bias in Natural Language Inference","authors":["H Dawkins"],"snippet":"… Otherwise, we apply the method to the 2Taken as the GloVe embeddings trained on the Common Crawl corpus for 840B tokens; available at https://nlp.stanford.edu/projects/glove/. Results were not found to vary …","url":["https://aclanthology.org/2021.findings-acl.369.pdf"]}
-{"year":"2021","title":"MarkupLM: Pre-training of Text and Markup Language for Visually-rich Document Understanding","authors":["J Li, Y Xu, L Cui, F Wei - arXiv preprint arXiv:2110.08518, 2021"],"snippet":"… Equipped with the existing webpage datasets Common Crawl (CC)3, we pre-train MarkupLM with large-scale unlabeled HTML data and evaluate the pre-trained models on web-based structural reading comprehension and information extraction tasks. …","url":["https://arxiv.org/pdf/2110.08518"]}
-{"year":"2021","title":"MasakhaNER: Named Entity Recognition for African Languages","authors":["DI Adelani, J Abbott, G Neubig, D D'souza, J Kreutzer… - arXiv preprint arXiv …, 2021"],"snippet":"… XLMR XLMR (Conneau et al., 2020) was trained on 100 languages including Amharic, Hausa, and Swahili. The major differences be tween XLMR and mBERT are (1) XLMR was trained on Common Crawl while mBERT was …","url":["https://arxiv.org/pdf/2103.11811"]}
-{"year":"2021","title":"Masked Language Model Entity Matching for Cultural Heritage Data","authors":["D Piché, A Zouaq, M Gagnon, L Font - 2021"],"snippet":"… CamemBERT [10] is trained on the French portion of the OSCAR corpus, a pre-filtered version of Common Crawl, while FlauBERT [8] trains on a combination of French sets, including WMT19, OPUS, Wikimedia and Project Gutenberg. 3 Data overview …","url":["http://ceur-ws.org/Vol-2949/paper5.pdf"]}
-{"year":"2021","title":"Mastering Transformers: Build state-of-the-art models from scratch with advanced natural language processing techniques","authors":["S Yildirim, M Asgari-Chenaghlu - 2021"],"snippet":"Page 1. Mastering Transformers Build state-of-the-art models from scratch with advanced natural language processing techniques 0001) il -0 1 0 -0 -O 0 - -0 1 -0 - -0 1 1. -0 -0 -0 -0 -0 -0 1 1 0 010 1 0 1 0 1 01100110 0001101010 …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=A9Y6EAAAQBAJ&oi=fnd&pg=PP1&dq=commoncrawl&ots=vd7ymgpejf&sig=Vl9kWAVZADIBu0pKOCgd-uJ7Xw8"]}
-{"year":"2021","title":"Matches Made in Heaven: Toolkit and Large-Scale Datasets for Supervised Query Reformulation","authors":["N Arabzadeh, A Bigdeli, S Seyedsalehi, M Zihayat…"],"snippet":"Page 1. Matches Made in Heaven: Toolkit and Large-Scale Datasets for Supervised Query Reformulation Negar Arabzadeh University of Waterloo narabzad@uwaterloo. ca Amin Bigdeli Ryerson University abigdeli@ryerson.ca …","url":["http://ls3.rnet.ryerson.ca/wiki/images/a/ab/Matches-made-in-heaven.pdf"]}
-{"year":"2021","title":"MDAPT: Multilingual Domain Adaptive Pretraining in a Single Model","authors":["RK Jørgensen, M Hartmann, X Dai, D Elliott - arXiv preprint arXiv:2109.06605, 2021"],"snippet":"Page 1. MDAPT: Multilingual Domain Adaptive Pretraining in a Single Model Rasmus Kær Jørgensen1,2 and Mareike Hartmann3∗ and Xiang Dai1 and Desmond Elliott1 1University of Copenhagen, Denmark 2PricewaterhouseCoopers …","url":["https://arxiv.org/pdf/2109.06605"]}
-{"year":"2021","title":"Measuring associational thinking through word embeddings","authors":["C Periñán-Pascual - Artificial Intelligence Review, 2021"],"snippet":"The development of a model to quantify semantic similarity and relatedness between words has been the major focus of many studies in various fields, eg p.","url":["https://link.springer.com/article/10.1007/s10462-021-10056-6"]}
-{"year":"2021","title":"Measuring Gender Bias in Word Embeddings for Russian Language","authors":["AS Pestova"],"snippet":"… The effect size is calculated as Cohen's d [6]: mean𝑥𝑥∈𝑋𝑋 𝑐𝑐(𝑥𝑥𝑎 𝐴𝐴𝑎 𝐵𝐵) - mean𝑦𝑦∈𝑌𝑌 𝑐𝑐(𝑦𝑦𝑎 𝐴𝐴𝑎 𝐵𝐵) std - dev𝑤𝑤∈𝑋𝑋∪𝑌𝑌 𝑐𝑐(𝑤𝑤𝑎 𝐴𝐴𝑎 𝐵𝐵) (4) 3https://tatianashavrina.github.io/taiga\\_site …","url":["http://www.dialog-21.ru/media/5322/pestovaas047.pdf"]}
-{"year":"2021","title":"Memes in the Wild: Assessing the Generalizability of the Hateful Memes Challenge Dataset","authors":["HR Kirk, Y Jun, P Rauba, G Wachtel, R Li, X Bai… - arXiv preprint arXiv …, 2021"],"snippet":"… F T-SNE Text Embeddings The meme-level embeddings are calculated by (i) extracting a 300-dimensional embedding for each word in the meme, using fastText embeddings trained on Wikipedia and Common Crawl; (ii) …","url":["https://arxiv.org/pdf/2107.04313"]}
-{"year":"2021","title":"Mengzi: Towards Lightweight yet Ingenious Pre-trained Models for Chinese","authors":["Z Zhang, H Zhang, K Chen, Y Guo, J Hua, Y Wang… - arXiv preprint arXiv …, 2021"],"snippet":"Although pre-trained models (PLMs) have achieved remarkable improvements in a wide range of NLP tasks, they are expensive in terms of time and resources. This calls for the study of training more efficient models with less computation but still …","url":["https://arxiv.org/pdf/2110.06696"]}
-{"year":"2021","title":"MetaXL: Meta Representation Transformation for Low-resource Cross-lingual Learning","authors":["M Xia, G Zheng, S Mukherjee, M Shokouhi, G Neubig… - arXiv preprint arXiv …, 2021"],"snippet":"… The Hausdorff distance between the source and target representations drops from 0.57 to 0.20 with F1 score improvement from 74.07 to 78.15. Wikipedia and XLM-R (Conneau et al., 2020) is pre-trained on 100 languages with CommonCrawl Corpora …","url":["https://arxiv.org/pdf/2104.07908"]}
-{"year":"2021","title":"Metric Learning in Multilingual Sentence Similarity Measurement for Document Alignment","authors":["C Rajitha, L Piyarathne, D Sachintha, S Ranathunga - arXiv preprint arXiv …, 2021"],"snippet":"… applied to the training data. XLM-R is trained with common crawl data from 100 languages, and has shown to outperform mBERT on multiple Natural Language Processing tasks. 3 Metric Learning Unsupervised metrics such as …","url":["https://arxiv.org/pdf/2108.09495"]}
-{"year":"2021","title":"MFAQ: a Multilingual FAQ Dataset","authors":["M De Bruyn, E Lotfi, J Buhmann, W Daelemans - arXiv preprint arXiv:2109.12870, 2021"],"snippet":"… provides an open repository of the web.5 Common Crawl's complete web archive consists of petabytes of data collected over 10 years of web crawling (Ortiz Suárez et al., 2020). The repository is organized in monthly bucket …","url":["https://arxiv.org/pdf/2109.12870"]}
-{"year":"2021","title":"Mind the Gap: Assessing Temporal Generalization in Neural Language Models","authors":["A Lazaridou, A Kuncoro, E Gribovskaya, D Agrawal… - Advances in Neural …, 2021"],"snippet":"Abstract Our world is open-ended, non-stationary, and constantly evolving; thus what we talk about and how we talk about it change over time. This inherent dynamic nature of language contrasts with the current static language modelling …","url":["https://proceedings.neurips.cc/paper/2021/file/f5bf0ba0a17ef18f9607774722f5698c-Paper.pdf"]}
-{"year":"2021","title":"Minimum Bayes Risk Decoding with Neural Metrics of Translation Quality","authors":["M Freitag, D Grangier, Q Tan, B Liang - arXiv preprint arXiv:2111.09388, 2021"],"snippet":"This work applies Minimum Bayes Risk (MBR) decoding to optimize diverse automated metrics of translation quality. Automatic metrics in machine translation have made tremendous progress recently. In particular, neural metrics, fine-tuned on …","url":["https://arxiv.org/pdf/2111.09388"]}
-{"year":"2021","title":"Mining emotion-aware sequential rules at user-level from micro-blogs","authors":["MP Skenduli, M Biba, C Loglisci, M Ceci, D Malerba - Journal of Intelligent Information …, 2021"],"snippet":"… the fine-grained emotion analysis task. Based on the obtained results, we decide to use multi-lingual word embeddings, pre-trained on Common Crawl and Wikipedia corpora using fastText. These models were trained using …","url":["https://link.springer.com/article/10.1007/s10844-021-00647-8"]}
-{"year":"2021","title":"Misinformation Retrieval","authors":["S Rizvi - 2021"],"snippet":"… 34 4.1 Excerpt from a correct document from the Common Crawl Collection with fact used to validate tweets in blue. . . . . 43 viii Page 9 … for a given topic. The corpus used for both tasks was the common crawl corpus consisting of news articles online …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/17609/Rizvi_Saira.pdf?sequence=3&isAllowed=y"]}
-{"year":"2021","title":"Mitigating the Position Bias of Transformer Models in Passage Re-Ranking","authors":["S Hofstätter, A Lipani, S Althammer, M Zlabinger… - arXiv preprint arXiv:2101.06980"],"snippet":"… For the Transformer layers in TK we evaluate 2 layers each with 16 attention heads with size 32 and a feed-forward dimension of 100. For kernel-pooling we set the number 3 github.com/microsoft/BlingFire 4 42B CommonCrawl …","url":["https://arxiv.org/pdf/2101.06980"]}
-{"year":"2021","title":"MKPM: Multi keyword-pair matching for natural language sentences","authors":["X Lu, Y Deng, T Sun, Y Gao, J Feng, X Sun, R Sutcliffe - Applied Intelligence, 2021"],"snippet":"Sentence matching is widely used in various natural language tasks, such as natural language inference, paraphrase identification and question answering. F.","url":["https://link.springer.com/article/10.1007/s10489-021-02306-5"]}
-{"year":"2021","title":"MLLP-VRAIN Spanish ASR Systems for the Albayzin-RTVE 2020 Speech-To-Text Challenge","authors":["J Jorge, A Giménez, P Baquero-Arnal…"],"snippet":"… El Periódico [28] 2677 46637 291 Common Crawl [29] 1719 41792 486 Internal: parliamentary data 1361 35170 126 … [27] “Eldiario.es,” https://www.eldiario.es/. [28] “ElPeriodico.com,” https://www.elperiodico …","url":["https://www.isca-speech.org/archive/IberSPEECH_2021/pdfs/25.pdf"]}
-{"year":"2021","title":"mLUKE: The Power of Entity Representations in Multilingual Pretrained Language Models","authors":["R Ri, I Yamada, Y Tsuruoka - arXiv preprint arXiv:2110.08151, 2021"],"snippet":"… 2019) trained with CommonCrawl data from 100 languages, and the parameters in common (eg, the weights of the transformer encoder and the word embeddings) are initialized using the checkpoint from the Transformers library.The size of the …","url":["https://arxiv.org/pdf/2110.08151"]}
-{"year":"2021","title":"Mobile Testing Framework Exploiting Machine Learning and NLP","authors":["L ARDITO, M MORISIO, R COPPOLA - 2021"],"snippet":"… the NLP step. Bert-Base, Multilingual Cased for BERT feature vector, GloVe Common Crawl 300 dimensional model for Glove, and lastly Fasttext 300 dimensional pre-trained model for Fasttext vector was used. On the android …","url":["https://webthesis.biblio.polito.it/19106/1/tesi.pdf"]}
-{"year":"2021","title":"Model Averaging in Distributed Machine Learning: A Case Study with Apache Spark","authors":["Y Guo, Z Zhang, J Jiang, W Wu, C Zhang, B Cui, J Li"],"snippet":"Page 1. Noname manuscript No. (will be inserted by the editor) Model Averaging in Distributed Machine Learning: A Case Study with Apache Spark Yunyan Guo · Zhipeng Zhang · Jiawei Jiang · Wentao Wu · Ce Zhang · Bin …","url":["http://pages.cs.wisc.edu/~wentaowu/papers/vldbj-model-avg.pdf"]}
-{"year":"2021","title":"Modeling Endorsement for Multi-Document Abstractive Summarization","authors":["L Lebanoff, B Wang, Z Feng, F Liu - arXiv preprint arXiv:2110.07844, 2021"],"snippet":"A crucial difference between singleand multi-document summarization is how salient content manifests itself in the document(s). While such content may appear at the beginning of a single document, essential information is frequently reiterated in a …","url":["https://arxiv.org/pdf/2110.07844"]}
-{"year":"2021","title":"Modeling Global and Local Interactions for Online Conversation Recommendation","authors":["X Zeng, J Li, L Wang, KF Wong - ACM Transactions on Information Systems (TOIS), 2021"],"snippet":"… For the parameters with respect to local interactions, we initialize the word embedding layer with 200-dimensional Glove embedding [66], where the Twitter version is used for our Twitter dataset, and the Common Crawl version is applied on …","url":["https://dl.acm.org/doi/full/10.1145/3473970"]}
-{"year":"2021","title":"Modern-Day Shakespeare: Training Set Experiments with a Generative Pre-Trained Transformer-Best Paper","authors":["R Sheverack - 2021"],"snippet":"Page 1. 1 Modern-Day Shakespeare: Training Set Experiments with a Generative Pre-Trained Transformer Applied Project Final Report By Roksolana Maria Sheverack Spring 2021 A paper submitted in partial …","url":["http://archive.nyu.edu/bitstream/2451/62802/2/R.Sheverack%20-%20Final%20Project%20Report%20-%20Modern-Day%20Shakespeare%3ATraining%20Set%20Experiments%20with%20a%20Generative%20Pre-Trained%20Transformer.pdf"]}
-{"year":"2021","title":"Monitoring COVID-19 pandemic through the lens of social media using natural language processing and machine learning","authors":["Y Liu, C Whitfield, T Zhang, A Hauser, T Reynolds… - Health Information Science …, 2021"],"snippet":"… The custom NER model that we trained was based on spaCy's multi-task, OntoNotes-trained Convolutional Neural Network which uses GloVe vectors that were trained using Common Crawl [37] corpus. Topic modeling. Topic …","url":["https://link.springer.com/article/10.1007/s13755-021-00158-4"]}
-{"year":"2021","title":"Monolingual and Cross-Lingual Acceptability Judgments with the Italian CoLA corpus","authors":["D Trotta, R Guarasci, E Leonardelli, S Tonelli - arXiv preprint arXiv:2109.12053, 2021"],"snippet":"… Each sentence is represented as a sequence of word embeddings, obtained with the Italian model of FastText (Grave et al., 2018) trained on Common Crawl and Wikipedia with size 300.4 The network is implemented with Keras …","url":["https://arxiv.org/pdf/2109.12053"]}
-{"year":"2021","title":"Moral rights","authors":["NB Eve"],"snippet":"… offer other services, including: CC Search, which makes openly licensed material easier to discover and use. As it makes use of the Common Crawl dataset, creators do not have to apply to be included (“About CC Search”) …","url":["http://sharedspaces.usask.ca/ipandcopyright"]}
-{"year":"2021","title":"More Data and New Tools. Advances in Parsing the Index Thomisticus Treebank","authors":["F Gamba, M Passarotti, P Ruffolo - Proceedings http://ceur-ws. org ISSN, 2021"],"snippet":"Abstract This paper investigates the recent advances in parsing the Index Thomisticus Treebank, which encompasses Medieval Latin texts by Thomas Aquinas. The research focuses on two types of variables. On the one hand, it examines the …","url":["http://ceur-ws.org/Vol-2989/long_paper20.pdf"]}
-{"year":"2021","title":"More Than Reading Comprehension: A Survey on Datasets and Metrics of Textual Question Answering","authors":["Y Bai, DZ Wang - arXiv preprint arXiv:2109.12264, 2021"],"snippet":"… Long-form QA ELI5[16] 2019 EN Web. Common Crawl Reddit Reddit Free-form ROUG-1,2,L MASH-QA[17] 2020 EN Health WebMD QA section QA section Span of words F1, EM NLQuAD[18] 2021 EN News BBC …","url":["https://arxiv.org/pdf/2109.12264"]}
-{"year":"2021","title":"Morph Call: Probing Morphosyntactic Content of Multilingual Transformers","authors":["V Mikhailov, O Serikov, E Artemova - arXiv preprint arXiv:2104.12847, 2021"],"snippet":"… languages. D-BERT (Sanh et al., 2019) or DistilBERT is a 6-layer distilled version of M-BERT model. XLM-R (Conneau et al., 2019) was pre-trained over filtered CommonCrawl data in 100 languages (Wenzek et al., 2019). MiniLM …","url":["https://arxiv.org/pdf/2104.12847"]}
-{"year":"2021","title":"Morphological Skip-Gram: Replacing FastText characters n-gram with morphological knowledge","authors":["TD Bispo, FAO Santos, HT Macedo, C Zanchettin - Inteligencia Artificial, 2021"],"snippet":"Page 1. Inteligencia Artificial, 24(67), 1-17 doi: 10.4114/intartif.vol24iss67pp1-17 INTELIGENCIA ARTIFICIAL http://journal.iberamia.org/ Morphological Skip-Gram: Replacing FastText characters n-gram with morphological knowledge …","url":["https://www.journal.iberamia.org/index.php/intartif/article/download/588/131"]}
-{"year":"2021","title":"Multi-granular Legal Topic Classification on Greek Legislation","authors":["C Papaloukas, I Chalkidis, K Athinaios, DA Pantazi… - arXiv preprint arXiv …, 2021"],"snippet":"… learning rate. Based on this study, Conneau et al. (2020) proposed the XLMRoBERTa model, which supports 100 different languages (Greek included) and is trained on 2.5TB of filtered Common Crawl data. GREEK-BERT …","url":["https://arxiv.org/pdf/2109.15298"]}
-{"year":"2021","title":"Multi-Granularity Contrasting for Cross-Lingual Pre-Training","authors":["S Li, P Yang, F Luo, J Xie"],"snippet":"… Following Conneau et al. (2019), we re- construct Common-Crawl Corpus to obtain monolingual training datasets while the bilingual data is obtained from the OPUS website 5. We also conduct up/down-sample for all pre-training data with a smoothing parameter …","url":["https://aclanthology.org/2021.findings-acl.149.pdf"]}
-{"year":"2021","title":"Multi-level Embeddings for Processing Arabic Social Media Contents","authors":["L Moudjari, F Benamara, K Akli-Astouati - Computer Speech & Language, 2021"],"url":["https://www.sciencedirect.com/science/article/pii/S0885230821000474"]}
-{"year":"2021","title":"Multi-Level Sentiment Analysis of Product Reviews Based on Grammar Rules","authors":["HD Nguyen, T Le, K Tran, ST Luu, SN Hoang, HT Phan - New Trends in Intelligent …, 2021"],"snippet":"… BERT is a transfer learning method which is trained on large language corpus such as Wikipedia and Common Crawl in different languages, then applied to specific tasks by fine tuning the model [7]. The appearance of BERT makes …","url":["https://ebooks.iospress.nl/volumearticle/57466"]}
-{"year":"2021","title":"Multi-task Learning Using a Combination of Contextualised and Static Word Embeddings for Arabic Sarcasm Detection and Sentiment Analysis","authors":["AI Alharbi, M Lee - Proceedings of the Sixth Arabic Natural Language …, 2021"],"snippet":"… al., 2017). The Ara2Vec word embeddings is a well-known open-source tool made up of six Arabic models. Data was obtained from Wikipedia, Twitter and Common Crawl (webpage crawl data) to train Ara2Vec. Al- though it …","url":["https://www.aclweb.org/anthology/2021.wanlp-1.39.pdf"]}
-{"year":"2021","title":"MultiEmo: Multilingual, Multilevel, Multidomain Sentiment Analysis Corpus of Consumer Reviews","authors":["K Kanclerz"],"snippet":"… The first model, Unsupervised Cross-lingual Representation Learning at Scale (XLM-RoBERTa), is a large multillingual language model, trained on 2.5TB of filtered CommonCrawl data, using self-supervised training techniques to achieve state-of-the-art performance …","url":["https://www.iccs-meeting.org/archive/iccs2021/papers/127430291.pdf"]}
-{"year":"2021","title":"MultiEURLEX--A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer","authors":["I Chalkidis, M Fergadiotis, I Androutsopoulos - arXiv preprint arXiv:2109.00904, 2021"],"snippet":"… It is pretrained on Common Crawl with a vocabulary of 250k sub-words shared across languages … (2021) released a multilingual variant of T5 (Raffel et al., 2020), an encoder-decoder TRANSFORMER-based model …","url":["https://arxiv.org/pdf/2109.00904"]}
-{"year":"2021","title":"Multilingual and Zero-Shot is Closing in on Monolingual Web Register Classification","authors":["S Rönnqvist, V Skantsi, M Oinonen, V Laippala - NoDaLiDa 2021, 2021"],"snippet":"… The English CORE is based on unrestricted search queries of extremely frequent n-grams, while the other datasets are randomly sampled from the 2017 CoNLL Shared Task datasets, originally drawn from Common Crawl (Ginter et al., 2017) …","url":["https://ep.liu.se/ecp/178/ecp2021178.pdf#page=173"]}
-{"year":"2021","title":"Multilingual Autoregressive Entity Linking","authors":["N De Cao, L Wu, K Popat, M Artetxe, N Goyal… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Multilingual Autoregressive Entity Linking Nicola De Cao1,2, Ledell Wu1, Kashyap Popat1, Mikel Artetxe1, Naman Goyal1, Mikhail Plekhanov1, Luke Zettlemoyer1,3, Nicola Cancedda1, Sebastian Riedel1,4, Fabio Petroni1 …","url":["https://arxiv.org/pdf/2103.12528"]}
-{"year":"2021","title":"Multilingual Counter Narrative Type Classification","authors":["YL Chung, M Guerini, R Agerri - arXiv preprint arXiv:2109.13664, 2021"],"snippet":"… The XLM-R language model (Conneau et al., 2020), pre-trained on CommonCrawl for 100 languages, reports strong performance on several cross-lingual downstream tasks such as natural language inference or …","url":["https://arxiv.org/pdf/2109.13664"]}
-{"year":"2021","title":"Multilingual discussion summarisation in social networks","authors":["TN Andreevic - 2021"],"snippet":"Page 1. Санкт–Петербургский государственный университет Тарасов Никита Андреевич Выпускная квалификационная работа Суммаризация мультиязычных дискуссий в социальных сетях Уровень образования: магистратура …","url":["https://dspace.spbu.ru/bitstream/11701/32265/1/thesis.pdf"]}
-{"year":"2021","title":"Multilingual ELMo and the Effects of Corpus Sampling","authors":["V Ravishankar, A Kutuzov, L Øvrelid, E Velldal - NoDaLiDa 2021, 2021"],"snippet":"… 3.2 Sampling Our initial starting point for collecting the language model training corpora were the CoNLL 2017 Wikipedia/Common Crawl dumps released as part of the shared task on Universal Dependencies parsing …","url":["https://ep.liu.se/ecp/178/ecp2021178.pdf#page=395"]}
-{"year":"2021","title":"Multilingual Epidemic Event Extraction","authors":["S Mutuvi, E Boros, A Doucet, G Lejeune, A Jatowt… - International Conference on …, 2021"],"snippet":"Abstract In this paper, we focus on epidemic event extraction in multilingual and low-resource settings. The task of extracting epidemic events is defined as the detection of disease names and locations in a document. We experiment with a multilingual …","url":["https://link.springer.com/chapter/10.1007/978-3-030-91669-5_12"]}
-{"year":"2021","title":"Multilingual Learning for Mild Cognitive Impairment Screening from a Clinical Speech Task","authors":["H Lindsay, P Müller, I Kröger, J Tröger, N Linz, A König… - 2021"],"snippet":"… al., 2020a). As semantic vectors are learned from large amounts of text corpora (usually Wikipedia and OSCAR common crawl), embedding quality heavily depends on the quantity of the available training data. While French …","url":["https://www.researchgate.net/profile/Hali-Lindsay-2/publication/354604884_Multilingual_Learning_for_Mild_Cognitive_Impairment_Screening_from_a_Clinical_Speech_Task/links/61420ec62db97e68051fbf26/Multilingual-Learning-for-Mild-Cognitive-Impairment-Screening-from-a-Clinical-Speech-Task.pdf"]}
-{"year":"2021","title":"Multilingual Named Entity Recognition through Data and Model Transfer","authors":["S Palma-Suominen - 2021"],"snippet":"Page 1. UNIVERSITY OF HELSINKI FACULTY OF ARTS DEPARTMENT OF DIGITAL HUMANITIES Master's Thesis Multilingual Named Entity Recognition through Data and Model Transfer Saara Palma-Suominen 014291850 …","url":["https://helda.helsinki.fi/bitstream/handle/10138/330451/palma-suominen_saara_tutkielma_2021.pdf?sequence=2"]}
-{"year":"2021","title":"Multilingual Neural Semantic Parsing for Low-Resourced Languages","authors":["M Xia, E Monti - arXiv preprint arXiv:2106.03469, 2021"],"snippet":"… It is trained for 100 languages on the CommonCrawl corpus, which is several orders of magnitude larger than the Wikipedia dump, especially for low-resourced languages. We use the public XLM-R Base model3 (12-layer, 768-hidden, 12 heads) in our experiment …","url":["https://arxiv.org/pdf/2106.03469"]}
-{"year":"2021","title":"Multilingual Sentiment Analysis and Toxicity Detection for Text Messages in Russian","authors":["D Bogoradnikova, O Makhnytkina, A Matveev… - 2021 29th Conference of …, 2021"],"snippet":"… 179M pa- rameters, trained on cased texts in the top 104 languages with the largest Wikipedias), and xlm-roberta (270M parameters with 12-layers, 768-hidden-state, 3072 feed-forward hiddenstate, 8-heads, trained on 2.5 …","url":["https://ieeexplore.ieee.org/abstract/document/9435584/"]}
-{"year":"2021","title":"Multilingual Transfer Learning for Code-Switched Language and Speech Neural Modeling","authors":["GI Winata - arXiv preprint arXiv:2104.06268, 2021"],"snippet":"Page 1. Multilingual Transfer Learning for Code-Switched Language and Speech Neural Modeling by Genta Indra Winata A Thesis Submitted to The Hong Kong University of Science and Technology in Partial Fulfillment of the Requirements for …","url":["https://arxiv.org/pdf/2104.06268"]}
-{"year":"2021","title":"Multilingual Translation from Denoising Pre-Training","authors":["Y Tang, C Tran, X Li, PJ Chen, N Goyal, V Chaudhary…"],"snippet":"… al., 2019; Brown et al., 2020). Monolingual data is far more prevalent for low resource languages, particularly in resources such as Wikipedia or Commoncrawl, a version of the web. Recent work has explored monolingual denoising …","url":["https://aclanthology.org/2021.findings-acl.304.pdf"]}
-{"year":"2021","title":"Multilingual Zero-Shot and Few-Shot Causality Detection","authors":["SM Reimann - 2021"],"snippet":"… BPE vocabulary with 100k subwords. Moreover, regarding training data, they build a CommonCrawl corpus for 100 languages, which is notably larger than the Wikipedia corpus used for mBERT. For pretraining XLM-R, they …","url":["https://www.diva-portal.org/smash/get/diva2:1569716/FULLTEXT01.pdf"]}
-{"year":"2021","title":"Multimodal and Multilingual Embeddings for Large-Scale Speech Mining","authors":["PA Duquenne, H Gong, H Schwenk - Advances in Neural Information Processing …, 2021"],"snippet":"… Using a similarity metric in that multimodal embedding space, we perform mining of audio in German, French, Spanish and English from Librivox against billions of sentences from Common Crawl. This yielded more than twenty thousand hours of …","url":["https://proceedings.neurips.cc/paper/2021/file/8466f9ace6a9acbe71f75762ffc890f1-Paper.pdf"]}
-{"year":"2021","title":"Multimodal datasets: misogyny, pornography, and malignant stereotypes","authors":["A Birhane, VU Prabhu, E Kahembwe - arXiv preprint arXiv:2110.01963, 2021"],"snippet":"… project to train a GDPR-Article(9)-Sensitive-URL classifier which revealed that, of the 1 Billion URLs they audited in the Common Crawl project, 155 million URLs fell into the sensitive category. The Realtoxicityprompts work …","url":["https://arxiv.org/pdf/2110.01963"]}
-{"year":"2021","title":"Multimodal Emotion Recognition Using Transfer Learning on Audio and Text Data","authors":["JJ Deng, CHC Leung, Y Li - … Conference on Computational Science and Its …, 2021"],"snippet":"… As for text representation, we adopt fine-tuned Text-To-Text Transfer Transformer (T5) [23] model trained by a common crawl (C4) dataset to extract text embeddings. Operations of transfer learning have greatly accelerated model training and applied in specific domains …","url":["https://link.springer.com/chapter/10.1007/978-3-030-86970-0_39"]}
-{"year":"2021","title":"Multimodal MRI cerebral correlates of verbal fluency switching and its impairment in women with depression","authors":["L Domain, M Guillery, N Linz, A König, JM Batail… - NeuroImage: Clinical, 2021"],"snippet":"Background The search of biomarkers in the field of depression requires easy implementable tests that are biologically rooted. Qualitative analysis of verbal fluency tests (VFT) are good candidates, but its cerebral correlates are unknown …","url":["https://www.sciencedirect.com/science/article/pii/S2213158221003545"]}
-{"year":"2021","title":"Multimodal or Text? Retrieval or BERT? Benchmarking Classifiers for the Shared Task on Hateful Memes","authors":["V Kougia, J Pavlopoulos"],"snippet":"… for English pre-trained on Common Crawl (Grave et al., 2018) (MNN:base). 2 The second variant em- ploys three BERT models, each fine-tuned on one of our tasks (see subsection 3.2), from which we extracted the CLS tokens …","url":["https://aclanthology.org/2021.woah-1.24.pdf"]}
-{"year":"2021","title":"Multiplicative Position-aware Transformer Models for Language Understanding","authors":["Z Huang, D Liang, P Xu, B Xiang - arXiv preprint arXiv:2109.12788, 2021"],"snippet":"Page 1. Multiplicative Position-aware Transformer Models for Language Understanding Zhiheng Huang AWS AI zhiheng@amazon.com Davis Liang AWS AI liadavis@amazon.com Peng Xu AWS AI pengx@amazon.com …","url":["https://arxiv.org/pdf/2109.12788"]}
-{"year":"2021","title":"Multitask Learning for Complaint Identification and Sentiment Analysis","authors":["A Singh, S Saha, M Hasanuzzaman, K Dey - Cognitive Computation, 2021"],"snippet":"In today's competitive business world, customer service is often at the heart of businesses that can help strengthen their brands. Resolution of cust.","url":["https://link.springer.com/article/10.1007/s12559-021-09844-7"]}
-{"year":"2021","title":"MuRIL: Multilingual Representations for Indian Languages","authors":["S Khanuja, D Bansal, S Mehtani, S Khosla, A Dey… - arXiv preprint arXiv …, 2021"],"snippet":"… Monolingual Data: We collect monolingual data for the 17 languages mentioned above from the Common Crawl OSCAR corpus1 and Wikipedia2 … Wikipedia Common Crawl Wikipedia Common Crawl PMINDIA …","url":["https://arxiv.org/pdf/2103.10730"]}
-{"year":"2021","title":"My House, My Rules: Learning Tidying Preferences with Graph Neural Networks","authors":["I Kapelyukh, E Johns - arXiv preprint arXiv:2111.03112, 2021"],"snippet":"… We load word embeddings from a FastText model [20], pre-trained on the Common Crawl dataset of over 600 billion tokens. Names of objects are provided to NeatNet either by the simulator or by an object detection system if deployed …","url":["https://arxiv.org/pdf/2111.03112"]}
-{"year":"2021","title":"Nahuatl Neural Machine Translation Using Attention Based Architectures: A Comparative Analysis for RNNs and Transformers as a Mobile Application Service","authors":["SK Bello García, E Sánchez Lucero, E Bonilla Huerta… - … International Conference on …, 2021"],"snippet":"… Trained with 175 billions parameters and more than a trillion words from Common Crawl’s [27] and Wikipedia, making GPT-3 the largest language model at the time. The architecture is composed by 96 stacked encoder-decoder layers, 96 multi-head …","url":["https://link.springer.com/chapter/10.1007/978-3-030-89820-5_10"]}
-{"year":"2021","title":"Named Entity Recognition and Classification on Historical Documents: A Survey","authors":["M Ehrmann, A Hamdi, EL Pontes, M Romanello… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Named Entity Recognition and Classification on Historical Documents: A Survey MAUD EHRMANN, Ecole Polytechnique Fédérale de Lausanne AHMED HAMDI, University of La Rochelle ELVYS LINHARES PONTES …","url":["https://arxiv.org/pdf/2109.11406"]}
-{"year":"2021","title":"Named entity recognition and linking augmented with large-scale structured data","authors":["P Rychlikowski, A Lancucki, A Kaczmarek, B Najdecki… - Proceedings of the 8th …, 2021"],"snippet":"… possible. This line of reasoning applied especially to word-level embeddings. Ideally we wanted our systems to have, for every language, em- beddings trained on Wikipedia, Common Crawl1, and a collection of news articles. We …","url":["https://www.aclweb.org/anthology/2021.bsnlp-1.14.pdf"]}
-{"year":"2021","title":"Named Entity Recognition and Normalization in Biomedical Literature: A Practical Case in SARS-CoV-2 Literature","authors":["ÁA Casero - 2021"],"snippet":"Page 1. Universidad Politécnica de Madrid Escuela Técnica Superior de Ingenieros Informáticos Máster Universitario en Inteligencia Artificial Trabajo Fin de Máster Named Entity Recognition and Normalization in Biomedical Literature: A …","url":["http://oa.upm.es/67933/1/TFM_ALVARO_ALONSO_CASERO.pdf"]}
-{"year":"2021","title":"Naming unrelated words predicts creativity","authors":["JA Olson, J Nahas, D Chmoulevitch, SJ Cropper… - Proceedings of the National …, 2021"],"snippet":"Skip to main content. Main menu. Home; Articles: Current; Special Feature Articles - Most Recent; Special Features; Colloquia; Collected Articles; PNAS Classics; List of Issues. Front Matter: Front Matter Portal; Journal Club. News: For …","url":["https://www.pnas.org/content/pnas/118/25/e2022340118.full.pdf"]}
-{"year":"2021","title":"Natural and artificial intelligence; natural and artificial language","authors":["D Santos - 2021"],"snippet":"… desinteligência, Inteligência, inteligência-do-cinema, inteligibilidade, inteligXancia, deligência, inteligencia, inteligência (0.85) 300 columns, obtained on 2 billion words, common crawl: fasttext, words: inteligencia (0.77), Inteligência, ainteligência …","url":["https://www.linguateca.pt/Diana/download/SantosSLATE2021.pdf"]}
-{"year":"2021","title":"Natural language inference for Malayalam language using language agnostic sentence representation","authors":["S Renjit, S Idicula - PeerJ Computer Science, 2021"],"snippet":"… It is available in many languages, including Malayalam. fastText provided pretrained word vector representations trained on Common Crawl and Wikipedia data in 294 languages, including Malayalam, which we utilized to create sentence representations …","url":["https://peerj.com/articles/cs-508/"]}
-{"year":"2021","title":"Negation typology and general representation models for cross-lingual zero-shot negation scope resolution in Russian, French, and Spanish.","authors":["A Shaitarova, F Rinaldi - Proceedings of the 2021 Conference of the North …, 2021"],"snippet":"… We build on this work and compare mBERT with a new multilingual general purpose representation model, XLM-R. Unlike mBERT, XLM-R was pre-trained on more than two terabytes of filtered data collected by CommonCrawl …","url":["https://www.aclweb.org/anthology/2021.naacl-srw.3.pdf"]}
-{"year":"2021","title":"Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding","authors":["Z Wang, L Wang, T Wu, T Li, G Wu - arXiv preprint arXiv:2109.04872, 2021"],"snippet":"Page 1. Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding Zhenzhi Wang, Limin Wang*, Tao Wu, Tianhao Li, Gangshan Wu State Key Laboratory for Novel Software Technology, Nanjing University …","url":["https://arxiv.org/pdf/2109.04872"]}
-{"year":"2021","title":"Network embeddings from distributional thesauri for improving static word representations","authors":["A Jana, S Haldar, P Goyal - Expert Systems with Applications, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0957417421012276"]}
-{"year":"2021","title":"Neural approaches to discourse coherence: modeling, evaluation and application","authors":["Y Farag - 2021"],"snippet":"Page 1. Neural approaches to discourse coherence: modeling, evaluation and application Youmna Farag Murray Edwards College This dissertation is submitted in September 2020 for the degree of Doctor of Philosophy Page 2. Page 3. Declaration …","url":["https://www.repository.cam.ac.uk/bitstream/handle/1810/322567/thesis.pdf?sequence=3"]}
-{"year":"2021","title":"Neural Machine Translation: A Review of Methods, Resources, and Tools","authors":["Z Tan, S Wang, Z Yang, G Chen, X Huang, M Sun… - arXiv preprint arXiv …, 2020"],"snippet":"Page 1. Neural Machine Translation: A Review of Methods, Resources, and Tools Zhixing Tana,c,d, Shuo Wanga,c,d, Zonghan Yanga,c,d, Gang Chena,c,d, Xuancheng Huanga,c,d, Maosong Suna,c,d,e, Yang Liua,b,c,d,e,∗ …","url":["https://arxiv.org/pdf/2012.15515"]}
-{"year":"2021","title":"Neural Methods for Answer Passage Retrieval over Sparse Collections","authors":["D Cohen - 2021"],"snippet":"Page 1. University of Massachusetts Amherst ScholarWorks@UMass Amherst Doctoral Dissertations Dissertations and Theses April 2021 Neural Methods for Answer Passage Retrieval over Sparse Collections Daniel Cohen …","url":["https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=3157&context=dissertations_2"]}
-{"year":"2021","title":"Neural Representation Learning onTables","authors":["H Sun"],"snippet":"Page 1. From Tables to Knowledge (KDD'21): Jay Pujara, Pedro Szekely, Huan Sun, Muhao Chen Huan Sun The Ohio State University From Tables to Knowledge: Recent Advances in Table Understanding (Part III) Neural …","url":["https://pdfs.semanticscholar.org/62f0/dc599074928447c2582a136e08151255f79c.pdf"]}
-{"year":"2021","title":"Neural Search: Learning Query and Product Representations in Fashion E-commerce","authors":["L Kumar, S Sarkar - arXiv preprint arXiv:2107.08291, 2021"],"snippet":"Page 1. Neural Search: Learning Query and Product Representations in Fashion E-commerce Sagnik Sarkar* sagnik.sarkar@myntra.com Myntra Designs Pvt. Ltd. India Lakshya Kumar* lakshya.kumar@myntra.com Myntra Designs Pvt. Ltd. India …","url":["https://arxiv.org/pdf/2107.08291"]}
-{"year":"2021","title":"Neural Sequential Modeling and Applications","authors":["G Lai - 2021"],"snippet":"Page 1. Neural Sequential Modeling and Applications Guokun Lai CMU-LTI-21-010 Language Technology Institute School of Computer Science Carnegie Mellon University 5000 Forbes Ave., Pittsburgh, PA 15213 www.lti.cs.cmu.edu …","url":["https://www.lti.cs.cmu.edu/sites/default/files/lai%2C%20guokun%20-%20Thesis.pdf"]}
-{"year":"2021","title":"Neural Supervised Domain Adaptation by Augmenting Pre-trained Models with Random Units","authors":["S Meftah, N Semmar, Y Tamaazousti, H Essafi, F Sadat - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Neural Supervised Domain Adaptation by Augmenting Pre-trained Models with Random Units Sara Meftah∗, Nasredine Semmar∗, Youssef Tamaazousti∗, Hassane Essafi∗, Fatiha Sadat+ ∗CEA-List, Université Paris …","url":["https://arxiv.org/pdf/2106.04935"]}
-{"year":"2021","title":"Neural Text Generation with Artificial Negative Examples to Address Repeating and Dropping Errors","authors":["K Shirai, K Hashimoto, A Eriguchi, T Ninomiya, S Mori - Journal of Natural Language …, 2021"],"snippet":"… Both Japanese and English sentences were preprocessed as recommended in WAT'15.5 For the De-En task, we used the datasets provided by WMT'166 as well as all parallel corpora (Europarl v7 …","url":["https://www.jstage.jst.go.jp/article/jnlp/28/3/28_751/_pdf"]}
-{"year":"2021","title":"Neural Text Generation with Artificial Negative Examples","authors":["K Shirai, K Hashimoto, A Eriguchi, T Ninomiya, S Mori - arXiv preprint arXiv …, 2020"],"snippet":"… For the De-En task, we used the datasets provided by WMT'166 and used all parallel corpora (Europarl v7, Common Crawl corpus, and News Commentary v11) for training, NewsTest2013 for development, and NewsTest2014 for testing …","url":["https://arxiv.org/pdf/2012.14124"]}
-{"year":"2021","title":"Neural Transfer Learning for Domain Adaptation in Natural Language Processing","authors":["S Meftah - 2021"],"snippet":"Page 1. Neural Transfer Learning for Domain Adaptation in Natural Language Processing Apprentissage par Transfert Neuronal pour l'Adaptation aux Domaines en Traitement Automatique de la Langue Thèse de doctorat de l'université Paris-Saclay …","url":["https://www.theses.fr/2021UPASG021.pdf"]}
-{"year":"2021","title":"Neural Transfer Learning with Transformers for Social Science Text Analysis","authors":["S Wankmüller - arXiv preprint arXiv:2102.02111, 2021"],"snippet":"Page 1. Neural Transfer Learning with Transformers for Social Science Text Analysis Sandra Wankmüller Ludwig-Maximilians-University Munich sandra.wankmueller@ gsi.lmu.de Abstract. During the last years, there have been …","url":["https://arxiv.org/pdf/2102.02111"]}
-{"year":"2021","title":"NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned","authors":["S Min, J Boyd-Graber, C Alberti, D Chen, E Choi… - arXiv preprint arXiv …, 2021"],"snippet":"… T5-XL+SSM T5 [13] is a text-to-text Transformer language model utilizing an encoder-decoder architecture that was pre-trained using a “span corruption” objective on a cleaned and de-duplicated subset of Common Crawl. Roberts et al …","url":["https://arxiv.org/pdf/2101.00133"]}
-{"year":"2021","title":"New Synonyms Extraction Model Based on a Novel Terms Weighting Scheme","authors":["AH Ababneh, J Lu, Q Xu"],"snippet":"Page 1. 171 JIOS, VOL. 45. NO. 1 (2021), PP. 171-221 JIOS, VOL. 45, NO. 1 (2021) SUBMITTED 08/20; ACCEPTED 11/20 New Synonyms Extraction Model Based on a Novel Terms Weighting Scheme Ahmad Hussein Ababneh ahmad.ababneh@aum.edu.jo …","url":["https://jios.foi.hr/index.php/jios/article/view/1526/904"]}
-{"year":"2021","title":"News Headline Summarization","authors":["A Kulkarni, A Shivananda, A Kulkarni - Natural Language Processing Projects, 2022"],"snippet":"… This transformer model is trained on the Colossal Clean Common Crawl (C4) data set. The architecture is integrated to devise text2text model. And hence T5 can also be used for many text-to-text-based applications. …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-7386-9_10"]}
-{"year":"2021","title":"NICT-2 Translation System at WAT-2021: Applying a Pretrained Multilingual Encoder-Decoder Model to Low-resource Language Pairs","authors":["K Imamura, E Sumita - Malay (Ms)"],"snippet":"… model can learn multiple languages. The published pretrained mBART model2 consists of a 12-layer encoder and decoder with a model dimension of 1,024 on 16 heads. This model was trained on 25 languages in the Common Crawl corpus (Wenzek et al., 2019) …","url":["https://aclanthology.org/2021.wat-1.8.pdf"]}
-{"year":"2021","title":"NLI Data Sanity Check: Assessing the Effect of Data Corruption on Model Performance","authors":["A Talman, M Apidianaki, S Chatzikyriakidis… - arXiv preprint arXiv …, 2021"],"snippet":"… 4The contexts for R1 and R2 consist of sentences re- trieved from Wikipedia. In R3 the contexts are retrieved from Wikipedia, News (Common Crawl), fiction, The Children's Book Test (CBT), formal spoken text and …","url":["https://arxiv.org/pdf/2104.04751"]}
-{"year":"2021","title":"NLM at TREC 2020 Health Misinformation and Deep Learning Tracks","authors":["Y Mrabet, M Sarrouti, AB Abacha, S Gayen, T Goodwin…"],"snippet":"… Figure 1 presents an overview of our data pipeline, approaches and workflow. 1 Common Crawl News: https://github.com/commoncrawl/news-crawl 2 https://github.com/optimaize/ language-detector Page 2. 2 Authors Suppressed Due to Excessive Length Fig …","url":["https://trec.nist.gov/pubs/trec29/papers/NLM.HM.DL.pdf"]}
-{"year":"2021","title":"No News is Good News: A Critique of the One Billion Word Benchmark","authors":["H Ngo, JGM Araújo, J Hui, N Frosst - arXiv preprint arXiv:2110.12609, 2021"],"snippet":"… We train models solely on Common Crawl web scrapes partitioned by year, and demonstrate that they perform worse on this task over time due to distributional shift. Analysis of this corpus reveals that it contains several examples of harmful text, as …","url":["https://arxiv.org/pdf/2110.12609"]}
-{"year":"2021","title":"Node. js based Document Store for Web Crawling","authors":["D Bui - 2021"],"snippet":"… and internet archiving such as the Common Crawl Project. While the Internet Archive focuses on preservation, Common Crawl focuses on making web crawled data publicly accessible for scientific analysis and studies [3]. Common Crawl …","url":["https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=2039&context=etd_projects"]}
-{"year":"2021","title":"NormFormer: Improved Transformer Pretraining with Extra Normalization","authors":["S Shleifer, J Weston, M Ott - arXiv preprint arXiv:2110.09456, 2021"],"snippet":"During pretraining, the Pre-LayerNorm transformer suffers from a gradient magnitude mismatch: gradients at early layers are much larger than at later layers. These issues can be alleviated by our proposed NormFormer architecture, which …","url":["https://arxiv.org/pdf/2110.09456"]}
-{"year":"2021","title":"Not a Mirror, but an Engine: Digital Methods for Contextual Analysis of “Social Big Data”","authors":["JA Schwarz - Digital Human Sciences"],"snippet":"… In SNA, for example, the set of social relations is always at least two-dimensional 16 and is usually represented in the form of a node table (listing all the nodes 14 There are, eg, open science projects like …","url":["https://stockholmuniversitypress.se/site/books/10.16993/bbk/download/7869/#page=34"]}
-{"year":"2021","title":"Not Far Away, Not So Close: Sample Efficient Nearest Neighbour Data Augmentation via MiniMax","authors":["E Kamalloo, M Rezagholizadeh, P Passban, A Ghodsi - arXiv preprint arXiv …, 2021"],"snippet":"… The aim of this stage is to find interpretable unannotated augmented samples that are semantically close to training data. For this purpose, we use one of the sentence repositories from SentAugment (Du et al., 2021), comprising …","url":["https://arxiv.org/pdf/2105.13608"]}
-{"year":"2021","title":"Novelty Detection in Textual Data using Document Encoders and Self Attention.","authors":["A Parkhi - 2021"],"snippet":"… two-layer neural network. We try to minimize the negative log-likelihood of the next word for an entire corpus. GloVe vectors are trained on the common crawl dataset, consisting of 840B tokens and 2.2M different tokens. We use glove vectors with a spacy …","url":["https://repository.lib.ncsu.edu/bitstream/handle/1840.20/38854/etd.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"NPVec1: Word Embeddings for Nepali-Construction and Evaluation","authors":["P Koirala, NB Niraula"],"snippet":"… Common Crawl3 is a non-profit organization which collects data through web crawling and makes it publicly available. 3.1.3 Nepali Wikipedia Corpus We obtained Nepali Wikipedia corpus from Kaggle (Gaurav, 2020) …","url":["https://aclanthology.org/2021.repl4nlp-1.18.pdf"]}
-{"year":"2021","title":"NUIG at TIAD 2021: Cross-lingual Word Embeddings for Translation Inference","authors":["S Banerjee, JP McCrae"],"snippet":"… concepts WordNet [13] graph analysis and cross-lingual word embeddings monolingual corpora of Common Crawl and Wikipedia [8] graph analysis relying on paths, synonyms, similarities and cardinality in the translation graph …","url":["https://sinaahmadi.github.io/docs/articles/ahmadi2021TIAD.pdf"]}
-{"year":"2021","title":"NukeLM: Pre-Trained and Fine-Tuned Language Models for the Nuclear and Energy Domains","authors":["L Burke, K Pazdernik, D Fortin, B Wilson, R Goychayev… - arXiv preprint arXiv …, 2021"],"snippet":"… which tokens to predict in each batch rather than deciding offline, before training; it uses much larger batch sizes; it uses byte-level tokenization instead of character-level; and finally, it considers much more pre-training data …","url":["https://arxiv.org/pdf/2105.12192"]}
-{"year":"2021","title":"Obtaining Better Static Word Embeddings Using Contextual Embedding Models","authors":["P Gupta, M Jaggi - arXiv preprint arXiv:2106.04302, 2021"],"snippet":"… We also evaluate some pre-trained 300 dimensional GLOVE (Pennington et al., 2014) and FASTTEXT (Bojanowski et al., 2016) models in Table 3. The GLOVE model was trained on Common-Crawl corpus of 840 Billion …","url":["https://arxiv.org/pdf/2106.04302"]}
-{"year":"2021","title":"of black-box classifiers'","authors":["K Sinha - 2021"],"snippet":"… The embeddings used came from the 840b token Common Crawl pre-trained 300 dimensional GloVe vectors, limited to the vocabulary present in the SST dataset4. Ultimately, this model achieves 84% accuracy on the bi- nary SST classification task …","url":["https://www.researchgate.net/profile/Mario-Holubar/publication/352058956_Re_Replication_Study_of_'Generative_causal_explanations_of_black-box_classifiers'/links/60b77888a6fdcc476be1c863/Re-Replication-Study-of-Generative-causal-explanations-of-black-box-classifiers.pdf"]}
-{"year":"2021","title":"Offensive Language Detection in Turkish Tweets with Bert Models","authors":["A Özberk, İ Çiçekli - 2021 6th International Conference on Computer …, 2021"],"snippet":"… XLM-RoBERTa that is a transformer-based cross-lingual model is pre-trained using a multilingual masNed language model objective on 2.5 TB of CommonCrawl data in 100 languages [15]. Our offensive language detection models use BERT …","url":["https://ieeexplore.ieee.org/abstract/document/9559000/"]}
-{"year":"2021","title":"Offensive Language Identification in Low-resourced Code-mixed Dravidian languages using Pseudo-labeling","authors":["A Hande, K Puranik, K Yasaswini, R Priyadharshini… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Offensive Language Identification in Low-resourced Code-mixed Dravidian languages using Pseudo-labeling Adeep Handea,, Karthik Puranika,, Konthala Yasaswinia, Ruba Priyadharshinib, Sajeetha Thavareesanc …","url":["https://arxiv.org/pdf/2108.12177"]}
-{"year":"2021","title":"Offensive, aggressive, and hate speech analysis: From data-centric to human-centered approach","authors":["J Kocoń, A Figas, M Gruza, D Puchalska… - Information Processing & …, 2021"],"url":["https://www.sciencedirect.com/science/article/pii/S0306457321001333"]}
-{"year":"2021","title":"Omission of Information: Identifying Political Slant via an Analysis of Co-occurring Entities","authors":["J Ehrhardt, T Spinde, A Vardasbi, F Hamborg - 2021"],"snippet":"… 3 https://commoncrawl.org/ Page 6. Omission of Information: Identifying Political Slant via an Analysis of … 85 We scraped a total of 76.221 articles from nine different news outlets equally distributed over the three slant …","url":["https://epub.uni-regensburg.de/44939/1/isi_ehrhardt_et_al.pdf"]}
-{"year":"2021","title":"OmniNet: Omnidirectional Representations from Transformers","authors":["Y Tay, M Dehghani, V Aribandi, J Gupta, P Pham, Z Qin… - arXiv preprint arXiv …, 2021"],"snippet":"… We run experiments on large-scale autoregressive (unidirectional) language modeling. We use two large-scale datasets, language modeling one billion (LM1B) (Chelba et al., 2013) and the Colossal Cleaned Common …","url":["https://arxiv.org/pdf/2103.01075"]}
-{"year":"2021","title":"On a Utilitarian Approach to Privacy Preserving Text Generation","authors":["Z Xu, A Aggarwal, O Feyisetan, N Teissier - arXiv preprint arXiv:2104.11838, 2021"],"snippet":"… Due to the high dimensional nature of textual tasks and very large vocabulary sizes (eg 2.2M words for GLOVE common crawl (Pennington et al., 2014)), this can lead to adding a lot of noise for achieving the desired privacy …","url":["https://arxiv.org/pdf/2104.11838"]}
-{"year":"2021","title":"On Anytime Learning at Macroscale","authors":["L Caccia, J Xu, M Ott, MA Ranzato, L Denoyer - arXiv preprint arXiv:2106.09563, 2021"],"snippet":"… For instance, every once in a while new data from common crawl is gathered to train even larger language models, or every few weeks new images and associated labels are collected to train better visual object recognizers …","url":["https://arxiv.org/pdf/2106.09563"]}
-{"year":"2021","title":"On the dangers of stochastic parrots: Can language models be too big","authors":["EM Bender, T Gebru, A McMillan-Major, S Shmitchell - Proceedings of FAccT, 2021"],"snippet":"… show that models like GPT-3 trained with at least 570GB of data derived mostly from Common Crawl16 can generate sentences with high toxicity … 16https://commoncrawl.org/the-data/ 17GPT-3's training data is not openly …","url":["http://faculty.washington.edu/ebender/papers/Stochastic_Parrots.pdf"]}
-{"year":"2021","title":"On the Language Coverage Bias for Neural Machine Translation","authors":["S Wang, Z Tu, Z Tan, S Shi, M Sun, Y Liu - arXiv preprint arXiv:2106.03297, 2021"],"snippet":"Page 1. On the Language Coverage Bias for Neural Machine Translation Shuo Wang1 Zhaopeng Tu2 Zhixing Tan1 Shuming Shi2 Maosong Sun1,3 Yang Liu1,3,4 1Dept. of Comp. Sci. & Tech., Institute for AI, BNRist Center, Tsinghua …","url":["https://arxiv.org/pdf/2106.03297"]}
-{"year":"2021","title":"On the Learning Dynamics of Semi-Supervised Training for ASR}}","authors":["E Wallington, B Kershenbaum, O Klejch, P Bell - Proc. Interspeech 2021, 2021"],"snippet":"… Following initial analysis, we use these same varying-quality models to investigate iSST. 2.1. Language Models The LM training data consists of the Tagalog CommonCrawl data-set1 and four smaller Tagalog sets provided …","url":["https://www.isca-speech.org/archive/pdfs/interspeech_2021/wallington21_interspeech.pdf"]}
-{"year":"2021","title":"On the Multilingual Capabilities of Very Large-Scale English Language Models","authors":["J Armengol-Estapé, OG Bonet, M Melero - arXiv preprint arXiv:2108.13349, 2021"],"snippet":"… models (Nozza et al., 2020). Even the multilingual ones2 such as mBERT (Devlin et al., 2018) or XLM-R (Conneau et al., 2019) employ large multilingual datasets based on Wikipedia or CommonCrawl. A very recent work trained …","url":["https://arxiv.org/pdf/2108.13349"]}
-{"year":"2021","title":"On the Robustness of Neural Network: Attacks and Defenses","authors":["M Cheng - 2021"],"snippet":"Page 1. UCLA UCLA Electronic Theses and Dissertations Title On the Robustness of Neural Network: Attacks and Defenses Permalink https://escholarship.org/uc/item/3k2780bg Author Cheng, Minhao Publication …","url":["https://escholarship.org/content/qt3k2780bg/qt3k2780bg.pdf"]}
-{"year":"2021","title":"On the Usability of Transformers-based models for a French Question-Answering task","authors":["O Cattan, C Servan, S Rosset - Recent Advances in Natural Language Processing …, 2021"],"snippet":"… Transformer-based language models such as BERT (Devlin et al., 2019) are pre-trained on largescale data collections sourced from Wikipedia or Common Crawl (CC) with one or multiple training objectives (masked …","url":["https://hal.archives-ouvertes.fr/hal-03336060/document"]}
-{"year":"2021","title":"On the validity of pre-trained transformers for natural language processing in the software engineering domain","authors":["J von der Mosel, A Trautsch, S Herbold - arXiv preprint arXiv:2109.04738, 2021"],"snippet":"… Therefore, most of the available models are pre-trained by large companies on vast amounts of general domain data such as the entire English Wikipedia or the Common Crawl News dataset [5]. While these models achieve …","url":["https://arxiv.org/pdf/2109.04738"]}
-{"year":"2021","title":"On-Line Retrieval of Health Information Based on Language Complexity, Information Customization and Information Quality","authors":["M Alfano - … and Communication Technologies for Ageing Well and …, 2021"],"snippet":"… initiative. The Web Data Commons (WDC)[30] contain all Microformat, Microdata and RDFa (Resource Description Framework in Attributes) data extracted from the open repository of Web crawl data named Common Crawl (CC) …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=9kQgEAAAQBAJ&oi=fnd&pg=PA1&dq=commoncrawl&ots=V3u-4Vufj1&sig=xQGsuQdnwOKvDO0cKw5-XZNUvjM"]}
-{"year":"2021","title":"One to rule them all: Towards Joint Indic Language Hate Speech Detection","authors":["M Bhatia, TS Bhotia, A Agarwal, P Ramesh, S Gupta… - arXiv preprint arXiv …, 2021"],"snippet":"… A summary for each model is as follows: • XLM-RoBERTa: The pre-training of XLM-RoBERTa is based on 100 languages, using around 2.5TB of preprocessed CommonCrawl dataset to train cross-language …","url":["https://arxiv.org/pdf/2109.13711"]}
-{"year":"2021","title":"Open Dataset Archive","authors":["T Weber"],"snippet":"… data: to name an example, while large corpora of tabular data from Web tables have been made available via CommonCrawl [5], the … Common Crawl The Common Crawl Foundation is a also a non-profit organization which …","url":["https://aic.ai.wu.ac.at/~polleres/supervised_theses/Thomas_Weber_BSc_2020.pdf"]}
-{"year":"2021","title":"Open-Domain Conversational Search Assistant with Transformers","authors":["R Ferreira, M Leite, D Semedo, J Magalhaes - arXiv preprint arXiv:2101.08197, 2021"],"snippet":"… Page 6. 6 R. Ferreira et al. – Text-to-Text Transfer Transformer (T5) [26] is a text-to-text model based on the encoder-decoder Transformer architecture, pre-trained on the large C4 corpus, which was derived from Common …","url":["https://arxiv.org/pdf/2101.08197"]}
-{"year":"2021","title":"Opening up Military Innovation: Causal Effects of 'Bottom-Up'Reforms to US Defense Research","authors":["ST Howell, J Rathje, J Van Reenen, J Wong - Available at SSRN 3825034, 2021"],"snippet":"Page 1. Opening up Military Innovation: Causal Effects of 'Bottom-Up' Reforms to US Defense Research Sabrina T. Howell, Jason Rathje, John Van Reenen and Jun Wong ∗ April 8, 2021 Abstract When investing in research …","url":["https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3825034"]}
-{"year":"2021","title":"OpenViDial: A Large-Scale, Open-Domain Dialogue Dataset with Visual Contexts","authors":["Y Meng, S Wang, Q Han, X Sun, F Wu, R Yan, J Li - arXiv preprint arXiv:2012.15015, 2020"],"snippet":"… and the open-sourced OCR model suffices to fulfill our need. With text-free images in hand, we pair them with texts. Texts are randomly selected from the CommonCrawl English corpus, then added to the images. Texts in images …","url":["https://arxiv.org/pdf/2012.15015"]}
-{"year":"2021","title":"Operationalizing a National Digital Library: The Case for a Norwegian Transformer Model","authors":["PE Kummervold, J De la Rosa, F Wetjen, SA Brygfjeld - arXiv preprint arXiv …, 2021"],"snippet":"… For resource-rich languages such as Chinese, En- glish, French, and Spanish, collections of texts from open sources such as Wikipedia (2021a), variations of Common Crawl data (2021), and other open-source corpora such as the BooksCorpus (Zhu et al., 2015) are …","url":["https://arxiv.org/pdf/2104.09617"]}
-{"year":"2021","title":"Opinion Classification via Word and Emoji Embedding Models with LSTM","authors":["I Rabbimov, S Kobilov, I Mporas - International Conference on Speech and Computer, 2021"],"snippet":"… Twitter. 1,661. 300. The UzbekFastText1 word vector is the fastText model trained with crawled texts published on Wikipedia using Common Crawl [36]. UzbekFastText2 was presented in [37] and it is a 300-dimensional Uzbek …","url":["https://www.researchgate.net/profile/Ilyos-Rabbimov/publication/354758888_Opinion_Classification_via_Word_and_Emoji_Embedding_Models_with_LSTM/links/614e7a91154b3227a8a8b8b8/Opinion-Classification-via-Word-and-Emoji-Embedding-Models-with-LSTM.pdf"]}
-{"year":"2021","title":"Out-of-vocabulary but not meaningless: Evidence for semantic-priming effects in pseudoword processing","authors":["D Gatti, M Marelli, L Rinaldi - 2021"],"snippet":"… The model was trained on Common Crawl (around 630 billion words) and Wikipedia (around 9 billion words) using the Continuous Bag of … The model was trained on Common Crawl and Italian Wikipedia (around 11 billion words) using …","url":["https://psyarxiv.com/y2fm3/download?format=pdf"]}
-{"year":"2021","title":"Overcoming Data Challenges in Machine Translation","authors":["H Khayrallah - 2021"],"snippet":"Page 1. OVERCOMING DATA CHALLENGES IN MACHINE TRANSLATION by Huda Khayrallah A dissertation submitted to The Johns Hopkins University in conformity with the requirements for the degree of Doctor of Philosophy. Baltimore, Maryland July, 2021 …","url":["https://jscholarship.library.jhu.edu/bitstream/handle/1774.2/64381/KHAYRALLAH-DISSERTATION-2021.pdf?sequence=1"]}
-{"year":"2021","title":"Overlapping Community Detection in Social Networks","authors":["A Panchal - 2021"],"snippet":"Page 1. San Jose State University SJSU ScholarWorks Master's Projects Master's Theses and Graduate Research Spring 5-25-2021 Overlapping Community Detection in Social Networks Akshar Panchal Follow this and additional …","url":["https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=2011&context=etd_projects"]}
-{"year":"2021","title":"Overview of Touché 2021: Argument Retrieval","authors":["A Bondarenko, L Gienapp, M Fröbe, M Beloucif… - 2021"],"snippet":"… Other argument retrieval systems such as ArgumenText [3] and TARGER [4] take advantage of the large web document collection Common Crawl, but their ability to reliably retrieve arguments to support sides in a decision process is limited …","url":["https://webis.de/downloads/publications/papers/bondarenko_2021b.pdf"]}
-{"year":"2021","title":"PAGnol: An Extra-Large French Generative Model","authors":["J Launay, EL Tommasone, B Pannier, F Boniface… - arXiv preprint arXiv …, 2021"],"snippet":"… Having been pre-trained on Common Crawl-based corpora, our models are certainly not immune from toxic content generation. Gehman et al. (2020) explored two main ways to filter toxic outputs, one being based on the pursuing the pretraining on less …","url":["https://arxiv.org/pdf/2110.08554"]}
-{"year":"2021","title":"PALI at SemEval-2021 Task 2: Fine-Tune XLM-RoBERTa for Word in Context Disambiguation","authors":["S Xie, J Ma, H Yang, L Jiang, Y Mo, J Shen - arXiv preprint arXiv:2104.10375, 2021"],"snippet":"… 2017). Especially, the XLM-RoBERTa (Conneau et al., 2020) model is a newly released large cross-lingual language model based on RoBERTa and is trained on 2.5TB filtered CommonCrawl data in 100 languages. Different …","url":["https://arxiv.org/pdf/2104.10375"]}
-{"year":"2021","title":"PAN: Prototype-based Adaptive Network for Robust Cross-modal Retrieval","authors":["Z Zeng, S Wang, N Xu, W Mao - Proceedings of the 44th International ACM SIGIR …, 2021"],"snippet":"Page 1. PAN: Prototype-based Adaptive Network for Robust Cross-modal Retrieval Zhixiong Zeng, Shuai Wang, Nan Xu, Wenji Mao∗ SKL-MCCS, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China …","url":["https://dl.acm.org/doi/abs/10.1145/3404835.3462867"]}
-{"year":"2021","title":"PanGu-$\\alpha $: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation","authors":["W Zeng, X Ren, T Su, H Wang, Y Liao, Z Wang, X Jiang… - arXiv preprint arXiv …, 2021"],"snippet":"… To build Chinese corpus with comprehensive coverage, we collect a large amount of data from a wide range of resources, including Common Crawl, e-Books, encyclopedias, news, and so on … Common Crawl 176.2B 62.81 …","url":["https://arxiv.org/pdf/2104.12369"]}
-{"year":"2021","title":"PARADISE: Exploiting Parallel Data for Multilingual Sequence-to-Sequence Pretraining","authors":["M Reid, M Artetxe - arXiv preprint arXiv:2108.01887, 2021"],"snippet":"Page 1. PARADISE: Exploiting Parallel Data for Multilingual Sequence-to-Sequence Pretraining Machel Reid The University of Tokyo machelreid@weblab.tu-tokyo.ac.jp Mikel Artetxe Facebook AI Research artetxe@fb.com Abstract …","url":["https://arxiv.org/pdf/2108.01887"]}
-{"year":"2021","title":"Parallel feature weight decay algorithms for fast development of machine translation models","authors":["E Biçici - Machine Translation, 2021"],"snippet":"Parallel feature weight decay algorithms, parfwd, are engineered for languageand task-adaptive instance selection to build distinct machine translation (.","url":["https://link.springer.com/article/10.1007/s10590-021-09275-z"]}
-{"year":"2021","title":"Parallelizing Legendre Memory Unit Training","authors":["N Chilkuri, C Eliasmith - arXiv preprint arXiv:2102.11417, 2021"],"snippet":"… After showing that the training of this simplified variant can be 1https:// commoncrawl.org … Therefore, we construct parameter efficient models that em- ploy just the DN layer, with d = 1 and θ = maxlen. We use 300D Glove …","url":["https://arxiv.org/pdf/2102.11417"]}
-{"year":"2021","title":"Paraphrase Generation as Unsupervised Machine Translation","authors":["C Fan, Y Tian, Y Meng, N Peng, X Sun, F Wu, J Li - arXiv preprint arXiv:2109.02950, 2021"],"snippet":"… LDA and K-means algorithms are performed on part of the the CommonCrawl corpus containing 10 billion English tokens … An overview of deriving the UMT-Multi model is shown in Figure 1. Up to now, UMT-Multi is purely based on unlabeled commoncrawl corpus …","url":["https://arxiv.org/pdf/2109.02950"]}
-{"year":"2021","title":"Pathogens Are Linked to Human Moral Systems Across Time and Space","authors":["M Atari, NK Reimer, J Graham, J Hoover, B Kennedy… - 2021"],"snippet":"Infectious diseases have been an impending threat to the survival of individuals and groups throughout our evolutionary history. As a result, humans have developed psychological pathogen-avoidance mechanisms and groups have developed …","url":["https://psyarxiv.com/tnyh9/download?format=pdf"]}
-{"year":"2021","title":"Pegasus@ Dravidian-CodeMix-HASOC2021: Analyzing Social Media Content for Detection of Offensive Text","authors":["PK Jada, K Yasaswini, K Puranik, A Sampath… - arXiv preprint arXiv …, 2021"],"snippet":"… One of the reason for the unparalleled performance is that it was trained on a mammoth 2.5 TB of CommonCrawl data [25]. It was trained with MLM loss as it’s objective on 100 different languages, and it shares similar training routine as the …","url":["https://arxiv.org/pdf/2111.09836"]}
-{"year":"2021","title":"PENGEMBANGAN APLIKASI INFORMATION GATHERING MENGGUNAKAN METODE HYBRID SCAN BERBASIS GRAPHICAL USER INTERFACE","authors":["M Riasetiawan, A Wisnuaji, D Hariyadi, T Febrianto - Cyber Security dan Forensik …, 2021"],"snippet":"… F-Secure Riddler, Cert Spotter, Hacker Target, Certificate Search, DN Dumpster, AlienFault, Rapid DNS, URL Scan, Threat Crowd, Wayback Machine, dan Common Crawl … q=\"+self.url, 1 2 \"https://riddler.io/search …","url":["http://202.0.92.5/saintek/cybersecurity/article/download/2449/1994"]}
-{"year":"2021","title":"Penn-Helsinki Parsed Corpus of Early Modern English: First Parsing Results and Analysis","authors":["S Kulick, N Ryant, B Santorini - arXiv preprint arXiv:2112.08532, 2021"],"snippet":"We present the first parsing results on the Penn-Helsinki Parsed Corpus of Early Modern English (PPCEME), a 1.9 million word treebank that is an important resource for research in syntactic change. We describe key features of PPCEME that …","url":["https://arxiv.org/pdf/2112.08532"]}
-{"year":"2021","title":"Personalized sentiment classification of customer reviews via an interactive attributes attention model","authors":["Y Zhang, J Wang, X Zhang - Knowledge-Based Systems, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0950705121003981"]}
-{"year":"2021","title":"Phishing Detection Methods: A Review","authors":["M Alanezi - 2021"],"snippet":"Abstract The web has turned into a principal part of our conventional social and financial activities. The web isn't significant for singular clients just yet additionally for associations, since associations that offer web-based exchanging can accomplish …","url":["https://techniumscience.com/index.php/technium/article/view/4973/1723"]}
-{"year":"2021","title":"PhoMT: A High-Quality and Large-Scale Benchmark Dataset for Vietnamese-English Machine Translation","authors":["L Doan, LT Nguyen, NL Tran, T Hoang, DQ Nguyen - arXiv preprint arXiv:2110.12199, 2021"],"snippet":"We introduce a high-quality and large-scale Vietnamese-English parallel dataset of 3.02M sentence pairs, which is 2.9M pairs larger than the benchmark Vietnamese-English machine translation corpus IWSLT15. We conduct experiments comparing strong …","url":["https://arxiv.org/pdf/2110.12199"]}
-{"year":"2021","title":"Planning with Entity Chains for Abstractive Summarization","authors":["S Narayan, Y Zhao, J Maynez, G Simoes, R McDonald - arXiv preprint arXiv …, 2021"],"snippet":"… Pre-training Datasets. Following Zhang et al. (2019), our model pretraining also relied on two large web corpus which were processed to look like plain text: (i) C4 (Raffel et al., 2019) is composed of 350M Web-pages …","url":["https://arxiv.org/pdf/2104.07606"]}
-{"year":"2021","title":"Planning with Learned Entity Prompts for Abstractive Summarization","authors":["S Narayan, Y Zhao, J Maynez, G Simões, V Nikolaev… - Transactions of the …, 2021"],"snippet":"We introduce a simple but flexible mechanism to learn an intermediate plan to ground the generation of abstractive summaries. Specifically, we prepend (or prompt) target summaries with entity chains—ordered sequences of entities mentioned in the …","url":["https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00438/108867"]}
-{"year":"2021","title":"Polish Web resources described in the\" Polish World\" directory (1997). Characteristics of domains and their conservation state","authors":["M Wilkowski - Archiwa-Kancelarie-Zbiory, 2020"],"snippet":"… Sep. 2008, p. 6. https://hal-bnf.archives-ouvertes.fr/hal-01098538 (accessed 19.09.2020). 18 Common Crawl, https://commoncrawl.org/ (accessed 12.09.2020). 19 HTTP Archive, https://httparchive.org/ (accessed 12.09.2020). Page 8. 126 Marcin Wilkowski …","url":["https://apcz.umk.pl/czasopisma/index.php/AKZ/article/download/AKZ.2020.005/28213"]}
-{"year":"2021","title":"Political Attacks in 280 Characters or Less: A New Tool for the Automated Classification of Campaign Negativity on Social Media","authors":["V Petkevic, A Nai - American Politics Research, 2021"],"snippet":"Negativity in election campaign matters. To what extent can the content of social media posts provide a reliable indicator of candidates' campaign negativity? We introduce and critically assess an automated classification procedure that we trained …","url":["https://journals.sagepub.com/doi/pdf/10.1177/1532673X211055676"]}
-{"year":"2021","title":"Political Polarization in Online News Consumption","authors":["K Garimella, T Smith, R Weiss, R West - arXiv preprint arXiv:2104.06481, 2021"],"snippet":"… The Common Crawl project1 regularly crawls the Web and releases datasets of the discovered webpages on a regular schedule, which are generally considered the most extensive publicly available sources …","url":["https://arxiv.org/pdf/2104.06481"]}
-{"year":"2021","title":"PoolRank: Max/Min Pooling-based Ranking Loss for Listwise Learning & Ranking Balance","authors":["Z Chen, C Eickhoff - arXiv preprint arXiv:2108.03586, 2021"],"snippet":"… Our GloVe word embeddings are trained on the Common Crawl dataset 2. We use an Adam optimizer [13] with 0.0001 learning rate to train all models … Most queries 1https://www.tensor ow.org/ 2https://commoncrawl …","url":["https://arxiv.org/pdf/2108.03586"]}
-{"year":"2021","title":"Postal address extraction from the web: a comprehensive survey","authors":["M Kayed, S Dakrory, AA Ali - Artificial Intelligence Review, 2021"],"snippet":"The Web is a source of information for Location-Based Service (LBS) applications. These applications lack postal addresses for the user's Point of In.","url":["https://link.springer.com/article/10.1007/s10462-021-09983-1"]}
-{"year":"2021","title":"Practical Wavelet Tree Construction","authors":["P Dinklage, J Ellert, J Fischer, F Kurpicz, M Löbel - Journal of Experimental …, 2021","VIN LÖBEL - 2021"],"snippet":"… alphabet. We denote the resulting file by RuWB. Suffix Array of Common Crawl We construct the suffix array [35] of CommonCrawl, which is a permutation of the positive integers smaller than the length of CommonCrawl. We …","url":["https://dl.acm.org/doi/pdf/10.1145/3457197","https://www.kurpicz.org/assets/pdfs/jea_2021.pdf"]}
-{"year":"2021","title":"Pre-trained Language Models for Tagalog with Multi-source Data","authors":["S Jiang, Y Fu, X Lin, N Lin - CCF International Conference on Natural Language …, 2021"],"snippet":"… [19] to process, filter and classify Common Crawl, which is a non-profit organization that produces and maintains an open, freely available repository of crawled data from the web. The filtering step used to create OSCAR involves …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88480-2_17"]}
-{"year":"2021","title":"Pre-trained Language Models in Biomedical Domain: A Survey from Multiscale Perspective","authors":["B Wang, Q Xie, J Pei, P Tiwari, Z Li - arXiv preprint arXiv:2110.05006, 2021"],"snippet":"Pre-trained language models have been the de facto paradigm for most natural language processing (NLP) tasks. In the biomedical domain, which also benefits from NLP techniques, various pre-trained language models were proposed by …","url":["https://arxiv.org/pdf/2110.05006"]}
-{"year":"2021","title":"Pre-trained Models and Evaluation Data for the Myanmar Language","authors":["S Jiang, X Huang, X Cai, N Lin - International Conference on Neural Information …, 2021"],"snippet":"… On the one hand, we utilized all the Myanmar data from the OSCAR corpus 3 , a humongous multilingual corpus whose texts all come from the Common Crawl corpus 4 . In addition, articles on CC-100 [16] were also used as part of our corpus …","url":["https://link.springer.com/chapter/10.1007/978-3-030-92310-5_52"]}
-{"year":"2021","title":"Pre-Trained Transformer-Based Language Models for Sundanese","authors":["W Wongso, H Lucky, D Suhartono - 2021"],"snippet":"… Data The dataset used during pre-training consists of Sundanese subsets of multilingual common-crawl corpora of OSCAR [18], CC-100 [19, 20], and C4 [21]. They are of the size 141KB, 15MB, and 464MB, respectively. Seeing …","url":["https://www.researchsquare.com/article/rs-907893/latest.pdf"]}
-{"year":"2021","title":"Pre-trained Word Embeddings for Malayalam Language: A Review","authors":["KR Rahmath, PCR Raj, PC Rafeeque - … on Artificial Intelligence and Smart Systems …, 2021"],"snippet":"… pre-trained on 17 In- dian languages, and their transliterated counterparts including Malayalam [8]. The corpora used for pre-training process are Wikipedia, Common Crawl, PMINDIA and … This dataset has been augmented …","url":["https://ieeexplore.ieee.org/abstract/document/9396042/"]}
-{"year":"2021","title":"Pre-training Methods in Information Retrieval","authors":["Y Fan, X Xie, Y Cai, J Chen, X Ma, X Li, R Zhang, J Guo… - arXiv preprint arXiv …, 2021"],"snippet":"The core of information retrieval (IR) is to identify relevant information from large-scale resources and return it as a ranked list to respond to user's information need. Recently, the resurgence of deep learning has greatly advanced this field and leads …","url":["https://arxiv.org/pdf/2111.13853"]}
-{"year":"2021","title":"Predicting cross-linguistic adjective order with information gain","authors":["W Dyer, R Futrell, Z Liu, G Scontras - arXiv preprint arXiv:2012.15263, 2020"],"snippet":"… 4.1 Data Our study relies on two types of source data, both extracted from the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal De- pendencies (Ginter et al., 2017; Zeman et al., 2017) a set of …","url":["https://arxiv.org/pdf/2012.15263"]}
-{"year":"2021","title":"Predicting Depression and Suicide Ideation in the Canadian Population Using Social Media Data","authors":["R Skaik - 2021"],"snippet":"Page 1. Predicting Depression and Suicide Ideation in the Canadian Population Using Social Media Data by Ruba Skaik Thesis submitted to the University of Ottawa in partial Fulfillment of the requirements for the Ph.D. degree in Computer Science …","url":["https://ruor.uottawa.ca/bitstream/10393/42346/7/Skaik_Ruba_2021_thesis.pdf"]}
-{"year":"2021","title":"Predicting leadership perception with large-scale natural language data","authors":["S Bhatia, CY Olivola, N Bhatia, A Ameen - The Leadership Quarterly, 2021"],"snippet":"","url":["https://www.sciencedirect.com/science/article/pii/S1048984321000400"]}
-{"year":"2021","title":"Predicting Next Dialogue Action in Emotionally Loaded Conversation","authors":["D Deksne, R Skadiņš - Proceedings of the Future Technologies Conference, 2021"],"snippet":"… the Latvian Wikipedia data 2 and trained with our internal monolingual corpora, as well as several BERT models: multilingual BERT [26], BERT-LV [27], Language-agnostic BERT Sentence Embedding (LaBSE) [28], and the multilingual XLM-R model trained …","url":["https://link.springer.com/chapter/10.1007/978-3-030-89906-6_19"]}
-{"year":"2021","title":"Predicting the Performance of Multilingual NLP Models","authors":["A Srinivasan, S Sitaram, T Ganu, S Dandapat, K Bali… - arXiv preprint arXiv …, 2021"],"snippet":"… The pretraining procedure makes use of only unlabelled data (raw text), which is easy to obtain for a large number of languages from various sources including CommonCrawl1 and Wikipedia dumps2. These models can then be used to solve a …","url":["https://arxiv.org/pdf/2110.08875"]}
-{"year":"2021","title":"Preprint from: https://www. gipp. com/pub","authors":["T Spinde, L Rudnitckaia, K Sinha, F Hamborg"],"snippet":"… We scraped articles from both news outlets, published in the last decade, from 2010 to 2020, from Common Crawl [4]. For preprocessing, we use Genism simple preprocessing and generate n-grams. 3.4 Linear mapping between vector spaces …","url":["https://www.gipp.com/wp-content/papercite-data/pdf/spinde2021.pdf"]}
-{"year":"2021","title":"PREPRINT–ARTICLE IN PRESS: Kennedy, B., Atari, M., Mostafazadeh Davani, A., Hoover, J., Omrani, A., Graham, J., & Dehghani, M.(in press). Moral Concerns are …","authors":["B Kennedy"],"snippet":"… of posts, GloVe word embedding vectors (Pennington et al., 2014), which were trained on text from the Common Crawl4, were mapped to the individual words in the posts and subsequently averaged element-wise (ie, across the dimensions of the embedding). The …","url":["https://files.osf.io/v1/resources/uqmty/providers/osfstorage/5eb44939a2199500cd5d4b7c?format=pdf&action=download&direct&version=2"]}
-{"year":"2021","title":"Prescriptions in NLP with Transformer Models","authors":["OEC Zaragoza"],"snippet":"… is optimized BERT. XLMR is trained with a filtered version of CommonCrawl data with 100 languages and it uses a subword tokenization, SentencePiece [20] with a unigram language model [19]. mT5 Multilingual TexttoText …","url":["https://payberah.github.io/files/download/students/omar_contreras_master_thesis.pdf"]}
-{"year":"2021","title":"Pretrained models and evaluation data for the Khmer language","authors":["S Jiang, S Fu, N Lin, Y Fu - Tsinghua Science and Technology, 2021"],"snippet":"… On the one hand, we use all the central Khmer data from the OSCAR corpus , a large multilingual corpus whose texts come from the Common Crawl corpus . Although Common Crawl comprises scraped data from the Internet and covers a …","url":["https://ieeexplore.ieee.org/iel7/5971803/9645434/09645441.pdf"]}
-{"year":"2021","title":"Prevalence in News Media of Two Competing Hypotheses about COVID-19 Origins","authors":["D Rozado - Social Sciences, 2021"],"snippet":"… 2. Methods. The textual content of news and opinion articles from the outlets listed in Figure 1 is available in the outlets online domains and/or public cache repositories such as Google cache, The Internet Wayback Machine …","url":["https://www.mdpi.com/2076-0760/10/9/320/htm"]}
-{"year":"2021","title":"Prevalence of Prejudice-Denoting Words in News Media Discourse: A Chronological Analysis","authors":["D Rozado, M Al-Gharbi, J Halberstadt - Social Science Computer Review, 2021"],"snippet":"This work analyzes the prevalence of words denoting prejudice in 27 million news and opinion articles written between 1970 and 2019 and published in 47 of the most popular news media outlets in the...","url":["https://journals.sagepub.com/doi/abs/10.1177/08944393211031452"]}
-{"year":"2021","title":"Preventing author profiling through zero-shot multilingual back-translation","authors":["DI Adelani, M Zhang, X Shen, A Davody, T Kleinbauer… - arXiv preprint arXiv …, 2021"],"snippet":"… The languages chosen are German (DE), Spanish (ES), French (FR), Japanese (JA), Russian (RU), and Chinese (ZH) based on the large amount of resources they have on OPUS (Tiedemann, 2012) and Common Crawl corpora 2 …","url":["https://arxiv.org/pdf/2109.09133"]}
-{"year":"2021","title":"Price Determinants of Airbnb Apartments","authors":["A Piispanen - 2021"],"snippet":"Page 1. Antti Piispanen Price Determinants of Airbnb Apartments An Approach with Deep Language Representations Master of Science Thesis Faculty of Information Technology and Communication Sciences Examiner …","url":["https://trepo.tuni.fi/bitstream/handle/10024/130318/PiispanenAntti.pdf?sequence=2"]}
-{"year":"2021","title":"Prioritizing Original News on Facebook","authors":["X Ni, S Bu, I Markov - arXiv preprint arXiv:2102.08465, 2021"],"snippet":"… There are other open-source crawlers that serve the same purpose. Common Crawl3 is a well-maintained open repository of Web crawl data that can be accessed and analyzed by anyone. We limit news articles in the graph to …","url":["https://arxiv.org/pdf/2102.08465"]}
-{"year":"2021","title":"Privacy and AI Ethics–Understanding the convergences and tensions for the responsible development of machine learning","authors":["I Cofone, O Abimana, B Bonan, E Grand-Pierre, A Qarri"],"snippet":"Context. The democratization of mobile systems and the development of information technologies have been accompanied by a massive increase in the amount and the diversity of data collected about individuals, often referred to as Big Data …","url":["https://sebastiengambs.openum.ca/files/sites/82/2021/11/OPC_final.pdf"]}
-{"year":"2021","title":"Privacy-Preserving Learning of Human Activity Predictors in Smart Environments","authors":["S Zehtabian, S Khodadadeh, L Bölöni, D Turgut - arXiv preprint arXiv:2101.06564"],"snippet":"… However, many deep learning algorithms work best under big data regimes, where the number of data samples are counted from the tens of thousands (eg the MNIST dataset) to 500 billion (the Common Crawl dataset used to train the GPT-3 model) …","url":["https://arxiv.org/pdf/2101.06564"]}
-{"year":"2021","title":"PrivaSeer: A Privacy Policy Search Engine","authors":["S Wilson"],"snippet":"… The URLs in the Common Crawl archive were first filtered based on a selection criteria that took advantage of the fact that most privacy policy URLs either have the word 'privacy' or the words 'data' and 'protection' in them … 6 https://commoncrawl.org …","url":["https://link.springer.com/content/pdf/10.1007/978-3-030-74296-6_22.pdf"]}
-{"year":"2021","title":"Probabilistic Text Entry—Case Study 3","authors":["K Vertanen - Intelligent Computing for Interactive System Design …, 2021"],"snippet":"Page 1. 7Probabilistic Text Entry—Case Study 3 Keith Vertanen The reading and writing of text is an activity that has long dominated our interac tions with computers. Early user interfaces often displayed only text and relied on input obtained via a desktop keyboard …","url":["https://dl.acm.org/doi/abs/10.1145/3447404.3447420"]}
-{"year":"2021","title":"Probing Multilingual Language Models for Discourse","authors":["M Kurfalı, R Östling - arXiv preprint arXiv:2106.04832, 2021"],"snippet":"… the XLM-tlm. Instead, it is a RoBERTa model (Liu et al., 2019), which is an optimized version of BERT, trained on 2.5 TB of cleaned CommonCrawl data covering 100 languages (Conneau et al., 2020). There are two released …","url":["https://arxiv.org/pdf/2106.04832"]}
-{"year":"2021","title":"Proceedings of the First Workshop on Weakly Supervised Learning (WeaSuL)","authors":["MA Hedderich, B Roth, K Kann, B Plank, A Ratner… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. WeaSuL 2021 Proceedings of the First Workshop on Weakly Supervised Learning (WeaSuL) May 7, 2021 Co-located with ICLR (Online) arXiv:2107.03690 v1 [cs.LG] 8 Jul 2021 Page 2. Introduction Welcome to WeaSuL …","url":["https://arxiv.org/pdf/2107.03690"]}
-{"year":"2021","title":"Processing large-scale Internet topology data to model Autonomous System Networks","authors":["K Bakhshaliyev - 2020"],"snippet":"… such interrelated data. The number of Facebook users grew from 500 million in 2010 to 1.5 billion in 2014. The Common Crawl web corpora [29] covered for 2012 contains 3.5 billion web pages and 128 billion hyperlinks between …","url":["https://scholarworks.unr.edu/bitstream/handle/11714/7672/Bakhshaliyev_unr_0139D_13330.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"Proof Artifact Co-training for Theorem Proving with Language Models","authors":["JM Han, J Rute, Y Wu, EW Ayers, S Polu - arXiv preprint arXiv:2102.06203, 2021"],"snippet":"Page 1. Proof Artifact Co-training for Theorem Proving with Language Models Jesse Michael Han 1 Jason Rute 2 Yuhuai Wu 3 Edward W. Ayers 4 Stanislas Polu 5 Abstract Labeled data for imitation learning of theorem proving …","url":["https://arxiv.org/pdf/2102.06203"]}
-{"year":"2021","title":"Propaganda in Press: Challenges of Automatic Detection","authors":["D Pušelj, T Škalec - Text Analysis and Retrieval 2020 Course Project …"],"snippet":"… trained on cased Wikipedia text. RoBERTa has 125M parameters with 12 layers, 768 hidden states, 3072 feed-forward hidden states and 8 heads and is trained on CommonCrawl data in 100 languages. The XLNet is a Large …","url":["https://www.fer.unizg.hr/_download/repository/TAR-2020-ProjectReports.pdf#page=61"]}
-{"year":"2021","title":"ProphetNet-X: Large-Scale Pre-training Models for English, Chinese, Multi-lingual, Dialog, and Code Generation","authors":["W Qi, Y Gong, Y Yan, C Xu, B Yao, B Zhou, B Cheng… - arXiv preprint arXiv …, 2021"],"snippet":"… models with downstream task finetuning scripts, including ProphetNet-En pre-trained with 160GB English raw text, ProphetNet-Zh pre-trained with 160GB Chinese raw text, ProphetNet-Multi with 101GB Wiki-100 corpus and …","url":["https://arxiv.org/pdf/2104.08006"]}
-{"year":"2021","title":"Proposed Use of a Conversational Agent for Patient Empowerment","authors":["M Alfano, J Kellett, B Lenzitti, M Helfert - 2021"],"snippet":"… Depression 1 https://schema.org/ 2 https://health-lifesci.schema.org/ 3 http:// webdatacommons.org/ 4 http://commoncrawl.org o Dermatitis o Tuberculosis 4.2 Creation of Repository of Schema.org and Health-lifesci Structured Data …","url":["https://www.scitepress.org/Papers/2021/104144/104144.pdf"]}
-{"year":"2021","title":"Protecting Anonymous Speech: A Generative Adversarial Network Methodology for Removing Stylistic Indicators in Text","authors":["R Balakrishnan, S Sloan, A Aswani - arXiv preprint arXiv:2110.09495, 2021"],"snippet":"With Internet users constantly leaving a trail of text, whether through blogs, emails, or social media posts, the ability to write and protest anonymously is being eroded because artificial intelligence, when given a sample of previous work, can match text …","url":["https://arxiv.org/pdf/2110.09495"]}
-{"year":"2021","title":"Psychographic traits identification based on political ideology: An author analysis study on Spanish politicians' tweets posted in 2020","authors":["JA García-Díaz, R Colomo-Palacios, R Valencia-García - Future Generation …, 2021"],"snippet":"… The pre-trained model of Spanish have been trained from Common Crawl and Wikipedia but adjusted with the PoliCorpus 2020 during training. SE assemble a single vector of dimension 300 for a sequence of the individual word embeddings …","url":["https://www.sciencedirect.com/science/article/pii/S0167739X21004921"]}
-{"year":"2021","title":"Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning","authors":["J Wang, C Xu, F Guzman, A El-Kishky, Y Tang… - arXiv preprint arXiv …, 2021"],"snippet":"… While this type of attack might appear unrealistic, the nature of the largest collections of monolingual data like Common Crawl (Buck et al., 2014; Wenzek et al., 2020; El-Kishky et al., 2020) (which contains blogs and other …","url":["https://arxiv.org/pdf/2107.05243"]}
-{"year":"2021","title":"QMUL-SDS at EXIST: Leveraging Pre-trained Semantics and Lexical Features for Multilingual Sexism Detection in Social Networks","authors":["A Jiang, A Zubiaga - 2021"],"snippet":"… RoBERTa model (XLM-R) [7] has extended the way of pre-training MLM by scaling the amount of data by two orders of magnitude (from Wikipedia to Common Crawl) and training … FastText + TextCNN: we use the Fasttext …","url":["http://www.zubiaga.org/publications/files/jiang2021exist.pdf"]}
-{"year":"2021","title":"Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets","authors":["I Caswell, J Kreutzer, L Wang, A Wahab, D van Esch… - arXiv preprint arXiv …, 2021"],"snippet":"… CC: CommonCrawl; TED-6: da, cr, sl, sk, lt, et; TED-45: 45-language subset of (Qi … et al., 2019, 2020) is a set of monolingual corpora extracted from Common Crawl snapshots, specifically from the plain text WET format distributed by Common Crawl which removes …","url":["https://arxiv.org/pdf/2103.12028"]}
-{"year":"2021","title":"QuALITY: Question Answering with Long Input Texts, Yes!","authors":["RY Pang, A Parrish, N Joshi, N Nangia, J Phang… - arXiv preprint arXiv …, 2021"],"snippet":"To enable building and testing models on long-document comprehension, we introduce QuALITY, a multiple-choice QA dataset with context passages in English that have an average length of about 5,000 tokens, much longer than typical current …","url":["https://arxiv.org/pdf/2112.08608"]}
-{"year":"2021","title":"Quantifying context with and without statistical language models","authors":["CL Jacobs, B Hall"],"snippet":"… Others, such as the Common Crawl (Smith et al., 2013) are a hodge-podge grabbed from across the entire internet, which may include forum posts, blogs, tweets, or computer code, in addition to news articles, fan fiction, and so on …","url":["https://osf.io/mpqut/download"]}
-{"year":"2021","title":"Quantum-inspired Hierarchical Attention Mechanism for Question Answering","authors":["P Guo - 2021 IEEE 33rd International Conference on Tools with …, 2021"],"snippet":"… We initialize word embeddings with 300-dimensional Glove word vectors pretrained from the 840B Common Crawl corpus. The LSTM hidden size is set to 100 over WikiQA and TrecQA. AdamOptimizer is used for updating parameters with …","url":["https://ieeexplore.ieee.org/abstract/document/9643371/"]}
-{"year":"2021","title":"Query2Prod2Vec Grounded Word Embeddings for eCommerce","authors":["F Bianchi, J Tagliabue, B Yu - arXiv preprint arXiv:2104.02061, 2021"],"snippet":"Page 1. Query2Prod2Vec Grounded Word Embeddings for eCommerce Federico Bianchi Bocconi University Milano, Italy f.bianchi@unibocconi.it Jacopo Tagliabue∗ Coveo Labs New York, USA jtagliabue@coveo.com …","url":["https://arxiv.org/pdf/2104.02061"]}
-{"year":"2021","title":"Question Classification for the Travel Domain using Deep Contextualized Word Embedding Models","authors":["C Weerakoon, S Ranathunga - 2021 Moratuwa Engineering Research Conference …, 2021"],"snippet":"… XLNet [5] has pre-trained data over 129 GB collected from BooksCorpus, Wikipedia, CommonCrawl, Giga5, and ClueWeb 2012-B. XLNet at its core uses the permutation technique to predict tokens in random order contrary to masked model of BERT …","url":["https://ieeexplore.ieee.org/abstract/document/9525789/"]}
-{"year":"2021","title":"Re-entry Prediction for Online Conversations via Self-Supervised Learning","authors":["L Wang, X Zeng, H Hu, KF Wong, D Jiang - arXiv preprint arXiv:2109.02020, 2021"],"snippet":"… For the parameters in the main model, we first initialize the embedding layer with 200-dimensional Glove embedding (Pennington et al., 2014), whose Twitter version is used for the Twitter dataset and Common Crawl version …","url":["https://arxiv.org/pdf/2109.02020"]}
-{"year":"2021","title":"Re-Evaluating GermEval17 Using German Pre-Trained Language Models","authors":["M Aßenmacher, A Corvonato, C Heumann - arXiv preprint arXiv:2102.12330, 2021"],"snippet":"… DBMDZ combine Wikipedia, EU Bookshop (Skadin š et al., 2014), Open Subtitles (Lison and Tiedemann, 2016), CommonCrawl (Ortiz Suárez et al., 2019), ParaCrawl (Espl`a-Gomis et al., 2019) and News Crawl (Haddow …","url":["https://arxiv.org/pdf/2102.12330"]}
-{"year":"2021","title":"Read & Improve: A Novel Reading Tutoring System","authors":["R Watson, E Kochmar - EDM 2021: Educational Data Mining, 2021"],"snippet":"… To source news content, R&I monitors both RSS Feeds from news websites and the publicly available Common Crawl News (CC-NEWS) Dataset.3 A fully automated Indexing Pipeline (RIIP, herein) processes article URLs …","url":["https://purehost.bath.ac.uk/ws/files/219929943/EDM_2021.pdf"]}
-{"year":"2021","title":"Reading Key Figures from Annual Reports","authors":["S Nordin Hällgren - 2021"],"snippet":"Page 1. Reading Numbers from Annual Reports Using OCR and NLP to Extract Key Figures from Documents Master's thesis in Engineering Mathematics and Computational Science Sara Nordin Hällgren DEPARTMENT OF MATHEMATICAL SCIENCES …","url":["https://odr.chalmers.se/bitstream/20.500.12380/302433/1/Master_thesis_Sara_Nordin_H%C3%A4llgren_210604.pdf"]}
-{"year":"2021","title":"Recent advances of low-resource neural machine translation","authors":["R Haque, CH Liu, A Way - Machine Translation, 2021"],"snippet":"… As for the low-resource pairs, monolingual data was provided by the Common Crawl (Buck et al. ) and English monolingual data is blog … 12.Buck C, Heafield K, van Ooyen B (2014) N-gram counts and language models from the common crawl. In …","url":["https://link.springer.com/article/10.1007/s10590-021-09281-1"]}
-{"year":"2021","title":"Recent Automatic Post Editing Research","authors":["H Moon, C Park, S Eo, J Seo, H Lim - Journal of Digital Convergence, 2021"],"snippet":"… 진행되었다. 사전학습에는 100개 언어에 대한 Common Crawl[21] 단일 언어 말 뭉치가 이용된다 … 도출하였다. 사전학습에는 25개 언어에 대한 Common Crawl 단 일 언어데이터를 활용하였고, BART[24]에서 제안된 자 기 지도 학습 방법론을 차용하였다 …","url":["https://www.koreascience.or.kr/article/JAKO202123157277846.pdf"]}
-{"year":"2021","title":"Recent Research on Phishing Detection Through Machine Learning Algorithm","authors":["A Selamat, O Krejcar - … Conference on Industrial, Engineering and Other …, 2021"],"snippet":"… Phishing URLs, websites or emails are generally collected from PhishTank, Phishing Corpus, OpenPhish, SpamAssassin, etc. [12, 23, 31], whereas legitimate ones are selected from Alexa, Common Crawl, Ham, etc. [16, 24, 28, 31, 35]. Table 4 …","url":["https://link.springer.com/chapter/10.1007/978-3-030-79457-6_42"]}
-{"year":"2021","title":"Recognizing and Splitting Conditional Sentences for Automation of Business Processes Management","authors":["NPA Vo, I Manotas, O Popescu, A Cerniauskas… - arXiv preprint arXiv …, 2021"],"snippet":"… length. 4.3 XLM-R-based Model XLM-RoBERTa (XLM-R) is a state of the art multilingual masked language model trained on 2.5 TB of newly created clean CommonCrawl data in 100 languages (Conneau et al., 2019). It obtains …","url":["https://arxiv.org/pdf/2104.00660"]}
-{"year":"2021","title":"Reconstructing Implicit Knowledge with Language Models","authors":["M Becker, S Liang, A Frank - Proceedings of Deep Learning Inside Out (DeeLIO) …, 2021"],"snippet":"… GPT-2 is pre-trained on web pages from CommonCrawl, XLNet on CommonCrawl+ ClueWeb (Callan et al., 2009), and BART on the CNN/DM summarization dataset (Hermann et al., 2015). 3.3 Fine-tuning LMs Task-adapted Datasets for LM Fine-tuning …","url":["https://www.aclweb.org/anthology/2021.deelio-1.2.pdf"]}
-{"year":"2021","title":"Reducing Human Labor Cost in Deep Learning for Natural Language Processing","authors":["H Jiang - 2021"],"snippet":"… cause it can be trained in a completely unsupervised manner with huge amount of unlabeled data, which are extremely cheap to fetch from internet nowadays. For example, the wellknown “Common Crawl Project”2 is …","url":["https://smartech.gatech.edu/bitstream/handle/1853/64783/JIANG-DISSERTATION-2021.pdf?sequence=1"]}
-{"year":"2021","title":"Reference-based Weak Supervision for Answer Sentence Selection using Web Data","authors":["V Krishnamurthy, T Vu, A Moschitti - arXiv preprint arXiv:2104.08943, 2021"],"snippet":"… Work was conducted while the author was an intern at Amazon Alexa AI. more than 100MM Web documents from Common Crawl's data. Given a question-reference pair, the question is used as query to retrieve a set of relevant documents from the index …","url":["https://arxiv.org/pdf/2104.08943"]}
-{"year":"2021","title":"Refined Commonsense Knowledge from Large-Scale Web Contents","authors":["TP Nguyen, S Razniewski, J Romero, G Weikum - arXiv preprint arXiv:2112.04596, 2021"],"snippet":"Commonsense knowledge (CSK) about concepts and their properties is useful for AI applications. Prior works like ConceptNet, COMET and others compiled large CSK collections, but are restricted in their expressiveness to subject-predicate-object (SPO) …","url":["https://arxiv.org/pdf/2112.04596"]}
-{"year":"2021","title":"Relational Header Discovery using Similarity Search in a Table Corpus","authors":["H Harmouch, T Papenbrock, F Naumann - 2021 IEEE 37th International Conference …, 2021"],"snippet":"… Because web tables contain many distinct values (eg, there are „185M unique values in web tables extracted from the Web Common Crawl [13]), such indexes would be huge and, hence, easily exhaust available memory capacities …","url":["https://ieeexplore.ieee.org/abstract/document/9458838/"]}
-{"year":"2021","title":"Reliability Prediction for Health-related Content: A Replicability Study","authors":["M Fernández-Pichel, D Losada, JC Pichel, D Elsweiler - 2021"],"snippet":"… [31] to generate the assessment pool, instead of using a fixed-depth pooling strategy. After the pool was formed, human assessors from 12 http://commoncrawl.org Page 9. Reliability Prediction for Health-related Content 9 Schwarz et al …","url":["https://tec.citius.usc.es/ir/pdf/ECIR_2021_replicability.pdf"]}
-{"year":"2021","title":"Representations of Language Varieties Are Reliable Given Corpus Similarity Measures","authors":["J Dunn - arXiv preprint arXiv:2104.01294, 2021"],"snippet":"… The experiments draw on existing geographic corpora from the web (ultimately derived from the Common Crawl data) and from tweets (Dunn and Adams … discussed in Section 4. Data from tweets (TW) is shown on the …","url":["https://arxiv.org/pdf/2104.01294"]}
-{"year":"2021","title":"Reproducibility Study: On Heavy-User Bias in A/B Testing","authors":["M Hofmaier, J Schneider, A Wagne"],"snippet":"… they obtained whole Wikipedia to compare it against itself. For the without-analysis they took a 10%-sample of the Common Crawl, which is an open repository for web crawl data. This results in 4.2 million articles consisting of …","url":["https://scholar.archive.org/work/i4ksgrqfh5ekva44jfx6oc433u/access/wayback/https://zenodo.org/record/4459284/files/Reproducibility%20Study%20On%20Heavy-User%20Bias%20in%20AB%20Testing.pdf"]}
-{"year":"2021","title":"Research on Recent Quality Estimation","authors":["S Eo, C Park, H Moon, J Seo, H Lim - Journal of the Korea Convergence Society, 2021"],"snippet":"… XLM-R에서는 CommonCrawl[30] 데이터 중 100개 언어에 해당하는 CC100을, mBART에서 25개 언어에 해당하는 CC25를 사전 학습에 활용하였다 … 100개의 언어를 포함하는 2TB 이상의 CommonCrawl 데이터에 …","url":["https://www.koreascience.or.kr/article/JAKO202123162176745.pdf"]}
-{"year":"2021","title":"Residual Energy-Based Models for Text","authors":["A Bakhtin, Y Deng, S Gross, M Ott, MA Ranzato… - Journal of Machine …, 2021"],"snippet":"… (2015); Kiros et al. (2015), which consists of fiction books in 16 different genres, totaling about half a billion words. • CCNews: We collect a de-duplicated subset of the English portion of the CommonCrawl news …","url":["https://www.jmlr.org/papers/volume22/20-326/20-326.pdf"]}
-{"year":"2021","title":"Retaining Named Entities for Headline Generation","authors":["B Singh, A Marathe, AA Rizvi, AR Joshi - Inventive Computation and Information …"],"snippet":"… These vectors are Page 246. 226 B. Singh et al. trained using word co-occurrence statistics on the Common Crawl corpus. The word embeddings of more than 94% of the words of the dataset's vocabulary are present in the glove. 840B. 300d …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=XhomEAAAQBAJ&oi=fnd&pg=PA221&dq=commoncrawl&ots=EStSRi0ndc&sig=9S5PclK2A3dTQ9RjYbxYB4YNjLI"]}
-{"year":"2021","title":"RetroGAN: A Cyclic Post-Specialization System for Improving Out-of-Knowledge and Rare Word Representations","authors":["P Colon-Hernandez, Y Xin, H Lieberman, C Havasi…"],"snippet":"… In our tests we use the English Common Crawl FastText with sub-word information (FT-CC) and Numberbatch 19.08 (NB) to see how performance would be affected by using embeddings that were already retrofitted with a large KB …","url":["https://aclanthology.org/2021.findings-acl.183.pdf"]}
-{"year":"2021","title":"Revisiting Additive Compositionality: AND, OR and NOT Operations with Word Embeddings","authors":["M Naito, S Yokoi, G Kim, H Shimodaira - arXiv preprint arXiv:2105.08585, 2021"],"snippet":"Page 1. Revisiting Additive Compositionality: AND, OR and NOT Operations with Word Embeddings Masahiro Naito1,3 Sho Yokoi 2,3 Geewook Kim4 Hidetoshi Shimodaira 1,3 1Kyoto University 2Tohoku University 3RIKEN 4 Naver …","url":["https://arxiv.org/pdf/2105.08585"]}
-{"year":"2021","title":"Revisiting Document Representations for Large-Scale Zero-Shot Learning","authors":["J Kil, WL Chao - arXiv preprint arXiv:2104.10355, 2021"],"snippet":"… al., 2009) that has more than 20,000 classes, ex- isting ZSL algorithms (Frome et al., 2013; Norouzi et al., 2013) mostly resort to word vectors of classes names (Mikolov et al., 2013; Pennington et al., 2014) that are automatically …","url":["https://arxiv.org/pdf/2104.10355"]}
-{"year":"2021","title":"Revisiting the Primacy of English in Zero-shot Cross-lingual Transfer","authors":["I Turc, K Lee, J Eisenstein, MW Chang, K Toutanova - arXiv preprint arXiv …, 2021"],"snippet":"… with impressive crosslingual transfer capabilities. mT5 Multilingual T5 (mT5) (Xue et al., 2020) is an encoder-decoder model that was jointly trained on 101 languages from Common Crawl. We use its mT5-Base variant, whose …","url":["https://arxiv.org/pdf/2106.16171"]}
-{"year":"2021","title":"Revisiting Tri-training of Dependency Parsers","authors":["J Wagner, J Foster - arXiv preprint arXiv:2109.08122, 2021"],"snippet":"… 3.4 Unlabelled Data To match the training data of the word embeddings (Section 3.5), we use the Wikipedia and Common Crawl data of the CoNLL 2017 Shared Task in UD Parsing (Ginter et al., 2017; Zeman et al., 2017) as unlabelled data in tri-training …","url":["https://arxiv.org/pdf/2109.08122"]}
-{"year":"2021","title":"Rewarding Open-Domain Conversational Agents Using Memory Networks","authors":["S Majumdar - 2021"],"snippet":"… To collect such pairs of sentences, we use the Common Crawl Monolingual datasets [5]. Hence the final rescaled reward that we use for our experiments is … url: https://commoncrawl.org/. [6] Jacob Devlin et al. “Bert: Pre-training of deep …","url":["https://search.proquest.com/openview/381df303e754ecee58f50ac4b9c84b17/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"Rissanen Data Analysis: Examining Dataset Characteristics via Description Length","authors":["E Perez, D Kiela, K Cho - arXiv preprint arXiv:2103.03872, 2021"],"snippet":"Page 1. Rissanen Data Analysis: Examining Dataset Characteristics via Description Length Ethan Perez1 Douwe Kiela2 Kyunghyun Cho1 3 1New York University, 2Facebook AI Research 3CIFAR Fellow in Learning in Machines & Brains perez@nyu.edu Abstract …","url":["https://arxiv.org/pdf/2103.03872"]}
-{"year":"2021","title":"Robustness of Machine Translation for Low-Resource Languages","authors":["O Aarnikoivu"],"snippet":"Abstract It is becoming increasingly common for researchers and practitioners to rely on methods within the field of Neural Machine Translation (NMT) that require the use of an extensive amount of auxiliary data. This is especially true for low-resource …","url":["https://project-archive.inf.ed.ac.uk/msc/20215190/msc_proj.pdf"]}
-{"year":"2021","title":"Robustness Testing of Language Understanding in Dialog Systems","authors":["J Liu, R Takanobu, J Wen, D Wan, W Nie, H Li, C Li… - arXiv preprint arXiv …, 2020"],"snippet":"… system. We directly use the released models in the repository as DeepSpeech2's configuration, where the speech model is trained on Baidu Internal English Dataset, and the language model is trained on CommonCrawl Data …","url":["https://arxiv.org/pdf/2012.15262"]}
-{"year":"2021","title":"RoGPT2: Romanian GPT2 for Text Generation","authors":["MA Niculescu, S Ruseti, M Dascalu - 2021 IEEE 33rd International Conference on …, 2021"],"snippet":"… First, OSCAR [21] has the highest percentage of the total training corpus, is a multi-language corpus, each language being extracted via language classification, filtered, and cleaned from Common Crawl. Second, the latest version of the Wikipedia Dumps for …","url":["https://ieeexplore.ieee.org/abstract/document/9643330/"]}
-{"year":"2021","title":"Role of Language Relatedness in Multilingual Fine-tuning of Language Models: A Case Study in Indo-Aryan Languages","authors":["TI Dhamecha, R Murthy V, S Bharadwaj… - arXiv preprint arXiv …, 2021"],"snippet":"… 4.1 Data To train the language models, we obtained text data from various sources including: Wikipedia Dump6, WMT Common Crawl 7, WMT News CommonCrawl8, Urdu Charles University Corpus (Bojar et al., 2014; Jawaid …","url":["https://arxiv.org/pdf/2109.10534"]}
-{"year":"2021","title":"ROMANIAN SPEECH RECOGNITION EXPERIMENTS FROM THE ROBIN PROJECT","authors":["AM AVRAM, V PĂIȘ, DAN TUFIȘ - ISSN 1843-911X"],"snippet":"… model could benefit in terms of accuracy. 4 http://corolaws. racai. ro/ corola_sound_search/index. php 5 http://www. racai. ro/p/reterom/ 6 https:// commoncrawl. org/ Page 116. ANDREI-MARIUS AVRAM, VASILE PĂIȘ, DAN TUFIȘ …","url":["https://profs.info.uaic.ro/~consilr/wp-content/uploads/2021/02/volum-ConsILR-v-4-final-revizuit.pdf#page=111"]}
-{"year":"2021","title":"RuSentEval: Linguistic Source, Encoder Force!","authors":["V Mikhailov, E Taktasheva, E Sigdel, E Artemova - arXiv preprint arXiv:2103.00573, 2021"],"snippet":"… XLM-R (Conneau et al., 2020a) is trained on 'dy- namic' MLM task, over filtered CommonCrawl data in 100 languages (Wenzek et al., 2020). MiniLM (Wang et al., 2020) is a distilled transformer of BERT architecture, but uses the XLMRoBERTa tokenizer …","url":["https://arxiv.org/pdf/2103.00573"]}
-{"year":"2021","title":"S&P500 INDEX DIRECTION PREDICTION USING TEXTUAL TWEETS AND THEIR CORRESPONDING SENTIMENT","authors":["P Mohammadalizadeh, M Jafari - 2021"],"snippet":"… The model structure is a standard sort of encoder-decoder transformer. T5 model structure is shown in Fig. 3. T5 uses common crawl web extracted text and the authors applied a simple heuristic filtering. T5 removes any …","url":["http://journal.research.fanap.com/article_135403_775c4f187c40181e2720e9fc5fc5eaec.pdf"]}
-{"year":"2021","title":"S-NLP at SemEval-2021 Task 5: An Analysis of Dual Networks for Sequence Tagging","authors":["VA Nguyen, TM Nguyen, HQ Dao, QH Pham"],"snippet":"… We discard subword part, take only word vector part of a FastText model (pre-trained on Common Crawl dataset) for word representation and utilize an external English Byte Pair Embedding for out-of-vocabulary functionality …","url":["https://aclanthology.org/2021.semeval-1.120.pdf"]}
-{"year":"2021","title":"SAFFRON: tranSfer leArning For Food-disease RelatiOn extractioN","authors":["G Cenikj, T Eftimov, BK Seljak - Proceedings of the 20th Workshop on Biomedical …, 2021"],"snippet":"… Wikipedia, which are used for the pretraining of BERT, RoBERTa is trained on data from 3 additional sources: the CommonCrawl News dataset (Nagel, 2016), the OpenWebText corpus (Gokaslan and Cohen, 2019) and Stories …","url":["https://www.aclweb.org/anthology/2021.bionlp-1.4.pdf"]}
-{"year":"2021","title":"Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages","authors":["G Ramesh, S Doddapaneni, A Bheemaraj… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages Gowtham Ramesh1∗ Sumanth Doddapaneni1∗ Aravinth Bheemaraj2,5 Mayank Jobanputra3 …","url":["https://arxiv.org/pdf/2104.05596"]}
-{"year":"2021","title":"SAU'S Submission for CCMT 2021 Quality Estimation Task","authors":["Y Li, N Ye, D Cai"],"snippet":"… XLM-R is a multi-language pre-training model proposed by Facebook, which uses 2.5TB CommonCrawl to filter data, and masked language model pre-trained on text in 100 languages, which obtains state-of-the-art performance on cross-lingual …","url":["http://sc.cipsc.org.cn/mt/conference/2021/papers/T21-2012.pdf"]}
-{"year":"2021","title":"SAUCE: Truncated Sparse Document Signature Bit-Vectors for Fast Web-Scale Corpus Expansion","authors":["M Wahed, D Gruhl, A Alba, AL Gentile, P Ristoski… - arXiv preprint arXiv …, 2021"],"snippet":"… This experiment facilitates evaluation on a limited seed corpus scenario. The document collection is a snapshot (approximately 200 million documents) of the Common Crawl web archive1, which is regularly updated and consists …","url":["https://arxiv.org/pdf/2108.11948"]}
-{"year":"2021","title":"Say What? Collaborative Pop Lyric Generation Using Multitask Transfer Learning","authors":["N Ram, T Gummadi, R Bhethanabotla, RJ Savery… - Proceedings of the 9th …, 2021"],"snippet":"… The authors opted for an encoder-decoder transformer based design, trained on a variant of the Common Crawl corpus named the Colossal Common Crawl Corpus (or C4 for short). The T5 shows a remarkable ability to tackle many different tasks with …","url":["https://dl.acm.org/doi/abs/10.1145/3472307.3484175"]}
-{"year":"2021","title":"Scalable Graph Convolutional Variational Autoencoders","authors":["D Unyi, B Gyires-Tóth - 2021 IEEE 15th International Symposium on Applied …, 2021"],"snippet":"… In Reddit, nodes are Reddit posts, and if the same user commented on two posts, a link is drawn between them; node features are GloVe CommonCrawl word vectors [31] based on the average embedding of the …","url":["https://ieeexplore.ieee.org/abstract/document/9465579/"]}
-{"year":"2021","title":"SCALE EFFICIENTLY: INSIGHTS FROM PRE-TRAINING AND FINE-TUNING TRANSFORMERS","authors":["AT Vaswani, D Yogatama, D Metzler, HW Chung… - 2022","FT TRANSFORMERS","Y Tay, M Dehghani, J Rao, W Fedus, S Abnar… - arXiv preprint arXiv …, 2021"],"snippet":"Abstract: There remain many open questions pertaining to the scaling behaviour of Transformer architectures. These scaling decisions and findings can be critical, as training runs often come with an associated computational cost which have both …","url":["https://arxiv.org/pdf/2109.10686","https://openreview.net/pdf?id=f2OYVDyfIB","https://research.google/pubs/pub52066.pdf"]}
-{"year":"2021","title":"Scaling Laws for Transfer","authors":["D Hernandez, J Kaplan, T Henighan, S McCandlish - arXiv preprint arXiv:2102.01293, 2021"],"snippet":"… Pre-trained text models were trained on a mix of WebText2 described in [KMH+20], Common Crawl5 [RSR+20], English Wikipedia, and publicly available Internet Books … 5https://commoncrawl.org/the-data/ 6https://www.gharchive.org/ 6 Page 7. 3 Results …","url":["https://arxiv.org/pdf/2102.01293"]}
-{"year":"2021","title":"Scarecrow: A Framework for Scrutinizing Machine Text","authors":["Y Dou, M Forbes, R Koncel-Kedziorski, NA Smith… - arXiv preprint arXiv …, 2021"],"snippet":"… GPT-3 DaVinci (Brown et al., 2020) The 175B parameter variant of GPT-3, which is trained on a version of the Common Crawl web scrape with additional filtering and deduplicating. These model choices allow us to study several …","url":["https://arxiv.org/pdf/2107.01294"]}
-{"year":"2021","title":"SCOPA: Soft Code-Switching and Pairwise Alignment for Zero-Shot Cross-lingual Transfer","authors":["D Lee, J Lee, G Lee, B Chun, S Hwang - Proceedings of the 30th ACM International …, 2021"],"snippet":"… To enhance such transfer, XLM-R [4] is pre-trained on 100 languages with CommonCrawl Corpora, supervised by translational objectives, to transfer from resource-rich languages (eg, English and Chinese) to resource-poor languages …","url":["https://dl.acm.org/doi/abs/10.1145/3459637.3482176"]}
-{"year":"2021","title":"Screening Gender Transfer in Neural Machine Translation","authors":["G Wisniewski, L Zhu, N Bailler, F Yvon - … of the Fourth BlackboxNLP Workshop on …, 2021"],"snippet":"… It includes the Europarl, NewsCommentary and CommonCrawl corpora, and altogether contains 4,813,682 sentences and nearly 141 million French running words. All the corpora were tokenized and segmented into sub-lexical units using …","url":["https://aclanthology.org/2021.blackboxnlp-1.24.pdf"]}
-{"year":"2021","title":"Screening hardware and volume factors in distributed machine learning algorithms on spark","authors":["JB Rodrigues, GC Vasconcelos, PRM Maciel - Computing, 2021"],"snippet":"This paper presents an approach to investigate distributed machine learning workloads on Spark. The work analyzes hardware and volume data factors regardin.","url":["https://link.springer.com/article/10.1007/s00607-021-00965-3"]}
-{"year":"2021","title":"Selecting Parallel In-domain Sentences for Neural Machine Translation Using Monolingual Texts","authors":["JPR Sharami, D Shterionov, P Spronck - arXiv preprint arXiv:2112.06096, 2021"],"snippet":"Continuously-growing data volumes lead to larger generic models. Specific use-cases are usually left out, since generic models tend to perform poorly in domain-specific cases. Our work addresses this gap with a method for selecting in-domain data from …","url":["https://arxiv.org/pdf/2112.06096"]}
-{"year":"2021","title":"Selecting the best data filtering method for NMT training","authors":["F Bane, A Zaretskaya - Proceedings of Machine Translation Summit XVIII …, 2021"],"snippet":"… Rule Based Classifier for Translation Memory Cleaning. Online. Smith, JR, Saint-Amand, H., Plamada, M., Koehn, P., Callison-Burch, C., and Lopez, A. (2013). Dirt cheap web-scale parallel text from the Common Crawl. In …","url":["https://aclanthology.org/2021.mtsummit-up.9.pdf"]}
-{"year":"2021","title":"Self-Attention Network for Text Representation Learning","authors":["T Shen - 2021"],"snippet":"Page 1. Self-Attention Network for Text Representation Learning by Tao SHEN Thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy under the supervision of Dist. Prof. Chengqi ZHANG, Prof. Guodong LONG and Dr. Jing JIANG …","url":["https://opus.lib.uts.edu.au/bitstream/10453/149266/2/02Whole.pdf"]}
-{"year":"2021","title":"Self-Contextualized Attention for Abusive Language Identification","authors":["H Jarquín-Vásquez, HJ Escalante, M Montes - … of the Ninth International Workshop on …, 2021"],"snippet":"… For word representation we used pre-trained fastText embeddings (Mikolov et al., 2018), trained with subword information on Common Crawl, which have been recognized as useful for this task ac- cording to the study presented in (Corazza et al., 2020) …","url":["https://www.aclweb.org/anthology/2021.socialnlp-1.9.pdf"]}
-{"year":"2021","title":"Self-Supervised Representation Learning: Introduction, Advances and Challenges","authors":["L Ericsson, H Gouk, CC Loy, TM Hospedales - arXiv preprint arXiv:2110.09327, 2021"],"snippet":"Self-supervised representation learning methods aim to provide powerful deep feature learning without the requirement of large annotated datasets, thus alleviating the annotation bottleneck that is one of the main barriers to practical deployment of …","url":["https://arxiv.org/pdf/2110.09327"]}
-{"year":"2021","title":"Self-Training Pre-Trained Language Models for Zero-and Few-Shot Multi-Dialectal Arabic Sequence Labeling","authors":["M Khalifa, M Abdul-Mageed, K Shaalan - arXiv preprint arXiv:2101.04758, 2021"],"snippet":"… XLM-R also uses Common Crawl for training, which is more likely to have dialectal data than the Arabic Wikipedia (used in mBERT), making it more suited to our work … mBERT, XLM-R was trained on much larger data …","url":["https://arxiv.org/pdf/2101.04758"]}
-{"year":"2021","title":"Self-training vs Pre-trained Embeddings for Automatic Essay Scoring","authors":["X Zhou, L Yang, X Fan, G Ren, Y Yang, H Lin - China Conference on Information …, 2021"],"snippet":"… In the training process, we use both the pre-trained embeddings and the randomly initialized self-trained embeddings, where the pre-trained word vector comes from Glove Common Crawl (6B token) and the dimension is …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88189-4_12"]}
-{"year":"2021","title":"Self–other moral bias: Evidence from implicit measures and the Word-Embedding Association Test","authors":["MH Li, PW Li, LL Rao - Personality and Individual Differences, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0191886921004864"]}
-{"year":"2021","title":"Semantic Detection of Targeted Attacks Using DOC2VEC Embedding","authors":["MS El-Rahmany, EH Mohamed, MH Haggag"],"snippet":"… This model was trained using Common Crawl and Wikipedia. CBOW was used to train these models. In this study, we used dimension 300, character n-grams of length 5, a window of size 5, and 10 negatives. …","url":["https://softcom2020.fesb.unist.hr/pdfs/v17n4_2021-0113_rahmany.pdf"]}
-{"year":"2021","title":"Semantic maps and metrics for science Semantic maps and metrics for science using deep transformer encoders","authors":["B Chambers, J Evans - arXiv preprint arXiv:2104.05928, 2021"],"snippet":"Page 1. Semantic maps and metrics for science using deep transformer encoders Brendan Chambers QuillBot Knowledge Lab at the University of Chicago James Evans Department of Sociology and Knowledge Lab, University of Chicago Santa Fe Institute …","url":["https://arxiv.org/pdf/2104.05928"]}
-{"year":"2021","title":"Semantic Networks for Engineering Design: State of the Art and Future Directions","authors":["J Han, S Sarica, F Shi, J Luo - Journal of Mechanical Design, 2021"],"snippet":"Page 1. Journal of Mechanical Design 1 Semantic Networks for Engineering Design: State of the Art and Future Directions Ji Han1 School of Engineering University of Liverpool, the United Kingdom e-mail: ji.han@liverpool.ac.uk …","url":["https://asmedigitalcollection.asme.org/mechanicaldesign/article-abstract/doi/10.1115/1.4052148/1115821"]}
-{"year":"2021","title":"Semantic Search of Mobile Applications Using Word Embeddings","authors":["J Coelho, A Neto, M Tavares, C Coutinho, R Ribeiro… - 10th Symposium on …, 2021"],"snippet":"… This way, character-level embeddings are considered, instead of word-level representations. In preliminary tests, we compared a CBOW [12] fastText model (FT1), pre-trained on English Common Crawl considering word 5-grams …","url":["https://drops.dagstuhl.de/opus/volltexte/2021/14429/pdf/OASIcs-SLATE-2021-12.pdf"]}
-{"year":"2021","title":"Semantic Similarity Based Evaluation for Abstractive News Summarization","authors":["FB Fikri, K Oflazer, B Yanıkoglu - GEM 2021, 2021"],"snippet":"… et al., 2019). mT5 Multilingual T5 (mT5)(Xue et al., 2020) is a variant of T5 model (Raffel et al., 2020) that was pre-trained for 101 languages including Turkish on a new Common Crawl-based dataset. For Turkish summarization …","url":["https://aclanthology.org/2021.gem-1.pdf#page=36"]}
-{"year":"2021","title":"Semantic-WER: A Unified Metric for the Evaluation of ASR Transcript for End Usability","authors":["S Roy - arXiv preprint arXiv:2106.02016, 2021"],"snippet":"… A 4-gram language model trained on common crawl dataset is used for decoding 6 7[28] … 4https://github.com/pytorch/fairseq/tree/master/examples/ wav2vec 5https://github.com/facebookresearch/wav2letter/tree/master/recipes …","url":["https://arxiv.org/pdf/2106.02016"]}
-{"year":"2021","title":"Semantically Meaningful Sentence Embeddings","authors":["R Deuja - 2021"],"snippet":"Text embedding is an approach used in Natural Language Processing (NLP) to represent words, phrases, sentences, and documents. It is the process of obtaining numeric representations of text to feed into machine learning models as vectors (arrays …","url":["https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1247&context=computerscidiss"]}
-{"year":"2021","title":"SemFace: Pre-training Encoder and Decoder with a Semantic Interface for Neural Machine Translation","authors":["S Ren, L Zhou, S Liu, F Wei, M Zhou, S Ma"],"snippet":"… Table 1: The datasets used in our experiments. Lang: language; Mono: monolingual; Para: parallel; #Sent: number of sentences in the monolingual corpus; NC: NewsCrawl; CC: CommonCrawl; BE: BigEst Estonian corpus; Wiki: Wiki dumps …","url":["https://aclanthology.org/2021.acl-long.348.pdf"]}
-{"year":"2021","title":"Semi-automatic Construction of Sight Words Dictionary for Filipino Text Readability","authors":["JM Imperial - Knowledge Management and Acquisition for Intelligent …"],"snippet":"… The Filipino word embedding model has been pre-trained from the articles of Wikipedia and the publicly-available webscraped data of the Common Crawl project using the Continuous Bag-of-Words (CBOW) model [2]. Word …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=oTofEAAAQBAJ&oi=fnd&pg=PA168&dq=commoncrawl&ots=a3xsZgmDzY&sig=HvrePT8d-vC6XeT31rVJoZx_cyI"]}
-{"year":"2021","title":"Semi-supervised log-based anomaly detection via probabilistic label estimation","authors":["L Yang, J Chen, Z Wang, W Wang, J Jiang, X Dong… - 2021 IEEE/ACM 43rd …, 2021"],"snippet":"… Then, PLELog adopts the pre-trained word vectors based on Common Crawl Corpus using the FastText algorithm [46] (which can effectively capture the intrinsic relationship among words in natural language), to extract the …","url":["https://ieeexplore.ieee.org/abstract/document/9401970/"]}
-{"year":"2021","title":"Sentence encoding for Dialogue Act classification","authors":["N Duran, S Battle, J Smith - Natural Language Engineering, 2021"],"snippet":"In this study, we investigate the process of generating single-sentence representations for the purpose of Dialogue Act (DA) classification, including several aspects of text pre-processing and input representation which are often overlooked …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/sentence-encoding-for-dialogue-act-classification/2EF3DC8E57D1019960D18FDE685B1EBA"]}
-{"year":"2021","title":"Sentence simplification with ruGPT3","authors":["AA Shatilov, AI Rey"],"snippet":"… One of the latest works [12] uses an unsupervised approach to automatically create training corpora for simplification in multiple languages from raw Common Crawl web data and train simplification systems in any language with a controllable generation mechanism …","url":["http://www.dialog-21.ru/media/5281/shatilovaaplusreyai142.pdf"]}
-{"year":"2021","title":"Sentiment Analysis of Code-Mixed Roman Urdu-English Social Media Text using Deep Learning Approaches","authors":["A Younas, R Nasim, S Ali, G Wang, F Qi - 2020 IEEE 23rd International Conference on …"],"snippet":"… Similarly, authors have developed XLM-RoBERTa (XLM-R) - a multilingual language model trained on 2.5 terabyte of filtered CommonCrawl data using BERT-large architecture [9]. It provides strong advantage over mBERT model …","url":["https://ieeexplore.ieee.org/abstract/document/9345887/"]}
-{"year":"2021","title":"Sentiment analysis of Korean movie reviews using XLM-R","authors":["NR Shin, TH Kim, DY Yun, SJ Moon, C Hwang - International Journal of Advanced …, 2021"],"snippet":"… Among them, the Facebook AI team unveiled the XLM-R (XLM-RoBERTa), an upgraded XLM model. XLM-R solved the data limitation and the curse of multilinguality by training XLM with 2TB or more refined CC (CommonCrawl), not Wikipedia data …","url":["https://www.koreascience.or.kr/article/JAKO202119559811514.pdf"]}
-{"year":"2021","title":"Sentiment Analysis of Latin Poetry: First Experiments on the Odes of Horace","authors":["R Sprugnoli, F Mambrini, M Passarotti, G Moretti - Eighth Italian Conference on …, 2021"],"snippet":"In this paper we present a set of annotated data and the results of a number of unsupervised experiments for the analysis of sentiment in Latin poetry. More specifically, we describe a small gold standard made of eight poems by Horace, in …","url":["http://ceur-ws.org/Vol-3033/paper25.pdf"]}
-{"year":"2021","title":"Sentiment Analysis of Sinhala News Comments","authors":["S Ranathunga, IU Liyanage - Transactions on Asian and Low-Resource Language …, 2021"],"snippet":"… 2009], and the Sinhala Common Crawl dataset1 are examples of un-annotated Sinhala corpora. Common crawl is the largest among these, with about 110 million uncleaned tokens … Both SinMin and Common Crawl contain a lot of noise …","url":["https://dl.acm.org/doi/abs/10.1145/3445035"]}
-{"year":"2021","title":"Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset","authors":["K Ahmad, F Alam, J Qadir, B Qolomany, I Khan, T Khan… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. 1 Sentiment Analysis of Users' Reviews on COVID-19 Contact Tracing Apps with a Benchmark Dataset Kashif Ahmad∗, Firoj Alam†, Junaid Qadir‡, Basheer Qolomany§, Imran Khan¶, Talhat Khan¶, Muhammad Suleman …","url":["https://arxiv.org/pdf/2103.01196"]}
-{"year":"2021","title":"Sentiment Analysis Using XLM-R Transformer and Zero-shot Transfer Learning on Resource-poor Indian Language","authors":["A Kumar, VHC Albuquerque - Transactions on Asian and Low-Resource Language …, 2021"],"snippet":"… It is a scaled cross-lingual sentence encoder trained on 2.5 Tb of data across 100 languages data filtered from CommonCrawl texts. Compared to the original version, the biggest update of XLM-Roberta is a significant …","url":["https://dl.acm.org/doi/abs/10.1145/3461764"]}
-{"year":"2021","title":"Sentiment Polarity Classification of Corporate Review Data with a Bidirectional Long-Short Term Memory (biLSTM) Neural Network Architecture","authors":["RE Loke, O Kachaniuk - 2020"],"snippet":"… Therefore, it was decided to proceed with fastText embeddings. Accordingly, pre-trained vectors for Dutch language were added to the biLSTM model as one of the layers. Moreover, these vectors were trained on Common Crawl and Wikipedia using fastText …","url":["https://pure.hva.nl/ws/files/17012226/DATA_2020_75.pdf"]}
-{"year":"2021","title":"Sequential Reptile: Inter-Task Gradient Alignment for Multilingual Learning","authors":["S Lee, HB Lee, J Lee, SJ Hwang - arXiv preprint arXiv:2110.02600, 2021"],"snippet":"Page 1. Preprint SEQUENTIAL REPTILE: INTER-TASK GRADIENT ALIGNMENT FOR MULTILINGUAL LEARNING Seanie Lee1∗, Hae Beom Lee1∗, Juho Lee1,2, Sung Ju Hwang1,2 KAIST1, AITRICS2, South Korea …","url":["https://arxiv.org/pdf/2110.02600"]}
-{"year":"2021","title":"SG-MLP: Switch Gated Multi-Layer Perceptron Model for Natural Language Understanding","authors":["G Son, S Kim, SJ Joo, W Cho, JE Nah - … of the Korea Information Processing Society …, 2021"],"snippet":"… SG-MLP Small 은 약 16GB 에 해당하는 Book Corpus 와 Wiki 데이터로 학습 되었으며 이외의 모델은 Common Crawl’s Web Crawl Corpus 를 한 차례 정제한 Allen·C4·En[8] 데이터를 학습에 활용하였으며 이는 약 305GB 정도의 분량이다. 보유한 하드웨어 …","url":["https://www.koreascience.or.kr/article/CFKO202133649066979.pdf"]}
-{"year":"2021","title":"Shall I Work with Them? A Knowledge Graph-Based Approach for Predicting Future Research Collaborations","authors":["N Kanakaris, N Giarelis, I Siachos, N Karacapilidis - Entropy, 2021"],"snippet":"We consider the prediction of future research collaborations as a link prediction problem applied on a scientific knowledge graph. To the best of our knowledge, this is the first work on the prediction of future research collaborations that …","url":["https://www.mdpi.com/1099-4300/23/6/664/pdf"]}
-{"year":"2021","title":"Shallow Discourse Parsing for German","authors":["P Bourgonje"],"snippet":"Page 1. Shallow Discourse Parsing for German Peter Bourgonje Dissertation eingereicht bei der Humanwissenschaftlichen Fakultät der Universität Potsdam 2021 Page 2. Datum der Einreichung: 22-07-2020 Wissenschaftlicher Betreuer und Gutachter: Prof …","url":["https://publishup.uni-potsdam.de/files/50663/bourgonje_diss.pdf"]}
-{"year":"2021","title":"Sharp Learning Bounds for Contrastive Unsupervised Representation Learning","authors":["H Bao, Y Nagano, K Nozawa - arXiv preprint arXiv:2110.02501, 2021"],"snippet":"Page 1. Sharp Learning Bounds for Contrastive Unsupervised Representation Learning *Han Bao, Yoshihiro Nagano, Kento Nozawa The University of Tokyo & RIKEN AIP {tsutsumi@ms., nagano@, nozawa@ms.}ku-tokyo.ac.jp October 7, 2021 …","url":["https://arxiv.org/pdf/2110.02501"]}
-{"year":"2021","title":"Should we find another model?: Improving Neural Machine Translation Performance with ONE-Piece Tokenization Method without Model Modification","authors":["C Park, S Eo, H Moon, HS Lim - Proceedings of the 2021 Conference of the North …, 2021"],"snippet":"… corpus. In mBART (Liu et al., 2020), the CC25 corpus was composed of a total of 25 languages extracted from CommonCrawl (CC) (Lample and Conneau, 2019; Wenzek et al., 2019) and used for unified vocabulary extraction …","url":["https://www.aclweb.org/anthology/2021.naacl-industry.13.pdf"]}
-{"year":"2021","title":"Show, tell and summarise: learning to generate and summarise radiology findings from medical images","authors":["S Singh, S Karimi, K Ho-Shon, L Hamey - Neural Computing and Applications, 2021"],"snippet":"Radiology plays a vital role in health care by viewing the human body for diagnosis, monitoring, and treatment of medical problems. In radiology practice,.","url":["https://link.springer.com/article/10.1007/s00521-021-05943-6"]}
-{"year":"2021","title":"SJ_AJ@ DravidianLangTech-EACL2021: Task-Adaptive Pre-Training of Multilingual BERT models for Offensive Language Identification","authors":["SM Jayanthi, A Gupta - arXiv preprint arXiv:2102.01051, 2021"],"snippet":"… mon Crawl data6. The common crawl data consists of textual data both in native scripts as well as in romanized script for some of the languages. Among the three languages in this task, only Tamil has Romanized data in the Common Crawl …","url":["https://arxiv.org/pdf/2102.01051"]}
-{"year":"2021","title":"Sketch-Based Creativity Support Tools Using Deep Learning","authors":["F Huang, E Schoop, D Ha, J Nichols, J Canny - Artificial Intelligence for Human …, 2021"],"snippet":"Abstract Sketching is a natural and effective visual communication medium commonly used in creative processes. Recent developments in deep-learning models drastically improved machines’ ability in understanding and generating …","url":["https://link.springer.com/chapter/10.1007/978-3-030-82681-9_12"]}
-{"year":"2021","title":"SLAM: A Unified Encoder for Speech and Language Modeling via Speech-Text Joint Pre-Training","authors":["A Bapna, Y Chung, N Wu, A Gulati, Y Jia, JH Clark… - arXiv preprint arXiv …, 2021"],"snippet":"Unsupervised pre-training is now the predominant approach for both text and speech understanding. Self-attention models pre-trained on large amounts of unannotated data have been hugely successful when fine-tuned on downstream …","url":["https://arxiv.org/pdf/2110.10329"]}
-{"year":"2021","title":"Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic languages","authors":["J Piskorski, B Babych, Z Kancheva, O Kanishcheva… - The 8th Workshop onBalto …, 2021"],"snippet":"Page 1. Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic languages Jakub Piskorski,1 Bogdan Babych,2 Zara Kancheva,3 Olga Kanishcheva …","url":["https://tuhat.helsinki.fi/ws/files/161998023/Slav_NER_Shared_Task.pdf"]}
-{"year":"2021","title":"SlovakBERT: Slovak Masked Language Model","authors":["M Pikuliak, Š Grivalský, M Konôpka, M Blšták… - arXiv preprint arXiv …, 2021"],"snippet":"… is a suite of RoBERTa-style LMs. The models support 100 languages, including Slovak. Training data are based on CommonCrawl Web-crawled corpus. Slovak part has 23.2 GB (3.5B tokens). The XLM-R models differ in their …","url":["https://arxiv.org/pdf/2109.15254"]}
-{"year":"2021","title":"Small Data? No Problem! Exploring the Viability of Pretrained Multilingual Language Models for Low-Resource Languages","authors":["K Ogueji, Y Zhu, J Lin"],"snippet":"… We select these languages because they are the languages supported by the British Broadcasting Corporation (BBC) News, which was our main source of data.4 We also obtain additional data from the Common Crawl …","url":["https://cs.uwaterloo.ca/~jimmylin/publications/Ogueji_etal_MRL2021.pdf"]}
-{"year":"2021","title":"Smart integration of sensors, computer vision and knowledge representation for intelligent monitoring and verbal human-computer interaction","authors":["T Mavropoulos, S Symeonidis, A Tsanousa… - Journal of Intelligent …, 2021"],"snippet":"The details presented in this article revolve around a sophisticated monitoring framework equipped with knowledge representation and computer vision capabi.","url":["https://link.springer.com/article/10.1007/s10844-021-00648-7"]}
-{"year":"2021","title":"SOAR: A Synthesis Approach for Data Science API Refactoring","authors":["A Ni, D Ramos, A Yang, I Lynce, V Manquinho… - arXiv preprint arXiv …, 2021"],"snippet":"… is greatly reduced. However, GloVe is trained with Common Crawl [30] which contains raw webpages, which is a mismatch from our domain of textual data (ie, data science and programming). API matching. Given the representation …","url":["https://arxiv.org/pdf/2102.06726"]}
-{"year":"2021","title":"Social network analysis using deep learning: applications and schemes","authors":["AM Abbas - Social Network Analysis and Mining, 2021"],"snippet":"Abstract Online social networks (OSNs) are part of daily life of human beings. Millions of users are connected through online social networks. Due to very large number of users and huge amount of data, social network analysis is a challenging …","url":["https://link.springer.com/article/10.1007/s13278-021-00799-z"]}
-{"year":"2021","title":"Social Networks Analysis to Retrieve Critical Comments on Online Platforms","authors":["S Bhandari, R Raju - arXiv preprint arXiv:2102.10495, 2021"],"snippet":"… 2019 IEEE International Conference on Healthcare Informatics (ICHI), pp. 1–3, 2019. [13] S. Nagel, “Cc-news.” https://commoncrawl.org/2016/10/news-datasetavailable/, 2016. [14] M. Heidari and JH Jones, “Using bert to extract …","url":["https://arxiv.org/pdf/2102.10495"]}
-{"year":"2021","title":"Social Norm Bias: Residual Harms of Fairness-Aware Algorithms","authors":["M Cheng, M De-Arteaga, L Mackey, AT Kalai - arXiv preprint arXiv:2108.11056, 2021"],"snippet":"… We use the dataset1 and task described by De-Arteaga et al. [25]. The dataset, containing 397,340 biographies spanning twenty-eight occupations, is obtained by using regular expressions to filter the Common Crawl for online biographies …","url":["https://arxiv.org/pdf/2108.11056"]}
-{"year":"2021","title":"SOLID: A Large-Scale Semi-Supervised Dataset for Offensive Language Identification","authors":["S Rosenthal, P Atanasova, G Karadzhov, M Zampieri… - Proceedings of the Findings …, 2021"],"snippet":"… relations between words. First is an embedding layer initialized with a concatenation of the GloVe 300-dimensional (Pennington et al., 2014) and FastText's Common Crawl 300-dimensional embeddings (Grave et al., 2018). It is …","url":["https://aclanthology.org/2021.findings-acl.80.pdf"]}
-{"year":"2021","title":"Spanish Biomedical Crawled Corpus: A Large, Diverse Dataset for Spanish Biomedical Language Models","authors":["CP Carrino, J Armengol-Estapé, OG Bonet… - arXiv preprint arXiv …, 2021"],"snippet":"… The CommonCrawl1 is very a large repository of crawled websites. However, it needs preprocessing to extract the text relevant to the user. The OSCAR corpus [10] was built applying language identification to CommonCrawl …","url":["https://arxiv.org/pdf/2109.07765"]}
-{"year":"2021","title":"Sparse Distillation: Speeding Up Text Classification by Using Bigger Models","authors":["Q Ye, M Khabsa, M Lewis, S Wang, X Ren, A Jaech - arXiv preprint arXiv:2110.08536, 2021"],"snippet":"Distilling state-of-the-art transformer models into lightweight student models is an effective way to reduce computation cost at inference time. However, the improved inference speed may be still unsatisfactory for certain time-sensitive applications. In …","url":["https://arxiv.org/pdf/2110.08536"]}
-{"year":"2021","title":"Spreadsheet Data Transformation for Ontology Engineering in Petrochemical Equipment Inspection Tasks","authors":["NO Dorodnykh, AY Yurin - … Conference on Intelligent Information Technologies for …, 2021"],"snippet":"… world. The exploration of the Web crawl (“Google Crawl”, “Common Crawl”, “ClueWeb”) discovered hundreds of millions of tables containing relational data [3]. Presumably, billions of valuable facts can be extracted from them …","url":["https://link.springer.com/chapter/10.1007/978-3-030-87178-9_55"]}
-{"year":"2021","title":"SQYQP@ Vaxxstance: Stance Detection for the Antivaxxers Movement","authors":["J Calleja, A Méndez - 2021"],"snippet":"… embeddings, Multilingual cased BERT embeddings are employed, which are trained on cased text in the top 104 languages with the largest Wikipedias, as well as XML-RoBERTa embeddings, which are trained on 2.5 TB of newly …","url":["http://ceur-ws.org/Vol-2943/vaxx_paper2.pdf"]}
-{"year":"2021","title":"Stacked Embeddings and Multiple Fine-Tuned XLM-RoBERTa Models for Enhanced Hostility Identification","authors":["XLM Fine-Tuned - Combating Online Hostile Posts in Regional …"],"snippet":"… XLM-RoBERTa. XLM-RoBERTa [10] is a large multilingual model trained on the CommonCrawl Dataset. There are two versions: base and large; both have around 250k words in the vocabulary, and the base has 250M parameters, while large has 560M …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=yD8oEAAAQBAJ&oi=fnd&pg=PA224&dq=commoncrawl&ots=ai1kFeEaRU&sig=UkWmp4nmnIiSJ004dO8RQkmOvmk"]}
-{"year":"2021","title":"StarryThoughts: Facilitating Diverse Opinion Exploration on Social Issues","authors":["H Kim, H Kim, KJ Jo, J Kim - Proceedings of the ACM on Human-Computer …, 2021"],"snippet":"… After translation, we computed each opinion's embedded vector with the algorithm using pre-trained GloVe word embeddings built upon 42B tokens from Common Crawl [49]. 4.3 Implementation details The front-end of StarryThoughts is implemented with React …","url":["https://dl.acm.org/doi/abs/10.1145/3449140"]}
-{"year":"2021","title":"Step-unrolled Denoising Autoencoders for Text Generation","authors":["N Savinov, J Chung, M Binkowski, E Elsen, A Oord - arXiv preprint arXiv:2112.06749, 2021"],"snippet":"… results on unconditional language modeling on the Colossal Cleaned Common Crawl dataset and a dataset of Python code from GitHub. … • We demonstrate good qualitative results for unconditional generation and inpainting on Colossal Clean …","url":["https://arxiv.org/pdf/2112.06749"]}
-{"year":"2021","title":"Stepmothers are mean and academics are pretentious: What do pretrained language models learn about you?","authors":["R Choenni, E Shutova, R van Rooij - arXiv preprint arXiv:2109.10052, 2021","WWE Do, FLDT Fine-Tuning"],"snippet":"09/21/21 - In this paper, we investigate what types of stereotypical information are captured by pretrained language models. We present the f...","url":["https://arxiv.org/pdf/2109.10052","https://deepai.org/publication/stepmothers-are-mean-and-academics-are-pretentious-what-do-pretrained-language-models-learn-about-you"]}
-{"year":"2021","title":"Stock Volume Prediction Based on Polarity of Tweets, News, and Historical Data Using Deep Learning","authors":["N Jawahar, J Chelladurai, I Sakthivel, B Bajracharya - 2020 2nd International …, 2020"],"snippet":"… token in order to predict the entity of that token. The CNN core model is pre-trained with GloVe vectors on Common Crawl, with 86.43% precision and 86.37% recall for NER. A python script is written that uses Psycopg to extract …","url":["https://dl.acm.org/doi/abs/10.1145/3440054.3440063"]}
-{"year":"2021","title":"Storytelling Exhibitions: Identity, Truth and Wonder","authors":["P Hughes - 2021"],"snippet":""}
-{"year":"2021","title":"Strategyproof Learning: Building Trustworthy User-Generated Datasets","authors":["S Farhadkhani, R Guerraoui, LN Hoang - arXiv preprint arXiv:2106.02398, 2021"],"snippet":"Page 1. arXiv:2106.02398v1 [cs.LG] 4 Jun 2021 Strategyproof Learning: Building Trustworthy User-Generated Datasets Sadegh Farhadkhani IC School, EPFL Lausanne, Switzerland sadegh.farhadkhani@epfl.ch Rachid Guerraoui …","url":["https://arxiv.org/pdf/2106.02398"]}
-{"year":"2021","title":"Streaming cascade-based speech translation leveraged by a direct segmentation model","authors":["J Iranzo-Sánchez, J Jorge, P Baquero-Arnal… - Neural Networks, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0893608021002057"]}
-{"year":"2021","title":"Streamlining the Identification of Emerging Tasks in the O* NET System Using Natural Language Processing (NLP): Technical Summary","authors":["JA Dahlke, DJ Putka - 2021"],"snippet":"… In our case, we used embeddings from the Global Vectors for Word Representation (GloVe; Pennington, Socher, & Manning, 2014) algorithm trained on a “common crawl” of the internet consisting of 42 billion tokens (ie, wordlike pieces of text) …","url":["https://www.onetcenter.org/dl_files/EmergingTasksNLP.pdf"]}
-{"year":"2021","title":"Structured Text Generation for Spanish Freestyle Battles using Neural Networks","authors":["P Dal Bianco, I Mindlin, L Lanzarini, F Ronchetti… - 2021 XLVII Latin American …, 2021"],"snippet":"… It was trained on a version of the Common Crawl database [6], which consists of around a trillion words. GPT-3 achieves very good results for text generation, via training first on large databases such as the one mentioned and then performing fine-tuning …","url":["https://ieeexplore.ieee.org/abstract/document/9639929/"]}
-{"year":"2021","title":"Study of automatic text summarization approaches in different languages","authors":["Y Kumar, K Kaur, S Kaur - Artificial Intelligence Review, 2021"],"snippet":"Nowadays we see huge amount of information is available on both, online and offline sources. For single topic we see hundreds of articles are available, co.","url":["https://link.springer.com/article/10.1007/s10462-021-09964-4"]}
-{"year":"2021","title":"Studying the Relationship between Social Position and the Meaning of Work using Siamese BERT Networks and Generalized K-Means Clustering","authors":["S Stewart"],"snippet":"… 1https://www.glassdoor.com 2Specifically, I used the 300-dimensional embeddings with a 1.9 million-token vocabulary that was pretrained on Common Crawl data. 2 Page 3. Review Occupation Flexible working hours …","url":["http://cs230.stanford.edu/projects_fall_2020/reports/57221844.pdf"]}
-{"year":"2021","title":"Style Change Detection on Real-World Data using LSTM-powered Attribution Algorithm","authors":["R Deibel, D Löfflad - CLEF, 2021"],"snippet":"… lab [18]. They were trained on Common Crawl and Wikipedia data, using continuous bag of words with position-weights, in dimension 300, with character n-grams of length five, a window of size five and ten negatives. Unlike …","url":["http://ceur-ws.org/Vol-2936/paper-163.pdf"]}
-{"year":"2021","title":"SU-NLP at CheckThat! 2021: Check-Worthiness of Turkish Tweets","authors":["B Carik, R Yeniterzi - 2021"],"snippet":"… Loodos_ALBERT5: pre-trained on the same dataset as Loodos_BERT. • mBERT6: multilingual BERT model pre-trained on Wikipedia in 104 languages. • XLM-RoBERTa 7: this cross-lingual model was pretrained on the CommonCrawl corpus in 100 languages …","url":["http://ceur-ws.org/Vol-2936/paper-37.pdf"]}
-{"year":"2021","title":"Sub-Subword N-Gram Features for Subword-Level Neural Machine Translation","authors":["A Martinez, K Sudoh, Y Matsumoto - Journal of Natural Language Processing, 2021"],"snippet":"Page 1. IA0248_04martinez (2021-03-05 13:42) General Paper Sub-Subword N-Gram Features for Subword-Level Neural Machine Translation Ander Martinez † , Katsuhito Sudoh † and Yuji Matsumoto †,†† Neural machine …","url":["https://www.jstage.jst.go.jp/article/jnlp/28/1/28_82/_pdf"]}
-{"year":"2021","title":"Subword Pooling Makes a Difference","authors":["J Ács, Á Kádár, A Kornai - arXiv preprint arXiv:2102.10864, 2021"],"snippet":"… We pick these two since they are architecturally similar (both have 12 layers and the same hidden size) making our comparison easier. mBERT was trained on Wikipedia while XLM-RoBERTa was trained on CommonCrawl (Wenzek et al., 2020) …","url":["https://arxiv.org/pdf/2102.10864"]}
-{"year":"2021","title":"Subwords-Only Alternatives to fastText for Morphologically Rich Languages","authors":["T Ghukasyan, Y Yeshilbashyan, K Avetisyan - Programming and Computer Software, 2021"],"snippet":"… Furthermore, as a result of embedding whole words, fastText models typically weigh a few gigabytes (Facebook's Common Crawl vectors' .bin and .vec files weigh 7.3 GB and 4.5 GB respectively [8]). This especially becomes …","url":["https://link.springer.com/article/10.1134/S0361768821010059"]}
-{"year":"2021","title":"Surprise Language Challenge: Developing a Neural Machine Translation System between Pashto and English in Two Months","authors":["A Birch, B Haddow, AVM Barone, J Helcl, J Waldendorf…"],"snippet":"… Finally, we also use the Pashto-English corpus that was submitted by the Bytedance team to the WMT 2020 cleaning shared task (Koehn et al., 2020). For pretraining the German–English model we use exisiting WMT data …","url":["https://aclanthology.org/2021.mtsummit-research.8.pdf"]}
-{"year":"2021","title":"Surveillance of COVID-19 Pandemic using Social Media: A Reddit Study in North Carolina","authors":["C Whitfield, Y Liu, M Anwar - arXiv preprint arXiv:2106.04515, 2021"],"snippet":"… The custom NER models trained for this study were based on spaCy's multi-task convolutional neural network (CNN) which was trained using the OntoNotes 6 corpus, and contain GloVe vectors [31] that were trained on Common Crawl …","url":["https://arxiv.org/pdf/2106.04515"]}
-{"year":"2021","title":"Survey of Generative Methods for Social Media Analysis","authors":["S Matwin, A Milios, P Prałat, A Soares, F Théberge - arXiv preprint arXiv:2112.07041, 2021"],"snippet":"This survey draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the research in generative methods for the analysis of social media data. It fills a void, as the existing survey articles are either much narrower in their scope or are dated …","url":["https://arxiv.org/pdf/2112.07041"]}
-{"year":"2021","title":"SwissDial: Parallel Multidialectal Corpus of Spoken Swiss German","authors":["P Dogan-Schönberger, J Mäder, T Hofmann - arXiv preprint arXiv:2103.11401, 2021"],"snippet":"… Page 2. 2. Related Work For various high-resource languages, there are parallel text corpora [2, 3, 4] and monolingual text corpora such as [5], Google News, Common Crawl that are used for the tasks of language modeling and machine translation …","url":["https://arxiv.org/pdf/2103.11401"]}
-{"year":"2021","title":"Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity","authors":["W Fedus, B Zoph, N Shazeer - arXiv preprint arXiv:2101.03961, 2021"],"snippet":"Page 1. SWITCH TRANSFORMERS: SCALING TO TRILLION PARAMETER MODELS WITH SIMPLE AND EFFICIENT SPARSITY William Fedus∗ Google Brain liamfedus@google.com Barret Zoph∗ Google Brain barretzoph@google.com …","url":["https://arxiv.org/pdf/2101.03961"]}
-{"year":"2021","title":"SYMBOLIC AND NEURAL APPROACHES TO NATURAL LANGUAGE INFERENCE","authors":["H Hu - 2021"],"snippet":"Page 1. SYMBOLIC AND NEURAL APPROACHES TO NATURAL LANGUAGE INFERENCE Hai Hu Submitted to the faculty of the University Graduate School in partial fulfillment of the requirements for the degree …","url":["https://scholarworks.iu.edu/dspace/bitstream/handle/2022/26642/dissertation_final_hai_hu.pdf?sequence=1"]}
-{"year":"2021","title":"Symbolic Knowledge Distillation: from General Language Models to Commonsense Models","authors":["P West, C Bhagavatula, J Hessel, JD Hwang, L Jiang… - arXiv preprint arXiv …, 2021"],"snippet":"The common practice for training commonsense models has gone from-human-to-corpus-to-machine: humans author commonsense knowledge graphs in order to train commonsense models. In this work, we investigate an alternative, from-machine-to-corpus-to-machine …","url":["https://arxiv.org/pdf/2110.07178"]}
-{"year":"2021","title":"Syntax-Enhanced Pre-trained Model","authors":["Z Xu, D Guo, D Tang, Q Su, L Shou, M Gong, W Zhong… - arXiv preprint arXiv …, 2020"],"snippet":"… pre-training and fine-tuning stages. We construct a pre-training dataset by applying an offthe-shell dependency parser (Qi et al., 2020) to one billion sentences from common crawl news. With these data, we introduce a syntax …","url":["https://arxiv.org/pdf/2012.14116"]}
-{"year":"2021","title":"Systemic racism: individuals and interactions, institutions and society","authors":["MR Banaji, ST Fiske, DS Massey - Cognitive Research: Principles and Implications, 2021","ST Fiske, DS Massey - Cognitive Research, 2021"],"snippet":"Systemic racism is a scientifically tractable phenomenon, urgent for cognitive scientists to address. This tutorial reviews the built-in systems that undermine life opportunities and outcomes by racial category, with a focus on challenges to Black …","url":["https://cognitiveresearchjournal.springeropen.com/articles/10.1186/s41235-021-00349-3","https://search.proquest.com/openview/05ee76c9a6696a3ec2aa4bcd2f966d1d/1?pq-origsite=gscholar&cbl=4402895"]}
-{"year":"2021","title":"Tab2KG: Semantic Table Interpretation with Lightweight Semantic Profiles","authors":["S Gottschalk, E Demidova"],"snippet":"… Subsequent steps such as property mapping are based on the results of this lookup step. However, as shown by Ritze et al. [14], only about 3% of the tables contained in the 3.5 billion HTML pages of the Common …","url":["http://semantic-web-journal.net/system/files/swj2731.pdf"]}
-{"year":"2021","title":"TABBIE: Pretrained Representations of Tabular Data","authors":["H Iida, D Thai, V Manjunatha, M Iyyer - arXiv preprint arXiv:2105.02584, 2021"],"snippet":"… TaBERT's pretraining data was not publicly released at the time of our work, but their dataset consists of 26.6M ta- bles from Wikipedia and the Common Crawl. We thus form a pretraining dataset of equivalent size by combining …","url":["https://arxiv.org/pdf/2105.02584"]}
-{"year":"2021","title":"Tabular Data Concept Type Detection Using Star-Transformers","authors":["Y Zhou, S Singh, C Christodoulopoulos - 2021"],"snippet":"… We directly fine-tune TURL's concept type detection model on our dataset using its re- leased code. 4.2 Training Details We use 300 dimensional Glove [12] word embeddings pre-trained on 42 billion uncased tokens from Common …","url":["https://assets.amazon.science/80/73/db622f0344878705986e0a99dc1f/tabular-data-concept-type-detection-using-star-transformers.pdf"]}
-{"year":"2021","title":"Tackling Cyber-Aggression: Identification and Fine-Grained Categorization of Aggressive Texts on Social Media using Weighted Ensemble of Transformers","authors":["O Sharif, MM Hoque - Neurocomputing, 2021"],"snippet":"… This model is trained with monolingual Bengali CommonCrawl corpus and utilises the BERT base model’s architecture. XLM-R is a cross-lingual model which outdoes m-BERT in various benchmarks. This model is built over the of 100 …","url":["https://www.sciencedirect.com/science/article/pii/S0925231221018567"]}
-{"year":"2021","title":"Tackling Italian University Assessment Tests with Transformer-Based Language Models","authors":["D Puccinelli, S Demartini, PL Ferrari - 2021"],"snippet":"Cloze tests are a great tool to asses reading proficiency as well as analytical thinking, and are therefore employed in admission and assessment tests at various levels of the education system in multiple countries. In Italy, cloze tests are administered to …","url":["http://ceur-ws.org/Vol-3033/paper20.pdf"]}
-{"year":"2021","title":"Targeted Feedback Generation for Constructed-Response Questions","authors":["J Zhao, K Larson, W Xu, N Gattani, C Thille - 2020"],"snippet":"… TextRank, BERT basic, and BERT fine-tuned models achieve better FPR scores. For non-transformer-based approaches, we ap- ply multitask CNN (trained on OntoNotes) and GloVe (1.2m 300d vectors trained on Common Crawl) as our embedding methods …","url":["https://assets.amazon.science/bb/f6/ea2108414befb188d20e2b75ac87/targeted-feedback-generation-for-constructed-response-questions.pdf"]}
-{"year":"2021","title":"Task Aware Multi-Task Learning for Speech to Text Tasks","authors":["S Indurthi, MA Zaidi, NK Lakumarapu, B Lee, H Han… - ICASSP 2021-2021 IEEE …, 2021"],"snippet":"… We use the following datasets for ST English-German, ASR English, MT English-German tasks: MT En-De: We use the Open Subtitles [9] and WMT 19 corpora. WMT 19 consists of Common Crawl, Europarl v9, and News …","url":["https://ieeexplore.ieee.org/abstract/document/9414703/"]}
-{"year":"2021","title":"Taxonomy Enrichment with Text and Graph Vector Representations","authors":["I Nikishina, M Tikhomirov, V Logacheva, Y Nazarov…"],"snippet":"Page 1. Semantic Web 0 (0) 1 1 IOS Press 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 11 11 12 12 13 13 14 14 15 15 16 16 17 17 18 18 19 19 20 20 21 21 22 22 23 23 24 24 25 25 26 26 27 27 28 28 29 29 30 30 31 31 32 32 33 …","url":["http://www.semantic-web-journal.net/system/files/swj2729.pdf"]}
-{"year":"2021","title":"TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels","authors":["M Imran, U Qazi, F Ofli - arXiv preprint arXiv:2110.03664, 2021"],"snippet":"… Although the original XLM-R model is trained on one hundred languages using more than two terabytes of filtered CommonCrawl data4, its Twitter variant XLM-T achieves better performance on a large multilingual benchmark for sentiment analysis17 …","url":["https://arxiv.org/pdf/2110.03664"]}
-{"year":"2021","title":"Technology-Skill Complementarity and Labor Displacement: Evidence from Linking Two Centuries of Patents with Occupations","authors":["L Kogan, D Papanikolaou, LDW Schmidt, B Seegmiller"],"snippet":"Abstract We construct new technology indicators using textual analysis of patent documents and occupation task descriptions that span of two centuries (1850–2010). At the industry level, improvements in technology are associated with higher labor …","url":["https://www.bryanseegmiller.com/files/Draft_v2021-1017.pdf"]}
-{"year":"2021","title":"Temporal Effects on Pre-trained Models for Language Processing Tasks","authors":["O Agarwal, A Nenkova - arXiv preprint arXiv:2111.12790, 2021"],"snippet":"Keeping the performance of language technologies optimal as time passes is of great practical interest. Here we survey prior work concerned with the effect of time on system performance, establishing more nuanced terminology for discussing the …","url":["https://arxiv.org/pdf/2111.12790"]}
-{"year":"2021","title":"Term-community-based topic detection with variable resolution","authors":["A Hamm, S Odrowski - arXiv preprint arXiv:2103.13550, 2021"],"snippet":"… The pre-trained fastText models are shallow neural nets with output vectors of dimension 300 that were trained on huge text collections from Wikipedia and Common Crawl, using the so called CBOW task of predicting a word by its surrounding words …","url":["https://arxiv.org/pdf/2103.13550"]}
-{"year":"2021","title":"Term-Community-Based Topic Detection with Variable Resolution. Information 2021, 12, 221","authors":["A Hamm, S Odrowski - 2021"],"snippet":"Page 1. information Article Term-Community-Based Topic Detection with Variable Resolution Andreas Hamm * and Simon Odrowski Citation: Hamm, A.; Odrowski, S. Term-Community-Based Topic Detection with …","url":["https://128.84.4.13/pdf/2103.13550.pdf"]}
-{"year":"2021","title":"Text Analysis for Psychology: Methods, Principles, and Practices","authors":["B Kennedy, A Ashokkumar, RL Boyd, M Dehghani - 2021"],"snippet":"Page 1. Running Head: TEXT ANALYSIS METHODS FOR PSYCHOLOGY Text Analysis for Psychology: Methods, Principles, and Practices Brendan Kennedy​1​, Ashwini Ashokkumar​2​, Ryan Boyd​3–5​, Morteza …","url":["https://psyarxiv.com/h2b8t/download?format=pdf"]}
-{"year":"2021","title":"Text Classification for Predicting Multi-level Product Categories","authors":["H Jahanshahi, O Ozyegen, M Cevik, B Bulut, D Yigit… - arXiv preprint arXiv …, 2021"],"snippet":"… next-sentence pretraining objectives, and training with larger batch sizes. For our experiments, we use the multi-lingual version of this architecture pretrained on 2.5TB of CommonCrawl data in 100 languages using a …","url":["https://arxiv.org/pdf/2109.01084"]}
-{"year":"2021","title":"Text Normalization for Low-Resource Languages of Africa","authors":["A Zupon, E Crew, S Ritchie - arXiv preprint arXiv:2103.15845, 2021"],"snippet":"… The size of available corpora also varies greatly from 10K sentences (Swahili Newscrawl) to 1M sentences (Afrikaans Web and Mixed). The OSCAR9 corpus is a multilingual corpus of data obtained by language classification and filtering of the Common Crawl corpus …","url":["https://arxiv.org/pdf/2103.15845"]}
-{"year":"2021","title":"Text Similarity Techniques for Matching Employee Objectives","authors":["A Elnaggar, M Ghanem, F Matthes, AD Mckinnon…"],"snippet":"… https://huggingface.co/albert-xxlarge-v2 11. https://huggingface.co/distilbertbase-uncased 12. https://huggingface.co/roberta-base 13. https:// commoncrawl.org/2016/10/news-dataset-available/ 14. https://github.com …","url":["https://wwwmatthes.in.tum.de/file/wpu1f6pvjvt4/Sebis-Public-Website/-/Guided-Research-Mohab-Ghanem/Text_Similarity_Techniques_For_Matching_Employee_Objective.pdf"]}
-{"year":"2021","title":"Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents","authors":["U Bhattacharya, N Rewkowski, A Banerjee, P Guhan… - arXiv preprint arXiv …, 2021"],"snippet":"… W = [w1 ... ws ... wTsen ], with Tsen being the maximum sentence length, using word embeddings ws ∈ R300. We obtain the word em- beddings using the GloVe model pre-trained on the Common Crawl corpus [52]. We opt …","url":["https://arxiv.org/pdf/2101.11101"]}
-{"year":"2021","title":"Text2Gestures: A Transformer-Based Network for Generating Emotive Body Gestures for Virtual Agents** This work has been supported in part by ARO Grants …","authors":["U Bhattacharya, N Rewkowski, A Banerjee, P Guhan… - 2021 IEEE Virtual Reality …, 2021"],"snippet":"… W = [w1 ... ws ... wTsen], with Tsen being the maximum sentence length, using word embeddings ws ∈ R300. We obtain the word embeddings using the GloVe model pre-trained on the Common Crawl corpus [52]. We opt …","url":["https://ieeexplore.ieee.org/abstract/document/9417647/"]}
-{"year":"2021","title":"TextSETTR: Few-Shot Text Style Extraction and Tunable Targeted Restyling","authors":["P Rileya, N Constantb, M Guob, G Kumarc, D Uthusb…"],"snippet":"… For this purpose, we train a single general-purpose TextSETTR model, with the same configuration as our model from Section 3, except fine-tuned for 200k steps on English Common Crawl data (the same “C4” data that T5 pretrained on) instead of Amazon reviews …","url":["https://aclanthology.org/2021.acl-long.293.pdf"]}
-{"year":"2021","title":"Textual Analysis of News for Stock Market Prediction","authors":["AV Bogdanov, M Bogan, A Stankus - … Conference on Computational Science and Its …, 2021"],"snippet":"… So, for Word2Vec there are pre-trained word-vectors on Google news with a dimension of 300. There is a dictionary for GloVe trained on various textual data, including on news with Common Crawl with a dimension of 300 …","url":["https://link.springer.com/chapter/10.1007/978-3-030-87010-2_22"]}
-{"year":"2021","title":"TGIF: Tree-Graph Integrated-Format Parser for Enhanced UD with Two-Stage Generic-to Individual-Language Finetuning","authors":["T Shi, L Lee - arXiv preprint arXiv:2107.06907, 2021"],"snippet":"… Representation The first step is to extract contextual representations. For this purpose, we use the pre-trained XLM-R model (Conneau et al., 2020), which is trained on multilingual CommonCrawl data and supports all 17 languages in the shared task …","url":["https://arxiv.org/pdf/2107.06907"]}
-{"year":"2021","title":"The 2020 Bilingual, Bi-Directional WebNLG+ Shared Task Overview and Evaluation Results (WebNLG","authors":["T Ferreira, C Gardent, N Ilinykh, C van der Lee, S Mille…"],"snippet":"… 3.3 Mono-task, Bilingual Approaches cuni-ufal. The mBART model (Liu et al., 2020) is pre-trained for multilingual denoising on the large-scale multilingual CC25 corpus extracted from Common Crawl, which contains …","url":["https://pure.uvt.nl/ws/portalfiles/portal/48450135/2020.webnlg_1.7.pdf"]}
-{"year":"2021","title":"The Advantages of Human Evaluation of Sociomedical Question Answering Systems","authors":["V Firsanova - International Journal of Open Information Technologies, 2021"],"snippet":"… XLM-RoBERTa is a model for one hundred languages trained on CommonCrawl data. According to the developers, this model improved the performance on low-resource languages of other crossand multilingual models developed earlier. This model is …","url":["http://injoit.ru/index.php/j1/article/download/1227/1166"]}
-{"year":"2021","title":"The Croatian psycholinguistic database: Estimates for 6000 nouns, verbs, adjectives and adverbs","authors":["A Peti-Stantić, M Anđel, V Gnjidić, G Keresteš… - Behavior Research Methods, 2021"],"snippet":"Psycholinguistic databases containing ratings of concreteness, imageability, age of acquisition, and subjective frequency are used in psycholinguistic and.","url":["https://link.springer.com/article/10.3758/s13428-020-01533-x"]}
-{"year":"2021","title":"The Danish Gigaword Corpus","authors":["L Derczynski, ITU Copenhagen, MR Ciosici, R Baglini…"],"snippet":"… Massive, monolithic, automatically collected datasets of web content, such as Common Crawl, support the training of large language models but suffer from quality issues (Radford et al., 2019) and bias (Ferrer et al., 2021) …","url":["http://derczynski.com/papers/dagw.pdf"]}
-{"year":"2021","title":"The Data Set Knowledge Graph: Creating a Linked Open Data Source for Data Sets","authors":["M Färber, D Lamprecht - 2021"],"snippet":"ABSTRACT Several scholarly knowledge graphs have been proposed to model and analyze the academic landscape. However, although the number of data sets has increased remarkably in recent years, these knowledge graphs do not primarily …","url":["https://www.aifb.kit.edu/images/6/66/DSKG_QSS2021_v0.pdf"]}
-{"year":"2021","title":"The Demand for Executive Skills","authors":["J Fuller, S Hansen, T Ramdas, R Sadun - 2021"],"snippet":"… tions. 'Off-the-shelf' models—typically estimated on large corpora that are representative of written language such as Wikipedia and Common Crawl for English—do exist, but se- mantic relatedness in generic English may …","url":["https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3886751"]}
-{"year":"2021","title":"The Effect of Domain and Diacritics in Yorubá–English Neural Machine Translation","authors":["DI Adelani, D Ruiter, JO Alabi, D Adebonojo, A Ayeni… - Proceedings of Machine …, 2021"],"snippet":"… Fine-tuning mT5 We examine a transfer learning approach by fine-tuning a massively multilingual model mT5 (Xue et al., 2021). mT5 had been pre-trained on 6.3T tokens originating from Common Crawl in 101 languages (including Yor`ubá) …","url":["https://www.cs.upc.edu/~cristinae/CV/docs/2021.mtsummit.adelani.pdf"]}
-{"year":"2021","title":"The Effectiveness of Intermediate-Task Training for Code-Switched Natural Language Understanding","authors":["A Prasad, MA Rehan, S Pathak, P Jyothi - arXiv preprint arXiv:2107.09931, 2021"],"snippet":"… XLM-R uses a similar training objective as mBERT but is trained on orders of magnitude more data from the CommonCrawl corpus spanning 100 languages and yields competitive results on low-resource languages(Conneau et al., 2020) …","url":["https://arxiv.org/pdf/2107.09931"]}
-{"year":"2021","title":"The FinSim-2 2021 Shared Task: Learning Semantic Similarities for the Financial Domain","authors":["Y Mansar, J Kang, IE Maarouf - Companion Proceedings of the Web Conference 2021, 2021"],"snippet":"… where english words of similar meaning are grouped into sets called synsets, Wikidata is a knowledge base maintained by the Wikimedia Foundation and contains entities like \"MSCI World\" and finally WebIsALOD is a hypernymy …","url":["https://dl.acm.org/doi/abs/10.1145/3442442.3451381"]}
-{"year":"2021","title":"The Impact of Main Content Extraction on Near-Duplicate Detection","authors":["M Fröbe, M Hagen, J Bevendorff, M Völske, B Stein… - arXiv preprint arXiv …, 2021"],"snippet":"… Widely available web crawls—most notably the ClueWebs† and the Common Crawl‡—contain the (near-)duplicate documents that the crawler encountered during the crawling process. While the inclusion of near-duplicates enables many …","url":["https://arxiv.org/pdf/2111.10864"]}
-{"year":"2021","title":"The Impact of Positional Encodings on Multilingual Compression","authors":["V Ravishankar, A Søgaard - arXiv preprint arXiv:2109.05388, 2021"],"snippet":"… The second corpus uses the English Wikipedia as the training split, and Common Crawl as validation. We present corpus statistics in Table 3. For each corpus, we learn and apply a BPE vocabulary of size 2048. Train Validation Bible 30602 9080 Wikipedia 50000 20000 …","url":["https://arxiv.org/pdf/2109.05388"]}
-{"year":"2021","title":"The information retrieval anthology 2021: inaugural status report and challenges ahead","authors":["M Potthast, B Stein, M Hagen - ACM SIGIR Forum, 2021"],"snippet":"… Originally developed as a reproducible baseline search engine for the ClueWeb09, the ClueWeb12, and the Common Crawl, ChatNoir's distributed Elasticsearch backend also enables the inclusion of other kinds of indexes …","url":["https://dl.acm.org/doi/abs/10.1145/3476415.3476417"]}
-{"year":"2021","title":"The Information Retrieval Anthology","authors":["M Potthast, S Günther, J Bevendorff, JP Bittner… - 2021"],"snippet":"… To allow users to easily search the IR Anthology, we provide a dedicated search index accessible via our search engine ChatNoir [6], a proven web search engine indexing around 5 billion web pages from the ClueWeb crawls and Common Crawl versions …","url":["https://webis.de/downloads/publications/papers/potthast_2021j.pdf"]}
-{"year":"2021","title":"The IWSLT 2021 BUT Speech Translation Systems","authors":["HK Vydana, M Karafi'at, L Burget - arXiv preprint arXiv:2107.06155, 2021"],"snippet":"… Corpora #Sentences Audio Source text Target Text MT -Train-set ParaCrawl v3 31M - OpenSubtitles 2018 12M - Rapid 2019 1.5M - Europarl v9 1.81M - News Commentary 365K - Common Crawl 2.4M - Wikititles …","url":["https://arxiv.org/pdf/2107.06155"]}
-{"year":"2021","title":"The Language of Situational Empathy","authors":["KE ZHOU, LM AIELLO, S SCEPANOVIC, D QUERCIA… - 2021"],"snippet":"… Specifically, we averaged the 300-dimensional embedding vectors for each lexicon word using GloVe embeddings [55] trained on the Common Crawl corpus8. The above two approaches used a machine learning algorithm on top of our lexicon for the final prediction …","url":["https://social-dynamics.net/docs/empathy.pdf"]}
-{"year":"2021","title":"The NiuTrans End-to-End Speech Translation System\\\\for IWSLT 2021 Offline Task","authors":["C Xu, X Liu, X Liu, L Wang, C Huang, T Xiao, J Zhu - arXiv preprint arXiv:2107.02444, 2021"],"snippet":"… Task Corpora Size Time ASR LibriSpeech 281241 960h Common Voice 1000000 1387h Total 1281241 2347h MT CommonCrawl 2014304 - Europarl 1802849 - ParaCrawl 31528317 - Wiki 5714363 - OpenSubtitles 14449099 - Total 55508932 - ST …","url":["https://arxiv.org/pdf/2107.02444"]}
-{"year":"2021","title":"The NiuTrans Machine Translation Systems for WMT21","authors":["S Zhou, T Zhou, B Wei, Y Luo, Y Mu, Z Zhou, C Wang… - arXiv preprint arXiv …, 2021"],"snippet":"… For the ParaCrawl v7.1, we only selected 8.5 million data according to the score of sentences provided by the dataset. We chose all of News Crawl and News Commentary and 12 million data sampled from Common Crawl for the Japanese monolingual data …","url":["https://arxiv.org/pdf/2109.10485"]}
-{"year":"2021","title":"The Pile: An 800GB Dataset of Diverse Text for Language Modeling","authors":["L Gao, S Biderman, S Black, L Golding, T Hoppe… - arXiv preprint arXiv …, 2020"],"snippet":"… The growing need for data in language modeling has caused most existing large-scale language models to turn to the Common Crawl for most or all of their data (Brown et al., 2020; Raffel et al., 2019). While training on the …","url":["https://arxiv.org/pdf/2101.00027"]}
-{"year":"2021","title":"The Potential of Automated Text Analytics in Social Knowledge Building","authors":["R Németh, J Koltai - Pathways Between Social Science and Computational …, 2021"],"snippet":"… Finally, big data are often samples themselves, resulting from an unknown or hard-to-formalize sampling procedure. See, eg, Common Crawl (http://commoncrawl.org), an open repository of textual web page data …","url":["https://link.springer.com/chapter/10.1007/978-3-030-54936-7_3"]}
-{"year":"2021","title":"The Power of Anchor Text in the Neural Retrieval Era","authors":["M Fröbe, S Günther, M Probst, M Potthast, M Hagen"],"snippet":"… and Eiron and McCurley on MS MARCO, we extract anchor texts from Common Crawl snapshots. We randomly select one snapshot from each year from 2016 to 2021 (each containing 1.7–3.4 billion documents) and extract the anchor texts of …","url":["https://webis.de/downloads/publications/papers/froebe_2022a.pdf"]}
-{"year":"2021","title":"The practical ethics of bias reduction in machine translation: why domain adaptation is better than data debiasing","authors":["M Tomalin, B Byrne, S Concannon, D Saunders… - Ethics and Information …, 2021"],"snippet":"This article probes the practical ethical implications of AI system design by reconsidering the important topic of bias in the datasets used to train auton.","url":["https://link.springer.com/article/10.1007/s10676-021-09583-1"]}
-{"year":"2021","title":"The Rediscovery Hypothesis: Language Models Need to Meet Linguistics","authors":["T Maxat - 2022","V Nikoulina, M Tezekbayev, N Kozhakhmet… - arXiv preprint arXiv …, 2021"],"snippet":"… English-to-German translation. The authors used the CommonCrawl-840B GloVe model (Pennington et al., 2014) for English word vectors, which was completely fixed during pretraining, and we follow their setup. This entails that …","url":["https://arxiv.org/pdf/2103.01819","https://nur.nu.edu.kz/bitstream/handle/123456789/6141/Tezekbayev,%20Maxat.pdf?sequence=1"]}
-{"year":"2021","title":"The SPECTRANS System Description for the WMT21 Terminology Task","authors":["NBDCB Faye, ZYKHM Mojca, PJBYG Wisniewski…"],"snippet":"… The latter did better for sacreBLEU and Window Overlap Accuracy (n=3) but probably having seen the terminological resources in the training data gave an edge for Exact-Match Accuracy to our model trained with Common Crawl and the terminological …","url":["http://www.statmt.org/wmt21/pdf/2021.wmt-1.80.pdf"]}
-{"year":"2021","title":"The Trade-offs of Domain Adaptation for Neural Language Models","authors":["D Iter, D Grangier - arXiv preprint arXiv:2109.10274, 2021"],"snippet":"Page 1. The Trade-offs of Domain Adaptation for Neural Language Models David Grangier Google, Mountain View, CA grangier@google.com Dan Iter∗ Stanford, Palo Alto, CA daniter@stanford.edu Abstract This work connects …","url":["https://arxiv.org/pdf/2109.10274"]}
-{"year":"2021","title":"The University of Edinburgh's Bengali-Hindi Submissions to the WMT21 News Translation Task","authors":["P Pal, AF Aji, P Chen, S Sen"],"snippet":"Abstract We describe the University of Edinburgh’s Bengali↔ Hindi constrained systems submitted to the WMT21 News Translation task. We submitted ensembles of Transformer models built with large-scale back-translation and finetuned on subsets …","url":["https://www.statmt.org/wmt21/pdf/2021.wmt-1.16.pdf"]}
-{"year":"2021","title":"The University of Edinburgh's English-German and English-Hausa Submissions to the WMT21 News Translation Task","authors":["PCJHU Germann, LBN Bogoychev…"],"snippet":"… Page 2. • Crawled parallel: ParaCrawl, WikiMatrix, CommonCrawl, and WikiTitles … For back-translation, we use 9.5 million monolingual Hausa sentences from Common Crawl, Extended Common Crawl, and News Crawl provided by the task organizers …","url":["https://pinzhenchen.github.io/paper/2021-wmt-deen.pdf"]}
-{"year":"2021","title":"The USTC-NELSLIP Systems for Simultaneous Speech Translation Task at IWSLT 2021","authors":["D Liu, M Du, X Li, Y Hu, L Dai - arXiv preprint arXiv:2107.00279, 2021"],"snippet":"… sentences from it. Corpus Sentences EN→DE MuST-C(v2) 229.7k Europarl 1828.5k Rapid-2019 1531.3k WIT3-TED 209.5k Commoncrawl 2399.1k WikiMatrix 6227.2k Wikititles 1382.6k Paracrawl 82638.2k EN→JA WIT3-TED 225.0 …","url":["https://arxiv.org/pdf/2107.00279"]}
-{"year":"2021","title":"The USYD-JD Speech Translation System for IWSLT 2021","authors":["L Ding, D Wu, D Tao - arXiv preprint arXiv:2107.11572, 2021"],"snippet":"… Corpus #Sent. commoncrawl English 4,366,344 commoncrawl Swahili 38,928 + upsampling (14×) 544,992 … Mono. Corpus for Tagged BT #Sent. Totally collected corpus commoncrawl English 30,513,498 Cleaned corpus …","url":["https://arxiv.org/pdf/2107.11572"]}
-{"year":"2021","title":"The Utility and Interplay of Gazetteers and Entity Segmentation for Named Entity Recognition in English","authors":["O Agarwal, A Nenkova"],"snippet":"… We use two input word representations: the 300-d GloVe vectors trained on Common Crawl (Pennington et al., 2014), which is the dominant representation in NER, and the 1024-d contextual ELMo (Peters et al …","url":["https://aclanthology.org/2021.findings-acl.349.pdf"]}
-{"year":"2021","title":"The Volctrans Neural Speech Translation System for IWSLT 2021","authors":["C Zhao, Z Liu, J Tong, T Wang, M Wang, R Ye, Q Dong… - arXiv preprint arXiv …, 2021"],"snippet":"… Data Combination and Sampling Strategy We train transformer models with different combina5http://www.statmt.org/wmt20/ translation-task.html, including Common Crawl, tions of data sets because increasing the model's diversity can benefit the model ensemble …","url":["https://arxiv.org/pdf/2105.07319"]}
-{"year":"2021","title":"The Web Is Your Oyster--Knowledge-Intensive NLP against a Very Large Web Corpus","authors":["A Piktus, F Petroni, V Karpukhin, D Okhonko… - arXiv preprint arXiv …, 2021"],"snippet":"… CCNet processes Common Crawl by performing deduplication, language identification and quality filtering (articles are split into three quality tiers: head, … We pick the CCNet snapshot corresponding to the August 2019 Common Crawl …","url":["https://arxiv.org/pdf/2112.09924"]}
-{"year":"2021","title":"TheEyeCorpus: Experiments in Reducing NLP Bias and Identifiability for Large LMs","authors":["J Herrera, D Bernal"],"snippet":"… 2020), a state of the art large language model, that used terabytes of the mostly unfiltered Common Crawl. Making corpuses is usually as simple as downloading and extracting the common crawl database. This isn’t the most ideal approach …","url":["https://openreview.net/pdf?id=CxMuhSuXIW"]}
-{"year":"2021","title":"Thor at Touché 2021: Argument Retrieval for Comparative Questions","authors":["E Shirshakova, A Wattar - Working Notes of CLEF, 2021"],"snippet":"… doi:10.1145/2348283.2348429. [4] J. Bevendorff, B. Stein, M. Hagen, M. Potthast, Elastic ChatNoir: Search Engine for the ClueWeb and the Common Crawl, in: L. Azzopardi, A. Hanbury, G. Pasi, B. Piwowarski (Eds.), Advances in Information Retrieval …","url":["http://ceur-ws.org/Vol-2936/paper-219.pdf"]}
-{"year":"2021","title":"Three Essays on the Role of Unstructured Data in Marketing Research","authors":["ISK Chakraborty - 2021"],"snippet":"Page 1. Abstract Three Essays on the Role of Unstructured Data in Marketing Research Ishita Sunity Kumar Chakraborty 2021 This thesis studies the use of firm and user-generated unstructured data (eg, text and videos) for …","url":["https://search.proquest.com/openview/c265768db80d44b3e2c4fef8b9b0df95/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"Time and Cost Prediction Models for Language Classification Over a Large Corpus on Spark","authors":["JB Rodrigues, GC Vasconcelos, PRM Maciel - 2020 IEEE Symposium Series on …, 2020"],"snippet":"… All nodes were managed by a Debian GNU/Linux 9 OS, Apache Spark 2.3, and Apache Hadoop 2.9. 2 The Common Crawl Foundation - http://commoncrawl.org/ 1) Analysis of Variance: Fig. 1 displays the results over the log-transformed data …","url":["https://ieeexplore.ieee.org/abstract/document/9308299/"]}
-{"year":"2021","title":"TMEKU System for the WAT2021 Multimodal Translation Task","authors":["Y Zhao, M Komachi, T Kajiwara, C Chu - red"],"snippet":"… Subsequently, we utilize fastText (Bojanowski et al., 2017) to learn subword embeddings. We use a pre-trained model4 containing two million word vectors trained with subword information on Common Crawl (600B tokens) …","url":["https://aclanthology.org/2021.wat-1.20.pdf"]}
-{"year":"2021","title":"Token-Level Multilingual Epidemic Dataset for Event Extraction","authors":["S Mutuvi, E Boros, A Doucet, G Lejeune, A Jatowt… - International Conference on …, 2021"],"snippet":"… 8. XLM-RoBERTa-base was trained on 2.5TB of CommonCrawl data in 100 languages. References. 1. Aiello, AE, Renson, A., Zivich, PN: Social media-and internet-based disease surveillance for public health. Annu. Rev. Public …","url":["https://link.springer.com/chapter/10.1007/978-3-030-86324-1_6"]}
-{"year":"2021","title":"Touché Task 2: Comparative Argument Retrieval. A Document-based Search Engine for Answering Comparative Questions","authors":["D Helmrich, D Streitmatter, F Fuchs, M Heykeroth - Working Notes of CLEF, 2021"],"snippet":"… eg faster). The results are sentences from the Common Crawl2 retrieved via ElasticSearch [7] and then reduced to comparative sentences (either by certain keywords or a machine learning approach) and ranked. The system …","url":["http://ceur-ws.org/Vol-2936/paper-214.pdf"]}
-{"year":"2021","title":"Toward Gender-Inclusive Coreference Resolution: An Analysis of Gender and Bias throughout the Machine Learning Lifecyle","authors":["YT Cao, H Daumé - Computational Linguistics, 2021"],"snippet":"Page 1. Toward Gender-Inclusive Coreference Resolution An Analysis of Gender and Bias throughout the Machine Learning Lifecyle∗ Yang Trista Cao∗∗ University of Maryland Hal Daumé III† Microsoft Research University of Maryland …","url":["https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli_a_00413/1928379/coli_a_00413.pdf"]}
-{"year":"2021","title":"Toward the Understanding of Deep Text Matching Models for Information Retrieval","authors":["L Chen, Y Lan, L Pang, J Guo, X Cheng - arXiv preprint arXiv:2108.07081, 2021"],"snippet":"… For the input word embeddings, we initialize the embedding layer with the 300-dimensional Glove[29] word vectors pre-trained in the 840B Common Crawl corpus4. For the out-of … 3https://github.com/NTMC-Community …","url":["https://arxiv.org/pdf/2108.07081"]}
-{"year":"2021","title":"Towards a Machine Learning Based Generalizable Framework for Detecting COVID-19 Misinformation on Social Media","authors":["Y Chen - 2021"],"snippet":"Page 1. University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln …","url":["https://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1232&context=computerscidiss"]}
-{"year":"2021","title":"TOWARDS A ROMANIAN END-TO-END AUTOMATIC SPEECH RECOGNITION BASED ON DEEPSPEECH2","authors":["AM AVRAM, P Vasile, D Tufiș"],"snippet":"… [17]) layers that have 768 units. The output of the LSTM layers is 7 https://commoncrawl org/ 8 We used langdetect to detect Romanian sentences: https://github.com/Mimino666/ langdetect. Page 4. Andrei-Marius AVRAM, Vasile PĂIȘ, Dan TUFIȘ 398 …","url":["https://academiaromana.ro/sectii2002/proceedings/doc2020-4/11-Avram_Tufis.pdf"]}
-{"year":"2021","title":"Towards better subtitles: A multilingual approach for punctuation restoration of speech transcripts","authors":["NM Guerreiro, R Rei, F Batista - Expert Systems with Applications, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0957417421011180"]}
-{"year":"2021","title":"Towards Change Detection in Privacy Policies with Natural Language Processing","authors":["A Adhikari, R Dewri - 2021 18th International Conference on Privacy …, 2021"],"snippet":"Privacy policies notify users about the privacy practices of websites, mobile apps, and other products and services. However, users rarely read them and struggle to understand their contents. Due to the complicated nature of these documents, it gets …","url":["https://ieeexplore.ieee.org/abstract/document/9647767/"]}
-{"year":"2021","title":"Towards Continual Knowledge Learning of Language Models","authors":["J Jang, S Ye, S Yang, J Shin, J Han, G Kim, SJ Choi… - arXiv preprint arXiv …, 2021"],"snippet":"… 3CC-RECENTNEWS consists of 221,779 articles (∼168M tokens), which is estimated to be about 750 times smaller than C4, a cleansed version of the April 2019 Common Crawl dataset (https://commoncrawl.org/) that was …","url":["https://arxiv.org/pdf/2110.03215"]}
-{"year":"2021","title":"Towards Continual Learning for Multilingual Machine Translation via Vocabulary Substitution","authors":["X Garcia, N Constant, AP Parikh, O Firat - arXiv preprint arXiv:2103.06799, 2021"],"snippet":"Page 1. Towards Continual Learning for Multilingual Machine Translation via Vocabulary Substitution Xavier Garcia and Noah Constant and Ankur P. Parikh and Orhan Firat Google Research Mountain View California …","url":["https://arxiv.org/pdf/2103.06799"]}
-{"year":"2021","title":"Towards Controllable Neural Generation of Arguments","authors":["X Hua - 2021"],"snippet":"Page 1. Page 2. TOWARDS CONTROLLABLE NEURAL GENERATION OF ARGUMENTS A Dissertation Presented to The Khoury College of Computer Sciences of Northeastern University in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy …","url":["https://search.proquest.com/openview/b002097758dccea01c78e5461afe631f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"Towards Generalization in Dialog through Inductive Biases","authors":["S Mehri - 2021"],"snippet":"Abstract Generalization is imperative in dialog research. Data-driven models have been shown to be capable of performing specific tasks in constrained contexts, given ample data. However, the complexity of human communication necessitates …","url":["http://shikib.com/proposal.pdf"]}
-{"year":"2021","title":"Towards Learning a Joint Representation from Transformer in Multimodal Emotion Recognition","authors":["JJ Deng, CHC Leung - International Conference on Brain Informatics, 2021"],"snippet":"… modality of speech audio. As for text representation, we adopt fine-tuned Text-To-Text Transfer Transformer (T5) [18] model trained by a common crawl (C4) dataset to extract text embeddings. Operations of transfer learning …","url":["https://link.springer.com/chapter/10.1007/978-3-030-86993-9_17"]}
-{"year":"2021","title":"Towards Learning Language Agnostic Features for NLP in Low-resource Languages","authors":["AJ Antony - 2020"],"snippet":"Page 1. Towards Learning Language Agnostic Features for NLP in Low-resource Languages Thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and …","url":["http://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.bfe7226242875ee5.5468657369735f416c6c656e2e706466.pdf"]}
-{"year":"2021","title":"Towards Learning Terminological Concept Systems from Multilingual Natural Language Text","authors":["L Wachowiak, C Lang, B Heinisch, D Gromann - 3rd Conference on Language, Data …, 2021"],"snippet":"… [6]. We further added to the data by manually annotating around 200 acronym-term pairs from ACTER with relations other than synonymy and another 271 sample sentences from the Common Crawl News Corpus5 … 5 …","url":["https://drops.dagstuhl.de/opus/volltexte/2021/14558/pdf/OASIcs-LDK-2021-22.pdf"]}
-{"year":"2021","title":"Towards Making the Most of Dialogue Characteristics for Neural Chat Translation","authors":["Y Liang, C Zhou, F Meng, J Xu, Y Chen, J Su, J Zhou - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Towards Making the Most of Dialogue Characteristics for Neural Chat Translation Yunlong Liang1∗, Chulun Zhou2∗, Fandong Meng3, Jinan Xu1†, Yufeng Chen1, Jinsong Su2 and Jie Zhou3 1Beijing Key Lab of Traffic …","url":["https://arxiv.org/pdf/2109.00668"]}
-{"year":"2021","title":"Towards Making the Most of Multilingual Pretraining for Zero-Shot Neural Machine Translation","authors":["G Chen, S Ma, Y Chen, D Zhang, J Pan, W Wang… - arXiv preprint arXiv …, 2021"],"snippet":"… 2018, SPM) learned on the full Common Crawl data that includes 250k subword tokens. We do not apply additional preprocessing, such as truecasing or normalizing punctuation/characters. Following XLMR, we add the [BOS] and [EOS] tokens at the …","url":["https://arxiv.org/pdf/2110.08547"]}
-{"year":"2021","title":"Towards Model Understanding","authors":["D Pruthi - 2021"],"snippet":"While deep learning models have become increasingly accurate over the last decade, concerns about their (lack of) interpretability have taken a center stage. In response, a growing sub-field on interpretability and analysis of these models has …","url":["https://www.cs.cmu.edu/~ddanish/files/thesis.pdf"]}
-{"year":"2021","title":"Towards More Effective and Economic Sparsely-Activated Model","authors":["H Jiang, K Zhan, J Qu, Y Wu, Z Fei, X Zhang, L Chen… - arXiv preprint arXiv …, 2021","L Chen, Z Dou, X Qiu, Z Guo, R Lai, J Wu, E Hu…"],"snippet":"… RealNews is a large scale dataset about news articles from Common Crawl OpenWebText dataset contains a large amount of text data from social media platform Reddit. They scraped all outbound links from Reddit as data sources and …","url":["https://ar5iv.labs.arxiv.org/html/2110.07431","https://arxiv.org/pdf/2110.07431"]}
-{"year":"2021","title":"Towards Multi-modal Entity Resolution for Product Matching","authors":["M Wilke, E Rahm"],"snippet":"… Finally a procedure to query the internet archive2 for missing images is used. Due to its slow speed this method is only applied selectively to achieve higher coverage of images for the experiments. 1http://commoncrawl.org/ 2https://archive.org/ Page 3 …","url":["https://dbs.uni-leipzig.de/file/GvDB21_multi_modal_product_matching.pdf"]}
-{"year":"2021","title":"Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer","authors":["E Tokarchuk, J Rosendahl, W Wang, P Petrushkov… - arXiv preprint arXiv …, 2021"],"snippet":"Page 1. Towards Reinforcement Learning for Pivot-based Neural Machine Translation with Non-autoregressive Transformer Evgeniia Tokarchuk 1 2 Jan Rosendahl 2 Weiyue Wang 2 Pavel Petrushkov 1 Tomer Lancewicki 1 Shahram Khadivi 1 Hermann Ney 2 …","url":["https://arxiv.org/pdf/2109.13097"]}
-{"year":"2021","title":"Towards Selecting Informative Content for Cyber Threat Intelligence","authors":["P Panagiotou, C Iliou, K Apostolou, T Tsikrika… - 2021 IEEE International …, 2021"],"snippet":"… NER model. For their implementation, we used the Delft tool3, and the Glove Common Crawl embeddings4. The Bi- directional LSTM-CNNs-CRF architecture of [29] performs the best according to all metrics considered. We …","url":["https://ieeexplore.ieee.org/abstract/document/9527909/"]}
-{"year":"2021","title":"Towards Target-dependent Sentiment Classification in News Articles","authors":["F Hamborg, K Donnay, B Gipp"],"snippet":"… category-dataset Page 10. 10 F. Hamborg et al. 23. Nagel, S.: Common Crawl: News Crawl (2016), https://web. archive.org/web/20191118111519/https://commoncrawl org/2016/10/ news-dataset-available/ 24. Nakov, P., Ritter …","url":["https://www.gipp.com/wp-content/papercite-data/pdf/hamborg2021.pdf"]}
-{"year":"2021","title":"Towards the smart use of embedding and instance features for property matching","authors":["D Ayala, I Hernández, D Ruiz, E Rahm - 2021 IEEE 37th International Conference on …, 2021"],"snippet":"… To compute embeddings, we use the pre-trained GloVe approach [25]1, specifically for the uncased Common Crawl corpus that includes 300-dimensional vectors for 1.9 million words. Unknown words are mapped to a vector filled with zeroes …","url":["https://ieeexplore.ieee.org/abstract/document/9458651/"]}
-{"year":"2021","title":"Towards Zero-Shot Cross-Lingual Named Entity Disambiguation","authors":["A Barrena Madinabeitia, A Soroa Echave… - 2021","A Barrena, A Soroa, E Agirre - Expert Systems with Applications, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://addi.ehu.es/bitstream/handle/10810/54482/1-s2.0-S0957417421009490-main.pdf?sequence=1&isAllowed=y","https://www.sciencedirect.com/science/article/pii/S0957417421009490"]}
-{"year":"2021","title":"Traceability recovery between bug reports and test cases-a Mozilla Firefox case study","authors":["G Gadelha, F Ramalho, T Massoni - Automated Software Engineering, 2021"],"snippet":"Automatic recovery of traceability between software artifacts may promote early detection of issues and better calculate change impact. Information Retriev.","url":["https://link.springer.com/article/10.1007/s10515-021-00287-w"]}
-{"year":"2021","title":"Trafilatura: A Web Scraping Library and Command-Line Tool for Text Discovery and Extraction","authors":["A Barbaresi - 2021"],"snippet":"… Data collection approaches using the CommonCrawl1 have flourished as they allow for faster download and processing by skipping (or more precisely outsourcing) the crawling phase … 1https://commoncrawl.org Page 2. 123 …","url":["https://aclanthology.org/2021.acl-demo.15.pdf"]}
-{"year":"2021","title":"Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation","authors":["O Press, NA Smith, M Lewis - arXiv preprint arXiv:2108.12409, 2021"],"snippet":"Page 1. TRAIN SHORT, TEST LONG: ATTENTION WITH LINEAR BIASES ENABLES INPUT LENGTH EXTRAPOLATION Ofir Press1,2 Noah A. Smith1,3 Mike Lewis2 1Paul G. Allen School of Computer Science & Engineering …","url":["https://arxiv.org/pdf/2108.12409"]}
-{"year":"2021","title":"Training Domain Specific Multilingually Aligned Word Embeddings","authors":["X Wang, C Fan, M Frantzen - 2021"],"snippet":"… FastText The pre-trained Fasttext embeddings follow the training procedure proposed in [5]. They use a mixture of Wikipedia and CommonCrawl as training data and learn 300 dimensional embeddings with a CBOW model defined …","url":["https://xinpeng-wang.github.io/pdfs/nlp_final_report.pdf"]}
-{"year":"2021","title":"Training ELECTRA Augmented with Multi-word Selection","authors":["J Shen, J Liu, T Liu, C Yu, J Han - arXiv preprint arXiv:2106.00139, 2021"],"snippet":"Page 1. Training ELECTRA Augmented with Multi-word Selection Jiaming Shen∇⋆, Jialu Liu O , Tianqi Liu O , Cong Yu O , Jiawei Han∇ ∇University of Illinois Urbana-Champaign, IL, USA, 3 Google Research, NY, USA ∇{js2 …","url":["https://arxiv.org/pdf/2106.00139"]}
-{"year":"2021","title":"Transfer Learning for Automated Responses to the BDI Questionnaire","authors":["C Spartalis, G Drosatos, A Arampatzis - Working Notes of CLEF, 2021"],"snippet":"… batches, and over more data. More specifically, its pretraining corpus also includes CC-News (portion of the CommonCrawl News dataset [44]), OpenWebText [45], and Stories [46]). Furthermore, there are some modifications …","url":["http://ceur-ws.org/Vol-2936/paper-84.pdf"]}
-{"year":"2021","title":"Transfer Learning for Sequence Generation: from Single-source to Multi-source","authors":["X Huang, J Xu, M Sun, Y Liu - arXiv preprint arXiv:2105.14809, 2021"],"snippet":"Page 1. Transfer Learning for Sequence Generation: from Single-source to Multi-source Xuancheng Huang1, Jingfang Xu4, Maosong Sun1,3, and Yang Liu1,2,3∗ 1Dept. of Comp. Sci. & Tech., BNRist Center, Institute for AI, Tsinghua …","url":["https://arxiv.org/pdf/2105.14809"]}
-{"year":"2021","title":"Transfer Learning Model for Disrupting Misinformation During a COVID-19 Pandemic","authors":["R Raju, S Bhandari, SA Mohamud, EN Ceesay - 2021 IEEE 11th Annual Computing …, 2021"],"snippet":"… 19–27, IEEE Computer Society, 2015. [30] S. Nagel, “Cc-news.” https://commoncrawl.org/ 2016/10/news-datasetavailable/, 2016. [31] A. Gokaslan and V. Cohen, “Openwebtext corpus.” https://skylion007.github.io/OpenWebTextCorpus/, 2016 …","url":["https://ieeexplore.ieee.org/abstract/document/9376066/"]}
-{"year":"2021","title":"Transfer Learning Techniques for Sequence Labeling in Network File System Specifications","authors":["A Singh - 2021"],"snippet":"… English Wikipedia and BookCorpus (Zhu et al., 2015), and RoBERTa (Liu et al., 2019) is pre-trained on Common-Crawl News (Nagel, 2016), OpenWebText (Radford et al., 2019), and Stories (Trinh and Le, 2019) …","url":["https://search.proquest.com/openview/754b6463cd54e1b58537a7d6558d4825/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"Transformer-Based Automatic Punctuation Prediction and Word Casing Reconstruction of the ASR Output","authors":["J Švec, J Lehečka, L Šmídl, P Ircing - International Conference on Text, Speech, and …, 2021"],"snippet":"… For experiments with English data, we used the Google's T5-base English model (version from October 21th, 2019) 3 trained from Common Crawl data 4 . We replicated the same pre-processing procedure to obtain the …","url":["https://link.springer.com/chapter/10.1007/978-3-030-83527-9_7"]}
-{"year":"2021","title":"Transformer-based identification of stochastic information cascades in social networks using text and image similarity","authors":["P Kasnesis, R Heartfield, X Liang, L Toumanidis… - Applied Soft Computing, 2021"],"snippet":"… An advantage of RoBERTa against BERT for text-based information cascade identification is its pretrained architecture which benefits from a more diverse range of datasets (larger corpus). For example, its training corpus includes the CommonCrawl News dataset.","url":["https://www.sciencedirect.com/science/article/pii/S1568494621003367"]}
-{"year":"2021","title":"TRANSFORMERS AND THEIR APPLICATIONS IN NATURAL LANGUAGE PROCESSING","authors":["N Sarzhan"],"snippet":"Page 1. Page 2. E¨OTV¨OS LORÁND UNIVERSITY FACULTY OF SCIENCE TRANSFORMERS AND THEIR APPLICATIONS IN NATURAL LANGUAGE PROCESSING MASTER'S THESIS Nurzhan Sarzhan MSc mathematics …","url":["https://web.cs.elte.hu/blobs/diplomamunkak/msc_alkmat/2021/nurzhan_sarzhan.pdf"]}
-{"year":"2021","title":"Transforming Term Extraction: Transformer-Based Approaches to Multilingual Term Extraction Across Domains","authors":["C Lang, L Wachowiak, B Heinisch, D Gromann"],"snippet":"… XLM-R (Conneau et al., 2020) is a multilingual variant of BERT, which was pretrained in 100 languages using 2.5 terabytes of Common Crawl data. Moreover, it makes use of the improved training routine introduced by RoBERTa (Liu et al., 2019) …","url":["https://aclanthology.org/2021.findings-acl.316.pdf"]}
-{"year":"2021","title":"Translate and Classify: Improving Sequence Level Classification for English-Hindi Code-Mixed Data","authors":["D Gautam, K Gupta, M Shrivastava - Proceedings of the Fifth Workshop on …, 2021"],"snippet":"… auto-encoder. It has been pre-trained using the BART (Lewis et al., 2020) objective on large-scale monolingual corpora of 25 languages extracted from Common Crawl1 (Wenzek et al., 2020; Conneau et al., 2020). Both English …","url":["https://www.aclweb.org/anthology/2021.calcs-1.3.pdf"]}
-{"year":"2021","title":"TrollsWithOpinion: A Dataset for Predicting Domain-specific Opinion Manipulation in Troll Memes","authors":["S Suryawanshi, BR Chakravarthi, M Arcan, S Little… - arXiv preprint arXiv …, 2021"],"snippet":"… 5.2 Deep Learning baselines Bag of words (BOW) : This unimodal baseline used text representation in the form of 300-dimensional pre-trained GloVe Pennington et al. (2014) (common crawl) word embeddings, which were fed to a classification layer …","url":["https://arxiv.org/pdf/2109.03571"]}
-{"year":"2021","title":"TunBERT: Pretrained Contextualized Text Representation for Tunisian Dialect","authors":["A Messaoudi, A Cheikhrouhou, H Haddad, N Ferchichi… - arXiv preprint arXiv …, 2021"],"snippet":"… They also concluded that a model trained on a CommonCrawl-based corpus performed consistently better than the one trained on the French Wikipedia. They suggested that a 4 GB heterogeneous dataset in terms of genre and style is large enough as a …","url":["https://arxiv.org/pdf/2111.13138"]}
-{"year":"2021","title":"Turkic Interlingua: A Case Study of Machine Translation in Low-resource Languages","authors":["J Mirzakhalov - 2021"],"snippet":"… production. Table 4 shows results from the CCAligned dataset, which is a parallel dataset compiled from 68 Common Crawl snapshots … shown in Table 6. Data for OSCAR is also a compilation of Common Crawl snapshots and follows a similar filtering process …","url":["https://scholarcommons.usf.edu/cgi/viewcontent.cgi?article=10026&context=etd"]}
-{"year":"2021","title":"Twin Question Pair Classification","authors":["A Sharma, SS Jha, S Arora, S Garg, S Tayal - Smart and Sustainable Intelligent …, 2021"],"snippet":"… 4 Embedding Embedding maps words in a text document to number space (these number-space representations are called word vectors). We have to use Fast text embedding [6]. The Fast text model for English is pre-trained …","url":["http://books.google.de/books?hl=en&lr=lang_en&id=7fEhEAAAQBAJ&oi=fnd&pg=PA215&dq=commoncrawl&ots=oxs_QNhHWM&sig=OazT1mzKhUG_fOXx1LjGsEMtRKI"]}
-{"year":"2021","title":"Twitter Dataset and Evaluation of Transformers for Turkish Sentiment Analysis","authors":["A Köksal, A Özgür - 2021 29th Signal Processing and Communications …, 2021"],"snippet":"… Kelime Büyüklü˘gü 128,000 119,547 250,002 Kullanılan Diller Türkçe Türkçe + 103 dil Türkçe + 99 dil E˘gitim Derlemi Oscar + Wikipedia + Opus Wikipedia CommonCrawl vektör uzunlu˘gu, dikkat ve gizli katmanların sayısı bu üç mo- delde de aynıdır …","url":["https://ieeexplore.ieee.org/abstract/document/9477814/"]}
-{"year":"2021","title":"Two Parents, One Child: Dual Transfer for Low-Resource Neural Machine Translation","authors":["M Zhang, L Li, Q Liu"],"snippet":"Page 1. Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, pages 2726–2738 August 1–6, 2021. ©2021 Association for Computational Linguistics 2726 Two Parents, One Child: Dual Transfer for Low-Resource Neural Machine Translation …","url":["https://aclanthology.org/2021.findings-acl.241.pdf"]}
-{"year":"2021","title":"Two-stage Visual Cues Enhancement Network for Referring Image Segmentation","authors":["Y Jiao, Z Jie, W Luo, J Chen, YG Jiang, X Wei, L Ma - arXiv preprint arXiv:2110.04435, 2021"],"snippet":"… As for language processing, GloVe [27] word embeddings pretrained on Common Crawl 840B tokens are firstly used for constructing word embedding look-up table. Then a LSTM takes GloVe word embeddings as input for capturing context information …","url":["https://arxiv.org/pdf/2110.04435"]}
-{"year":"2021","title":"Type-and Token-based Word Embeddings in the Digital Humanities","authors":["A Ehrmanntraut, T Hagen, L Konle, F Jannidis - Proceedings http://ceur-ws. org ISSN, 2021"],"snippet":"Abstract In the general perception of the NLP community, the new dynamic, context-sensitive, token-based embeddings from language models like BERT have replaced the older static, type-based embeddings like word2vec or fastText, due to their better …","url":["http://ceur-ws.org/Vol-2989/long_paper35.pdf"]}
-{"year":"2021","title":"UGTO: Uncommon Words and Proper Nouns","authors":["X Zhong, E Cambria - Time Expression and Named Entity Recognition, 2021"],"snippet":"… they are (1) word2vec, which is trained on the Google News dataset [13], (2) GloVe, which is trained on the Wikipedia 2014 and Gigaword 5 corpora [20], and (3) FastText, which is trained on the Wikipedia 2017, UMBC corpus …","url":["https://link.springer.com/chapter/10.1007/978-3-030-78961-9_6"]}
-{"year":"2021","title":"Uncovering the Limits of Text-based Emotion Detection","authors":["N Alvarez-Gonzalez, A Kaltenbrunner, V Gómez - arXiv preprint arXiv:2109.01900, 2021"],"snippet":"Page 1. Uncovering the Limits of Text-based Emotion Detection Nurudin Alvarez-Gonzalez ∗, Andreas Kaltenbrunner, Vicenç Gómez nuralgon@gmail.com, andreas.kaltenbrunner@ upf.edu, vicen.gomez@upf.edu Universitat Pompeu Fabra. Barcelona, Spain. Abstract …","url":["https://arxiv.org/pdf/2109.01900"]}
-{"year":"2021","title":"Understanding and Countering Stereotypes: A Computational Approach to the Stereotype Content Model","authors":["KC Fraser, I Nejadgholi, S Kiritchenko"],"snippet":"… trained word em- beddings in the gensim library ( ˇRehurek and Sojka, 2010), with the results given in Table 2. The FastText embeddings generally outperform the other embeddings on this task, with the 2M word model trained …","url":["https://www.svkir.com/papers/Fraser-et-al-SCM-ACL2021.pdf"]}
-{"year":"2021","title":"Understanding the Effect of Out-of-distribution Examples and Interactive Explanations on Human-AI Decision Making","authors":["H Liu, V Lai, C Tan - arXiv preprint arXiv:2101.05303, 2021"],"snippet":"… Race. There are 7,214 defendants in this dataset. • BIOS [9]. This dataset contains hundreds of thousands of online biographies from the Common Crawl corpus. The task is to predict a person's profession given a biography …","url":["https://arxiv.org/pdf/2101.05303"]}
-{"year":"2021","title":"Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus","authors":["J Abadji, PJ Ortiz Suárez, L Romary, B Sagot - … of the Workshop on Challenges in the …, 2021"],"snippet":"… The most recent Common Crawl dump contains 64,000 shards. Each shard is composed of numerous records, and each record holds textual content along with metadata. While CommonCrawl shards hold document-level …","url":["https://ids-pub.bsz-bw.de/files/10468/Abadji_Suarez_Romary_Ungoliant_2021.pdf"]}
-{"year":"2021","title":"Unified Open-Domain Question Answering with Structured and Unstructured Knowledge","authors":["B Oguz, X Chen, V Karpukhin, S Peshterliev… - arXiv preprint arXiv …, 2020"],"snippet":"… KBQA is ultimately limited in its coverage of facts and the types of questions it can answer. On the other hand, large collections of text such as Wikipedia or CommonCrawl promise to be a richer source of knowledge for truly open do- main question answering systems …","url":["https://arxiv.org/pdf/2012.14610"]}
-{"year":"2021","title":"Universal Sentence Representation Learning with Conditional Masked Language Model","authors":["Z Yang, Y Yang, D Cer, J Law, E Darve - arXiv preprint arXiv:2012.14388, 2020"],"snippet":"… For training English sentence encoders with CMLM, we use three Common Crawl dumps … Similarly, we also train QuickThought, a competitive unsupervised sentence representations learning model, on the same …","url":["https://arxiv.org/pdf/2012.14388"]}
-{"year":"2021","title":"University of Copenhagen Participation in TREC Health Misinformation Track 2020","authors":["LC Lima, DB Wright, I Augenstein, M Maistro - arXiv preprint arXiv:2103.02462, 2021"],"snippet":"… The corpus of the Total Recall and Ad Hoc Tasks consits of news articles in the CommonCrawl News crawl, sampled from January, 1st 2020 … Since there are no credibility assessments for the Common Crawl News sample …","url":["https://arxiv.org/pdf/2103.02462"]}
-{"year":"2021","title":"University of Regensburg@ PAN: Profiling Hate Speech Spreaders on Twitter","authors":["KO Akomeah, U Kruschwitz, B Ludwig - CLEF, 2021"],"snippet":"… This preprocessor is a companion to the BERT models for preprocsssing plain text inputs into the input format expected by BERT. The model uses a vocabulary for multilingual models extracted from Wikipedia, CommonCrawl, and translation pairs from the Web …","url":["http://ceur-ws.org/Vol-2936/paper-184.pdf"]}
-{"year":"2021","title":"Unraveling Social Perceptions & Behaviors towards Migrants on Twitter","authors":["A Khatua, W Nejdl - arXiv preprint arXiv:2112.06642, 2021"],"snippet":"We draw insights from the social psychology literature to identify two facets of Twitter deliberations about migrants, ie, perceptions about migrants and behaviors towards mi-grants. Our theoretical anchoring helped us in identifying two prevailing …","url":["https://arxiv.org/pdf/2112.06642"]}
-{"year":"2021","title":"Unsupervised Clustering of Structured and Unstructured Text Collections","authors":["L Bungum - 2021"],"snippet":"Page 1. Lars B u n g u m Doctoral theses at NTNU, 202 1 :179 ISBN 978-82-326-5390-4 (printed ver.) ISBN 978-82-326-6966-0 (electronic ver.) ISSN 1503-8181 (printed ver.) ISSN 2703-8084 (electronic ver.) Do cto ral …","url":["https://ntnuopen.ntnu.no/ntnu-xmlui/bitstream/handle/11250/2759145/Lars%20Bungum_PhD.pdf?sequence=1"]}
-{"year":"2021","title":"Unsupervised Cross-Domain and Cross-Lingual Methods for Text Classification, Slot-Filling, and Question-Answering","authors":["J Krishnan - 2021"],"snippet":"Page 1. UNSUPERVISED CROSS-DOMAIN AND CROSS-LINGUAL METHODS FOR TEXT CLASSIFICATION, SLOT-FILLING, AND QUESTION-ANSWERING by Jitin Krishnan A Dissertation Submitted to the Graduate Faculty …","url":["https://search.proquest.com/openview/5ef2690ad3bc61870ee72a9048d3a4f9/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2021","title":"Unsupervised Neural Machine Translation with Generative Language Models Only","authors":["JM Han, I Babuschkin, H Edwards, A Neelakantan… - arXiv preprint arXiv …, 2021"],"snippet":"We show how to derive state-of-the-art unsupervised neural machine translation systems from generatively pre-trained language models. Our method consists of three steps: few-shot amplification, distillation, and backtranslation. We first use the …","url":["https://arxiv.org/pdf/2110.05448"]}
-{"year":"2021","title":"Uppsala NLP at SemEval-2021 Task 2: Multilingual Language Models for Fine-tuning and Feature Extraction in Word-in-Context Disambiguation","authors":["H You, X Zhu, S Stymne - arXiv preprint arXiv:2104.03767, 2021"],"snippet":"… 3 Multilingual Language Models 3.1 XLMR XLMR (XLM-RoBERTa) is a scaled cross-lingual sentence encoder (Conneau et al., 2020), which is trained on 2.5T of data obtained from Common Crawl that covers more than 100 languages …","url":["https://arxiv.org/pdf/2104.03767"]}
-{"year":"2021","title":"UPV at TREC Health Misinformation Track 2021 Ranking with SBERT and Quality Estimators","authors":["IB Schlicht, AFM de Paula, P Rosso - arXiv preprint arXiv:2112.06080, 2021"],"snippet":"Health misinformation on search engines is a significant problem that could negatively affect individuals or public health. To mitigate the problem, TREC organizes a health misinformation track. This paper presents our submissions to this …","url":["https://arxiv.org/pdf/2112.06080"]}
-{"year":"2021","title":"UQuAD1. 0: Development of an Urdu Question Answering Training Data for Machine Reading Comprehension","authors":["S Kazi, S Khoja - arXiv preprint arXiv:2111.01543, 2021"],"snippet":"… The Third model used is XLM-Roberta, a multi-lingual pre-trained transformer model from common Crawl trained on 100 languages, including Urdu. XLM-Roberta outperformed previous multi-lingual models such as mBERT and XLM on a variety of …","url":["https://arxiv.org/pdf/2111.01543"]}
-{"year":"2021","title":"User Identification in Online Social Networks using Graph Transformer Networks","authors":["KNP Kumar, ML Gavrilova - 2021 18th International Conference on Privacy …, 2021"],"snippet":"… We used the model with 2 million word vectors trained with subword information on Common Crawl (600B tokens). (v) Skip-thought Vectors (StV) [30]: A Gated Recurrent Unit (GRU) encoder trained to predict adjacent sentences in a books …","url":["https://ieeexplore.ieee.org/abstract/document/9647749/"]}
-{"year":"2021","title":"Using Embedding-Based Similarities to Improve Lexical Resources","authors":["NV Loukachevitch, MM Tikhomirov, EA Parkhomenko - Lobachevskii Journal of …, 2021"],"snippet":"In this paper we discuss the usefulness of applying semi-automatic checking procedures to existing thesauri for natural language processing—large man.","url":["https://link.springer.com/article/10.1134/S1995080221070167"]}
-{"year":"2021","title":"Using mixed methods to study the historical use of web beacons in web tracking","authors":["J Nielsen - International Journal of Digital Humanities, 2021"],"snippet":"… pixel. The approach is inspired by the study of web beacons by Ruohonen and Leppänen (2018) and Schelter and Kunegis' study of third-party embeddings in the Common Crawl 2012 corpus (Schelter & Kunegis, 2016, 2018) …","url":["https://link.springer.com/article/10.1007/s42803-021-00033-4"]}
-{"year":"2021","title":"USING SEMANTIC RELATIONSHIPS TO ENHANCE NEURAL WORD EMBEDDINGS","authors":["Y Yin, X Sun, H Lv, P Wang, H Ma, D Yang"],"snippet":"Neural language models have significantly improved current natural language understanding tasks. However, distributional semantics, derived from neural language models is less competitive in computing semantic relatedness or similarity …","url":["https://www.researchgate.net/profile/Dongqiangdongqiang-Yang/publication/356592344_USING_SEMANTIC_RELATIONSHIPS_TO_ENHANCE_NEURAL_WORD_EMBEDDINGS/links/61a2f3196a0f6e76c2b43389/USING-SEMANTIC-RELATIONSHIPS-TO-ENHANCE-NEURAL-WORD-EMBEDDINGS.pdf"]}
-{"year":"2021","title":"Using Visual Features to Generate Language Context","authors":["I Zachmann - 2021"],"snippet":"Page 1. Using Visual Features to Generate Language Context Undergraduate Honors Research Thesis Presented in Partial Fulfillment of the Requirements for Undergraduate Honors Research Thesis in the College of Engineering at The Ohio State University By …","url":["https://kb.osu.edu/bitstream/handle/1811/92666/Thesis.pdf?sequence=1"]}
-{"year":"2021","title":"Using Word Embeddings to Determine Concepts of Values In Insurance Claim Spreadsheets","authors":["V Justnes - 2021"],"snippet":"Page 1. Using Word Embeddings to Determine Concepts of Values In Insurance Claim Spreadsheets Vemund Justnes Thesis submitted for the degree of Master in Informatics: Programming and System Architecture 60 credits Institute for Informatics …","url":["https://www.duo.uio.no/bitstream/handle/10852/87784/1/using_word_embeddings_for_concept_determiniation.pdf"]}
-{"year":"2021","title":"Using word embeddings to probe sentiment associations of politically loaded terms in news and opinion articles from news media outlets","authors":["D Rozado, M al-Gharbi - Journal of Computational Social Science, 2021"],"snippet":"… word embeddings also absorb many of the biases that are prevalent within a cultural system, as a result of embedding models being trained on culturally relevant language artifacts that are presumed to contain cultural biases, such …","url":["https://link.springer.com/article/10.1007/s42001-021-00130-y"]}
-{"year":"2021","title":"Utility-Preserving Anonymization of Textual Documents","authors":["FAM Hassan - 2021"],"snippet":"Page 1. UTILITY-PRESERVING ANONYMIZATION OF TEXTUAL DOCUMENTS Fadi Abdulfattah Mohammed Hassan ADVERTIMENT. L'accés als continguts d'aquesta tesi doctoral i la seva utilització ha de respectar els drets de la persona autora …","url":["https://84.88.27.106/bitstream/handle/10803/672012/TESI%20Fadi%20Abdulfattah%20Mohammed%20Hassan.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"Utility-Preserving Privacy Protection of Textual Documents via Word Embeddings","authors":["F Hassan, D Sanchez, J Domingo-Ferrer - IEEE Transactions on Knowledge and Data …, 2021"],"snippet":"Page 1. 1041-4347 (c) 2021 IEEE. Personal use is permitted, but republication/ redistribution requires IEEE permission. See http://www.ieee.org/ publications_standards/publications/rights/index.html for more information. This …","url":["https://ieeexplore.ieee.org/abstract/document/9419784/"]}
-{"year":"2021","title":"UXLA: A Robust Unsupervised Data Augmentation Framework for Zero-Resource Cross-Lingual NLP","authors":["MS Bari, T Mohiuddin, S Joty"],"snippet":"… Manning, 2019). We use XLM-R masked LM (Conneau et al., 2020) as our vicinity model θmlm, which is trained on massive multilingual corpora (2.5 TB of Common-Crawl data in 100 languages). The Page 4. 1981 Algorithm 1 …","url":["https://aclanthology.org/2021.acl-long.154.pdf"]}
-{"year":"2021","title":"UzBERT: pretraining a BERT model for Uzbek","authors":["B Mansurov, A Mansurov - arXiv preprint arXiv:2108.09814, 2021"],"snippet":"… Page 3. 3 Uzbek Wikipedia and the Common Crawl corpus. According … 2006], where full words are replaced by their abbreviations to save space in print. The filtered Common Crawl corpus5 used by XLM-R [Conneau et al. 2019 …","url":["https://arxiv.org/pdf/2108.09814"]}
-{"year":"2021","title":"Validating Word Embedding as a Tool for the Psychological Sciences","authors":["V Swift - 2021"],"snippet":"Page 1. Validating Word Embedding as a Tool for the Psychological Sciences by Victor Swift A thesis submitted in conformity with the requirements for the degree of Doctorate of Philosophy Department of Psychology University of …","url":["https://tspace.library.utoronto.ca/bitstream/1807/104927/3/Swift_Victor_202103_PhD_thesis.pdf"]}
-{"year":"2021","title":"Variational Autoencoder with Interactive Attention for Affective Text Generation","authors":["R Chen, J Wang, X Zhang - CCF International Conference on Natural Language …, 2021"],"snippet":"… The word embeddings used in this experiment was pre-trained on Common Crawl 840B 1 by GloVe [10]. For baselines, the polarity label \\(\\mathbf {c}\\) was treated as a scalar (ie, 0 or 1) and directly concatenated into the latent variables. For …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88483-3_9"]}
-{"year":"2021","title":"VECO: Variable and Flexible Cross-lingual Pre-training for Language Understanding and Generation","authors":["F Luo, W Wang, J Liu, Y Liu, B Bi, S Huang, F Huang…"],"snippet":"… mBART (Liu et al., 2020b) Encoder-decoder 680M 12 12 25 250k CommonCrawl VECO Flexible 662M 24* 50 250k CommonCrawl + Translation … For monolingual training datasets, we reconstruct CommonCrawl Corpus used in XLM-R (Conneau et al., 2019) …","url":["https://aclanthology.org/2021.acl-long.308.pdf"]}
-{"year":"2021","title":"Vera: Prediction Techniques for Reducing Harmful Misinformation in Consumer Health Search","authors":["R Pradeep, X Ma, R Nogueira, J Lin - Proceedings of the 44th Annual International …, 2021"],"snippet":"… The document collection comprises news articles from the CommonCrawl news crawl spanning the first four months of 2020 (January 1st, 2020 to April 30th, 2020), covering the onset of the COVID-19 pandemic. This corpus …","url":["https://cs.uwaterloo.ca/~jimmylin/publications/Pradeep_etal_SIGIR2021.pdf"]}
-{"year":"2021","title":"VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations","authors":["A Rathore, S Dev, JM Phillips, V Srikumar, Y Zheng… - arXiv preprint arXiv …, 2021"],"snippet":"… It also provides a larger GLoVe embedding (300-dimensional with the 100K most frequent words) from the Common Crawl corpus (https://commoncrawl.org/). 5 USE CASES We demonstrate the efficacy of VERB on several examples …","url":["https://arxiv.org/pdf/2104.02797"]}
-{"year":"2021","title":"VieSum: How Robust Are Transformer-based Models on Vietnamese Summarization?","authors":["H Nguyen, L Phan, J Anibal, A Peltekian, H Tran - arXiv preprint arXiv:2110.04257, 2021"],"snippet":"… Common Crawl is a publicly web archive that provides text scraped from websites. These datasets (C4, CC25, and Common Crawl) may include Vietnamese Wikipedia languages website that help the model excel in constrained domain corpus (Wikipedia) …","url":["https://arxiv.org/pdf/2110.04257"]}
-{"year":"2021","title":"Visual and Affective Multimodal Models of Word Meaning in Language and Mind","authors":["S De Deyne, DJ Navarro, G Collell, A Perfors - Cognitive Science, 2021"],"snippet":"Abstract One of the main limitations of natural language‐based approaches to meaning is that they do not incorporate multimodal representations the way humans do. In this study, we evaluate how wel...","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/cogs.12922"]}
-{"year":"2021","title":"Visual Grounding Strategies for Text-Only Natural Language Processing","authors":["D Sileo - arXiv preprint arXiv:2103.13942, 2021"],"snippet":"… A linear projection maps the region features to the input space of the cross-modal encoder. We also provide K rank 6We use the CommonCrawl version https:// fasttext.cc/docs/en/english-vectors.html. and discard stop-words with NLTK …","url":["https://arxiv.org/pdf/2103.13942"]}
-{"year":"2021","title":"Visualizing large-scale high-dimensional data via hierarchical embedding of KNN graphs","authors":["H Zhu, M Zhu, Y Feng, D Cai, Y Hu, S Wu, X Wu… - Visual Informatics, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S2468502X21000292"]}
-{"year":"2021","title":"VITALITY: Promoting Serendipitous Discovery of Academic Literature with Transformers & Visual Analytics","authors":["A Narechania, A Karduni, R Wesslen, E Wall - arXiv preprint arXiv:2108.03366, 2021"],"snippet":"… Unlike many pre-trained language models that use a general corpus like Wikipedia or the Common Crawl [14, 43, 49], SPECTER was pre-trained on academic literature (sciBERT [?]) and fine-tuned with citations which …","url":["https://arxiv.org/pdf/2108.03366"]}
-{"year":"2021","title":"VOH. CoLAB at TREC 2020 Health Misinformation Track⋆","authors":["SN Gonçalves, F Martins"],"snippet":"… 2.1 Collection The collection contains 65 million news articles from CommonCrawl News4 corresponding to the period from January to April of 2020 … Recently, vinegar has been promoted as a disinfectant (...) 4 …","url":["https://trec.nist.gov/pubs/trec29/papers/vohcolab.HM.pdf"]}
-{"year":"2021","title":"Voted In, Standing Out: Public Response to Immigrants' Political Accession","authors":["G Grossman, S Zonszein - 2021"],"snippet":"… newspapers, covering the general elections from 2010–2019.8 This data is from Common Crawl, which is an open repository of web crawl data. We assume that an article refers to a candidate's ethnic group when three conditions are met: 1) the publication date is …","url":["https://files.osf.io/v1/resources/xd4wk/providers/osfstorage/614782978ae0920335d8c84c?action=download&direct&version=2"]}
-{"year":"2021","title":"We Need to Talk About Data: The Importance of Data Readiness in Natural Language Processing","authors":["F Olsson, M Sahlgren - arXiv preprint arXiv:2110.05464, 2021"],"snippet":"In this paper, we identify the state of data as being an important reason for failure in applied Natural Language Processing (NLP) projects. We argue that there is a gap between academic research in NLP and its application to problems outside …","url":["https://arxiv.org/pdf/2110.05464"]}
-{"year":"2021","title":"Web Archive Analytics","authors":["M Völske, J Bevendorff, J Kiesel, B Stein, M Fröbe… - INFORMATIK 2020, 2021"],"snippet":"… in Figure 5, beginning with the bottom-most data acquisition layerȷ Primary sources for data ingestion include web crawls and web archives, such as the aforementioned Internet Archive, the Common Crawl,13 the older … 13 …","url":["https://dl.gi.de/bitstream/handle/20.500.12116/34759/A8-1.pdf?sequence=1&isAllowed=y"]}
-{"year":"2021","title":"Web Content Authentication: A Machine Learning Approach to Identify Fake and Authentic Web Pages on Internet","authors":["J Ashok, P Badoni - … Technology for Competitive Strategies (ICTCS 2020) …"],"snippet":"… SpringerLink (Springer, 21 June 2017). www. link. springer. com/chapter/10.1007/978- 3-319-69784-0_15 42. Link to GitHub where code is hosted. https://github. com/Jkrish1011/Web-Content-Authentic ator 43. https://commoncrawl. org/","url":["http://books.google.de/books?hl=en&lr=lang_en&id=Dwo3EAAAQBAJ&oi=fnd&pg=PA85&dq=commoncrawl&ots=RCTLIhR7zF&sig=_9zgxY48BSktz0Jk-c6Y7XTbVf0"]}
-{"year":"2021","title":"Web Table Classification based on Visual Features","authors":["B Bühler, H Paulheim - arXiv preprint arXiv:2103.05110, 2021"],"snippet":"… Lehmberg et al. [17] conduct web table classification in order to create a large open corpus of relational HTML tables, ie, the WebDataCommons HTML Ta- bles Dataset3 based on the 2012 version of the Common Crawl web corpus …","url":["https://arxiv.org/pdf/2103.05110"]}
-{"year":"2021","title":"WeChat Neural Machine Translation Systems for WMT21","authors":["P Li, J Xu, J Zhou","X Zeng, Y Liu, E Li, Q Ran, F Meng, P Li, J Xu, J Zhou - arXiv preprint arXiv …, 2021"],"snippet":"… 4.2 Dataset For each language pair, the bilingual training data is the combination of all parallel data released by WMT21. For monolingual data, we filter out clean data from News Crawl, Common Crawl and Ex- tended Common Crawl …","url":["https://ar5iv.labs.arxiv.org/html/2108.02401","https://arxiv.org/pdf/2108.02401"]}
-{"year":"2021","title":"What Can Unsupervised Machine Translation Contribute to High-Resource Language Pairs?","authors":["K Marchisio, M Freitag, D Grangier - arXiv preprint arXiv:2106.15818, 2021"],"snippet":"… As bilingual training data, we use News Commentary v13, Europarl v7, Common Crawl and EU Press Release. We deduplicate and filter out pairs with > 250 to- kens in either language or length ratio over 1.5. This results in 5.2 million parallel sentence pairs …","url":["https://arxiv.org/pdf/2106.15818"]}
-{"year":"2021","title":"What Does Your Bio Say? Inferring Twitter Users' Depression Status From Multimodal Profile Information Using Deep Learning","authors":["S Ghosh, A Ekbal, P Bhattacharyya - IEEE Transactions on Computational Social …, 2021"],"snippet":"… Word embedding has been trained on the Common Crawl corpus (840 billion tokens). Padding arrays of zeros are done to make input sequences the same length. In our training set, we create an embedding matrix (E) that contains the embedding …","url":["https://ieeexplore.ieee.org/abstract/document/9567734/"]}
-{"year":"2021","title":"What is this cluster about? Explaining textual clusters by extracting relevant keywords","authors":["A Penta, A Pal - Knowledge-Based Systems, 2021"],"snippet":"JavaScript is disabled on your browser. Please enable JavaScript to use all the features on this page. Skip to main content Skip to article …","url":["https://www.sciencedirect.com/science/article/pii/S0950705121006043"]}
-{"year":"2021","title":"What Makes Sentences Semantically Related: A Textual Relatedness Dataset and Empirical Study","authors":["M Abdalla, K Vishnubhotla, SM Mohammad - arXiv preprint arXiv:2110.04845, 2021"],"snippet":"The degree of semantic relatedness (or, closeness in meaning) of two units of language has long been considered fundamental to understanding meaning. Automatically determining relatedness has many applications such as question …","url":["https://arxiv.org/pdf/2110.04845"]}
-{"year":"2021","title":"What Transformers Might Know About the Physical World: T5 and the Origins of Knowledge","authors":["H Shi, P Wolff - Proceedings of the Annual Meeting of the Cognitive …, 2021"],"snippet":"… stack of decoders. All versions of T5 were trained on a cleaned version of the common crawl called the Colossal Cleaned Common Crawl (C4). The training corpus is over two times larger than Wikipedia. The largest version …","url":["https://escholarship.org/content/qt0kr3t179/qt0kr3t179.pdf"]}
-{"year":"2021","title":"What Vision-Language ModelsSee'when they See Scenes","authors":["M Cafagna, K van Deemter, A Gatt - arXiv preprint arXiv:2109.07301, 2021"],"snippet":"Page 1. What Vision-Language Models 'See' when they See Scenes Michele Cafagna1 Kees van Deemter2 Albert Gatt1,2 1University of Malta, Institute of Linguistics and Language Technology 2Universiteit Utrecht, Information …","url":["https://arxiv.org/pdf/2109.07301"]}
-{"year":"2021","title":"What's in the Box? An Analysis of Undesirable Content in the Common Crawl Corpus","authors":["A Sasha Luccioni, JD Viviano - arXiv e-prints, 2021","AS Luccioni, JD Viviano - arXiv preprint arXiv:2105.02732, 2021"],"snippet":"Whereas much of the success of the current generation of neural language models has been driven by increasingly large training corpora, relatively little research has been dedicated to analyzing these massive sources of textual data. In this …","url":["https://arxiv.org/pdf/2105.02732","https://ui.adsabs.harvard.edu/abs/2021arXiv210502732S/abstract"]}
-{"year":"2021","title":"When FastText Pays Attention","authors":["V Novotný, M Štefánik, EF Ayetiran, P Sojka - 2021"],"snippet":"… (Hyper)-Parameter Optimization 3. Experiments & 4. Results I 3.3. (Hyper-)Parameter Optimization Dataset Number of tokens 2017 English Wikipedia 2,423,655,228 English Common Crawl 823,575,128,431 Table: Our datasets and their sizes in tokens …","url":["https://nlp.fi.muni.cz/trac/research/chrome/site/seminar2020/VNovotny-FastText_Attention_slides.pdf"]}
-{"year":"2021","title":"When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting","authors":["V Novotný, M Štefánik, EF Ayetiran, P Sojka - arXiv preprint arXiv:2104.09691, 2021"],"snippet":"… For qualitative evaluation and performance estimation, we use the deduplicated English Common Crawl4 as the training corpus. See the statistics in Table 1. Dataset Number of tokens 2017 English Wikipedia 2,423,655,228 English Common Crawl 823,575,128,431 …","url":["https://arxiv.org/pdf/2104.09691"]}
-{"year":"2021","title":"When few-shot learning meets large-scale knowledge-enhanced pre-training: Alibaba at FewCLUE","authors":["Z Xu, C Wang, P Li, Y Li, M Wang, B Hou, M Qiu… - … International Conference on …, 2021"],"snippet":"… In the pre-training steps, we use CLUECorpus2020 [28], which contains 100 GB Chinese raw texts retrieved from Common Crawl. We also employ 100 million high-quality Chinese knowledge SPOs from our in-house KG as the structured knowledge source …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88483-3_34"]}
-{"year":"2021","title":"When in Doubt, Summon the Titans: Efficient Inference with Large Models","authors":["AS Rawat, M Zaheer, AK Menon, A Ahmed, S Kumar - arXiv preprint arXiv …, 2021"],"snippet":"Scaling neural networks to \"large\" sizes, with billions of parameters, has been shown to yield impressive results on many challenging problems. However, the inference cost incurred by such large models often prevents their application in most …","url":["https://arxiv.org/pdf/2110.10305"]}
-{"year":"2021","title":"When is BERT Multilingual? Isolating Crucial Ingredients for Cross-lingual Transfer","authors":["A Deshpande, P Talukdar, K Narasimhan - arXiv preprint arXiv:2110.14782, 2021"],"snippet":"… (same) which uses different splits of Wikipedia data (hence, same domain), and (2) non-parallel (diff) which uses Wikipedia data for the original and common crawl data (web text) for the derived language (hence, different domain). We use the …","url":["https://arxiv.org/pdf/2110.14782"]}
-{"year":"2021","title":"Which Apple Keeps Which Doctor Away Colorful Word Representations with Visual Oracles","authors":["Z Zhang, H Yu, H Zhao, M Utiyama - IEEE/ACM Transactions on Audio, Speech, and …, 2021"],"snippet":"Recent pre-trained language models (PrLMs) offer a new performant method of contextualized word representations by leveraging the sequence-level context for modeling. Although the PrLMs generally provide more effective contextualized word …","url":["https://ieeexplore.ieee.org/abstract/document/9627795/"]}
-{"year":"2021","title":"Which is Better for Deep Learning: Python or MATLAB? Answering Comparative Questions in Natural Language","authors":["V Chekalina, A Bondarenko, C Biemann, M Beloucif…"],"snippet":"… with respect to an aspect specified by the user. First, using the Elasticsearch BM25, CAM retrieves sentences containing the two compared objects and the comparison aspect from the Common Crawl-based corpus featuring …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2021-chekalinaetal-eacldemo-coqas.pdf"]}
-{"year":"2021","title":"Which model is helpful in solving privacy, memorization, and bias problems?","authors":["S Yoon, H Lee"],"snippet":"Page 1. Which model is helpful in solving privacy, memorization, and bias problems? Soyoung Yoon * 1 Hyunji Lee * 1 Abstract Recently, language models of huge size are achieving stunning performance on natural language understanding tasks …","url":["https://soyoung97.github.io/profile/assets/papers/CS774.pdf"]}
-{"year":"2021","title":"Who Blames or Endorses Whom? Entity-to-Entity Directed Sentiment Extraction in News Text","authors":["K Park, Z Pan, J Joo - arXiv preprint arXiv:2106.01033, 2021"],"snippet":"… For each of the target media outlets, we collected news articles shared throughout 2020 until September from the Common Crawl corpus, which has been collecting web data since 20088. The total number of retrieved …","url":["https://arxiv.org/pdf/2106.01033"]}
-{"year":"2021","title":"Who is Accountable for Data Bias?","authors":["C Parkey - CHANCE, 2021"],"snippet":"… The OpenAI researchers use the data from Common Crawl, which provides a corpus for collaborative research, analysis, and education. It is an open data set containing petabytes of data collected since 2008 from raw web …","url":["https://www.tandfonline.com/doi/abs/10.1080/09332480.2021.1915032"]}
-{"year":"2021","title":"Why Do Masked Neural Language Models Still Need Semantic Knowledge in Question Answering?","authors":["C Kang - 2021"],"snippet":"… Lastly, RoBERTa is pre-trained with much larger data. Especially, the data is about 160GB, which is composed of CommonCrawl News dataset [40], Open WebText corpus [41], and STORIES corpus [42] in addition to the pre-training data of BERT …","url":["http://sailab.kaist.ac.kr/wp-content/uploads/2021/03/MS_Thesis_cheongwoong.pdf"]}
-{"year":"2021","title":"Wide and Deep Learning in Crowdfunding Success Prediction","authors":["D George"],"snippet":"The thesis studies to which extent deep learning models can predict whether crowdfunding campaigns will be successfully funded by drawing upon a dataset of 246,891 projects and 40 structured and text features from the crowdfunding platform …","url":["https://research.cbs.dk/files/68329943/1186110_Master_Thesis_133104_Wide_and_Deep_Learning_in_Crowdfunding_Success_Prediction.pdf"]}
-{"year":"2021","title":"with Graph Neural Networks","authors":["M House, M Rules"],"snippet":"… example “pen” and “pencil”, or “salt” and “pepper”. We load word embeddings from a FastText 155 model [18], pre-trained on the Common Crawl dataset of over 600 billion tokens. Names of objects 156 are converted to word …","url":["https://openreview.net/pdf?id=Ei3MOY2rDHB"]}
-{"year":"2021","title":"WITS: Wikipedia for Italian Text Summarization","authors":["S Casola, A Lavelli - 2021"],"snippet":"Abstractive text summarization has recently improved its performance due to the use of sequence to sequence models. However, while these models are extremely data-hungry, datasets in languages other than English are few. In this work, we introduce WITS (Wikipedia …","url":["http://ceur-ws.org/Vol-3033/paper65.pdf"]}
-{"year":"2021","title":"Word embeddings for the classification of main conditions with samples of patient text describing symptoms","authors":["A Lamproudis - 2020"],"snippet":"Page 1. IN DEGREE PROJECT COMPUTER SCIENCE AND ENGINEERING, SECOND CYCLE, 30 CREDITS , STOCKHOLM SWEDEN 2020 Word embeddings for the classification of main conditions with samples of patient text describing symptoms …","url":["https://www.diva-portal.org/smash/get/diva2:1523304/FULLTEXT01.pdf"]}
-{"year":"2021","title":"Word embeddings reveal social group attitudes and stereotypes in large language corpora","authors":["TES Charlesworth, MR Banaji"],"snippet":"… Surprisingly, less than half of the 45 languages studied by DeFranza and colleagues revealed a male-good/female-bad2 association across data from Wikipedia and the Common Crawl. This … For example, in the Common Crawl, 67% of languages with …","url":["http://www.people.fas.harvard.edu/~banaji/research/publications/articles/2021_Charlesworth_TAL.pdf"]}
-{"year":"2021","title":"Word Vector Representations using Shallow Neural Networks","authors":["O Adewumi - 2021"],"snippet":"… We obtain better performance in both languages on the downstream task with far smaller training data, compared to recently released, common crawl versions; and character n-grams appear useful for Swedish, a morphologically rich language. Keywords …","url":["https://www.diva-portal.org/smash/record.jsf?pid=diva2:1543295"]}
-{"year":"2021","title":"Word-level Korean-English Quality Estimation","authors":["S Eo, C Park, J Seo, H Moon, H Lim - Annual Conference on Human and Language …, 2021"],"snippet":"Abstract 기계번역 품질 예측 (Quality Estimation, QE) 은 정답 문장에 대한 참조없이 소스 문장과 기계번역 결과를 통해 기계번역 결과에 대한 품질을 수준별 주석으로 나타내주는 태스크이며, 다양한 활용도가 있다는 점에서 꾸준히 연구가 수행되고 있다 …","url":["https://www.koreascience.or.kr/article/CFKO202130060780846.pdf"]}
-{"year":"2021","title":"Words as a window: Using word embeddings to explore the learned representations of Convolutional Neural Networks","authors":["D Dharmaretnam, C Foster, A Fyshe - Neural Networks, 2021"],"snippet":"… here. Elmo is trained on a random sample of Wikipedia and the common crawl, and we use an average of the three 512-dimensional output layers … 2016). The Lexvec model has 300 dimensions and is trained on the common crawl …","url":["https://www.sciencedirect.com/science/article/pii/S0893608020304263"]}
-{"year":"2021","title":"WTR: A Test Collection for Web Table Retrieval","authors":["Z Chen, S Zhang, BD Davison - arXiv e-prints, 2021"],"snippet":"… PA, USA ABSTRACT We describe the development, characteristics and availability of a test collection for the task of Web table retrieval, which uses a largescale Web Table Corpora extracted from the Common Crawl. Since …","url":["https://arxiv.org/pdf/2105.02354"]}
-{"year":"2021","title":"XLM-E: Cross-lingual Language Model Pre-training via ELECTRA","authors":["Z Chi, S Huang, L Dong, S Ma, S Singhal, P Bajaj… - arXiv preprint arXiv …, 2021"],"snippet":"… different languages. 4 Experiments 4.1 Setup Data We use the CC-100 (Conneau et al., 2020) dataset for the replaced token detection task. CC- 100 contains texts in 100 languages collected from the CommonCrawl dump. We use …","url":["https://arxiv.org/pdf/2106.16138"]}
-{"year":"2021","title":"XLM-K: Improving Cross-Lingual Language Model Pre-Training with Multilingual Knowledge","authors":["X Jiang, Y Liang, W Chen, N Duan - arXiv preprint arXiv:2109.12573, 2021"],"snippet":"… 4.1 Implementation Details Data and Model Structure For the multilingual masked language modeling task, we use Common Crawl dataset (Wenzek et al. 2020) … 2020) was trained on Common Crawl dataset (Wenzek et al. 2020), which covers our training data Wikipedia …","url":["https://arxiv.org/pdf/2109.12573"]}
-{"year":"2021","title":"XLM-T: A Multilingual Language Model Toolkit for Twitter","authors":["F Barbieri, LE Anke, J Camacho-Collados - arXiv preprint arXiv:2104.12250, 2021"],"snippet":"… 2.1). For the monolingual experiments we also include a FastText (FT) baseline (Joulin et al., 2017), which relies on monolingual FT embeddings trained on Common Crawl and Wikipedia (Grave et al., 2018) as initialization for each language lookup table …","url":["https://arxiv.org/pdf/2104.12250"]}
-{"year":"2021","title":"XLM-T: Scaling up Multilingual Machine Translation with Pretrained Cross-lingual Transformer Encoders","authors":["S Ma, J Yang, H Huang, Z Chi, L Dong, D Zhang… - arXiv preprint arXiv …, 2020"],"snippet":"… cross-lingual representations. In this work, we adopt XLM-R BASE (Conneau et al., 2020) as the pretrained encoder. It was trained in 100 languages, using more than two terabytes of filtered CommonCrawl data. XLM-R is …","url":["https://arxiv.org/pdf/2012.15547"]}
-{"year":"2021","title":"XLS-R: Self-supervised Cross-lingual Speech Representation Learning at Scale","authors":["A Babu, C Wang, A Tjandra, K Lakhotia, Q Xu, N Goyal… - arXiv preprint arXiv …, 2021"],"snippet":"This paper presents XLS-R, a large-scale model for cross-lingual speech representation learning based on wav2vec 2.0. We train models with up to 2B parameters on nearly half a million hours of publicly available speech audio in 128 …","url":["https://arxiv.org/pdf/2111.09296"]}
-{"year":"2021","title":"XRR: Explainable Risk Ranking for Financial Reports","authors":["TW Lin, RY Sun, HL Chang, CJ Wang, MF Tsai"],"snippet":"… permutation test with p < 0.05. Table 1: Performance comparison 3. GloVe [20] representations are 300-dimensional word vectors6 trained on 840 billion tokens of Common Crawl data. In the following experiments, we denote …","url":["https://2021.ecmlpkdd.org/wp-content/uploads/2021/07/sub_506.pdf"]}
-{"year":"2021","title":"XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation","authors":["S Ruder, N Constant, J Botha, A Siddhant, O Firat, J Fu… - arXiv preprint arXiv …, 2021"],"snippet":"… Rebalanced mBERT (RemBERT; Chung et al., 2021) is a more efficient, scaled-up reparameterization of mBERT. These models have been pre-trained on unlabeled data in around 100 languages from Wikipedia …","url":["https://arxiv.org/pdf/2104.07412"]}
-{"year":"2021","title":"XtremeDistilTransformers: Task Transfer for Task-agnostic Distillation","authors":["S Mukherjee, AH Awadallah, J Gao - arXiv preprint arXiv:2106.04563, 2021"],"snippet":"… To address these issues, we ex- plore techniques to automatically generate largescale task-specific transfer sets leveraging a very large bank of web sentences from Common Crawl in Section 4.1. 3 Distillation Framework Overview …","url":["https://arxiv.org/pdf/2106.04563"]}
-{"year":"2021","title":"You too Brutus! Trapping Hateful Users in Social Media: Challenges, Solutions & Insights","authors":["M Das, P Saha, R Dutt, P Goyal, A Mukherjee… - arXiv preprint arXiv …, 2021"],"snippet":"… We experiment with the following text-classifiers. fastText: We leverage the pre-trained fastText embedding by Grave et al. [14] which has been trained on Common Crawl and Wikipedia. Each user's document has been represented as a 100 dimensional vector …","url":["https://arxiv.org/pdf/2108.00524"]}
-{"year":"2021","title":"Yuan 1.0: Large-Scale Pre-trained Language Model in Zero-Shot and Few-Shot Learning","authors":["S Wu, X Zhao, T Yu, R Zhang, C Shen, H Liu, F Li… - arXiv preprint arXiv …, 2021"],"snippet":"… c) After this step, the data size of Common Crawl is decreased from 866,304GB to 12,200GB. • Traditional to Simplified Chinese: Converts traditional Chinese characters to simplified Chinese characters. • Sensitive Words Filtering: Removes …","url":["https://arxiv.org/pdf/2110.04725"]}
-{"year":"2021","title":"Zero-Resource Multi-Dialectal Arabic Natural Language Understanding","authors":["M Khalifa, H Hassan, A Fahmy"],"snippet":"… XLM-R is a cross-lingual model, and we choose it since it is reported to perform better than mBERT, the multilingual model from Google [5]. XLM-R also uses Common Crawl for training, which is more likely to have …","url":["https://www.researchgate.net/profile/Muhammad-Khalifa/publication/350530331_Zero-Resource_Multi-Dialectal_Arabic_Natural_Language_Understanding/links/6064d0ba458515614d272082/Zero-Resource-Multi-Dialectal-Arabic-Natural-Language-Understanding.pdf"]}
-{"year":"2021","title":"Zeroshot Crosslingual Transfer of a Gloss Language Model for Semantic Change Detection","authors":["M Rachinskiy, N Arefyev"],"snippet":"… finetuned. data with MLM (Masked Language Modeling) objective. But in contrast to BERT and RoBERTa, it is pretrained not on monolingual data but on 2.5 TB of texts from CommonCrawl in 100 languages. 3 System overview …","url":["http://www.dialog-21.ru/media/5278/rachinskiymplusarefyevn130.pdf"]}
-{"year":"2021","title":"ZmBART: An Unsupervised Cross-lingual Transfer Framework for Language Generation","authors":["KK Maurya, MS Desarkar, Y Kano, K Deepshikha - arXiv preprint arXiv:2106.01597, 2021"],"snippet":"… languages. It is a transformer-based sequence- to-sequence pre-trained model. The model is trained on monolingual data in many languages from Wikipedia Common Crawl corpus with BART language model objective. Particularly …","url":["https://arxiv.org/pdf/2106.01597"]}
-{"year":"2022","title":"(Commercial) Automatic Speech Recognition as a Tool in Sociolinguistic Research","authors":["N Markl - University of Pennsylvania Working Papers in …, 2022"],"snippet":"As speech datasets used in sociolinguistic research increase in size, laborious and time-intensive manual orthographic transcription is a challenge, limiting the amount of (transcribed) data which can be analysed. In this paper, I discuss the use of (commercial) …","url":["https://repository.upenn.edu/cgi/viewcontent.cgi?article=2163&context=pwpl"]}
-{"year":"2022","title":"2 Related Work","authors":["M Kasri, M Birjali, M Nabil, A Beni-Hssane, A El-Ansari…"],"snippet":"Word embedding aims to learn distributed vector representations of words by exploiting the existence of a huge amount of contextual information in a large text corpus using different techniques. This idea starts with [30]. They proposed a neural …","url":["https://journals.riverpublishers.com/index.php/JICTS/article/download/13885/14689?inline=1"]}
-{"year":"2022","title":"22 ZYX","authors":["MC Quadri, L Schaffner, P Ullrich"],"snippet":"As is the case with many people, my first direct lessons about failure and errors happened at kindergarten and school. In my case, it was primarily due to my (back then undiagnosed) ADHD and, since it wasn’t my mother tongue, my precarious …","url":["https://apria.artez.nl/wp-content/uploads/2022/12/APRIA-Issue-5-Print-Out-V10-1.pdf"]}
-{"year":"2022","title":"4 Touché Task 1: Conversational Argument Retrieval","authors":["A Bondarenko, M Fröbe, M Beloucif, L Gienapp…"],"snippet":"… Other argument retrieval systems, such as ArgumenText [40] and TARGER [9], use the larger Common Crawl, requiring additionally also argument … scenarios, based on billions of sentences from the Common Crawl, however, it still lacks a …","url":["https://9dok.net/document/y4w4p04v-touch%C3%A9-task-conversational-argument-retrieval.html"]}
-{"year":"2022","title":"5 The Role of Language Prediction Models in Contractual Interpretation: The Challenges and Future Prospects of GPT-3","authors":["M Katrak - Legal Analytics: The Future of Analytics in Law, 2022"],"snippet":"… For training GPT-3, researchers used the Common Crawl dataset, which constituted nearly a trillion words. The Common Crawl dataset contains petabytes of data collected over the years and includes webpage data, text extracts, and …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=2NeSEAAAQBAJ&oi=fnd&pg=PT48&dq=commoncrawl&ots=lPkjRPXu5b&sig=pq4AW4fB8kV84NhHBTZk2NGs6o4"]}
-{"year":"2022","title":"\" Way back then\": A Data-driven View of 25+ years of Web Evolution","authors":["V Agarwal, N Sastry - arXiv preprint arXiv:2202.08239, 2022"],"snippet":"… For example, the use of historical crawls of the web such as the Common Crawl5. [30] is a brief history of web crawlers. [9] considers … Similarly, the common crawl12 represents a huge dataset of Web URLs and their content, that can provide …","url":["https://arxiv.org/pdf/2202.08239"]}
-{"year":"2022","title":"A California Effect For Artificial Intelligence","authors":["H Josephson"],"snippet":"… (Respectively, they used 4.9 terabytes of English and Chinese text and images, 1.56 trillion words compiled from various datasets, and a combination of English Wikipedia with ten years of Common Crawl data.) As the inconsistent units show …","url":["https://techhenzy.com/final-a-california-effect-for-artificial-intelligence/"]}
-{"year":"2022","title":"A code-mixed task-oriented dialog dataset for medical domain","authors":["S Dowlagar, R Mamidi - Computer Speech & Language, 2022"],"snippet":"In the healthcare domain, medical and patient interactions form a crucial part of the diagnosis. Initially, the AI models developed for healthcare centered only on monolingual data. However, such models do not cater to the multilingual regions …","url":["https://www.sciencedirect.com/science/article/pii/S0885230822000729"]}
-{"year":"2022","title":"A Comparative Study of Pre-trained Encoders for Low-Resource Named Entity Recognition","authors":["Y Chen, J Mikkelsen, A Binder, C Alt, L Hennig - arXiv preprint arXiv:2204.04980, 2022"],"snippet":"Pre-trained language models (PLM) are effective components of few-shot named entity recognition (NER) approaches when augmented with continued pre-training on task-specific out-of-domain data or fine-tuning on in-domain data. However, their …","url":["https://arxiv.org/pdf/2204.04980"]}
-{"year":"2022","title":"A Comparative Study of Pre-trained Word Embeddings for Arabic Sentiment Analysis","authors":["M Zouidine, M Khalil - 2022 IEEE 46th Annual Computers, Software, and …, 2022"],"snippet":"In this paper, we conduct a series of experiments to systematically study both context-independent and context-dependent word embeddings for the purpose of Arabic sentiment analysis. We use pretrained word embeddings as fixed features extractors to provide …","url":["https://ieeexplore.ieee.org/abstract/document/9842526/"]}
-{"year":"2022","title":"A comparative study on vectorization methods for non-functional requirements classification","authors":["P Leelaprute, S Amasaki - Information and Software Technology, 2022"],"snippet":"… The pre-trained model with 840 billion tokens of Common Crawl was used. This study used a vectorization method [30] based on the … For fastText, the pre-trained model with Common Crawl and Wikipedia was used. This study also used a …","url":["https://www.sciencedirect.com/science/article/pii/S0950584922001239"]}
-{"year":"2022","title":"A Comparative Text Classification Study with Deep Learning-Based Algorithms","authors":["Ö Köksal, Ö Akgül - 2022 9th International Conference on Electrical and …, 2022"],"snippet":"… The vectors are trained from Wikipedia and Common Crawl, and each has a length of 300. Furthermore, the vectors are generated for n-grams, n length sequences of characters, instead of words. This property allows FastText to …","url":["https://ieeexplore.ieee.org/abstract/document/9772587/"]}
-{"year":"2022","title":"A Comparison of Approaches for Imbalanced Classification Problems in the Context of Retrieving Relevant Documents for an Analysis","authors":["S Wankmüller - arXiv preprint arXiv:2205.01600, 2022"],"snippet":"One of the first steps in many text-based social science studies is to retrieve documents that are relevant for the analysis from large corpora of otherwise irrelevant documents. The conventional approach in social science to address this …","url":["https://arxiv.org/pdf/2205.01600"]}
-{"year":"2022","title":"A COMPREHENSIVE ANALYSIS OF SUBWORD TOKENIZERS FOR MORPHOLOGICALLY RICH LANGUAGES","authors":["E Erkaya - 2022"],"snippet":"… The corpus contains 33 gigabyte (GB) of text which is obtained by filtering the Common Crawl corpus. As shown in Table 4.1, each tokenizer can produce different tokens for the same word. To compare the tokenizers, we used BOUN Treebank [30] …","url":["https://www.cmpe.boun.edu.tr/~gungort/theses/A%20Comprehensive%20Analysis%20of%20Subword%20Tokenizers%20for%20Morphologically%20Rich%20Languages.pdf"]}
-{"year":"2022","title":"A Comprehensive Survey of Natural Language Generation Advances from the Perspective of Digital Deception","authors":["K Jones, E Altuncu, VNL Franqueira, Y Wang, S Li - arXiv preprint arXiv:2208.05757, 2022"],"snippet":"… Common Crawl: The Common Crawl dataset is a massive collection of petabytes of web data currently hosted by Amazon (https://commoncrawl.… Due to its size, Common Crawl has been popularly used in the training and pre-training of many …","url":["https://arxiv.org/pdf/2208.05757"]}
-{"year":"2022","title":"A Comprehensive Survey on Multi-hop Machine Reading Comprehension Approaches","authors":["A Mohammadi, R Ramezani, A Baraani - arXiv preprint arXiv:2212.04072, 2022"],"snippet":"… To decompose multi-hop question 𝑄 to simpler corpus 𝐷, First some candidate sub-question from a simple corpus 𝑆 will be created by mining 10M possible sub-questions from Common Crawl with a classifier. It then trains a decomposition model on the …","url":["https://arxiv.org/pdf/2212.04072"]}
-{"year":"2022","title":"A Corpus for Suggestion Mining of German Peer Feedback","authors":["R Rietsche, E Ritz, J Janda, D Pfütze"],"snippet":"Peer feedback in online education becomes increasingly important to meet the demand for feedback in large scale classes, such as eg Massive Open Online Courses (MOOCs). However, students are often not experts in how to write helpful …","url":["https://www.researchgate.net/profile/Roman-Rietsche/publication/362013990_A_Corpus_for_Suggestion_Mining_of_German_Peer_Feedback/links/62d10a069b8b7d1f6f712393/A-Corpus-for-Suggestion-Mining-of-German-Peer-Feedback.pdf"]}
-{"year":"2022","title":"A Critique Empirical Evaluation of Relevance Computation for Focused Web Crawlers","authors":["JDPNR Mary, S Balasubramanian, RSP Raj - Brazilian Archives of Biology and …, 2022"],"snippet":"HIGHLIGHTS This paper presents a survey on focused web crawlers. This paper presents the challenges in focused crawling research. This paper presents the highlights and hindrances of existing focused web crawlers. This paper also …","url":["https://www.scielo.br/j/babt/a/yG9Bw9htLXd554BfFcwwLCy/abstract/?lang=en"]}
-{"year":"2022","title":"A Data-driven Approach to Natural Language Processing for Contemporary and Historical French","authors":["PO Suarez - 2022"],"snippet":"… Each monthly Common Crawl snapshot is in itself a massive multilingual corpus, where every single file contains data coming from multiple web … Common Crawl has already been successfully used to train language models, even multilingual …","url":["https://tel.archives-ouvertes.fr/tel-03770337/document"]}
-{"year":"2022","title":"A Deep Learning approach to real-world Entity Linking: extracting and matching organisation mentions from unstructured text","authors":["T Bonomo - 2022"],"snippet":"… Specifically, the authors built a clean CommonCrawl Corpus composed of text scraped from the web in 100 different languages, amounting to around 2.5 TB of text data. The amount of data obviously varies from language to language, but Conneau …","url":["https://aaltodoc.aalto.fi/bitstream/handle/123456789/112889/master_Bonomo_Tommaso_2022.pdf?sequence=1"]}
-{"year":"2022","title":"A Dual Attention-Based Representation for the Detection of Abusive Language in Texts and Memes. Technical Report No. CCC-22-005","authors":["HJJ Vásquez - 2022"],"snippet":"… For word representation we used pretrained fastText embeddings [83], trained with subword information on Common Crawl, which have been recognized as useful for this task according to the study presented in [8]. All the non-BERT based DNNs …","url":["https://ccc.inaoep.mx/archivos/2021/CCC-22-005.pdf"]}
-{"year":"2022","title":"A Format-Aware Reducer for Scriptable Rewriting of PDF Files","authors":["P Anantharaman, S Cheung, N Boorman, ME Locasto"],"snippet":"Sanitizing untrusted input is a significant unsolved problem in defensive cybersecurity and input handling. Even if we assume that a safe, provably correct parser exists to validate the input syntax, processing logic may still require the …","url":["https://prashant.at/files/pdffixer.pdf"]}
-{"year":"2022","title":"A Framework for Deprecating Datasets: Standardizing Documentation, Identification, and Communication","authors":["AS Luccioni, F Corry, H Sridharan, M Ananny, J Schultz… - 2022"],"snippet":"… , given their sheer size (C4 represents 2.3 TB of data, whereas the Common Crawl has 139TB), filtering them is complex and time-consuming, … In practice, documenting and deprecating these datasets is akin to a game of whack-a-mole …","url":["https://facctconference.org/static/pdfs_2022/facct22-17.pdf"]}
-{"year":"2022","title":"A Gated Recurrent Unit based architecture for recognizing ontology concepts from biological literature","authors":["P Devkota, SD Mohanty, P Manda - BioData Mining, 2022"],"snippet":"Annotating scientific literature with ontology concepts is a critical task in biology and several other domains for knowledge discovery. Ontology based annotations can power large-scale comparative analyses in a wide range of applications ranging …","url":["https://biodatamining.biomedcentral.com/articles/10.1186/s13040-022-00310-0"]}
-{"year":"2022","title":"A generating model for Finnish nominal inflection using distributional semantics","authors":["A Nikolaev, YY Chuang, RH Baayen - 2022"],"snippet":"Finnish nouns are characterized by rich inflectional variation, with obligatory marking of case and number, with optional possessive suffixes and with the possibility of further cliticization. We present a model for the conceptualization of …","url":["https://psyarxiv.com/ndtv2/download"]}
-{"year":"2022","title":"A Holistic Approach to Undesired Content Detection in the Real World","authors":["T Markov, C Zhang, S Agarwal, T Eloundou, T Lee… - arXiv preprint arXiv …, 2022"],"snippet":"… PUB consists of around 90k public examples including both samples from academic datasets and Web data (Common Crawl) labeled by our annotators. SYN adds additional 69k curated synthetic examples. MIX contains all examples in SYN …","url":["https://arxiv.org/pdf/2208.03274"]}
-{"year":"2022","title":"A Holistic Assessment of the Carbon Footprint of Noor, a Very Large Arabic Language Model","authors":["I Lakim, E Almazrouei, IA Alhaol, M Debbah, J Launay - Challenges {\\&, 2022"],"snippet":"… We use Common Crawl (CC) for acquiring large amounts of web data. Each CC dump is on average around 10TB, and we discard it immediately after processing it. On average, it takes 24 hours to fully process a dump: we used 21 dumps from CC …","url":["https://openreview.net/pdf?id=B-lS3zH8Zq"]}
-{"year":"2022","title":"A Hybrid Deep Learning Approach to Detect Bangla Social Media Hate Speech","authors":["T Ghosh, AAK Chowdhury, M Banna, H Al, M Nahian… - Proceedings of International …, 2022"],"snippet":"Social media has become an integral part of our day-to-day life. In our activities or posts on social media, the presence of hate speech written in the native language or English has increased significantly. It often leads to the spread of negativity …","url":["https://link.springer.com/chapter/10.1007/978-981-19-2445-3_50"]}
-{"year":"2022","title":"A hybrid feature-based approach for classification of Fake News in Sinhala on social media","authors":["W Wijayarathna, S Jayalal"],"snippet":"… According to research work on evaluating the word embedding for the Sinhala language, FastText trained on the Common Crawl dataset is the best word embedding for Sinhala compared to the Pre-trained Facebook FastText model, Word2Vec, and …","url":["https://www.researchgate.net/profile/Shantha-Jayalal/publication/356842533_A_hybrid_feature-based_approach_for_classification_of_Fake_News_in_Sinhala_on_social_media/links/62d4f3a166bd1654d66edb11/A-hybrid-feature-based-approach-for-classification-of-Fake-News-in-Sinhala-on-social-media.pdf"]}
-{"year":"2022","title":"A Hybrid Phishing Detection System Using Deep Learning-based URL and Content Analysis","authors":["M Korkmaz, E Kocyigit, OK Sahingoz, B Diri - Elektronika ir Elektrotechnika, 2022"],"snippet":"… With a new dataset (1 million URLs, half of which was obtained from PhishTank and the rest from the CommonCrawl database, and the dataset contains 10,000 images) which researchers used in [21], CNN and LSTM were tested in Intelligent …","url":["https://www.eejournal.ktu.lt/index.php/elt/article/download/31197/15556"]}
-{"year":"2022","title":"A hybrid quantum approach to leveraging data from HTML tables","authors":["P Jiménez Aguirre, JC Roldán Salvador… - Knowledge and Information …, 2022","P Jiménez, JC Roldán, R Corchuelo - Knowledge and Information Systems, 2022"],"snippet":"… Unfortunately, a recent analysis of the 32.04 million domains in the November 2019 Common Crawl has revealed that only 11.92 million domains provide such tags [5], which means that there are roughly 20.12 million domains that do not …","url":["https://idus.us.es/bitstream/handle/11441/131991/Jim%C3%A9nez2022_Article_AHybridQuantumApproachToLevera.pdf?sequence=1&isAllowed=y","https://link.springer.com/article/10.1007/s10115-021-01636-7"]}
-{"year":"2022","title":"A Knowledge-Enhanced Adversarial Model for Cross-lingual Structured Sentiment Analysis","authors":["Q Zhang, J Zhou, Q Chen, Q Bai, J Xiao, L He - arXiv preprint arXiv:2205.15514, 2022"],"snippet":"… XLM-RoBERTa model is pre-trained on the 100 languages with 2.5TB of filtered CommonCrawl data. Moreover, [35] finetuned XLM-RoBERTa models on named-entity-recognition (NER) task with multilingual datasets. However, most existing works use one of …","url":["https://arxiv.org/pdf/2205.15514"]}
-{"year":"2022","title":"A Large and Diverse Arabic Corpus for Language Modeling","authors":["AR Ali, W Antoun"],"snippet":"… The Open Super-large Crawled ALMAnaCH coRpus (OSCAR) is a multi-lingual corpus, extracted from Common Crawl (CC) by performing … N-gram counts and language models from the common crawl. In Proceedings of the Language Resources …","url":["http://percipience.io/papers/14-A%20Large%20and%20Diverse%20Arabic%20Corpus%20for%20Language%20Modeling.pdf"]}
-{"year":"2022","title":"A LEGAL FRAMEWORK FOR ARTIFICIAL INTELLIGENCE FAIRNESS REPORTING","authors":["JQ Yap, E Lim - The Cambridge Law Journal"],"snippet":"Clear understanding of artificial intelligence (AI) usage risks and how they are being addressed is needed, which require proper and adequate corporate disclosure. We advance a legal framework for AI Fairness Reporting to which companies can and …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C2D73FBE9BB74E5D41DDA6BDCA208424/S0008197322000460a.pdf/legal_framework_for_artificial_intelligence_fairness_reporting.pdf"]}
-{"year":"2022","title":"A Lite Romanian BERT: ALR-BERT","authors":["DC Nicolae, RK Yadav, D Tufiş - Computers, 2022"],"snippet":"… OSCAR—OSCAR, or Open Super-large Crawled ALMAnaCH corpora, is a massive multilingual corpus derived from the Common Crawl corpus using language categorization and filtering [16]. There are approximately 11 GB of text in …","url":["https://www.mdpi.com/2073-431X/11/4/57/htm"]}
-{"year":"2022","title":"A Literature Survey of Recent Advances in Chatbots. Information 2022, 13, 41","authors":["G Caldarini, S Jaf, K McGarry - 2022"],"snippet":"… This led to the development of pretrained systems such as BERT (Bidirectional Encoder Representations from transformers) [39] and GPT (Generative Pre-trained Transformer), which were trained with huge language datasets, such as Wikipedia …","url":["https://www.researchgate.net/profile/Sardar-Jaf-2/publication/357839467_A_Literature_Survey_of_Recent_Advances_in_Chatbots/links/61e2ca739a753545e2d1d107/A-Literature-Survey-of-Recent-Advances-in-Chatbots.pdf"]}
-{"year":"2022","title":"A Longitudinal Study of Semantic Networks in Schizophrenia and other Psychotic Disorders using the Word Association Task","authors":["AS Pintos, CLM Hui, S De Deyne, C Cheung, WT Ko… - Schizophrenia Bulletin …, 2022"],"snippet":"Background and Hypothesis The underpinnings of language deviations in psychotic symptoms (eg, formal thought disorder, delusions) remains unclear. We examined whether the semantic networks underlying word associations are useful predictors of …","url":["https://academic.oup.com/schizbullopen/advance-article/doi/10.1093/schizbullopen/sgac054/6674699"]}
-{"year":"2022","title":"A Machine Learning approach for Fake News Detection.","authors":["WH Bisen, A Paunikar, B Thakur, A Garg, K Nangliya - International Journal of Next …, 2022"],"snippet":"A vital role is played by the media in the circulation of public information about the happenings. A fast spread of information using social media and social networks or websites is possible due to the quick development of the internet. With no worry …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=09765034&AN=160489051&h=vXvZ1C0skCEklVQHU1w%2BTwUttEuXD97YHxfGI7eP6GbTwor0eizcYbuqmIlDWIsykEHZBsH0ixNrZw%2BxAqBidQ%3D%3D&crl=c"]}
-{"year":"2022","title":"A mechanism for personalized Automatic Speech Recognition for less frequently spoken languages: the Greek case","authors":["P Antoniadis, E Tsardoulias, A Symeonidis"],"snippet":"Automatic Speech Recognition (ASR) has become increasingly popular since it significantly simplifies human-computer interaction, providing a more intuitive way of communication. Building an accurate, general-purpose ASR system is a challenging …","url":["https://panosantoniadis.github.io/files/personalized_asr.pdf"]}
-{"year":"2022","title":"A Multi-dimensional Evaluation of Tokenizer-free Multilingual Pretrained Models","authors":["J Sun, P Fernandes, X Wang, G Neubig - arXiv preprint arXiv:2210.07111, 2022"],"snippet":"… Both ByT5 and mT5 are pretrained on the multilingual Common Crawl (mC4) corpus1 using the span reconstruction objective proposed by Raffel et al. (2020). ByT5 operates on the raw UTF8 bytes of the input without any downsampling …","url":["https://arxiv.org/pdf/2210.07111"]}
-{"year":"2022","title":"A Multi-modal Approach to Mining Intent from Code-Mixed Hindi-English Calls in the Hyperlocal-Delivery Domain","authors":["J Mathew, P Sahu, B Singhal, A Joshi, KR Medikonda… - International Conference on …, 2022"],"snippet":"In this work we outline an approach to mine insights from calls between delivery partners (DP) and customers involved in hyperlocal food delivery in India. Incorrect addresses/ locations or other impediments prompt the DPs to call customers leading …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20980-2_41"]}
-{"year":"2022","title":"A Multi-task Multi-modal Framework for Sentiment and Emotion aided Cyberbully Detection","authors":["K Maity, A Kumar, S Saha - IEEE Internet Computing, 2022"],"snippet":"… The model uses a BERT based architecture pretrained by the Wikipedia and Common Crawl, along with PMINDIA and Dakshina corpora … So to overcome this issue, we have chosen MuRIL BERT, which has been pre-trained by Wikipedia and …","url":["https://ieeexplore.ieee.org/abstract/document/9733228/"]}
-{"year":"2022","title":"A Multilingual Approach to Scene Text Visual Question Answering","authors":["D Karatzas - Document Analysis Systems: 15th IAPR International …","J Brugués i Pujolràs, L Gómez i Bigordà, D Karatzas - International Workshop on …, 2022"],"snippet":"… The provided FastText embeddings are either trained on Wikipedia (Wiki) or Common Crawl (CC) corpora and are available in 157 languages Footnote 3 . We have used the monolingual embeddings trained in both Wiki and CC, and we have …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=81xwEAAAQBAJ&oi=fnd&pg=PA65&dq=commoncrawl&ots=vQu3SxHxPs&sig=P3my4WCb63x3Ok5GPvjtzpy_FcI","https://link.springer.com/chapter/10.1007/978-3-031-06555-2_5"]}
-{"year":"2022","title":"A Multilingual Simplified Language News Corpus","authors":["R Hauser, J Vamvas, S Ebling, M Volk - 2nd Workshop on Tools and Resources for …, 2022"],"snippet":"Simplified language news articles are being offered by specialized web portals in several countries. The thousands of articles that have been published over the years are a valuable resource for natural language processing, especially for efforts …","url":["https://cental.uclouvain.be/readi2022/readi_2022_proceedings.pdf#page=35"]}
-{"year":"2022","title":"A multistage retrieval system for health-related misinformation detection","authors":["M Fernández-Pichel, DE Losada, JC Pichel - Engineering Applications of Artificial …, 2022"],"snippet":"Web search is widely used to find online medical advice. As such, health-related information access requires retrieval algorithms capable of promoting reliable documents and filtering out unreliable ones. To this end, different types of …","url":["https://www.sciencedirect.com/science/article/pii/S0952197622002950"]}
-{"year":"2022","title":"A Novel Approach to Train Diverse Types of Language Models for Health Mention Classification of Tweets","authors":["PI Khan, I Razzak, A Dengel, S Ahmed - arXiv preprint arXiv:2204.06337, 2022"],"snippet":"Health mention classification deals with the disease detection in a given text containing disease words. However, non-health and figurative use of disease words adds challenges to the task. Recently, adversarial training acting as a means of …","url":["https://arxiv.org/pdf/2204.06337"]}
-{"year":"2022","title":"A Paradigm Shift from “Human Writing” to “Machine Generation” in Personality Test Development: an Application of State-of-the-Art Natural Language Processing","authors":["P Lee, S Fyffe, M Son, Z Jia, Z Yao - Journal of Business and Psychology, 2022"],"snippet":"Natural language processing (NLP) techniques have become increasingly popular in areas of psychological assessment. Recently, researchers have sought to use NLP techniques for automatic item generation (AIG) in the personality domain …","url":["https://link.springer.com/article/10.1007/s10869-022-09864-6"]}
-{"year":"2022","title":"A Part-of-Speech Tagger for Yiddish: First Steps in Tagging the Yiddish Book Center Corpus","authors":["S Kulick, N Ryant, B Santorini, J Wallenberg - arXiv preprint arXiv:2204.01175, 2022"],"snippet":"We describe the construction and evaluation of a part-of-speech tagger for Yiddish (the first one, to the best of our knowledge). This is the first step in a larger project of automatically assigning part-of-speech tags and syntactic structure to Yiddish text for …","url":["https://arxiv.org/pdf/2204.01175"]}
-{"year":"2022","title":"A Persian ASR-based SER: Modification of Sharif Emotional Speech Database and Investigation of Persian Text Corpora","authors":["A Yazdani, Y Shekofteh - arXiv preprint arXiv:2211.09956, 2022"],"snippet":"Speech Emotion Recognition (SER) is one of the essential perceptual methods of humans in understanding the situation and how to interact with others, therefore, in recent years, it has been tried to add the ability to recognize emotions to human-machine …","url":["https://arxiv.org/pdf/2211.09956"]}
-{"year":"2022","title":"A Projection-Based Asymmetric Similarity Measure for Distributional Semantic Models","authors":["R Das"],"snippet":"… We apply our model to GloVe vector representations (trained on the Common Crawl 42B corpus) of pairs of words taken from two databases on free association norms, and compute the correlation between the human responses and our model’s …","url":["https://riadas.github.io/files/6_804_Final_Project.pdf"]}
-{"year":"2022","title":"A Review on Phishing Websites Revealing through Machine Learning","authors":["AS Sengar, A Bhola, RK Shukla, A Gupta - … on System Modeling & Advancement in …, 2021"],"snippet":"Phishing is a frequent assault in which unsuspecting people’s unique, private, and sensitive information is stolen through fake websites. The primary objective of phishing websites’consistent resource allocators isto steal unique, private, and …","url":["https://ieeexplore.ieee.org/abstract/document/9676288/"]}
-{"year":"2022","title":"A Review on Text-Based Emotion Detection--Techniques, Applications, Datasets, and Future Directions","authors":["S Kusal, S Patil, J Choudrie, K Kotecha, D Vora… - arXiv preprint arXiv …, 2022"],"snippet":"Artificial Intelligence (AI) has been used for processing data to make decisions, interact with humans, and understand their feelings and emotions. With the advent of the internet, people share and express their thoughts on day-to-day activities and …","url":["https://arxiv.org/pdf/2205.03235"]}
-{"year":"2022","title":"A Roadmap for Big Model","authors":["S Yuan, H Zhao, S Zhao, J Leng, Y Liang, X Wang… - arXiv preprint arXiv …, 2022"],"snippet":"… C4 is a colossal, cleaned version of Common Crawl’s web crawl corpus. It is based on Common Crawl dataset and was used to train the … CLUECorpus2020 is a high-quality Chinese pre-training corpus obtained by cleaning the Chinese part of …","url":["https://arxiv.org/pdf/2203.14101"]}
-{"year":"2022","title":"A Simple Multi-Modality Transfer Learning Baseline for Sign Language Translation","authors":["Y Chen, F Wei, X Sun, Z Wu, S Lin - arXiv preprint arXiv:2203.04287, 2022"],"snippet":"This paper proposes a simple transfer learning baseline for sign language translation. Existing sign language datasets (eg PHOENIX-2014T, CSL-Daily) contain only about 10K-20K pairs of sign videos, gloss annotations and texts, which …","url":["https://arxiv.org/pdf/2203.04287"]}
-{"year":"2022","title":"A Study of Commonsense Reasoning with Language Models","authors":["RMR Branco - 2021"],"snippet":"Artificial Intelligence (AI) has gone through an increasing growth in the past decades, which in the present day translates to its usage in almost every sector of society. From its inception, AI pursues the reproduction of human intelligence. Currently, AI¬equipped …","url":["https://repositorio.ul.pt/bitstream/10451/51357/1/TM_Ruben_Branco.pdf"]}
-{"year":"2022","title":"A Study of Implicit Bias in Pretrained Language Models against People with Disabilities","authors":["PN Venkit, M Srinath, S Wilson - Proceedings of the 29th International Conference on …, 2022"],"snippet":"Pretrained language models (PLMs) have been shown to exhibit sociodemographic biases, such as against gender and race, raising concerns of downstream biases in language technologies. However, PLMs’ biases against people with disabilities (PWDs) …","url":["https://aclanthology.org/2022.coling-1.113.pdf"]}
-{"year":"2022","title":"A Study of Implicit Language Model Bias Against People With Disabilities","authors":["PN Venkit, M Srinath, S Wilson"],"snippet":"Pretrained language models (PLMs) have been shown to exhibit sociodemographic biases, such as against gender and race, raising concerns of downstream biases in language technologies. However, PLMs’ biases against people with disabilities (PWDs) …","url":["https://shomir.net/pdf/publications/coling_2022_pranav.pdf"]}
-{"year":"2022","title":"A Study of Various Word Embeddings in Deep Learning","authors":["P Shah, S Shah, S Joshi - 2022 3rd International Conference for Emerging …, 2022"],"snippet":"With the number of users and reviews rising on the internet, and the liberty was given to post anything on it, it is still a major issue to identify the sentiment of the reviews. The traditional machine learning models are taking a lot of computational …","url":["https://ieeexplore.ieee.org/abstract/document/9824963/"]}
-{"year":"2022","title":"A Study on Chinese-English Machine Translation Based on Transfer Learning and Neural Networks","authors":["C Li - Wireless Communications and Mobile Computing, 2022"],"snippet":"The existing Chinese-English machine translation has problems such as inaccurate word translation and difficult translation of long sentences. To this end, this paper proposes a new machine translation model based on bidirectional Chinese-English …","url":["https://www.hindawi.com/journals/wcmc/2022/8282164/"]}
-{"year":"2022","title":"A Study on Extracting Named Entities from Fine-tuned vs. Differentially Private Fine-tuned BERT Models","authors":["A Diera, N Lell, A Garifullina, A Scherp - arXiv preprint arXiv:2212.03749, 2022"],"snippet":"… During prompt creation, we sampled a 100 character length string either from the Common Crawl dataset (naive prompting) or from the test set (informed prompting). We set the sequence length to 256 tokens. We removed the tokens of the prompt …","url":["https://arxiv.org/pdf/2212.03749"]}
-{"year":"2022","title":"A Survey on Artificial Intelligence for Source Code: A Dialogue Systems Perspective","authors":["E Al-Hossami, S Shaikh - arXiv preprint arXiv:2202.04847, 2022"],"snippet":"In this survey paper, we overview major deep learning methods used in Natural Language Processing (NLP) and source code over the last 35 years. Next, we present a survey of the applications of Artificial Intelligence (AI) for source code, also …","url":["https://arxiv.org/pdf/2202.04847"]}
-{"year":"2022","title":"A Survey on Gender Bias in Natural Language Processing","authors":["K Stanczak, I Augenstein - arXiv preprint arXiv:2112.14168, 2021"],"snippet":"Language can be used as a means of reproducing and enforcing harmful stereotypes and biases and has been analysed as such in numerous research. In this paper, we present a survey of 304 papers on gender bias in natural language …","url":["https://arxiv.org/pdf/2112.14168"]}
-{"year":"2022","title":"A Survey on NLP resources, tools and techniques for Marathi Language Processing","authors":["P Lahoti, N Mittal, G Singh - Transactions on Asian and Low-Resource Language …, 2022"],"snippet":"… using goclassy architecture through language classiication and iltering the Common Crawl2 corpus. The current version of OSCAR corpus … CC-Net corpus applied an automatic pipeline to extract massive high-quality monolingual text from …","url":["https://dl.acm.org/doi/abs/10.1145/3548457"]}
-{"year":"2022","title":"A Survey on Phishing Website Detection Using Deep Neural Networks","authors":["V Sharma, T Halevi - International Conference on Human-Computer …, 2022"],"snippet":"Phishing is a social engineering attack, where an attacker poses as a legitimate individual or institution and convinces a victim to divulge their details through human interaction. There has been a steep rise in phishing cases across the globe. A report …","url":["https://link.springer.com/chapter/10.1007/978-3-031-19682-9_87"]}
-{"year":"2022","title":"A Survey on Semantics in Automated Data Science","authors":["U Khurana, K Srinivas, H Samulowitz - arXiv preprint arXiv:2205.08018, 2022"],"snippet":"Data Scientists leverage common sense reasoning and domain knowledge to understand and enrich data for building predictive models. In recent years, we have witnessed a surge in tools and techniques for {\\em automated machine learning} …","url":["https://arxiv.org/pdf/2205.08018"]}
-{"year":"2022","title":"A survey on text classification: Practical perspectives on the Italian language","authors":["A Gasparetto, A Zangari, M Marcuzzo, A Albarelli - PloS one, 2022"],"snippet":"Text Classification methods have been improving at an unparalleled speed in the last decade thanks to the success brought about by deep learning. Historically, state-of-the-art approaches have been developed for and benchmarked against English datasets …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0270904"]}
-{"year":"2022","title":"A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions","authors":["B Qin, B Hui, L Wang, M Yang, J Li, B Li, R Geng… - arXiv preprint arXiv …, 2022"],"snippet":"… WDC WebTables [79] is a large-scale table collection, which contains over 233 million tables and has been extracted from the July 2015 version of the CommonCrawl. Those tables are classified as either relational (90 million), entity (139 …","url":["https://arxiv.org/pdf/2208.13629"]}
-{"year":"2022","title":"A Symmetric Fusion Learning Model for Detecting Visual Relations and Scene Parsing","authors":["X Liu, X Jing, Z Zheng, W Du, X Ding, Q Zhu - Scientific Programming, 2022"],"snippet":"… We employ a pretrained word vector fastText trained on Common Crawl [38] to implement our purpose. Unlike the word vector models that ignore the morphological features inside words, the fastText model utilizes a bag of n-grams to …","url":["https://www.hindawi.com/journals/sp/2022/5985392/"]}
-{"year":"2022","title":"A Systematic Review on Machine Learning and Deep Learning Models for Electronic Information Security in Mobile Networks","authors":["C Gupta, I Johri, K Srinivasan, YC Hu, SM Qaisar… - Sensors, 2022"],"snippet":"Today’s advancements in wireless communication technologies have resulted in a tremendous volume of data being generated. Most of our information is part of a widespread network that connects various devices across the globe. The …","url":["https://www.mdpi.com/1424-8220/22/5/2017/pdf"]}
-{"year":"2022","title":"A thesis that writes itself: On the threat of AI-generated essays within academia","authors":["A Olsson, O Engelbrektsson - 2022"],"snippet":"… 3 The CommonCrawl dataset is a large dataset of web crawl data that is freely available. The dataset is made up of data from various web crawls and contains a wealth of information on the web. The dataset used by GPT-3 is 570GB. …","url":["https://www.diva-portal.org/smash/get/diva2:1669744/FULLTEXT02"]}
-{"year":"2022","title":"A Tool for Study on Impact of Big Data Technologies on firm performance","authors":["C Lotfi, S Srinivasan, M Ertz, I Latrous"],"snippet":"Organizations can use big data analytics to evaluate large data volumes and collect new information. It aids in answering basic inquiries concerning business operations and performance. It also aids in the discovery of unknown patterns in massive …","url":["https://www.researchgate.net/profile/Myriam-Ertz/publication/358504492_A_Tool_for_Study_on_Impact_of_Big_Data_Technologies_on_Firm_Performance/links/62053348634ff774f4c0b07c/A-Tool-for-Study-on-Impact-of-Big-Data-Technologies-on-Firm-Performance.pdf"]}
-{"year":"2022","title":"A Transferable and Automatic Tuning of Deep Reinforcement Learning for Cost Effective Phishing Detection","authors":["O Lavie, A Shabtai, G Katz - arXiv preprint arXiv:2209.09033, 2022"],"snippet":"… The first dataset is Bahnsen [16], which contains 1.2M benign URLs taken from the Common Crawl corpus, and 1.146M phishing URLs from PhishTank. The second dataset is Wang [19], which contains 245K phishing URLs collected from …","url":["https://arxiv.org/pdf/2209.09033"]}
-{"year":"2022","title":"A Transformer-based Sequence-labeling Approach to the Slovenian Cross-domain Automatic Term Extraction","authors":["THH Tran, M Martinc, A Repar, A Doucet, S Pollak"],"snippet":"Automatic term extraction (ATE) is a popular research task that eases the time and effort of manually identifying terms from domainspecific corpora by providing a list of candidate terms. In this paper, we treat terminology extraction as a sequence-labeling …","url":["https://nl.ijs.si/jtdh22/pdf/JTDH2022_Tran-et-al_A-Transformer-based-Sequence-labeling-Approach-to-the-Slovenian-Cross-domain-Automatic-Term-Extraction.pdf"]}
-{"year":"2022","title":"A Unified Strategy for Multilingual Grammatical Error Correction with Pre-trained Cross-Lingual Language Model","authors":["X Sun, T Ge, S Ma, J Li, F Wei, H Wang - arXiv preprint arXiv:2201.10707, 2022"],"snippet":"Synthetic data construction of Grammatical Error Correction (GEC) for non-English languages relies heavily on human-designed and language-specific rules, which produce limited error-corrected patterns. In this paper, we propose a generic and …","url":["https://arxiv.org/pdf/2201.10707"]}
-{"year":"2022","title":"A Universal Deduplication Architecture for Secure and Efficient Cloud Storage","authors":["K Saric, G Ramachandran, S Pal, R Jurdak, S Nepal - Proceedings of the Fourth IEEE …, 2022"],"snippet":"… Bloom filters populated with lists of filenames found in the Common Crawl dataset returned query responses in under 5 milliseconds on a typical laptop while configured with a false positive probability of 1 in 1015 (1 in a quadrillion) This is a …","url":["https://eprints.qut.edu.au/236903/1/Saric_A_Universal_Deduplication_Architecture.pdf"]}
-{"year":"2022","title":"A Use Case of Patent Classification Using Deep Learning with Transfer Learning","authors":["R Henriques, A Ferreira, M Castelli - Journal of Data and Information Science, 2022"],"snippet":"Abstract: Purpose: Patent classification is one of the areas in Intellectual Property Analytics (IPA), and a growing use case since the number of patent applications has been increasing worldwide. We propose using machine learning algorithms to …","url":["http://manu47.magtech.com.cn/Jwk3_jdis/EN/article/downloadArticleFile.do?attachType=PDF&id=441"]}
-{"year":"2022","title":"A User Study on Clarifying Comparative Questions","authors":["A Bondarenko, E Shirshakova, M Hagen - Proceedings of CHIIR, 2022"],"snippet":"… From the obtained entities, we selected the pairs with the highest sentence-wise co-occurrence frequencies in the Common Crawl snapshot 2014154 (eg, ‘drummer’ and ‘guitarist’ for occupation or ‘amoxicillin’ and ‘ciprofloxacin’ for antibiotics). As for …","url":["https://webis.de/downloads/publications/papers/bondarenko_2022b.pdf"]}
-{"year":"2022","title":"A Warm Start and a Clean Crawled Corpus--A Recipe for Good Language Models","authors":["V Snæbjarnarson, HB Símonarson, PO Ragnarsson… - arXiv preprint arXiv …, 2022"],"snippet":"… We also demonstrate how to directly extract Icelandic text from the Common Crawl corpus in … that in mC4, which is also sourced from Common Crawl, there are 107 labelled languages, with … We believe that by using text extracted from the …","url":["https://arxiv.org/pdf/2201.05601"]}
-{"year":"2022","title":"A Web-Scale Analysis of the Community Origins of Image Memes","authors":["D Morina, MS Bernstein - Proceedings of the ACM on Human-Computer …, 2022"],"snippet":"… So, we adopted a common revision called harmonic centrality [43], endorsed and used by the Common Crawl foundation in their web-wide web crawl snapshot [13]. We obtained harmonic centrality scores for each community from a full web crawl by …","url":["https://dl.acm.org/doi/abs/10.1145/3512921"]}
-{"year":"2022","title":"Abstractive Summarization of Broadcast News Stories for Estonian","authors":["H Henry, A Tanel"],"snippet":"We present an approach for generating abstractive summaries for Estonian spoken news stories in a low-resource setting. Given a recording of a radio news story, the goal is to create a summary that captures the essential information in a short format …","url":["https://www.bjmc.lu.lv/fileadmin/user_upload/lu_portal/projekti/bjmc/Contents/10_3_23_Harm.pdf"]}
-{"year":"2022","title":"Accurate Dependency Parsing and Tagging of Latin","authors":["S Nehrdich, O Hellwig"],"snippet":"Having access to high-quality grammatical annotations is important for downstream tasks in NLP as well as for corpus-based research. In this paper, we describe experiments with the Latin BERT word embeddings that were recently be made …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/LT4HALA/pdf/2022.lt4hala2022-1.3.pdf"]}
-{"year":"2022","title":"Accurately Identifying Cerebroarterial Stenosis from Angiography Reports Using Natural Language Processing Approaches","authors":["CH Lin, KC Hsu, CK Liang, TH Lee, CS Shih, YC Fann - Diagnostics, 2022"],"snippet":"Patients with intracranial artery stenosis show high incidence of stroke. Angiography reports contain rich but underutilized information that can enable the detection of cerebrovascular diseases. This study evaluated various natural language …","url":["https://www.mdpi.com/2075-4418/12/8/1882/pdf?version=1659537394"]}
-{"year":"2022","title":"Active Exploration based on Information Gain by Particle Filter for Efficient Spatial Concept Formation","authors":["A Taniguchi, Y Tabuchi, T Ishikawa, LE Hafi… - arXiv preprint arXiv …, 2022"],"snippet":"Autonomous robots are required to actively and adaptively learn the categories and words of various places by exploring the surrounding environment and interacting with users. In semantic mapping and spatial language acquisition conducted using …","url":["https://arxiv.org/pdf/2211.10934"]}
-{"year":"2022","title":"Ad creative generation using reinforced generative adversarial network","authors":["S Terzioğlu, KN Çoğalmış, A Bulut - Electronic Commerce Research, 2022"],"snippet":"… T5 and PEGASUS models were trained on 750 GB of English-language text from the public Common Crawl web scrape. BART model was trained on the CNN/Daily Mail dataset, which contains over 300k unique news articles from CNN and the Daily …","url":["https://link.springer.com/article/10.1007/s10660-022-09564-6"]}
-{"year":"2022","title":"Adam Mickiewicz University at WMT 2022: NER-Assisted and Quality-Aware Neural Machine Translation","authors":["A Nowakowski, G Pałka, K Guttmann, M Pokrywka - arXiv preprint arXiv:2209.02962, 2022"],"snippet":"This paper presents Adam Mickiewicz University's (AMU) submissions to the constrained track of the WMT 2022 General MT Task. We participated in the Ukrainian $\\leftrightarrow$ Czech translation directions. The systems are a weighted …","url":["https://arxiv.org/pdf/2209.02962"]}
-{"year":"2022","title":"Adam mickiewicz university's english-hausa submissions to the wmt 2021 news translation task","authors":["A Nowakowski, T Dwojak - Proceedings of the Sixth Conference on Machine …, 2021"],"snippet":"This paper presents the Adam Mickiewicz University’s (AMU) submissions to the WMT 2021 News Translation Task. The submissions focus on the English↔ Hausa translation directions, which is a low-resource translation scenario between distant …","url":["https://aclanthology.org/2021.wmt-1.14.pdf"]}
-{"year":"2022","title":"Adapting Automatic Speech Recognition to the Radiology Domain for a Less-Resourced Language: The Case of Latvian","authors":["N Gruzitis, R Dargis, VJ Lasmanis, G Garkaje, D Gosko - Intelligent Sustainable …, 2022"],"snippet":"Automatic speech recognition (ASR) is becoming available to more and more languages. Training a quality ASR system typically requires significant amount of language resources—representative speech and text corpora. Recent advances in …","url":["https://link.springer.com/chapter/10.1007/978-981-16-6309-3_27"]}
-{"year":"2022","title":"Adapting Pretrained Models for Machine Translation","authors":["A Kurniawan - 2022"],"snippet":"Pre-trained language models received extensive attention in recent years. However, it is still challenging to incorporate a pre-trained model such as BERT into natural language generation tasks. This work investigates a recent method called adapters …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/175352/120426661.pdf?sequence=1"]}
-{"year":"2022","title":"Adapting Pretrained Text-to-Text Models for Long Text Sequences","authors":["W Xiong, A Gupta, S Toshniwal, Y Mehdad, W Yih - arXiv preprint arXiv:2209.10052, 2022"],"snippet":"We present an empirical study of adapting an existing pretrained text-to-text model for long-sequence inputs. Through a comprehensive study along three axes of the pretraining pipeline -- model architecture, optimization objective, and pretraining …","url":["https://arxiv.org/pdf/2209.10052"]}
-{"year":"2022","title":"Adapting Transformers for Multi-Label Text Classification","authors":["H Fallah, P Bellot, E Bruno, E Murisasco - 2022"],"snippet":"… , in addition to text crawled from the internet (Common-Crawl), on wikipedia article and books, thus getting more vocabulary coverage of MFHAD than CamemBERT that is pre-trained on a corpus derived from Common-Crawl. The …","url":["http://ceur-ws.org/Vol-3178/CIRCLE_2022_paper_07.pdf"]}
-{"year":"2022","title":"Addressing religious hate online: from taxonomy creation to automated detection","authors":["A Ramponi, B Testa, S Tonelli, E Jezek - PeerJ Computer Science, 2022"],"snippet":"… et al., 2020), a RoBERTa-based model pretrained on 2.5TB of CommonCrawl raw text containing 100 languages. We use the bert-base-multilingual-cased … OSCAR is a large-scale multilingual corpus based on filtered Common Crawl data that has …","url":["https://peerj.com/articles/cs-1128/"]}
-{"year":"2022","title":"Adversarial Cross-domain Community Question Retrieval","authors":["A Guo, X Li, N Pang, X Zhao - Transactions on Asian and Low-Resource Language …, 2022"],"snippet":"… In practice, we choose the embedding set (Common Crawl, glove.840B.300d), which contains 840B tokens and 2.2M vocabulary. The word embeddings are of 300 dimensions. The word embedding is updated during the training process. …","url":["https://dl.acm.org/doi/abs/10.1145/3487291"]}
-{"year":"2022","title":"AfriBERTa: Towards Viable Multilingual Language Models for Low-resource Languages","authors":["K Ogueji - 2022"],"snippet":"… Given that there is significant overlap between the African language corpora in Common Crawl and the BBC News data that we crawled, we … We observe that the quality of the dataset from Common Crawl is very low, confirming recent findings …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/18662/Ogueji_Kelechi.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"AfroLID: A Neural Language Identification Tool for African Languages","authors":["I Adebara, AR Elmadany, M Abdul-Mageed, AA Inciarte - arXiv preprint arXiv …, 2022"],"snippet":"Language identification (LID) is a crucial precursor for NLP, especially for mining web data. Problematically, most of the world's $7000$+ languages today are not covered by LID technologies. We address this pressing issue for Africa by …","url":["https://arxiv.org/pdf/2210.11744"]}
-{"year":"2022","title":"AfroLM: A Self-Active Learning-based Multilingual Pretrained Language Model for 23 African Languages","authors":["BFP Dossou, AL Tonja, O Yousuf, S Osei, A Oppong… - arXiv preprint arXiv …, 2022"],"snippet":"In recent years, multilingual pre-trained language models have gained prominence due to their remarkable performance on numerous downstream Natural Language Processing tasks (NLP). However, pre-training these large multilingual language …","url":["https://arxiv.org/pdf/2211.03263"]}
-{"year":"2022","title":"AI Personification: Estimating the Personality of Language Models","authors":["SR Karra, S Nguyen, T Tulabandhula - arXiv preprint arXiv:2204.12000, 2022"],"snippet":"… GPT-3 was pretrained on an open-source dataset called Common Crawl, and other text corpora from sources such as Wikipedia (a popular online encyclopedia). TransformerXL: TransformerXL is a transformer-based language model capable of …","url":["https://arxiv.org/pdf/2204.12000"]}
-{"year":"2022","title":"AI WITH ALIEN CONTENT AND ALIEN METASEMANTICS","authors":["H Cappelen, J Dever"],"snippet":"… by the Common Crawl archiving service. Give the role that the Common Crawl database plays in the training of GPT-3, maybe the Common Crawl … in some way we can’t fully comprehend) by the way in which Common Crawl extracts and stores …","url":["https://hermancappelen.net/docs/AIAlienMetasemantics.pdf"]}
-{"year":"2022","title":"AI-based Structured Web Data Extraction","authors":["J Joneš - 2022"],"snippet":"In this thesis, we explore current approaches for automatic web data extraction, define their limitations, and aim to overcome them. We propose a deep learning model to extract structured data from graph and visual representations of web pages …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/174143/120418601.pdf?sequence=1"]}
-{"year":"2022","title":"AI-supported Natural Language Processing in project management–capabilities and research agenda","authors":["H NUHN, A OSWALD, A FLORE, R LANG"],"snippet":"AI-based natural language processing (NLP) models show remarkable performance in tasks like question answering or text generation in general. We argue that recent NLP-AI models will play a major role in the transformation of our societies, an …","url":["https://www.researchgate.net/profile/Helge-Nuhn/publication/361439333_AI-supported_Natural_Language_Processing_in_project_management_-capabilities_and_research_agenda/links/62b1979189e4f1160c8fde4d/AI-supported-Natural-Language-Processing-in-project-management-capabilities-and-research-agenda.pdf"]}
-{"year":"2022","title":"ALEXSIS-PT: A New Resource for Portuguese Lexical Simplification","authors":["K North, M Zampieri, T Ranasinghe - arXiv preprint arXiv:2209.09034, 2022"],"snippet":"Lexical simplification (LS) is the task of automatically replacing complex words for easier ones making texts more accessible to various target populations (eg individuals with low literacy, individuals with learning disabilities, second language …","url":["https://arxiv.org/pdf/2209.09034"]}
-{"year":"2022","title":"Algal bloom monitoring using multi-spectral satellite data","authors":["D Grendaitė, L Petkevičius - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148380852/148380852.pdf"]}
-{"year":"2022","title":"Aligning Word Vectors on Low-Resource Languages with Wiktionary","authors":["M Izbicki - Proceedings of the Fifth Workshop on Technologies for …, 2022"],"snippet":"… these languages are of particular interest to the Wiktionary community for their historical importance, and thus have a lot of entries; but their historical nature also means there are few webpages written in these languages, and so the word vectors …","url":["https://aclanthology.org/2022.loresmt-1.14.pdf"]}
-{"year":"2022","title":"An Analysis of Social Biases Present in BERT Variants Across Multiple Languages","authors":["A Milios, P BehnamGhader - arXiv preprint arXiv:2211.14402, 2022"],"snippet":"… GreekBERT [15] is trained on the Greek Wikipedia, the Greek portion of Oscar [16] (a filtered and cleaned multilingual version of the Common Crawl dataset), and the Greek portion of the European Parliament Proceedings Parallel Corpus [17] …","url":["https://arxiv.org/pdf/2211.14402"]}
-{"year":"2022","title":"An Approach to Generate Realistic HTTP Parameters for Application Layer Deception","authors":["M Sahin, C Hébert, R Cabrera Lozoya - International Conference on Applied …, 2022"],"snippet":"… While the names of the honey HTML elements are ideally chosen by the user, authors also implement a suggestion tool based on a Markov model of URLs gathered from the Common Crawl [2] dataset. However, the paper does not provide …","url":["https://link.springer.com/chapter/10.1007/978-3-031-09234-3_17"]}
-{"year":"2022","title":"An Automatic Speech Recognition System for Bengali Language based on Wav2Vec2 and Transfer Learning","authors":["TT Showrav - arXiv preprint arXiv:2209.08119, 2022"],"snippet":"An independent, automated method of decoding and transcribing oral speech is known as automatic speech recognition (ASR). A typical ASR system extracts featured from audio recordings or streams and run one or more algorithms to map …","url":["https://arxiv.org/pdf/2209.08119"]}
-{"year":"2022","title":"An empirical study of the impact of log parsers on the performance of log-based anomaly detection","authors":["Y Fu, M Yan, Z Xu, X Xia, X Zhang, D Yang - Empirical Software Engineering, 2023"],"snippet":"… The word vectors are pre-trained on the Common Crawl Corpus dataset, and the dimension of word vectors is 300. Secondly, it uses the TF-IDF weight to sum up all word vectors in a log event to generate the log event vector. At the same time, the …","url":["https://link.springer.com/article/10.1007/s10664-022-10214-6"]}
-{"year":"2022","title":"An Empirical Study on the Fairness of Pre-trained Word Embeddings","authors":["E Sesari, M Hort, F Sarro - 2022"],"snippet":"… from 42 billion and 840 billion tokens of Common Crawl corpus. Pre-trained embeddings trained on … + UMBCWeb Base + statmt.org News and 600 billion tokens from Common Crawl. … Also according to these data, we can infer that …","url":["https://discovery.ucl.ac.uk/id/eprint/10149529/1/ACL___Word_Embedding_Bias.pdf"]}
-{"year":"2022","title":"An Ensemble Approach to Acronym Extraction using Transformers","authors":["P Sharma, H Saadany, L Zilio, D Kanojia, C Orasan - 2022"],"snippet":"… 2019) is a multilingual contextualised Language Model (LM) pre-trained on filtered CommonCrawl data from 100+ languages. Each … feed-forward hidden states, 8 heads; and is pre-trained on CommonCrawl data in over 100 languages …","url":["https://dipteshkanojia.github.io/files/sdu-ST-aaai-2022-acronym.pdf"]}
-{"year":"2022","title":"An ensemble multilingual model for toxic comment classification","authors":["G Xie - … Conference on Algorithms, Microchips and Network …, 2022"],"snippet":"… Unlabeled text in 100 languages is extracted from CommonCrawl datasets, totaling 2.5TB of text. It is trained in a RoBERTa fashion, that is, only using the MLM objective. XLM-R is a transformer-based multilingual masked language model pre-trained …","url":["https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12176/121761P/An-ensemble-multilingual-model-for-toxic-comment-classification/10.1117/12.2636419.full"]}
-{"year":"2022","title":"An Ensemble of Arabic Transformer-based Models for Arabic Sentiment Analysis","authors":["I El Karfi, S El Fkihi"],"snippet":"In recent years, sentiment analysis has gained momentum as a research area. This task aims at identifying the opinion that is expressed in a subjective statement. An opinion is a subjective expression describing personal thoughts and feelings. These …","url":["https://search.proquest.com/openview/ad34f3c57aa402f7589c6884ff93cbaf/1?pq-origsite=gscholar&cbl=5444811"]}
-{"year":"2022","title":"An ensemble transformer-based model for Arabic sentiment analysis","authors":["O Mohamed, AM Kassem, A Ashraf, S Jamal… - Social Network Analysis and …, 2023"],"snippet":"… XLM-R is a multilingual MLM trained on 2.5 TB of clean Common Crawl data in 100 languages. It provides a solid improvement over previous multilingual models such as mBERT. It performs well in various tasks such as classification, sequence …","url":["https://link.springer.com/article/10.1007/s13278-022-01009-0"]}
-{"year":"2022","title":"An image and text-based multimodal model for detecting fake news in OSN's","authors":["SK Uppada, P Patel - Journal of Intelligent Information Systems, 2022"],"snippet":"… RoBERTa is pre-trained on Books Corpus and English Wikipedia; in addition to this dataset, RoBERTa is trained on CommonCrawl, Web text corpus, and stories from Common Crawl datasets. A dense output layer with softmax as an activation …","url":["https://link.springer.com/article/10.1007/s10844-022-00764-y"]}
-{"year":"2022","title":"An Information Minimization Based Contrastive Learning Model for Unsupervised Sentence Embeddings Learning","authors":["S Chen, J Zhou, Y Sun, L He - arXiv preprint arXiv:2209.10951, 2022"],"snippet":"Unsupervised sentence embeddings learning has been recently dominated by contrastive learning methods (eg, SimCSE), which keep positive pairs similar and push negative pairs apart. The contrast operation aims to keep as much information …","url":["https://arxiv.org/pdf/2209.10951"]}
-{"year":"2022","title":"An integrated data framework for policy guidance during the coronavirus pandemic: Towards real-time decision support for economic policymakers","authors":["JO Dörr, J Kinne, D Lenz, G Licht, P Winker - PloS one, 2022"],"snippet":"… Specifically, XLM-RoBERTa has been trained on more than two terabyte of filtered common-crawl data [39]. It has acquired its basic language understanding using the masked language model approach [40], ie given a sequence of text—eg a …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0263898"]}
-{"year":"2022","title":"An Interactive Visual Demo of Bias Mitigation Techniques for Word Representations From a Geometric Perspective","authors":["A Rathore, S Dev, V Srikumar, JM Phillips, Y Zheng… - NeurIPS 2021 Competitions …, 2022"],"snippet":"Abstract Language representations are known to encode and propagate biases, ie, stereotypical associations between words or groups of words that may cause representational harm. In this demo, we utilize interactive visualization to increase …","url":["https://proceedings.mlr.press/v176/rathore22a/rathore22a.pdf"]}
-{"year":"2022","title":"An Interpretable Word Sense Classifier for Human Explainable Chatbot","authors":["RK Yadav, L Jiao, OC Granmo, M Goodwin - International Conference on Agents and …, 2022"],"snippet":"… The three models employ static embedding obtained from two sources, CommonCrawl and Base, and are trained using 1 layer neural network … This is because of the enriched information in CommonCrawl in comparison to Base word …","url":["https://link.springer.com/chapter/10.1007/978-3-031-10161-8_13"]}
-{"year":"2022","title":"An Unsupervised Approach to Genuine Health Information Retrieval Based on Scientific Evidence","authors":["R Upadhyay, G Pasi, M Viviani - International Conference on Web Information …, 2022"],"snippet":"… The original dataset is constituted by CommonCrawl news, Footnote 21 sampled from January, 1st 2020 to April 30th, 2020, which contains health-related news articles from all over the world. For our experiments, given the large volume of the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20891-1_10"]}
-{"year":"2022","title":"Analysing Environmental Narratives Computationally","authors":["RS Purves, O Koblet, B Adams - Unlocking Environmental Narratives: Towards …, 2022"],"snippet":"This book’s origins lie in a desire to showcase, through an interdisciplinary approach, the potential for computational methods in analysing text that describes the environment. Our argument is that these computational methods need not be …","url":["https://ubiquitypress.com/site/chapters/10.5334/bcs.c/download/5953/"]}
-{"year":"2022","title":"Analysis and Application of Language Models to Human-Generated Textual Content","authors":["M Di Giovanni - 2022"],"snippet":"… The authors trained the model on corpora of different sizes; the larger includes 42 billion tokens of web data from Common Crawl, tokenized and lowercased. A clear correlation between corpus size and performance is observed for syntactic tasks but …","url":["http://amsdottorato.unibo.it/10057/1/Tesi%20con%20Frontespizio.pdf"]}
-{"year":"2022","title":"Analysis and control of online interactions through neural natural language processing","authors":["L Laugier - 2022"],"snippet":"Natural Language Processing is motivated by applications where computers should gain a semantic and syntactic understanding of human language. Recently, the field has been impacted by a paradigm shift. Deep learning architectures coupled with …","url":["https://theses.hal.science/tel-03884481/document"]}
-{"year":"2022","title":"Analysis of Scientific Literature of LDOW Workshops: A Scientometric and NLP approach","authors":["S Shekarpour"],"snippet":"This paper contributes to compiling and publishing a structured dataset from the scientific literature of the Linked Data on the Web (LDOW) workshop series. This workshop was the primary venue for publishing the frontier topics related to …","url":["https://www.researchgate.net/profile/Enayat-Rajabi/publication/358973156_Analysis_of_Scientific_Literature_of_LDOW_Workshops_A_Scientometric_and_NLP_approach/links/62201e29c4c4fa27cd236da6/Analysis-of-Scientific-Literature-of-LDOW-Workshops-A-Scientometric-and-NLP-approach.pdf"]}
-{"year":"2022","title":"Analysis of Semantic Shift Before and After COVID-19 in Spanish Diachronic Word Embeddings","authors":["ER Betancourt, EC Murillo - 2022 XVLIII Latin American Computer Conference …, 2022"],"snippet":"… Como origen de los datos se usó el proyecto CommonCrawl (https://commoncrawl.org/), el cual regularmente recolecta documentos de … Se descargaron desde CommonCrawl los documentos correspondientes a la semana 51 del 2018 y la …","url":["https://ieeexplore.ieee.org/abstract/document/9959896/"]}
-{"year":"2022","title":"Analysis of the Full-Size Russian Corpus of Internet Drug Reviews with Complex NER Labeling Using Deep Learning Neural Networks and Language Models","authors":["A Sboev, S Sboeva, I Moloshnikov, A Gryaznov… - Applied Sciences, 2022"],"snippet":"The paper presents the full-size Russian corpus of Internet users’ reviews on medicines with complex named entity recognition (NER) labeling of pharmaceutically relevant entities. We evaluate the accuracy levels reached on this …","url":["https://www.mdpi.com/2076-3417/12/1/491/pdf"]}
-{"year":"2022","title":"Analysis of the Semantic Vector Space Induced by a Neural Language Model and a Corpus","authors":["X Chen, J Hůla, A Dvořák - 2022"],"snippet":"… The language model that we use for this study is XLM-RoBERTa [1], which is a transformer-based model pre-trained on a large corpus (2.5TB of filtered CommonCrawl data) in a self-supervised fashion. The model uses a tokenizer based on …","url":["http://ceur-ws.org/Vol-3226/paper12.pdf"]}
-{"year":"2022","title":"Analysis of Word-level Embeddings for Indic Languages on AI4Bharat-IndicNLP Corpora","authors":["D Goswami, S Malviya, R Mishra, US Tiwary - 2021 IEEE 8th Uttar Pradesh Section …, 2021"],"snippet":"This paper presents the analysis of non-contextual word embeddings trained on AI4Bharat-IndicNLP corpus containing 2.7 billion words covering 10 Indian languages. We share the pre-trained embeddings for research and development in …","url":["https://ieeexplore.ieee.org/abstract/document/9667615/"]}
-{"year":"2022","title":"Analytical Engines With Context-Rich Processing: Towards Efficient Next-Generation Analytics","authors":["V Sanca, A Ailamaki - arXiv preprint arXiv:2212.07517, 2022"],"snippet":"As modern data pipelines continue to collect, produce, and store a variety of data formats, extracting and combining value from traditional and context-rich sources such as strings, text, video, audio, and logs becomes a manual process where such …","url":["https://arxiv.org/pdf/2212.07517"]}
-{"year":"2022","title":"Analyzing Antisemitism and Islamophobia using a Lexicon-based Approach","authors":["M Ali, S Zannettou - Workshop Proceedings of the 16th International AAAI …, 2022"],"snippet":"The spread of Antisemitic and Islamophobic content in a longstanding problem, in particular within fringe Web communities. In this work, we attempt to analyze the spread of Antisemitic and Islamophobic content on 4chan’s Politically Incorrect …","url":["https://workshop-proceedings.icwsm.org/pdf/2022_61.pdf"]}
-{"year":"2022","title":"Analyzing Gender Representation in Multilingual Models","authors":["H Gonen, S Ravfogel, Y Goldberg - arXiv preprint arXiv:2204.09168, 2022"],"snippet":"Multilingual language models were shown to allow for nontrivial transfer across scripts and languages. In this work, we study the structure of the internal representations that enable this transfer. We focus on the representation of gender …","url":["https://arxiv.org/pdf/2204.09168"]}
-{"year":"2022","title":"Analyzing the Mono-and Cross-Lingual Pretraining Dynamics of Multilingual Language Models","authors":["T Blevins, H Gonen, L Zettlemoyer - arXiv preprint arXiv:2205.11758, 2022"],"snippet":"… This dataset consists of filtered Common Crawl data for 100 languages, with a wide range of data quantities ranging from 0.1 GiB for languages like Xhosa and Scottish Gaelic to over 300 Gib for English. As with XLM-R, we train on CC100 for 1.5M …","url":["https://arxiv.org/pdf/2205.11758"]}
-{"year":"2022","title":"Analyzing the Web: Are Top Websites Lists a Good Choice for Research?","authors":["T Alby, R Jäschke - International Conference on Theory and Practice of …, 2022"],"snippet":"… We present a heuristic-driven alternative based on the Common Crawl host-level web graph while also taking language-… the Common Crawl graph due to 94.9% of hosts in the Common Crawl graph being unknown to the other data sources. Instead …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16802-4_2"]}
-{"year":"2022","title":"ANNA: Enhanced Language Representation for Question Answering","authors":["C Jun, H Jang, M Sim, H Kim, J Choi, K Min, K Bae - arXiv preprint arXiv:2203.14507, 2022"],"snippet":"… of 127,490 wordpieces that are extracted from the English Common Crawl corpus (Raffel et al.… corpora such as a ColossalCleaned version of Common Crawl (C4) corpus (Raffel et al.… for the deletion of documents written in non-English words in …","url":["https://arxiv.org/pdf/2203.14507"]}
-{"year":"2022","title":"Annotation Projection-based Dependency Parser Development for Nepali","authors":["P Rai, S Chatterji - Transactions on Asian and Low-Resource Language …, 2022"],"snippet":"Building computational resources and tools for the under-resourced languages is strenuous for any Natural Language Processing (NLP) task. This paper presents the first dependency parser for an under-resourced Indian language, Nepali. A …","url":["https://dl.acm.org/doi/pdf/10.1145/3542696"]}
-{"year":"2022","title":"Answering Binary Causal Questions Using Role-oriented Concept Embedding","authors":["H Kayesh, MS Islam, J Wang - IEEE Transactions on Artificial Intelligence, 2022"],"snippet":"Answering binary causal questions is a challenging task, and it requires rich background knowledge to answer such questions. Extracting useful causal features from the background knowledge base and applying them effectively in a model is a …","url":["https://ieeexplore.ieee.org/abstract/document/9878044/"]}
-{"year":"2022","title":"Answering Consumer Health Questions on the Web","authors":["A Vakili Tahami - 2022"],"snippet":"… In this work, we implement a document filtering technique based on topic-sensitive PageRank that uses a web graph of the hosts in common crawl. We develop a new passage extraction technique that performs query-based contextualized sentence …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/18979/VakiliTahami_Amir.pdf?sequence=3&isAllowed=y"]}
-{"year":"2022","title":"APIRO: A Framework for Automated Security Tools API Recommendation","authors":["ZT Sworna, C Islam, MA Babar - arXiv preprint arXiv:2201.07959, 2022"],"snippet":"… Moreover, for augmenting data with the same Aug and same action, we propose to use a wide variety of data sources, ie, thesaurus and embedding (eg, PPDB, GloVe Common Crawl). Hence, a set of 𝛼 number of Data Augmentation …","url":["https://arxiv.org/pdf/2201.07959"]}
-{"year":"2022","title":"AppClassNet: a commercial-grade dataset for application identification research","authors":["C Wang, A Finamore, L Yang, K Fauvel, D Rossi - ACM SIGCOMM Computer …, 2022"],"snippet":"… Similarly, in the NLP field the Common Crawl [2] project gathered several hundreds of billions of text tokens. This is in stark contrast with the networking field where a commonly identified limit to AI deployment is the lack of publicly available …","url":["https://dl.acm.org/doi/abs/10.1145/3561954.3561958"]}
-{"year":"2022","title":"Appendix C: Data Augmentation and Pretraining to Improve Neural Headline Generation in Low-Resource Setting","authors":["M Martinc, S Montariol, L Pivovarova, E Zosa - Cross-Lingual Embeddings for Less …"],"snippet":"We tackle the problem of neural headline generation in a low-resource setting, where only limited amount of data is available to train a model. We compare the ideal high-resource scenario on English with results obtained on a smaller subset of …","url":["http://embeddia.eu/wp-content/uploads/EMBEDDIA-D57-FinalEvaluationReportOnTextGeneration-T54-submitted.pdf#page=54"]}
-{"year":"2022","title":"Application of convolutional deep neural network for human detection in through the wall radar signals","authors":["D Navakauskas, J Skirelis, E Šabanovič, M Kazlauskas… - DAMSS 2022: 13th …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:148962697/148962697.pdf"]}
-{"year":"2022","title":"Application of neural network language models based on distributive semantics for ontological modeling of the domain","authors":["MG Shishaev, VV Dikovitsky, VK Pimeshkov - Journal of Physics: Conference Series, 2022"],"snippet":"… Common Crawl'. The network architecture included 5 layers with a 631-500-350-250-1503 funnel, the ReLU activation function was used, and training was carried out in 15 epochs. The results of testing the resulting model on verification data are shown in …","url":["https://iopscience.iop.org/article/10.1088/1742-6596/2182/1/012033/pdf"]}
-{"year":"2022","title":"Applications of machine learning for COVID-19 misinformation: a systematic review","authors":["AR Sanaullah, A Das, A Das, MA Kabir, K Shu - Social Network Analysis and Mining, 2022"],"snippet":"… (2021) had chosen crawl-300d-2M4 embedding Footnote 4 , a 2 million word vectors which are trained with subword information on Common Crawl (… Footnote 5 which is trained on Common Crawl consisting of 2 million words. Hossain et al. (2020) …","url":["https://link.springer.com/article/10.1007/s13278-022-00921-9"]}
-{"year":"2022","title":"Applying Text Analytics to Insider Risk Analysis: A Case Study on Keyword Generation","authors":["C Gardner, WR Clacyomb - 2022 IEEE International Carnahan Conference on …, 2022"],"snippet":"Recent advancements in text analytics demonstrate significant gains in many natural language processing tasks, taking advantage of newer neural network architectures and transfer learning. In this article, we present findings from a literature review and …","url":["https://ieeexplore.ieee.org/abstract/document/9896598/"]}
-{"year":"2022","title":"Approaching what and how people with mental disorders communicate in social media–Introducing a multi-channel representation","authors":["ME Aragón, AP López-Monroy, LC González… - Neural Computing and …, 2022"],"snippet":"… This model was pre-trained with high-dimensional corpora from Twitter, Common Crawl, and Wikipedia. GloVe presents a lower dimensionality in their word vectors, ranging between 50 and 300 dimensions. GloVe pre-trained with information from …","url":["https://link.springer.com/article/10.1007/s00521-022-07569-8"]}
-{"year":"2022","title":"Arabic abstractive text summarization using RNN-based and transformer-based architectures","authors":["M Bani-Almarjeh, MB Kurdy - Information Processing & Management, 2023"],"snippet":"… To build our dataset, we used Common Crawl to download the archived … Common Crawl are to make it easy to rebuild our dataset by other researchers and to comply with the copyrights of the respective crawled websites. The data are …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322003284"]}
-{"year":"2022","title":"Arabic Fake News Detection: A Fact Checking Based Deep Learning Approach","authors":["F Harrag, MK Djahli - Transactions on Asian and Low-Resource Language …, 2022"],"snippet":"Fake news stories can polarize society, particularly during political events. They undermine confidence in the media in general. Current NLP systems are still lacking the ability to properly interpret and classify Arabic fake news. Given the high stakes …","url":["https://dl.acm.org/doi/abs/10.1145/3501401"]}
-{"year":"2022","title":"AraNPCC: The Arabic Newspaper COVID-19 Corpus","authors":["A Al-Thubaity, S Alkhereyf, A Bahanshal - Politics"],"snippet":"This paper introduces a corpus for Arabic newspapers during COVID-19: AraNPCC. The AraNPCC corpus covers 2019 until 2021 via automatically-collected data from 12 Arab countries. It comprises more than 2 billion words and 7.2 million texts …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/OSACT/pdf/2022.osact-1.4.pdf"]}
-{"year":"2022","title":"ArSphere: Arabic word vectors embedded in a polar sphere","authors":["S Rizkallah, AF Atiya, S Shaheen, HED Mahgoub - International Journal of Speech …, 2022"],"snippet":"Word embeddings mean the mapping of words into vectors in an N-dimensional space. ArSphere: is an approach that designs word embeddings for the Arabic language. This approach overcomes one of the shortcomings of word embeddings (for …","url":["https://link.springer.com/article/10.1007/s10772-022-09966-9"]}
-{"year":"2022","title":"Artificial intelligence and the affective labour of understanding: The intimate moderation of a language model","authors":["C Perrotta, N Selwyn, C Ewin - New Media & Society, 2022"],"snippet":"Interest in artificial intelligence (AI) language models has grown considerably following the release of ‘generative pre-trained transformer’ (GPT). Framing AI as an extractive technology, this article details how GPT harnesses human labour and …","url":["https://journals.sagepub.com/doi/abs/10.1177/14614448221075296"]}
-{"year":"2022","title":"Artificial Intelligence, Deepfakes, and Disinformation","authors":["TC HELMUS - 2022"],"snippet":"CAI Content Authenticity Initiative GAN generative adversarial network GPT-3 Generative Pre-Trained Transformer 3 OSINT open-source intelligence technique in American society: increasing disagreement in evaluations of facts and analytical …","url":["https://www.rand.org/content/dam/rand/pubs/perspectives/PEA1000/PEA1043-1/RAND_PEA1043-1.pdf"]}
-{"year":"2022","title":"Artificial Intelligence: A Medium that Hides Its Nature","authors":["A Huxor - Artificial Intelligence and Its Discontents, 2022"],"snippet":"… This technology builds a vast language model based on a corpus of many written texts, drawn from the Internet which themselves previously created by humans, including texts garnered by crawling the web and made available at Common Crawl …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88615-8_6"]}
-{"year":"2022","title":"Artificial Intelligent Context-Aware Machine-Learning Tool to Detect Adverse Drug Events from Social Media Platforms","authors":["D Roosan, AV Law, MR Roosan, Y Li - Journal of Medical Toxicology, 2022"],"snippet":"… We selected FastText embeddings with 300-dimensional vectors and 3 million vocabularies trained with subword information on Common Crawl with 600 Billion tokens to capture the context of our corpus. We used fastText, which has pre-trained …","url":["https://link.springer.com/article/10.1007/s13181-022-00906-2"]}
-{"year":"2022","title":"Artificial Knowing Otherwise","authors":["O Keyes, K Creel - Feminist Philosophy Quarterly, 2022"],"snippet":"… Machine learning’s reliance on free, large-scale resources (some prominent examples include Flickr content for facial and object recognition, Wikipedia for text analysis and image classification, and CommonCrawl for web pages) means that …","url":["https://ojs.lib.uwo.ca/index.php/fpq/article/download/14313/12138"]}
-{"year":"2022","title":"Asking Clarifying Questions: To benefit or to disturb users in Web search?","authors":["J Zou, A Sun, C Long, M Aliannejadi, E Kanoulas - Information Processing & …, 2023"],"snippet":"Modern information-seeking systems are becoming more interactive, mainly through asking Clarifying Questions (CQs) to refine users’ information needs. System-generated CQs may be of different qualities. However, the impact of asking multiple CQs of …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322002771"]}
-{"year":"2022","title":"Assembly Models for SimpleText Task 2: Results from Wuhan University Research Group","authors":["J Huang, J Mao - 2022"],"snippet":"… The pre-trained embedding we choose is trained on Common Crawl, which is from the public domain. There can be pre-trained word embeddings for technology and medical fields, as are the domains covered by the task corpus. Thus, one work …","url":["http://ceur-ws.org/Vol-3180/paper-239.pdf"]}
-{"year":"2022","title":"Assessment of Massively Multilingual Sentiment Classifiers","authors":["K Rajda, Ł Augustyniak, P Gramacki, M Gruza… - arXiv preprint arXiv …, 2022"],"snippet":"… We also included models trained on multilingual corpus like Wikipedia (Wiki) or Common Crawl (CC) as well as models trained with the use of parallel datasets. Selected models differ in size - from LASER with 52M parameters to LaBSE with …","url":["https://arxiv.org/pdf/2204.04937"]}
-{"year":"2022","title":"Assisting Children with Special Needs in Their Daily Interaction with Other People","authors":["M Allouche - 2022"],"snippet":"Children and adults with special needs may find it difficult to recognize danger and threats as well as socially complex situations. They are thus at risk of becoming victims of exploitation and violence. In addition, they may find themselves …","url":["http://azariaa.com/Content/Theses/PhD_MeravA.pdf"]}
-{"year":"2022","title":"ASurvey ON GPT-3","authors":["M Zong, B Krishnamachari - 2022"],"snippet":"This paper provides an introductory survey to GPT-3. We cover some of the historical development behind this technology, some of the key features of GPT-3, and discuss the machine learning model and the datasets used. We survey both academic and …","url":["https://anrg.usc.edu/www/wp-content/uploads/2022/12/A_Survey_On_GPT3.pdf"]}
-{"year":"2022","title":"Attack or Block? Repertoires of Digital Censorship in Autocracies","authors":["L Kawerau, NB Weidmann, A Dainotti - Journal of Information Technology & Politics, 2022"],"snippet":"… When a given host is visited by CommonCrawl multiple times and has the same IP address in two adjacent observations, we assume that the host had the same address on every day between those two observations. We call this period a “stable …","url":["https://www.tandfonline.com/doi/abs/10.1080/19331681.2022.2037118"]}
-{"year":"2022","title":"Attention Fusion: a light yet efficient late fusion mechanism for task adaptation in NLU","authors":["J Cao, CS Prakash, W Hamza, AI Amazon"],"snippet":"Fine-tuning a pre-trained language model using annotated data has become the de-facto standard for adapting general-purpose pretrained models like BERT to downstream tasks. However, given the trend of larger pretrained models, fine-tuning these …","url":["https://assets.amazon.science/99/58/7342d03044d7a4f83324191c4bd3/attention-fusion-a-light-yet-efficient-late-fusion-mechanism-for-task-adaptation-in-nlu.pdf"]}
-{"year":"2022","title":"Attention-Based Bi-LSTM Network for Abusive Language Detection","authors":["KB Nelatoori, HB Kommanti - IETE Journal of Research, 2022"],"snippet":"… These GloVe embeddings are trained on Common Crawl which contains 42 billion tokens and a Twitter corpus with 2 billion tweets. GloVe trained on Twitter contains 25, 50, 100 and 200-dimensional word embeddings with 1.2 million …","url":["https://www.tandfonline.com/doi/abs/10.1080/03772063.2022.2034534"]}
-{"year":"2022","title":"Attention-Based Models for Classifying Small Data Sets Using Community-Engaged Research Protocols: Classification System Development and Validation Pilot …","authors":["BJ Ferrell, SE Raskin, EB Zimmerman, DH Timberline… - JMIR Formative Research, 2022"],"snippet":"Background Community-engaged research (CEnR) is a research approach in which scholars partner with community organizations or individuals with whom they share an interest in the study topic, typically with the goal of supporting that community’s …","url":["https://formative.jmir.org/2022/9/e32460"]}
-{"year":"2022","title":"Attribute Representation in Neural Language Models","authors":["D Yu - 2022"],"snippet":"… Data and preprocessing To train our multilingual model, we use the CommonCrawl dataset from the CoNLL 2017 shared task [96] to obtain monolingual plain text in various languages. To represent words across different languages in a …","url":["https://escholarship.org/content/qt2j78k662/qt2j78k662.pdf"]}
-{"year":"2022","title":"Autoblog 2021: The Importance of Language Models for Spontaneous Lecture Speech","authors":["A Hernandez, P Klumpp, B Das, A Maier, SH Yang - International Conference on Text …, 2022","SH Yang - Text, Speech, and Dialogue: 25th International …, 2022"],"snippet":"… This corpus contains text from news articles, European parliament speeches, and text from Common Crawl [15]. The transcripts from the training set of TED-LIUM 3 [7] based on 2,351 TED talks are used to build a lecture-style LM. While this model is …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=qaiJEAAAQBAJ&oi=fnd&pg=PA289&dq=commoncrawl&ots=Nf2wRagpV3&sig=wYalqpKDbKnCbxHtuBrI94UFe2Q","https://link.springer.com/chapter/10.1007/978-3-031-16270-1_24"]}
-{"year":"2022","title":"Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?","authors":["R Dong, Z Qi, L Zhang, J Zhang, J Sun, Z Ge, L Yi… - arXiv preprint arXiv …, 2022"],"snippet":"The success of deep learning heavily relies on large-scale data with comprehensive labels, which is more expensive and time-consuming to fetch in 3D compared to 2D images or natural languages. This promotes the potential of utilizing models …","url":["https://arxiv.org/pdf/2212.08320"]}
-{"year":"2022","title":"Automated Essay Scoring using Transformers","authors":["K Gupta - arXiv preprint arXiv:2210.12809, 2022"],"snippet":"Despite being investigated for over five decades, the task of automated essay scoring continues to draw a lot of attention in the NLP community, in part because of its commercial and educational values as well as the associated research …","url":["https://arxiv.org/pdf/2210.12809"]}
-{"year":"2022","title":"Automated Fake News Detection using cross-checking with reliable sources","authors":["Z Ghadiri, M Ranjbar, F Ghanbarnejad, S Raeisi - arXiv preprint arXiv:2201.00083, 2022"],"snippet":"… We trained this word embedding on Common Crawl and Wikipedia [9]. For two semantically close tweets, their embedding vector should be relatively close. To find the distance between two tweets, we use the cosine between their corresponding vectors. …","url":["https://arxiv.org/pdf/2201.00083"]}
-{"year":"2022","title":"AUTOMATED GENERATION OF MANDARIN EDUCATIONAL MULTIMEDIA CONTENT FROM EXISTING ENGLISH CONTENT","authors":["MJ Israel, A Qin, Y Zhang, J Xin, N Shaghaghi - ICERI2022 Proceedings, 2022"],"snippet":"With the advancement of digital technology, multimedia contents have proliferated in recent years. Large collections of such multimedia content are accrued both in public on the internet and in private enterprise settings. However, the vast majority of …","url":["https://library.iated.org/view/ISRAEL2022AUT"]}
-{"year":"2022","title":"Automated Identification of Toxic Code Reviews: How Far Can We Go?","authors":["J Sarker, AK Turzo, M Dong, A Bosu - arXiv preprint arXiv:2202.13056, 2022"],"snippet":"Toxic conversations during software development interactions may have serious repercussions on a Free and Open Source Software (FOSS) development project. For example, victims of toxic conversations may become afraid to express …","url":["https://arxiv.org/pdf/2202.13056"]}
-{"year":"2022","title":"AUTOMATED LABELING OF MITRE ATT&CK TACTICS AND TECHNIQUES IN MALWARE THREAT REPORTS","authors":["E Domschot - 2022"],"snippet":"… Initially, we used the common crawl GloVe embedding, which was trained over 42 billion tokens, with a 300 dimensional vector space [22]. It was then used as the embedding layer of the BiLSTM model. The results (method GloVe Pretrained) can …","url":["https://search.proquest.com/openview/339b13e8f859e794cefe03c9ef7628d3/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"Automated text-level semantic markers of Alzheimer's disease","authors":["C Sanz, F Carrillo, A Slachevsky, G Forno… - Alzheimer's & Dementia …, 2022"],"snippet":"Methods Combining statistical and machine learning analyses of natural speech data, we aimed to discriminate ADD patients from healthy controls (HCs) based on automated measures of domains typically affected in ADD: semantic granularity (coarseness …","url":["https://alz-journals.onlinelibrary.wiley.com/doi/pdf/10.1002/dad2.12276"]}
-{"year":"2022","title":"Automatic and Manual Detection of Generated News: Case Study, Limitations and Challenges","authors":["J Bogaert, A Descampe, MC de Marneffe, FX Standaert - 2022"],"snippet":"In this paper, we study the exploitation of language generation models for disinformation purposes from two viewpoints. Quantitatively, we argue that language models hardly deal with domain adaptation (ie, the ability to generate text on topics …","url":["https://perso.uclouvain.be/fstandae/PUBLIS/277.pdf"]}
-{"year":"2022","title":"Automatic Generation and Detection of Motivational-Interviewing-Style Reflections for Smoking Cessation Therapeutic Conversations Using Transformer-based …","authors":["I Ahmed - 2022"],"snippet":"… The GPT-3 model [9] has 175 billion parameters and is trained on 499GB of text data from multiple datasets: Common Crawl from 2016-2019 [48], WebText, Books1 and Books2 (collection of books and movie script text data) [49], and English-language …","url":["https://www.eecg.utoronto.ca/~jayar/download/ahmed_imtihan_202201_masc_thesis.pdf"]}
-{"year":"2022","title":"Automatic generation of medical reports from chest X-rays in Czech","authors":["L Chaloupský - 2022"],"snippet":"This thesis deals with the problem of automatic generation of medical reports in the Czech language based on the input chest X-ray images using deep neural networks. The first part deals with the analysis of the problem itself including a comparison of …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/176356/120426657.pdf?sequence=1"]}
-{"year":"2022","title":"Automatic Grammar Correction of Commas in Czech Written Texts: Comparative Study","authors":["J Machura, A Frémund, J Švec - International Conference on Text, Speech, and …, 2022","J Švec"],"snippet":"… We used our own pre-trained model from a collection of web data processed in our web mining tool [reference-hidden], Common Crawl data2 and texts collected from the Czech part of Wikipedia. We followed all the training steps, mentioned in [15] …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16270-1_10","https://www.researchgate.net/profile/Jakub-Machura-2/publication/363599973_Automatic_Grammar_Correction_of_Commas_in_Czech_Written_Texts_Comparative_Study/links/6347f0bdff870c55ce215a4c/Automatic-Grammar-Correction-of-Commas-in-Czech-Written-Texts-Comparative-Study.pdf"]}
-{"year":"2022","title":"Automatic Pull Request Title Generation","authors":["T Zhang, IC Irsan, F Thung, DG Han, D Lo, L Jiang - arXiv preprint arXiv:2206.10430, 2022"],"snippet":"… Unlike BART, T5 was pre-trained with the Colossal Clean Crawled Corpus (C4) dataset, which consists of 750GB of English text from the public Common Crawl web scrape. T5 was reported to achieve state-of-the-art results on many benchmarks …","url":["https://arxiv.org/pdf/2206.10430"]}
-{"year":"2022","title":"Automatic question answering for multiple stakeholders, the epidemic question answering dataset","authors":["TR Goodwin, D Demner-Fushman, K Lo, LL Wang… - Scientific Data, 2022"],"snippet":"… In the end-to-end collection, we also included 265 Reddit threads as well as a subset of the CommonCrawl News Crawl (CCNC) from … e2e/ccns_trec/ contains 114,645 JSON files, each corresponding to an HTML-parsed website included in the …","url":["https://www.nature.com/articles/s41597-022-01533-w"]}
-{"year":"2022","title":"AUTOMATIC ROMANIAN TEXT GENERATION USING GPT-2","authors":["MC BUZEA, Ș TRĂUȘAN, T REBEDEA"],"snippet":"… from Transformers (BLEURT) – a BLEURT checkpoint was used – a self-contained folder that contained a regression model which was tested on several languages, but should work for the 100+ languages of multilingual C4 (a cleaned version of …","url":["https://www.scientificbulletin.upb.ro/rev_docs_arhiva/rez734_186024.pdf"]}
-{"year":"2022","title":"Automatic Term Extraction with Joint Multilingual Learning","authors":["IN Karaman, I Cicekli, G Ercan - 2022 7th International Conference on Computer …, 2022"],"snippet":"Automatic term extraction using deep learning achieves promising results if sufficient training data exists. Unfortunately, some languages may lack these resources in some domains causing poor performance due to under-fitting. In this study, we …","url":["https://ieeexplore.ieee.org/abstract/document/9919455/"]}
-{"year":"2022","title":"Automatic Text Summarization for Moroccan Arabic Dialect Using an Artificial Intelligence Approach","authors":["I Benelallam - … Intelligence: 7th International Conference, CBI 2022 …"],"snippet":"A major advantage of artificial intelligence is its ability to automatically perform tasks at a human-like level quickly; this is needed in many fields, and more particularly in Automatic Text Summarization (ATS). Several advances related to this technique …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=mZxvEAAAQBAJ&oi=fnd&pg=PA158&dq=commoncrawl&ots=R3bP_X-osy&sig=StHLey4LgAHWwHnofHZYygV5YzA"]}
-{"year":"2022","title":"Automatic text summarization of konkani texts using pre-trained word embeddings and deep learning.","authors":["J D'Silva, U Sharma - International Journal of Electrical & Computer …, 2022"],"snippet":"… The models are trained on documents from Common Crawl and Wikipedia to obtain embeddings for words in the languages offered [12], [13]. With Konkani, the number of Konkani language articles is significantly low on Wikipedia compared to …","url":["http://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=20888708&AN=154204023&h=YgeWf2sTl1O%2FMKtu7OeHz%2FHcc2De9w9RwaYA14TSEkzxauPv0vrRqD%2Bdn4LVWiwHi7XNZke8S5Wuv%2BL1wGg8hQ%3D%3D&crl=c"]}
-{"year":"2022","title":"Automating Feedback to Improve Teachers' Effective Use of Instructional Discourse in K-12 Mathematics Classrooms","authors":["A Suresh - 2022"],"snippet":"… In our model, we use the vectors trained on Common Crawl with 840 billion tokens and 300 dimensions. For a given sentence, we identify the GloVe representation for each word in the sentence and compute a mean vector. …","url":["https://search.proquest.com/openview/15e25cc3c1547a2e1390d398d1ea42fd/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"Automating Idea Unit Segmentation and Alignment for Assessing Reading Comprehension via Summary Protocol Analysis","authors":["M Gecchele, H Yamada, T Tokunaga, Y Sawaki…"],"snippet":"In this paper, we approach summary evaluation from an applied linguistics (AL) point of view. We provide computational tools to AL researchers to simplify the process of Idea Unit (IU) segmentation. The IU is a segmentation unit that can …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.498.pdf"]}
-{"year":"2022","title":"Autonomous schema markups based on intelligent computing for search engine optimization","authors":["BUD Abbasi, I Fatima, H Mukhtar, S Khan, A Alhumam… - PeerJ Computer Science, 2022"],"snippet":"With advances in artificial intelligence and semantic technology, search engines are integrating semantics to address complex search queries to improve the results. This requires identification of well-known concepts or entities and their relationship from …","url":["https://peerj.com/articles/cs-1163/"]}
-{"year":"2022","title":"Balancing between holistic and cumulative sentiment classification","authors":["P Agathangelou, I Katakis - Online Social Networks and Media, 2022"],"snippet":"Sentiment analysis is a fast-accelerating discipline that develops algorithms for knowledge discovery from opinionated content. The challenges however, when it comes to analyzing user reviews are plenty. Bad-quality, informal use of language …","url":["https://www.sciencedirect.com/science/article/pii/S2468696422000039"]}
-{"year":"2022","title":"Balancing novelty and appropriateness leads to creative associations in children","authors":["C Rastelli, A Greco, N De Pisapia, C Finocchiaro - 2022"],"snippet":"Creative cognition is conceived as the process whereby something novel and appropriate is generated. However, the contribution of novelty and appropriateness to creativity is far from being understood, especially during developmental age. Here …","url":["https://psyarxiv.com/k5pz3/download?format=pdf"]}
-{"year":"2022","title":"BanglaNLG: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla","authors":["A Bhattacharjee, T Hasan, WU Ahmad, R Shahriyar - arXiv preprint arXiv:2205.11081, 2022"],"snippet":"This work presents BanglaNLG, a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language in the web domain. We aggregate three challenging conditional text …","url":["https://arxiv.org/pdf/2205.11081"]}
-{"year":"2022","title":"Based on billions of words on the internet,< scp> people</scp>=< scp> men</scp","authors":["AH Bailey, A Williams, A Cimpian"],"snippet":"Recent advances have made it possible to precisely measure the extent to which any two words are used in similar contexts. In turn, this measure of similarity in linguistic context also captures the extent to which the concepts being denoted are …","url":["https://ouci.dntb.gov.ua/en/works/733X5j07/"]}
-{"year":"2022","title":"Being Polite: Modeling Politeness Variation in a Personalized Dialog Agent","authors":["M Firdaus, A Shandilya, A Ekbal, P Bhattacharyya - IEEE Transactions on …, 2022"],"snippet":"… The word embedding dimension is set as 300 for which we use FastText Embeddings [52] pretrained on the common crawl. We apply 0.5 dropout rate [53] to the layer before softmax. All the models are trained on a single NVIDIA 1080Ti GPU. …","url":["https://ieeexplore.ieee.org/abstract/document/9801557/"]}
-{"year":"2022","title":"Benchmarking Library Recognition in Tweets","authors":["T Zhang, DP Chandrasekaran, F Thung, D Lo - 2022"],"snippet":"… News dataset); OpenWebText [2] (an open-source recreation of the WebText corpus), and Stories [40] (a subset of CommonCrawl data that … Compared to BERT, XLNet also involved more pre-training data, such as Common Crawl [1]. XLNet …","url":["https://happygirlzt.com/files/icpc22.pdf"]}
-{"year":"2022","title":"Benchmarking Transformers-based models on French Spoken Language Understanding tasks","authors":["O Cattan, S Ghannay, C Servan, S Rosset - INTERSPEECH 2022, 2022"],"snippet":"… Most models are pre-trained on the content of either Wikipedia, the web pages gathered by Common Crawl (CC) or a combination of diverse corpora. This represents a few gigabytes to several hundred or even several terabytes of text. The …","url":["https://hal.archives-ouvertes.fr/hal-03715340/document"]}
-{"year":"2022","title":"Benefits from Variational Regularization in Language Models","authors":["C Ferner, S Wegenkittl - Machine Learning and Knowledge Extraction, 2022"],"snippet":"… WMT19 contains data from news commentaries, Wiki titles, Europarl, ParaCrawl, and Common Crawl corpora. The data are tokenized using … Both BERT and MiniBERT were trained on a much larger collection of datasets (Wikipedia …","url":["https://www.mdpi.com/2504-4990/4/2/25/pdf?version=1654773213"]}
-{"year":"2022","title":"Bengali POS Tagging Using Bi-LSTM with Word Embedding and Character-Level Embedding","authors":["K Bose, K Sarkar - COMSYS 2021"],"snippet":"Part-of-speech tagging (POS) is an important and very fundamental process in natural language processing (NLP). POS tagging is required as a preprocessing task in many types of linguistic research such as named entity recognition (NER) …","url":["https://link.springer.com/content/pdf/10.1007/978-981-19-0105-8.pdf#page=563"]}
-{"year":"2022","title":"Bernice: A Multilingual Pre-trained Encoder for Twitter","authors":["A DeLucia, S Wu, A Mueller, C Aguirre, M Dredze…"],"snippet":"… XLM-T and TwHIN-BERT* models use the XLM-R tokenizer, which was trained on out-of-domain CommonCrawl data and has the same vocabulary size as Bernice (250K tokens), but covers 100 languages versus 66.While trained on tweets, BERTweet is …","url":["https://www.cs.jhu.edu/~mdredze/publications/2022_emnlp_bernice.pdf"]}
-{"year":"2022","title":"BERT based Multiple Parallel Co-attention Model for Visual Question Answering","authors":["M Dias, H Aloj, N Ninan, D Koshti - 2022 6th International Conference on Intelligent …, 2022"],"snippet":"Humans can easily interpret visual and textual content whereas for a machine this is a challenging task. Visual question answering is a well-known problem in the field of computer vision and NLP where an image and a question related to the image are …","url":["https://ieeexplore.ieee.org/abstract/document/9788253/"]}
-{"year":"2022","title":"Bertifying sinhala-a comprehensive analysis of pre-trained language models for sinhala text classification","authors":["V Dhananjaya, P Demotte, S Ranathunga, S Jayasena - Proceedings of the 13th …, 2022"],"snippet":"This research provides the first comprehensive analysis of the performance of pre-trained language models for Sinhala text classification. We test on a set of different Sinhala text classification tasks and our analysis shows that out of the pre-trained …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.803.pdf"]}
-{"year":"2022","title":"BERTuit: Understanding Spanish language in Twitter through a native transformer","authors":["J Huertas-Tato, A Martin, D Camacho - arXiv preprint arXiv:2204.03465, 2022"],"snippet":"The appearance of complex attention-based language models such as BERT, Roberta or GPT-3 has allowed to address highly complex tasks in a plethora of scenarios. However, when applied to specific domains, these models encounter …","url":["https://arxiv.org/pdf/2204.03465"]}
-{"year":"2022","title":"Beyond Counting Datasets: A Survey of Multilingual Dataset Construction and Necessary Resources","authors":["J Hu, E Choi"],"snippet":"While the NLP community is generally aware of resource disparities among languages, we lack research that quantifies the extent and types of such disparity. Prior surveys estimating the availability of resources based on the number of …","url":["https://akariasai.github.io/files/multilingual_datasets_analysis_emnlp_findings_2022.pdf"]}
-{"year":"2022","title":"Beyond English-Centric Bitexts for Better Multilingual Language Representation Learning","authors":["B Patra, S Singhal, S Huang, Z Chi, L Dong, F Wei… - arXiv preprint arXiv …, 2022"],"snippet":"… 2020) which contains texts in 100 languages collected from Common Crawl. As mentioned in (§3.1), we explore the utility of the CCMatrix and the … Furthermore, the raw data was compiled from static Common Crawl snapshots from January …","url":["https://arxiv.org/pdf/2210.14867"]}
-{"year":"2022","title":"Bilingual attention based neural machine translation","authors":["L Kang, S He, M Wang, F Long, J Su - Applied Intelligence, 2022"],"snippet":"… Our contrast models mainly include (1) the winning system in WMT2014 [3], a phrase-based system of which language models were trained on the Common Crawl corpus; (2) GNMT [16] that is the most competitive RNN-based NMT model to …","url":["https://link.springer.com/article/10.1007/s10489-022-03563-8"]}
-{"year":"2022","title":"Bilingual Tabular Inference: A Case Study on Indic Languages","authors":["C Agarwal, V Gupta, A Kunchukuttan, M Shrivastava"],"snippet":"Existing research on Tabular Natural Language Inference (TNLI) exclusively examines the task in a monolingual setting where the tabular premise and hypothesis are in the same language. However, due to the uneven distribution of …","url":["https://vgupta123.github.io/docs/NAACL2022.pdf"]}
-{"year":"2022","title":"Biomedical Semantic Textual Similarity: Evaluation of Sentence Representations Enhanced with Principal Component Reduction and Word Frequency Weighting","authors":["K Kantor, M Morzy - International Conference on Artificial Intelligence in …, 2022"],"snippet":"… We examine 50-dimension and 300-dimension GloVe models built on Wikipedia corpus and 300-dimension models trained on the Common Crawl. We choose the BERT model [7] trained on BookCorpus and English Wikipedia for neural-based …","url":["https://link.springer.com/chapter/10.1007/978-3-031-09342-5_39"]}
-{"year":"2022","title":"Bitext Mining Using Distilled Sentence Representations for Low-Resource Languages","authors":["K Heffernan, O Çelebi, H Schwenk - arXiv preprint arXiv:2205.12654, 2022"],"snippet":"… Our monolingual data comes mostly from Common Crawl and other public sources like ParaCrawl5, and some additional targeted … Our main source of monolingual data was Common Crawl, complemented and targeted crawling (see …","url":["https://arxiv.org/pdf/2205.12654"]}
-{"year":"2022","title":"BJTU-WeChat's Systems for the WMT22 Chat Translation Task","authors":["Y Liang, F Meng, J Xu, Y Chen, J Zhou - arXiv preprint arXiv:2211.15009, 2022"],"snippet":"… For monolingual data, we use the News Crawl, Common Crawl, and Extended Common Crawl. For synthetic data generation, we back-translate all the target monolingual data and forward-translate the source monolingual data. For the in-domain …","url":["https://arxiv.org/pdf/2211.15009"]}
-{"year":"2022","title":"BLOOM: A 176B-Parameter Open-Access Multilingual Language Model","authors":["TL Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow… - arXiv preprint arXiv …, 2022"],"snippet":"… The latter required the development of new tools to extract text from the HTML in the Common Crawl WARC files, which we made available on the main data preparation repository.We were able to find and extract usable text data from all …","url":["https://arxiv.org/pdf/2211.05100"]}
-{"year":"2022","title":"Boosting named entity recognition in domain-specific and low-resource settings","authors":["S Najem-Meyer - 2022"],"snippet":"Recent researches in natural language processing have leveraged attention-based models to produce state-of-the-art results in a wide variety of tasks. Using transfer learning, generic models like BERT can be fine-tuned for domain-specific tasks …","url":["https://infoscience.epfl.ch/record/291236/files/2021SemProj___Boosting_NER%20%281%29.pdf"]}
-{"year":"2022","title":"Bootstrapping Icelandic Knowledge Graph Data","authors":["SR Friðriksdóttir, H Einarsson - 2022"],"snippet":"… The model is trained on several sources of bitext data, including ccMatrix [13], ccAligned [3] and OPUS [15], as well as monolingual data from Common Crawl 2. The model uses a modified transformer architecture which reaches a BLEU-score of …","url":["https://scholar.archive.org/work/rx2eruubtrfubafg3hnrvrz65q/access/wayback/https://s3.nl-ams.scw.cloud/pstorage-amster-45168546/36407967/FririksdttirEinarsson2022BootstrappingIcelandicKnowledgeGraphData.pdf?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=SCW90ENHXE6G7FVJV73C/20220729/nl-ams/s3/aws4_request&X-Amz-Date=20220729T090312Z&X-Amz-Expires=10&X-Amz-SignedHeaders=host&X-Amz-Signature=1a3d652c1534a09b587552fc159ec377ec6b493140a3c488e49368e28e36bb77"]}
-{"year":"2022","title":"Bridging Cross-Lingual Gaps During Leveraging the Multilingual Sequence-to-Sequence Pretraining for Text Generation","authors":["C Zan, L Ding, L Shen, Y Cao, W Liu, D Tao - arXiv preprint arXiv:2204.07834, 2022"],"snippet":"For multilingual sequence-to-sequence pretrained language models (multilingual Seq2Seq PLMs), eg mBART, the self-supervised pretraining task is trained on a wide range of monolingual languages, eg 25 languages from commoncrawl, while …","url":["https://arxiv.org/pdf/2204.07834"]}
-{"year":"2022","title":"Build-a-Bot: Teaching Conversational AI Using a Transformer-Based Intent Recognition and Question Answering Architecture","authors":["K Pearce, S Alghowinem, C Breazeal - arXiv preprint arXiv:2212.07542, 2022"],"snippet":"As artificial intelligence (AI) becomes a prominent part of modern life, AI literacy is becoming important for all citizens, not just those in technology careers. Previous research in AI education materials has largely focused on the introduction of …","url":["https://arxiv.org/pdf/2212.07542"]}
-{"year":"2022","title":"Building a Closed-Domain Question Answering System for a Low-Resource Language","authors":["P Tran, D Nguyen, HA Tran, T Nguyen, T Tran - Transactions on Asian and Low …, 2022"],"snippet":"… The authors announced two models including XLM-Rbase with 250 million parameters and XLM-Rlarge with 560 million parameters trained over 2.5 terabytes of data in 100 languages (including Vietnamese) from Common Crawl. XLM-R …","url":["https://dl.acm.org/doi/pdf/10.1145/3566123"]}
-{"year":"2022","title":"Building a comprehensive NER model for Satellite Domain","authors":["P Maurya, O Jafari, B Thatte, C Ingram, P Nagarkar - SN Computer Science, 2022"],"snippet":"… A model trained on the OntoNotes 5 and GloVe Common Crawl datasets. All of these models can recognize types of entities such as PERSON, NORP, FAC, ORG, GPE, LOC, PRODUCT, EVENT, WORK_OF_ART, LAW, LANGUAGE, DATE, TIME …","url":["https://link.springer.com/article/10.1007/s42979-022-01085-1"]}
-{"year":"2022","title":"Building a Connected Web Observatory","authors":["T Tiropanis, X Wang, R Tinati, W Hall"],"snippet":"… For the SUWO, we are harvesting a variety of Web feeds, which include real-time streams from social networking and user-generated content sites (Twitter, Facebook, YouTube), Web-crawled datasets using existing resources such as the ’CommonCrawl’1 …","url":["https://www.academia.edu/download/78199864/web-obs-arch-bwow14.pdf"]}
-{"year":"2022","title":"Building a Multilingual Taxonomy of Olfactory Terms with Timestamps","authors":["S Menini, T Paccosi, SS Tekiroglu, S Tonelli - To"],"snippet":"Olfactory references play a crucial role in our memory and, more generally, in our experiences, since researchers have shown that smell is the sense that is most directly connected with emotions. Nevertheless, only few works in NLP have tried to …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.429.pdf"]}
-{"year":"2022","title":"Building AI Enabled Note-taking Interfaces for Patient Encounters","authors":["J Wang - 2022"],"snippet":"Current clinical note-taking approaches cannot capture the entirety of information available from patient encounters and detract from patient-clinician interactions. To address those issues we investigate the feasibility and suitability of using artificial …","url":["https://tspace.library.utoronto.ca/bitstream/1807/123369/1/Wang_Jixuan__202206_PhD_thesis.pdf"]}
-{"year":"2022","title":"Building better machine learning models for rhetorical analyses: The use of rhetorical feature sets for training artificial neural network models","authors":["ZP Majdik, J Wynn - Technical Communication Quarterly, 2022"],"snippet":"In this paper, we investigate two approaches to building artificial neural network models to compare their effectiveness for accurately classifying rhetorical structures across multiple (non-binary) classes in small textual datasets. We find that the most …","url":["https://www.tandfonline.com/doi/abs/10.1080/10572252.2022.2077452"]}
-{"year":"2022","title":"Building Comparable Corpora for Assessing Multi-Word Term Alignment","authors":["O Adjali, E Morin, P Zweigenbaum - Proceedings of the 13th Language Resources …, 2022"],"snippet":"Recent work has demonstrated the importance of dealing with Multi-Word Terms (MWTs) in several Natural Language Processing applications. In particular, MWTs pose serious challenges for alignment and machine translation systems because of their …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.332.pdf"]}
-{"year":"2022","title":"Building Korean NER models for a manually annotated corpus from clinical notes using cross-lingual transfer learning","authors":["J Li, J Park, X Hu, J Wang, RW Park, H Xu"],"snippet":"… text dataset, BERT-MULTILINGUALBASE was a multilingual BERT model that was pre-trained on 104 languages with the largest Wikipedias dataset, and XLM-ROBERTABASE was a multilingual language model that was pre-trained on 100 languages with 2TB …","url":["https://www.ohdsi.org/wp-content/uploads/2022/10/96-Jianfu-Li_KoreanClinicalNotesNER_2022symposium-Jianfu-Li.pdf"]}
-{"year":"2022","title":"Building Machine Translation System for Software Product Descriptions Using Domain-specific Sub-corpora Extraction","authors":["P Lohar, S Madden, E O'Connor, M Popović… - Proceedings of the 15th …, 2022"],"snippet":"Building Machine Translation systems for a specific domain requires a sufficiently large and good quality parallel corpus in that domain. However, this is a bit challenging task due to the lack of parallel data in many domains such as economics …","url":["https://aclanthology.org/2022.amta-research.1.pdf"]}
-{"year":"2022","title":"Building Sentiment Lexicons for Mainland Scandinavian Languages Using Machine Translation and Sentence Embeddings","authors":["P Liu, C Marco, JA Gulla"],"snippet":"This paper presents a simple but effective method to build sentiment lexicons for the three Mainland Scandinavian languages: Danish, Norwegian and Swedish. This method benefits from the English Sentiwordnet and a thesaurus in one of the target …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.301.pdf"]}
-{"year":"2022","title":"Building Siamese Attention-Augmented Recurrent Convolutional Neural Networks for Document Similarity Scoring","authors":["S Han, L Shi, R Richie, FR Tsui - Information Sciences, 2022"],"snippet":"Automatically measuring document similarity is imperative in natural language processing, with applications ranging from recommendation to duplicate document detection. State-of-the-art approach in document similarity commonly involves deep …","url":["https://www.sciencedirect.com/science/article/pii/S0020025522011537"]}
-{"year":"2022","title":"Business Document Information Extraction: Towards Practical Benchmarks","authors":["M Skalický, Š Šimsa, M Uřičář, M Šulc - arXiv preprint arXiv:2206.11229, 2022"],"snippet":"… [93] was not published, while pre-training on it was crucial for the proposed method, and the C4 dataset [64] is shared in the form of code that extracts it directly from Common Crawl. Publicly available datasets for KI(L)E from business …","url":["https://arxiv.org/pdf/2206.11229"]}
-{"year":"2022","title":"C-OSINT: COVID-19 Open Source artificial INTelligence framework","authors":["L Ranaldi, A Nourbakhsh, F Fallucchid, FM Zanzotto - 2022"],"snippet":"With the emergence of COVID-19 disease worldwide, a market of the products related to this disease formed across the Internet. By the time these goods were in short supply, many uncontrolled Dark Web Marketplaces (DWM) were active in …","url":["http://ceur-ws.org/Vol-3260/paper16.pdf"]}
-{"year":"2022","title":"Can Cross-Domain Term Extraction Benefit from Cross-lingual Transfer?","authors":["HTH Tran, M Martinc, A Doucet, S Pollak - International Conference on Discovery …, 2022"],"snippet":"Automatic term extraction (ATE) is a natural language processing task that eases the effort of manually identifying terms from domain-specific corpora by providing a list of candidate terms. In this paper, we experiment with XLM-RoBERTa to evaluate the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-18840-4_26"]}
-{"year":"2022","title":"Can Foundation Models Help Us Achieve Perfect Secrecy?","authors":["S Arora, C Ré - arXiv preprint arXiv:2205.13722, 2022"],"snippet":"… 4A particular challenge was obtaining an FM for Reddit, since most FMs are trained on generic Common Crawl — we thus use Grover FMs, which are pretrained only on news articles and find the performance of Grover models directly match or …","url":["https://arxiv.org/pdf/2205.13722"]}
-{"year":"2022","title":"Can linguistic features extracted from geo-referenced tweets help building function classification in remote sensing?","authors":["M Häberle, EJ Hoffmann, XX Zhu - ISPRS Journal of Photogrammetry and Remote …, 2022"],"snippet":"… To add more heterogeneous language, they additionally utilized CommonCrawl 13 to train the word embedding using fastText, and words were left in upper and lower case to add some semantics and context to words (cf. Section 3.4). For our …","url":["https://www.sciencedirect.com/science/article/pii/S0924271622001058"]}
-{"year":"2022","title":"Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?","authors":["P Schramowski, C Tauchmann, K Kersting - arXiv preprint arXiv:2202.06675, 2022"],"snippet":"… The most recent and successful models, such as GPT-3 [5], CLIP [36], DALL-E [38] and other similar models, are trained on data scraped from the web, eg using CommonCrawl. The information they acquire from this data is largely uncontrolled …","url":["https://arxiv.org/pdf/2202.06675"]}
-{"year":"2022","title":"Capturing Failures of Large Language Models via Human Cognitive Biases","authors":["E Jones, J Steinhardt - arXiv preprint arXiv:2202.12299, 2022"],"snippet":"Large language models generate complex, open-ended outputs: instead of outputting a single class, they can write summaries, generate dialogue, and produce working code. In order to study the reliability of these open-ended systems, we must …","url":["https://arxiv.org/pdf/2202.12299"]}
-{"year":"2022","title":"Catching a Phish: Frontiers of Deep Learning-Based Anticipating Detection Engines","authors":["H Salah, H Zuhair - International Conference of Reliable Information and …, 2022"],"snippet":"In recent years, cyber-security gains high attention in the light of ethical hacking and social engineering attacks like phishing that riskily overshadow the development of social networking, e commerce, and information technology. Thus, mitigation of such …","url":["https://link.springer.com/chapter/10.1007/978-3-030-98741-1_40"]}
-{"year":"2022","title":"CATER: Intellectual Property Protection on Text Generation APIs via Conditional Watermarks","authors":["X He, Q Xu, Y Zeng, L Lyu, F Wu, J Li, R Jia - arXiv preprint arXiv:2209.08773, 2022"],"snippet":"… Since the training data of the victim model is unknown to the malicious users, we randomly select 5M sentences from common crawl data as the benign corpus. Then we obtain the word distribution for the watermarked and benign corpora, respectively …","url":["https://arxiv.org/pdf/2209.08773"]}
-{"year":"2022","title":"CausalDialogue: Modeling Utterance-level Causality in Conversations","authors":["YL Tuan, A Albalak, W Xu, M Saxon, C Pryor, L Getoor… - arXiv preprint arXiv …, 2022"],"snippet":"Despite their widespread adoption, neural conversation models have yet to exhibit natural chat capabilities with humans. In this research, we examine user utterances as causes and generated responses as effects, recognizing that changes in a cause …","url":["https://arxiv.org/pdf/2212.10515"]}
-{"year":"2022","title":"Cedille: A large autoregressive French language model","authors":["M Müller, F Laurent - arXiv preprint arXiv:2202.03371, 2022"],"snippet":"… Experiments conducted on GPT-3 (which has been trained on 570GB of text data from Common Crawl) show that the model may generate toxic sentences even when prompted with non-toxic text [11]. Although applying filtering of training data using …","url":["https://arxiv.org/pdf/2202.03371"]}
-{"year":"2022","title":"Challenges and limits of an open source approach to Artificial Intelligence","authors":["A THEBEN, L GUNDERSON, L LÓPEZ-FORÉS…"],"snippet":"… It takes the GPT model to a whole new level as it is trained on a massive number of parameters (ie 175 billions, which is over 10x the size of its predecessor) on an open source dataset called 'Common Crawl,' and other texts from OpenAI such as …","url":["https://www.staten-generaal.nl/eu/documenteu/pe_662908_challenges_and_limits_of/f=/vlkvn20v47an.pdf"]}
-{"year":"2022","title":"Challenges in Measuring Bias via Open-Ended Language Generation","authors":["AF Akyürek, MY Kocyigit, S Paik, D Wijaya - arXiv preprint arXiv:2205.11601, 2022"],"snippet":"Researchers have devised numerous ways to quantify social biases vested in pretrained language models. As some language models are capable of generating coherent completions given a set of textual prompts, several prompting datasets …","url":["https://arxiv.org/pdf/2205.11601"]}
-{"year":"2022","title":"Changing Language Ideological Concepts in the Human-Machine Era. Questions, Themes and Topics","authors":["D Dippold, I Erdocia, T Fester-Seeger, S Höhn…"],"snippet":"It introduces general thoughts on language ideological reformulations in the age of digital technologies as well as exemplary empirical studies that display language ideological changes, conducted by individual members of the Working Group. In this …","url":["https://www.researchgate.net/profile/Britta-Schneider/publication/365838026_Changing_Language_Ideological_Concepts_in_the_Human-Machine_Era_Questions_Themes_and_Topics/links/63860e357b0e356feb974905/Changing-Language-Ideological-Concepts-in-the-Human-Machine-Era-Questions-Themes-and-Topics.pdf"]}
-{"year":"2022","title":"Changing the Narrative Perspective: A New Language Processing Task and Machine Learning Approaches","authors":["M Chen - 2022"],"snippet":"In this dissertation I introduce the novel text processing task of changing the narrative perspective, where characters in a story are assigned a point of view that is di erent from the one originally used by the writer. The resulting shift in the narrative …","url":["https://etd.ohiolink.edu/apexprod/rws_etd/send_file/send?accession=ohiou1647655979201374&disposition=inline"]}
-{"year":"2022","title":"ChapterBreak: A Challenge Dataset for Long-Range Language Models","authors":["S Sun, K Thai, M Iyyer - arXiv preprint arXiv:2204.10878, 2022"],"snippet":"While numerous architectures for long-range language models (LRLMs) have recently been proposed, a meaningful evaluation of their discourse-level language understanding capabilities has not yet followed. To this end, we introduce …","url":["https://arxiv.org/pdf/2204.10878"]}
-{"year":"2022","title":"Characterization and Prediction of Mobile Tasks","authors":["Y Tian, K Zhou, D Pelleg - ACM Transactions on Information Systems (TOIS), 2022"],"snippet":"Mobile devices have become an increasingly ubiquitous part of our everyday life. We use mobile services to perform a broad range of tasks (eg, booking travel or conducting remote office work), leading to often lengthy interactions with several …","url":["https://dl.acm.org/doi/abs/10.1145/3522711"]}
-{"year":"2022","title":"Characterizing accident narratives with word embeddings: Improving accuracy, richness, and generalizability","authors":["DM Goldberg - Journal of Safety Research, 2021"],"snippet":"Introduction: Ensuring occupational health and safety is an enormous concern for organizations, as accidents not only harm workers but also result in financial losses. Analysis of accident data has the potential to reveal insights that may improve …","url":["https://www.sciencedirect.com/science/article/pii/S0022437521001754"]}
-{"year":"2022","title":"Characterizing and Resolving Degeneracies in Neural Autoregressive Text Generation","authors":["I Kulikov - 2022"],"snippet":"… We use the subset of WMT’19 training set consisting of news commentary v12 and common crawl resulting in slightly more than 1M and 2M training sentence pairs for Ru→En and De↔En pairs, respectively. We ne-tuned single model checkpoints …","url":["https://search.proquest.com/openview/b0268b79afd971636daec6ad90c0ec2c/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"Choose Your QA Model Wisely: A Systematic Study of Generative and Extractive Readers for Question Answering","authors":["M Luo, K Hashimoto, S Yavuz, Z Liu, C Baral, Y Zhou - arXiv preprint arXiv …, 2022"],"snippet":"While both extractive and generative readers have been successfully applied to the Question Answering (QA) task, little attention has been paid toward the systematic comparison of them. Characterizing the strengths and weaknesses of the two …","url":["https://arxiv.org/pdf/2203.07522"]}
-{"year":"2022","title":"City of Disguise: A Query Obfuscation Game on the ClueWeb","authors":["M Fröbe, NL Libera, M Hagen"],"snippet":"We present City of Disguise, a retrieval game that tests how well searchers are able to reformulate some sensitive query in a ‘Taboo’-style setup but still retrieve good results. Given one of 200 sensitive information needs and a relevant example …","url":["https://webis.de/downloads/publications/papers/froebe_2022b.pdf"]}
-{"year":"2022","title":"Classification of Construction Accident Court Cases Via Natural Language Processing in Hong Kong","authors":["RYM Li, HCY Li, B Tang, WC Au - Current State of Art in Artificial Intelligence and …, 2022"],"snippet":"… The fastText system has a trained English language vector model derived from Wikipedia, Common Crawl and other sources. Every word is stored along with several different tokens, and the morphology and word representations are replaced …","url":["https://link.springer.com/chapter/10.1007/978-981-19-0737-1_5"]}
-{"year":"2022","title":"Classification of German Jungian Extraversion and Introversion Texts with Assessment of Changes during the COVID-19 Pandemic","authors":["D Johannßen, C Biemann, D Scheffer"],"snippet":"The corona pandemic and countermeasures such as social distancing and lockdowns have confronted individuals with new challenges for their mental health and well-being. It can be assumed that the Jungian psychology types of extraverts …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2022-johannssen-biemann-scheffer-rapid4.pdf"]}
-{"year":"2022","title":"Classification of Indian Media Titles using Deep Learning Techniques","authors":["S Kumar, DD Rajesh, S Pranesh, VNH Kollipara… - International Journal of …, 2022"],"snippet":"Automatic speech recognition is being used everywhere these days. An essential part of this is language identification. Our goal here is to identify the language of the media title, such as song names and movie titles, to help in speech recognition. The …","url":["https://www.sciencedirect.com/science/article/pii/S2666307422000109"]}
-{"year":"2022","title":"Classification of Layout vs Relational Tables on the Web: Machine Learning with Rendered Pages","authors":["W Haider, Y Yesilada - ACM Transactions on the Web (TWEB), 2022"],"snippet":"Table mining on the web is an open problem, and none of the previously proposed techniques provides a complete solution. Most research focuses on the structure of the HTML document, but because of the nature and structure of the web, it is still a …","url":["https://dl.acm.org/doi/abs/10.1145/3555349"]}
-{"year":"2022","title":"Classifying and labeling the relationships between cities with high levels of co-occurrence on the English Wikipedia","authors":["D Rijen - 2022"],"snippet":"This study delves into three different approaches of document classification in order to successfully classify the type of relationship between European cities: ”LDA Topic modeling, Word embedding classification and Word frequency representation”. The …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/42413/THESIS__CITYNET____APPLIED_DATA_SCIENCE_FINAL_V3.pdf?sequence=1"]}
-{"year":"2022","title":"Classifying Documents by Viewpoint Using Word2Vec and Support Vector Machines","authors":["J Harwell, Y Li - International Conference on Applications of Natural …, 2022"],"snippet":"Ensuring viewpoint diversity in mass media is a historical challenge and recent political events, and the ever-increased use of the Internet, have made it an increasingly critical and contentious issue. This research explores the relationship …","url":["https://link.springer.com/chapter/10.1007/978-3-031-08473-7_13"]}
-{"year":"2022","title":"Classifying multi-level product categories using dynamic masking and transformer models","authors":["O Ozyegen, H Jahanshahi, M Cevik, B Bulut, D Yigit… - Journal of Data, Information …, 2022"],"snippet":"In an online shopping platform, a detailed categorization of the products greatly enhances user navigation. Online retailers also benefit from well-defined product categories as various sales and marketing operations such as special discounts and …","url":["https://link.springer.com/article/10.1007/s42488-022-00066-6"]}
-{"year":"2022","title":"ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization","authors":["J Wang, F Meng, Z Lu, D Zheng, Z Li, J Qu, J Zhou - arXiv preprint arXiv:2202.05599, 2022"],"snippet":"We present ClidSum, a benchmark dataset for building cross-lingual summarization systems on dialogue documents. It consists of 67k+ dialogue documents from two subsets (ie, SAMSum and MediaSum) and 112k+ annotated summaries in different …","url":["https://arxiv.org/pdf/2202.05599"]}
-{"year":"2022","title":"CLSE: Corpus of Linguistically Significant Entities","authors":["A Chuklin, J Zhao, M Kale - arXiv preprint arXiv:2211.02423, 2022"],"snippet":"One of the biggest challenges of natural language generation (NLG) is the proper handling of named entities. Named entities are a common source of grammar mistakes such as wrong prepositions, wrong article handling, or incorrect entity …","url":["https://arxiv.org/pdf/2211.02423"]}
-{"year":"2022","title":"ClueWeb22: 10 Billion Web Documents with Rich Information","authors":["A Overwijk, C Xiong, J Callan - Proceedings of the 45th International ACM SIGIR …, 2022"],"snippet":"… One approach is to sift CommonCrawl data, eg, the C4 dataset used to pretrain T5 [10], which provides sufficient quantity, but the quality quickly becomes a concern. For example, the cleaned CommonCrawl reflects a quite weird distribution of the …","url":["https://dl.acm.org/doi/abs/10.1145/3477495.3536321"]}
-{"year":"2022","title":"CM3: A Causal Masked Multimodal Model of the Internet","authors":["A Aghajanyan, B Huang, C Ross, V Karpukhin, H Xu… - arXiv preprint arXiv …, 2022"],"snippet":"… on close to a Terabyte of multi-modal simplified HTML data from the common crawl. • We present the causally masked objective, a hybrid of … all of Common Crawl and instead opt into using a subset of the Common Crawl News (CC-NEWS) …","url":["https://arxiv.org/pdf/2201.07520"]}
-{"year":"2022","title":"CoCo: Coherence-Enhanced Machine-Generated Text Detection Under Data Limitation With Contrastive Learning","authors":["X Liu, Z Zhang, Y Wang, Y Lan, C Shen - arXiv preprint arXiv:2212.10341, 2022"],"snippet":"… (2019a), in which HWTs are collected from RealNews, a large corpus of news articles from Common Crawl, and MGTs are generated by Grover-Mega, a transformer-based news generator with parameters sized 1.5B. …","url":["https://arxiv.org/pdf/2212.10341"]}
-{"year":"2022","title":"Cognitive linguistics meets computational linguistics: Construction grammar, dialectology, and linguistic diversity","authors":["J Dunn - Data Analytics in Cognitive Linguistics: Methods and …, 2022"],"snippet":"Computational linguistics and cognitive linguistics come together when we use data-driven methods to conduct linguistic experiments on corpora. This chapter uses usage-based construction grammar to model geographic variation in language. The basic …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=mpZuEAAAQBAJ&oi=fnd&pg=PA273&dq=commoncrawl&ots=QDhNj-UIiF&sig=Gkw4yCUdjqDM0EjTNJ7mpG44xyA"]}
-{"year":"2022","title":"Combining shallow and deep learning approaches against data scarcity in legal domains","authors":["F Sovrano, M Palmirani, F Vitali - Government Information Quarterly, 2022"],"snippet":"We are recently witnessing a radical shift towards digitisation in many aspects of our daily life, including law, public administration and governance. This has sometimes been done with the aim of reducing costs and human errors by improving data …","url":["https://www.sciencedirect.com/science/article/pii/S0740624X2200048X"]}
-{"year":"2022","title":"Commonsense Validation for Arabic Sentences using Deep Learning","authors":["E Al-Bashabsheh, H Al-Khazaleh, O Elayan, R Duwairi - 2021 22nd International Arab …, 2021"],"snippet":"… -based masked language model trained on a massive 2.5 TB of clean CommonCrawl data. The data includes 100 languages and obtained a decent performance as it … The XLM-Roberta was trained on 2.5 TB of recently produced …","url":["https://ieeexplore.ieee.org/abstract/document/9677156/"]}
-{"year":"2022","title":"Compact N-gram Language Models for Armenian","authors":["DS Karamyan, TS Karamyan - Mathematical Problems of Computer Science, 2022"],"snippet":"Applications such as speech recognition and machine translation use language models to select the most likely translation among many hypotheses. For on-device applications, inference time and model size are just as important as performance. In …","url":["https://www.mpcs.sci.am/index.php/mpcs/article/download/732/549"]}
-{"year":"2022","title":"Company recommendation model: Empowering the accounting system and publicly available data","authors":["R Štrimaitis, P Stefanovič, S Ramanauskaitė… - DAMSS 2022: 13th …, 2022"],"snippet":"[eng] Business management requires constant decision-making. Usually, the selection of suitable partners for collaboration is very intuitive, experience-based skill or requires the usage of data analytics. The most important aspect to get an …","url":["https://vb.vgtu.lt/object/elaba:148377608/148377608.pdf"]}
-{"year":"2022","title":"Comparative Analysis of Cross-lingual Contextualized Word Embeddings","authors":["HS Saadi, V Hangya, T Eder, A Fraser"],"snippet":"Contextualized word embeddings have emerged as the most important tool for performing NLP tasks in a large variety of languages. In order to improve the crosslingual representation and transfer learning quality, contextualized embedding …","url":["https://www.cis.uni-muenchen.de/~fraser/pubs/saadi_mrl2022.pdf"]}
-{"year":"2022","title":"Comparative Analysis of Machine Learning Classifiers for Phishing Detection","authors":["MF Ab Razak, MI Jaya, F Ernawan, A Firdaus… - 2022 6th International …, 2022"],"snippet":"… The source for this dataset is from the University Malaysia of Sarawak, compiled from PhishTank, OpenPhish, Alexa and Common Crawl. One method for detecting new phishing websites is to utilize heuristics such as the URL and CSS detection …","url":["https://ieeexplore.ieee.org/abstract/document/9930531/"]}
-{"year":"2022","title":"Comparative Analysis of Transformer Models on WikiHow Dataset","authors":["D Jadeja, A Khetri, A Mittal, DK Vishwakarma - 2022 International Conference on …, 2022"],"snippet":"Because of the ever-increasing amount of information around us, it has become highly essential to consume it in the most efficient way as possible. Text Summarization is a way of generating a summary for a long piece of text while …","url":["https://ieeexplore.ieee.org/abstract/document/9761043/"]}
-{"year":"2022","title":"Comparative Analysis of Transformers to Support Fine-Grained Emotion Detection in Short-Text Data","authors":["RH Frye, DC Wilson - The International FLAIRS Conference Proceedings, 2022"],"snippet":"… A clean derivation of the CommonCrawl Corpus was used in pretraining XLM-R, with one English version and twelve versions inclusive of other languages. Conneau et al. reported 95.0% accuracy on the SST binary sentiment classification task. Clark …","url":["https://journals.flvc.org/FLAIRS/article/download/130612/133913"]}
-{"year":"2022","title":"Comparative Evaluation of Transformer-Based Nepali Language Models","authors":["SR Tamrakar, C Silpasuwanchai - 2022"],"snippet":"… OSCAR (Open Super-large Crawled Aggregated coRpus) is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the Ungoliant architecture, a high-performance pipeline that provides …","url":["https://www.researchsquare.com/article/rs-2289743/latest.pdf"]}
-{"year":"2022","title":"Comparative Study of Classification Algorithms for Website Phishing Detection on Multiple Datasets","authors":["W Sarasjati, S Rustad, HA Santoso, A Syukur… - 2022 International Seminar …, 2022"],"snippet":"… The legitimate sites are collected from Alexa and Common Crawl, whereas the phishing sites are collected from PhishTank and OpenPhish. Mendeley dataset is different from UCI dataset because it has binary labels for classes. For example, 0 …","url":["https://ieeexplore.ieee.org/abstract/document/9920475/"]}
-{"year":"2022","title":"Comparative Study of Marathi Text Classification Using Monolingual and Multilingual Embeddings","authors":["F Eranpurwala - … Network Technologies and Intelligent Computing: First …, 2022"],"snippet":"… It was trained on Common Crawl and Wikipedia dataset using the CBOW model with position-weighted vocabulary of size 99882. IndicBERT was trained on ALBERT [18] using standard masked language model with vocabulary 200K and …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=8v9fEAAAQBAJ&oi=fnd&pg=PA441&dq=commoncrawl&ots=fyNHOEuz9Q&sig=fjU_MoFQFWMcxfuV5Mhyv1Tl15M"]}
-{"year":"2022","title":"Comparative study of text representation and learning for Persian named entity recognition","authors":["MM Abdollah Pour, S Momtazi - ETRI Journal, 2022"],"snippet":"… XLM-R [6] is a multilingual language model trained using a large corpus of CommonCrawl data from 100 languages. XLM-R has been shown to significantly outperform previous multilingual models, for example, the mBERT and XLM models. In addition …","url":["https://onlinelibrary.wiley.com/doi/abs/10.4218/etrij.2021-0269"]}
-{"year":"2022","title":"Comparing Different Approaches for Detecting Hate Speech in Online Portuguese Comments","authors":["BC Matos, RB Santos, P Carvalho, R Ribeiro, F Batista - 11th Symposium on …, 2022"],"snippet":"Online Hate Speech (OHS) has been growing dramatically on social media, which has motivated researchers to develop a diversity of methods for its automated detection. However, the detection of OHS in Portuguese is still little studied. To fill …","url":["https://drops.dagstuhl.de/opus/volltexte/2022/16756/pdf/OASIcs-SLATE-2022-10.pdf"]}
-{"year":"2022","title":"Comparing Emotion and Sentiment Analysis Tools on Italian anti-vaccination for COVID-19 posts","authors":["E Bellodi, A Bertagnon, M Gavanelli - Proceedings of the Sixth Workshop on Natural …, 2022"],"snippet":"Since the beginning of the vaccination campaign against Covid-19 in our country, resistance to vaccination has emerged on the part of a not negligible portion of the Italian population. Emotions (such as sadness, fear, etc.) and the polarity (positive/negative) …","url":["https://ceur-ws.org/Vol-3287/paper9.pdf"]}
-{"year":"2022","title":"Comparison of Different Modeling Techniques for Flemish Twitter Sentiment Analysis","authors":["M Reusens, M Reusens, M Callens, S vanden Broucke… - Analytics, 2022"],"snippet":"… The FastText approach, on the other hand, used Wikipedia and Common Crawl as training data. Common Crawl is a nonprofit company that crawls the web and then makes the obtained data publicly available [34]. It is possible that because our …","url":["https://www.mdpi.com/2813-2203/1/2/9/pdf"]}
-{"year":"2022","title":"Comparison of fuzzy sets based on the concept of imprecision","authors":["J Miliauskaitė, D Kalibatienė - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148957123/148957123.pdf"]}
-{"year":"2022","title":"Comparison of Named Entity Recognition Methods on Real-World and Highly Imbalanced Business Document Datasets","authors":["JC Vásquez-Correa, JR Orozco-Arroyave - Applied Computer Sciences in …, 2022","SA Moreno-Acevedo, D Escobar-Grisales… - Workshop on Engineering …, 2022"],"snippet":"… RoBERTa was pre-trained with 2.5 TB of data from the cleaned Common Crawl corpus [18], which includes text data in 100 different languages and allows for computing text representations in multiple languages. Embeddings from RoBERTa …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=zoedEAAAQBAJ&oi=fnd&pg=PA41&dq=commoncrawl&ots=yJmgKGYOPH&sig=aL9Xc2rF3T8jv2DP7kNa7WHOCok","https://link.springer.com/chapter/10.1007/978-3-031-20611-5_4"]}
-{"year":"2022","title":"Comparison of Semantic Similarity Models on Constrained Scenarios","authors":["R Teixeira, M Antunes, D Gomes, RL Aguiar - Information Systems Frontiers, 2022"],"snippet":"The technological world has grown by incorporating billions of small sensing devices, collecting and sharing large amounts of diversified data over the new generation of wireless and mobile networks. We can use semantic similarity models to help …","url":["https://link.springer.com/article/10.1007/s10796-022-10350-w"]}
-{"year":"2022","title":"Comparison of Text Mining Models for Food and Dietary Constituent Named-Entity Recognition","authors":["N Perera, TTL Nguyen, M Dehmer, F Emmert-Streib - Machine Learning and …, 2022"],"snippet":"Biomedical Named-Entity Recognition (BioNER) has become an essential part of text mining due to the continuously increasing digital archives of biological and medical articles. While there are many well-performing BioNER tools for entities …","url":["https://www.mdpi.com/2504-4990/4/1/12/pdf"]}
-{"year":"2022","title":"Comparison of text preprocessing methods","authors":["CP Chai - Natural Language Engineering, 2022"],"snippet":"Text preprocessing is not only an essential step to prepare the corpus for modeling but also a key area that directly affects the natural language processing (NLP) application results. For instance, precise tokenization increases the accuracy of part-of-speech …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/comparison-of-text-preprocessing-methods/43A20821D65F1C0C4366B126FC794AE3"]}
-{"year":"2022","title":"Compilation and evaluation of the Spanish SatiCorpus 2021 for satire identification using linguistic features and transformers","authors":["JA García-Díaz, R Valencia-García - Complex & Intelligent Systems, 2022"],"snippet":"Satirical content on social media is hard to distinguish from real news, misinformation, hoaxes or propaganda when there are no clues as to which medium these news were originally written in. It is important, therefore, to provide Information Retrieval …","url":["https://link.springer.com/article/10.1007/s40747-021-00625-1"]}
-{"year":"2022","title":"Complex Word Identification for Language Learners","authors":["A Srivastava, C Biemann, Ö Alaçam, X Wang - 2022"],"snippet":"… In my experiment, I used the pre-trained English word vectors from FastText, which contains 2 million word vectors with subword information on Common Crawl (600B tokens). Table 6.3 displays the results achieved by training the sequential model …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2022-ma-srivastava.pdf"]}
-{"year":"2022","title":"Comprehensive Survey: Approaches to Emerging Technologies Detection within Scientific Publications","authors":["A Yelenov, AA Pak, AA A Ziyaden, I Akhmetov… - Computación y Sistemas, 2022"],"snippet":"The identification of breakthrough topics and emerging technologies has been of interest to the governments of many countries and the scientific community since the last century. This study presents the status and trend of the research field through a …","url":["https://cys.cic.ipn.mx/ojs/index.php/CyS/article/viewFile/4424/3458"]}
-{"year":"2022","title":"Compressed FastText Models for Czech Tagger","authors":["Z Nevěřilová - RASLAN 2022 Recent Advances in Slavonic Natural …, 2022"],"snippet":"… Instead of CommonCrawl, we decided to use the SYN corpus, version 9. The SYN corpus [9] … The SYN corpus is therefore about half of the size of the 2017 CommonCrawl used in the … This is surprising since we supposed the training data …","url":["http://nlp.fi.muni.cz/raslan/raslan22.pdf#page=89"]}
-{"year":"2022","title":"COMPS: Conceptual Minimal Pair Sentences for testing Property Knowledge and Inheritance in Pre-trained Language Models","authors":["K Misra, JT Rayz, A Ettinger - arXiv preprint arXiv:2210.01963, 2022"],"snippet":"A characteristic feature of human semantic memory is its ability to not only store and retrieve the properties of concepts observed through experience, but to also facilitate the inheritance of properties (can breathe) from superordinate concepts (animal) to …","url":["https://arxiv.org/pdf/2210.01963"]}
-{"year":"2022","title":"COMPUTATIONAL INFERENCE OF TRUSTWORTHINESS IN SOCIAL FIGURES THROUGH ANALYSIS OF SPEECH ACOUSTIC, TEXTUAL, AND VISUAL SIGNALS","authors":["SMS Shah - 2022"],"snippet":"This chapter provides a general introduction to the field of Social Signal Processing (SSP) and its application areas. It commences by providing a brief description of motivation for this research and use of SSP for behavioural analysis, presenting the research …","url":["https://researchrepository.rmit.edu.au/view/pdfCoverPage?instCode=61RMIT_INST&filePid=13293466670001341&download=true"]}
-{"year":"2022","title":"Computer Vision based Automated Spare Part Finder App","authors":["G Jugroop, P Seegolum, A Chiniah, BB Humaïra - 2022 International Conference on …, 2022"],"snippet":"The “Automated car spare part finder app” aims at building a spare part detection mobile application using image recognition technique that will assist users in finding desired spare parts and provide a list of websites where those spare parts can be …","url":["https://ieeexplore.ieee.org/abstract/document/9792778/"]}
-{"year":"2022","title":"Conceptual framework of data science for good squad","authors":["D Krikščiūnienė, V Sakalauskas, G Romeika - DAMSS 2022: 13th conference on data …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148214567/148214567.pdf"]}
-{"year":"2022","title":"Conditional Generation with a Question-Answering Blueprint","authors":["S Narayan, J Maynez, RK Amplayo, K Ganchev… - arXiv preprint arXiv …, 2022"],"snippet":"The ability to convey relevant and faithful information is critical for many tasks in conditional generation and yet remains elusive for neural seq-to-seq models whose outputs often reveal hallucinations and fail to correctly cover important details. In this …","url":["https://arxiv.org/pdf/2207.00397"]}
-{"year":"2022","title":"Conditional Supervised Contrastive Learning for Fair Text Classification","authors":["J Chi, W Shand, Y Yu, KW Chang, H Zhao, Y Tian - arXiv preprint arXiv:2205.11485, 2022"],"snippet":"… The data consist of nearly 400,000 online biographies collected from the Common Crawl corpus. These biographies are annotated with one of the 28 professions to which their subject belongs. The data are mapped to a binary gender …","url":["https://arxiv.org/pdf/2205.11485"]}
-{"year":"2022","title":"Considerations for Multilingual Wikipedia Research","authors":["I Johnson, E Lescak - arXiv preprint arXiv:2204.02483, 2022"],"snippet":"English Wikipedia has long been an important data source for much research and natural language machine learning modeling. The growth of non-English language editions of Wikipedia, greater computational resources, and calls for equity in the …","url":["https://arxiv.org/pdf/2204.02483"]}
-{"year":"2022","title":"Considerations for the social impact of natural language processing","authors":["AGJ Paullada - 2021"],"snippet":"Natural language processing (NLP) technologies have transformed how people access information and communicate with one another. It has thus become critical to take stock of the social impact of natural language processing technologies. In this …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/48281/Paullada_washington_0250E_23796.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Consolidation of Crowd-Sourced Geo-Tagged Data for Parameterized Travel Recommendations","authors":["A Luberg"],"snippet":"The general subject area of this dissertation is automated creation of recommendations for tourism, with the focus on sights and visit-worthy locations. This stands in contrast to the recommendations provided by mainstream travel …","url":["https://scholar.archive.org/work/2pvxz3c6nvdelbkan4y5l5ykdy/access/wayback/https://digikogu.taltech.ee/et/Download/e6d95cdb-97f5-405e-af8a-dd617fa4c922/ConsolidationofCrowdSourcedGeoTaggedDatafor.pdf"]}
-{"year":"2022","title":"Constructing and analyzing domain-specific language model for financial text mining","authors":["M Suzuki, H Sakaji, M Hirano, K Izumi - Information Processing & Management, 2023"],"snippet":"The application of natural language processing (NLP) to financial fields is advancing with an increase in the number of available financial documents. Transformer-based models such as Bidirectional Encoder Representations from Transformers (BERT) …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322002953"]}
-{"year":"2022","title":"Constructing novel datasets for intent detection and ner in a korean healthcare advice system: guidelines and empirical results","authors":["YM Kim, TH Lee, SO Na - Applied Intelligence, 2022"],"snippet":"The demand for intelligent dialogue systems has increased rapidly in recent years. However, building such systems involves numerous complicated processes, including training data construction for language understanding. Although training …","url":["https://link.springer.com/article/10.1007/s10489-022-03400-y"]}
-{"year":"2022","title":"Construction and Evaluation of Sentiment Datasets for Low-Resource Languages: The Case of Uzbek","authors":["C Gómez-Rodrıguez - … Technology. Challenges for Computer Science and …"],"snippet":"To our knowledge, the majority of human language processing technologies for low-resource languages don’t have well-established linguistic resources for the development of sentiment analysis applications. Therefore, it is in dire need of such tools and …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=sF1zEAAAQBAJ&oi=fnd&pg=PA232&dq=commoncrawl&ots=DEPUp0f29K&sig=ynTMQqraKZa4eht38ObNrhsNhPw"]}
-{"year":"2022","title":"CONSTRUCTION OF A TRANSLATION TOOL FROM FRENCH TO FALC","authors":["FST TCHATCHOUANG, KW NZOKOU"],"snippet":"We started our internship on 06/06/2021 and ended on the 16/09/2022, which was an opportunity got after a sequence of offers sent by Mr Yasser ALMEHIO amongst which was found the internship at ISEP-école d'ingénieurs du numérique. For this …","url":["https://www.researchgate.net/profile/Tchouanga-Franck/publication/363780793_CONSTRUCTION_OF_A_TRANSLATION_TOOL_FROM_FRENCH_TO_FALC/links/632dc9c56063772afd8919ad/CONSTRUCTION-OF-A-TRANSLATION-TOOL-FROM-FRENCH-TO-FALC.pdf"]}
-{"year":"2022","title":"Context-aware IoT Service Recommendation: A Deep Collaborative Filtering-based Approach","authors":["Z Wang, CA Sun, M Aiello - 2022 IEEE International Conference on Web Services …, 2022"],"snippet":"The advantages of Service-Oriented Architecture (SOA) combined with the emerging and diffusion of the Internet of Things (IoT) instances have given birth to a new paradigm for IoT components integration, ie, Service-Oriented IoT. Microservices …","url":["https://ieeexplore.ieee.org/abstract/document/9885270/"]}
-{"year":"2022","title":"Contextual Answer Validation","authors":["A Baksi - 2022"],"snippet":"… Among these is the Common Crawl dataset[2]. It is acquired via scraping web pages, skipping over any HTML markup. Each month, it generates about 20TB of data via scraping. However, a significant quantity of Common Crawl contains …","url":["http://library.isical.ac.in:8080/xmlui/bitstream/handle/10263/7340/Arkadeep_Thesis-dissertation-18-7-22.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Contextualization and Generalization in Entity and Relation Extraction","authors":["B Taillé - arXiv preprint arXiv:2206.07558, 2022"],"snippet":"During the past decade, neural networks have become prominent in Natural Language Processing (NLP), notably for their capacity to learn relevant word representations from large unlabeled corpora. These word embeddings can then be …","url":["https://arxiv.org/pdf/2206.07558"]}
-{"year":"2022","title":"Contrastive Language-Vision AI Models Pretrained on Web-Scraped Multimodal Data Exhibit Sexual Objectification Bias","authors":["R Wolfe, Y Yang, B Howe, A Caliskan - arXiv preprint arXiv:2212.11261, 2022"],"snippet":"Nine language-vision AI models trained on web scrapes with the Contrastive Language-Image Pretraining (CLIP) objective are evaluated for evidence of a bias studied by psychologists: the sexual objectification of girls and women, which occurs …","url":["https://arxiv.org/pdf/2212.11261"]}
-{"year":"2022","title":"Contrastive Training Improves Zero-Shot Classification of Semi-structured Documents","authors":["M Khalifa, Y Vyas, S Wang, G Horwood, S Mallya… - arXiv preprint arXiv …, 2022"],"snippet":"… B Pre-training data from Common Crawl We build our pre-training corpus by first extracting all documents from CommonCrawl with a ‘.pdf‘ extension. We then remove duplicate documents based on the MD5 hash using fdupes.. The resulting …","url":["https://arxiv.org/pdf/2210.05613"]}
-{"year":"2022","title":"Controlling Formality in Low-Resource NMT with Domain Adaptation and Re-Ranking: SLT-CDT-UoS at IWSLT2022","authors":["ST Vincent, L Barrault, C Scarton - arXiv preprint arXiv:2205.05990, 2022"],"snippet":"This paper describes the SLT-CDT-UoS group's submission to the first Special Task on Formality Control for Spoken Language Translation, part of the IWSLT 2022 Evaluation Campaign. Our efforts were split between two fronts: data engineering …","url":["https://arxiv.org/pdf/2205.05990"]}
-{"year":"2022","title":"Conversational Humor Analysis: Developing Data, Annotation Schema and Models","authors":["V Pamulapati - 2021"],"snippet":"Conversational humor (CH) is a sub-domain of humor where the participants (speakers or listeners) engage in different types of humor such as retorts or teasing for various purposes. There are shared complexities between this phenomenon and the larger …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.8971852bf2270413.76616973686e6176695f70616d756c61706174695f66696e616c5f7468657369732e706466.pdf"]}
-{"year":"2022","title":"Core words in semantic representation","authors":["A Wang, S De Deyne, M McKague, A Perfors - Proceedings of the Annual Meeting of …, 2022"],"snippet":"A central question in cognitive science is how semantic information is mentally represented. Two dominant theories of semantic representation are language-based distributional semantic models (which suggest that word meaning is based on which …","url":["https://escholarship.org/content/qt8t34p5t8/qt8t34p5t8.pdf"]}
-{"year":"2022","title":"Correcting diacritics and typos with ByT5 transformer model","authors":["L Stankevičius, M Lukoševičius, J Kapočiūtė-Dzikienė… - arXiv preprint arXiv …, 2022"],"snippet":"… Good examples of the first side are the Common Crawl dataset of more than 20TB of data and its version OSCAR [107] filtered by language. Such huge datasets are now one of the main building blocks of popular transformer model pre-training but …","url":["https://arxiv.org/pdf/2201.13242"]}
-{"year":"2022","title":"CoSearcher: studying the effectiveness of conversational search refinement and clarification through user simulation","authors":["A Salle, S Malmasi, O Rokhlenko, E Agichtein - Information Retrieval Journal, 2022"],"snippet":"A key application of conversational search is refining a user’s search intent by asking a series of clarification questions, aiming to improve the relevance of search results. Training and evaluating such conversational systems currently requires …","url":["https://link.springer.com/article/10.1007/s10791-022-09404-z"]}
-{"year":"2022","title":"Cost-Effective Updating of Distributed Reordered Indexes","authors":["J Mackenzie, A Moffat - 2021"],"snippet":"Index reordering techniques allow document collections to be renumbered, with the goal of developing a permutation of the initial document ordinal identifiers that places documents that are (somehow) like each other into positions near each other …","url":["https://jmmackenzie.io/pdf/mm21-adcs.pdf"]}
-{"year":"2022","title":"COVID vaccine stigma: detecting stigma across social media platforms with computational model based on deep learning","authors":["N Straton - Applied Intelligence, 2022"],"snippet":"The study presents the first computational model of COVID vaccine stigma that can identify stigmatised sentiment with a high level of accuracy and generalises well across a number of social media platforms. The aim of the study is to understand the …","url":["https://link.springer.com/article/10.1007/s10489-022-04311-8"]}
-{"year":"2022","title":"COVID-19 and cyberbullying: deep ensemble model to identify cyberbullying from code-switched languages during the pandemic","authors":["S Paul, S Saha, JP Singh - Multimedia Tools and Applications, 2022"],"snippet":"… We have experimented with two different language specific fasttext Footnote 6 word embeddings, ie, English and Hindi as our code-switched corpus contains aforementioned two languages which are trained on Common Crawl and Wikipedia …","url":["https://link.springer.com/article/10.1007/s11042-021-11601-9"]}
-{"year":"2022","title":"COVID-19 Tweets Classification Based on a Hybrid Word Embedding Method. Big Data Cogn. Comput. 2022, 6, 58","authors":["Y Didi, A Walha, A Wali - 2022"],"snippet":"… pre-trained Word2Vec, FastText, and GloVe embedding trained on Common Crawl and Wikipedia with 300-D vectors, for word embedding. … vectors freely available on corpora, which is the combination of Gigaword5 and Wikipedia2014 …","url":["https://www.researchgate.net/profile/Yosra-Didi/publication/360686590_COVID-19_Tweets_Classification_Based_on_a_Hybrid_Word_Embedding_Method/links/62877bdb8ecbaa07fcc54606/COVID-19-Tweets-Classification-Based-on-a-Hybrid-Word-Embedding-Method.pdf"]}
-{"year":"2022","title":"Cramming: Training a Language Model on a Single GPU in One Day","authors":["J Geiping, T Goldstein - arXiv preprint arXiv:2212.14034, 2022"],"snippet":"Recent trends in language modeling have focused on increasing performance through scaling, and have resulted in an environment where training language models is out of reach for most researchers and practitioners. While most in the …","url":["https://arxiv.org/pdf/2212.14034"]}
-{"year":"2022","title":"Crawling Under-Resourced Languages–A Portal for Community-Contributed Corpus Collection","authors":["E Körner, F Helfer, C Schröder, T Eckart, D Goldhahn"],"snippet":"… The full texts might also be contained and accessible in larger web crawls and collections such as archive.org or commoncrawl.org. To alleviate the likelihood of copyright and license infringement, the largest related text segments published are …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/DCLRL/pdf/2022.dclrl-1.5.pdf"]}
-{"year":"2022","title":"Creating a Large Language Model of a Philosopher","authors":["E Schwitzgebel, D Schwitzgebel, A Strasser"],"snippet":"Can large language models be trained to produce philosophical texts that are difficult to distinguish from texts produced by human philosophers? To address this question, we fine-tuned OpenAI’s GPT-3 with two sets of training data: the blog posts …","url":["http://www.faculty.ucr.edu/~eschwitz/SchwitzPapers/GPT-3-Dennett-221102.pdf"]}
-{"year":"2022","title":"CRIM's Speech Recognition system description for OpenASR21 evaluation","authors":["V Gupta, G Boulianne"],"snippet":"CRIM participated in all the 15 low resource languages and the three languages with case sensitive scoring in the OpenASR21 Challenge for the constrained condition. For acoustic modeling, we developed both hybrid DNN-HMM systems and …","url":["https://www.nist.gov/document/crim-openasr21-system-description"]}
-{"year":"2022","title":"CRIM's Speech Recognition System for OpenASR21 Evaluation with Conformer and Voice Activity Detector Embeddings","authors":["V Gupta, G Boulianne - International Conference on Speech and Computer, 2022"],"snippet":"CRIM participated in all the 15 low resource languages and the three languages with case sensitive scoring in OpenASR21 for the constrained condition. For acoustic modeling, we developed both hybrid DNN-HMM systems and a conformer …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20980-2_21"]}
-{"year":"2022","title":"Cross-Language Learning for Product Matching","authors":["R Peeters, C Bizer - 2022"],"snippet":"… As multilingual models, we use multi-lingual BERT (’bert-base-multilingual-uncased’), which is trained on the top 100 largest Wikipedias, as well as XLMRoBERTa (’xlm-roberta-base’), which is trained on a CommonCrawl corpus consisting of 100 different languages …","url":["https://www2022.thewebconf.org/PaperFiles/48.pdf"]}
-{"year":"2022","title":"Cross-Lingual Ability of Multilingual Masked Language Models: A Study of Language Structure","authors":["Y Chai, Y Liang, N Duan - arXiv preprint arXiv:2203.08430, 2022"],"snippet":"Multilingual pre-trained language models, such as mBERT and XLM-R, have shown impressive cross-lingual ability. Surprisingly, both of them use multilingual masked language model (MLM) without any cross-lingual supervision or aligned data …","url":["https://arxiv.org/pdf/2203.08430"]}
-{"year":"2022","title":"Cross-Lingual and Cross-Domain Crisis Classification for Low-Resource Scenarios","authors":["C Sánchez, H Sarmiento, J Pérez, A Abeliuk, B Poblete - arXiv preprint arXiv …, 2022"],"snippet":"Social media data has emerged as a useful source of timely information about real-world crisis events. One of the main tasks related to the use of social media for disaster management is the automatic identification of crisis-related messages. Most of the …","url":["https://arxiv.org/pdf/2209.02139"]}
-{"year":"2022","title":"Cross-Lingual Approaches to Identifying Argument Components and Relations in Norwegian Reviews","authors":["Y Khutarniuk - 2022"],"snippet":"Argument mining is the process of automatic extraction of certain argumentation structures from data. Argument mining consists of several stages such as argument component detection, argument component classification, and argumentative …","url":["https://www.duo.uio.no/bitstream/handle/10852/94450/yauhenk_master_thesis.pdf?sequence=5"]}
-{"year":"2022","title":"Cross-lingual Coreference Resolution and Neural Machine Translation","authors":["JF Hetzer - 2022"],"snippet":"Like many other Natural Language Processing (NLP) tasks, coreference resolution has benefited massively from new developments in recent years. Deeper and more complex architectures enabled coreference resolution systems that work end-to-end …","url":["https://isl.anthropomatik.kit.edu/downloads/Jannik%20Hetzer%20Master%20Arbeit.pdf"]}
-{"year":"2022","title":"Cross-lingual transfer of knowledge in distributional language models: Experiments in Hungarian","authors":["A Novák, B Novák - Acta Linguistica Academica, 2022"],"snippet":"In this paper, we argue that the very convincing performance of recent deep-neural-model-based NLP applications has demonstrated that the distributionalist approach to language description has proven to be more successful than the earlier subtle rule-based …","url":["https://akjournals.com/view/journals/2062/aop/article-10.1556-2062.2022.00580/article-10.1556-2062.2022.00580.xml"]}
-{"year":"2022","title":"Cross-Modal Recurrent Semantic Comprehension for Referring Image Segmentation","authors":["C Shang, H Li, H Qiu, Q Wu, F Meng, T Zhao, KN Ngan - IEEE Transactions on …, 2022"],"snippet":"… For language encoder, we adopt a vanilla GRU [20] and initialize the word embeddings by GloVe [65] pretrained on Common Crawl 840B. The input images are resized to 416×416. The maximum length of language expression is set to 15 in …","url":["https://ieeexplore.ieee.org/abstract/document/9998537/"]}
-{"year":"2022","title":"Crosslingual Sharing for Low-Resource Natural Language Processing","authors":["P Mulcaire - 2022"],"snippet":"… Common Crawl, a repository of content scraped from the web which is frequently used as a source of text data, includes text from hundreds of languages—but more than 45% of the documents crawled are in English, just ten languages together …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/48884/Mulcaire_washington_0250E_24163.pdf?sequence=1"]}
-{"year":"2022","title":"CrossQE: HW-TSC 2022 Submission for the Quality Estimation Shared Task","authors":["S Tao, C Su, M Ma, H Yang, M Zhang, X Geng…"],"snippet":"Quality estimation (QE) is a crucial method to investigate automatic methods for estimating the quality of machine translation results without reference translations. This paper presents Huawei Translation Services Center’s (HWTSC’s) work called …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.61.pdf"]}
-{"year":"2022","title":"Current Research in Ecological and Social Psychology","authors":["M Atari, NK Reimer, J Graham, J Hoover, B Kennedy…"],"snippet":"Infectious diseases have been an impending threat to the survival of individuals and groups throughout our evolutionary history. As a result, humans have developed psychological pathogen-avoidance mechanisms and groups have developed …","url":["https://www.researchgate.net/profile/Mohammad-Atari-3/publication/362589037_Pathogens_Are_Linked_to_Human_Moral_Systems_Across_Time_and_Space/links/62ff8f10aa4b1206fac139f7/Pathogens-Are-Linked-to-Human-Moral-Systems-Across-Time-and-Space.pdf"]}
-{"year":"2022","title":"Customer Support Chat Intent Classification using Weak Supervision and Data Augmentation","authors":["S Prabhu, AK Brahma, H Misra - 5th Joint International Conference on Data Science …, 2022"],"snippet":"Understanding the actual intent of customers is an essential step in automating the conversational experience on a chat platform. Typically, chatbots are powered by machine learning algorithms that rely on the acquisition of a large amount of high …","url":["https://dl.acm.org/doi/abs/10.1145/3493700.3493729"]}
-{"year":"2022","title":"Cyber-Phishing Website Detection Using Fuzzy Rule Interpolation","authors":["M Almseidin, M Alkasassbeh, M Alzubi, J Al-Sawwa - Cryptography, 2022"],"snippet":"This paper introduces a novel detection method for phishing website attacks while avoiding the issues associated with the deficiencies of the knowledge-based representation and the binary decision. The suggested detection method was …","url":["https://www.mdpi.com/2410-387X/6/2/24/pdf?version=1651912543"]}
-{"year":"2022","title":"Data Analytics and Modeling in IoT-Fog Environment for Resourceconstrained IoT-Applications: A Review","authors":["O Farooq, P Singh - Recent Advances in Computer Science and …, 2022"],"snippet":"Objective: The emergence of the concepts like Big Data, Data Science, Machine Learning (ML), and the Internet of Things (IoT) in recent years has added the potential of research in today's world. The continuous use of IoT devices, sensors, etc …","url":["https://www.ingentaconnect.com/content/ben/rascs/2022/00000015/00000007/art00008"]}
-{"year":"2022","title":"Data Augmentation for Automated Essay Scoring using Transformer Models","authors":["K Gupta"],"snippet":"Automated essay scoring is one of the most important problem in Natural Language Processing. It has been explored for a number of years, and it remains partially solved. In addition to its economic and educational usefulness, it presents research …","url":["https://www.researchgate.net/profile/Kshitij_Gupta30/publication/364689774_Data_Augmentation_for_Automated_Essay_Scoring_using_Transformer_Models/links/636a743d37878b3e87913dcc/Data-Augmentation-for-Automated-Essay-Scoring-using-Transformer-Models.pdf"]}
-{"year":"2022","title":"Data Augmentation for Inline Tag-Aware Neural Machine Translation","authors":["Y Ryu, Y Choi, S Kim"],"snippet":"Despite the wide use of inline formatting, not much has been studied on translating sentences with inline formatted tags. The detag-andproject approach using word alignments is one solution to translating a tagged sentence. However, the method …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.81.pdf"]}
-{"year":"2022","title":"Data Augmentation for Intent Classification of German Conversational Agents in the Finance Domain","authors":["S Rentschler, M Riedl, C Stab, M Rückert - Proceedings of the 18th Conference on …, 2022"],"snippet":"In this paper, we focus on improving the intent recognition for a conversational agent. For languages other than English, labeled data needed for training is often limited. Limitations rise even more when moving to specific domains. Here, our goal is to …","url":["https://aclanthology.org/2022.konvens-1.1.pdf"]}
-{"year":"2022","title":"Data Augmentation to Address Out-of-Vocabulary Problem in Low-Resource Sinhala-English Neural Machine Translation","authors":["A Fernando, S Ranathunga - arXiv preprint arXiv:2205.08722, 2022"],"snippet":"Out-of-Vocabulary (OOV) is a problem for Neural Machine Translation (NMT). OOV refers to words with a low occurrence in the training data, or to those that are absent from the training data. To alleviate this, word or phrase-based Data Augmentation (DA) …","url":["https://arxiv.org/pdf/2205.08722"]}
-{"year":"2022","title":"Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languages","authors":["M Das, S Banerjee, A Mukherjee - arXiv preprint arXiv:2204.12543, 2022"],"snippet":"Abusive language is a growing concern in many social media platforms. Repeated exposure to abusive speech has created physiological effects on the target users. Thus, the problem of abusive language should be addressed in all forms for online …","url":["https://arxiv.org/pdf/2204.12543"]}
-{"year":"2022","title":"Data Efficient Multilingual Natural Language Processing","authors":["X Wang - 2022"],"snippet":"… ; the top five languages in CommonCrawl, a popular source of web-crawled data for the development of NLP models, account for about 70% of the total data, while the majority of languages in the world have much less data or no data at all in …","url":["https://www.lti.cs.cmu.edu/sites/default/files/wang%2C%20cindy%20-%20Thesis.pdf"]}
-{"year":"2022","title":"Data Governance in the Age of Large-Scale Data-Driven Language Technology","authors":["Y JERNITE, HUU NGUYEN, S BIDERMAN, A ROGERS… - 2022"],"snippet":"New families of algorithms relying on deep learning have made it possible to extract ever more complex language statistics from growing numbers of text and speech records to drastically improve the performance and applicability of data-driven …","url":["https://yjernite.github.io/content/LangDataGov.pdf"]}
-{"year":"2022","title":"Data integration and ethical quality: fundamental steps of the data analysis pipeline","authors":["F Azzalini - 2022"],"snippet":"… and the corpus on which it was trained is Common Crawl2. Regarding GloVe we use the model glove.840B.300d [106] and again each word is represented as a 300-dimensional vector and the training corpus was still Common Crawl. Once the single words are …","url":["https://www.politesi.polimi.it/bitstream/10589/187689/1/Azzalini%20Fabio%20PhD%20Thesis%20-%20POLITESI.pdf"]}
-{"year":"2022","title":"Data paper","authors":["W Tongjing, Z Yin, Z Bao, E Meijers"],"snippet":"… The dataset was extracted from Common Crawl, a web archive, which has periodically crawled … We used the entire Common Crawl text archive of April 2019 for processing and conducting … We subsequently used the entire Common Crawl …","url":["https://www.researchgate.net/profile/Evert-Meijers/publication/362952059_Dataset_of_intercity_relationships_between_293_Chinese_cities_extracted_and_classified_on_the_basis_of_toponym_co-occurrences_on_Common_Crawl/links/6308bfc25eed5e4bd11f7938/Dataset-of-intercity-relationships-between-293-Chinese-cities-extracted-and-classified-on-the-basis-of-toponym-co-occurrences-on-Common-Crawl.pdf"]}
-{"year":"2022","title":"Data Selection Curriculum for Neural Machine Translation","authors":["T Mohiuddin, P Koehn, V Chaudhary, J Cross… - arXiv preprint arXiv …, 2022"],"snippet":"… In our experiments, we use the newscrawl data as in-domain and commoncrawl data combined with newscrawl as general-domain for training the LMs. After scoring each parallel sentence pair (xi,yi) ∈ Dd by any of the above methods, we rank Dd …","url":["https://arxiv.org/pdf/2203.13867"]}
-{"year":"2022","title":"Data-Centric Debugging: mitigating model failures via targeted data collection","authors":["S Singla, AM Chegini, M Moayeri, S Feiz - arXiv preprint arXiv:2211.09859, 2022"],"snippet":"Deep neural networks can be unreliable in the real world when the training set does not adequately cover all the settings where they are deployed. Focusing on image classification, we consider the setting where we have an error distribution $\\mathcal{E} …","url":["https://arxiv.org/pdf/2211.09859"]}
-{"year":"2022","title":"Data-Driven Natural Language Inference","authors":["Y Nie - 2022"],"snippet":"Natural Language Inference (NLI) research involves the development of models that can mimic human inference processes based on natural language and classify the inference relation between sentences. For example, given the premise that “In 2019 …","url":["https://search.proquest.com/openview/2df1409d8beb3f8ab2883f74138fa258/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"Database Systems for Advanced Applications: 27th International Conference, DASFAA 2022, Virtual Event, April 11–14, 2022, Proceedings, Part III","authors":["A Bhattacharya, JLM Li, D Agrawal, PK Reddy… - 2022"],"snippet":"The three-volume set LNCS 13245, 13246 and 13247 constitutes the proceedings of the 26th International Conference on Database Systems for Advanced Applications, DASFAA 2022, held online, in April 2021. The total of 72 full papers, along with 76 …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=4XtsEAAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=GfE_2IqJct&sig=IIumPcUnOioFQO9gemsHu9RotXc"]}
-{"year":"2022","title":"Datasheet for the Pile","authors":["S Biderman, K Bicheno, L Gao - arXiv preprint arXiv:2201.07311, 2022"],"snippet":"This datasheet describes the Pile, a 825 GiB dataset of human-authored text compiled by EleutherAI for use in large-scale language modeling. The Pile is comprised of 22 different text sources, ranging from original scrapes done for this …","url":["https://arxiv.org/pdf/2201.07311"]}
-{"year":"2022","title":"DBkWik++--Multi Source Matching of Knowledge Graphs","authors":["S Hertling, H Paulheim - arXiv preprint arXiv:2210.02864, 2022"],"snippet":"Large knowledge graphs like DBpedia and YAGO are always based on the same source, ie, Wikipedia. But there are more wikis that contain information about long-tail entities such as wiki hosting platforms like Fandom. In this paper, we present the …","url":["https://arxiv.org/pdf/2210.02864"]}
-{"year":"2022","title":"Dead or Murdered? Predicting Responsibility Perception in Femicide News Reports","authors":["G Minnema, S Gemelli, C Zanchi, T Caselli, M Nissim - arXiv preprint arXiv …, 2022"],"snippet":"Different linguistic expressions can conceptualize the same event from different viewpoints by emphasizing certain participants over others. Here, we investigate a case where this has social consequences: how do linguistic expressions of gender-based …","url":["https://arxiv.org/pdf/2209.12030"]}
-{"year":"2022","title":"Debiasing isn't enough!--On the Effectiveness of Debiasing MLMs and their Social Biases in Downstream Tasks","authors":["M Kaneko, D Bollegala, N Okazaki - arXiv preprint arXiv:2210.02938, 2022"],"snippet":"We study the relationship between task-agnostic intrinsic and task-specific extrinsic social bias evaluation measures for Masked Language Models (MLMs), and find that there exists only a weak correlation between these two types of evaluation measures …","url":["https://arxiv.org/pdf/2210.02938"]}
-{"year":"2022","title":"Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features","authors":["C Du, K Fu, J Li, H He - arXiv preprint arXiv:2210.06756, 2022"],"snippet":"… several studies have addressed the idea of decoding naturalistic visual experiences from brain activity using purely linguistic features [15], [16], they merely use standard word vectors of class names that are automatically extracted from large …","url":["https://arxiv.org/pdf/2210.06756"]}
-{"year":"2022","title":"Deep cascaded multitask framework for detection of temporal orientation, sentiment and emotion from suicide notes","authors":["S Ghosh, A Ekbal, P Bhattacharyya - Scientific Reports, 2022"],"snippet":"… To capture the syntactic and semantic information of the words in a phrase, we use the efficacy of a 300-dimensional pre-trained GloVe word embedding 51 that is trained on the Common Crawl (42 billion tokens) corpus. …","url":["https://www.nature.com/articles/s41598-022-08438-z"]}
-{"year":"2022","title":"Deep Learning Approach for Aspect-Based Sentiment Analysis of Restaurants Reviews in Spanish","authors":["BC Martínez-Seis, O Pichardo-Lagunas, S Miranda… - Computación y Sistemas, 2022"],"snippet":"Online reviews of products and services have become important for customers and enterprises. Recent research focuses on analyzing and managing those kinds of reviews using natural language processing. This paper focuses on aspect-based …","url":["https://www.cys.cic.ipn.mx/ojs/index.php/CyS/article/download/4258/3387"]}
-{"year":"2022","title":"Deep learning based semantic textual similarity for applications in translation technology","authors":["T Ranasinghe - 2021"],"snippet":"Semantic Textual Similarity (STS) measures the equivalence of meanings between two textual segments. It is a fundamental task for many natural language processing applications. In this study, we focus on employing STS in the context of translation …","url":["https://wlv.openrepository.com/bitstream/handle/2436/624530/Ranasinghe_PhD_Thesis.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Deep Learning in Sentiment Analysis: A Survey of Recent Architectures","authors":["T Abdullah, A Ahmet - ACM Computing Surveys (CSUR), 2022"],"snippet":"Humans are increasingly integrated with devices that enable the collection of vast unstructured opinionated data. Accurately analysing subjective information from this data is the task of sentiment analysis (an actively researched area in NLP). Deep …","url":["https://dl.acm.org/doi/abs/10.1145/3548772"]}
-{"year":"2022","title":"DEEP LEARNING-BASED DEPENDENCY PARSING FOR TURKISH","authors":["SB Ozates - 2022"],"snippet":"… While XLM-R is pretrained on 2.5TB of unlabeled text data across 100 languages extracted from CommonCrawl Corpus [48], the multilingual version of BERT is pretrained on a much smaller Wikipedia Corpus for 104 languages. Another …","url":["https://www.cmpe.boun.edu.tr/~gungort/theses/Deep%20Learning-based%20Dependency%20Parsing%20for%20Turkish.pdf"]}
-{"year":"2022","title":"Deep Lexical Hypothesis: Identifying personality structure in natural language","authors":["A Cutler, DM Condon - 2022"],"snippet":"Recent advances in natural language processing (NLP) have produced general models that can perform complex tasks such as summarizing long passages and translating across languages. Here, we introduce a method to extract adjective …","url":["https://psyarxiv.com/gdm5v/download?format=pdf"]}
-{"year":"2022","title":"Deepfake Text Detection: Limitations and Opportunities","authors":["J Pu, Z Sarwar, SM Abdullah, A Rehman, Y Kim…"],"snippet":"… This generator is trained on the RealNews dataset [8], a large corpus (120GB) of news articles from Common Crawl [35]. The GPT-2 model is … [35] “Common crawl: A nonprofit 501 organization that crawls the web and freely provides its archives and …","url":["https://jmpu.github.io/files/Deepfake%20Text%20Detection%20Limitations%20and%20Opportunities_CR.pdf"]}
-{"year":"2022","title":"Delivering Fairness in Human Resources AI: Mutual Information to the Rescue","authors":["L Hemamou, W Coleman - Proceedings of the 2nd Conference of the Asia-Pacific …, 2022"],"snippet":"Automatic language processing is used frequently in the Human Resources (HR) sector for automated candidate sourcing and evaluation of resumes. These models often use pre-trained language models where it is difficult to know if possible biases …","url":["https://aclanthology.org/2022.aacl-main.64.pdf"]}
-{"year":"2022","title":"Demographic-Aware Language Model Fine-tuning as a Bias Mitigation Technique","authors":["A Garimella, A Amarnath, R Mihalcea"],"snippet":"BERT-like language models (LMs), when exposed to large unstructured datasets, are known to learn and sometimes even amplify the biases present in such data. These biases generally reflect social stereotypes with respect to gender, race, age …","url":["https://web.eecs.umich.edu/~mihalcea/papers/garimella.aacl22.pdf"]}
-{"year":"2022","title":"Demonstrator of Automatic Minuting","authors":["M Singh, R Kumar, T Ghosal, O Bojar, CC PV, AS PV… - 2022"],"snippet":"… framework to suit a variety of challenges in the domain of natural language understanding T5 also explained the advantage of scaling up the model size (to 11B parameters) and pre-training corpus, by introducing C4 (a massive text corpus which …","url":["https://elitr.eu/wp-content/uploads/2022/03/D65.FINAL_.pdf"]}
-{"year":"2022","title":"Demystifying Prompts in Language Models via Perplexity Estimation","authors":["H Gonen, S Iyer, T Blevins, NA Smith, L Zettlemoyer - arXiv preprint arXiv:2212.04037, 2022"],"snippet":"Language models can be prompted to perform a wide variety of zeroand few-shot learning problems. However, performance varies significantly with the choice of prompt, and we do not yet understand why this happens or how to pick the best …","url":["https://arxiv.org/pdf/2212.04037"]}
-{"year":"2022","title":"Dense-to-Sparse Gate for Mixture-of-Experts","authors":["X Nie, S Cao, X Miao, L Ma, J Xue, Y Miao, Z Yang… - arXiv preprint arXiv …, 2021"],"snippet":"… Wikipedia is a single domain of text, which contains about 2,500 words, and WebText is a large and diverse dataset in various domains, which is collected using 45 million links from Common Crawl. We apply GPT2-BPE (vocabulary size of 50257) …","url":["https://arxiv.org/pdf/2112.14397"]}
-{"year":"2022","title":"DESIGN AND IMPLEMENTATION OF A REALWORLD SEARCH ENGINE BASED ON OKAPI BM25 AND SENTENCEBERT","authors":["L Bonetti, P Torroni"],"snippet":"The work conducted in this thesis aims to present an hybrid model for a real world application search engine. The project presented was part of an intern ship work carried out in a startup which deals with Knowledge Management and Artificial …","url":["https://amslaurea.unibo.it/24774/1/Thesis_Bonetti.pdf"]}
-{"year":"2022","title":"Design of an GIS-based Investment Heatmap System using Topic Classification and NER","authors":["TT Van, KV Sy, TT Anh, TL Quang, PH Xuan, HL Viet… - 2021 13th International …, 2021"],"snippet":"… A multilingual fastText model [7], pre-trained on Common Crawl and Wikipedia corpus, is used to train on our collected corpus using transfer learning approach. The model was trained using CBOW with position-weights, in dimension 300, with …","url":["https://ieeexplore.ieee.org/abstract/document/9648730/"]}
-{"year":"2022","title":"Design of Oral English Intelligent Evaluation System Based on DTW Algorithm","authors":["Y Fang - Mobile Networks and Applications, 2022"],"snippet":"The accuracy of the existing spoken English intelligent evaluation system is not high, and the spoken English evaluation effect is poor. To improve the accuracy and speed of spoken English evaluation, this paper puts forward the design and …","url":["https://link.springer.com/article/10.1007/s11036-022-01925-7"]}
-{"year":"2022","title":"Designing Machine Learning Systems","authors":["C Huyen - 2022"],"snippet":"Machine learning systems are both complex and unique. Complex because they consist of many different components and involve many different stakeholders. Unique because they're data dependent, with data varying wildly from one use case …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=EThwEAAAQBAJ&oi=fnd&pg=PT51&dq=commoncrawl&ots=puuVz2C8kK&sig=TP64dzZehXbV5rEytHJY3Yhl3ow"]}
-{"year":"2022","title":"Detecting ambiguity in conversational systems","authors":["A Banerjee - 2021"],"snippet":"The question of detection of user search queries has been explored by many authors. With the advent of speech based search interfaces, narrowing down the scope of search based on user intent becomes even more important. A prominent part of …","url":["https://elib.uni-stuttgart.de/bitstream/11682/11953/1/Banerjee_Master%20Thesis.pdf"]}
-{"year":"2022","title":"Detecting autism from picture book narratives using deep neural utterance embeddings","authors":["A Wawer, I Chojnicka - International Journal of Language & Communication …, 2022"],"snippet":"… Pre-training of ELMoForManyLangs was performed on a 20 million-word data set sampled from Wikipedia and Common Crawl. For each input utterance, the representation obtained from ELMo was a vector of 1024 elements. The vectors …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/1460-6984.12731"]}
-{"year":"2022","title":"Detecting Backdoors in Deep Text Classifiers","authors":["Y Guo, J Wang, T Cohn - arXiv preprint arXiv:2210.11264, 2022"],"snippet":"Deep neural networks are vulnerable to adversarial attacks, such as backdoor attacks in which a malicious adversary compromises a model during training such that specific behaviour can be triggered at test time by attaching a specific word or …","url":["https://arxiv.org/pdf/2210.11264"]}
-{"year":"2022","title":"Detecting explicit lyrics: a case study in Italian music","authors":["M Rospocher - Language Resources and Evaluation, 2022"],"snippet":"Preventing the reproduction of songs whose textual content is offensive or inappropriate for kids is an important issue in the music industry. In this paper, we investigate the problem of assessing whether music lyrics contain content unsuitable …","url":["https://link.springer.com/article/10.1007/s10579-022-09595-3"]}
-{"year":"2022","title":"Detecting Psychological Phenomena in Dialogues","authors":["MO SOTOLAR - 2022"],"snippet":"Instant messaging (IM) is a type of online communication that allows for the synchronous exchange of text, images, voice, and videos between two or more people [1] using applications and platforms, such as Messenger or WhatsApp. This …","url":["https://is.muni.cz/th/x42fc/sotolar_teze_clanky_Archive.pdf"]}
-{"year":"2022","title":"Detection and Performance Evaluation of Online-Fraud Using Deep Learning Algorithms","authors":["A Khan, M Patil - Intelligent Computing and Networking, 2022"],"snippet":"Online News Portals are currently one of the primary sources used by people, though its credibility is under serious question. Because the problem associated with this is Click-bait. Click-baiting being the growing phenomenon on internet has the …","url":["https://link.springer.com/chapter/10.1007/978-981-16-4863-2_16"]}
-{"year":"2022","title":"Detection and Prevention of Sophisticated Cyberattacks","authors":["P Zhang - 2022"],"snippet":"Despite extensive research by the security community, cyberattacks such as phishing and Internet of Things (IoT) attacks remain profitable to criminals and continue to cause substantial damage not only to the victim users that they target …","url":["https://search.proquest.com/openview/3fdbd0bb47f35012a7243652fa10f045/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"Detection of Bangla Hate Comments and Cyberbullying in Social Media Using NLP and Transformer Models","authors":["M Emon, I Haque, KN Iqbal, M Mehedi, H Kabir… - International Conference on …, 2022"],"snippet":"Hate speech and cyberbullying detection on social media is one of the most trending natural language processing tasks in the current scenario. However, due to the lack of resources, a few work has been done in detection of cyberbullying in social media …","url":["https://link.springer.com/chapter/10.1007/978-3-031-12638-3_8"]}
-{"year":"2022","title":"Detection of dangerous events on social media: a critical review","authors":["ML Jamil, S Pais, J Cordeiro - Social Network Analysis and Mining, 2022"],"snippet":"… The additional data includes the CommonCrawl News dataset (63 million articles, 76 GB), Web text corpus (38 GB), and Stories from Common Crawl (31 GB). This, combined with a massive 1024 V100 Tesla GPU’s running for a day, resulting in pre-training …","url":["https://link.springer.com/article/10.1007/s13278-022-00980-y"]}
-{"year":"2022","title":"Detection of prosodic boundaries in speech using Wav2Vec 2.0","authors":["M Kunešová, M Řezáčková - International Conference on Text, Speech, and …, 2022"],"snippet":"Prosodic boundaries in speech are of great relevance to both speech synthesis and audio annotation. In this paper, we apply the wav2vec 2.0 framework to the task of detecting these boundaries in speech signal, using only acoustic information. We …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16270-1_31"]}
-{"year":"2022","title":"Developing a battery of measures for unobtrusive indicators of organisational culture: a research","authors":["TW Reader, A Gillespie - 2022"],"snippet":"… Then, using word embeddings based Common Crawl (2.6 unannotated billion web pages; 840 billion occurrences of 2.2 million unique tokens or words) and OntoNotes 5 (2.9 million annotated words), lists of similar words were generated for …","url":["https://scholar.archive.org/work/ot4molvh5bbmtmyupzmsijv5b4/access/wayback/https://www.tandfonline.com/doi/pdf/10.1080/13669877.2022.2108116?needAccess=true"]}
-{"year":"2022","title":"Developing a general-purpose clinical language inference model from a large corpus of clinical notes","authors":["M Sushil, D Ludwig, AJ Butte, VA Rudrapatna - arXiv preprint arXiv:2210.06566, 2022"],"snippet":"Several biomedical language models have already been developed for clinical language inference. However, these models typically utilize general vocabularies and are trained on relatively small clinical corpora. We sought to evaluate the impact …","url":["https://arxiv.org/pdf/2210.06566"]}
-{"year":"2022","title":"Developing a news classifier for Greek using BERT","authors":["G Gkolfopoulos, I Varlamis - 2022 7th South-East Europe Design Automation …, 2022"],"snippet":"Text categorization is a significant task in the re-search field of text mining, which has recently benefited from deep neural network algorithms and advanced learning techniques that extract language models from large textual corpora. These Pre-Trained …","url":["https://ieeexplore.ieee.org/abstract/document/9932996/"]}
-{"year":"2022","title":"Developing disinformation detection models in low-resource contexts: Czech news article dataset for source-level credibility","authors":["M Bohácek"],"snippet":"… To first obtain URLs of sites with individual articles from those domains, we used the Commoncrawl API 1. We specified for the API to include only articles discovered between January 2019 and September 2021. Once these 1Commoncrawl library …","url":["https://data.matsworld.io/research/cnsc-paper-bohacek.pdf"]}
-{"year":"2022","title":"Developing Technology Tools to Combat Fake Science","authors":["C Impey, A Danehy - Future of Information and Communication Conference, 2022"],"snippet":"… In the next phase of the project, this technology will be scaled to large samples of content drawn from CommonCrawl, and it will be applied across more domains of science. Then it will be deployed as a web browser extension that presents the …","url":["https://link.springer.com/chapter/10.1007/978-3-030-98012-2_25"]}
-{"year":"2022","title":"Development of lumbar spine MRI referrals vetting models using machine learning and deep learning algorithms: Comparison models vs healthcare professionals","authors":["AH Alanazi, A Cradock, L Rainford - Radiography, 2022"],"snippet":"Introduction Referrals vetting is a necessary daily task to ensure the appropriateness of radiology referrals. Vetting requires extensive clinical knowledge and may challenge those responsible. This study aims to develop AI models to automate the …","url":["https://www.sciencedirect.com/science/article/pii/S1078817422000682"]}
-{"year":"2022","title":"Diachronic Neural Network Predictor of Word Animacy","authors":["V Bochkarev, A Achkeev, A Shevlyakova… - … International Conference on …, 2022"],"snippet":"The paper considers the problem of automatic recognition of animacy in the Russian language. We propose a recognizer that is based on the analysis of co-occurrence with the most frequent words and is trained on data from the Russian subcorpus of …","url":["https://link.springer.com/chapter/10.1007/978-3-031-19496-2_16"]}
-{"year":"2022","title":"Dialog Inpainting: Turning Documents into Dialogs","authors":["Z Dai, AT Chaganty, V Zhao, A Amini, QM Rashid… - arXiv preprint arXiv …, 2022"],"snippet":"Many important questions (eg \"How to eat healthier?\") require conversation to establish context and explore in depth. However, conversational question answering (ConvQA) systems have long been stymied by scarce training data that is expensive …","url":["https://arxiv.org/pdf/2205.09073"]}
-{"year":"2022","title":"Dictionary with the Evaluation of Positivity/Negativity Degree of the Russian Words","authors":["V Solovyev, M Islamov, V Bayrasheva - International Conference on Speech and …, 2022"],"snippet":"… It was a feed-forward neural network, with the fastText vectors of the Common Crawl model fed to its input. Significant improvement of results has been achieved: 0.870. Scores extrapolation was carried out for some other languages. …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20980-2_55"]}
-{"year":"2022","title":"Did I Miss Anything? A Study on Ranking Fusion and Manual Query Rewriting in Consumer Health Search","authors":["GM Di Nunzio, F Vezzani - International Conference of the Cross-Language …, 2022"],"snippet":"In this paper, we describe the methodology and experimental analysis of a twofold strategy for the retrieval of medical relevant information: a ranking fusion and a query reformulation approach. In particular, the query reformulation approach is …","url":["https://link.springer.com/chapter/10.1007/978-3-031-13643-6_17"]}
-{"year":"2022","title":"DiffCSE: Difference-based Contrastive Learning for Sentence Embeddings","authors":["YS Chuang, R Dangovski, H Luo, Y Zhang, S Chang… - arXiv preprint arXiv …, 2022"],"snippet":"… However, they use 1TB of the training data from Common Crawl dumps while our model only use 115MB of the Wikipedia data for pretraining. We put their scores in Table 2 for reference. In SimCSE, the authors propose to use MLM as an auxiliary …","url":["https://arxiv.org/pdf/2204.10298"]}
-{"year":"2022","title":"Differentially Private Decoding in Large Language Models","authors":["J Majmudar, C Dupuy, C Peris, S Smaili, R Gupta… - arXiv preprint arXiv …, 2022"],"snippet":"Recent large-scale natural language processing (NLP) systems use a pre-trained Large Language Model (LLM) on massive and diverse corpora as a headstart. In practice, the pre-trained model is adapted to a wide array of tasks via fine-tuning on …","url":["https://arxiv.org/pdf/2205.13621"]}
-{"year":"2022","title":"Digital artifacts reveal development and diffusion of climate research","authors":["B Carneiro, G Resce, TB Sapkota - Scientific Reports, 2022"],"snippet":"… While public web archives exist—eg WayBack Machine 48 or Common Crawl 49 —they might miss a good number of web pages, resulting in limited outcomes 50 . Building a dedicated search engine could solve the coverage issue but would …","url":["https://www.nature.com/articles/s41598-022-17717-8"]}
-{"year":"2022","title":"Dilated Convolutional Neural Networks for Lightweight Diacritics Restoration","authors":["B Csanády, A Lukács - arXiv preprint arXiv:2201.06757, 2022"],"snippet":"… In the case of HunWeb2, we used the \"2017-2018\" part of the Common Crawl subcorpus. We decided not to split up the documents to multiple chunks or sentences, as we have found that there can be a lot of repeated sentences within one document …","url":["https://arxiv.org/pdf/2201.06757"]}
-{"year":"2022","title":"DiscoSense: Commonsense Reasoning with Discourse Connectives","authors":["P Bhargava, V Ng - arXiv preprint arXiv:2210.12478, 2022"],"snippet":"We present DiscoSense, a benchmark for commonsense reasoning via understanding a wide variety of discourse connectives. We generate compelling distractors in DiscoSense using Conditional Adversarial Filtering, an extension of …","url":["https://arxiv.org/pdf/2210.12478"]}
-{"year":"2022","title":"Discrete Cross-Modal Alignment Enables Zero-Shot Speech Translation","authors":["C Wang, Y Liu, B Chen, J Zhang, W Luo, Z Huang… - arXiv preprint arXiv …, 2022"],"snippet":"End-to-end Speech Translation (ST) aims at translating the source language speech into target language text without generating the intermediate transcriptions. However, the training of end-to-end methods relies on parallel ST data, which are difficult and …","url":["https://arxiv.org/pdf/2210.09556"]}
-{"year":"2022","title":"Distillation or loss of information?: The effects of distillation on model redundancy","authors":["EE Sventickaite - 2022"],"snippet":"… The XLM-Roberta could be comparable to mBERT, as the model can process 100 languages, it was trained on 2.1 terabytes of data extracted from CommonCrawl. It is important to note, that although lacking the next sentence prediction functionality …","url":["https://www.diva-portal.org/smash/get/diva2:1681230/FULLTEXT01.pdf"]}
-{"year":"2022","title":"Distributional evidence for derivational paradigms","authors":["O Bonami, MG Naranjo - The semantics of derivational morphology. Theory …"],"snippet":"This paper provides evidence from distributional semantics on the importance of paradigmatic relations in word formation systems. We argue that, if paradigmatic relations play a systemic role, that role should be measurable by examining whether …","url":["http://www.llf.cnrs.fr/sites/llf.cnrs.fr/files/u35/MGN-OB.pdf"]}
-{"year":"2022","title":"Do children texts hold the key to commonsense knowledge?","authors":["J Romero, S Razniewski - arXiv preprint arXiv:2210.04530, 2022","S Razniewski, J Romero"],"snippet":"Compiling comprehensive repositories of commonsense knowledge is a long-standing problem in AI. Many concerns revolve around the issue of reporting bias, ie, that frequency in text sources is not a good proxy for relevance or truth. This paper …","url":["https://arxiv.org/pdf/2210.04530","https://hal.science/hal-03832361v1/file/kid_books-1.pdf"]}
-{"year":"2022","title":"Do CoNLL-2003 Named Entity Taggers Still Work Well in 2023?","authors":["S Liu, A Ritter - arXiv preprint arXiv:2212.09747, 2022"],"snippet":"… Our dataset follows this distribution to collect Reuters news articles published between December 5th and 7th, 2020, collected from the Common Crawl Foundation3. We tokenized the data with the same tokenizer used for the CoNLL-2003 corpus …","url":["https://arxiv.org/pdf/2212.09747"]}
-{"year":"2022","title":"Do Images really do the Talking?","authors":["SU Hegde, A Hande, R Priyadharshini, S Thavareesan…"],"snippet":"… The text encoder was XLM-Roberta [58], which was trained on the 100 languages Common Crawl dataset, and the image feature extraction was ResNet [59] with 152 layers, followed by linear transformation to match the word embedding size of the …","url":["https://adeeph.github.io/pdf/meme_ACI%20(1).pdf"]}
-{"year":"2022","title":"Do language models make human-like predictions about the coreferents of Italian anaphoric zero pronouns?","authors":["JA Michaelov, BK Bergen - arXiv preprint arXiv:2208.14554, 2022"],"snippet":"Some languages allow arguments to be omitted in certain contexts. Yet human language comprehenders reliably infer the intended referents of these zero pronouns, in part because they construct expectations about which referents are …","url":["https://arxiv.org/pdf/2208.14554"]}
-{"year":"2022","title":"Do We Need a Specific Corpus and Multiple High-Performance GPUs for Training the BERT Model? An Experiment on COVID-19 Dataset","authors":["N Nuntachit, P Sugunnasil - Machine Learning and Knowledge Extraction, 2022"],"snippet":"The COVID-19 pandemic has impacted daily lives around the globe. Since 2019, the amount of literature focusing on COVID-19 has risen exponentially. However, it is almost impossible for humans to read all of the studies and classify them. This article …","url":["https://www.mdpi.com/2504-4990/4/3/30/pdf?version=1656917033"]}
-{"year":"2022","title":"Document Classification with Hierarchical Graph Neural Networks","authors":["A Guille, H Attali"],"snippet":"Various neural architectures have been explored for document classification, such as convolutional and recurrent networks or as of late, Transformers. In parallel, graph neural networks have vastly improved over the recent years. In this paper, we …","url":["https://adrienguille.github.io/publications/docgat.pdf"]}
-{"year":"2022","title":"Documenting Geographically and Contextually Diverse Data Sources: The BigScience Catalogue of Language Data and Resources","authors":["A McMillan-Major, Z Alyafeai, S Biderman, K Chen… - arXiv preprint arXiv …, 2022"],"snippet":"… Typically, this data is collected from online sources, ranging from highly edited and structured text such as Wikipedia to the myriad text and audiovisual components of web pages collected by Common Crawl1. Several issues concerning their …","url":["https://arxiv.org/pdf/2201.10066"]}
-{"year":"2022","title":"Does Corpus Quality Really Matter for Low-Resource Languages?","authors":["M Artetxe, I Aldabe, R Agerri, O Perez-de-Viñaspre… - arXiv preprint arXiv …, 2022"],"snippet":"… 2020), respectively, and were built by filtering CommonCrawl. Wikipedia has been a … Instead of filtering CommonCrawl, we do tailored crawling on 33 websites with high-quality content in … First of all, we find that, even if CommonCrawl derived …","url":["https://arxiv.org/pdf/2203.08111"]}
-{"year":"2022","title":"Domain Adaptation for Multi-Modal Foundation Models","authors":["AO Wiehe - 2022"],"snippet":"The multi-modal foundation model CLIP extracts representations of texts and images that can be used to achieve unprecedented performance in various tasks. However, this model was only trained on public data from the internet. Thus it lacks knowledge …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2022-ma-wiehe.pdf"]}
-{"year":"2022","title":"Domain Adaptation for Sparse-Data Settings: What Do We Gain by Not Using Bert?","authors":["M Sedinkina, M Schmitt, H Schütze - arXiv preprint arXiv:2203.16926, 2022"],"snippet":"The practical success of much of NLP depends on the availability of training data. However, in real-world scenarios, training data is often scarce, not least because many application domains are restricted and specific. In this work, we compare …","url":["https://arxiv.org/pdf/2203.16926"]}
-{"year":"2022","title":"Domain Adaptation of Machine Translation with Crowdworkers","authors":["M Morishita, J Suzuki, M Nagata - arXiv preprint arXiv:2210.15861, 2022"],"snippet":"… However, since CommonCrawl only covers a small portion of the web, it may overlook websites that contain valuable resources. Thus, the … In contrast, our work does not rely on CommonCrawl but on crowdworkers who can search the whole …","url":["https://arxiv.org/pdf/2210.15861"]}
-{"year":"2022","title":"Domain Adaptation of Transformer-Based Models using Unlabeled Data for Relevance and Polarity Classification of German Customer Feedback","authors":["A Idrissi-Yaghir, H Schäfer, N Bauer, CM Friedrich - arXiv preprint arXiv:2212.05764, 2022"],"snippet":"Understanding customer feedback is becoming a necessity for companies to identify problems and improve their products and services. Text classification and sentiment analysis can play a major role in analyzing this data by using a variety of machine …","url":["https://arxiv.org/pdf/2212.05764"]}
-{"year":"2022","title":"Domain Mismatch Doesn't Always Prevent Cross-Lingual Transfer Learning","authors":["D Edmiston, P Keung, NA Smith"],"snippet":"Cross-lingual transfer learning without labeled target language data or parallel text has been surprisingly effective in zero-shot cross-lingual classification, question answering, unsupervised machine translation, etc. However, some recent …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.94.pdf"]}
-{"year":"2022","title":"Domain over size: Clinical ELECTRA surpasses general BERT for bleeding site classification in the free text of electronic health records","authors":["JS Pedersen, MS Laursen, C Soguero-Ruiz… - 2022 IEEE-EMBS …, 2022"],"snippet":"Bleeding can be a life-threatening condition which occurs for 3.2% of medical patients. Information about previous bleeding and bleeding site is used to predict the risk of future bleeding and guide anticoagulant treatment. However, obtaining this …","url":["https://ieeexplore.ieee.org/abstract/document/9926955/"]}
-{"year":"2022","title":"Domain Parking: Largely Present, Rarely Considered!","authors":["J Zirngibl, S Deusch, P Sattler, J Aulbach, G Carle…"],"snippet":"… Common Crawl While visual identification allowed us to validate the inferences to a reasonable extent, we wanted to upscale validation. Therefore, we consider Common Crawl (CC) data [21] and calculate the similarity of pages. Common Crawl …","url":["https://www.net.in.tum.de/fileadmin/bibtex/publications/papers/zirngibl2022prevalenceofparking.pdf"]}
-{"year":"2022","title":"Domain-aware Multi-modality Fusion Network for Generalized Zero-shot Learning","authors":["J Wang, X Wang, H Zhang - Neurocomputing, 2022"],"snippet":"… Specifically, we investigate two word embedding methods including Word2vec[30] and Glove [36], which are trained on 1.4M Google News 2 and 2.2M Common Crawl 3 . We also consider hierarchical embeddings where similarity between objects can …","url":["https://www.sciencedirect.com/science/article/pii/S0925231222002168"]}
-{"year":"2022","title":"Domain-specific language models for multi-label classification of medical text","authors":["V Yogarajan - 2022"],"snippet":"Recent advancements in machine learning-based medical text multi-label classifications can be used to enhance the understanding of the human body and aid the need for patient care. This research considers predicting medical codes from …","url":["https://researchcommons.waikato.ac.nz/bitstream/handle/10289/14757/thesis.pdf?sequence=4&isAllowed=y"]}
-{"year":"2022","title":"Domain-Specific Machine Learning-A Human Learning Perspective","authors":["C Shan - 2022"],"snippet":"This dissertation focuses on Domain-Specific Machine Learning (DSML) with applications in the semiconductor industry. We first illustrate characteristics of DSML in view of semiconductor design and test processes, where a task is usually carried …","url":["https://escholarship.org/content/qt3m62p0hk/qt3m62p0hk.pdf"]}
-{"year":"2022","title":"Double Retrieval and Ranking for Accurate Question Answering","authors":["Z Zhang, T Vu, A Moschitti - arXiv preprint arXiv:2201.05981, 2022"],"snippet":"… Then, we used it to build a large index having up to 130MM passages extracted from 54MM documents of CommonCrawl2. We selected English Web documents of 5,000 most popular domains, including Wikipedia, from the recent releases of …","url":["https://arxiv.org/pdf/2201.05981"]}
-{"year":"2022","title":"DS4DH at TREC Health Misinformation 2021: Multi-Dimensional Ranking Models with Transfer Learning and Rank Fusion","authors":["B Zhang, N Naderi, F Jaume-Santero, D Teodoro - arXiv preprint arXiv:2202.06771, 2022"],"snippet":"This paper describes the work of the Data Science for Digital Health (DS4DH) group at the TREC Health Misinformation Track 2021. The TREC Health Misinformation track focused on the development of retrieval methods that provide relevant, correct …","url":["https://arxiv.org/pdf/2202.06771"]}
-{"year":"2022","title":"Dutch SQuAD and Ensemble Learning for Question Answering from Labour Agreements","authors":["NJ Rouws, S Vakulenko, S Katrenko - Benelux Conference on Artificial Intelligence, 2021"],"snippet":"The Dutch Ministry of Social Affairs and Employment has to regularly explore the content of labour agreements. Studies on topics such as diversity and work flexibility are conducted on the regular basis by means of specialised questionnaires. We …","url":["https://link.springer.com/chapter/10.1007/978-3-030-93842-0_9"]}
-{"year":"2022","title":"Early depression detection in social media based on deep learning and underlying emotions","authors":["JSL Figuerêdo, ALLM Maia, RT Calumby - Online Social Networks and Media, 2022"],"snippet":"Depression is a challenge to public health, frequently related to disability and one of the reasons that lead to suicide. Many of the ones who suffer depression use social media to obtain information or even to talk about their problem. Some studies have …","url":["https://www.sciencedirect.com/science/article/pii/S2468696422000283"]}
-{"year":"2022","title":"Early risk detection of mental illnesses using various types of textual features","authors":["R Ferreira, A Trifan, JL Oliveira - Working Notes of CLEF, 2022"],"snippet":"This paper documents the participation of our team, BioInfo@ UAVR, in the first and second task of the 2022 edition of CLEF eRisk. With the goal of achieving an early detection of subjects at risk of specific mental illnesses, pathological gambling and …","url":["http://ceur-ws.org/Vol-3180/paper-72.pdf"]}
-{"year":"2022","title":"EDIN: An End-to-end Benchmark and Pipeline for Unknown Entity Discovery and Indexing","authors":["N Kassner, F Petroni, M Plekhanov, S Riedel… - arXiv preprint arXiv …, 2022"],"snippet":"Existing work on Entity Linking mostly assumes that the reference knowledge base is complete, and therefore all mentions can be linked. In practice this is hardly ever the case, as knowledge bases are incomplete and because novel concepts arise …","url":["https://arxiv.org/pdf/2205.12570"]}
-{"year":"2022","title":"Effective Approaches to Neural Query Language Identification","authors":["X Ren, B Yang, D Liu, H Zhang, X Lv, L Yao, J Xie - Computational Linguistics, 2022"],"snippet":"… Commoncow: Massively huge web corpora from commoncrawl data and a method to distribute them freely under restrictive EU copyright laws. In Proceedings of the Tenth International Conference on Language Resources and Evaluation …","url":["https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli_a_00451/2035281/coli_a_00451.pdf"]}
-{"year":"2022","title":"Effective Transfer Learning for Low-Resource Natural Language Understanding","authors":["Z Liu - arXiv preprint arXiv:2208.09180, 2022"],"snippet":"Natural language understanding (NLU) is the task of semantic decoding of human languages by machines. NLU models rely heavily on large training data to ensure good performance. However, substantial languages and domains have very few …","url":["https://arxiv.org/pdf/2208.09180"]}
-{"year":"2022","title":"Effectiveness of French Language Models on Abstractive Dialogue Summarization Task","authors":["Y Zhou, F Portet, F Ringeval - arXiv preprint arXiv:2207.08305, 2022"],"snippet":"Pre-trained language models have established the state-of-the-art on various natural language processing tasks, including dialogue summarization, which allows the reader to quickly access key information from long conversations in meetings …","url":["https://arxiv.org/pdf/2207.08305"]}
-{"year":"2022","title":"Effectiveness of Text, Acoustic, and Lattice-based representations in Spoken Language Understanding tasks","authors":["E Villatoro-Tello, S Madikeri, J Zuluaga-Gomez… - arXiv preprint arXiv …, 2022"],"snippet":"In this paper, we perform an exhaustive evaluation of different representations to address the intent classification problem in a Spoken Language Understanding (SLU) setup. We benchmark three types of systems to perform the SLU intent detection task …","url":["https://arxiv.org/pdf/2212.08489"]}
-{"year":"2022","title":"Effects of Physiological Signals in Different Types of Multimodal Sentiment Estimation","authors":["S Katada, S Okada, K Komatani - IEEE Transactions on Affective Computing, 2022"],"snippet":"… FastText word vectors FastText is a recently developed language model for training word vectors with subword information on Wikipedia and the Common Crawl corpus [41]. This language model is not restricted to English and is available …","url":["https://ieeexplore.ieee.org/abstract/document/9726810/"]}
-{"year":"2022","title":"Effects of Similarity Score Functions in Attention Mechanisms on the Performance of Neural Question Answering Systems","authors":["Y Shen, EMK Lai, M Mohaghegh - Neural Processing Letters, 2022"],"snippet":"Attention mechanisms have been incorporated into many neural network-based natural language processing (NLP) models. They enhance the ability of these models to learn and reason with long input texts. A critical part of such mechanisms …","url":["https://link.springer.com/article/10.1007/s11063-021-10730-4"]}
-{"year":"2022","title":"Efficient and Accurate Closed-Domain and Open-Domain Long-Form Question Answering","authors":["RS Butler, VD Duggirala, F Banaei-Kashani - International Conference on Computer …, 2022"],"snippet":"We present an efficient and accurate long-form question answering platform, dubbed iLFQA (ie, short for intelligent Long-Form Question Answering). iLFQA was created as a continuation of iTA (ie, short for intelligent Teaching Assistant). iTA was …","url":["https://link.springer.com/chapter/10.1007/978-3-031-14756-2_9"]}
-{"year":"2022","title":"Efficient Language Modeling with Sparse all-MLP","authors":["P Yu, M Artetxe, M Ott, S Shleifer, H Gong, V Stoyanov… - arXiv preprint arXiv …, 2022"],"snippet":"All-MLP architectures have attracted increasing interest as an alternative to attention-based models. In NLP, recent work like gMLP shows that all-MLPs can match Transformers in language modeling, but still lag behind in downstream tasks. In this work, we …","url":["https://arxiv.org/pdf/2203.06850"]}
-{"year":"2022","title":"Efficient Multilingual Multi-modal Pre-training through Triple Contrastive Loss","authors":["Y Lee, KT Lim, W Baek, B Roh, S Kim - … of the 29th International Conference on …, 2022"],"snippet":"… Image-text pairs We follow the data collection process of ALIGN to create our in-house 1B imagetext pairs dataset from Common crawl 2. The raw descriptions are gathered from the Alt-text HTML attribute associated with web images. We only apply …","url":["https://aclanthology.org/2022.coling-1.504.pdf"]}
-{"year":"2022","title":"Effortless and beneficial processing of natural languages using transformers","authors":["K Amrutha, P Prabu - Journal of Discrete Mathematical Sciences and …, 2022"],"snippet":"Natural Language Processing plays a vital role in our day-to-day life. Deep learning models for NLP help make human life easier as computers can think, talk, and interact like humans. Applications of the NLP models can be seen in many domains …","url":["https://www.tandfonline.com/doi/abs/10.1080/09720529.2022.2133239"]}
-{"year":"2022","title":"ELF22: A Context-based Counter Trolling Dataset to Combat Internet Trolls","authors":["H Lee, YJ NA, H Song, J Shin, JC Park"],"snippet":"Online trolls increase social costs and cause psychological damage to individuals. With the proliferation of automated accounts making use of bots for trolling, it is difficult for targeted individual users to handle the situation both quantitatively and …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.378.pdf"]}
-{"year":"2022","title":"Elite Environmental Aesthetics: Placing Nature in a Changing Climate","authors":["A McCumber, A Davis - American Journal of Cultural Sociology, 2022"],"snippet":"What does it mean to escape to nature in a changing climate? We investigate the properties that make a place resonant with ideas of “nature,” particularly for liberal elite vacationers consuming place through travel. By analyzing over 10,000 articles …","url":["https://link.springer.com/article/10.1057/s41290-022-00179-w"]}
-{"year":"2022","title":"ElitePLM: An Empirical Study on General Language Ability Evaluation of Pretrained Language Models","authors":["J Li, T Tang, Z Gong, L Yang, Z Yu, Z Chen, J Wang… - arXiv preprint arXiv …, 2022"],"snippet":"Nowadays, pretrained language models (PLMs) have dominated the majority of NLP tasks. While, little research has been conducted on systematically evaluating the language abilities of PLMs. In this paper, we present a large-scale empirical study …","url":["https://arxiv.org/pdf/2205.01523"]}
-{"year":"2022","title":"Emerging trends: General fine-tuning (gft)","authors":["KW Church, X Cai, Y Ying, Z Chen, G Xun, Y Bian - Natural Language Engineering, 2022"],"snippet":"This paper describes gft (general fine-tuning), a little language for deep nets, introduced at an ACL-2022 tutorial. gft makes deep nets accessible to a broad audience including non-programmers. It is standard practice in many fields to use …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/909A753B5EC40310A8DC2A3093CAE9F6/S1351324922000237a.pdf/emerging-trends-general-fine-tuning-gft.pdf"]}
-{"year":"2022","title":"Emerging Trends: SOTA-Chasing","authors":["KW Church, V Kordoni - Natural Language Engineering, 2022"],"snippet":"Many papers are chasing state-of-the-art (SOTA) numbers, and more will do so in the future. SOTA-chasing comes with many costs. SOTA-chasing squeezes out more promising opportunities such as coopetition and interdisciplinary collaboration. In …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/5E9F9F796159040973053C52C443C1D6/S1351324922000043a.pdf/emerging_trends_sotachasing.pdf"]}
-{"year":"2022","title":"Emotion Classification of MIDI Lyrics Using Transformers","authors":["PMP de Oliveira - 2022"],"snippet":"… It uses the common crawl web extracted text [34] as a dataset for pre-training, where after some data cleaning and filtering, it ends up with 750GB of uncompressed English text, way more than RoBERTa, which was already an …","url":["https://repositorio-aberto.up.pt/bitstream/10216/142445/2/570765.pdf"]}
-{"year":"2022","title":"Emotion Detection using Deep Learning","authors":["Y Shaaban, H Korashy, W Medhat - 2021 16th International Conference on Computer …, 2021"],"snippet":"Emotion detection is one of the challenging tasks in Natural Language Processing. The applications of emotion detection can be utilized in different fields like data mining, psychology, and human-computer interaction. The paper aims to train …","url":["https://ieeexplore.ieee.org/abstract/document/9686108/"]}
-{"year":"2022","title":"Emotion-Aware Multimodal Pre-training for Image-Grounded Emotional Response Generation","authors":["Z Tian, Z Wen, Z Wu, Y Song, J Tang, D Li, NL Zhang - International Conference on …, 2022"],"snippet":"Face-to-face communication leads to better interactions between speakers than text-to-text conversations since the speakers can capture both textual and visual signals. Image-grounded emotional response generation (IgERG) tasks requires chatbots to generate a …","url":["https://link.springer.com/chapter/10.1007/978-3-031-00129-1_1"]}
-{"year":"2022","title":"Empirical Evaluation and Theoretical Analysis for Representation Learning: A Survey","authors":["K Nozawa, I Sato - arXiv preprint arXiv:2204.08226, 2022"],"snippet":"Representation learning enables us to automatically extract generic feature representations from a dataset to solve another machine learning task. Recently, extracted feature representations by a representation learning algorithm and a …","url":["https://arxiv.org/pdf/2204.08226"]}
-{"year":"2022","title":"Employing a Multilingual Transformer Model for Segmenting Unpunctuated Arabic Text","authors":["AM Alshanqiti, S Albouq, AB Alkhodre, A Namoun… - 2022"],"snippet":"Long unpunctuated texts containing complex linguistic sentences are a stumbling block to processing any low-resource languages. Thus, approaches that attempt to segment lengthy texts with no proper punctuation into simple candidate sentences …","url":["https://www.preprints.org/manuscript/202208.0451/download/final_file"]}
-{"year":"2022","title":"En-SeqGAN: An Efficient Sequence Generation Model for Deceiving URL Classifiers","authors":["TD Pham, TTT Pham, VC Ta - Asian Conference on Intelligent Information and …, 2022"],"snippet":"… The URLs in the data are crawled from Common Crawl website [19] and Phishtank [20] It resulted in 6 million legitimate URLs from Common Crawl and 1 million phish URLs from Phishtank. We follow the preprocessing procedure from [21] …","url":["https://link.springer.com/chapter/10.1007/978-981-19-8234-7_37"]}
-{"year":"2022","title":"Energy-Efficient Data Transfer Optimization via Decision-Tree Based Uncertainty Reduction","authors":["H Jamil, L Rodolph, J Goldverg, T Kosar - arXiv preprint arXiv:2204.07601, 2022"],"snippet":"… These include: (1) the small file size dataset consisting of 20,000 HTML files derived from the common crawl project [24]; (2) the medium file size dataset consisting of 5,000 image files derived from Flickr [25]; (3) the large file size dataset …","url":["https://arxiv.org/pdf/2204.07601"]}
-{"year":"2022","title":"Enhanced Distance-aware Self-attention and Multi-level Match for Sentence Semantic Matching","authors":["Y Deng, X Li, M Zhang, X Lu, X Sun - Neurocomputing, 2022"],"snippet":"Sentence semantic matching is a core research area in natural language processing, which is widely used in various natural language tasks. In recent years, attention mechanism has shown good performance in deep neural networks for sentence …","url":["https://www.sciencedirect.com/science/article/pii/S0925231222006877"]}
-{"year":"2022","title":"Enhancing Cross-lingual Prompting with Mask Token Augmentation","authors":["M Zhou, X Li, Y Jiang, L Bing - arXiv preprint arXiv:2202.07255, 2022"],"snippet":"… Model Details XLM-R base model, containing 270M parameters, is pretrained on 2.5TB of filtered CommonCrawl on 100 languages. It contains 12 Transformer layers with hidden space dimensions of 768 and 12 attention heads in each layer. …","url":["https://arxiv.org/pdf/2202.07255"]}
-{"year":"2022","title":"Enhancing Indic Handwritten Text Recognition Using Global Semantic Information","authors":["A Mondal, CV Jawahar - International Conference on Frontiers in Handwriting …, 2022"],"snippet":"Handwritten Text Recognition (htr) is more interesting and challenging than printed text due to uneven variations in the handwriting style of the writers, content, and time. htr becomes more challenging for the Indic languages because of (i) multiple …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21648-0_25"]}
-{"year":"2022","title":"Enhancing Mobile App Bug Reporting via Real-time Understanding of Reproduction Steps","authors":["M Fazzini, K Moran, CB Cardenas, T Wendland, A Orso… - arXiv preprint arXiv …, 2022"],"snippet":"… The module uses the FastText model trained on the Common Crawl dataset [39] to identify the semantic similarity between S2R descriptions and GUI element properties. The web application also provides access to bug reports saved in a …","url":["https://arxiv.org/pdf/2203.12093"]}
-{"year":"2022","title":"Enhancing the Performance of Text Mining","authors":["FM Al Shanik - 2021"],"snippet":"The amount of text data produced in science, finance, social media, and medicine is growing at an unprecedented pace. The raw text data typically introduces major computational and analytical obstacles (eg, extremely high dimensionality) to data …","url":["https://tigerprints.clemson.edu/cgi/viewcontent.cgi?article=3929&context=all_dissertations"]}
-{"year":"2022","title":"Enhancing Vietnamese Question Generation with Reinforcement Learning","authors":["N Vu, K Van Nguyen - Asian Conference on Intelligent Information and …, 2022"],"snippet":"Along with automatic question answering and machine reading comprehension, question generation has become a popular yet challenging task of natural language understanding in recent years. However, as far as we are concerned, there was no …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21743-2_45"]}
-{"year":"2022","title":"Enriching Grammatical Error Correction Resources for Modern Greek","authors":["K Korre, J Pavlopoulos"],"snippet":"… T5 was pre-trained on 750GB of Englishlanguage text that was sourced from the public Common Crawl web.MT5 was pre-trained on data from all of the 71 monthly web scrapes released so far by Common Crawl, which is more than the source data …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.532.pdf"]}
-{"year":"2022","title":"Ensembling of Various Transformer Based Models for the Fake News Detection Task in the Urdu Language","authors":["S Kalraa, P Vermaa, Y Sharmaa, GS Chauhanb"],"snippet":"The spread of misinformation has become a severe issue affecting society. Inaccurate information has enormous potential to cause real-world impacts. Developing algorithms to detect fake news automatically will be very useful in …","url":["http://ceur-ws.org/Vol-3159/T7-10.pdf"]}
-{"year":"2022","title":"Entity-Assisted Language Models for Identifying Check-worthy Sentences","authors":["T Su, C Macdonald, I Ounis - arXiv preprint arXiv:2211.10678, 2022"],"snippet":"We propose a new uniform framework for text classification and ranking that can automate the process of identifying check-worthy sentences in political debates and speech transcripts. Our framework combines the semantic analysis of the sentences …","url":["https://arxiv.org/pdf/2211.10678"]}
-{"year":"2022","title":"Entry and Acquisitions in Software Markets","authors":["L Eisfeld - 2022"],"snippet":"How do acquisitions of young, innovative, venture capital funded firms (startups) affect entry incentives of new firms? I create a new dataset by merging web-scraped product-level data on enterprise software with data on firms’ entry and acquisition …","url":["https://luiseeisfeld.github.io/assets/docs/JMP_Eisfeld_TSE.pdf"]}
-{"year":"2022","title":"Epidemic Question Answering: question generation and entailment for Answer Nugget discovery","authors":["MA Weinzierl, SM Harabagiu - Journal of the American Medical Informatics …, 2022"],"snippet":"Objective The rapidly growing body of communications during the COVID-19 pandemic posed a challenge to information seekers, who struggled to find answers to their specific and changing information needs. We designed a Question …","url":["https://academic.oup.com/jamia/advance-article-abstract/doi/10.1093/jamia/ocac222/6832056"]}
-{"year":"2022","title":"Equivocal URLs: Understanding the Fragmented Space of URL Parser Implementations","authors":["J Reynolds, A Bates, M Bailey - European Symposium on Research in Computer …, 2022"],"snippet":"Uniform Resource Locators (URLs) are integral to the Web and have existed for nearly three decades. Yet URL parsing differs subtly among parser implementations, leading to ambiguity that can be abused by attackers. We measure agreement …","url":["https://link.springer.com/chapter/10.1007/978-3-031-17143-7_9"]}
-{"year":"2022","title":"ERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for Programming Languages","authors":["Y Chai, S Wang, C Pang, Y Sun, H Tian, H Wu - arXiv preprint arXiv:2212.06742, 2022"],"snippet":"… 25 languages from CommonCrawl. It learns to reconstruct the full NL texts from corrupted ones with an arbitrary noising function. mT5 (Xue et al., 2021) is a multilingual-NL encoder-decoder model adapted from T5. It is trained on 101 NLs …","url":["https://arxiv.org/pdf/2212.06742"]}
-{"year":"2022","title":"esCorpius: A Massive Spanish Crawling Corpus","authors":["A Gutiérrez-Fandiño, D Pérez-Fernández… - arXiv e-prints, 2022"],"snippet":"… In this paper, we introduce esCorpius, a Spanish crawling corpus obtained from near 1 Pb of Common Crawl data. It is the most extensive corpus in Spanish with this level of quality in the extraction, purification and deduplication of web textual content …","url":["https://ui.adsabs.harvard.edu/abs/2022arXiv220615147G/abstract"]}
-{"year":"2022","title":"Estimating Confidence of Predictions of Individual Classifiers and Their Ensembles for the Genre Classification Task","authors":["M Lepekhin, S Sharoff"],"snippet":"… It has a similar architecture but uses a bigger and more genre-diverse corpus based on Common Crawl (instead of Wikipedia for the multilingual BERT). Therefore, we choose XLM-RoBERTa as the classifier for the experiments in our research. One …","url":["http://corpus.leeds.ac.uk/serge/publications/2022-LREC-genre.pdf"]}
-{"year":"2022","title":"Estimating Intelligence Quotient Using Stylometry and Machine Learning Techniques: A Review","authors":["GO Adebayo, RV Yampolskiy - Big Data Mining and Analytics, 2022"],"snippet":"… the curve of the collegiate word ratio (CWR) — the ratio of the total count of collegiate words (words SAT consider a part of strong vocabulary usage) used in a written text to the total count of words in the text, of sample texts with more than 100 …","url":["https://ieeexplore.ieee.org/iel7/8254253/9793354/09793359.pdf"]}
-{"year":"2022","title":"Estimating time-series changes in social sentiment@ Twitter in US metropolises during the COVID-19 pandemic","authors":["R Saito, S Haruyama - Journal of Computational Social Science, 2022"],"snippet":"Since early 2020, the global coronavirus pandemic has strained economic activities and traditional lifestyles. For such emergencies, our paper proposes a social sentiment estimation model that changes in response to infection conditions and …","url":["https://link.springer.com/article/10.1007/s42001-022-00186-4"]}
-{"year":"2022","title":"Estimation on the Importance of Semantic Web Integration for Art and Culture Related Online Media Outlets","authors":["A Giannakoulopoulos, M Pergantis, N Konstantinou… - Future Internet, 2022"],"snippet":"… Such a list was acquired through Common Crawl a “non-profit organization dedicated to … This process, which was developed in PHP, used Common Crawl’s API to receive a list of domains … The language of a website was identified based …","url":["https://www.mdpi.com/1999-5903/14/2/36/pdf"]}
-{"year":"2022","title":"Estonian Language Understanding: a Case Study on the COPA Task","authors":["HA KUULMETS, A TATTAR, M FISHEL"],"snippet":"The lack of Estonian NLU datasets severely affects advancing Estonian-specific NLP research. With this paper we aim to relieve the issue by publishing a new Estonian NLU dataset EstCOPA. We benchmark the task on several Estonian and multilingual …","url":["https://www.bjmc.lu.lv/fileadmin/user_upload/lu_portal/projekti/bjmc/Contents/10_3_19_Kuulmets.pdf"]}
-{"year":"2022","title":"Ethnic Bias in Judicial Decision-making: Evidence from Criminal Appeals in Kenya","authors":["DD Choi, JA Harris, F Shen-Bayh"],"snippet":"… ), we used the Common Crawl GLoVe model that was trained using a . million word vocabulary. Rodriguez and Spirling (Nd) further nd that pretrained word vectors perform well against both locally trained vectors and human coders. …","url":["https://www.dhdannychoi.com/files/CHS_EthnicBias.pdf"]}
-{"year":"2022","title":"eTranslation's Submissions to the WMT22 General Machine Translation Task","authors":["C Oravecz, K Bontcheva, D Kolovratník, B Kovachev…"],"snippet":"The paper describes the 3 NMT models submitted by the eTranslation team to the WMT22 general machine translation shared task. In the WMT news task last year, multilingual systems with deep and complex architectures utilizing immense …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.29.pdf"]}
-{"year":"2022","title":"EtriCA: Event-Triggered Context-Aware Story Generation Augmented by Cross Attention","authors":["C Tang, C Lin, H Huang, F Guerin, Z Zhang - arXiv preprint arXiv:2210.12463, 2022"],"snippet":"One of the key challenges of automatic story generation is how to generate a long narrative that can maintain fluency, relevance, and coherence. Despite recent progress, current story generation systems still face the challenge of how to …","url":["https://arxiv.org/pdf/2210.12463"]}
-{"year":"2022","title":"European Language Equality-Report on the French Language","authors":["G Adda, A Braffort, I Vasilescu, F Yvon - 2022"],"snippet":"This report presents a survey of the current state of technologies for the automatic processing of the French language as well as French Sign Language (FSL). Similar reports have been prepared independently for all languages of the European Union …","url":["https://hal.archives-ouvertes.fr/hal-03637776/document"]}
-{"year":"2022","title":"Evaluate and Visualize Legal Embeddings for Explanation Purpose","authors":["NH Thanh, DT Binh, BM Quan, N Le Minh - 2021 13th International Conference on …, 2021"],"snippet":"Deep learning models have recently demonstrated promising results on legal-related tasks. However, the performance of the models is not enough for us to have a clear understanding of their behavior and the reason for such performance. This paper is …","url":["https://ieeexplore.ieee.org/abstract/document/9648655/"]}
-{"year":"2022","title":"Evaluate Similarity of Requirements with Multilingual Natural Language Processing","authors":["U Bisang, J Brünnhäußer, P Lünnemann, L Kirsch… - Proceedings of the Design …, 2022"],"snippet":"Finding redundant requirements or semantically similar ones in previous projects is a very time-consuming task in engineering design, especially with multilingual data. Due to modern NLP it is possible to automate such tasks. In this paper we compared …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/2733FA14767D66DEE559E39594732BDD/S2732527X22001535a.pdf/div-class-title-evaluate-similarity-of-requirements-with-multilingual-natural-language-processing-div.pdf"]}
-{"year":"2022","title":"Evaluating Computational Models of Similarity against a Human Rated Dataset","authors":["E BARBU, VB MITITELU"],"snippet":"… The English distributional models were trained on Wikipedia and on the Common Crawl corpus containing English text. The semantic … a language identifier from Common Crawl and Wikipedia. The model is trained with a vector size of 100 …","url":["https://www.bjmc.lu.lv/fileadmin/user_upload/lu_portal/projekti/bjmc/Contents/10_3_03_Barbu1.pdf"]}
-{"year":"2022","title":"Evaluating Pre-Trained Transformers on Italian Administrative Texts","authors":["S Auriemma, M Miliani, A Bondielli, LC Passaro… - 2022"],"snippet":"In recent years, Transformer-based models have been widely used in NLP for various downstream tasks and in different domains. However, a language model explicitly built for the Italian administrative language is still lacking. Therefore, in this …","url":["https://ceur-ws.org/Vol-3285/paper4.pdf"]}
-{"year":"2022","title":"Evaluating Pre-training Objectives for Low-Resource Translation into Morphologically Rich Languages","authors":["P Dhar, A Bisazza, G van Noord"],"snippet":"The scarcity of parallel data is a major limitation for Neural Machine Translation (NMT) systems, in particular for translation into morphologically rich languages (MRLs). An important way to overcome the lack of parallel data is to leverage target monolingual …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.527.pdf"]}
-{"year":"2022","title":"Evaluating the Construct Validity of Text Embeddings with Application to Survey Questions","authors":["Q Fang, D Nguyen, DL Oberski - arXiv preprint arXiv:2202.09166, 2022"],"snippet":"Text embedding models from Natural Language Processing can map text data (eg words, sentences, documents) to supposedly meaningful numerical representations (aka text embeddings). While such models are increasingly applied in social science …","url":["https://arxiv.org/pdf/2202.09166"]}
-{"year":"2022","title":"Evaluating the Impact of OCR Quality on Short Texts Classification Task","authors":["O Vitman, Y Kostiuk, P Plachinda, A Zhila, G Sidorov… - … International Conference on …, 2022"],"snippet":"… As those embeddings have been trained on different kinds of text corpora ranging from Wikipedia to CommonCrawl Corpus Footnote 7 , they … On the other hand, Common Crawl Corpus is a huge corpus of a large chunk of the Internet, and the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-19496-2_13"]}
-{"year":"2022","title":"Evaluating Topic Modeling Pre-processing Pipelines for Portuguese Texts","authors":["APDS Júnior, P Cecilio, F Viegas, W Cunha… - Brazilian Symposium on …, 2022"],"snippet":"… De acordo com [31], os autores utilizam os vetores pré-treinados do FastText – modelo pré-treinado a partir do corpus Common Crawl. Dessa forma, adaptamos as CluWords para representação de textos em português utilizando os vetores …","url":["https://dl.acm.org/doi/abs/10.1145/3539637.3557052"]}
-{"year":"2022","title":"Evaluating transfer learning approach for detecting Arabic anti-refugee/migrant speech on social media","authors":["D Mohdeb, M Laifa, F Zerargui, O Benzaoui - Aslib Journal of Information …, 2022"],"snippet":"Purpose The present study was designed to investigate eight research questions that are related to the analysis and the detection of dialectal Arabic hate speech that targeted African refugees and illegal migrants on the YouTube Algerian space …","url":["https://www.emerald.com/insight/content/doi/10.1108/AJIM-10-2021-0293/full/html"]}
-{"year":"2022","title":"Evaluation and Analysis of the NLP Model Zoo for Ukrainian Text Classification","authors":["D Panchenko, D Maksymenko, O Turuta, A Yerokhin… - International Conference on …, 2022"],"snippet":"One of the crucial problems of natural language processing for languages such as Ukrainian is lack of datasets both unlabeled (for pretraining of word embeddings or large deep learning models) and labeled (for benchmarking existing approaches). In …","url":["https://link.springer.com/chapter/10.1007/978-3-031-20834-8_6"]}
-{"year":"2022","title":"Evaluation Methods for Representation Learning: A Survey","authors":["K Nozawa, I Sato - IJCAI-ECAI Survey Track, 2022"],"snippet":"Abstract Representation learning enables us to automatically extract generic feature representations from a dataset to solve another machine learning task. Recently, extracted feature representations by a representation learning algorithm and a …","url":["https://www.ijcai.org/proceedings/2022/0776.pdf"]}
-{"year":"2022","title":"Evaluation of an automated Presidio anonymisation model for unstructured radiation oncology electronic medical records in an Australian setting","authors":["DP Kotevsk, RI Smee, M Field, YN Nemes, K Broadley… - International Journal of …, 2022"],"snippet":"Background Electronic medical records (EMRs) contain valuable information for clinical research, however, the presence of personally identifying information (PII) restricts their use. Anonymisation of PII from EMRs enables clinical information to be …","url":["https://www.sciencedirect.com/science/article/pii/S1386505622001940"]}
-{"year":"2022","title":"Evaluation of Transfer Learning for Polish with a Text-to-Text Model","authors":["A Chrabrowa, Ł Dragan, K Grzegorczyk, D Kajtoch… - arXiv preprint arXiv …, 2022"],"snippet":"We introduce a new benchmark for assessing the quality of text-to-text models for Polish. The benchmark consists of diverse tasks and datasets: KLEJ benchmark adapted for text-to-text, en-pl translation, summarization, and question answering. In …","url":["https://arxiv.org/pdf/2205.08808"]}
-{"year":"2022","title":"Evaluation of Word Embedding Models in Latvian NLP Tasks Based on Publicly Available Corpora","authors":["R Laucis, G Jēkabsons - Applied Computer Systems, 2021"],"snippet":"Nowadays, natural language processing (NLP) is increasingly relaying on pre-trained word embeddings for use in various tasks. However, there is little research devoted to Latvian–a language that is much more morphologically complex than English. In …","url":["https://sciendo.com/pdf/10.2478/acss-2021-0016"]}
-{"year":"2022","title":"Event prediction from news text using subgraph embedding and graph sequence mining","authors":["RF Cekinel, P Karagoz - World Wide Web, 2022"],"snippet":"Event detection from textual content by using text mining concepts is a well-researched field in the literature. On the other hand, graph modeling and graph embedding techniques in recent years provide an opportunity to represent textual contents as …","url":["https://link.springer.com/article/10.1007/s11280-021-01002-1"]}
-{"year":"2022","title":"Expanding Knowledge Graphs with Humans in the Loop","authors":["E Manzoor, J Tong, S Vijayaraghavan, R Li - arXiv preprint arXiv:2212.05189, 2022"],"snippet":"… The PinText embeddings are trained on millions of tokens from the Pinterest platform8, whereas the FastText embeddings are trained on 6.3 billion tokens from the Common Crawl website archive. Thus, the two embedding approaches have …","url":["https://arxiv.org/pdf/2212.05189"]}
-{"year":"2022","title":"Experimental Comparison of Ansätze for Quantum Natural Language Processing","authors":["N Khatri"],"snippet":"The DisCoCat model of natural language is a framework which serves as the foundation for several contemporary experiments in Quantum Natural Language Processing (QNLP). In this model, sentences are represented as string diagrams …","url":["http://www.cs.ox.ac.uk/people/aleks.kissinger/theses/khatri-thesis.pdf"]}
-{"year":"2022","title":"Experimental Study on Backwash of Tsunami Acting on Caisson-Type Quay Wall","authors":["CTQ Wall"],"snippet":"Documents in HENRY are made available under the Creative Commons License CC BY 4.0, if no other license is applicable. Under CC BY 4.0 commercial use and sharing, remixing, transforming, and building upon the material of the work is …","url":["https://9dok.net/document/dzxor4oz-experimental-study-backwash-tsunami-acting-caisson-type-quay.html"]}
-{"year":"2022","title":"Explainable detection of adverse drug reaction with imbalanced data distribution","authors":["J Wang, LC Yu, X Zhang - PLOS Computational Biology, 2022"],"snippet":"… For BiLSTM, the word vectors were pre-trained using GloVe on the 840B Common Crawl corpus [28]. The dimensionality of the word vectors is 300. Words that don’t appear in GloVe were initialized with a uniform distribution U(−0.25, 0.25). …","url":["https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010144"]}
-{"year":"2022","title":"Exploiting Document-based Features for Clarification in Conversational Search","authors":["I Sekulić, M Aliannejadi, F Crestani - European Conference on Information Retrieval, 2022"],"snippet":"… For that purpose, we utilise Chatnoir [7] – a freely accessible Elasticsearch-based search engine with indexes of ClueWeb and CommonCrawl … Elastic ChatNoir: search engine for the ClueWeb and the common crawl. In: Pasi, G., Piwowarski, B …","url":["https://link.springer.com/chapter/10.1007/978-3-030-99736-6_28"]}
-{"year":"2022","title":"Exploiting Ensemble of Transformer Models for Detecting Informative Tweets","authors":["AN Chowdhury, S Guha, N Amin, SI Khan - 2021 IEEE 18th India Council …, 2021"],"snippet":"Microblogging platforms especially Twitter is considered as one of the prominent medium of getting user-generated information. Millions of tweets were posted daily during COVID-19 pandemic days and the rate increases gradually. Tweets include a …","url":["https://ieeexplore.ieee.org/abstract/document/9691734/"]}
-{"year":"2022","title":"Exploiting Linguistic Information from Nepali Transcripts for Early Detection of Alzheimer's Disease using the State-of-the-art Techniques of Machine Learning and …","authors":["S Adhikari, S Thapa, U Naseem, P Singh, A Huo…"],"snippet":"… Similarly, for the pre-trained fastText embeddings, the pre-trained word vectors trained on Common Crawl and Wikipedia using fastText were used [39]. The model was trained by using CBOW with position-weights, in dimension 300, with character …","url":["https://www.researchgate.net/profile/Surendrabikram-Thapa/publication/357190395_Exploiting_Linguistic_Information_from_Nepali_Transcripts_for_Early_Detection_of_Alzheimer's_Disease_using_Natural_Language_Processing_and_Machine_Learning_Techniques/links/6380f5107b0e356feb823970/Exploiting-Linguistic-Information-from-Nepali-Transcripts-for-Early-Detection-of-Alzheimers-Disease-using-Natural-Language-Processing-and-Machine-Learning-Techniques.pdf"]}
-{"year":"2022","title":"Exploration of text features representation on applications to the insurance domain","authors":["M Garcia Ribes - 2022"],"snippet":"The recent popularization of a more data-centric paradigm in machine learning has turned the study of the quality of feature representation into a very relevant topic. In this document an exploration of different text features representation applied to a …","url":["https://upcommons.upc.edu/bitstream/handle/2117/363257/165184.pdf?sequence=1"]}
-{"year":"2022","title":"Exploring Automatic Text Simplification of Requirements","authors":["EG Guren - 2022"],"snippet":"… The mined paraphrases are sequences of words with the same meaning extracted from a large collection of texts from Common Crawl7, an open-source collection of web crawl data. The system simplifies text by using the mined …","url":["https://www.duo.uio.no/bitstream/handle/10852/95635/8/thesis_final.pdf"]}
-{"year":"2022","title":"Exploring Capabilities of Monolingual Audio Transformers using Large Datasets in Automatic Speech Recognition of Czech","authors":["J Lehečka, J Švec, A Pražák, JV Psutka - arXiv preprint arXiv:2206.07627, 2022"],"snippet":"… is a huge collection of cleaned and deduplicated web pages from Common Crawl project4. Since this text corpus contains almost 13 billion … • adding LM into the beam search CTC decoder; we found the Common Crawl project to be a useful …","url":["https://arxiv.org/pdf/2206.07627"]}
-{"year":"2022","title":"Exploring Dimensionality Reduction Techniques in Multilingual Transformers","authors":["Á Huertas-García, A Martín, J Huertas-Tato… - arXiv preprint arXiv …, 2022"],"snippet":"Both in scientific literature and in industry,, Semantic and context-aware Natural Language Processing-based solutions have been gaining importance in recent years. The possibilities and performance shown by these models when dealing with …","url":["https://arxiv.org/pdf/2204.08415"]}
-{"year":"2022","title":"Exploring Models for Automatic Keyword Labelling of Scientific Documents","authors":["J Gabín, ME Ares, J Parapar - 2022"],"snippet":"Automatic keyword labelling methods generate a set of short phrases for a given document providing a short and good description of its content. Those labels are critical in tasks such as exploratory search and for improving the information …","url":["http://ceur-ws.org/Vol-3178/CIRCLE_2022_paper_04.pdf"]}
-{"year":"2022","title":"Exploring Swedish & English fastText Embeddings","authors":["T Adewumi, F Liwicki, M Liwicki"],"snippet":"In this paper, we show that embeddings from relatively smaller corpora sometimes outperform those from larger corpora and we introduce a new Swedish analogy test set and make it publicly available. To achieve good performance in Natural …","url":["https://aic20.aass.oru.se/aic-pdfs/AIC-2022-camera-ready-short-paper-07.pdf"]}
-{"year":"2022","title":"Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping","authors":["J He, X Li, D Yu, H Zhang, J Kulkarni, YT Lee… - arXiv preprint arXiv …, 2022"],"snippet":"Differentially private deep learning has recently witnessed advances in computational efficiency and privacy-utility trade-off. We explore whether further improvements along the two axes are possible and provide affirmative answers …","url":["https://arxiv.org/pdf/2212.01539"]}
-{"year":"2022","title":"Exploring Transformers models for Emotion Recognition: a comparision of BERT, DistilBERT, RoBERTa, XLNET and ELECTRA","authors":["D Cortiz - 2022 3rd International Conference on Control …, 2022"],"snippet":"This paper investigates the performance of different Transformers Models for Emotion Recognition, a specific NLU (Natural Language Understanding) task in Affective Computing. We implemented and finetuned different transformers …","url":["https://dl.acm.org/doi/abs/10.1145/3562007.3562051"]}
-{"year":"2022","title":"Exposing Cross-Lingual Lexical Knowledge from Multilingual Sentence Encoders","authors":["I Vulić, G Glavaš, F Liu, N Collier, EM Ponti… - arXiv preprint arXiv …, 2022"],"snippet":"Pretrained multilingual language models (LMs) can be successfully transformed into multilingual sentence encoders (SEs; eg, LaBSE, xMPNET) via additional fine-tuning or model distillation on parallel data. However, it remains uncertain how to best …","url":["https://arxiv.org/pdf/2205.00267"]}
-{"year":"2022","title":"Exposing the many biases in machine learning","authors":["S Richardson - Business Information Review, 2022"],"snippet":"In recent years, there have been numerous articles highlighting issues with bias in machine learning algorithms underpinning the use of AI in decision making. Specifically, algorithms trained on historical real-world observations. However, less …","url":["https://journals.sagepub.com/doi/abs/10.1177/02663821221121024"]}
-{"year":"2022","title":"Exposure and Emergence in Usage-Based Grammar: Computational Experiments in 35 Languages","authors":["J Dunn - arXiv preprint arXiv:2211.14160, 2022"],"snippet":"This paper uses computational experiments to explore the role of exposure in the emergence of construction grammars. While usage-based grammars are hypothesized to depend on a learner's exposure to actual language use, the …","url":["https://arxiv.org/pdf/2211.14160"]}
-{"year":"2022","title":"Extended Overview of HIPE-2022: Named Entity Recognition and Linking in Multilingual Historical Documents","authors":["M Ehrmann, M Romanello, S Najem-Meyer, A Doucet… - Working Notes of CLEF, 2022"],"snippet":"This paper presents an overview of the second edition of HIPE (Identifying Historical People, Places and other Entities), a shared task on named entity recognition and linking in multilingual historical documents. Following the success of the first CLEF-HIPE-2020 …","url":["http://ceur-ws.org/Vol-3180/paper-83.pdf"]}
-{"year":"2022","title":"Extracting Cultural Commonsense Knowledge at Scale","authors":["TP Nguyen, S Razniewski, A Varde, G Weikum - arXiv preprint arXiv:2210.07763, 2022"],"snippet":"Structured knowledge is important for many AI applications. Commonsense knowledge, which is crucial for robust human-centric AI, is covered by a small number of structured knowledge projects. However, they lack knowledge about …","url":["https://arxiv.org/pdf/2210.07763"]}
-{"year":"2022","title":"Extracting Impact Model Narratives from Social Services' Text","authors":["B Gajderowicz, D Rosu, MS Fox - 2022"],"snippet":"Named entity recognition (NER) is an important task in narration extraction. Narration, as a system of stories, provides insights into how events and characters in the stories develop over time. This paper proposes an architecture for NER on a corpus …","url":["http://ceur-ws.org/Vol-3117/paper6.pdf"]}
-{"year":"2022","title":"Extractive and Abstractive Summarization Methods for Financial Narrative Summarization in English, Spanish and Greek","authors":["A Vaca, A Segurado, D Betancur, A Barbero - Proceedings of the 4th Financial …, 2022"],"snippet":"This paper describes the three summarization systems submitted to the Financial Narrative Summarization Shared Task (FNS-2022). We developed a task-specific extractive summarization method for the reports in English. It was based on a …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/FNP/pdf/2022.fnp-1.8.pdf"]}
-{"year":"2022","title":"Extractive Question Answering on Queries in Hindi and Tamil","authors":["A Thirumala, E Ferracane - arXiv preprint arXiv:2210.06356, 2022"],"snippet":"… This is achieved by training the model on a large corpus of webcrawl data called the Common Crawl. The Common Crawl is a dataset that contains over 7 years of webcrawl data in over 40 languages. The question answering head applied to XLM- …","url":["https://arxiv.org/pdf/2210.06356"]}
-{"year":"2022","title":"Extreme Multilabel Text Classification on Indonesian Tax Court Ruling using Single Channel CNN and IndoBERT Embedding","authors":["IN Khasanah, AA Krisnadhi - 2021 6th International Workshop on Big Data and …, 2021"],"snippet":"Manual searching for legal basis such as paragraphs, articles, and laws when preparing for a tax court hearing is time-consuming. In this paper, we use extreme multilabel text classification approach to predict paragraphs, articles, and laws …","url":["https://ieeexplore.ieee.org/abstract/document/9631855/"]}
-{"year":"2022","title":"Face-Dubbing++: Lip-Synchronous, Voice Preserving Translation of Videos","authors":["A Waibel, M Behr, FI Eyiokur, D Yaman, TN Nguyen… - arXiv preprint arXiv …, 2022"],"snippet":"In this paper, we propose a neural end-to-end system for voice preserving, lip-synchronous translation of videos. The system is designed to combine multiple component models and produces a video of the original speaker speaking in the target …","url":["https://arxiv.org/pdf/2206.04523"]}
-{"year":"2022","title":"Fact-checking Multidimensional Statistic Claims in French","authors":["O Balalau, S Ebel, T Galizzi, A Deiana, E Gautreau… - TTO 2022-Truth and Trust …, 2022"],"snippet":"To strengthen public trust and counter disinformation, computational fact-checking, leveraging digital data sources, attracts interest from the journalists and the computer science community. A particular class of interesting data sources …","url":["https://hal.archives-ouvertes.fr/hal-03791175/document"]}
-{"year":"2022","title":"FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarization","authors":["D Wan, M Bansal - arXiv preprint arXiv:2205.07830, 2022"],"snippet":"We present FactPEGASUS, an abstractive summarization model that addresses the problem of factuality during pre-training and fine-tuning: (1) We augment the sentence selection strategy of PEGASUS's (Zhang et al., 2020) pre-training objective …","url":["https://arxiv.org/pdf/2205.07830"]}
-{"year":"2022","title":"Factual Consistency of Multilingual Pretrained Language Models","authors":["C Fierro, A Søgaard - arXiv preprint arXiv:2203.11552, 2022"],"snippet":"Pretrained language models can be queried for factual knowledge, with potential applications in knowledge base acquisition and tasks that require inference. However, for that, we need to know how reliable this knowledge is, and recent work …","url":["https://arxiv.org/pdf/2203.11552"]}
-{"year":"2022","title":"Fair and Optimal Classification via Transports to Wasserstein-Barycenter","authors":["R Xian, L Yin, H Zhao - arXiv preprint arXiv:2211.01528, 2022"],"snippet":"… The task is to determine the occupation (out of 28) of female and male individuals by their biography in text; the biographies, occupations and genders are mined from the Common Crawl corpus. Gender is the sensitive attribute, and to which certain …","url":["https://arxiv.org/pdf/2211.01528"]}
-{"year":"2022","title":"Fake news detection: When complex problems demand complex solutions","authors":["C Oliva, IP Marín, LF Lago-Fernández… - 2021"],"snippet":"Fake news detection is one of the most challenging problems in today's information and communication systems. In this article we address the challenge of detecting the generation and spreading of misleading information in the specific scenario of …","url":["https://digital.csic.es/bitstream/10261/257188/1/main_applied_intelligence.pdf"]}
-{"year":"2022","title":"Fake or Genuine? Contextualised Text Representation for Fake Review Detection","authors":["R Mohawesh, S Xu, M Springer, M Al-Hawawreh… - arXiv preprint arXiv …, 2021"],"snippet":"… Along with the English Wikipedia and book corpora, RoBERTa is pre-trained on the Common Crawl News dataset, comprising 63 million English-language news stories. RoBERTa base architecture consists of 768 hidden layers, 12 layers, 125 …","url":["https://arxiv.org/pdf/2112.14343"]}
-{"year":"2022","title":"FastClass: A Time-Efficient Approach to Weakly-Supervised Text Classification","authors":["T Xia, Y Wang, Y Tian, Y Chang - arXiv preprint arXiv:2212.05506, 2022"],"snippet":"Weakly-supervised text classification aims to train a classifier using only class descriptions and unlabeled data. Recent research shows that keyword-driven methods can achieve state-of-the-art performance on various tasks. However, these …","url":["https://arxiv.org/pdf/2212.05506"]}
-{"year":"2022","title":"FCM: Forgetful Causal Masking Makes Causal Language Models Better Zero-Shot Learners","authors":["H Liu, X Geng, L Lee, I Mordatch, S Levine, S Narang… - arXiv preprint arXiv …, 2022"],"snippet":"Large language models (LLM) trained using the next-token-prediction objective, such as GPT3 and PaLM, have revolutionized natural language processing in recent years by showing impressive zero-shot and few-shot capabilities across a wide …","url":["https://arxiv.org/pdf/2210.13432"]}
-{"year":"2022","title":"FD-GATDR: A Federated-Decentralized-Learning Graph Attention Network for Doctor Recommendation Using EHR","authors":["L Bi, Y Wang, F Zhang, Z Liu, Y Cai, E Zhao - arXiv preprint arXiv:2207.05750, 2022"],"snippet":"… The GloVe model is loaded with the pretrained parameters on Common Crawl which has 840B tokens and 2.2M vocab [11]. Each word is converted to a 300-dimension vector. Then the model is fine-tuned with LSTM for the classification. …","url":["https://arxiv.org/pdf/2207.05750"]}
-{"year":"2022","title":"Feasibility study of long-form question answering","authors":["S Antikainen - 2022"],"snippet":"Long-form question answering (LFQA) is a challenging natural language processing task as it asks to produce paragraph-length answers to questions. Meaningful progress in LFQA would significantly speed up how fast people can seek information …","url":["https://aaltodoc.aalto.fi/bitstream/handle/123456789/112850/master_Antikainen_Simo_2022.pdf?sequence=1"]}
-{"year":"2022","title":"Feature-based Question Routing in Community Question Answering Platforms","authors":["S Sorkhani, R Etemadi, A Bigdeli, M Zihayat, E Bagheri - Information Sciences, 2022"],"snippet":"… To do so, we use the Fasttext model with the pre-trained embeddings on the Common Crawl dataset 4 to obtain embedding vectors for question’s tags and tags of the questions answered by the user. Subsequently, we compute this feature for …","url":["https://www.sciencedirect.com/science/article/pii/S0020025522006661"]}
-{"year":"2022","title":"Few shot learning with fine-tuned language model for suicidal text detection","authors":["S Varma, S Shivam, B Ray, A Banerjee - 2022"],"snippet":"… The corpus used for pre-training the language model has been obtained from Wikipedia and Common crawl web scrapes which are vast and prone to have fairly low quality. Therefore, cleaning methods like deduplication, removal of incomplete …","url":["https://www.researchsquare.com/article/rs-2392230/latest.pdf"]}
-{"year":"2022","title":"Few-shot learning with language models: Learning from instructions and contexts","authors":["T Schick - 2022"],"snippet":"Pretraining deep neural networks to perform language modeling–that is, to reconstruct missing words from incomplete pieces of text–has brought large improvements throughout natural language processing (NLP). However, even …","url":["https://edoc.ub.uni-muenchen.de/29867/1/Schick_Timo.pdf"]}
-{"year":"2022","title":"Few-shot Learning with Retrieval Augmented Language Models","authors":["G Izacard, P Lewis, M Lomeli, L Hosseini, F Petroni… - arXiv preprint arXiv …, 2022"],"snippet":"… Another explanation might be that Wikipedia is a higher-quality and denser source of knowledge than common crawl. Second, when using a common crawl index, we observe that pre-training on Wikipedia data leads to lower performance …","url":["https://arxiv.org/pdf/2208.03299"]}
-{"year":"2022","title":"Few-Shot Natural Language Processing by Meta-Learning Without Labeled Data","authors":["T Bansal - 2022"],"snippet":"Humans show a remarkable capability to accurately solve a wide range of problems efficiently--utilizing a limited amount of computation and experience. Deep learning models, by stark contrast, can be trained to be highly accurate on a narrow task …","url":["https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=3507&context=dissertations_2"]}
-{"year":"2022","title":"Fight Against COVID-19 Misinformation via Clustering-Based Subset Selection Fusion Methods","authors":["Y Huang, Q Xu, S Wu, C Nugent, A Moore - 2022"],"snippet":"The worldwide COVID-19 pandemic has brought about a lot of changes in people’s life. It also emerges as a new challenge to information search services. This is because up to now our understanding about the virus is still limited, and there is a lot …","url":["http://ceur-ws.org/Vol-3138/paper2_jot.pdf"]}
-{"year":"2022","title":"Finding and Fixing Undesirable Behaviors in Pretrained Language Models","authors":["E Perez - 2022"],"snippet":"In machine learning, we often do not know how to specify the desired objective for our learning algorithms. For example, we typically train models to answer questions correctly by using a proxy objective: training models to answer questions as people …","url":["https://ethanperez.net/thesis.pdf"]}
-{"year":"2022","title":"Finding Memo: Extractive Memorization in Constrained Sequence Generation Tasks","authors":["V Raunak, A Menezes - arXiv preprint arXiv:2210.12929, 2022"],"snippet":"Memorization presents a challenge for several constrained Natural Language Generation (NLG) tasks such as Neural Machine Translation (NMT), wherein the proclivity of neural models to memorize noisy and atypical samples reacts adversely …","url":["https://arxiv.org/pdf/2210.12929"]}
-{"year":"2022","title":"Findings of the 2022 Conference on Machine Translation (WMT22)","authors":["T Kocmi, R Bawden, O Bojar, A Dvorkovich…"],"snippet":"This paper presents the results of the General Machine Translation Task organised as part of the Conference on Machine Translation (WMT) 2022. In the general MT task, participants were asked to build machine translation systems for any of 11 …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.1.pdf"]}
-{"year":"2022","title":"Findings of the WMT 2022 Biomedical Translation Shared Task: Monolingual Clinical Case Reports","authors":["M Neves, AJYA Siu, R Roller, P Thomas, MV Navarro…"],"snippet":"In the seventh edition of the WMT Biomedical Task, we addressed a total of seven language pairs, namely English/German, English/French, English/Spanish, English/Portuguese, English/Chinese, English/Russian, English/Italian. This year’s test sets covered …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.69.pdf"]}
-{"year":"2022","title":"Findings of the WMT 2022 shared task on large-scale machine translation evaluation for african languages","authors":["DI Adelani, MMI Alam, A Anastasopoulos, A Bhagia… - Proceedings of the Seventh …, 2022"],"snippet":"… We then performed bitext mining against 21.5 billion English sentences from Common Crawl, and 3.3 million sentences in French, respectively. These resources as well as the sentence encoders were made available to the participants of this …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.72.pdf"]}
-{"year":"2022","title":"Fine-grained Czech News Article Dataset: An Interdisciplinary Approach to Trustworthiness Analysis","authors":["M Boháček, M Bravanský, F Trhlík, V Moravec - arXiv preprint arXiv:2212.08550, 2022"],"snippet":"We present the Verifee Dataset: a novel dataset of news articles with fine-grained trustworthiness annotations. We develop a detailed methodology that assesses the texts based on their parameters encompassing editorial transparency, journalist …","url":["https://arxiv.org/pdf/2212.08550"]}
-{"year":"2022","title":"Fine-grained semantic type discovery for heterogeneous sources using clustering","authors":["F Piai, P Atzeni, P Merialdo, D Srivastava - The VLDB Journal, 2022"],"snippet":"We focus on the key task of semantic type discovery over a set of heterogeneous sources, an important data preparation task. We consider the challenging setting of multiple Web data sources in a vertical domain, which present sparsity of data and a …","url":["https://link.springer.com/article/10.1007/s00778-022-00743-3"]}
-{"year":"2022","title":"Fine-tuning and multilingual pre-training for abstractive summarization task for the Arabic language","authors":["M Kahla, A Novák, ZG Yang - Annales Mathematicae et Informaticae"],"snippet":"… We chose to download Arabic Deutsche Welle resources from Common Crawl4, as this solution does not interfere with the site. A very positive aspect of this resource is that the items downloaded from the DW news website address a wide range of …","url":["http://publikacio.uni-eszterhazy.hu/7512/1/AMI_online_1323.pdf"]}
-{"year":"2022","title":"Fine-tuning Pre-trained Language Models with Noise Stability Regularization","authors":["H Hua, X Li, D Dou, CZ Xu, J Luo - arXiv preprint arXiv:2206.05658, 2022"],"snippet":"The advent of large-scale pre-trained language models has contributed greatly to the recent progress in natural language processing. Many state-of-the-art language models are first trained on a large text corpus and then fine-tuned on downstream …","url":["https://arxiv.org/pdf/2206.05658"]}
-{"year":"2022","title":"FINE-TUNING TRANSFORMERS: ASSESSMENTS OF","authors":["Z Sun - 2022"],"snippet":"… in the development of pre-trained systems such as BERT [4](Bidirectional Encoder Representations from Transformers) and GPT [23](Generative Pre-trained Transformer), which was trained on large language datasets such as the Wikipedia …","url":["https://scholarworks.csun.edu/bitstream/handle/10211.3/223189/Sun-Zhen-thesis-2022.pdf?sequence=1"]}
-{"year":"2022","title":"FitLayout: An RDF-Based Framework and Toolkit for Web Page Content Analysis","authors":["R Burget, H Salem"],"snippet":"Despite the ongoing development of technologies that allow the publication of structured information within web pages, there still exist many web sources that publish useful data solely in the form of plain HTML documents. The data published …","url":["https://www.semantic-web-journal.net/system/files/swj3217.pdf"]}
-{"year":"2022","title":"FLightNER: A Federated Learning Approach to Lightweight Named-Entity Recognition","authors":["MPA Abadeer - 2022"],"snippet":"We introduce FLightNER, a Federated Learning model that extends a state-of-the-art Named-Entity Recognition model using prompt-tuning known as LightNER. FLightNER allows the aggregation of only the trainable parameters of LightNER …","url":["https://curve.carleton.ca/system/files/etd/3b9a9b49-620f-45df-a224-9ec2a6744015/etd_pdf/c91661bd3335b24f70ac9658f97e40e0/abadeer-flightnerafederatedlearningapproachtolightweight.pdf"]}
-{"year":"2022","title":"Forecasting Future World Events with Neural Networks","authors":["A Zou, T Xiao, R Jia, J Kwon, M Mazeika, R Li, D Song… - arXiv preprint arXiv …, 2022"],"snippet":"… To this end, we provide a corpus of news articles scraped from CommonCrawl news (Nagel, 2016; Hamborg et al., 2017) that is organized by publish date. The articles were generated between 2016 to mid-2022 and total more than 200GB of …","url":["https://arxiv.org/pdf/2206.15474"]}
-{"year":"2022","title":"Formal Mathematics Statement Curriculum Learning","authors":["S Polu, JM Han, K Zheng, M Baksys, I Babuschkin…"],"snippet":"We explore the use of expert iteration in the context of language modeling applied to formal mathematics. We show that at same compute budget, expert iteration, by which we mean proof search interleaved with learning, dramatically outperforms …","url":["https://cdn.openai.com/papers/Formal_Mathematics_Statement_Curriculum_Learning__ICML_2022.pdf"]}
-{"year":"2022","title":"Formulating Automated Responses to Cognitive Distortions for CBT Interactions","authors":["I de Toledo Rodriguez, G Salton, R Ross - … of The Fourth International Conference on …, 2021"],"snippet":"… 2020), trained on a cleaned version of the Common Crawl corpus (C4). The published model checkpoints have been pre-trained in a diverse variety of unsupervised and supervised tasks (language modelling, word embedding, machine translation …","url":["https://aclanthology.org/2021.icnlsp-1.13.pdf"]}
-{"year":"2022","title":"FP8 Formats for Deep Learning","authors":["P Micikevicius, D Stosic, N Burgess, M Cornea… - arXiv preprint arXiv …, 2022"],"snippet":"FP8 is a natural progression for accelerating deep learning training inference beyond the 16-bit formats common in modern processors. In this paper we propose an 8-bit floating point (FP8) binary interchange format consisting of two encodings …","url":["https://arxiv.org/pdf/2209.05433"]}
-{"year":"2022","title":"FPSRS: A Fusion Approach for Paper Submission Recommendation System","authors":["ST Huynh, N Dang, DH Nguyen, PT Huynh, BT Nguyen - arXiv preprint arXiv …, 2022"],"snippet":"… We remove single letters that likely do not have pretrained weights in wellknown pretrained word vectors like FastText Common Crawl4. 4. We remove words within stopwords downloaded from the Natural Language Toolkit (NLTK5) and additional …","url":["https://arxiv.org/pdf/2205.05965"]}
-{"year":"2022","title":"French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English","authors":["A Névéol, Y Dupont, J Bezançon, K Fort - ACL 2022-60th Annual Meeting of the …, 2022"],"snippet":"Warning: This paper contains explicit statements of offensive stereotypes which may be upsetting. Much work on biases in natural language processing has addressed biases linked to the social and cultural experience of English speaking individuals in …","url":["https://hal.inria.fr/hal-03629677/document"]}
-{"year":"2022","title":"From Bag-of-Words to Transformers: A Deep Dive into the Participation in the eRisk Early Risk Detection of Depression Tasks with Classical and New Approaches","authors":["H Damm, M Trotzek, S Koitka, H Schäfer… - … : The First Five Years of the …, 2022"],"snippet":"… 12 For this work, a 50-dimensional GloVe model trained on Wikipedia and the Gigaword 5 news corpus as well as a 300-dimensional GloVe model trained on Common Crawl were chosen. In addition, three 300-dimensional pre-trained …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=03KJEAAAQBAJ&oi=fnd&pg=PA61&dq=commoncrawl&ots=ilEvY4CTlF&sig=dsM8zq8Ay1-T1sLV96NBraKKox4"]}
-{"year":"2022","title":"From Bag-of-Words to Transformers: A Deep Dive into the Participation in the eRisk Tasks with Classical and New Approaches","authors":["H Damm, M Trotzek, S Koitka, H Schäfer… - Early Detection of Mental …, 2022"],"snippet":"… Footnote 12 For this work, a 50-dimensional GloVe model trained on Wikipedia and the Gigaword 5 news corpus as well as a 300-dimensional GloVe model trained on Common Crawl were chosen. In addition, three 300-dimensional pre-trained …","url":["https://link.springer.com/chapter/10.1007/978-3-031-04431-1_4"]}
-{"year":"2022","title":"From tabular data to knowledge graphs: A survey of semantic table interpretation tasks and methods","authors":["J Liu, Y Chabot, R Troncy, VP Huynh, T Labbé… - Journal of Web Semantics, 2022"],"snippet":"Tabular data often refers to data that is organized in a table with rows and columns. We observe that this data format is widely used on the Web and within enterprise data repositories. Tables potentially contain rich semantic information that still needs …","url":["https://www.sciencedirect.com/science/article/pii/S1570826822000452"]}
-{"year":"2022","title":"Fully Automated Detection of Formal Thought Disorder with Time-series Augmented Representations for Detection of Incoherent Speech (TARDIS)","authors":["W Xu, W Wang, J Portanova, A Chander, A Campbell… - Journal of Biomedical …, 2022"],"snippet":"… For the current research, we used publicly available pre-trained vectors derived using the FastText [39] package 8 consisting of 2-million-word vectors trained on a corpus derived from Common Crawl 9 . Individual words are represented by their …","url":["https://www.sciencedirect.com/science/article/pii/S1532046422000144"]}
-{"year":"2022","title":"Fusion of Remote Sensing Images and Social Media Text Messages for Building Function Classification","authors":["M Häberle - 2022"],"snippet":"Detailed data about urban land-use, like building functions, is useful to governments for resource planning. To detect building functions, satellite imagery could be too course. In this work, individual buildings from 42 cities are classified with multilingual …","url":["https://mediatum.ub.tum.de/doc/1637448/document.pdf"]}
-{"year":"2022","title":"FuzzyDedup: Secure Fuzzy Deduplication for Cloud Storage","authors":["T Jiang, X Yuan, Y Chen, K Cheng, L Wang, X Chen… - IEEE Transactions on …, 2022"],"snippet":"Data deduplication is of critical importance to reduce the storage cost for clients and to relieve the unnecessary storage pressure for cloud servers. While various techniques have been proposed for secure deduplication of identical files/blocks …","url":["https://ieeexplore.ieee.org/abstract/document/9804218/"]}
-{"year":"2022","title":"Galactica: A Large Language Model for Science","authors":["R Taylor, M Kardas, G Cucurull, T Scialom, A Hartshorn… - arXiv preprint arXiv …, 2022"],"snippet":"… While we do pick up some high-school level content through encyclopedias, textbooks and the filtered CommonCrawl, this amounts to a small quantity of tokens (a few billion). We leave the question of how to capture more of this base scientific …","url":["https://arxiv.org/pdf/2211.09085"]}
-{"year":"2022","title":"Gauge against the machine: improving representations within sociotechnical instruments to enrich context and identify biases","authors":["J Minot - 2022"],"snippet":"The proliferation of digital data across all areas of society has transformed our ability to hypothesize, study, and understand social systems. From this richness of data we have seen the development of innovative instruments to study---and make decisions …","url":["https://scholarworks.uvm.edu/cgi/viewcontent.cgi?article=2607&context=graddis"]}
-{"year":"2022","title":"Gauging Engagement: Measuring Student Response to a Large-Scale College Advising Field Experiment","authors":["BH Kim, K Meyer, A Choe"],"snippet":"Interactive, text message-based advising programs have become an increasingly common strategy to support college access and success for underrepresented student populations. Despite the proliferation of these programs, we know relatively …","url":["https://edworkingpapers.org/sites/default/files/ai22-567.pdf"]}
-{"year":"2022","title":"Gender and Racial Stereotype Detection in Legal Opinion Word Embeddings","authors":["S Matthews, J Hudzina, D Sepehr - 2022"],"snippet":"… In addition, the instrument/weapons control display equivalent effect sizes between Caliskan’s Common Crawl corpus experiments and the legal … Gender Effects: While the effect sizes were comparable between the Common Crawl corpus …","url":["https://www.aaai.org/AAAI22Papers/AISI-10870.MatthewsS.pdf"]}
-{"year":"2022","title":"Gender Bias in Machine Translation Systems","authors":["S Ullmann - Artificial Intelligence and Its Discontents, 2022"],"snippet":"… The data was originally obtained from Common Crawl, a free online repository consisting of large amounts of internet data. Consequently, the data represents a variety of registers from formal to informal, slang and even archaic vocabulary due to …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88615-8_7"]}
-{"year":"2022","title":"Gender Bias in Meta-Embeddings","authors":["M Kaneko, D Bollegala, N Okazaki - arXiv preprint arXiv:2205.09867, 2022"],"snippet":"Combining multiple source embeddings to create meta-embeddings is considered effective to obtain more accurate embeddings. Different methods have been proposed to develop meta-embeddings from a given set of source embeddings …","url":["https://arxiv.org/pdf/2205.09867"]}
-{"year":"2022","title":"Generating Extended and Multilingual Summaries with Pre-trained Transformers","authors":["R Calizzano, M Ostendorff, Q Ruan, G Rehm"],"snippet":"Almost all summarisation methods and datasets focus on a single language and short summaries. We introduce a new dataset called WikinewsSum for English, German, French, Spanish, Portuguese, Polish, and Italian summarisation tailored for …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.175.pdf"]}
-{"year":"2022","title":"Generating Full Length Wikipedia Biographies: The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographies","authors":["A Fan, C Gardent - arXiv preprint arXiv:2204.05879, 2022"],"snippet":"… Given a person’s name, one or more occupation(s), and CommonCrawl as a source of … name, one or more occupations, a section header, and CommonCrawl as a retrieval corpus. … We reject all CommonCrawl links from Wikipedia, to prevent …","url":["https://arxiv.org/pdf/2204.05879"]}
-{"year":"2022","title":"Generating Music using AI","authors":["E Rickard"],"snippet":"Network speakers are used in public spaces for public announcements and sometimes to play background music. To play music, a special commercial music licence is required, specifically made for use in public environments. However …","url":["https://lup.lub.lu.se/student-papers/record/9093922/file/9093927.pdf"]}
-{"year":"2022","title":"Generating Role-Playing Game Quest Descriptions With the GPT-2 Language Model","authors":["S Värtinen - 2022"],"snippet":"Recent advances in artificial intelligence research have brought forth text-generating language models with promising computational storytelling capabilities. This thesis leveraged one of the most successful Transformer models, GPT-2, to automatically …","url":["https://aaltodoc.aalto.fi/bitstream/handle/123456789/112852/master_V%C3%A4rtinen_Susanna_2022.pdf?sequence=1"]}
-{"year":"2022","title":"Generating Scientific Definitions with Controllable Complexity","authors":["T August, K Reinecke, NA Smith"],"snippet":"… We use scientific abstracts, rather than general audience text like Wikipedia or the Common Crawl, for two reasons. First, scientific terms are originally introduced and most commonly used in research papers, making them the most reliable source for …","url":["https://homes.cs.washington.edu/~reinecke/Publications_files/August_ACL2022.pdf"]}
-{"year":"2022","title":"Generating Word Embeddings for the Azerbaijani Language and Their Empirical Evaluation on Intrinsic and Extrinsic Evaluation Tasks","authors":["U Suleymanov - 2021"],"snippet":"… al. has also partitioned their data corpora into smaller datasets, such as Common Crawl, Wikipedia, WebText and etc. The machine learning architecture they have built, is one of the largest language models ever built with 175 billion parameters …","url":["http://dspace.khazar.org/bitstream/20.500.12323/5448/1/Generating%20Word%20Embeddings%20for%20the%20Azerbaijani%20Language%20and%20Their%20Empirical%20Evaluation%20on%20Intrinsic%20and%20Extrinsic%20Evaluation%20Tasks.pdf"]}
-{"year":"2022","title":"Getting along to get ahead: Predictors of success in an online competitive social environment","authors":["SR Curtis - 2022"],"snippet":"The University of Nevada, Reno Getting along to get ahead: Predictors of success in an online competitive social environment A d Page 1 The University of Nevada, Reno Getting along to get ahead: Predictors of success in an online competitive …","url":["https://scholarworks.unr.edu/bitstream/handle/11714/8172/Curtis_unr_0139D_13732.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Getting to the root of linguistic alignment: Testing the predictions of Interactive Alignment across developmental and biological variation in language skill","authors":["R Foushee, D Byrne, M Casillas, S Goldin-Meadow - 2022"],"snippet":"Linguistic alignment—the contingent reuse of our interlocutors' language at all levels of linguistic structure—pervades human dialogue. Here, we design unique measures to capture the degree of linguistic alignment between interlocutors' …","url":["https://osf.io/tqrew/download"]}
-{"year":"2022","title":"Global Readiness of Language Technology for Healthcare: What would it Take to Combat the Next Pandemic?","authors":["I Mondal, K Ahuja, M Jain, JO Neil, K Bali… - arXiv preprint arXiv …, 2022"],"snippet":"The COVID-19 pandemic has brought out both the best and worst of language technology (LT). On one hand, conversational agents for information dissemination and basic diagnosis have seen widespread use, and arguably, had an important …","url":["https://arxiv.org/pdf/2204.02790"]}
-{"year":"2022","title":"Global-locality preserving projection for word embedding","authors":["B Wang, Y Sun, Y Chu, Z Yang, H Lin - … Journal of Machine Learning and Cybernetics, 2022"],"snippet":"… -the Common Crawl corpus consisting of 840b tokens and a vocabulary containing 2.2 M words with 300-dimensional, the Common Crawl (… Here we use the pre-trained word embedding of the Common Crawl corpus (840b tokens, 2.2 M …","url":["https://link.springer.com/article/10.1007/s13042-022-01574-y"]}
-{"year":"2022","title":"GPT-3 and Friends: Transformers in Natural Language Processing","authors":["L Reber - FMS-BERICHTE, 2022"],"snippet":"In 2020, the British newspaper “The Guardian” published an editorial written in its entirety by an artificial intelligence called “Generative Pre-trained Transformer 3”. GPT-3 is one of several “Natural Language Processors”(NLPs), allowing a computer …","url":["https://www.researchgate.net/profile/Andrea-Reindl/publication/364180536_FMS-BERICHTE_SOMMERSEMESTER_2022/links/633d93879cb4fe44f305a2dc/FMS-BERICHTE-SOMMERSEMESTER-2022.pdf#page=63"]}
-{"year":"2022","title":"GPT-3 and InstructGPT: technological dystopianism, utopianism, and “Contextual” perspectives in AI ethics and industry","authors":["A Chan - AI and Ethics, 2022"],"snippet":"This paper examines the ethical solutions raised in response to OpenAI’s language model Generative Pre-trained Transformer-3 (GPT-3) a year and a half from its release. I argue that hype and fear about GPT-3, even within the Natural Language …","url":["https://link.springer.com/article/10.1007/s43681-022-00148-6"]}
-{"year":"2022","title":"GPT-3 for Few-Shot Dialogue State Tracking","authors":["N Pezzotti"],"snippet":"GPT-3 (Brown et al., 2020) has attracted considerable attention due to its superior performance across a wide range of Natural Language Processing (NLP) tasks, especially with its powerful and versatile in-context few-shot learning ability. That is …","url":["https://www.mlmi.eng.cam.ac.uk/files/2020-2021_dissertations/gpt_3_for_few_shot_dialogue_state_tracking.pdf"]}
-{"year":"2022","title":"GPT-NeoX-20B: An Open-Source Autoregressive Language Model","authors":["S Black, S Biderman, E Hallahan, Q Anthony, L Gao…"],"snippet":"GPT-NeoX-20B is a 20 billion parameter autoregressive language model whose weights will be made freely and openly available to the public through a permissive license. It is, to the best of our knowledge, the largest dense autoregressive model …","url":["http://eaidata.bmk.sh/data/GPT_NeoX_20B.pdf"]}
-{"year":"2022","title":"GPTs at Factify 2022: Prompt Aided Fact-Verification","authors":["PK Sahu, S Aggarwal, T Gupta, G Das - arXiv preprint arXiv:2206.14913, 2022","S Aggarwal, P Sahu, T Gupta, G Das - Proceedings of De-Factify: Workshop on …, 2022"],"snippet":"One of the most pressing societal issues is the fight against false news. The false claims, as difficult as they are to expose, create a lot of damage. To tackle the problem, fact verification becomes crucial and thus has been a topic of interest …","url":["http://ceur-ws.org/Vol-3199/paper11.pdf","https://arxiv.org/pdf/2206.14913"]}
-{"year":"2022","title":"Grammatical Error Correction: A Survey of the State of the Art","authors":["C Bryant, Z Yuan, MR Qorib, H Cao, HT Ng, T Briscoe - arXiv preprint arXiv …, 2022"],"snippet":"Grammatical Error Correction (GEC) is the task of automatically detecting and correcting errors in text. The task not only includes the correction of grammatical errors, such as missing prepositions and mismatched subject-verb agreement, but …","url":["https://arxiv.org/pdf/2211.05166"]}
-{"year":"2022","title":"Granular Emotion Detection for Multi-Class Sentiment Analysis in Social Media","authors":["RH Frye - 2022"],"snippet":"… XLNet was trained on many of the same or similar datasets as BERT and RoBERTa, including CommonCrawl, BooksCorpus, and English … A clean derivation of the CommonCrawl Corpus was used in pretraining XLM-R, with one …","url":["https://search.proquest.com/openview/19befd3b5703b8663bf55b49a0bbf582/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"GraphIC: A graph-based approach for identifying complaints from code-mixed product reviews","authors":["A Singh, S Saha - Expert Systems with Applications, 2022"],"snippet":"… Wikipedia’s and Common Crawl’s publicly available corpora for 17 Indian languages were employed for monolingual data. PMINDIA and Dakshina corpora were used to obtain translated and transliterated data for parallel segments. For code-mixed …","url":["https://www.sciencedirect.com/science/article/pii/S0957417422024630"]}
-{"year":"2022","title":"GREENER: Graph Neural Networks for News Media Profiling","authors":["P Panayotov, U Shukla, HT Sencar, M Nabeel, P Nakov - arXiv preprint arXiv …, 2022"],"snippet":"We study the problem of profiling news media on the Web with respect to their factuality of reporting and bias. This is an important but under-studied problem related to disinformation and \"fake news\" detection, but it addresses the issue at a …","url":["https://arxiv.org/pdf/2211.05533"]}
-{"year":"2022","title":"GRILLBot: A flexible conversational agent for solving complex real-world tasks","authors":["C Gemmell, S Fischer, I Mackie, P Owoicho, F Rossetto…"],"snippet":"… We use Common Crawl to download the raw HTML for target domains and develop website-specific wrappers to extract semi-structured information about each task, ie title, author, description, ingredients, images, steps, ratings, videos, etc. We …","url":["https://assets.amazon.science/0c/2c/f214256a43bba8d97ade42c56be0/grillbot-a-flexible-conversational-agent-for-solving-complex-real-world-tasks.pdf"]}
-{"year":"2022","title":"GRILLBot: A multi-modal conversational agent for complex real-world tasks","authors":["C Gemmell, F Rossetto, I Mackie, P Owoicho, S Fischer… - Proceedings of the 23rd …, 2022"],"snippet":"… We use Common Crawl to download the raw HTML for target domains and develop website-specific wrappers to extract semi-structured information about each task, ie title, author, description, ingredients, images, steps, ratings, videos, infoboxes, FAQs. …","url":["https://aclanthology.org/2022.sigdial-1.63.pdf"]}
-{"year":"2022","title":"GRILLBot: An Assistant for Real-World Tasks with Neural Semantic Parsing and Graph-Based Representations","authors":["C Gemmell, I Mackie, P Owoicho, F Rossetto, S Fischer… - arXiv preprint arXiv …, 2022"],"snippet":"… We use Common Crawl to download the raw HTML for target domains and develop website-specific wrappers to extract semi-structured information about each task, ie title, author, description, ingredients, images, steps, ratings, videos, infoboxes, FAQs. …","url":["https://arxiv.org/pdf/2208.14884"]}
-{"year":"2022","title":"Grounded Keys-to-Text Generation: Towards Factual Open-Ended Generation","authors":["F Brahman, B Peng, M Galley, S Rao, B Dolan… - arXiv preprint arXiv …, 2022"],"snippet":"… The documents are citations in the Wikipedia article obtained by CommonCrawl or web pages returned by Google Search. Each instance in our data has 40 grounding passages. Note that our dataset is distantly supervised, and these …","url":["https://arxiv.org/pdf/2212.01956"]}
-{"year":"2022","title":"Grounding Language by Seeing, Hearing, and Interacting","authors":["R Zellers - 2022"],"snippet":"As humans, our understanding of language is grounded in a rich mental model about \"how the world works.\" As children, we learn this mental model gradually. We take in raw perceptual input about the world through all of our senses, and learn to …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/48898/Zellers_washington_0250E_24408.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Grounding Language Models on External Sources: A Comparison of Knowledge Graphs and Unstructured Text","authors":["T Kaminski"],"snippet":"… To get an idea of the size, WebText, for example, consists of 40GB of text from 8 million documents scraped from the internet, but an even larger example is the corpus used to train T5 [81], named C4, which consists of 750GB of text derived from …","url":["https://isl.anthropomatik.kit.edu/downloads/BA-Tom-Kaminski-final.pdf"]}
-{"year":"2022","title":"GROWN+ UP: A Graph Representation Of a Webpage Network Utilizing Pre-training","authors":["B Yeoh, H Wang - arXiv preprint arXiv:2208.02252, 2022"],"snippet":"… We can also pre-train on a more massive set of webpages from an identical time period as the target domain, as opposed to the relatively small CommonCrawl 2008 corpus that we used for all benchmarks in this work. Lastly, integrating image, audio …","url":["https://arxiv.org/pdf/2208.02252"]}
-{"year":"2022","title":"HalBERT at PoliticEs 2022: Are Machine Learning Algorithms better for Author Profiling?","authors":["CG Holgado, A Sinha - Development, 2022"],"snippet":"This paper presents an investigation of different machine and deep learning models for Author Profiling for the Shared Task PoliticEs: Spanish Author Profiling for Political Ideology at IberLEF 2022. We provide a broad comparative study to see …","url":["http://ceur-ws.org/Vol-3202/politices-paper5.pdf"]}
-{"year":"2022","title":"Handling and Presenting Harmful Text","authors":["L Derczynski, HR Kirk, A Birhane, B Vidgen - arXiv preprint arXiv:2204.14256, 2022"],"snippet":"… enormous internet-scraped datasets such as Common Crawl Corpus or WebText. As these unstructured corpora become larger, the risk of them containing harmful content increases, and the larger the dataset, the more difficult it is for humans to …","url":["https://arxiv.org/pdf/2204.14256"]}
-{"year":"2022","title":"Hate Speech and Offensive Language Detection in Bengali","authors":["M Das, S Banerjee, P Saha, A Mukherjee - arXiv preprint arXiv:2210.03479, 2022"],"snippet":"… 2020) is another form of Transformer model, pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. XLM-R was trained using a lot more data compared to m-BERT. Similar to BERT, it is a stack of transformer encoder …","url":["https://arxiv.org/pdf/2210.03479"]}
-{"year":"2022","title":"Hate speech and offensive language detection in Dravidian languages using deep ensemble framework","authors":["PK Roy, S Bhawal, CN Subalalitha - Computer Speech & Language, 2022"],"snippet":"… It is pretrained with 2.5 TB of CommonCrawl data in 100 languages. Due to the absence of language embedding it can result in much better performances in the case of code-switching and are much better compared to multilingual BERT …","url":["https://www.sciencedirect.com/science/article/pii/S0885230822000250"]}
-{"year":"2022","title":"HC4: A New Suite of Test Collections for Ad Hoc CLIR","authors":["D Lawrie, J Mayfield, D Oard, E Yang - arXiv preprint arXiv:2201.09992, 2022","DW Oard, E Yang"],"snippet":"… First, to develop a multilingual document collection that was easy to distribute, we chose the Common Crawl News Collection as the basis for the suite of collections. We applied automatic language identification to determine the language of each …","url":["https://arxiv.org/pdf/2201.09992","https://terpconnect.umd.edu/~oard/pdf/ecir22lawrie.pdf"]}
-{"year":"2022","title":"Health Talk: Understanding Practices of Popular Professional YouTubers","authors":["TT Phan, C Michoud, L Volpato, M del Rio Carral… - 2022"],"snippet":"Practices related to health are circulated widely on YouTube. With a health psychology perspective, we present a study to understand health and wellbeing-related practices of a group of popular, professional YouTubers from the audio-visual …","url":["http://publications.idiap.ch/attachments/papers/2022/Phan_MUM_2022.pdf"]}
-{"year":"2022","title":"HeLI-OTS, Off-the-shelf Language Identifier for Text","authors":["T Jauhiainen, H Jauhiainen, K Lindén"],"snippet":"This paper introduces HeLI-OTS, an off-the-shelf text language identification tool using the HeLI language identification method. The HeLI-OTS language identifier is equipped with language models for 200 languages and licensed for academic as …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.416.pdf"]}
-{"year":"2022","title":"HICEM: A High-Coverage Emotion Model for Artificial Emotional Intelligence","authors":["B Wortman, JZ Wang - arXiv preprint arXiv:2206.07593, 2022"],"snippet":"… Trained on Common Crawl and Wikipedia, this model provides a 300-dimensional embedding for each word. FastText was chosen over … We then once again proceeded with Facebook’s FastText models which have been trained on Common …","url":["https://arxiv.org/pdf/2206.07593"]}
-{"year":"2022","title":"Hierarchical Agglomerative Graph Clustering in Poly-Logarithmic Depth","authors":["L Dhulipala, D Eisenstat, J Łącki, V Mirronki, J Shi - arXiv preprint arXiv:2206.11654, 2022"],"snippet":"Obtaining scalable algorithms for hierarchical agglomerative clustering (HAC) is of significant interest due to the massive size of real-world datasets. At the same time, efficiently parallelizing HAC is difficult due to the seemingly sequential nature of the …","url":["https://arxiv.org/pdf/2206.11654"]}
-{"year":"2022","title":"Hierarchical Graph Decomposition for Natural Language Generation","authors":["L Jin - 2022"],"snippet":"Central to natural language understanding and generation is the ability to accurately model the semantics of text. We can frame understanding as parsing a semantic form from a given sentence that represents all sentences of equivalent meaning …","url":["https://search.proquest.com/openview/8bba4ec7c1c89c32f0af8202a5fd0c9b/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding","authors":["L Liu, O Perez-Concha, A Nguyen, V Bennett, L Jorm - arXiv preprint arXiv …, 2022"],"snippet":"International Classification of Diseases (ICD) coding plays an important role in systematically classifying morbidity and mortality data. In this study, we propose a hierarchical label-wise attention Transformer model (HiLAT) for the explainable …","url":["https://arxiv.org/pdf/2204.10716"]}
-{"year":"2022","title":"Hierarchical template transformer for fine-grained sentiment controllable generation","authors":["L Yuan, J Wang, LC Yu, X Zhang - Information Processing & Management, 2022"],"snippet":"Existing methods for text generation usually fed the overall sentiment polarity of a product as an input into the seq2seq model to generate a relatively fluent review. However, these methods cannot express more fine-grained sentiment polarity …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322001546"]}
-{"year":"2022","title":"High-frequency words have higher frequencies in Turkish social sciences article","authors":["N Gürsakal, S Çelik, S Özdemir - Quality & Quantity, 2022"],"snippet":"Abstract Words, sentences, and paragraphs are the basis of texts. When we consider texts as data and want to establish a relationship between qualitative and quantitative perspectives, we can do this with the word frequencies in a text. We aim …","url":["https://link.springer.com/article/10.1007/s11135-022-01444-3"]}
-{"year":"2022","title":"High-Resource Methodological Bias in Low-Resource Investigations","authors":["M ter Hoeve, D Grangier, N Schluter - arXiv preprint arXiv:2211.07534, 2022"],"snippet":"The central bottleneck for low-resource NLP is typically regarded to be the quantity of accessible data, overlooking the contribution of data quality. This is particularly seen in the development and evaluation of low-resource systems via down sampling …","url":["https://arxiv.org/pdf/2211.07534"]}
-{"year":"2022","title":"Hints of Independence in a Pre-scripted World: On Controlled Usage of Open-domain Language Models for Chatbots in Highly Sensitive Domains","authors":["E Basar, I Hendrickx, E Krahmer, GJ de Bruijn, T Bosse - Proceedings of the 14th …, 2022"],"snippet":"… Because the training approach is unsupervised, it is possible to include a massive amount of data from various online sources, such as Wikipedia and CommonCrawl, with minimal human labour required. Hence, these neural language …","url":["https://www.scitepress.org/Papers/2022/109143/109143.pdf"]}
-{"year":"2022","title":"Hints of Independence Independence Independence in a Pre-scripted e-scripted e-scripted World: On Controlled Usage of Open-domain Open-domain Open-domain …","authors":["EBE Basar, I Hendrickx, E Krahmer, GJ de Bruijn… - 2022"],"snippet":"… Because the Because the Because the training approach is unsupervised, unsupervised, unsupervised, it is possible to include a massive amount of data from various online sources, such as Wikipedia and CommonCrawl, CommonCrawl …","url":["https://repository.uantwerpen.be/docstore/d:irua:11354"]}
-{"year":"2022","title":"Hipsters and the cool: A game theoretic analysis of identity expression, trends, and fads.","authors":["R Golman, EH Bugbee, A Jain, S Saraf - Psychological Review, 2021"],"snippet":"Cultural trends and popularity cycles can be observed all around us, yet our theories of social influence and identity expression do not explain what perpetuates these complex, often unpredictable social dynamics. We propose a theory of social identity …","url":["https://psycnet.apa.org/record/2022-16685-001"]}
-{"year":"2022","title":"Homepage2Vec: Language-Agnostic Website Embedding and Classification","authors":["S Lugeon, T Piccardi, R West - Proceedings of the International AAAI Conference on …, 2022"],"snippet":"… Following this intuition, we collected from Common Crawl,5 a large-scale sample of the Web, the 19 most frequent TLDs: .com, .org, .net, .info, … We consider the 30 most frequent metatags from a sample of the Common Crawl and represent their …","url":["https://ojs.aaai.org/index.php/ICWSM/article/download/19380/19152"]}
-{"year":"2022","title":"Homophobic and Hate Speech Detection Using Multilingual-BERT Model on Turkish Social Media","authors":["H Karayiğit, A Akdagli, Çİ ACI - Information Technology and Control, 2022"],"snippet":"… The GloVe algorithm used in this study is trained on Common Crawl [24]. There are 253K words in the vocabulary and the dimension size is 300. Training data is web-crawled multilingual text with 2,736B … Available: https:// commoncrawl.org/2021 …","url":["http://apbs.mersin.edu.tr/files/caci/Publications_003.pdf"]}
-{"year":"2022","title":"HOTTEST: Hate and offensive content identification in Tamil using transformers and enhanced STemming","authors":["R Rajalakshmi, S Selvaraj, P Vasudevan - Computer Speech & Language, 2022"],"snippet":"… It is a transformer-based model which is pre-trained on about 2500 Gigabytes of filtered CommonCrawl data. This data consists of texts from about 100 languages. The model is trained in a self-supervised manner which makes the model more …","url":["https://www.sciencedirect.com/science/article/pii/S0885230822000870"]}
-{"year":"2022","title":"How can we detect Homophobia and Transphobia? Experiments in a multilingual code-mixed setting for social media governance","authors":["BR Chakravarthi, A Hande, R Ponnusamy… - International Journal of …, 2022"],"snippet":"… XLM-R is pretrained over two terabytes of CommonCrawl data spanning over 100 languages to boost the performances in cross-lingual tasks. All these models use transformers as the building blocks of their architecture. The vital attribute is self-attention …","url":["https://www.sciencedirect.com/science/article/pii/S2667096822000623"]}
-{"year":"2022","title":"How Different is Stereotypical Bias in Different Languages?","authors":["IT Öztürk - 2022"],"snippet":"Recent studies have demonstrated how to assess the stereotypical bias in pre-trained mono-lingual language models for the English language. In this master thesis, we extend this approach to multi-lingual models and multiple languages to show the …","url":["https://epub.ub.uni-muenchen.de/93576/1/Oeztuerk_Tolga_Komp.pdf"]}
-{"year":"2022","title":"How Effective is Byte Pair Encoding for Out-Of-Vocabulary Words in Neural Machine Translation?","authors":["A Araabi, C Monz, V Niculae - arXiv preprint arXiv:2208.05225, 2022"],"snippet":"Neural Machine Translation (NMT) is an open vocabulary problem. As a result, dealing with the words not occurring during training (aka out-of-vocabulary (OOV) words) have long been a fundamental challenge for NMT systems. The predominant …","url":["https://arxiv.org/pdf/2208.05225"]}
-{"year":"2022","title":"How good can an automatic translation of Pokémon names be?","authors":["L Talec-Bernarda - Proceedings of the Working Notes of CLEF, 2022"],"snippet":"For those of you who are not familiar with the successful franchise of Pokémon, it revolves around imaginary creatures often representing animals mixed with objects, plants, etc. Their names reflect these characteristics and are, most of the time …","url":["http://ceur-ws.org/Vol-3180/paper-145.pdf"]}
-{"year":"2022","title":"How Using a Foreign Language Influences Perceived Fairness","authors":["G Yu-Buck, A Mishra, H Mishra - ACR North American Advances, 2021"],"snippet":"… We used pre-trained word embedding vectors that were trained with the fastText algorithm and the Common Crawl corpus. The association between the fairness construct and each review is the dependent variable. We followed the procedure of …","url":["https://www.acrwebsite.org/volumes/v49/acr_vol49_3001028.pdf"]}
-{"year":"2022","title":"HTML Violations and Where to Find Them: A Longitudinal Analysis of Specification Violations in HTML","authors":["F Hantke, B Stock - 2022"],"snippet":"… To this end, we identify securityrelevant violations and leverage Common Crawl to check archived pages for these. Using this framework, we automatically analyze over 23K popular domains over time. This analysis reveals that while the number of …","url":["https://swag.cispa.saarland/papers/hantke2022violations.pdf"]}
-{"year":"2022","title":"Human Behavior in Domestic Environments: Prediction and Applications","authors":["S Zehtabian - 2021"],"snippet":"… However, many deep learning algorithms work best under big data regimes, where the number of data samples is counted from the tens of thousands (eg the MNIST dataset) to 500 billion (the Common Crawl dataset used to train the GPT-3 …","url":["https://stars.library.ucf.edu/cgi/viewcontent.cgi?article=1944&context=etd2020"]}
-{"year":"2022","title":"Human-Guided Generation of Sketches and Prototypes","authors":["ZF Huang - 2022"],"snippet":"Sketching and prototyping are central to creative activities that improve and advance many aspects of human lives. They enable non-experts to express themselves through drawing, or help User Interface (UI) designers explore diverse alternatives …","url":["https://escholarship.org/content/qt7tq101kp/qt7tq101kp.pdf"]}
-{"year":"2022","title":"HUMAN-INSPIRED COMPUTER VISION & REASONING","authors":["HJ Yi, J Tang, LJ Yu, WM Xuan"],"snippet":"… We used 300-dimensional GloVe vectors for the word embedding layer, which are pre-trained on the Common Crawl corpus consisting of 840B tokens and a 2.2M words vocabulary list [6]. GloVe vectors act as a non-trainable base to learn …","url":["https://www.dsta.gov.sg/ydsp/projects/pdf/research/reports/human-inspired-computer-vision-reasoning.pdf"]}
-{"year":"2022","title":"HW-TSC's Submissions to the WMT 2022 General Machine Translation Shared Task","authors":["D Wei, Z Rao, Z Wu, S Li, Y Luo, Y Xie, X Chen… - Proceedings of the Seventh …, 2022"],"snippet":"… It should be noted that in order to obtain better performance in the general domain, we mix the monolingual data from Common Crawl and News Crawl. … On En→Ru, after the Common Crawl monolingual is added, we observe 2.0 BLEU improvement …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.36.pdf"]}
-{"year":"2022","title":"Hybrid Architecture Based Intelligent Diagnosis Assistant for GP","authors":["R Wang, K Jayathunge, R Page, H Li, J Zhang, X Yang - Authorea Preprints, 2022"],"snippet":"… As mentioned in the introduction part, there mainly four pre-trained word embedding models, because of the wide coverage of different semantic lexical, the ‘crawl-300d-2M.vec’[29] (2-millionword vectors trained on Common Crawl (600B tokens)) of the Google’s …","url":["https://www.authorea.com/doi/pdf/10.22541/au.166741827.78885041"]}
-{"year":"2022","title":"Hypernymy Detection for Low-resource Languages: A Study for Hindi, Bengali, and Amharic","authors":["A Jana, G Venkatesh, SM Yimam, C Biemann - Transactions on Asian and Low …, 2022"],"snippet":"… Even though the focus of our study is not claiming superiority of the distributional semantic models over fastText, given that DT embeddings are prepared from a smaller corpus as compared to the corpus (Wikipedia, Common Crawl) on which …","url":["https://dl.acm.org/doi/abs/10.1145/3490389"]}
-{"year":"2022","title":"HyperTree Proof Search for Neural Theorem Proving","authors":["G Lample, MA Lachaux, T Lavril, X Martinet, A Hayat… - arXiv preprint arXiv …, 2022"],"snippet":"We propose an online training procedure for a transformer-based automated theorem prover. Our approach leverages a new search algorithm, HyperTree Proof Search (HTPS), inspired by the recent success of AlphaZero. Our model learns from …","url":["https://arxiv.org/pdf/2205.11491"]}
-{"year":"2022","title":"iCAR: Bridging Image Classification and Image-text Alignment for Visual Recognition","authors":["Y Wei, Y Cao, Z Zhang, Z Yao, Z Xie, H Hu, B Guo - arXiv preprint arXiv:2204.10760, 2022"],"snippet":"… It extracts image-caption pairs in random web pages crawled between 2014 and 2021 from the Common Crawl web data, and de-noises the dataset by scoring and filtering numerous raw pairs with a threshold using a CLIP ViT-B/32 [40] model …","url":["https://arxiv.org/pdf/2204.10760"]}
-{"year":"2022","title":"iCompass at CheckThat! 2022: ARBERT and AraBERT for Arabic Checkworthy Tweet Identification","authors":["B Taboubi, MAB Nessir, H Haddad - 2022"],"snippet":"This paper provides a detailed overview of systems and its achieved results, which were produced as part of CLEF2022-Check-That! Lab Fighting the COVID-19 Infodemic and Fake News Detection. The task was carried out using transformers pre-trained …","url":["http://ceur-ws.org/Vol-3180/paper-57.pdf"]}
-{"year":"2022","title":"Idea Mining From Online Reviews Using Transformation-Based Natural Language Processing Tasks","authors":["HF Mahdi, LK Gupta, T Choudhury, N Bansal - 2022 International Symposium on …, 2022"],"snippet":"Product reviews from online communities are good sources to innovative ideas. Making use of this unstructured data from these reviews is a complicated process. The major task of identifying good ideas is ensuring the correct reviews are picked …","url":["https://ieeexplore.ieee.org/abstract/document/9932785/"]}
-{"year":"2022","title":"Identifying Implicitly Abusive Remarks about Identity Groups using a Linguistically Informed Approach","authors":["M Wiegand, E Eder, J Ruppenhofer - Proceedings of the 2022 Conference of the …, 2022"],"snippet":"… regression classifier where each verb was represented by its (publicly available) word embedding induced on Common Crawl (Mikolov et al.… As features, we represented each verb by its word embedding from Common Crawl. (Using such a …","url":["https://aclanthology.org/2022.naacl-main.410.pdf"]}
-{"year":"2022","title":"Identifying Opinion Based Questions in Developer Chat Communication","authors":["K Muthu Subash - 2022"],"snippet":"… We have used a general GloVe [108] that uses a common crawl with 42B tokens, 1.9M vocabulary, and 300− dimensional vectors. GloVe Twitter [108] was a common crawl with 27B tokens, 1.2M vocabulary, and 200− dimensional vectors. We have …","url":["https://curve.carleton.ca/system/files/etd/c1f5bab8-ffe1-4dfc-9dd9-5850a5ad1bd7/etd_pdf/91899acd83d9b05a969f14e6a14dfa0a/muthusubash-identifyingopinionbasedquestionsindeveloper.pdf"]}
-{"year":"2022","title":"IDEOLOGY DETECTION USING TRANSFORMER-BASED MACHINE LEARNING MODELS","authors":["O ÖZTÜRK, A ÖZCAN"],"snippet":"Ideology detection has been a challenging but essential problem that has been studied for a long time. Certain groups and organizations, such as politicians, rely on people’s political views to make wise or forward-looking decisions. In the previous …","url":["https://www.researchgate.net/profile/Oktay-Ozturk-3/publication/357660800_Ideology_Detection_Using_Transformer-Based_Machine_Learning_Models/links/61d87712e669ee0f5c8f1b97/Ideology-Detection-Using-Transformer-Based-Machine-Learning-Models.pdf"]}
-{"year":"2022","title":"IDK-MRC: Unanswerable Questions for Indonesian Machine Reading Comprehension","authors":["RA Putri, A Oh - arXiv preprint arXiv:2210.13778, 2022"],"snippet":"… These language models are mostly pre-trained on the common-crawl dataset, which may contain harmful biases or stereotypes. All datasets in this work are publicly available and distributed under CC BY-SA 4.0 license. Our data collection …","url":["https://arxiv.org/pdf/2210.13778"]}
-{"year":"2022","title":"IELM: An Open Information Extraction Benchmark for Pre-Trained Language Models","authors":["C Wang, X Liu, D Song - arXiv preprint arXiv:2210.14128, 2022"],"snippet":"We introduce a new open information extraction (OIE) benchmark for pre-trained language models (LM). Recent studies have demonstrated that pre-trained LMs, such as BERT and GPT, may store linguistic and relational knowledge. In particular …","url":["https://arxiv.org/pdf/2210.14128"]}
-{"year":"2022","title":"IgboBERT Models: Building and Training Transformer Models for the Igbo Language","authors":["C Chukwuneke, I Ezeani, P Rayson, M El-Haj"],"snippet":"This work presents a standard Igbo named entity recognition (IgboNER) dataset as well as the results from training and fine-tuning state-of-the-art transformer IgboNER models. We discuss the process of our dataset creation-data collection and …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.547.pdf"]}
-{"year":"2022","title":"IIT Bombay's WMT22 Automatic Post-Editing Shared Task Submission","authors":["S Deoghare, P Bhattacharyya"],"snippet":"This paper describes IIT Bombay’s submission to the WMT-22 Automatic Post-Editing (APE) shared task for the English-Marathi (En-Mr) language pair. We follow the curriculum training strategy to train our APE system. First, we train an encoder-decoder …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.67.pdf"]}
-{"year":"2022","title":"Image Captioning for Thai Cultures","authors":["S Watcharabutsarakham, S Marukatat… - 2022 17th International Joint …, 2022"],"snippet":"Before each trip, tourists generally gather information or photos from different places. This work aims at providing additional information about touristic sites in Thailand via automatic image captioning. Image captioning is the process of generating a …","url":["https://ieeexplore.ieee.org/abstract/document/9960251/"]}
-{"year":"2022","title":"Imbalanced data as risk factor of discriminating automated decisions","authors":["A Vetrò - 2021"],"snippet":"… experiment on the search engine Common Crawl [17]. The authors compared three techniques of machine learning for occupational classification with almost 400.000 collected biographies. In all cases, even without explicitly using gender …","url":["https://www.jipitec.eu/issues/jipitec-12-4-2021/5452/vetro_pdf.pdf"]}
-{"year":"2022","title":"Impact of convolutional neural network and FastText embedding on text classification","authors":["M Umer, Z Imtiaz, M Ahmad, M Nappi, C Medaglia… - Multimedia Tools and …, 2022"],"snippet":"… It contains 2 million common crawl words with 300 −dimensions, providing 600 billion word-vectors. It uses hand-crafted n-grams as features in addition to single words. Text classification is performed very effectively and efficiently because of its …","url":["https://link.springer.com/article/10.1007/s11042-022-13459-x"]}
-{"year":"2022","title":"Impact of preprocessing and word embedding on extreme multi-label patent classification tasks","authors":["G Jung, J Shin, S Lee - Applied Intelligence, 2022"],"snippet":"… The Word2Vec pre-trained model learned approximately 3 million words using GoogleNews as a dataset, whereas the GloVe pre-trained model learned approximately 2.2 million words using the Common Crawl dataset [30, 31]. Because …","url":["https://link.springer.com/article/10.1007/s10489-022-03655-5"]}
-{"year":"2022","title":"Impact of Pretraining Term Frequencies on Few-Shot Reasoning","authors":["Y Razeghi, RL Logan IV, M Gardner, S Singh - arXiv preprint arXiv:2202.07206, 2022"],"snippet":"Pretrained Language Models (LMs) have demonstrated ability to perform numerical reasoning by extrapolating from a few examples in few-shot settings. However, the extent to which this extrapolation relies on robust reasoning is unclear. In this paper …","url":["https://arxiv.org/pdf/2202.07206"]}
-{"year":"2022","title":"Impact of Sentence Representation Matching in Neural Machine Translation","authors":["H Jung, K Kim, JH Shin, SH Na, S Jung, S Woo - Applied Sciences, 2022"],"snippet":"… To build a training set, we merged the Europarl parallel corpus and the Common-crawl corpus released from WMT-14 (http://www.statmt.org/wmt14/, accessed on 18 January 2022). We applied tokenizing and lowercasing and limited the length of …","url":["https://www.mdpi.com/2076-3417/12/3/1313/pdf"]}
-{"year":"2022","title":"Impact of Tokenization on Language Models: An Analysis for Turkish","authors":["C Toraman, EH Yilmaz, F Şahinuç, O Ozcelik - arXiv preprint arXiv:2204.08832, 2022"],"snippet":"… OSCAR is a multilingual corpus that is obtained by filtering of the Common Crawl corpus that maintain an open repository of publicly available web pages. We use the split of this corpus prepared for Turkish. However, we observe that this split includes …","url":["https://arxiv.org/pdf/2204.08832"]}
-{"year":"2022","title":"Implementación de algoritmos de reducción de sesgo en WEFE","authors":["MJ Zambrano Burrows - 2022"],"snippet":"Se ha demostrado en los últimos años que los modelos de word embeddings logran captar los sesgos presentes en los corpus de los que son entrenados, aprendiendo relaciones con estereotipos de género, raciales, entre otros. A modo de abordar el …","url":["https://repositorio.uchile.cl/bitstream/handle/2250/188824/Implementacion-de-algoritmos-de-reduccion-de-sesgo-en-WEFE.pdf?sequence=1"]}
-{"year":"2022","title":"Implicit Social Cognition","authors":["B Kurdi, MR Banaji"],"snippet":"Among the central features of the mind that drive social behavior are the attitudes and beliefs that humans bring to their engagement with other humans. Accordingly, ever since the inception of the field, research in social psychology has been guided …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=wD90EAAAQBAJ&oi=fnd&pg=PA323&dq=commoncrawl&ots=cFuiqkafcD&sig=PPJezjT4cihMsBdiO_1wITIQ09w"]}
-{"year":"2022","title":"Improved Zero-Shot Audio Tagging & Classification with Patchout Spectrogram Transformers","authors":["P Primus, G Widmer - arXiv preprint arXiv:2208.11402, 2022"],"snippet":"… We choose Word2Vec and Glove models that are pre-trained on the Google News and the Common Crawl dataset, respectively. Both produce embedding vectors of size 300. To embed textual labels made out of multiple words (eg, fire truck) …","url":["https://arxiv.org/pdf/2208.11402"]}
-{"year":"2022","title":"Improving Address Sequence Tagger Using Geographical Context","authors":["L Eriksson, M Olsson"],"snippet":"For humans, parsing an address into its components such as street and city is easy but time-consuming. Computers can have a harder time with such tasks. There are existing tools that use machine learning which has proven to be effective but still …","url":["https://lup.lub.lu.se/student-papers/record/9085667/file/9085668.pdf"]}
-{"year":"2022","title":"Improving BERTScore for Machine Translation Evaluation Through Contrastive Learning","authors":["O Yousuf - 2022"],"snippet":"… Scaled to one hundred languages, XLM-RoBERTa was pre-trained on 2.5TB of filtered CommonCrawl data (CC-100). However, it is … Furthermore, quality of data also poses challenges, as CommonCrawl or parallel localization data from projects …","url":["https://www.diva-portal.org/smash/get/diva2:1671848/FULLTEXT01.pdf"]}
-{"year":"2022","title":"Improving Bilingual Lexicon Induction with Cross-Encoder Reranking","authors":["Y Li, F Liu, I Vulić, A Korhonen - arXiv preprint arXiv:2210.16953, 2022"],"snippet":"… Panlex-BLI does not provide processed WEs, so we follow the original instructions from the authors and adopt fastText WEs trained on Common Crawl + Wikipedia.The WEs are trimmed to the most frequent 200k words for each language …","url":["https://arxiv.org/pdf/2210.16953"]}
-{"year":"2022","title":"Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles","authors":["S Ye, Y Xie, D Chen, Y Xu, L Yuan, C Zhu, J Liao - arXiv preprint arXiv:2211.16504, 2022"],"snippet":"This paper focuses on analyzing and improving the commonsense ability of recent popular vision-language (VL) models. Despite the great success, we observe that existing VL-models still lack commonsense knowledge/reasoning ability (eg, \"Lemons …","url":["https://arxiv.org/pdf/2211.16504"]}
-{"year":"2022","title":"Improving Domain-specific Cross-lingual Embeddings with Automatically Generated Bilingual Dictionaries","authors":["P Singh, AR Terryn, E Lefever - Computational Linguistics in the Netherlands Journal, 2022"],"snippet":"… To investigate this, we trained a set of FastText embeddings in English, initialised using the same Common Crawl and Wikipedia … Since the PubMed data would be vastly different from the Common Crawl and Wikipedia corpora, we can assume this …","url":["https://clinjournal.org/clinj/article/download/151/159"]}
-{"year":"2022","title":"Improving End-to-end Speech Translation by Leveraging Auxiliary Speech and Text Data","authors":["Y Zhang, C Xu, B Hu, C Zhang, T Xiao, J Zhu - arXiv preprint arXiv:2212.01778, 2022"],"snippet":"We present a method for introducing a text encoder into pre-trained end-to-end speech translation systems. It enhances the ability of adapting one modality (ie, source-language speech) to another (ie, source-language text). Thus, the speech …","url":["https://arxiv.org/pdf/2212.01778"]}
-{"year":"2022","title":"Improving Language Model Predictions via Prompts Enriched with Knowledge Graphs","authors":["R Brate, MH Dang, F Hoppe, Y He, A Meroño-Peñuela… - Workshop on Deep …, 2022"],"snippet":"… These entities are embedded in HTML pages on the web using Microformat, Microdata and RDFa from the Common Crawl web corpus, the largest and most up-to-date data web corpus available to the public. As more and more websites embed …","url":["https://www.fiz-karlsruhe.de/sites/default/files/FIZ/Dokumente/Forschung/ISE/Publications/Conferences-Workshops/Improving-Language-Model-Predictions-via_Prompts-Enriched-with-Knowledge-Graphs-HOPPE-DL4KG%40ISWC2022.pdf"]}
-{"year":"2022","title":"Improving Neural Question Answering with Retrieval and Generation","authors":["PSH Lewis - 2022"],"snippet":"Text-based Question Answering (QA) is a subject of interest both for its practical applications, and as a test-bed to measure the key Artificial Intelligence competencies of Natural Language Processing (NLP) and the representation and …","url":["https://discovery.ucl.ac.uk/id/eprint/10151750/2/Patrick_Lewis_Thesis__for_submission_to_UCL_.pdf"]}
-{"year":"2022","title":"Improving open text matching in a communication serious game","authors":["A Ungureanu - 2022"],"snippet":"… The ”clips/mfaq” model I am using for this application is pretrained on the ”MFAQ” [21] dataset, which is a multilingual corpus of Frequently Asked Questions parsed from the Common CrawlCommon Crawl is an open-source database of web crawling …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/43284/Andrei_Ungureanu_Master_Thesis.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Improving searchability of datasets","authors":["E Kacprzak - 2022"],"snippet":"Data is one of the most important digital assets in the world thanks to its business and social value. As is becoming increasingly available online, in order to use it effectively, we need tools that allow us to retrieve the most relevant datasets that …","url":["https://eprints.soton.ac.uk/457260/1/Emilia_Kacprzak_PhD_WAIS_27_March.pdf"]}
-{"year":"2022","title":"Improving Sentiment Analysis By Emotion Lexicon Approach on Vietnamese Texts","authors":["AL Doan, ST Luu - arXiv preprint arXiv:2210.02063, 2022"],"snippet":"The sentiment analysis task has various applications in practice. In the sentiment analysis task, words and phrases that represent positive and negative emotions are important. Finding out the words that represent the emotion from the text can …","url":["https://web7.arxiv.org/pdf/2210.02063"]}
-{"year":"2022","title":"Improving Short Text Classification With Augmented Data Using GPT-3","authors":["S Balkus, D Yan - arXiv preprint arXiv:2205.10981, 2022"],"snippet":"GPT-3 is a large-scale natural language model developed by OpenAI that can perform many different tasks, including topic classification. Although researchers claim that it requires only a small number of in-context examples to learn a task, in …","url":["https://arxiv.org/pdf/2205.10981"]}
-{"year":"2022","title":"Improving Taxonomy-based Categorization with Categorical Graph Neural Networks","authors":["T Du, K Chang, P Liu, R Zhang - 2021 IEEE International Conference on Big Data …, 2021"],"snippet":"… Then each query was converted to a 300-dimensional embedding by averaging each word’s FastText embedding [23] (pretrained on the common-crawl dataset). Each FastText word embedding was L2 normalized before use. The query …","url":["https://ieeexplore.ieee.org/abstract/document/9671372/"]}
-{"year":"2022","title":"Improving the Accessibility of Arabic Electronic Theses and Dissertations (ETDs) with Metadata and Classification","authors":["E Abdelrahman - 2021"],"snippet":"Much research work has been done to extract data from scientific papers, journals, and articles. However, Electronic Theses and Dissertations (ETDs) remain an unexplored genre of data in the research fields of natural language processing and …","url":["https://vtechworks.lib.vt.edu/bitstream/handle/10919/107790/Abdelrahman_E_T_2021.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Improving the Robustness of Summarization Models by Detecting and Removing Input Noise","authors":["K Krishna, Y Zhao, J Ren, B Lakshminarayanan, J Luo… - arXiv preprint arXiv …, 2022"],"snippet":"The evaluation of abstractive summarization models typically uses test data that is identically distributed as training data. In real-world practice, documents to be summarized may contain input noise caused by text extraction artifacts or data …","url":["https://arxiv.org/pdf/2212.09928"]}
-{"year":"2022","title":"Improving Word Translation via Two-Stage Contrastive Learning","authors":["Y Li, F Liu, N Collier, A Korhonen, I Vulić - arXiv preprint arXiv:2203.08307, 2022"],"snippet":"Word translation or bilingual lexicon induction (BLI) is a key cross-lingual task, aiming to bridge the lexical gap between different languages. In this work, we propose a robust and effective two-stage contrastive learning framework for the BLI …","url":["https://arxiv.org/pdf/2203.08307"]}
-{"year":"2022","title":"In Situ Answer Sentence Selection at Web-scale","authors":["Z Zhang, T Vu, A Moschitti - arXiv preprint arXiv:2201.05984, 2022"],"snippet":"… Question Sampling We sample the questions from a large collection of information inquiries collected from Web data, eg, CommonCrawl. … The candidates are extracted from 30MM passages, retrieved from a large index having …","url":["https://arxiv.org/pdf/2201.05984"]}
-{"year":"2022","title":"In-context Examples Selection for Machine Translation","authors":["S Agrawal, C Zhou, M Lewis, L Zettlemoyer… - arXiv preprint arXiv …, 2022"],"snippet":"… As XGLM is trained on monolingual Common Crawl snapshots, translation in any domain and language could be considered an out-of-domain task from the model’s perspective. However, we hypothesize that translation in specific domains like …","url":["https://arxiv.org/pdf/2212.02437"]}
-{"year":"2022","title":"INAUGURAL ARTICLE by a Recently Elected Academy Member: When danger strikes: A linguistic tool for tracking America's collective response to threats","authors":["VK Choi, S Shrestha, X Pan, MJ Gelfand - Proceedings of the National Academy of …, 2022"],"snippet":"In today’s vast digital landscape, people are constantly exposed to threatening language, which attracts attention and activates the human brain’s fear circuitry. However, to date, we have lacked the tools needed to identify threatening language …","url":["https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8795557/"]}
-{"year":"2022","title":"IndicXNLI: Evaluating Multilingual Inference for Indian Languages","authors":["D Aggarwal, V Gupta, A Kunchukuttan - arXiv preprint arXiv:2204.08776, 2022"],"snippet":"… XLM-RoBERTa is pre-trained using the common crawl monolingual data. mBERT (cased/uncased) includes pre-training on nine of eleven Indic lan… These model use the Indic enrich monolingual corpora: Common Crawl, Oscar and IndicCorp and …","url":["https://arxiv.org/pdf/2204.08776"]}
-{"year":"2022","title":"IndicXTREME: A Multi-Task Benchmark For Evaluating Indic Languages","authors":["S Doddapaneni, R Aralikatte, G Ramesh, S Goyal… - arXiv preprint arXiv …, 2022"],"snippet":"In this work, we introduce IndicXTREME, a benchmark consisting of nine diverse tasks covering 18 languages from the Indic sub-continent belonging to four different families. Across languages and tasks, IndicXTREME contains a total of 103 …","url":["https://arxiv.org/pdf/2212.05409"]}
-{"year":"2022","title":"Indonesian Hoax News Classification with Multilingual Transformer Model and BERTopic","authors":["LB Hutama, D Suhartono - Informatica, 2022"],"snippet":"… The most prominent development of the XLM-R model lies in the size of the dataset used where XLM-R is trained using 2.5TB of Common Crawl data in 100 languages, making the XLM-R model superior to previous multi-language models …","url":["https://www.informatica.si/index.php/informatica/article/viewFile/4336/1920"]}
-{"year":"2022","title":"InfoDCL: A Distantly Supervised Contrastive Learning Framework for Social Meaning","authors":["C Zhang, M Abdul-Mageed, G Jawahar - arXiv preprint arXiv:2203.07648, 2022"],"snippet":"Existing supervised contrastive learning frameworks suffer from two major drawbacks: (i) they depend on labeled data, which is limited for the majority of tasks in real-world, and (ii) they incorporate inter-class relationships based on instance-level information …","url":["https://arxiv.org/pdf/2203.07648"]}
-{"year":"2022","title":"Inria-ALMAnaCH at the WMT 2022 shared task: Does Transcription Help Cross-Script Machine Translation?","authors":["JO Alabi, L Nishimwe, B Muller, C Rey, B Sagot… - Proceedings of the Seventh …, 2022"],"snippet":"This paper describes the Inria ALMAnaCH team submission to the WMT 2022 general translation shared task. Participating in the language directions {cs,ru,uk}→en and cs↔uk, we experiment with the use of a dedicated Latin-script transcription …","url":["https://hal.inria.fr/hal-03836180/document"]}
-{"year":"2022","title":"Insights from heterogeneous data through transitive semantic relationships and text analytics","authors":["D Ralph - 2022"],"snippet":"Many organisations are finding that the volume of information they need to analyse to make effective decisions is increasing. An important element in effective decision making is the ability to prioritise information quickly and accurately from a variety of …","url":["https://eprints.soton.ac.uk/470732/1/David_Ralph_PhD_Thesis.pdf"]}
-{"year":"2022","title":"Instance-Specific Feature Propagation for Referring Segmentation","authors":["C Liu, X Jiang, H Ding - IEEE Transactions on Multimedia, 2022"],"snippet":"… We follow prior work [12], [36] and adopt the GloVe word embeddings [32] on Common Crawl 840B tokens. We use Adam with the base learning rate of 0.001 for optimization. Images are resized to 416 × 416 before sending to the network, and …","url":["https://ieeexplore.ieee.org/abstract/document/9745353/"]}
-{"year":"2022","title":"Integrating character-level and word-level representation for affect in Arabic tweets","authors":["AI Alharbi, P Smith, M Lee - Data & Knowledge Engineering, 2022"],"snippet":"Affect tasks, which range from sentiment polarity classification to finer grained sentiment strength and emotional intensity detection, have become of increasing interest due to the vast amount of user-generated content and advanced learning …","url":["https://www.sciencedirect.com/science/article/pii/S0169023X21000938"]}
-{"year":"2022","title":"Integrating Product Data using Deep Learning","authors":["R Peeters, C Bizer - Proceedings of the 7th bwHPC Symposium, 2022"],"snippet":"… A successful approach for dealing with the heterogeneity of product offers is to combine deep learning-based matching techniques with large amounts of training data which can be extracted from Web corpora such as the Common Crawl. Training …","url":["https://oparu.uni-ulm.de/xmlui/bitstream/handle/123456789/46143/bwHPC7_11.pdf?sequence=1"]}
-{"year":"2022","title":"Intelligent Techniques to Accelerate Everyday Text Communication","authors":["JK Adhikary - 2022"],"snippet":"People with some form of speech-or motor-impairments usually use a high-tech augmentative and alternative communication (AAC) device to communicate with other people in writing or in face-to-face conversations. Their text entry rate on these …","url":["https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=2550&context=etdr"]}
-{"year":"2022","title":"Interactive capsule network for implicit sentiment analysis","authors":["Y Qian, J Wang, D Li, X Zhang - Applied Intelligence, 2022"],"snippet":"Existing sentiment analysis models mainly rely on evident emotive words within phrases. When the apparent emotional words within phrases are eliminated, the performance of these models will inevitably decrease. The implicit communication of …","url":["https://link.springer.com/article/10.1007/s10489-022-03584-3"]}
-{"year":"2022","title":"Interactive Question Answering","authors":["E Toledo"],"snippet":"Artificial intelligence has long aspired to create systems that can perform real-world activities and converse with humans using natural language. In the pursuit of this goal, Interactive Question Answering was proposed. Specifically for language …","url":["https://showcase.sit.uct.ac.za/static/media/122/9ed8c65d-3e35-43d9-86ab-acd83c3abb7c.pdf"]}
-{"year":"2022","title":"International Journal of Knowledge Processing Studies","authors":["SS Moosavi, S Ciruskabiri, A Varnaseri"],"snippet":"The speed and ease of production and loading of content on the web, the exponential increase in the volume and short life cycle of data in this space, have made the processes of collection, refinement, organization, storage, management …","url":["http://kps.artahub.ir/article_152778_d3fab5eab308c5bb383c1a874e0354d4.pdf"]}
-{"year":"2022","title":"Internet-augmented language models through few-shot prompting for open-domain question answering","authors":["A Lazaridou, E Gribovskaya, W Stokowiec, N Grigorev - arXiv preprint arXiv …, 2022"],"snippet":"In this work, we aim to capitalize on the unique few-shot capabilities offered by large-scale language models to overcome some of their challenges with respect to grounding to factual and up-to-date information. Motivated by semi-parametric language models …","url":["https://arxiv.org/pdf/2203.05115"]}
-{"year":"2022","title":"Interpreting Arabic Transformer Models","authors":["A Abdelali, N Durrani, F Dalvi, H Sajjad - arXiv preprint arXiv:2201.07434, 2022"],"snippet":"Arabic is a Semitic language which is widely spoken with many dialects. Given the success of pre-trained language models, many transformer models trained on Arabic and its dialects have surfaced. While these models have been compared with …","url":["https://arxiv.org/pdf/2201.07434"]}
-{"year":"2022","title":"Interpreting Logical Metonymy through Dense Paraphrasing","authors":["B Ye, J Tu, E Jezek, J Pustejovsky - Proceedings of the Annual Meeting of the …, 2022"],"snippet":"… The extensive usage of C4 and the nature of it being sourced from the public Common Crawl web scrape ensure its huge volume and various language styles compared to other public datasets, which provides a “real world” text distribution for our task. …","url":["https://escholarship.org/content/qt19k4w0c1/qt19k4w0c1.pdf"]}
-{"year":"2022","title":"Interpreting mental state decoding with deep learning models","authors":["AW Thomas, C Ré, RA Poldrack - Trends in Cognitive Sciences, 2022"],"snippet":"In mental state decoding, researchers aim to identify the set of mental states (eg, experiencing happiness or fear) that can be reliably identified from the activity patterns of a brain region (or network). Deep learning (DL) models are highly …","url":["https://www.sciencedirect.com/science/article/pii/S1364661322001607"]}
-{"year":"2022","title":"Introducing EM-FT for Manipuri-English Neural Machine Translation","authors":["R Huidrom, Y Lepage"],"snippet":"This paper introduces pretrained word embeddings for Manipuri, a low-resourced Indian language. The pretrained word embeddings based on fastText is capable of handling the highly agglutinative language Manipuri (mni). We then perform …","url":["http://www.lrec-conf.org/proceedings/lrec2022/workshops/WILDRE6/pdf/2022.wildre6-1.1.pdf"]}
-{"year":"2022","title":"Introduction to Language Models","authors":["SM Jain - Introduction to Transformers for NLP, 2022"],"snippet":"… It was trained using the largest corpus a model has ever been trained on, which is known as the Common Crawl , and it has 175 billion different parameters. This is made possible in part by the semi-supervised training method of a language model …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-8844-3_1"]}
-{"year":"2022","title":"Intrusion detection based on keystroke biometrics and siamese neural networks","authors":["A Budžys, O Kurasova, V Medvedev - DAMSS: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148178661/148178661.pdf"]}
-{"year":"2022","title":"Investigating language relationships in multilingual sentence encoders through the lens of linguistic typology","authors":["R Choenni, E Shutova - Computational Linguistics, 2022"],"snippet":"Multilingual sentence encoders have seen much success in cross-lingual model transfer for downstream NLP tasks. The success of this transfer is, however, dependent on the model’s ability to encode the patterns of cross-lingual similarity …","url":["https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli_a_00444/2008428/coli_a_00444.pdf"]}
-{"year":"2022","title":"Investigating Opinions on Public Policies in Digital Media: Setting up a Supervised Machine Learning Tool for Stance Classification","authors":["C Viehmann, T Beck, M Maurer, O Quiring, I Gurevych - Communication Methods and …, 2022"],"snippet":"Supervised machine learning (SML) provides us with tools to efficiently scrutinize large corpora of communication texts. Yet, setting up such a tool involves plenty of decisions starting with the data needed for training, the selection of an algorithm …","url":["https://www.tandfonline.com/doi/abs/10.1080/19312458.2022.2151579"]}
-{"year":"2022","title":"Investigating the Country of Origin and the Role of the. eu TLD in External Trade of European Union Member States","authors":["A Giannakoulopoulos, M Pergantis, L Limniati… - Future Internet, 2022"],"snippet":"… that queried the Common Crawl Index servers for Web pages and collected all the unique domains found. Common Crawl is a non-profit foundation providing access to web information through an open database of web crawl data [28]. The …","url":["https://www.mdpi.com/1999-5903/14/6/174/pdf?version=1654339602"]}
-{"year":"2022","title":"Investigating the Efficient Use of Word Embedding with Neural-Topic Models for Interpretable Topics from Short Texts","authors":["R Murakami, B Chakraborty - Sensors, 2022"],"snippet":"With the rapid proliferation of social networking sites (SNS), automatic topic extraction from various text messages posted on SNS are becoming an important source of information for understanding current social trends or needs. Latent …","url":["https://www.mdpi.com/1424-8220/22/3/852/pdf"]}
-{"year":"2022","title":"Investigating the Quality of Static Anchor Embeddings from Transformers for Under-Resourced Languages","authors":["P Singh, O De Clercq, E Lefever - The 1st Annual Meeting of the ELRA/ISCA Special …, 2022"],"snippet":"… This problem could be solved by adding more monolingual data (from Common Crawl, for example) for the anchor extraction step. We also … Since most methodologies use the Wikipedia and/or the Common Crawl corpus as initial pre-training …","url":["https://biblio.ugent.be/publication/8759657/file/8759658.pdf"]}
-{"year":"2022","title":"Investigations of Performance and Bias in Human-AI Teamwork in Hiring","authors":["A Peng, B Nushi, E Kiciman, K Inkpen, E Kamar - arXiv preprint arXiv:2202.11812, 2022"],"snippet":"In AI-assisted decision-making, effective hybrid (human-AI) teamwork is not solely dependent on AI performance alone, but also on its impact on human decision-making. While prior work studies the effects of model accuracy on humans, we endeavour …","url":["https://arxiv.org/pdf/2202.11812"]}
-{"year":"2022","title":"Is It Out Yet? Automatic Future Product Releases Extraction from Web Data","authors":["G Fuchs, I Ben-Shaul, M Mandelbrod"],"snippet":"… As each monthly snapshot of the Common Crawl data may include hundreds of millions of web pages, we have decided to use a simple heuristics to select web pages which discuss future product releases. Our approach is based on manually curating …","url":["https://ebay.co.il/wp-content/uploads/2022/12/Is-It-Out-Yet-Automatic-Future-Product-Releases-Extraction-from-Web-Data.pdf"]}
-{"year":"2022","title":"Is this Question Real? Dataset Collection on Perceived Intentions and Implicit Attack Detection","authors":["MS Mirzaei, K Meshgi, S Sekine - Proceedings of the ACM Web Conference 2022, 2022"],"snippet":"… We used GloVe [38] word embedding (300d version on 840B Common Crawl data) for obtaining vector representations for words and Xavier initialization for the parameters. The batch size is set to 32, and the loss is calculated using binary cross-entropy …","url":["https://dl.acm.org/doi/abs/10.1145/3485447.3512005"]}
-{"year":"2022","title":"Is Using an AI to Simplify a Scientific Text Really Worth It","authors":["TB Talec-Bernard - Proceedings of the Working Notes of CLEF, 2022"],"snippet":"Nowadays, we encounter Artificial Intelligence (AI) everywhere and although it can help us save a lot of time when performing certain tasks such as translating or correcting a text, it can also lead to a loss in quality. When it comes to automatically …","url":["http://ceur-ws.org/Vol-3180/paper-245.pdf"]}
-{"year":"2022","title":"Isomorphic Cross-lingual Embeddings for Low-Resource Languages","authors":["S Sannigrahi, J Read - arXiv preprint arXiv:2203.14632, 2022"],"snippet":"… 2018) which uses Wikipedia dumps and Common Crawl for all languages. In addition to this, we use available parallel data between the following related language pairs respectively: English-Hindi (hi) for Nepali, English-Estonian (et) for …","url":["https://arxiv.org/pdf/2203.14632"]}
-{"year":"2022","title":"IsoVec: Controlling the Relative Isomorphism of Word Embedding Spaces","authors":["K Marchisio, N Verma, K Duh, P Koehn - arXiv preprint arXiv:2210.05098, 2022"],"snippet":"The ability to extract high-quality translation dictionaries from monolingual word embedding spaces depends critically on the geometric similarity of the spaces -- their degree of \"isomorphism.\" We address the root-cause of faulty cross-lingual …","url":["https://arxiv.org/pdf/2210.05098"]}
-{"year":"2022","title":"IT5: Large-scale Text-to-text Pretraining for Italian Language Understanding and Generation","authors":["G Sarti, M Nissim - arXiv preprint arXiv:2203.03759, 2022"],"snippet":"… 2020), a large collection including roughly 750GB of webscraped English texts sourced from the CommonCrawl. This was subsequently cleaned employing heuristics aimed at removing templated fillers, text deduplication, Javascript code …","url":["https://arxiv.org/pdf/2203.03759"]}
-{"year":"2022","title":"Jan Chołoniewski, B. Eng., M. Sc.","authors":["JA Hołyst, B Eng, J Sienkiewicz"],"snippet":"W pracy analizujemy i modelujemy działalność internetowych serwisów informacyjnych, łącząc ilościowe podejście medioznawcze z metodami fizyki statystycznej. Głównymi celami prezentowanych badań są:(i) charakterystyka …","url":["https://repo.pw.edu.pl/docstore/download/WUT6177f85542a746fd8ceaa3bc9fc6d8d1/PhD_fizyka_Jan_Choloniewski+do+druku.pdf"]}
-{"year":"2022","title":"Jointly Multi-Similarity Loss for Deep Metric Learning","authors":["L Zhang, S Shen, L Li, H Wang, X Li, J Lang - 2021 IEEE International Conference on …, 2021"],"snippet":"… In particular, all of the input sentences are split and initialized in the word representation layer with the 300-dimensional GloVe word vectors pre-trained from the 840B Common Crawl corpus [24], and the embeddings of the out-of-vocabulary …","url":["https://ieeexplore.ieee.org/abstract/document/9679139/"]}
-{"year":"2022","title":"JParaCrawl v3. 0: A Large-scale English-Japanese Parallel Corpus","authors":["M Morishita, K Chousa, J Suzuki, M Nagata - arXiv preprint arXiv:2202.12607, 2022"],"snippet":"… To list such parallel websites, we analyzed all the Common Crawl text archive data released from March 2019 to August 20213. We identified the language in the archive by CLD24 and listed 100,000 large websites that roughly have the same …","url":["https://arxiv.org/pdf/2202.12607"]}
-{"year":"2022","title":"Just Rank: Rethinking Evaluation with Word and Sentence Similarities","authors":["B Wang, CCJ Kuo, H Li - arXiv preprint arXiv:2203.02679, 2022"],"snippet":"Word and sentence embeddings are useful feature representations in natural language processing. However, intrinsic evaluation for embeddings lags far behind, and there has been no significant update since the past decade. Word and sentence …","url":["https://arxiv.org/pdf/2203.02679"]}
-{"year":"2022","title":"Just-In-Time Obsolete Comment Detection and Update","authors":["Z Liu, X Xia, D Lo, M Yan, S Li - IEEE Transactions on Software Engineering, 2021"],"snippet":"Comments are valuable resources for the development, comprehension and maintenance of software. However, while changing code, developers sometimes neglect the evolution of the corresponding comments, resulting in obsolete …","url":["https://ieeexplore.ieee.org/abstract/document/9664004/"]}
-{"year":"2022","title":"k 𝑘 k italic_k-Nearest Neighbor Augmented Neural Networks for Text Classification","authors":["Z Wang, W Hamza, L Song"],"snippet":"In recent years, many deep-learning based models are proposed for text classification. This kind of models well fits the training set from the statistical point of view. However, it lacks the capacity of utilizing instance-level information from …","url":["https://ar5iv.labs.arxiv.org/html/1708.07863"]}
-{"year":"2022","title":"Keyword Extraction in Scientific Documents","authors":["SX Rao, P Piriyatamwong, P Ghoshal, S Nasirian… - arXiv preprint arXiv …, 2022"],"snippet":"… As an additional hint to participants, document embeddings for each item in the train and test sets, as well as word embeddings for the entire corpus, were generated from a fastText model2 trained on the English Common Crawl dataset (cc.en.300.bin)3. …","url":["https://arxiv.org/pdf/2207.01888"]}
-{"year":"2022","title":"Knowledge Complementarity between Seed Investors and Startup Founders: Lessons from Accelerators","authors":["S Santamaria, S Breschi"],"snippet":"Which entrepreneurs benefit most from accelerator programs? In this paper, we argue that the value-added by startup accelerators depends critically on whether the knowledge these supporting institutions provide is complementary to or a substitute …","url":["https://kid2021.sciencesconf.org/data/program/kid2021_breschi.pdf"]}
-{"year":"2022","title":"Knowledge Distillation Transfer Sets and their Impact on Downstream NLU Tasks","authors":["C Peris, L Tan, T Gueudre, T Gojayev, V Wei, G Oz - arXiv preprint arXiv:2210.04834, 2022"],"snippet":"… We then sample 50K utterances each, from the Wikipedia and Common Crawl data sets of the corresponding language. We create a tf-… CommonCrawl have relatively larger improvement in SemER, when compared to domains that are more …","url":["https://arxiv.org/pdf/2210.04834"]}
-{"year":"2022","title":"Knowledge extraction from fictional texts","authors":["CX Chu - 2022"],"snippet":"Knowledge extraction from text is a key task in natural language processing, which involves many sub-tasks, such as taxonomy induction, named entity recognition and typing, relation extraction, knowledge canonicalization and so on. By constructing …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/32914/1/thesis-twoside-toprint.pdf"]}
-{"year":"2022","title":"Knowledge graph expansion using question answering by leveraging language models","authors":["H Fock - 2022"],"snippet":"… C4 is based on the Common Crawl Web Archive9, a massive collection of web-extracted text, with around 20 TB of text data added each month. The researchers took the massive collection of web-extracted text data with the actuality of April 2019. The …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/42416/MasterThesis_HagenAadFock_1935569_FinalVersion.pdf?sequence=1"]}
-{"year":"2022","title":"KNOWLEDGE REPRESENTATIONS+ SCHEMATA","authors":["LJ Martin"],"snippet":"… Data Source: Common Crawl …","url":["https://interactive-fiction-class.org/slides/CIS700-KnowledgeBases.pdf"]}
-{"year":"2022","title":"Korean and Multilingual Language Models Study for Cross-Lingual Post-Training (XPT)","authors":["S Son, C Park, J Lee, M Shim, C Lee, K Park, H Lim - Journal of the Korea …, 2022"],"snippet":"It has been proven through many previous researches that the pretrained language model with a large corpus helps improve performance in various natural language processing tasks. However, there is a limit to building a large-capacity corpus for …","url":["https://www.koreascience.or.kr/article/JAKO202210459401088.pdf"]}
-{"year":"2022","title":"Kv2vec: A Distributed Representation Method for Key-value Pairs from Metadata Attributes","authors":["C Niu, W Zhang, S Byna, Y Chen - 2022 IEEE High Performance Extreme Computing …, 2022"],"snippet":"… Common Crawl web corpus has the least error rate. Therefore, we choose to use the pre-trained dictionary generated from the word2vec model with Common Crawl … the pre-trained and retrofitted dictionary generated by the word2vec model on the …","url":["https://ieeexplore.ieee.org/abstract/document/9926389/"]}
-{"year":"2022","title":"L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT Language Models, and Resources","authors":["R Joshi - arXiv preprint arXiv:2202.01159, 2022"],"snippet":"We present L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources. We expand the existing Marathi monolingual corpus with 24.8M sentences and 289M tokens. We further present, MahaBERT, MahaAlBERT …","url":["https://arxiv.org/pdf/2202.01159"]}
-{"year":"2022","title":"L3Cube-MahaHate: A Tweet-based Marathi Hate Speech Detection Dataset and BERT models","authors":["A Velankar, H Patil, A Gore, S Salunke, R Joshi - arXiv preprint arXiv:2203.13778, 2022"],"snippet":"Social media platforms are used by a large number of people prominently to express their thoughts and opinions. However, these platforms have contributed to a substantial amount of hateful and abusive content as well. Therefore, it is important …","url":["https://arxiv.org/pdf/2203.13778"]}
-{"year":"2022","title":"L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking BERT Sentence Representations for Hindi and Marathi","authors":["A Joshi, A Kajale, J Gadre, S Deode, R Joshi - arXiv preprint arXiv:2211.11187, 2022"],"snippet":"Sentence representation from vanilla BERT models does not work well on sentence similarity tasks. Sentence-BERT models specifically trained on STS or NLI datasets are shown to provide state-of-the-art performance. However, building these models …","url":["https://arxiv.org/pdf/2211.11187"]}
-{"year":"2022","title":"Label Semantic Aware Pre-training for Few-shot Text Classification","authors":["A Mueller, J Krone, S Romeo, S Mansour, E Mansimov… - arXiv preprint arXiv …, 2022"],"snippet":"In text classification tasks, useful information is encoded in the label names. Label semantic aware systems have leveraged this information for improved text classification performance during fine-tuning and prediction. However, use of label-semantics …","url":["https://arxiv.org/pdf/2204.07128"]}
-{"year":"2022","title":"Landing AI on Networks: An equipment vendor viewpoint on Autonomous Driving Networks","authors":["D Rossi, L Zhang"],"snippet":"… Similarly, recently hyped advances [21] in NLP relied on hundred billions of text tokens corpus such as Common Crawl [47]. Even in lesser massmediatized fields such as computational biology, it is fairly well recognized that astonishing advances [48] …","url":["https://nonsns.github.io/paper/rossi22ai4net_vision.pdf"]}
-{"year":"2022","title":"Language Agnostic Code-Mixing Data Augmentation by Predicting Linguistic Patterns","authors":["SS Li, K Murray - arXiv preprint arXiv:2211.07628, 2022"],"snippet":"In this work, we focus on intrasentential code-mixing and propose several different Synthetic Code-Mixing (SCM) data augmentation methods that outperform the baseline on downstream sentiment analysis tasks across various amounts of …","url":["https://arxiv.org/pdf/2211.07628"]}
-{"year":"2022","title":"Language Agnostic Multilingual Information Retrieval with Contrastive Learning","authors":["X Hu, X Chen, P Qi, D Kong, K Liu, WY Wang, Z Huang - arXiv preprint arXiv …, 2022"],"snippet":"Multilingual information retrieval is challenging due to the lack of training datasets for many low-resource languages. We present an effective method by leveraging parallel and non-parallel corpora to improve the pretrained multilingual language …","url":["https://arxiv.org/pdf/2210.06633"]}
-{"year":"2022","title":"Language and Gender","authors":["J Berger, R Boghrati, S Rathee, R Pogacar, A Mecit - ACR North American Advances, 2021"],"snippet":"… We use Common Crawl and 11 million product reviews from Amazon and Yelp, to ask whether algorithms learn to associate women with … Common Crawl is a snapshot of the contents of the World Wide Web, a text repository of 2.45 billion web …","url":["https://www.acrwebsite.org/volumes/v49/acr_vol49_3000129.pdf"]}
-{"year":"2022","title":"Language Chameleon: Transformation analysis between languages using Cross-lingual Post-training based on Pre-trained language models","authors":["S Son, C Park, J Lee, M Shim, C Lee, Y Jang, J Seo… - arXiv preprint arXiv …, 2022"],"snippet":"… XLM-R XLM-R is a cross-lingual model (XLM), which is trained with commoncrawl corpus6 containing a hundred types of languages. Unlike previous XLM, it is based on RoBERTa. It has 550M … 6https://commoncrawl.org/ 7https://namu.wiki/ 8https://corpus.korean.go.kr/ …","url":["https://arxiv.org/pdf/2209.06422"]}
-{"year":"2022","title":"Language Detoxification with Attribute-Discriminative Latent Space","authors":["JM Kwak, M Kim, SJ Hwang - arXiv preprint arXiv:2210.10329, 2022"],"snippet":"Transformer-based Language Models (LMs) achieve remarkable performances on a variety of NLU tasks, but are also prone to generating toxic texts such as insults, threats, and profanities which limit their adaptations to the real-world applications …","url":["https://arxiv.org/pdf/2210.10329"]}
-{"year":"2022","title":"Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion","authors":["K Shuster, M Komeili, L Adolphs, S Roller, A Szlam… - arXiv preprint arXiv …, 2022"],"snippet":"… Knowledge Module Task To construct our knowledge task, we also start with Common Crawl, splitting it into sentences. We construct a Lucene5 search over Common Crawl, and then, for a given target sentence of a document, we find the …","url":["https://arxiv.org/pdf/2203.13224"]}
-{"year":"2022","title":"Language Pre-Training and Auxiliary Tasks for Vision and Language Navigation","authors":["S Bhatt - 2022"],"snippet":"The Vision and Language Navigation task came to life from the idea that we can build a robot or an autonomous system that can be instructed in human language and that will navigate using the instructions given. For example, we tell the agent to “Go …","url":["https://rc.library.uta.edu/uta-ir/bitstream/handle/10106/30243/BHATT-THESIS-2021.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Language-Agnostic Website Embedding and Classification","authors":["S Lugeon, T Piccardi, R West - arXiv preprint arXiv:2201.03677, 2022"],"snippet":"… Following this intuition, we collected from Common Crawl4, a large-scale sample of the Web, the 19 most frequent TLDs: .com, .org, .net, .info, … We consider the 30 most frequent metatags from a sample of the Common Crawl and represent their …","url":["https://arxiv.org/pdf/2201.03677"]}
-{"year":"2022","title":"Language-Bridged Spatial-Temporal Interaction for Referring Video Object Segmentation","authors":["Z Ding, T Hui, J Huang, X Wei, J Han, S Liu - … of the IEEE/CVF Conference on …, 2022"],"snippet":"… tic inputs, we adopt LSTM [9] to extract language features from GloVe word embeddings [32] pretrained on Common Crawl with 840B tokens. The maximum length of the input sentence is 25. We set the frame interval δ = 6 for calculating the …","url":["https://openaccess.thecvf.com/content/CVPR2022/papers/Ding_Language-Bridged_Spatial-Temporal_Interaction_for_Referring_Video_Object_Segmentation_CVPR_2022_paper.pdf"]}
-{"year":"2022","title":"Large Language Models Struggle to Learn Long-Tail Knowledge","authors":["N Kandpal, H Deng, A Roberts, E Wallace, C Raffel - arXiv preprint arXiv:2211.08411, 2022"],"snippet":"The internet contains a wealth of knowledge -- from the birthdays of historical figures to tutorials on how to code -- all of which may be learned by language models. However, there is a huge variability in the number of times a given piece of …","url":["https://arxiv.org/pdf/2211.08411"]}
-{"year":"2022","title":"Large pre-trained language models contain human-like biases of what is right and wrong to do","authors":["P Schramowski, C Turan, N Andersen, CA Rothkopf… - Nature Machine Intelligence, 2022"],"snippet":"Artificial writing is permeating our lives due to recent advances in large-scale, transformer-based language models (LMs) such as BERT, GPT-2 and GPT-3. Using them as pre-trained models and fine-tuning them for specific tasks, researchers have …","url":["https://www.nature.com/articles/s42256-022-00458-8"]}
-{"year":"2022","title":"Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All","authors":["E Guetta, A Shmidman, S Shmidman, CS Shmidman… - arXiv preprint arXiv …, 2022"],"snippet":"… Due to the lack of large public-domain textual corpora available for Modern Hebrew, we had to rely upon Wikipedia, Twitter, and the OSCAR common crawl Thus, other genres are unrepresented or underrepresented, including scientific …","url":["https://arxiv.org/pdf/2211.15199"]}
-{"year":"2022","title":"Large-scale Bilingual Language-Image Contrastive Learning","authors":["B Ko, G Gu - arXiv preprint arXiv:2203.14463, 2022"],"snippet":"This paper is a technical report to share our experience and findings building a Korean and English bilingual multimodal model. While many of the multimodal datasets focus on English and multilingual multimodal research uses machine-translated …","url":["https://arxiv.org/pdf/2203.14463"]}
-{"year":"2022","title":"Large-scale product classification for efficient matching in procurement systems","authors":["I Hrysha - 2022"],"snippet":"We consider the problem of recommending relevant suppliers given detailed request context in a procurement setting. The fundamental recommendation in procurement systems is that a single query has potentially hundreds of relevant …","url":["http://www.er.ucu.edu.ua:8080/bitstream/handle/1/3154/Hrysha%2C%20Ihor%20-%20Large-scale%20product%20classification%20for%20efficient%20matching%20in%20procurement%20systems.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Large-scale product classification to recommend suppliers in procurement systems","authors":["I Hrysha, S Grondahl"],"snippet":"We consider the problem of recommending relevant suppliers given detailed request context in a procurement setting. The fundamental recommendation in procurement systems is that a single query has potentially hundreds of relevant …","url":["https://s3.eu-central-1.amazonaws.com/ucu.edu.ua/wp-content/uploads/sites/8/2022/12/MS-AMLV_2022_paper_27.pdf"]}
-{"year":"2022","title":"Large-scale Semi-supervised Learning of Neural NLP Models","authors":["S Kiyono - 2022"],"snippet":"Deep neural network (DNN) based approaches have achieved remarkable performance in multiple research fields, such as natural language processing, computer vision, and speech processing. However, it is widely acknowledged that …","url":["https://www.cl.ecei.tohoku.ac.jp/publications/2022/kiyono-dthesis.pdf"]}
-{"year":"2022","title":"Large-scale study of web accessibility metrics","authors":["B Martins, C Duarte - Universal Access in the Information Society, 2022"],"snippet":"… The pages were obtained from CommonCrawl Footnote 5 . CommonCrawl is an open corpus of web crawl data, including metadata and source of billions of web pages since 2013. We used the most recent crawls to obtain the URLs of the pages …","url":["https://link.springer.com/article/10.1007/s10209-022-00956-x"]}
-{"year":"2022","title":"Laying the foundations for benchmarking open data automatically","authors":["AS Correa, FSC Da Silva"],"snippet":"… Common Crawl And Unlocking Web Archives For Research. Retrieved 2019-01-13 from https://www.forbes.com/sites/kalevleetaru/2017/09… Common Crawl And Unlocking Web Archives For Research. Retrieved 2019-01-13 from https://www.forbes.com/sites/kalevleetaru/2017/09…","url":["https://ouci.dntb.gov.ua/en/works/9j0eJBj4/"]}
-{"year":"2022","title":"Learner Profiling: Demographics Identification Based on NLP, Machine Learning, and MOOCs Metadata","authors":["T ALJOHANI, M MUSLIH - 2022"],"snippet":"Massive Open Online Courses (MOOCs) have become universal learning resources, and the COVID- 19 pandemic is rendering these platforms even more necessary. Many types of research are ongoing to improve the learning resources provided to …","url":["http://etheses.dur.ac.uk/14486/1/Thesis__Final_Version.pdf"]}
-{"year":"2022","title":"Learning GUI Completions with User-defined Constraints","authors":["L Brückner, LA Leiva, A Oulasvirta - ACM Transactions on Interactive Intelligent …, 2022","LA LEIVA - 2022"],"snippet":"A key objective in the design of graphical user interfaces (GUIs) is to ensure consistency across screens of the same product. However, designing a compliant layout is time-consuming and can distract designers from creative thinking. This …","url":["https://dl.acm.org/doi/abs/10.1145/3490034","https://research.aalto.fi/files/82497867/learning_gui_completions.pdf"]}
-{"year":"2022","title":"Learning High-Order Semantic Representation for Intent Classification and Slot Filling on Low-Resource Language via Hypergraph.","authors":["X Qi, Y Gao, R Wang, M Zhao, S Cui, M Mortazavi - Mathematical Problems in …, 2022"],"snippet":"… ey pretrained it on the Common Crawl and Wikipedia using fastText. is Indonesian word vector model is trained using CBOW with position-weights, in dimension 300 (ie, Wemb ∈ R1 × 300), with character n-grams of length 5, a window of size 5 and 10 …","url":["https://downloads.hindawi.com/journals/mpe/2022/8407713.pdf"]}
-{"year":"2022","title":"Learning interpretable word embeddings via bidirectional alignment of dimensions with semantic concepts","authors":["LK Şenel, F Şahinuç, V Yücesoy, H Schütze, T Çukur… - Information Processing & …, 2022"],"snippet":"We propose bidirectional imparting or BiImp, a generalized method for aligning embedding dimensions with concepts during the embedding learning phase. While preserving the semantic structure of the embedding space, BiImp makes dimensions …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322000498"]}
-{"year":"2022","title":"Learning Meta Word Embeddings by Unsupervised Weighted Concatenation of Source Embeddings","authors":["D Bollegala - arXiv preprint arXiv:2204.12386, 2022"],"snippet":"… Note that this is significantly smaller compared to vocabulary sizes and training corpora used in publicly available word embeddings (eg GloVe embeddings are trained on 42B tokens from Common Crawl corpus covering …","url":["https://arxiv.org/pdf/2204.12386"]}
-{"year":"2022","title":"Learning on Streaming Graphs with Experience Replay","authors":["M Perini, G Ramponi, P Carbone, V Kalavri - 2022"],"snippet":"… Text features have been generated using a 300-dimensional GloVe CommonCrawl word vector. Posts are linked with an edge if they have been commented by the same user and each edge bears the timestamp of the first comment. The …","url":["https://sites.bu.edu/casp/files/2021/12/online-gnn-SAC-preprint.pdf"]}
-{"year":"2022","title":"Learning Sample Importance for Cross-Scenario Video Temporal Grounding","authors":["P Bao, Y Mu - arXiv preprint arXiv:2201.02848, 2022"],"snippet":"The task of temporal grounding aims to locate video moment in an untrimmed video, with a given sentence query. This paper for the first time investigates some superficial biases that are specific to the temporal grounding task, and proposes a …","url":["https://arxiv.org/pdf/2201.02848"]}
-{"year":"2022","title":"Learning the Morphological and Syntactic Grammars for Named Entity Recognition","authors":["M Sun, Q Yang, H Wang, M Pasquine, IA Hameed - Information, 2022"],"snippet":"In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structures, such as inflection, that will confuse the data-driven models when perceiving the word’s actual meaning. This work tries to alleviate …","url":["https://www.mdpi.com/2078-2489/13/2/49/pdf"]}
-{"year":"2022","title":"Learning the Morphological and Syntactic Grammars for Named Entity Recognition. Information 2022, 13, 49","authors":["M Sun, Q Yang, H Wang, M Pasquine, IA Hameed - 2022"],"snippet":"In some languages, Named Entity Recognition (NER) is severely hindered by complex linguistic structures, such as inflection, that will confuse the data-driven models when perceiving the word’s actual meaning. This work tries to alleviate …","url":["https://www.researchgate.net/profile/Ibrahim-Hameed/publication/357970212_Learning_the_Morphological_and_Syntactic_Grammars_for_Named_Entity_Recognition/links/61e97f849a753545e2e50b09/Learning-the-Morphological-and-Syntactic-Grammars-for-Named-Entity-Recognition.pdf"]}
-{"year":"2022","title":"Learning to Enrich Query Representation with Pseudo-Relevance Feedback for Cross-lingual Retrieval","authors":["R Chandradevan, E Yang, M Yarmohammadi… - Proceedings of the 45th …, 2022"],"snippet":"… To help picking the best performing model across the training steps and tune the free parameters, we used CLIR Common Crawl Collection (HC4) [13] as the development dataset. In this dataset, the exact same English topics are queried over …","url":["https://dl.acm.org/doi/abs/10.1145/3477495.3532013"]}
-{"year":"2022","title":"Learning to Follow Instructions in Text-Based Games","authors":["M Tuli, AC Li, P Vaezipoor, TQ Klassen, S Sanner… - arXiv preprint arXiv …, 2022"],"snippet":"Text-based games present a unique class of sequential decision making problem in which agents interact with a partially observable, simulated environment via actions and observations conveyed through natural language. Such observations typically …","url":["https://arxiv.org/pdf/2211.04591"]}
-{"year":"2022","title":"Learning to translate by learning to communicate","authors":["CM Downey, LZ Liu, X Zhou, S Steinert-Threlkeld - arXiv preprint arXiv:2207.07025, 2022"],"snippet":"We formulate and test a technique to use Emergent Communication (EC) with a pretrained multilingual model to improve on modern Unsupervised NMT systems, especially for low-resource languages. It has been argued that the currently …","url":["https://arxiv.org/pdf/2207.07025"]}
-{"year":"2022","title":"Learning Trustworthy Web Sources to Derive Correct Answers and Reduce Health Misinformation in Search","authors":["D Zhang, A Vakili Tahami, M Abualsaud, M Smucker - 2022"],"snippet":"When searching the web for answers to health questions, people can make incorrect decisions that have a negative effect on their lives if the search results contain misinformation. To reduce health misinformation in search results, we need to be …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/18257/SIGIR%202022%20Misinformation.pdf?sequence=1"]}
-{"year":"2022","title":"Learning Two-Step Hybrid Policy for Graph-Based Interpretable Reinforcement Learning","authors":["T Mu, K Lin, F Niu, G Thattai - arXiv preprint arXiv:2201.08520, 2022"],"snippet":"We present a two-step hybrid reinforcement learning (RL) policy that is designed to generate interpretable and robust hierarchical policies on the RL problem with graph-based input. Unlike prior deep reinforcement learning policies parameterized by an end-to-end …","url":["https://arxiv.org/pdf/2201.08520"]}
-{"year":"2022","title":"Learnings from Federated Learning in the Real world","authors":["C Dupuy, TG Roosta, L Long, C Chung, R Gupta… - arXiv preprint arXiv …, 2022"],"snippet":"Federated Learning (FL) applied to real world data may suffer from several idiosyncrasies. One such idiosyncrasy is the data distribution across devices. Data across devices could be distributed such that there are some \"heavy devices\" with …","url":["https://arxiv.org/pdf/2202.03925"]}
-{"year":"2022","title":"Less is More: Task-aware Layer-wise Distillation for Language Model Compression","authors":["C Liang, S Zuo, Q Zhang, P He, W Chen, T Zhao - arXiv preprint arXiv:2210.01351, 2022"],"snippet":"Layer-wise distillation is a powerful tool to compress large models (ie teacher models) into small ones (ie, student models). The student distills knowledge from the teacher by mimicking the hidden representations of the teacher at every intermediate layer …","url":["https://web7.arxiv.org/pdf/2210.01351"]}
-{"year":"2022","title":"Lessons learned from the evaluation of Spanish Language Models","authors":["R Agerri Gascón, E Agirre Bengoa - 2023","R Agerri, E Agirre - arXiv preprint arXiv:2212.08390, 2022"],"snippet":"Given the impact of language models on the field of Natural Language Processing, a number of Spanish encoder-only masked language models (aka BERTs) have been trained and released. These models were developed either within large projects …","url":["https://arxiv.org/pdf/2212.08390","https://rua.ua.es/dspace/bitstream/10045/133264/1/PLN_70_13.pdf"]}
-{"year":"2022","title":"Leveraging Natural Supervision for Language Representation Learning and Generation","authors":["M Chen - arXiv preprint arXiv:2207.10617, 2022"],"snippet":"Recent breakthroughs in Natural Language Processing (NLP) have been driven by language models trained on a massive amount of plain text. While powerful, deriving supervision from textual resources is still an open question. For example, language …","url":["https://arxiv.org/pdf/2207.10617"]}
-{"year":"2022","title":"LeviRANK: Limited Query Expansion with Voting Integration for Document Retrieval and Ranking","authors":["A Rana, P Golchha, R Juntunen, A Coajă… - Working Notes Papers of the …, 2022"],"snippet":"In order to make informed decisions in personal life, the information available on the internet is often overwhelming, and thus comparative decision-making is particularly challenging. Given the plethora of online resources, it often results in wastage of …","url":["http://ceur-ws.org/Vol-3180/paper-259.pdf"]}
-{"year":"2022","title":"Lexical Semantics with Large Language Models: A Case Study of English break","authors":["E Petersen, C Potts"],"snippet":"Large neural language models (LLMs) can be powerful tools for research in lexical semantics. We illustrate this potential using the English verb break, which has numerous senses and appears in a wide range of syntactic frames. We show that …","url":["https://lingbuzz.net/lingbuzz/006859/current.pdf"]}
-{"year":"2022","title":"Lightweight diacritics restoration for V4 languages","authors":["B Csanády, A Lukács"],"snippet":"… In the case of HunWeb2, we used the \"2017-2018\" part of the Common Crawl subcorpus. Not splitting up the documents ensures that the train and dev data do not correlate too much, as we have found that there can be a lot of repeated sentences …","url":["http://acta.bibl.u-szeged.hu/75899/1/msznykonf_018_549-559.pdf"]}
-{"year":"2022","title":"Limitations and Challenges of Unsupervised Cross-lingual Pre-training","authors":["MQ Zaragoza, F Casacuberta - Proceedings of the 15th biennial conference of the …, 2022"],"snippet":"Cross-lingual alignment methods for monolingual language representations have received notable attention in recent years. However, their use in machine translation pre-training remains scarce. This work tries to shed light on the effects of some of the …","url":["https://aclanthology.org/2022.amta-research.13.pdf"]}
-{"year":"2022","title":"Linguistic and Emotion-based Identification of Tweets with Fake News: A Case Study","authors":["VS Bernardes - 2021"],"snippet":"Since the popularization of the term in 2016, we have observed a proliferation of so called “fake news” content, assisted by the widespread use of social media platforms. The dissemination of fake content brings with it serious political, economical, and …","url":["https://repositorio-aberto.up.pt/bitstream/10216/139434/2/528149.pdf"]}
-{"year":"2022","title":"Linguistic Approaches to the Analysis of Online Terrorist Threats","authors":["J Longhi - Language as Evidence, 2022"],"snippet":"This chapter focuses on online terrorist threats. For many linguists, the best training for a forensic linguist is a course in descriptive and applied linguistics because each case will normally require a different selection of tools from the linguistic toolbox …","url":["https://link.springer.com/chapter/10.1007/978-3-030-84330-4_13"]}
-{"year":"2022","title":"Linguistic resources for Romanian. Quality assessed machine-translated and post-edited Romanian corpus and opportunities for interdisciplinary research","authors":["G BULGARU - REVUE INTERNATIONALE D'ÉTUDES EN LANGUES …"],"snippet":"Despite the great progress over the last years, Romanian is still a low-resourced language. In this paper, we set to make a short overview of the language technology field and the linguistic resources available for Romanian. We also sketch out a short …","url":["https://www.academia.edu/download/77452310/RIELMA_no14_2021_Supplement.pdf#page=78"]}
-{"year":"2022","title":"LinkingPark: An automatic semantic table interpretation system","authors":["S Chen, A Karaoglu, C Negreanu, T Ma, JG Yao… - Journal of Web Semantics, 2022"],"snippet":"In this paper, we present LinkingPark, an automatic semantic annotation system for tabular data to knowledge graph matching. LinkingPark is designed as a modular framework which can handle Cell-Entity Annotation (CEA), Column-Type Annotation …","url":["https://www.sciencedirect.com/science/article/pii/S1570826822000233"]}
-{"year":"2022","title":"liveopp/keras-quora-question-pairs","authors":["GPK Tool, JFMAM Jun, JASON Dec, JSMTW Thu, F Sat"],"snippet":"… Max bag-of-embeddings (this work) GloVe Common Crawl (840B tokens, 300D) 0.83 \"Multi-Perspective-LSTM\" [5] GloVe Common Crawl (840B tokens, 300D) 0.83 … \"Max-out Window Encoding\" with depth 2 [7] GloVe Common Crawl pruned to 1M …","url":["https://giters.com/liveopp/keras-quora-question-pairs"]}
-{"year":"2022","title":"LLM. int8 (): 8-bit Matrix Multiplication for Transformers at Scale","authors":["T Dettmers, M Lewis, Y Belkada, L Zettlemoyer - arXiv preprint arXiv:2208.07339, 2022"],"snippet":"Large language models have been widely adopted but require significant GPU memory for inference. We develop a procedure for Int8 matrix multiplication for feed-forward and attention projection layers in transformers, which cut the memory needed for …","url":["https://arxiv.org/pdf/2208.07339"]}
-{"year":"2022","title":"lo-fi: distributed fine-tuning without communication","authors":["M Wortsman, S Gururangan, S Li, A Farhadi, L Schmidt… - arXiv preprint arXiv …, 2022"],"snippet":"… -tuning OPT language models (up to 1.3B parameters) on Common Crawl. By removing the communication requirement, lo-fi reduces resource … Finally, we test lo-fi beyond computer vision by fine-tuning OPT-125M and OPT-1.3B [72] on …","url":["https://arxiv.org/pdf/2210.11948"]}
-{"year":"2022","title":"Location-based Twitter Filtering for the Creation of Low-Resource Language Datasets in Indonesian Local Languages","authors":["M Amien, C Feng, H Huang - arXiv preprint arXiv:2206.07238, 2022"],"snippet":"Twitter contains an abundance of linguistic data from the real world. We examine Twitter for user-generated content in low-resource languages such as local Indonesian. For NLP to work in Indonesian, it must consider local dialects …","url":["https://arxiv.org/pdf/2206.07238"]}
-{"year":"2022","title":"Longitudinal analysis of sentiment and emotion in news media headlines using automated labelling with Transformer language models","authors":["D Rozado, R Hughes, J Halberstadt - Plos one, 2022"],"snippet":"This work describes a chronological (2000–2019) analysis of sentiment and emotion in 23 million headlines from 47 news media outlets popular in the United States. We use Transformer language models fine-tuned for detection of sentiment (positive …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0276367"]}
-{"year":"2022","title":"Low-level factors increase gaze-guidance under cognitive load: A comparison of image-salience and semantic-salience models","authors":["K Walter, P Bex - PLOS ONE, 2022"],"snippet":"… GloVe is trained on large web-based datasets, we used the Common Crawl dataset comprised of 840 billion tokens and 2.2 million words. GloVe categorizes words along feature dimensions to create a similarity web of various terms based on …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0277691"]}
-{"year":"2022","title":"Low-Resource Authorship Style Transfer with In-Context Learning","authors":["A Patel, N Andrews, C Callison-Burch - arXiv preprint arXiv:2212.08986, 2022"],"snippet":"… Other models were trained on variants of Common Crawl data. To the best of our knowledge, using various search … Common Crawl, as a breadth-first crawler, only contains a small amount of Reddit data, often a few thousand pages per month …","url":["https://arxiv.org/pdf/2212.08986"]}
-{"year":"2022","title":"LPT: Language-agnostic Prompt Tuning","authors":["Y Ji, Y Wang, Z Tang - Sci China Inf Sci"],"snippet":"… The pre-trained XLM-RoBERTa-base model contains 270M parameters, which is trained on 2.5 TB CommonCrawl data in 100 languages. Its vocabulary contains 250k tokens. The architecture of XLMRoBERTa-base is the same as RoBERTa-base. …","url":["https://lijuntaopku.github.io/SCIS_22_LPT.pdf"]}
-{"year":"2022","title":"Machine Comprehension System in Tamil and English based on BERT","authors":["G Srivatsun, S Thivaharan, BK KS, S Sudharsan - 2022 3rd International Conference …, 2022"],"snippet":"… XLM-R [6] used more than 2 terabytes of data filtered by Common Crawl to train a Transformer-based masked language model on 100 languages. It also gave a complete empirical study of the essential aspects that are necessary to improve cross-lingual …","url":["https://ieeexplore.ieee.org/abstract/document/9885657/"]}
-{"year":"2022","title":"Machine Learning and Deep Learning Based Phishing Websites Detection: The Current Gaps and Next Directions","authors":["K Adane, B Beyene - Review of Computer Engineering Research, 2022"],"snippet":"There are many phishing websites detection techniques in literature, namely white-listing, black-listing, visual-similarity, heuristic-based, and others. However, detecting zero-hour or newly designed phishing website attacks is an inherent property of machine …","url":["https://archive.conscientiabeam.com/index.php/76/article/download/2983/6434"]}
-{"year":"2022","title":"Machine learning and deep learning-based Natural Language Processing for auto-vetting the appropriateness of Lumbar Spine Magnetic Resonance Imaging …","authors":["A Alanazi, A Cradock, J Ryan, L Rainford - Informatics in Medicine Unlocked, 2022"],"snippet":"Manual vetting of radiology referrals is an essential daily task to ensure the appropriateness of the received referrals. Such tasks require sufficient clinical experience and may challenge the radiology staff. With the emerging of artificial …","url":["https://www.sciencedirect.com/science/article/pii/S2352914822001071"]}
-{"year":"2022","title":"Machine Learning approaches for Topic and Sentiment Analysis in multilingual opinions and low-resource languages: From English to Guarani","authors":["MM Agüero Torales - 2022"],"snippet":"This dissertation has focused on the study of machine learning techniques for sentiment analysis and topic modeling in texts from social media. It puts a special emphasis on approaches and methods for handling low-resource languages, ie …","url":["https://digibug.ugr.es/bitstream/handle/10481/72863/80733.pdf?sequence=4&isAllowed=y"]}
-{"year":"2022","title":"Machine Reading at Scale: A Search Engine for Scientific and Academic Research","authors":["N Sousa, N Oliveira, I Praça - Systems, 2022"],"snippet":"The Internet, much like our universe, is ever-expanding. Information, in the most varied formats, is continuously added to the point of information overload. Consequently, the ability to navigate this ocean of data is crucial in our day-to-day …","url":["https://www.mdpi.com/2079-8954/10/2/43/pdf"]}
-{"year":"2022","title":"Machine Reading at Scale: A Search Engine for Scientific and Academic Research. Systems 2022, 10, 43","authors":["N Sousa, N Oliveira, I Praça - 2022"],"snippet":"The Internet, much like our universe, is ever-expanding. Information, in the most varied formats, is continuously added to the point of information overload. Consequently, the ability to navigate this ocean of data is crucial in our day-to-day …","url":["https://www.mdpi.com/2079-8954/10/2/43/pdf?version=1649908028"]}
-{"year":"2022","title":"Machine Translation Performance Prediction System: Optimal Prediction for Optimal Translation","authors":["E Biçici - SN Computer Science, 2022"],"snippet":"Abstract Machine translation performance prediction (MTPP) system (MTPPS) is an automatic, accurate, language and natural language processing (NLP) output independent prediction model. MTPPS is optimal by the capability to predict …","url":["https://link.springer.com/article/10.1007/s42979-022-01183-0"]}
-{"year":"2022","title":"Machine's Conceptual Development Using FNet","authors":["D Jayanna - 2022"],"snippet":"Masked language modeling (MLM) is a well-known technique in Natural languageprocessing (NLP) to train a model on randomly masked tokens and use the trainedmodel to predict the masked words. FNet is a recently developed Fourier …","url":["https://search.proquest.com/openview/8e85ce3a1dea6ec809b32142fbb3db6c/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"Making AI work for skills-based training: A case study","authors":["R Robson, E Kelsey, A Goel, L Egerton, S Nasir…"],"snippet":"Motivated by the need to upskill workers rapidly and equitably in response to changes in work and the workplace, a team funded by the US National Science Foundation Convergence Accelerator program has developed and piloted an …","url":["https://www.researchgate.net/profile/Robby-Robson/publication/361742207_Extended_Abstract_Making_AI_work_for_skills-based_training_A_case_study/links/62c2fbd0c692f45113050e62/Extended-Abstract-Making-AI-work-for-skills-based-training-A-case-study.pdf"]}
-{"year":"2022","title":"MalGen: Malware Generation with Specific Behaviors to Improve Machine Learning-based Detectors.","authors":["M Smith, A Carbajal, E Domschot, NT Johnson… - 2022"],"snippet":"In recent years, infections and damage caused by malware have increased at exponential rates. At the same time, machine learning (ML) techniques have shown tremendous promise in many domains, often out performing human efforts by …","url":["https://www.osti.gov/servlets/purl/1893244"]}
-{"year":"2022","title":"MANER: Mask Augmented Named Entity Recognition for Extreme Low-Resource Languages","authors":["S Sonkar, Z Wang, RG Baraniuk - arXiv preprint arXiv:2212.09723, 2022"],"snippet":"This paper investigates the problem of Named Entity Recognition (NER) for extreme low-resource languages with only a few hundred tagged data samples. NER is a fundamental task in Natural Language Processing (NLP). A critical driver …","url":["https://arxiv.org/pdf/2212.09723"]}
-{"year":"2022","title":"Manifold's English-Chinese System at WMT22 General MT Task","authors":["C Jin, T Shi, Z Xue, X Lin - Proceedings of the Seventh Conference on Machine …, 2022"],"snippet":"Manifold’s English-Chinese System at WMT22 is an ensemble of 4 models trained by different configurations with scheduled sampling-based fine-tuning. The four configurations are DeepBig (XenC), DeepLarger (XenC), DeepBig-TalkingHeads (XenC) …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.20.pdf"]}
-{"year":"2022","title":"Many Languages, One Deep Learning Model Multilingual understanding is easier than you think!","authors":["C Wolfe"],"snippet":"How do we enable natural language-based deep learning systems to understand data in many languages? One naive approach would be to simply train a separate deep learning model on each of the desired languages. But, this approach is pretty …","url":["https://towardsdatascience.com/many-languages-one-deep-learning-model-69201d02dee1"]}
-{"year":"2022","title":"Marathi Social Media Opinion Mining using XLM-R","authors":["N Rathod, N Mistry, D Talati, M Parikh, A Kore… - … International Conference on …, 2022"],"snippet":"… XLM-R is a transformer-based multilingual masked model pre-trained on CommonCrawl data in 100 languages with base having 250M parameters, which obtains state-of-the-art results in the tasks of question answering, sequence labeling …","url":["https://ieeexplore.ieee.org/abstract/document/9793308/"]}
-{"year":"2022","title":"Match the Script, Adapt if Multilingual: Analyzing the Effect of Multilingual Pretraining on Cross-lingual Transferability","authors":["Y Fujinuma, J Boyd-Graber, K Kann - arXiv preprint arXiv:2203.10753, 2022"],"snippet":"Pretrained multilingual models enable zero-shot learning even for unseen languages, and that performance can be further improved via adaptation prior to finetuning. However, it is unclear how the number of pretraining languages …","url":["https://arxiv.org/pdf/2203.10753"]}
-{"year":"2022","title":"Matching Tweets With Applicable Fact-Checks Across Languages","authors":["A Kazemi, Z Li, V Pérez-Rosas, SA Hale, R Mihalcea - arXiv preprint arXiv …, 2022"],"snippet":"… The model is trained on more than 2TBs CommonCrawl data and supports one hundred languages. We also rely on recent language … language modeling trained on 17 billion monolingual sentences from CommonCrawl and 6 billion translated …","url":["https://arxiv.org/pdf/2202.07094"]}
-{"year":"2022","title":"Measuring document similarity with weighted averages of word embeddings.","authors":["B Seegmiller, D Papanikolaou, LDW Schmidt - Explorations in Economic History, 2022"],"snippet":"We detail a methodology for estimating the textual similarity between two documents while accounting for the possibility that two different words can have a similar meaning. We illustrate the method’s usefulness in facilitating comparisons between …","url":["https://www.sciencedirect.com/science/article/pii/S0014498322000729"]}
-{"year":"2022","title":"Measuring Gender Bias in Word Embeddings of Gendered Languages Requires Disentangling Grammatical Gender Signals","authors":["SO Sabbaghi, A Caliskan - arXiv preprint arXiv:2206.01691, 2022"],"snippet":"Does the grammatical gender of a language interfere when measuring the semantic gender information captured by its word embeddings? A number of anomalous gender bias measurements in the embeddings of gendered languages suggest this …","url":["https://arxiv.org/pdf/2206.01691"]}
-{"year":"2022","title":"Measuring harmful and toxic representations in Scandinavian language models","authors":["S Touileb"],"snippet":"… Combination of Danish texts from Common Crawl, Wikipedia, debate forums, and OpenSubtitles. DanishRoBERTa Danish subset of mC4 (from the Common Crawl). …","url":["https://mediafutures.no/wp-content/uploads/WP-5-1-ST_MF_annual_meeting_2022-min.pdf"]}
-{"year":"2022","title":"Measuring Harmful Representations in Scandinavian Language Models","authors":["S Touileb, D Nozza - arXiv preprint arXiv:2211.11678, 2022"],"snippet":"… trained on subsets of the Common Crawl corpus. The remaining four models were trained on datasets comprising languagespecific subsets from the Common Crawl. As previous works have shown that this corpus contains various types of …","url":["https://arxiv.org/pdf/2211.11678"]}
-{"year":"2022","title":"MEASURING NETWORK INTERFERENCE AND MITIGATING IT WITH DNS ENCRYPTION","authors":["SA Akhavan Niaki - 2022"],"snippet":"The Internet has emerged as one of the most important tools of communication. With around 4.5 billion active users as of July 2020, it provides people the opportunity to access a vast treasure trove of information and express their opinions online. How-ever …","url":["https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=3583&context=dissertations_2"]}
-{"year":"2022","title":"Measuring Similarity by Linguistic Features rather than Frequency","authors":["R Delmonte, N Busetto"],"snippet":"… As said above, we used BERT – with the Italian model taken from UWAC corpus, Umbertocommoncrawl - and examined the output of the first or projection layer5. In this way we intended to check the predicting ability of BERT on the masked word, by …","url":["https://sigsem.uvt.nl/isa18/ISA-18_11_Paper.pdf"]}
-{"year":"2022","title":"Measuring the Impact of (Psycho-) Linguistic and Readability Features and Their Spill Over Effects on the Prediction of Eye Movement Patterns","authors":["D Wiechmann, Y Qiao, E Kerz, J Mattern - arXiv preprint arXiv:2203.08085, 2022"],"snippet":"… BERT is trained on the BooksCorpus (800M words) and Wikipedia (2,500M words), whereas GPT-2 is trained on WebText, an 8-million documents subset of CommonCrawl amounting to 40 GB of text. We chose the BERT base model (cased) …","url":["https://arxiv.org/pdf/2203.08085"]}
-{"year":"2022","title":"Memory in humans and deep language models: Linking hypotheses for model augmentation","authors":["O Raccah, P Chen, TL Willke, D Poeppel, VA Vo - arXiv preprint arXiv:2210.01869, 2022"],"snippet":"The computational complexity of the self-attention mechanism in Transformer models significantly limits their ability to generalize over long temporal durations. Memory-augmentation, or the explicit storing of past information in external memory …","url":["https://web7.arxiv.org/pdf/2210.01869"]}
-{"year":"2022","title":"Mental Health Disorder Identification From Motivational Conversations","authors":["T Saha, SM Reddy, S Saha, P Bhattacharyya - IEEE Transactions on Computational …, 2022"],"snippet":"… 1) Embedding Features: To extract textual features of an utterance U having nu number of words, the representation of each of the words, w1,...,wu, where wi ∈ Rdu , wi s are obtained from the GloVe embeddings trained on the Common Crawl …","url":["https://ieeexplore.ieee.org/abstract/document/9729467/"]}
-{"year":"2022","title":"Menu close","authors":["J Ogden, M Kurzmeier, F Clavert, M Currie - 2022"],"snippet":"The aim of this guide is to provide a starting point for using web archives as a source for social science research. This guide provides a primer for how to approach web archives research design by first outlining what web archives are and how they differ …","url":["https://methods.sagepub.com/how-to-guide/how-to-design-web-archives-research"]}
-{"year":"2022","title":"Meta-Learning for Offensive Language Detection in Code-Mixed Texts","authors":["G Vadakkekara Suresh, BR Chakravarthi, JP McCrae - Forum for Information …, 2021"],"snippet":"This research investigates the application of Model-Agnostic Meta-Learning (MAML) and ProtoMAML to identify offensive code-mixed text content on social media in Tamil-English and Malayalam-English code-mixed texts. We follow a two-step …","url":["https://dl.acm.org/doi/pdf/10.1145/3503162.3503167"]}
-{"year":"2022","title":"METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals","authors":["P Bajaj, C Xiong, G Ke, X Liu, D He, S Tiwary, TY Liu… - arXiv preprint arXiv …, 2022"],"snippet":"We present an efficient method of pretraining large-scale autoencoding language models using training signals generated by an auxiliary model. Originated in ELECTRA, this training strategy has demonstrated sample-efficiency to pretrain …","url":["https://arxiv.org/pdf/2204.06644"]}
-{"year":"2022","title":"mFACE: Multilingual Summarization with Factual Consistency Evaluation","authors":["R Aharoni, S Narayan, J Maynez, J Herzig, E Clark… - arXiv preprint arXiv …, 2022"],"snippet":"Abstractive summarization has enjoyed renewed interest in recent years, thanks to pre-trained language models and the availability of large-scale datasets. Despite promising results, current models still suffer from generating factually inconsistent …","url":["https://arxiv.org/pdf/2212.10622"]}
-{"year":"2022","title":"mGPT: Few-Shot Learners Go Multilingual","authors":["O Shliazhko, A Fenogenova, M Tikhonova, V Mikhailov… - arXiv preprint arXiv …, 2022"],"snippet":"Recent studies report that autoregressive language models can successfully solve many NLP tasks via zeroand few-shot learning paradigms, which opens up new possibilities for using the pre-trained language models. This paper introduces two …","url":["https://arxiv.org/pdf/2204.07580"]}
-{"year":"2022","title":"MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge","authors":["L Fan, G Wang, Y Jiang, A Mandlekar, Y Yang, H Zhu… - arXiv preprint arXiv …, 2022"],"snippet":"Autonomous agents have made great strides in specialist domains like Atari games and Go. However, they typically learn tabula rasa in isolated environments with limited and manually conceived objectives, thus failing to generalize across a wide …","url":["https://arxiv.org/pdf/2206.08853"]}
-{"year":"2022","title":"Mini-Model Adaptation: Efficiently Extending Pretrained Models to New Languages via Aligned Shallow Training","authors":["K Marchisio, P Lewis, Y Chen, M Artetxe - arXiv preprint arXiv:2212.10503, 2022"],"snippet":"… 2020) as our training corpus, which is a filtered version of CommonCrawl. We report the full list of languages along with their corpus size and linguistic details in Table 1. Each language is preprocessed individually using SentencePiece (Kudo …","url":["https://arxiv.org/pdf/2212.10503"]}
-{"year":"2022","title":"minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Models","authors":["K Misra - arXiv preprint arXiv:2203.13112, 2022"],"snippet":"We present minicons, an open source library that provides a standard API for researchers interested in conducting behavioral and representational analyses of transformer-based language models (LMs). Specifically, minicons enables …","url":["https://arxiv.org/pdf/2203.13112"]}
-{"year":"2022","title":"Misreporting and Fake News Detection Techniques on the Social Media Platform","authors":["Y Feng - Highlights in Science, Engineering and Technology, 2022"],"snippet":"… RealNews is also a news article dataset scraped from Common Crawl with newspaper python library. The training sample includes the news dump from Common Crawl ranging from December 2016 to March 2019, and the articles in …","url":["https://drpress.org/ojs/index.php/HSET/article/download/1417/1344"]}
-{"year":"2022","title":"Misspelling Semantics in Thai","authors":["P Nakwijit, M Purver"],"snippet":"User-generated content is full of misspellings. Rather than being just random noise, we hypothesise that many misspellings contain hidden semantics that can be leveraged for language understanding tasks. This paper presents a fine-grained …","url":["http://www.eecs.qmul.ac.uk/~mpurver/papers/nakwijit-purver22lrec.pdf"]}
-{"year":"2022","title":"MLGL-MP: a Multi-Label Graph Learning framework enhanced by pathway interdependence for Metabolic Pathway prediction","authors":["BX Du, PC Zhao, B Zhu, SM Yiu, AK Nyamabo, H Yu… - Bioinformatics, 2022"],"snippet":"Motivation During lead compound optimization, it is crucial to identify pathways where a drug-like compound is metabolized. Recently, machine learning-based methods have achieved inspiring progress to predict potential metabolic pathways …","url":["https://academic.oup.com/bioinformatics/article/38/Supplement_1/i325/6617514"]}
-{"year":"2022","title":"Model and Data Transfer for Cross-Lingual Sequence Labelling in Zero-Resource Settings","authors":["I García-Ferrero, R Agerri, G Rigau - arXiv preprint arXiv:2210.12623, 2022"],"snippet":"Zero-resource cross-lingual transfer approaches aim to apply supervised models from a source language to unlabelled target languages. In this paper we perform an in-depth study of the two main techniques employed so far for cross-lingual zero-resource …","url":["https://arxiv.org/pdf/2210.12623"]}
-{"year":"2022","title":"Modeling Associative Reasoning Processes","authors":["U Furbach, C Schon, M Ragni - arXiv preprint arXiv:2201.00716, 2022"],"snippet":"The human capability to reason about one domain by using knowledge of other domains has been researched for more than 50 years, but models that are formally sound and predict cognitive process are sparse. We propose a formally sound …","url":["https://arxiv.org/pdf/2201.00716"]}
-{"year":"2022","title":"Modeling Intensification for Sign Language Generation: A Computational Approach","authors":["M İnan, Y Zhong, S Hassan, L Quandt, M Alikhani - arXiv preprint arXiv:2203.09679, 2022"],"snippet":"End-to-end sign language generation models do not accurately represent the prosody in sign language. A lack of temporal and spatial variations leads to poor-quality generated presentations that confuse human interpreters. In this paper, we aim to …","url":["https://arxiv.org/pdf/2203.09679"]}
-{"year":"2022","title":"Modeling Target-Side Morphology in Neural Machine Translation: A Comparison of Strategies","authors":["MWD Marco, M Huck, A Fraser - arXiv preprint arXiv:2203.13550, 2022"],"snippet":"Morphologically rich languages pose difficulties to machine translation. Machine translation engines that rely on statistical learning from parallel training data, such as state-of-the-art neural systems, face challenges especially with rich morphology …","url":["https://arxiv.org/pdf/2203.13550"]}
-{"year":"2022","title":"Modelling Commonsense Properties using Pre-Trained Bi-Encoders","authors":["A Gajbhiye, L Espinosa-Anke, S Schockaert - arXiv preprint arXiv:2210.02771, 2022"],"snippet":"Grasping the commonsense properties of everyday concepts is an important prerequisite to language understanding. While contextualised language models are reportedly capable of predicting such commonsense properties with human-level …","url":["https://arxiv.org/pdf/2210.02771"]}
-{"year":"2022","title":"MODERN INFORMATION TECHNOLOGIES AND IT-EDUCATION","authors":["AM NEGANOV - MODERN INFORMATION, 2022"],"snippet":"… The experiments in this section are performed with a CommonCrawl data . The CommonCrawl is an open repository of web crawl data. Said … The vocabulary of the CommonCrawl text is plenty rich due to nearly all human languages present in …","url":["https://elibrary.ru/item.asp?id=49299792"]}
-{"year":"2022","title":"MOE/RF: A Novel Phishing Detection Model based on Revised Multi-Objective Evolution Optimization Algorithm and Random Forest","authors":["E Zhu, Z Chen, J Cui, H Zhong - IEEE Transactions on Network and Service …, 2022"],"snippet":"To effectively boost computer usage, machine learning models are used in several phishing detection systems to classify enormous phishing datasets. Based on phishing patterns, researchers prefer to extract a considerable number of features to …","url":["https://ieeexplore.ieee.org/abstract/document/9744099/"]}
-{"year":"2022","title":"Mokey: Enabling Narrow Fixed-Point Inference for Out-of-the-Box Floating-Point Transformer Models","authors":["AH Zadeh, M Mahmoud, A Abdelhadi, A Moshovos - arXiv preprint arXiv:2203.12758, 2022"],"snippet":"Increasingly larger and better Transformer models keep advancing state-of-the-art accuracy and capability for Natural Language Processing applications. These models demand more computational power, storage, and energy. Mokey reduces …","url":["https://arxiv.org/pdf/2203.12758"]}
-{"year":"2022","title":"Mono vs Multilingual BERT for Hate Speech Detection and Text Classification: A Case Study in Marathi","authors":["A Velankar, H Patil, R Joshi - arXiv preprint arXiv:2204.08669, 2022"],"snippet":"Transformers are the most eminent architectures used for a vast range of Natural Language Processing tasks. These models are pre-trained over a large text corpus and are meant to serve state-of-the-art results over tasks like text classification. In …","url":["https://arxiv.org/pdf/2204.08669"]}
-{"year":"2022","title":"MonoByte: A Pool of Monolingual Byte-level Language Models","authors":["H Abonizio, LR de Souza, R Lotufo, R Nogueira - arXiv preprint arXiv:2209.11035, 2022"],"snippet":"… 2021b), the same corpus used to train mT5 and ByT5, which comprises 101 natural languages extracted from the Common Crawl web scrape. For each model, we selected only the documents written in the specific language, which was originally …","url":["https://arxiv.org/pdf/2209.11035"]}
-{"year":"2022","title":"Moving Stuff Around","authors":["A Câmara, C Hauff - 2022"],"snippet":"When training neural rankers with Large Language models, a practitioner generally leverages multiple GPUs, which increases the amount of available VRAM, allowing larger batches, and decreasing training time. However, managing how data moves …","url":["https://reneuir.org/assets/pdfs/ReNeuIR_2022_paper_2376.pdf"]}
-{"year":"2022","title":"MSCTD: A Multimodal Sentiment Chat Translation Dataset","authors":["Y Liang, F Meng, J Xu, Y Chen, J Zhou - arXiv preprint arXiv:2202.13645, 2022"],"snippet":"Multimodal machine translation and textual chat translation have received considerable attention in recent years. Although the conversation in its natural form is usually multimodal, there still lacks work on multimodal machine translation in …","url":["https://arxiv.org/pdf/2202.13645"]}
-{"year":"2022","title":"mSLAM: Massively multilingual joint pre-training for speech and text","authors":["A Bapna, C Cherry, Y Zhang, Y Jia, M Johnson… - arXiv preprint arXiv …, 2022"],"snippet":"We present mSLAM, a multilingual Speech and LAnguage Model that learns cross-lingual cross-modal representations of speech and text by pre-training jointly on large amounts of unlabeled speech and text in multiple languages. mSLAM combines w2v-BERT …","url":["https://arxiv.org/pdf/2202.01374"]}
-{"year":"2022","title":"MuCoT: Multilingual Contrastive Training for Question-Answering in Low-resource Languages","authors":["GK Kumar, AS Gehlot, SS Mullappilly, K Nandakumar - arXiv preprint arXiv …, 2022","GKKAS Gehlot, SSMK Nandakumar - DravidianLangTech 2022, 2022"],"snippet":"Accuracy of English-language Question Answering (QA) systems has improved significantly in recent years with the advent of Transformer-based models (eg, BERT). These models are pre-trained in a self-supervised fashion with a large English text …","url":["https://aclanthology.org/2022.dravidianlangtech-1.pdf#page=33","https://arxiv.org/pdf/2204.05814"]}
-{"year":"2022","title":"Multi language Email Classification Using Transfer learning","authors":["MJC Sousa - 2022"],"snippet":"In recent years Artificial Intelligence has become a core part of many businesses, from manufacturers to service providers, AI can be found helping to improve business processes as well as providing customized experiences and support for …","url":["https://run.unl.pt/bitstream/10362/134446/1/TGI0525.pdf"]}
-{"year":"2022","title":"Multi-class sentiment analysis of urdu text using multilingual BERT","authors":["L Khan, A Amjad, N Ashraf, HT Chang - Scientific Reports, 2022"],"snippet":"Sentiment analysis (SA) is an important task because of its vital role in analyzing people’s opinions. However, existing research is solely based on the English language with limited work on low-resource languages. This study introduced a new …","url":["https://www.nature.com/articles/s41598-022-09381-9"]}
-{"year":"2022","title":"Multi-domain Neural Machine Translation","authors":["MQ Pham - 2021"],"snippet":"Today, neural machine translation (NMT) systems constitute state-of-the-art systems in machine translation. However, such translation models require relatively large train data and struggle to handle a specific domain text. A domain may consist of …","url":["https://tel.archives-ouvertes.fr/tel-03546910/document"]}
-{"year":"2022","title":"Multi-label Movie Genre Classification Using Multiple Modalities","authors":["DA LeBaron"],"snippet":"This project explores an ensemble approach to the task of multi-label movie genre classification. The proposed model combines data from movie posters, video trailer previews, text plot summaries, and metadata using separate deep networks. Other …","url":["http://cs230.stanford.edu/projects_fall_2021/reports/102983714.pdf"]}
-{"year":"2022","title":"Multi-level Distillation of Semantic Knowledge for Pre-training Multilingual Language Model","authors":["M Li, F Ding, D Zhang, L Cheng, H Hu, F Luo - arXiv preprint arXiv:2211.01200, 2022"],"snippet":"Pre-trained multilingual language models play an important role in cross-lingual natural language understanding tasks. However, existing methods did not focus on learning the semantic structure of representation, and thus could not optimize their …","url":["https://arxiv.org/pdf/2211.01200"]}
-{"year":"2022","title":"Multi-modal Chest X-Ray analysis: classification and report generation using self-supervised learning","authors":["N Brazzale - 2022"],"snippet":"Automated medical systems for classification, localization and diagnosis are increasingly being researched and developed. Accurate and automated disease detection is beneficial both to medical personnel, who do not have to perform …","url":["https://aaltodoc.aalto.fi/bitstream/handle/123456789/116259/master_Brazzale_Nicola_2022.pdf?sequence=1"]}
-{"year":"2022","title":"Multi-objective search for gender-fair and semantically correct word embeddings","authors":["M Hort, R Moussa, F Sarro - Applied Soft Computing, 2022"],"snippet":"Fairness is a crucial non-functional requirement of modern software systems that rely on the use of Artificial Intelligence (AI) to make decisions regarding our daily lives in application domains such as justice, healthcare and education. In fact, these …","url":["https://www.sciencedirect.com/science/article/pii/S1568494622009656"]}
-{"year":"2022","title":"Multi-source Multi-domain Sentiment Analysis with BERT-based Models","authors":["G Roccaruna"],"snippet":"… FEEL-IT, the other BERTbased model, is a sentiment classifier based on UmBERTo2, which inherits the RoBERTa architecture and is pre-trained on Commoncrawl ITA. FEEL-IT has only one head used for predicting positive and …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.62.pdf"]}
-{"year":"2022","title":"Multi-task learning for toxic comment classification and rationale extraction","authors":["KB Nelatoori, HB Kommanti - Journal of Intelligent Information Systems, 2022"],"snippet":"Social media content moderation is the standard practice as on today to promote healthy discussion forums. Toxic span prediction is helpful for explaining the toxic comment classification labels, thus is an important step towards building automated …","url":["https://link.springer.com/article/10.1007/s10844-022-00726-4"]}
-{"year":"2022","title":"Multi-Wiki90k: Multilingual Benchmark Dataset for Paragraph Segmentation","authors":["M Swędrowski, P Miłkowski, B Bojanowski, J Kocoń - Conference on Computational …, 2022"],"snippet":"In this paper, we present paragraph segmentation using cross-lingual knowledge transfer models. In our solution, we investigate the quality of multilingual models, such as mBERT and XLM-RoBERTa, as well as language independent models …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16210-7_11"]}
-{"year":"2022","title":"Multiaztertest@ Exist-Iberlef2022: Sexism Identification in Social Networks","authors":["K Bengoetxea, A Aguirregoitia - 2022"],"snippet":"The automatic identification of sexism and the categorization of the message in different types of sexism in social networks is the focus of the systems taking part in the EXIST-IberLEF 2022 shared task. Detecting online sexism and encouraging …","url":["http://ceur-ws.org/Vol-3202/exist-paper8.pdf"]}
-{"year":"2022","title":"Multidimensional tie strength and economic development","authors":["LM Aiello, S Joglekar, D Quercia - Scientific Reports, 2022"],"snippet":"The strength of social relations has been shown to affect an individual’s access to opportunities. To date, however, the correspondence between tie strength and population’s economic prospects has not been quantified, largely because of the …","url":["https://www.nature.com/articles/s41598-022-26245-4"]}
-{"year":"2022","title":"Multilingual and Multitarget Hate Speech Detection in Tweets","authors":["PCF Benamara, V Moriceau, MCGA Kumar"],"snippet":"Social media networks have become a space where users are free to relate their opinions and sentiments which may lead to a large spreading of hatred or abusive messages which have to be moderated. This paper proposes a supervised …","url":["https://www.academia.edu/download/83169351/66.pdf"]}
-{"year":"2022","title":"Multilingual Auxiliary Tasks Training: Bridging the Gap between Languages for Zero-Shot Transfer of Hate Speech Detection Models","authors":["S Montariol, A Riabi, D Seddah - arXiv preprint arXiv:2210.13029, 2022"],"snippet":"Zero-shot cross-lingual transfer learning has been shown to be highly challenging for tasks involving a lot of linguistic specificities or when a cultural gap is present between languages, such as in hate speech detection. In this paper, we highlight …","url":["https://arxiv.org/pdf/2210.13029"]}
-{"year":"2022","title":"Multilingual Bidirectional Unsupervised Translation Through Multilingual Finetuning and Back-Translation","authors":["B Li, A Patel, C Callison-Burch, MS Rasooli - arXiv preprint arXiv:2209.02821, 2022"],"snippet":"… Some mined web data is available even for these low-resource languages, of which we use CommonCrawl and CC-100 datasets. … For the 8 test languages we draw from Common Crawl17 for {kk, gu, is} and CC-10018 for {my, ps, lv, ne, si}. …","url":["https://arxiv.org/pdf/2209.02821"]}
-{"year":"2022","title":"Multilingual fine-tuning for Grammatical Error Correction","authors":["K Pajak, D Pajak - Expert Systems with Applications, 2022"],"snippet":"… mT5 was pre-trained on a large mC4 dataset covering 101 languages and containing 26 TB of the Common Crawl web scrape. The model was pre-trained on the span corruption task, where consecutive spans of input tokens were replaced …","url":["https://www.sciencedirect.com/science/article/pii/S0957417422003773"]}
-{"year":"2022","title":"Multilingual Hate Speech Detection","authors":["V Lavrentiadou - 2022"],"snippet":"… It was trained on 100 languages, of a CommonCrawl Corpus, and it outperforms multilingual BERT on crosslingual classification. XLM-… The XLM-RoBERTa model, on the other hand, was trained on 2.5TB of filtered CommonCrawl data across 100 …","url":["https://ikee.lib.auth.gr/record/338409/files/GRI-2022-34410.pdf"]}
-{"year":"2022","title":"Multilingual hope speech detection in English and Dravidian languages","authors":["BR Chakravarthi - International Journal of Data Science and Analytics, 2022"],"snippet":"Recent work on language technology has aimed to identify negative language such as hate speech and cyberbullying as well as improve offensive language detection to mediate social media platforms. Most of these systems rely on using machine …","url":["https://link.springer.com/article/10.1007/s41060-022-00341-0"]}
-{"year":"2022","title":"Multilingual Language Model Adaptive Fine-Tuning: A Study on African Languages","authors":["JO Alabi, DI Adelani, M Mosbach, D Klakow - arXiv preprint arXiv:2204.06487, 2022"],"snippet":"Multilingual pre-trained language models (PLMs) have demonstrated impressive performance on several downstream tasks on both high resourced and low-resourced languages. However, there is still a large performance drop for languages unseen …","url":["https://arxiv.org/pdf/2204.06487"]}
-{"year":"2022","title":"Multilingual Name Entity Recognition and Intent Classification employing Deep Learning architectures","authors":["S Rizou, A Paflioti, A Theofilatos, A Vakali… - … Modelling Practice and …, 2022"],"snippet":"… For the fastText initialization we use a model which is pre-trained in Common Crawl and Wikipedia. … For the fastText initialization we used the model in Common Crawl and Wikipedia. For the GloVe initialization we used the 300 dimensional …","url":["https://www.sciencedirect.com/science/article/pii/S1569190X22000995"]}
-{"year":"2022","title":"Multilingual Natural Language Understanding for the FPT. AI Conversational Platform","authors":["P Le-Hong, TTL Nguyen, MT Pham, TH Vu - 2022 14th International Conference on …, 2022"],"snippet":"This paper presents a multilingual natural language understanding model which is based on BERT and ELECTRA neural networks. The model is pre-trained and fine-tuned on large datasets of four languages: Indonesian, Malaysian, Japanese and …","url":["https://ieeexplore.ieee.org/abstract/document/9953794/"]}
-{"year":"2022","title":"Multilingual Relation Classification via Efficient and Effective Prompting","authors":["Y Chen, D Harbecke, L Hennig - arXiv preprint arXiv:2210.13838, 2022"],"snippet":"Prompting pre-trained language models has achieved impressive performance on various NLP tasks, especially in low data regimes. Despite the success of prompting in monolingual settings, applying prompt-based methods in multilingual scenarios …","url":["https://arxiv.org/pdf/2210.13838"]}
-{"year":"2022","title":"Multilingual Representation Distillation with Contrastive Learning","authors":["W Tan, K Heffernan, H Schwenk, P Koehn - arXiv preprint arXiv:2210.05033, 2022"],"snippet":"Multilingual sentence representations from large models can encode semantic information from two or more languages and can be used for different cross-lingual information retrieval tasks. In this paper, we integrate contrastive learning into …","url":["https://arxiv.org/pdf/2210.05033"]}
-{"year":"2022","title":"Multilingual Sequence-to-Sequence Models for Hebrew NLP","authors":["M Eyal, H Noga, R Aharoni, I Szpektor, R Tsarfaty - arXiv preprint arXiv:2212.09682, 2022"],"snippet":"… 2021) in comparison, was trained on mC4, where its public replica1 is a 27TB collection of natural text in 101 languages drawn from the public Common Crawl, 66GB of which is Hebrew (4.125x more Hebrew training data compared to …","url":["https://arxiv.org/pdf/2212.09682"]}
-{"year":"2022","title":"Multilingual taxonomic text classification in an incremental number of languages","authors":["G CAMPESAN","N Navarin, G Campesan"],"snippet":"Taxonomic text classification is the Natural Language Processing (NLP) branch that aims at classifying text into a hierarchically organized schema. Its applications space from pure research to industrial and commercial purposes. In this thesis, in particular …","url":["https://thesis.unipd.it/bitstream/20.500.12608/36061/1/Campesan_Giulia.pdf","https://www.academia.edu/download/92194078/Campesan_Giulia.pdf"]}
-{"year":"2022","title":"Multilingual Transformer Encoders: a Word-Level Task-Agnostic Evaluation","authors":["F Gaschi, F Plesse, P Rastin, Y Toussaint - arXiv preprint arXiv:2207.09076, 2022"],"snippet":"… However, it could also be explained by the fact that mBERT is trained solely on Wikipedia whereas models like XLM-R are trained on the CommonCrawl corpus which might contain texts that are less comparable across languages. It is also to be …","url":["https://arxiv.org/pdf/2207.09076"]}
-{"year":"2022","title":"Multilingual Transformers for Product Matching--Experiments and a New Benchmark in Polish","authors":["A Wróblewska, S Tkachuk, S Łukasik - arXiv preprint arXiv:2205.15712, 2022"],"snippet":"… The authors of these studies extracted offers from websites collected under the CommonCrawl project.The selection of offers was based on the schema.org8 tags, which Internet sellers had started using in the last five … 7commoncrawl.org 8schema.org …","url":["https://arxiv.org/pdf/2205.15712"]}
-{"year":"2022","title":"Multilinguals at SemEval-2022 Task 11: Complex NER in Semantically Ambiguous Settings for Low Resource Languages","authors":["A Pandey, S Daw, N Unnam, V Pudi - Proceedings of the 16th International Workshop …, 2022"],"snippet":"We leverage pre-trained language models to solve the task of complex NER for two low-resource languages: Chinese and Spanish. We use the technique of Whole Word Masking (WWM) to boost the performance of masked language modeling …","url":["https://aclanthology.org/2022.semeval-1.201.pdf"]}
-{"year":"2022","title":"Multimodal Graph for Unaligned Multimodal Sequence Analysis via Graph Convolution and Graph Pooling","authors":["S Mai, S Xing, J He, Y Zeng, H Hu - ACM Transactions on Multimedia Computing …, 2022"],"snippet":"Multimodal sequence analysis aims to draw inferences from visual, language and acoustic sequences. A majority of existing works focus on the aligned fusion of three modalities to explore inter-modal interactions, which is impractical in real-world …","url":["https://dl.acm.org/doi/pdf/10.1145/3542927"]}
-{"year":"2022","title":"Multimodal sentiment analysis in real-life videos","authors":["L Stappen - 2022"],"snippet":"This thesis extends the emerging field of multimodal sentiment analysis of real-life videos, taking two components into consideration: the emotion and the emotion’s target. The emotion component of media is traditionally represented as a segment-based …","url":["https://opus.bibliothek.uni-augsburg.de/opus4/files/98988/Stappen_MultimodalSentimentAnalysisinReal-lifeVideos.pdf"]}
-{"year":"2022","title":"Multimodality for NLP-Centered Applications: Resources, Advances and Frontiers","authors":["M Garg, S Wazarkar, M Singh, O Bojar"],"snippet":"With advancements in the methods of Natural Language Processing (NLP) by explicitly considering other modalities than just text, the resurgence of multimodal datasets has attracted significant attention. However, there remains lack of a …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.738.pdf"]}
-{"year":"2022","title":"Multitasking of sentiment detection and emotion recognition in code-mixed Hinglish data","authors":["S Ghosh, A Priyankar, A Ekbal, P Bhattacharyya - Knowledge-Based Systems, 2022"],"snippet":"As the number of non-native English speakers on social media has skyrocketed in recent years, sentiment and emotion analysis on regional languages and code-mixed data has gained traction. Despite extensive research on English, the area of Hindi-English …","url":["https://www.sciencedirect.com/science/article/pii/S0950705122012783"]}
-{"year":"2022","title":"MUST-VQA: MUltilingual Scene-text VQA","authors":["E Vivoli, AF Biten, A Mafla, D Karatzas, L Gomez - arXiv preprint arXiv:2209.06730, 2022"],"snippet":"… The mT5 model was trained on a 101-language Common Crawl-based multilingual variation. Only English Common Crawl is what T5 has been pre-trained on. Additionally an increase in performance is obtained by the use of GeGLU nonlinearities [31]. …","url":["https://arxiv.org/pdf/2209.06730"]}
-{"year":"2022","title":"Mutual Relation of Machine Translation and Quality Estimation","authors":["I Tryhubyshyn - 2022"],"snippet":"Machine Translation Quality Estimation predicts quality scores for translations produced by Machine Translation systems based on source and output segments. Quality Estimation systems are usually trained in a supervised manner using training …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/175591/120426924.pdf?sequence=1"]}
-{"year":"2022","title":"naab: A ready-to-use plug-and-play corpus for Farsi","authors":["S Sabouri, E Rahmati, S Gooran, H Sameti - arXiv preprint arXiv:2208.13486, 2022"],"snippet":"… 2020) in Farsi is a 70GB cleaned text corpus from a compilation of 8 (Common Crawl - fa (Crawl… 2022) or Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the …","url":["https://arxiv.org/pdf/2208.13486"]}
-{"year":"2022","title":"NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis","authors":["SH Muhammad, DI Adelani, IS Ahmad, I Abdulmumin… - arXiv preprint arXiv …, 2022"],"snippet":"Sentiment analysis is one of the most widely studied applications in NLP, but most work focuses on languages with large amounts of data. We introduce the first large-scale human-annotated Twitter sentiment dataset for the four most widely spoken …","url":["https://arxiv.org/pdf/2201.08277"]}
-{"year":"2022","title":"NamedEntityRangers at SemEval-2022 Task 11: Transformer-based Approaches for Multilingual Complex Named Entity Recognition","authors":["A Miftahova, A Pugachev, A Skiba, K Artemova… - Proceedings of the 16th …, 2022"],"snippet":"This paper presents the two submissions of NamedEntityRangers Team to the MultiCoNER Shared Task, hosted at SemEval-2022. We evaluate two state-of-the-art approaches, of which both utilize pre-trained multi-lingual language models …","url":["https://aclanthology.org/2022.semeval-1.216.pdf"]}
-{"year":"2022","title":"NapierOne: A modern mixed file data set alternative to Govdocs1","authors":["SR Davies, R Macfarlane, WJ Buchanan - Forensic Science International: Digital …, 2022"],"snippet":"It was found when reviewing the ransomware detection research literature that almost no proposal provided enough detail on how the test data set was created, or sufficient description of its actual content, to allow it to be recreated by other …","url":["https://arxiv.org/pdf/2201.08154"]}
-{"year":"2022","title":"Natural Language Correction With Focus on Czech","authors":["J Náplava - 2022"],"snippet":"Natural language correction, a subfield of natural language processing (NLP), is the task of automatically correcting user errors in written texts. It includes, but is not limited to, grammatical error correction, spelling error correction and diacritics …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/174730/140102103.pdf?sequence=1"]}
-{"year":"2022","title":"Natural Language Inference with Self-Attention for Veracity Assessment of Pandemic Claims","authors":["M Arana-Catania, E Kochkina, A Zubiaga, M Liakata… - arXiv preprint arXiv …, 2022"],"snippet":"… on the health domain focused on information retrieval from general websites through the Common Crawl corpus (commoncrawl.org). … Research challenge using claims on the health domain focused on information retrieval from general …","url":["https://arxiv.org/pdf/2205.02596"]}
-{"year":"2022","title":"Natural Language Processing in toxicology: Delineating Adverse Outcome Pathways and guiding the application of New Approach Methodologies","authors":["MPF Corradi, AM de Haan, B Staumont, AH Piersma… - Biomaterials and …, 2022"],"snippet":"Adverse Outcome Pathways (AOPs) are conceptual frameworks that tie an initial perturbation (molecular initiating event) to a phenotypic toxicological manifestation (adverse outcome), through a series of steps (key events). They provide therefore a …","url":["https://www.sciencedirect.com/science/article/pii/S266653442200023X"]}
-{"year":"2022","title":"Natural Questions in Icelandic","authors":["V Snæbjarnarson, H Einarsson"],"snippet":"We present the first extractive question answering (QA) dataset for Icelandic, Natural Questions in Icelandic (NQiI). Developing such datasets is important for the development and evaluation of Icelandic QA systems. It also aids in the …","url":["https://vesteinn.is/uploads/snaebjarnarson2022natural.pdf"]}
-{"year":"2022","title":"Navigable Proximity Graph-Driven Native Hybrid Queries with Structured and Unstructured Constraints","authors":["M Wang, L Lv, X Xu, Y Wang, Q Yue, J Ni - arXiv preprint arXiv:2203.13601, 2022"],"snippet":"As research interest surges, vector similarity search is applied in multiple fields, including data mining, computer vision, and information retrieval. {Given a set of objects (eg, a set of images) and a query object, we can easily transform each object …","url":["https://arxiv.org/pdf/2203.13601"]}
-{"year":"2022","title":"Need for Wheel Speed: Generating synthetic wheel speeds using LSTM and GANs","authors":["E Berglund - 2022"],"snippet":"… One of the largest data sets available is Common crawl 1 which consists of over 5 Peta Bytes of data in total which is huge amounts of data, and it grows consistently with around 300 Tebibyte of data every two months. At this rate, it will take close to …","url":["https://www.diva-portal.org/smash/get/diva2:1694797/FULLTEXT01.pdf"]}
-{"year":"2022","title":"Nepali Encoder Transformers","authors":["U Maskey, M Bhatta, SR Bhatta, S Dhungel, BK Bal"],"snippet":"… ● XLM-RoBERTa: XLM-RoBERTa (Conneau et al., 2020) is a multi-lingual model that is trained on large dataset of filtered CommonCrawl data covering 100 languages. …","url":["https://sigul-2022.ilc.cnr.it/wp-content/uploads/2022/10/Nepali-Encoder-Transformers.pdf"]}
-{"year":"2022","title":"NER in Hindi Language Using Transformer Model: XLM-Roberta","authors":["AA Choure, RB Adhao, VK Pachghare - 2022 IEEE International Conference on …, 2022"],"snippet":"… It has been pre-trained on 2.5 TB of filtered Common-Crawl data with hundred languages. It was pre-trained with the Masked language modeling (MLM) goal. Taking a sentence as an example, the model masks 15% of the words in the input at …","url":["https://ieeexplore.ieee.org/abstract/document/9935841/"]}
-{"year":"2022","title":"NerKor+ Cars-OntoNotes+","authors":["A Novák, B Novák"],"snippet":"In this paper, we present an upgraded version of the Hungarian NYTK-NerKor named entity corpus, which contains about twice as many annotated spans and 7 times as many distinct entity types as the original version. We used an extended …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.203.pdf"]}
-{"year":"2022","title":"Net impact of large language models trained on code","authors":["P Gherciu - … tehnico-ştiinţifică a studenţilor, masteranzilor şi …, 2022"],"snippet":"Natural language processing has seen many improvements in recent years, particularly driven by machine learning models such as OpenAI’s GPT-3. This paper aims to present the various language models, as well as OpenAI Codex, which is …","url":["https://ibn.idsi.md/sites/default/files/imag_file/p-189-192.pdf"]}
-{"year":"2022","title":"Neural Approaches to Conversational Information Retrieval","authors":["J Gao, C Xiong, P Bennett, N Craswell - arXiv preprint arXiv:2201.05176, 2022"],"snippet":"A conversational information retrieval (CIR) system is an information retrieval (IR) system with a conversational interface which allows users to interact with the system to seek information via multi-turn conversations of natural language, in spoken or …","url":["https://arxiv.org/pdf/2201.05176"]}
-{"year":"2022","title":"Neural Language Models as What If?-Engines for HCI Research","authors":["P Hämäläinen, M Tavast, A Kunnari - 27th International Conference on Intelligent …, 2022"],"snippet":"Collecting data is one of the bottlenecks of Human-Computer Interaction (HCI) and user experience (UX) research. In this poster paper, we explore and critically evaluate the potential of large-scale neural language models like GPT-3 in …","url":["https://dl.acm.org/doi/abs/10.1145/3490100.3516458"]}
-{"year":"2022","title":"Neural machine translation for Hungarian","authors":["LJ Laki, ZG Yang - Acta Linguistica Academica, 2022"],"snippet":"In the scope of this research, we aim to give an overview of the currently existing solutions for machine translation and we assess their performance on the English-Hungarian language pair. Hungarian is considered to be a challenging language for machine …","url":["https://akjournals.com/view/journals/2062/aop/article-10.1556-2062.2022.00576/article-10.1556-2062.2022.00576.xml"]}
-{"year":"2022","title":"Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning","authors":["E Erdem, M Kuyu, S Yagcioglu, A Frank…"],"snippet":"Developing artificial learning systems that can understand and generate natural language has been one of the long-standing goals of artificial intelligence. Recent decades have witnessed an impressive progress on both of these problems, giving …","url":["https://web.cs.hacettepe.edu.tr/~erkut/publications/nnlg-survey.pdf"]}
-{"year":"2022","title":"Neural text summarization for Hungarian","authors":["ZG Yang - Acta Linguistica Academica, 2022"],"snippet":"… One of the most prominent representative dataset in this category is the Common Crawl. However, despite the fact that web scraping can give rise to large datasets, the filtering and the cleaning of data can be still challenging and often claimed as a …","url":["https://akjournals.com/view/journals/2062/aop/article-10.1556-2062.2022.00577/article-10.1556-2062.2022.00577.xml"]}
-{"year":"2022","title":"Neural Transfer Learning For Vietnamese Sentiment Analysis Using Pre-trained Contextual Language Models","authors":["AP Le, TV Pham, TV Le, DV Huynh - 2021 IEEE International Conference on Machine …, 2021"],"snippet":"We propose a fine-tuning methodology and a comprehensive comparison between state-of-the-art pre-trained language models (PLM) when applying to Vietnamese Sentiment Analysis. The fine-tuning architecture includes three main components: (1) …","url":["https://ieeexplore.ieee.org/abstract/document/9690554/"]}
-{"year":"2022","title":"New directions in empirical asset pricing: information, innovation, and stock returns","authors":["J Vahl - 2022"],"snippet":"This dissertation is a collection of three essays that explore new directions in empirical asset pricing. The first essay studies the role of textual information in analyst reports. I show that analysts use the report text to convey soft information that …","url":["https://open.library.ubc.ca/media/download/pdf/24/1.0417337/4"]}
-{"year":"2022","title":"New meaning for NLP: the trials and tribulations of natural language processing with GPT-3 in ophthalmology","authors":["S Nath, A Marie, S Ellershaw, E Korot, PA Keane - British Journal of Ophthalmology, 2022"],"snippet":"Natural language processing (NLP) is a subfield of machine intelligence focused on the interaction of human language with computer systems. NLP has recently been discussed in the mainstream media and the literature with the advent of Generative …","url":["https://bjo.bmj.com/content/early/2022/05/06/bjophthalmol-2022-321141.abstract"]}
-{"year":"2022","title":"New Methods and the Study of Vulnerable Groups: Using Machine Learning to Identify Immigrant-Oriented Nonprofit Organizations","authors":["C Ren, I Bloemraad - Socius, 2022"],"snippet":"Many migrants are vulnerable due to noncitizenship, linguistic or cultural barriers, and inadequate safety-net infrastructures. Immigrant-oriented nonprofits can play an important role in improving immigrant well-being. However, progress on …","url":["https://journals.sagepub.com/doi/pdf/10.1177/23780231221076992"]}
-{"year":"2022","title":"News Article Classification using a Transfer Learning Approach","authors":["K Abhishek - 2022 10th International Conference on Reliability …, 2022"],"snippet":"The increasing proliferation of electronic files in recent decades has been addressed by significant improvements in Natural Language Processing. As the text data generated is quite large, employing sophisticated algorithms that can process …","url":["https://ieeexplore.ieee.org/abstract/document/9965142/"]}
-{"year":"2022","title":"NLI Models for Assessing Facticity in Summarization Methods","authors":["BJ Dusil - 2022"],"snippet":"Guidelines: The task is to: 1) Research state-of-the-art NLP approaches for text summarization, focusing on evaluation methods for assessment of generated summaries. Explore mainly model-based approaches. 2) Discuss available options …","url":["https://wiki.control.fel.cvut.cz/mediawiki/images/8/88/Dp_2022_dusil_jan.pdf"]}
-{"year":"2022","title":"NMTScore: A Multilingual Analysis of Translation-based Text Similarity Measures","authors":["J Vamvas, R Sennrich - arXiv preprint arXiv:2204.13692, 2022"],"snippet":"Being able to rank the similarity of short text segments is an interesting bonus feature of neural machine translation. Translation-based similarity measures include direct and pivot translation probability, as well as translation cross-likelihood, which …","url":["https://arxiv.org/pdf/2204.13692"]}
-{"year":"2022","title":"No Language Left Behind: Scaling Human-Centered Machine Translation","authors":["N Team, MR Costa-jussà, J Cross, O Çelebi…"],"snippet":"Driven by the goal of eradicating language barriers on a global scale, machine translation has solidified itself as a key focus of artificial intelligence research today. However, such efforts have coalesced around a small subset of languages, leaving …","url":["https://arxiv.org/pdf/2207.04672"]}
-{"year":"2022","title":"No Word Embedding Model Is Perfect: Evaluating the Representation Accuracy for Social Bias in the Media","authors":["M Spliethöver, M Keiff, H Wachsmuth - arXiv preprint arXiv:2211.03634, 2022"],"snippet":"… (2021), we collected news articles from Common Crawl3. Since the media bias rating history is not available, we mapped each outlet to its current rating. To extract the pure text from the collected files in WARC format, we used the library news-please …","url":["https://arxiv.org/pdf/2211.03634"]}
-{"year":"2022","title":"Noise Reduction Learning based on XLNet-CRF for Biomedical Named Entity Recognition","authors":["Z Chai, H Jin, S Shi, S Zhan, L Zhuo, Y Yang, Q Lian - IEEE/ACM Transactions on …, 2022"],"snippet":"In recent years, Biomedical Named Entity Recognition (BioNER) systems have mainly been based on deep neural networks, which are used to extract information from the rapidly expanding biomedical literature. Long-distance context …","url":["https://ieeexplore.ieee.org/abstract/document/9730067/"]}
-{"year":"2022","title":"Noise-Reduction for Automatically Transferred Relevance Judgments","authors":["M Fröbe, C Akiki, M Potthast, M Hagen"],"snippet":"The TREC Deep Learning tracks used MS MARCO Version 1 as their official training data until 2020 and switched to Version 2 in 2021. For Version 2, all previously judged documents were re-crawled. Interestingly, in the track’s 2021 edition, models …","url":["https://webis.de/downloads/publications/papers/froebe_2022d.pdf"]}
-{"year":"2022","title":"Nominalizations with the suffixes-ee and-ation A distributional semantic analysis","authors":["V Schneider, I Plag"],"snippet":"… • FastText Common Crawl subword model (Bojanowski et al. 2016, Mikolov et al. 2018) … • FastText Common Crawl subword model (Bojanowski et al. 2016, Mikolov et al. 2018) … • FastText Common Crawl subword model (Bojanowski et al. 2016 …","url":["https://frames.phil.uni-duesseldorf.de/wp-content/uploads/2022/11/InSemantic22_Schneider.pdf"]}
-{"year":"2022","title":"Non-Autoregressive Machine Translation: It's Not as Fast as it Seems","authors":["J Helcl, B Haddow, A Birch - arXiv preprint arXiv:2205.01966, 2022"],"snippet":"Efficient machine translation models are commercially important as they can increase inference speeds, and reduce costs and carbon emissions. Recently, there has been much interest in non-autoregressive (NAR) models, which promise faster …","url":["https://arxiv.org/pdf/2205.01966"]}
-{"year":"2022","title":"Normalization and Attention","authors":["JC Ye - Geometry of Deep Learning, 2022"],"snippet":"… Sixty percent of the training data set comes from a filtered version of Common Crawl consisting of 410 billion tokens. Other sources are 19 billion tokens from WebText2, 12 billion tokens from Books1, 55 billion tokens from Books2, and 3 …","url":["https://link.springer.com/chapter/10.1007/978-981-16-6046-7_9"]}
-{"year":"2022","title":"NT5 at WMT 2022 General Translation Task","authors":["M Morishita, K Kudo, Y Oka, K Chousa, S Kiyono…"],"snippet":"… Monolingual Corpus We also used the following provided monolingual data: News Crawl, News Commentary, and Common Crawl. We backtranslated the monolingual sentences with a targetto-source model trained only with the provided …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.25.pdf"]}
-{"year":"2022","title":"NULL at SemEval-2022 Task 6: Intended Sarcasm Detection Using Stylistically Fused Contextualized Representation and Deep Learning","authors":["M Rahgouy, HB Giglou, T Rahgooy, C Seals - … of the 16th International Workshop on …, 2022"],"snippet":"… ), which is pre-trained on 2.5TB of CommonCrawl data containing 100 languages. The model learns an inner representation of 100 languages that can then be used to extract features useful for downstream tasks. The function CE ∈ R768 is a base …","url":["https://aclanthology.org/2022.semeval-1.120.pdf"]}
-{"year":"2022","title":"NUS-IDS at CheckThat! 2022: Identifying Check-worthiness of Tweets using CheckthaT5","authors":["M Du, SD Gollapalli, SK Ng - Working Notes of CLEF, 2022"],"snippet":"This paper describes our system CheckthaT5, which was designed in the context of the Checkthat! 2022 competition at CLEF. CheckthaT5 explores the feasibility of adapting sequence-to-sequence models for detecting check-worthy social media …","url":["http://ceur-ws.org/Vol-3180/paper-36.pdf"]}
-{"year":"2022","title":"NusaCrowd: Open Source Initiative for Indonesian NLP Resources","authors":["S Cahyawijaya, H Lovenia, AF Aji, GI Winata, B Wilie… - arXiv preprint arXiv …, 2022"],"snippet":"We present NusaCrowd, a collaborative initiative to collect and unite existing resources for Indonesian languages, including opening access to previously non-public resources. Through this initiative, we have has brought together 137 datasets and …","url":["https://arxiv.org/pdf/2212.09648"]}
-{"year":"2022","title":"OCHADAI at SemEval-2022 Task 2: Adversarial Training for Multilingual Idiomaticity Detection","authors":["LK Pereira, I Kobayashi - arXiv preprint arXiv:2206.03025, 2022"],"snippet":"We propose a multilingual adversarial training model for determining whether a sentence contains an idiomatic expression. Given that a key challenge with this task is the limited size of annotated data, our model relies on pre-trained contextual …","url":["https://arxiv.org/pdf/2206.03025"]}
-{"year":"2022","title":"OcWikiDisc: a Corpus of Wikipedia Talk Pages in Occitan","authors":["A Miletić, Y Scherrer - Proceedings of the Ninth Workshop on NLP for Similar …, 2022"],"snippet":"This paper presents OcWikiDisc, a new freely available corpus in Occitan, as well as language identification experiments on Occitan done as part of the corpus building process. Occitan is a regional language spoken mainly in the south of France and in …","url":["https://aclanthology.org/2022.vardial-1.8.pdf"]}
-{"year":"2022","title":"Odor Descriptor Understanding through Prompting","authors":["L Sisson - arXiv preprint arXiv:2205.03719, 2022"],"snippet":"Embeddings from contemporary natural language processing (NLP) models are commonly used as numerical representations for words or sentences. However, odor descriptor words, like \"leather\" or \"fruity\", vary significantly between their …","url":["https://arxiv.org/pdf/2205.03719"]}
-{"year":"2022","title":"Offensive language detection in Tamil YouTube comments by adapters and cross-domain knowledge transfer","authors":["M Subramanian, R Ponnusamy, S Benhur… - Computer Speech & …, 2022"],"snippet":"… XLM-RoBERTa is a self-supervised transformer model that has been pre-trained on 2.5TB of filtered CommonCrawl data from 100 languages. This model does not require lang tensors to understand which language is being used, and it should be …","url":["https://www.sciencedirect.com/science/article/pii/S0885230822000407"]}
-{"year":"2022","title":"Offensive Language Detection in Turkish Twitter Data with BERT Models","authors":["A Özberk - 2022"],"snippet":"As insulting statements become more frequent on online platforms, these negative statements create a reaction and disturb the peace of society. Identifying these expressions as early as possible is important to protect the victims. Offensive …","url":["http://www.openaccess.hacettepe.edu.tr:8080/xmlui/bitstream/handle/11655/26131/OFFENSIVE%20LANGUAGE%20DETECTION%20IN%20TURKISH%20TWITTER%20DATA%20WITH%20BERT%20MODELS.pdf?sequence=1"]}
-{"year":"2022","title":"On Explanations, Fairness, and Appropriate Reliance in Human-AI Decision-Making","authors":["J Schoeffer, M De-Arteaga, N Kuehl - arXiv preprint arXiv:2209.11812, 2022"],"snippet":"Explanations have been framed as an essential feature for better and fairer human-AI decision-making. In the context of fairness, this has not been appropriately studied, as prior works have mostly evaluated explanations based on their effects on …","url":["https://arxiv.org/pdf/2209.11812"]}
-{"year":"2022","title":"On Systematic Style Differences between Unsupervised and Supervised MT and an Application for High-Resource Machine Translation","authors":["K Marchisio, M Freitag, D Grangier"],"snippet":"Modern unsupervised machine translation (MT) systems reach reasonable translation quality under clean and controlled data conditions. As the performance gap between supervised and unsupervised MT narrows, it is interesting to ask …","url":["https://openreview.net/pdf?id=rqlQknbB-5"]}
-{"year":"2022","title":"On the Applicability of Zero-Shot Cross-Lingual Transfer Learning for Sentiment Classification in Distant Language Pairs","authors":["A Rusli, M Shishido"],"snippet":"This research explores the applicability of cross-lingual transfer learning from English to Japanese and Indonesian using the XLM-R pre-trained model. The results are compared with several previous works, either by models using a similar …","url":["https://www.anlp.jp/proceedings/annual_meeting/2022/pdf_dir/A6-1.pdf"]}
-{"year":"2022","title":"On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model","authors":["S Shin, SW Lee, H Ahn, S Kim, HS Kim, B Kim, K Cho… - arXiv preprint arXiv …, 2022"],"snippet":"Many recent studies on large-scale language models have reported successful in-context zeroand few-shot learning ability. However, the in-depth analysis of when in-context learning occurs is still lacking. For example, it is unknown how in-context learning …","url":["https://arxiv.org/pdf/2204.13509"]}
-{"year":"2022","title":"On the Effectiveness of Quasi Character-Level Models for Machine Translation","authors":["S Carrión-Ponz, F Casacuberta - Proceedings of the 15th biennial conference of the …, 2022"],"snippet":"Neural Machine Translation (NMT) models often use subword-level vocabularies to deal with rare or unknown words. Although some studies have shown the effectiveness of purely character-based models, these approaches have resulted in …","url":["https://aclanthology.org/2022.amta-research.10.pdf"]}
-{"year":"2022","title":"On the Geometry of Concreteness","authors":["C Wartena - Proceedings of the 7th Workshop on Representation …, 2022"],"snippet":"… For English we use the 300 dimensional fastText embeddings without subword information trained on the Common Crawl with 600 billion tokens. For German we also use 300 dimensional fastText embeddings trained on the Common Crawl and …","url":["https://aclanthology.org/2022.repl4nlp-1.21.pdf"]}
-{"year":"2022","title":"On the Role of Bidirectionality in Language Model Pre-Training","authors":["M Artetxe, J Du, N Goyal, L Zettlemoyer, V Stoyanov - arXiv preprint arXiv:2205.11726, 2022"],"snippet":"Prior work on language model pre-training has explored different architectures and learning objectives, but differences in data, hyperparameters and evaluation make a principled comparison difficult. In this work, we focus on bidirectionality as a key …","url":["https://arxiv.org/pdf/2205.11726"]}
-{"year":"2022","title":"On the Surrogate Gap between Contrastive and Supervised Losses","authors":["H Bao, Y Nagano, K Nozawa - International Conference on Machine Learning, 2022"],"snippet":"Contrastive representation learning encourages data representation to make semantically similar pairs closer than randomly drawn negative samples, which has been successful in various domains such as vision, language, and graphs. Recent …","url":["https://proceedings.mlr.press/v162/bao22e/bao22e.pdf"]}
-{"year":"2022","title":"One Document, Many Revisions: A Dataset for Classification and Description of Edit Intents","authors":["D Rajagopal, X Zhang, M Gamon, S Jauhar, D Yang…"],"snippet":"… It is important to note that BART was pretrained on written text over the C4 commoncrawl corpus6. And adapting it to wikipedia comment generation task did not directly lead to performance gains. Our experiments show that pretrained BART …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.591.pdf"]}
-{"year":"2022","title":"Online patient feedback as a safety valve: An automated language analysis of unnoticed and unresolved safety incidents","authors":["A Gillespie, TW Reader - Risk Analysis, 2022"],"snippet":"… Specifically, we used a publicly available language model created from the Common Crawl dataset of webpages, comprising 684,831 unique vectors represented in 300 dimensions (Explosion, 2020). While word embeddings trained on medical texts …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/risa.14002"]}
-{"year":"2022","title":"Online Social Networks and Media","authors":["JSL Figuerêdo, ALLM Maia, RT Calumby"],"snippet":"Depression is a challenge to public health, frequently related to disability and one of the reasons that lead to suicide. Many of the ones who suffer depression use social media to obtain information or even to talk about their problem. Some studies have …","url":["https://e-tarjome.com/storage/panel/fileuploads/2022-08-14/1660480282_e17068.pdf"]}
-{"year":"2022","title":"Open-domain conversational search assistants: the Transformer is all you need","authors":["R Ferreira, M Leite, D Semedo, J Magalhaes - Information Retrieval Journal, 2022"],"snippet":"On the quest of providing a more natural interaction between users and search systems, open-domain conversational search assistants have emerged, by assisting users in answering questions about open topics in a conversational manner. In this …","url":["https://link.springer.com/article/10.1007/s10791-022-09403-0"]}
-{"year":"2022","title":"OPT: Open Pre-trained Transformer Language Models","authors":["S Zhang, S Roller, N Goyal, M Artetxe, M Chen, S Chen… - arXiv preprint arXiv …, 2022"],"snippet":"… All corpora were previously collected or filtered to contain predominantly English text, but a small amount of non-English data is still present within the corpus via CommonCrawl. We removed duplicated documents across all datasets by filtering …","url":["https://arxiv.org/pdf/2205.01068"]}
-{"year":"2022","title":"Optimize_Prime@ DravidianLangTech-ACL2022: Abusive Comment Detection in Tamil","authors":["S Patankar, O Gokhale, O Litake, A Mandke, D Kadam - arXiv preprint arXiv …, 2022"],"snippet":"This paper tries to address the problem of abusive comment detection in low-resource indic languages. Abusive comments are statements that are offensive to a person or a group of people. These comments are targeted toward individuals belonging to …","url":["https://arxiv.org/pdf/2204.09675"]}
-{"year":"2022","title":"Optimize_Prime@ DravidianLangTech-ACL2022: Emotion Analysis in Tamil","authors":["O Gokhale, S Patankar, O Litake, A Mandke, D Kadam - arXiv preprint arXiv …, 2022"],"snippet":"This paper aims to perform an emotion analysis of social media comments in Tamil. Emotion analysis is the process of identifying the emotional context of the text. In this paper, we present the findings obtained by Team Optimize_Prime in the ACL 2022 …","url":["https://arxiv.org/pdf/2204.09087"]}
-{"year":"2022","title":"ORCA: A Challenging Benchmark for Arabic Language Understanding","authors":["AR Elmadany, EMB Nagoudi, M Abdul-Mageed - arXiv preprint arXiv:2212.10758, 2022"],"snippet":"… 2020b) is a transformerbased multilingual masked language model pretrained on more than 2TB of filtered CommonCrawl data in 100 languages, including Arabic (2.9B tokens). XLM-R uses a Transformer model trained a multilingual version of masked …","url":["https://arxiv.org/pdf/2212.10758"]}
-{"year":"2022","title":"Ordvektorer i lexikografiskt arbete","authors":["M Forsberg, E Sköldberg - LIVE and LEARN"],"snippet":"… Ordvektorerna är baserade på datamängden Common Crawl, som är ett stort insamlat material med webbsidor, och Wikipedia. Det finns en rik flora av vetenskapliga arbeten som kretsar runt hur frukten av lexikografiskt arbete kan …","url":["https://gupea.ub.gu.se/bitstream/handle/2077/74254/GU-ISS-2022-03%20Lars%20Borin%20Festskrift%20Digital%20publicering%20221121.pdf?sequence=1&isAllowed=y#page=51"]}
-{"year":"2022","title":"Out-of-Distribution Detection and Selective Generation for Conditional Language Models","authors":["J Ren, J Luo, Y Zhao, K Krishna, M Saleh… - arXiv preprint arXiv …, 2022"],"snippet":"Machine learning algorithms typically assume independent and identically distributed samples in training and at test time. Much work has shown that high-performing ML classifiers can degrade significantly and provide overly-confident, wrong …","url":["https://arxiv.org/pdf/2209.15558"]}
-{"year":"2022","title":"Overview of HIPE-2022: Named Entity Recognition and Linking in Multilingual Historical Documents","authors":["A Doucet, S Clematide - … IR Meets Multilinguality, Multimodality, and Interaction …, 2022","M Ehrmann, M Romanello, S Najem-Meyer, A Doucet… - International Conference of …, 2022","S Clematide"],"snippet":"This paper presents an overview of the second edition of HIPE (Identifying Historical People, Places and other Entities), a shared task on named entity recognition and linking in multilingual historical documents. Following the success of the first CLEF-HIPE-2020 …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=LzaFEAAAQBAJ&oi=fnd&pg=PA423&dq=commoncrawl&ots=LmT-NMkkn2&sig=Q_jxi2Mi1rvfcsodMOiSk1LYkXY","https://hipe-eval.github.io/HIPE-2022/assets/pdf/HIPE_2022_LNCS_CondensedLabOverview_accepted_version.pdf","https://link.springer.com/chapter/10.1007/978-3-031-13643-6_26"]}
-{"year":"2022","title":"Overview of NTCIR-16","authors":["T Yamamoto, Z Dou","Z Dou, T Yamamoto"],"snippet":"… Chuweb21 is a subset of the Common Crawl dataset and it contains 3,402,457 domains and 858,616,203 web pages. Secondly, two versions of relevance assessment are introduced: the Gold version given by the topic creators, and the …","url":["https://research.nii.ac.jp/ntcir/workshop/OnlineProceedings16/pdf/ntcir/01-NTCIR16-OV-YamamotoT-slides.pdf","https://research.nii.ac.jp/ntcir/workshop/OnlineProceedings16/pdf/ntcir/01-NTCIR16-OV-YamamotoT.pdf"]}
-{"year":"2022","title":"Overview of the 2022 BUCC Shared Task: Bilingual Term Alignment in Comparable Specialized Corpora","authors":["O Adjali, E Morin, S Sharoff, R Rapp, P Zweigenbaum - LREC 2022 Workshop …, 2022"],"snippet":"The BUCC 2022 shared task addressed bilingual terminology alignment in comparable corpora. Many research groups are working on this problem using a wide variety of approaches. However, as there is no standard way to measure the …","url":["https://comparable.limsi.fr/bucc2022/BUCC2022-proceedings-20220617.pdf#page=77"]}
-{"year":"2022","title":"Overview of Touché 2022: Argument Retrieval","authors":["A Bondarenko, M Fröbe, J Kiesel, S Syed, T Gurcke… - 2022","T Gurcke, M Beloucif, A Panchenko, C Biemann… - Experimental IR Meets …, 2022"],"snippet":"This paper is a report on the third year of the Touché lab on argument retrieval hosted at CLEF 2022. With the goal of supporting and promoting the research and development of new technologies for argument mining and argument analysis, we …","url":["http://ceur-ws.org/Vol-3180/paper-247.pdf","https://books.google.de/books?hl=en&lr=lang_en&id=LzaFEAAAQBAJ&oi=fnd&pg=PA311&dq=commoncrawl&ots=LmT-NMkkn2&sig=yArB4HgQifPyU4Ny0t18ZGgSD1E"]}
-{"year":"2022","title":"PANGUBOT: Efficient Generative Dialogue Pre-training from Pre-trained Language Model","authors":["F Mi, Y Li, Y Zeng, J Zhou, Y Wang, C Xu, L Shang… - arXiv preprint arXiv …, 2022"],"snippet":"In this paper, we introduce PANGUBOT, a Chinese pre-trained open-domain dialogue generation model based on a large pre-trained language model (PLM) PANGU-alpha (Zeng et al.,2021). Different from other pre-trained dialogue models …","url":["https://arxiv.org/pdf/2203.17090"]}
-{"year":"2022","title":"Papago's Submission for the WMT21 Quality Estimation Shared Task","authors":["S Lim, H Kim, H Kim - Proceedings of the Sixth Conference on Machine …, 2021"],"snippet":"This paper describes Papago submission to the WMT 2021 Quality Estimation Task 1: Sentence-level Direct Assessment. Our multilingual Quality Estimation system explores the combination of Pretrained Language Models and Multi-task Learning …","url":["https://aclanthology.org/2021.wmt-1.98.pdf"]}
-{"year":"2022","title":"Paragraph-based Transformer Pre-training for Multi-Sentence Inference","authors":["L Di Liello, S Garg, L Soldaini, A Moschitti - arXiv preprint arXiv:2205.01228, 2022"],"snippet":"Inference tasks such as answer sentence selection (AS2) or fact verification are typically solved by fine-tuning transformer-based models as individual sentence-pair classifiers. Recent studies show that these tasks benefit from modeling …","url":["https://arxiv.org/pdf/2205.01228"]}
-{"year":"2022","title":"Parameter-efficient feature-based transfer for paraphrase identification","authors":["X Liu, R Rzepka, K Araki - Natural Language Engineering, 2022"],"snippet":"There are many types of approaches for Paraphrase Identification (PI), an NLP task of determining whether a sentence pair has equivalent semantics. Traditional approaches mainly consist of unsupervised learning and feature engineering, which …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/parameterefficient-featurebased-transfer-for-paraphrase-identification/D587AA786E0B7F21AD61651E29551FE4"]}
-{"year":"2022","title":"Parameter-efficient Zero-shot Transfer for Cross-Language Dense Retrieval with Adapters","authors":["E Yang, S Nair, D Lawrie, J Mayfield, DW Oard - arXiv preprint arXiv:2212.10448, 2022"],"snippet":"A popular approach to creating a zero-shot cross-language retrieval model is to substitute a monolingual pretrained language model in the retrieval model with a multilingual pretrained language model such as Multilingual BERT. This multilingual …","url":["https://arxiv.org/pdf/2212.10448"]}
-{"year":"2022","title":"Parliamentary representative behaviour in times of crisis: a comparative perspective with a focus on Greece and the Eurozone crisis","authors":["EI Kartalis - 2022"],"snippet":"Much scholarly discussion has been devoted to the impact of the 2009 Eurozone economic Crisis on the functioning of European democracies. Especially for those countries that bailout agreements had to be implemented in, the literature has …","url":["https://repositorio.ul.pt/bitstream/10451/55162/1/PhDThesis_Final_Kartalis.pdf"]}
-{"year":"2022","title":"Parquet Containers","authors":["M Coscia, A Weber - 2022"],"snippet":"Archives preserve content and support various types of analysis, study, and use. Archiving the Web and social media (eg, Twitter) content involves use of representations like Web ARChive (WARC) and JavaScript Object Notation (JSON) …","url":["https://vtechworks.lib.vt.edu/bitstream/handle/10919/109995/ParquetContainersReport.pdf?sequence=2&isAllowed=y"]}
-{"year":"2022","title":"Partitioning Trillion-Edge Graphs","authors":["GM Slota, K Devine, K Madduri, S Rajamanickam - Massive Graph Analytics"],"snippet":"Graph partitioning is a key preprocessing step for distributed-memory graph analytics and scientific computations on meshes. This chapter introduces XtraPuLP, a new distributed-memory graph partitioner designed to process trillion-edge graphs …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781003033707-12/partitioning-trillion-edge-graphs-george-slota-karen-devine-kamesh-madduri-sivasankaran-rajamanickam"]}
-{"year":"2022","title":"Pełen tekst","authors":["T Harting, S Mesbah, C Lofi"],"snippet":"… For the language-individual model, we use FastText word em-beddings [11] which are trained on Common Crawl and Wikipedia dataset. For the language-consistent model, we use pre-trained mul-tilingual embeddings which are released by FastText …","url":["https://9lib.org/document/wyejx8rz-lorem.html"]}
-{"year":"2022","title":"Perplexed by Quality: A Perplexity-based Method for Adult and Harmful Content Detection in Multilingual Heterogeneous Web Data","authors":["T Jansen, Y Tong, V Zevallos, PO Suarez - arXiv preprint arXiv:2212.10440, 2022"],"snippet":"As demand for large corpora increases with the size of current state-of-the-art language models, using web data as the main part of the pre-training corpus for these models has become a ubiquitous practice. This, in turn, has introduced an …","url":["https://arxiv.org/pdf/2212.10440"]}
-{"year":"2022","title":"Personalized filled-pause generation with group-wise prediction models","authors":["Y Matsunaga, T Saeki, S Takamichi, H Saruwatari - arXiv preprint arXiv:2203.09961, 2022"],"snippet":"In this paper, we propose a method to generate personalized filled pauses (FPs) with group-wise prediction models. Compared with fluent text generation, disfluent text generation has not been widely explored. To generate more human-like texts …","url":["https://arxiv.org/pdf/2203.09961"]}
-{"year":"2022","title":"Perspectives on the Cognitive Unconscious","authors":["AS Reber, R Allen"],"snippet":"My interest in nonconscious processes goes back to my youth when I imagined that Sigmund Freud had discovered all that there was to be known about the human mind. But interest in the nonconscious and the role it plays in mind and behavior turned …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=wD90EAAAQBAJ&oi=fnd&pg=PA366&dq=commoncrawl&ots=cFuiqkafcD&sig=CqQx5Bv7dxtxoYrlkVD_Qp8nYdc"]}
-{"year":"2022","title":"PETCI: A Parallel English Translation Dataset of Chinese Idioms","authors":["K Tang - arXiv preprint arXiv:2202.09509, 2022"],"snippet":"… RoBERTa, for example, has part of its pre-training data from Reddit and CommonCrawl (Liu … Similarly, we expect the Wikipedia dataset to have a lower PoI than CommonCrawl. The … use the cased 300-dimensional GloVe vectors pre-trained on …","url":["https://arxiv.org/pdf/2202.09509"]}
-{"year":"2022","title":"Phishing Detection Using URL-based XAI Techniques","authors":["PRG Hernandes, CP Floret, KFC De Almeida… - 2021 IEEE Symposium …, 2021"],"snippet":"… As a result, 5,000 phishing web pages were selected based on URLs from PhishTank 1, OpenPhish 2, and another 5,000 legitimate pages based on URLs of Alexa 3 and the archive of CommonCrawl 4. Subsequently, this dataset was …","url":["https://ieeexplore.ieee.org/abstract/document/9659981/"]}
-{"year":"2022","title":"Phishing URL Detection: A novel hybrid Approach using Long Short-Term Memory and Gated Recurrent Units","authors":["BAS Dilhara - International Journal of Computer Applications"],"snippet":"Phishing is one of the oldest types of cyber-attack, which mostly comes in the form of camouflaged URLs to delude the users to disclose their personal information for malevolent purposes of the attacker. It is one of the easiest ways of inducing people …","url":["https://www.researchgate.net/profile/Shashie-Dilhara/publication/357269439_Phishing_URL_Detection_A_novel_hybrid_Approach_using_Long_Short-Term_Memory_and_Gated_Recurrent_Units/links/61c41df0abcb1b520ada4c9c/Phishing-URL-Detection-A-novel-hybrid-Approach-using-Long-Short-Term-Memory-and-Gated-Recurrent-Units.pdf"]}
-{"year":"2022","title":"Phishing URL Identification Using Machine Learning, Ensemble Learning and Deep Learning Techniques","authors":["K Laxmi Prasanna, KV Pradeepthi, A Saxena - Smart Intelligent Computing and …, 2022"],"snippet":"Demand for online applications and services is increasing day by day, whereas the security lapses in them is also becoming prominent. One of the major online threats, phishing, is consistently used to dupe users for retrieving sensitive information like …","url":["https://link.springer.com/chapter/10.1007/978-981-16-9705-0_56"]}
-{"year":"2022","title":"Phishing website detection: How effective are deep learning‐based models and hyperparameter optimization?","authors":["M Almousa, T Zhang, A Sarrafzadeh, M Anwar - Security and Privacy, 2022"],"snippet":"… The phishing webpages have been collected from PhishTank36 and OpenPhish,37 while the sources of legitimate webpages were Alexa38 and Common Crawl.The second dataset was obtained from Reference 40 that we refer to as Kumar-dataset …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1002/spy2.256"]}
-{"year":"2022","title":"Phonetic, Semantic, and Articulatory Features in Assamese-Bengali Cognate Detection","authors":["A Nath, R Ghosh, N Krishnaswamy"],"snippet":"In this paper, we propose a method to detect if words in two similar languages, Assamese and Bengali, are cognates. We mix phonetic, semantic, and articulatory features and use the cognate detection task to analyze the relative informational …","url":["https://www.nikhilkrishnaswamy.com/assets/docs/pdfs/VarDial-2022.pdf"]}
-{"year":"2022","title":"Phrase-Based Affordance Detection via Cyclic Bilateral Interaction","authors":["L Lu, W Zhai, H Luo, Y Kang, Y Cao - arXiv preprint arXiv:2202.12076, 2022"],"snippet":"… Meanwhile, for linguistic feature extraction, we first adopt the GloVe word embeddings [42] pre-trained on Common Crawl (840B tokens) to initialize the parameters of embedding layers then a LSTM is employed as the language feature …","url":["https://arxiv.org/pdf/2202.12076"]}
-{"year":"2022","title":"Plansformer: Generating Symbolic Plans using Transformers","authors":["V Pallagani, B Muppasani, K Murugesan, F Rossi… - arXiv preprint arXiv …, 2022"],"snippet":"… Large Language Models (LLM) such as BERT [16], RoBERTa [17], and GPT3 [3] are pre-trained on extensive unstructured knowledge from public data such as Wikipedia, Bookcorpus, and Commoncrawl, have shown impressive results in …","url":["https://arxiv.org/pdf/2212.08681"]}
-{"year":"2022","title":"PLAtE: A Large-scale Dataset for List Page Web Extraction","authors":["A San, J Bakus, C Lockard, D Ciemiewicz, Y Ji, S Atluri… - arXiv preprint arXiv …, 2022"],"snippet":"… We construct PLAtE by collecting list pages from Common Crawl, then annotating them on Mechanical Turk. Quantitative and qualitative analyses are performed to demonstrate PLAtE has high-quality annotations. We establish strong baseline …","url":["https://arxiv.org/pdf/2205.12386"]}
-{"year":"2022","title":"Political Event Coding as Text to Text Sequence Generation","authors":["Y Dai, BJ Radford, A Halterman"],"snippet":"We report on the current status of an effort to produce political event data from unstructured text via a Transformer language model. Compelled by the current lack of publicly available and up-to-date event coding software, we seek to train a model …","url":["https://yaoyaodai.github.io/files/CASE_2022.pdf"]}
-{"year":"2022","title":"Politics and Virality in the Time of Twitter: A Large-Scale Cross-Party Sentiment Analysis in Greece, Spain and United Kingdom","authors":["D Antypas, A Preece, JC Collados - arXiv preprint arXiv:2202.00396, 2022"],"snippet":"Social media has become extremely influential when it comes to policy making in modern societies especially in the western world (eg, 48% of Europeans use social media every day or almost every day). Platforms such as Twitter allow users to follow …","url":["https://arxiv.org/pdf/2202.00396"]}
-{"year":"2022","title":"Politics as Usual? Antecedents of Radical-Right Frames in US Electoral Discourse","authors":["B Bonikowski, Y Luo, O Stuhler - 2021"],"snippet":"… This extension of the original BERT model relies on the same general architecture but expands the training data to 63 million English news articles from CommonCrawl, 38 gigabytes of textual data from the OpenWebText corpus, and a 31-gigabyte …","url":["https://osf.io/preprints/socarxiv/uhvbp/download"]}
-{"year":"2022","title":"Politics as Usual? Measuring Populism, Nationalism, and Authoritarianism in US Presidential Campaigns (1952–2020) with Deep Neural Language Models","authors":["B Bonikowski, Y Luo, O Stuhler - Sociological Methods & Research, 2022"],"snippet":"… but expands the training data to 63 million English news articles from CommonCrawl, 38 gigabytes of textual data from the OpenWebText … corpus, and a 31-gigabyte subset of CommonCrawl data known as Stories. In addition, the …","url":["https://files.osf.io/v1/resources/uhvbp/providers/osfstorage/61eeccc0133169053a9928ce?action=download&direct&version=3"]}
-{"year":"2022","title":"POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detection","authors":["Y Liu, XF Zhang, D Wegsman, N Beauchamp, L Wang - arXiv preprint arXiv …, 2022"],"snippet":"Ideology is at the core of political science research. Yet, there still does not exist general-purpose tools to characterize and predict ideology across different genres of text. To this end, we study Pretrained Language Models using novel ideology-driven …","url":["https://arxiv.org/pdf/2205.00619"]}
-{"year":"2022","title":"Post-hoc analysis of Arabic transformer models","authors":["A Abdelali, N Durrani, F Dalvi, H Sajjad - arXiv preprint arXiv:2210.09990, 2022"],"snippet":"Arabic is a Semitic language which is widely spoken with many dialects. Given the success of pre-trained language models, many transformer models trained on Arabic and its dialects have surfaced. While there have been an extrinsic evaluation …","url":["https://arxiv.org/pdf/2210.09990"]}
-{"year":"2022","title":"Poster: PhishLex: A Proactive Zero-Day Phishing Defence Mechanism using URL Lexical Features","authors":["M Fernando, AN Mahmood, MJM Chowdhury"],"snippet":"Google reports that 68% of all Phishing URLs that are blocked by them are zero-day phishing attacks that remain undetected using traditional blacklist-based approaches. Machine learning-based (ML) techniques can improve the accuracy of detecting zero-day …","url":["https://www.researchgate.net/profile/Matheesha-Fernando/publication/363698036_PhishLex_A_Proactive_Zero-Day_Phishing_Defence_Mechanism_using_URL_Lexical_Features/links/632a985f071ea12e364c4afa/PhishLex-A-Proactive-Zero-Day-Phishing-Defence-Mechanism-using-URL-Lexical-Features.pdf"]}
-{"year":"2022","title":"Posts on central websites need less originality to be noticed","authors":["M Coscia, C Vandeweerdt - Scientific Reports, 2022"],"snippet":"… We only kept domains that are also found in the Common Crawl data. This reduced the data to 3.8M posts. … We downloaded the domain graph from the Common Crawl for the November 2019–January 2020 period. Since from the Reddit …","url":["https://www.nature.com/articles/s41598-022-19433-9"]}
-{"year":"2022","title":"Pre-Trained Language Models and Their Applications","authors":["H Wang, J Li, H Wu, E Hovy, Y Sun - Engineering, 2022"],"snippet":"Pre-trained language models have achieved striking success in natural language processing (NLP), leading to a paradigm shift from supervised learning to pre-training followed by fine-tuning. The NLP community has witnessed a surge of research …","url":["https://www.sciencedirect.com/science/article/pii/S2095809922006324"]}
-{"year":"2022","title":"Pre-Trained Multilingual Sequence-to-Sequence Models: A Hope for Low-Resource Language Translation?","authors":["ESA Lee, S Thillainathan, S Nayak, S Ranathunga… - arXiv preprint arXiv …, 2022"],"snippet":"… mined one like from Common Crawl? Comparing mBART trained on Common Crawl versus domain-specific data, we see that for several … both in and not in mBART, 10k high-quality in-domain sentences leads to better performance than …","url":["https://arxiv.org/pdf/2203.08850"]}
-{"year":"2022","title":"Pre-trained transformers: an empirical comparison","authors":["S Casola, I Lauriola, A Lavelli - Machine Learning with Applications, 2022"],"snippet":"Pre-trained transformers have rapidly become very popular in the Natural Language Processing (NLP) community, surpassing the previous state of the art in a wide variety of tasks. While their effectiveness is indisputable, these methods are …","url":["https://www.sciencedirect.com/science/article/pii/S2666827022000445"]}
-{"year":"2022","title":"Pre-training large NLP-models by utilizing low-resource NLP-pipelines","authors":["Z van Cauter"],"snippet":"The dominating approach to Natural Language Processing problems is by pre-training models on large amounts of unsupervised text and fine-tuning them for use on downstream tasks. Over the years, this amount of unsupervised text has grown …","url":["https://pure.tue.nl/ws/portalfiles/portal/199766232/Cauter_Z.pdf"]}
-{"year":"2022","title":"Pre-training Transformer Models with Sentence-Level Objectives for Answer Sentence Selection","authors":["L Di Liello, S Garg, L Soldaini, A Moschitti - arXiv preprint arXiv:2205.10455, 2022"],"snippet":"An important task for designing QA systems is answer sentence selection (AS2): selecting the sentence containing (or constituting) the answer to a question from a set of retrieved relevant documents. In this paper, we propose three novel sentence-level …","url":["https://arxiv.org/pdf/2205.10455"]}
-{"year":"2022","title":"Predicting Embedding Reliability in Low-Resource Settings Using Corpus Similarity Measures","authors":["J Dunn, H Li, D Sastre - arXiv preprint arXiv:2206.04330, 2022"],"snippet":"This paper simulates a low-resource setting across 17 languages in order to evaluate embedding similarity, stability, and reliability under different conditions. The goal is to use corpus similarity measures before training to predict properties of …","url":["https://arxiv.org/pdf/2206.04330"]}
-{"year":"2022","title":"Predicting Fine-Tuning Performance with Probing","authors":["Z Zhu, S Shahtalebi, F Rudzicz - Challenges {\\&, 2022"],"snippet":"… For example, after pre-training a deep neural model for 1000 steps on Wikipedia, is it more beneficial to continue training on Wikipedia or proceed to Common Crawl? The probing results could help answer questions of this kind, which we leave to …","url":["https://openreview.net/pdf?id=BLXlV3MBLZ5"]}
-{"year":"2022","title":"Preparing a Corpus and a Question Answering System for Slovene","authors":["M Zupanic, M Zirkelbach, U Šmajdek, M Jazbinšek"],"snippet":"Lack of proper training data is one of the key issues when developing natural language processing models based on less-resourced languages, such as Slovene. In this paper we discuss machine translation as a solution to this issue, with the …","url":["https://nl.ijs.si/jtdh22/pdf/JTDH2022_Zupancic-et-al_Preparing-a-Corpus-and-a-Question-Answering-System-for-Slovene.pdf"]}
-{"year":"2022","title":"Pretrained Language Models","authors":["J May"],"snippet":"… It was trained on 570gb of text (500b tokens) from common crawl, their previous data set, and some other ‘high quality’ data sets. When prompted with only a few examples (and sometimes with none at all) it outperformed SOTA on a wide variety …","url":["https://jonmay.github.io/USC-CS662/assets/files/pretrained.pdf"]}
-{"year":"2022","title":"Pretraining without Wordpieces: Learning Over a Vocabulary of Millions of Words","authors":["Z Feng, D Tang, C Zhou, J Liao, S Wu, X Feng, B Qin… - arXiv preprint arXiv …, 2022"],"snippet":"… Glove embedding is pretrained on Common Crawl dataset with 42B tokens 2 with 300 dimension. Given a sequence of words, we first get the corresponding 300-dimensional representation for each word through Glove Embedding. Then, we add a linear layer …","url":["https://arxiv.org/pdf/2202.12142"]}
-{"year":"2022","title":"Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy","authors":["D Ippolito, F Tramèr, M Nasr, C Zhang, M Jagielski… - arXiv preprint arXiv …, 2022"],"snippet":"Studying data memorization in neural language models helps us understand the risks (eg, to privacy or copyright) associated with models regurgitating training data, and aids in the evaluation of potential countermeasures. Many prior works -- and …","url":["https://arxiv.org/pdf/2210.17546"]}
-{"year":"2022","title":"Prior knowledge guided weakly supervised object detection and semantic segmentation","authors":["F Baltacı - 2022"],"snippet":"State-of-the-art recognition models in computer vision are trained using annotated training data. Collecting manual annotation for images is a time-consuming and tedious task. Annotation time and difficulty also change across computer vision tasks …","url":["https://open.metu.edu.tr/bitstream/handle/11511/96300/METU_Thesis_fatihbaltaci.pdf"]}
-{"year":"2022","title":"Privacy conflict analysis in web interaction models","authors":["P Inglis - 2022"],"snippet":"User privacy has become an important topic with strong implications for the manner by which software systems are designed and used. However, it is not a straightforward consideration on how the instrumentation of data processing …","url":["https://theses.gla.ac.uk/82875/1/2022inglisphd.pdf"]}
-{"year":"2022","title":"Privacy leakage analysis of text representations for Natural Language Processing","authors":["L CORÒ"],"snippet":"Natural language processing (NLP) offers powerful tools, such as text suggestions to help users be more efficient or classifiers that categorize documents by their content. These tools are usually powered by machine learning (ML) models that are trained …","url":["https://thesis.unipd.it/bitstream/20.500.12608/35514/1/Cor%C3%B2_Luca.pdf"]}
-{"year":"2022","title":"Privacy Policies of IoT Devices: Collection and Analysis","authors":["M Kuznetsov, E Novikova, I Kotenko, E Doynikova - Sensors, 2022"],"snippet":"Currently, personal data collection and processing are widely used while providing digital services within mobile sensing networks for their operation, personalization, and improvement. Personal data are any data that identifiably describe a person …","url":["https://www.mdpi.com/1424-8220/22/5/1838/pdf"]}
-{"year":"2022","title":"Proactive Interference-aware Resource Management in Deep Learning Training Cluster","authors":["GF Yeung - 2022"],"snippet":"Deep Learning (DL) applications are growing at an unprecedented rate across many domains, ranging from weather prediction, map navigation to medical imaging. However, training these deep learning models in large-scale compute clusters face …","url":["https://eprints.lancs.ac.uk/id/eprint/172142/1/2022yeungphd.pdf"]}
-{"year":"2022","title":"Probing for Dutch Relative Pronoun Choice","authors":["G Bouma - Computational Linguistics in the Netherlands Journal, 2021"],"snippet":"We propose a linguistically motivated version of the relative pronoun probing task for Dutch (where a model has to predict whether a masked token is either die or dat), collect realistic data for it using a parsed corpus, and probe the performance of four …","url":["https://www.clinjournal.org/index.php/clinj/article/download/121/105"]}
-{"year":"2022","title":"Probing language identity encoded in pre-trained multilingual models: a typological view","authors":["J Zheng, Y Liu - PeerJ Computer Science, 2022"],"snippet":"… It is trained on CommonCrawl corpora with 12 layers and 768 hidden states. The vocabulary size is 250k, The tool for tokenization is free, namely, the Sentence Piece (Kudo & Richardson, 2018). The only task is the dynamic mask language model. …","url":["https://peerj.com/articles/cs-899/"]}
-{"year":"2022","title":"Probing Pre-Trained Language Models for Cross-Cultural Differences in Values","authors":["A Arora, LA Kaffee, I Augenstein - arXiv preprint arXiv:2203.13722, 2022"],"snippet":"… 2019) and is trained with an MLM objective on 2.5 TB of filtered CommonCrawl corpus data in 100 languages. It shows strong multilingual performance across a range of benchmarks and is commonly used for extracting multilingual sentence encodings. …","url":["https://arxiv.org/pdf/2203.13722"]}
-{"year":"2022","title":"Proceedings of the 13th Conference on\" Data analysis methods for software systems","authors":["J Bernatavičienė - Vilnius University Proceedings, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://www.zurnalai.vu.lt/proceedings/article/download/29893/28890"]}
-{"year":"2022","title":"Project European Language Equality (ELE) Grant agreement no. LC-01641480–101018166 ELE Coordinator Prof. Dr. Andy Way (DCU) Co-coordinator Prof. Dr …","authors":["G Backfried, M Skowron, E Navas, A Bērziņš… - 2022"],"snippet":"D2. 14 provides an overview and describes the state of the art and developments within the field of Speech Technologies (ST). This field is interpreted to comprise technologies aimed at the processing and production of the human voice, both, from …","url":["https://european-language-equality.eu/wp-content/uploads/2022/03/ELE___Deliverable_D2_14__Speech__Technologies.pdf"]}
-{"year":"2022","title":"Prompt-GAN–Customisable hate speech and extremist datasets via radicalised neural language models","authors":["J Govers - 2022"],"snippet":"Online hate speech and violent extremism knows no borders, no political boundaries, no remorse. Researchers face an uphill battle to collect hate speech data in volumes and topical diversity suitable for training state-of-the art content-moderation systems …","url":["https://researchcommons.waikato.ac.nz/bitstream/handle/10289/15259/thesis.pdf?sequence=4&isAllowed=y"]}
-{"year":"2022","title":"Prompting ELECTRA: Few-Shot Learning with Discriminative Pre-Trained Models","authors":["M Xia, M Artetxe, J Du, D Chen, V Stoyanov - arXiv preprint arXiv:2205.15223, 2022"],"snippet":"Pre-trained masked language models successfully perform few-shot learning by formulating downstream tasks as text infilling. However, as a strong alternative in full-shot settings, discriminative pre-trained models like ELECTRA do not fit into the paradigm …","url":["https://arxiv.org/pdf/2205.15223"]}
-{"year":"2022","title":"Promt systems for wmt21 terminology translation task","authors":["A Molchanov, V Kovalenko, F Bykov - Proceedings of the Sixth Conference on …, 2021"],"snippet":"… We first build an English-Russian system using all parallel data (except commoncrawl which we believe to be of bad quality; basic filtering is applied) including the Edinborough corpus of Russian news translated into English and …","url":["https://aclanthology.org/2021.wmt-1.83.pdf"]}
-{"year":"2022","title":"Prospects for Dutch Emotion Detection: Insights from the new EmotioNL Dataset","authors":["L De Bruyne, O De Clercq, V Hoste - Computational Linguistics in the Netherlands …, 2021"],"snippet":"Although emotion detection has become a crucial research direction in NLP, the main focus is on English resources and data. The main obstacles for more specialized emotion detection are the lack of annotated data in smaller languages …","url":["https://clinjournal.org/index.php/clinj/article/download/138/144"]}
-{"year":"2022","title":"Protecting Systems From Exploits Using Language-Theoretic Security","authors":["P Anantharaman - 2022"],"snippet":"Any computer program processing input from the user or network must validate the input. Input-handling vulnerabilities occur in programs when the software component responsible for filtering malicious input---the parser---does not perform …","url":["https://digitalcommons.dartmouth.edu/cgi/viewcontent.cgi?article=1081&context=dissertations"]}
-{"year":"2022","title":"PsychBERT: A Mental Health Language Model for Social Media Mental Health Behavioral Analysis","authors":["V Vajre, M Naylor, U Kamath, A Shehu - 2021 IEEE International Conference on …, 2021"],"snippet":"Mental health behaviors are now recognized as primary factors contributing to suicide. This paper puts forth a novel mental health language model to address mental health and makes several contributions. First, it proposes a taxonomy and …","url":["https://ieeexplore.ieee.org/abstract/document/9669469/"]}
-{"year":"2022","title":"Punctuation Restoration in Spanish Customer Support Transcripts using Transfer Learning","authors":["X Zhu, S Gardiner, D Rossouw, T Roldán… - arXiv preprint arXiv …, 2022"],"snippet":"Automatic Speech Recognition (ASR) systems typically produce unpunctuated transcripts that have poor readability. In addition, building a punctuation restoration system is challenging for low-resource languages, especially for domain-specific …","url":["https://arxiv.org/pdf/2205.13961"]}
-{"year":"2022","title":"Qasar: Self-Supervised Learning Framework for Extractive Question Answering","authors":["H Assem, R Sarkar, S Dutta - 2021 IEEE International Conference on Big Data (Big …, 2021"],"snippet":"… Pretrained transformer based language models like BERT [8] are trained initially on large unlabelled data from common crawl corpus and Wikipedia dumps. With the creation of large labelled open-domain QA datasets like WikiQA [9], SQuAD [10] …","url":["https://ieeexplore.ieee.org/abstract/document/9671570/"]}
-{"year":"2022","title":"QianXun: A Novel Enterprise File Search Framework","authors":["C Si, P Qi, H Xue, Y Sun - 2022 IEEE 25th International Conference on Computer …, 2022"],"snippet":"… Subsequently, Google proposed mT5 [7], a multilingual variant of T5 that is pre-trained on a new Common Crawl-based dataset covering 101 languages, which offers the possibility of processing Chinese texts. Then, based on the mT5, Su Jianlin trained …","url":["https://ieeexplore.ieee.org/abstract/document/9776101/"]}
-{"year":"2022","title":"QMLEx: Data Driven Digital Transformation in Marketing Analytics","authors":["A Geronazzo, M Ziegler - 2021 IEEE International Conference on Big Data (Big …, 2021"],"snippet":"This paper presents a data driven approach to replace expert driven business processes. The QMLEx methodology combines NLP algorithms to improve data quality, ML techniques to perform the task and exploits external data sources to …","url":["https://ieeexplore.ieee.org/abstract/document/9671890/"]}
-{"year":"2022","title":"Qualitative Analysis of Text Summarization Techniques and Its Applications in Health Domain","authors":["D Yadav, N Lalit, R Kaushik, Y Singh, AK Yadav… - Computational Intelligence …, 2022"],"snippet":"For the better utilization of the enormous amount of data available to us on the Internet and in different archives, summarization is a valuable method. Manual summarization by experts is an almost impossible and time-consuming activity …","url":["https://www.hindawi.com/journals/cin/2022/3411881/"]}
-{"year":"2022","title":"Qualitative Measures for Ad hoc Table Retrieval","authors":["M Khodabakhsh, E Bagheri - Information Sciences, 2022"],"snippet":"The focus of our work is the ad hoc table retrieval task, which aims to rank a list of structured tabular objects in response to a user query. Given the importance of this task, various methods have already been proposed in the literature that focus on …","url":["https://www.sciencedirect.com/science/article/pii/S0020025522005126"]}
-{"year":"2022","title":"Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP","authors":["T Nguyen, G Ilharco, M Wortsman, S Oh, L Schmidt - arXiv preprint arXiv:2208.05516, 2022"],"snippet":"Web-crawled datasets have enabled remarkable generalization capabilities in recent image-text models such as CLIP (Contrastive Language-Image pre-training) or Flamingo, but little is known about the dataset creation processes. In this work, we …","url":["https://arxiv.org/pdf/2208.05516"]}
-{"year":"2022","title":"Quantifying Memorization Across Neural Language Models","authors":["N Carlini, D Ippolito, M Jagielski, K Lee, F Tramer… - arXiv preprint arXiv …, 2022"],"snippet":"… These models were trained on C4, a cleaned and filtered version of the English web pages from the Common Crawl, which totals 806 GB in size. At 11 billion parameters, the largest T5 model is the largest publicly available masked language …","url":["https://arxiv.org/pdf/2202.07646"]}
-{"year":"2022","title":"Quantifying the Polarity of Noun Phrases","authors":["BI Ersoy"],"snippet":"While sentiment analysis is a popular NLP subfield, not every area within gets the same amount of attention. For example, classifying the sentiment of texts seems to be quite in demand, however, rarely does it also include determining how positive or …","url":["https://www.cl.uzh.ch/dam/jcr:d3356468-e322-4a8a-befb-23f95590e497/BachelorThesis_BernaErsoy_2022.pdf"]}
-{"year":"2022","title":"Query Refinement Prompts for Closed-Book Long-Form Question Answering","authors":["RK Amplayo, K Webster, M Collins, D Das, S Narayan - arXiv preprint arXiv …, 2022"],"snippet":"Large language models (LLMs) have been shown to perform well in answering questions and in producing long-form texts, both in few-shot closed-book settings. While the former can be validated using well-known evaluation metrics, the latter is …","url":["https://arxiv.org/pdf/2210.17525"]}
-{"year":"2022","title":"Query-Driven Graph-Based User Recommender System","authors":["Y Li - 2022"],"snippet":"Current Social Networking Systems (SNS) such as YouTube are creator-driven systems in which creators create content and users search among available content to find what they want. However, queries from users can be time-sensitive, such as …","url":["https://ruor.uottawa.ca/bitstream/10393/43742/1/Li_Yansong_2022_thesis.pdf"]}
-{"year":"2022","title":"QueryForm: A Simple Zero-shot Form Entity Query Framework","authors":["Z Wang, Z Zhang, J Devlin, CY Lee, G Su, H Zhang… - arXiv preprint arXiv …, 2022"],"snippet":"Zero-shot transfer learning for document understanding is a crucial yet under-investigated scenario to help reduce the high cost involved in annotating document entities. We present a novel query-based framework, QueryForm, that extracts entity values from …","url":["https://arxiv.org/pdf/2211.07730"]}
-{"year":"2022","title":"Question Answering in Czech via Machine Translation and Cross-lingual Transfer","authors":["K Macková - 2022"],"snippet":"Reading comprehension and question answering are computer science disciplines in the field of natural language processing and information retrieval. Reading comprehension is the ability of the model to read text, process it and understand its …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/178197/150056797.pdf?sequence=1"]}
-{"year":"2022","title":"Question Generation and Answering in the Electrical Power System Components Domain","authors":["A Malik - 2022"],"snippet":"… This is English portion of Common Crawl data-set [Nag]. It has 63 M news articles crawled between … It is a subset of CommonCrawl data after filtering to match the story-like style of Winograd … To generate question corpus questions were …","url":["https://mediatum.ub.tum.de/doc/1690759/document.pdf"]}
-{"year":"2022","title":"Quick and (Maybe Not So) Easy Detection of Anorexia in Social Media","authors":["H Amini, E Mohammadi, L Kosseim - Early Detection of Mental Health Disorders by …, 2022"],"snippet":"This book chapter overviews our participation to the first sub-task of eRisk 2019 shared task, which was focused on the task of early detection of anorexia in Reddit posts. Our approach was to utilize several attention-based neural sub-models to …","url":["https://link.springer.com/chapter/10.1007/978-3-031-04431-1_6"]}
-{"year":"2022","title":"Quick and (Maybe Not So) Easy Detection of Anorexia in Social Media: To Explainability and Beyond","authors":["H Amini, E Mohammadi, L Kosseim - Early Detection of Mental Health Disorders by …, 2022"],"snippet":"This book chapter overviews our participation to the first sub-task of eRisk 2019 shared task, which was focused on the task of early detection of anorexia in Reddit posts. Our approach was to utilize several attention-based neural sub-models to …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=03KJEAAAQBAJ&oi=fnd&pg=PA141&dq=commoncrawl&ots=ilEvY4CTlF&sig=PwxjLELSMl0YX7p_MJjbgn7ZghI"]}
-{"year":"2022","title":"RAPIDS cuGraph","authors":["A Fender, B Rees, J Eaton - Massive Graph Analytics"],"snippet":"… -scale PageRank computations using the Common Crawl dataset [5].The Common Crawl dataset captures link relationships between web … Our system delivered much faster performance for the Common Crawl dataset, but the largest …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781003033707-22/rapids-cugraph-alex-fender-brad-rees-joe-eaton"]}
-{"year":"2022","title":"Readability of English, German, and Russian Disease-Related Wikipedia Pages: Automated Computational Analysis","authors":["J Gordejeva, R Zowalla, M Pobiruchin, M Wiesner - Journal of Medical Internet …, 2022"],"snippet":"Background Wikipedia is a popular encyclopedia for healthand disease-related information in which patients seek advice and guidance on the web. Yet, Wikipedia articles can be unsuitable as patient education materials, as investigated in previous …","url":["https://www.jmir.org/2022/5/e36835/"]}
-{"year":"2022","title":"Reading Comprehension","authors":["RS Roy, A Anand - Question Answering for the Curated Web, 2022"],"snippet":"… Corpora of curated text (like Wikipedia), large volumes of uncurated social-media posts, and massive Web document collection projects such as Common Crawl,1 are used to train these models. The key idea is that rather than going through the trouble …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-79512-1_9.pdf"]}
-{"year":"2022","title":"RECOGNITION THROUGH SPONTANEOUS SPEECH","authors":["S Luz, F Haider, D Fromm, B MacWhinney"],"snippet":"Alzheimer’s disease (AD) is a chronic neurodegenerative disease, without any known treatment. This disease progressively destroys brain structures, such as the hippocampus and entorhinal cortex, due to the accumulation of pathological forms of …","url":["https://www.research.ed.ac.uk/files/260484259/9782889718542_3.PDF"]}
-{"year":"2022","title":"Reducing Disambiguation Biases in NMT by Leveraging Explicit Word Sense Information","authors":["N Campolungo, T Pasini, D Emelin, R Navigli - … of the 2022 Conference of the North …, 2022"],"snippet":"Recent studies have shed some light on a common pitfall of Neural Machine Translation (NMT) models, stemming from their struggle to disambiguate polysemous words without lapsing into their most frequently occurring senses in the …","url":["https://aclanthology.org/2022.naacl-main.355.pdf"]}
-{"year":"2022","title":"Reducing Health Misinformation in Search Results","authors":["D Zhang - 2022"],"snippet":"… But topics in the 2020 track don’t have relevant documents in C4.en.noclean because it was extracted from the April 2019 snapshot3 of the Common Crawl corpus. Therefore, we performed our experiments on the data from the 2019 track …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/18602/Zhang_Dake.pdf?sequence=3"]}
-{"year":"2022","title":"Reducing the labeling effort for entity resolution using distant supervision and active learning","authors":["A Primpeli - 2022"],"snippet":"… during the period 2012 to 2020 by extracting structured data from the Common Crawl web corpus.Along with this analysis, we are the first to … [C3] WDC Product Corpus We exploit semantically annotated productrelated data extracted from the …","url":["https://madoc.bib.uni-mannheim.de/62507/1/PhD_Thesis_Primpeli.pdf"]}
-{"year":"2022","title":"Refining Low-Resource Unsupervised Translation by Language Disentanglement of Multilingual Model","authors":["XP Nguyen, S Joty, W Kui, AT Aw - arXiv preprint arXiv:2205.15544, 2022"],"snippet":"… For each group, we use monolingual corpora from the relevant languages of the Common Crawl dataset, which contains data from totally 25 languages [21]. We limit the amount of monolingual data per language to up to 100M sentences. Similarly to …","url":["https://arxiv.org/pdf/2205.15544"]}
-{"year":"2022","title":"Refining Word Embeddings with Sentiment Information for Sentiment Analysis","authors":["M Kasri, M Birjali, M Nabil, A Beni-Hssane, A El-Ansari… - Journal of ICT …, 2022"],"snippet":"Natural Language Processing problems generally require the use of pre-trained distributed word representations to be solved with deep learning models. However, distributed representations usually rely on contextual information which prevents …","url":["https://journals.riverpublishers.com/index.php/JICTS/article/download/13885/14687"]}
-{"year":"2022","title":"Register identification from the unrestricted open Web using the Corpus of Online Registers of English","authors":["V Laippala, S Rönnqvist, M Oinonen, AJ Kyröläinen… - Language Resources and …, 2022"],"snippet":"This article examines the automatic identification of Web registers, that is, text varieties such as news articles and reviews. Most studies have focused on corpora restricted to include only preselected classes with well-defined characteristics …","url":["https://link.springer.com/article/10.1007/s10579-022-09624-1"]}
-{"year":"2022","title":"Register variation remains stable across 60 languages","authors":["H Li, J Dunn, A Nini - Corpus Linguistics and Linguistic Theory, 2022"],"snippet":"This paper measures the stability of cross-linguistic register variation. A register is a variety of a language that is associated with extra-linguistic context. The relationship between a register and its context is functional: the linguistic features that make up a …","url":["https://arxiv.org/pdf/2209.09813"]}
-{"year":"2022","title":"Regressing Word and Sentence Embeddings for Low-Resource Neural Machine Translation","authors":["IJ Unanue, EZ Borzeshi, M Piccardi - IEEE Transactions on Artificial Intelligence, 2022"],"snippet":"… The training set contains over 5M sentence pairs collected from the Europarl, CommonCrawl and Newscommentary parallel corpora. As validation and test sets, we have used the newstest2017 and the newstest2018 datasets, respectively. This …","url":["https://ieeexplore.ieee.org/abstract/document/9813389/"]}
-{"year":"2022","title":"Regularization-based Pruning of Irrelevant Weights in Deep Neural Architectures","authors":["B Giovanni, R Matteo, C Rossella - APPLIED INTELLIGENCE, 2022","G Bonetta, M Ribero, R Cancelliere - arXiv preprint arXiv:2204.04977, 2022"],"snippet":"Deep neural networks exploiting millions of parameters are nowadays the norm in deep learning applications. This is a potential issue because of the great amount of computational resources needed for training, and of the possible loss of …","url":["https://arxiv.org/pdf/2204.04977","https://iris.unito.it/bitstream/2318/1877432/1/Sparsity_Applied_Intelligence_Final.pdf"]}
-{"year":"2022","title":"Related Questions Retrieval Model in Stack Overflow based on Semantic Matching","authors":["Z Qin, Y Wu, J Pei, J Lu, S Huang, L Liu - … IEEE 46th Annual Computers, Software, and …, 2022"],"snippet":"… The GloVe-840B [23] is pre-trained on the Common Crawl corpus with many texts that are irrelevant to the software engineering domain. The SE (15G) [9] is pre-trained on a 15GB corpus collected from Stack Overflow data dumps. …","url":["https://ieeexplore.ieee.org/abstract/document/9842482/"]}
-{"year":"2022","title":"Relational Embeddings for Language Independent Stance Detection","authors":["JF de Landa, R Agerri - arXiv preprint arXiv:2210.05715, 2022"],"snippet":"The large majority of the research performed on stance detection has been focused on developing more or less sophisticated text classification systems, even when many benchmarks are based on social network data such as Twitter. This paper …","url":["https://arxiv.org/pdf/2210.05715"]}
-{"year":"2022","title":"Report 2 on ASR Systems","authors":["TNN KIT, CH KIT - 2022"],"snippet":"1 Executive Summary In this deliverable we describe the final automatic speech recognition (ASR) systems that we created for the ELITR speech translation system. In Section 2 we describe our work. In the subsections 2.1 and 2.2 we address tasks …","url":["https://elitr.eu/wp-content/uploads/2022/06/D2.2.pdf"]}
-{"year":"2022","title":"Representations of emotion concepts: Comparison across pairwise, appraisal feature-based, and word embedding-based similarity spaces","authors":["M Kwon, T Wager, J Phillips - Proceedings of the Annual Meeting of the Cognitive …, 2022"],"snippet":"A question that has long interested cognitive scientists is how to best represent the different emotions we experience and attribute to others. For example, constructionist and appraisal theories propose that differences between emotions …","url":["https://escholarship.org/content/qt8vj3d366/qt8vj3d366.pdf"]}
-{"year":"2022","title":"Reproducible scaling laws for contrastive language-image learning","authors":["M Cherti, R Beaumont, R Wightman, M Wortsman… - arXiv preprint arXiv …, 2022"],"snippet":"… More recently, larger image-text datasets have been collected from Common Crawl [1]. The resulting datasets, LAION-400M [66] and … Both LAION-400M [66] and LAION-5B [65] are open, public image-text datasets that were composed by …","url":["https://arxiv.org/pdf/2212.07143"]}
-{"year":"2022","title":"Reproduction and Replication of an Adversarial Stylometry Experiment","authors":["H Wang, P Juola, A Riddell - arXiv preprint arXiv:2208.07395, 2022"],"snippet":"Maintaining anonymity while communicating using natural language remains a challenge. Standard authorship attribution techniques that analyze candidate authors' writing styles achieve uncomfortably high accuracy even when the number …","url":["https://arxiv.org/pdf/2208.07395"]}
-{"year":"2022","title":"Research Article COVID-19 Outbreak Forecasting Based on Vaccine Rates and Tweets Classification","authors":["Y Didi, A Walha, MB Halima, A Wali - 2022"],"snippet":"Copyright© 2022 Y. Didi et al. is is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. e …","url":["https://downloads.hindawi.com/journals/cin/2022/4535541.pdf"]}
-{"year":"2022","title":"Research Article Qualitative Analysis of Text Summarization Techniques and Its Applications in Health Domain","authors":["AK Yadav, KV Bhadane, A Kumar, B Khan - 2022"],"snippet":"Summarizing textual information requires understanding and analyzing the linguistic, conceptual, and semantic attributes of the given information. In addition, a summary generated should succeed in incorporating the essential details and the main ideas …","url":["https://www.academia.edu/download/83013544/3411881.pdf"]}
-{"year":"2022","title":"Research Background","authors":["R Richner - Auto-Grader-Auto-Grading Free Text Answers, 2022"],"snippet":"Research Background Page 1 3 Research Background Firstly, this chapter will introduce the technological background needed to understand how a state-of-the-art auto-grader may look and secondly elaborate on related work in the field of …","url":["https://link.springer.com/content/pdf/10.1007/978-3-658-39203-1_3.pdf"]}
-{"year":"2022","title":"Rethinking Data Governance: A Labor-Oriented Approach","authors":["H LI, N VINCENT - 2022"],"snippet":"… Prominent examples include Flickr photos [12], Wikipedia articles [14], and the Common Crawl dataset consisting of publicly available webpages [11]. In many of such cases, users produce data without being aware of its value and potential …","url":["https://criticalautomation.org/wp-content/uploads/2022/03/li-vincent-data-governance.pdf"]}
-{"year":"2022","title":"Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?","authors":["S Min, X Lyu, A Holtzman, M Artetxe, M Lewis… - arXiv preprint arXiv …, 2022","WMICL Work"],"snippet":"Large language models (LMs) are able to in-context learn--perform a new task via inference alone by conditioning on a few input-label pairs (demonstrations) and making predictions for new inputs. However, there has been little understanding of …","url":["https://arxiv.org/pdf/2202.12837","https://openreview.net/pdf?id=cnRGMv-Ak7u"]}
-{"year":"2022","title":"Revisiting CCNet for Quality Measurements in Galician","authors":["JE Ortega, I de-Dios-Flores, JR Pichel, P Gamallo - International Conference on …, 2022","JR Pichel, P Gamallo","P Gamallo - … Processing of the Portuguese Language: 15th …"],"snippet":"… In this article, we present our findings on reproducing the introduction of the common crawl corpus by Facebook, known as the CCNet … as the Common Crawl 2 corpus based on a “snapshot” of the web at a given time – the work on CCNet is …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Df9kEAAAQBAJ&oi=fnd&pg=PA407&dq=commoncrawl&ots=UGnguc7I3u&sig=8yrKGw8bPU5TtHaLaA-1I63OUas","https://gramatica.usc.es/~gamallo/artigos-web/PROPOR2022.pdf","https://link.springer.com/chapter/10.1007/978-3-030-98305-5_38"]}
-{"year":"2022","title":"Revisiting DocRED--Addressing the Overlooked False Negative Problem in Relation Extraction","authors":["Q Tan, L Xu, L Bing, HT Ng - arXiv preprint arXiv:2205.12696, 2022"],"snippet":"The DocRED dataset is one of the most popular and widely used benchmarks for document-level relation extraction (RE). It adopts a recommend-revise annotation scheme so as to have a large-scale annotated dataset. However, we find that the …","url":["https://arxiv.org/pdf/2205.12696"]}
-{"year":"2022","title":"Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding","authors":["A Ghaddar, Y Wu, S Bagga, A Rashid, K Bibi… - arXiv preprint arXiv …, 2022"],"snippet":"… We collect pre-training data from the following sources: common crawl (CC), news (NEWS, ELKHAIR), and Wikipedia (WIKI).Recent … Common Crawl (CC): We used 10 shards of Common Crawl8 data from March to December 2020. After …","url":["https://arxiv.org/pdf/2205.10687"]}
-{"year":"2022","title":"RigoBERTa: A State-of-the-Art Language Model For Spanish","authors":["AV Serrano, GG Subies, HM Zamorano, NA Garcia… - arXiv preprint arXiv …, 2022"],"snippet":"… OSCAR [28] [29] is a very large multilingual corpus, obtained by language classification and filtering of the CommonCrawl7. It has a portion of … For example, javascript code, automatic writings, poor automatic translations or malformed …","url":["https://arxiv.org/pdf/2205.10233"]}
-{"year":"2022","title":"RobBERT-2022: Updating a Dutch Language Model to Account for Evolving Language Use","authors":["P Delobelle, T Winters, B Berendt - arXiv preprint arXiv:2211.08192, 2022"],"snippet":"… 2019) is based on automatically language-classified Common Crawl documents.The corpus has a release with data up until January 2022, which in contrast with previous releases is now a full documents corpus instead of the previous pre-shuffled …","url":["https://arxiv.org/pdf/2211.08192"]}
-{"year":"2022","title":"Robust Domain Adaptation for Pre-trained Multilingual Neural Machine Translation Models","authors":["M Grosso, P Ratnamogan, A Mathey, W Vanhuffel… - arXiv preprint arXiv …, 2022"],"snippet":"Recent literature has demonstrated the potential of multilingual Neural Machine Translation (mNMT) models. However, the most efficient models are not well suited to specialized industries. In these cases, internal data is scarce and expensive to …","url":["https://arxiv.org/pdf/2210.14979"]}
-{"year":"2022","title":"Robust Knowledge Acquisition in Answering Information-seeking Questions At Scale","authors":["E Kamalloo - 2022"],"snippet":"Answering information-seeking question involves retrieving relevant documents from a massive haystack of unstructured text corpora. This dissertation aims at building question answering (QA) systems that can be deployed in the wild where …","url":["https://era.library.ualberta.ca/items/7c56859b-ba57-40fc-8af3-6a6ab168e1e5/download/60cf2b19-0dbb-4340-a6e2-33fc1964ffd7"]}
-{"year":"2022","title":"Robust Phishing Detection Against Adversaries","authors":["S Al-Ahmadi - Journal: WSEAS TRANSACTIONS ON COMPUTER …, 2022"],"snippet":"Phishing websites have grown more recently than ever, and they become more intelligent, even against well-designed phishing detection techniques. Formerly, we have proposed in the literature a state-of-the-art URL-exclusive phishing detection …","url":["https://ouci.dntb.gov.ua/en/works/lRjbXjjl/"]}
-{"year":"2022","title":"Robustness Analysis of Grover for Machine-Generated News Detection","authors":["R Gagiano, MMH Kim, X Zhang, J Biggs"],"snippet":"Advancements in Natural Language Generation have raised concerns on its potential misuse for deep fake news. Grover is a model for both generation and detection of neural fake news. While its performance on automatically discriminating …","url":["https://alta2021.alta.asn.au/files/ALTW_2021_paper_7.pdf"]}
-{"year":"2022","title":"Romantic-Computing","authors":["E Horishny - arXiv preprint arXiv:2206.11864, 2022"],"snippet":"In this paper we compare various text generation models' ability to write poetry in the style of early English Romanticism. These models include: Character-Level Recurrent Neural Networks with Long Short-Term Memory, Hugging Face's GPT-2 …","url":["https://arxiv.org/pdf/2206.11864"]}
-{"year":"2022","title":"Russian Web Tables: A Public Corpus of Web Tables for Russian Language Based on Wikipedia","authors":["P Fedorov, A Mironov, G Chernishev - arXiv preprint arXiv:2210.06353, 2022"],"snippet":"… Therefore, relying on the Common Crawl dataset would require a multimachine environment. For example, in case of the WDC Web Table Corpus, the … Therefore, it is prohibitevely expensive for low-budged projects or individual students to use the …","url":["https://arxiv.org/pdf/2210.06353"]}
-{"year":"2022","title":"SALTED: A Framework for SAlient Long-Tail Translation Error Detection","authors":["V Raunak, M Post, A Menezes - arXiv preprint arXiv:2205.09988, 2022"],"snippet":"Traditional machine translation (MT) metrics provide an average measure of translation quality that is insensitive to the long tail of behavioral problems in MT. Examples include translation of numbers, physical units, dropped content and …","url":["https://arxiv.org/pdf/2205.09988"]}
-{"year":"2022","title":"Sample, Translate, Recombine: Leveraging Audio Alignments for Data Augmentation in End-to-end Speech Translation","authors":["TK Lam, S Schamoni, S Riezler - arXiv preprint arXiv:2203.08757, 2022"],"snippet":"End-to-end speech translation relies on data that pair source-language speech inputs with corresponding translations into a target language. Such data are notoriously scarce, making synthetic data augmentation by back-translation or …","url":["https://arxiv.org/pdf/2203.08757"]}
-{"year":"2022","title":"Samsung R&D Institute participation in WMT 2022 General MT Task","authors":["A Dobrowolski, M Klimaszewski, A Mysliwy…"],"snippet":"… CommonCrawl, we used only lines/paragraphs containing three or more sentences, which we split into single sentences. News-CommonCrawl … crawl and 100k sentences from CommonCrawl. Using this model, we selected sentences classified …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.17.pdf"]}
-{"year":"2022","title":"Sarcasm Detection Framework Using Emotion and Sentiment Features","authors":["O Vitman, Y Kostiuk, G Sidorov, A Gelbukh - arXiv preprint arXiv:2211.13014, 2022"],"snippet":"… We used Glove Common Crawl4 pretrained vectors (42 billion words version). For words with no pre-trained vectors, we checked their stemmed versions. If no pre-trained embedding were found, random vector was initialized. …","url":["https://arxiv.org/pdf/2211.13014"]}
-{"year":"2022","title":"Sarcasm detection using deep learning and ensemble learning","authors":["P Goel, R Jain, A Nayyar, S Singhal, M Srivastava - Multimedia Tools and …, 2022"],"snippet":"Across the globe, there is a noticeable upward trend of incorporating sarcasm in everyday life. This trend can be easily attributed to the frequent use of sarcasm in everyday life, but more specifically to social media and the Internet. This study aims …","url":["https://link.springer.com/article/10.1007/s11042-022-12930-z"]}
-{"year":"2022","title":"Scaling Laws and Interpretability of Learning from Repeated Data","authors":["D Hernandez, T Brown, T Conerly, N DasSarma… - arXiv preprint arXiv …, 2022"],"snippet":"Recent large language models have been trained on vast datasets, but also often on repeated data, either intentionally for the purpose of upweighting higher quality data, or unintentionally because data deduplication is not perfect and the model is …","url":["https://arxiv.org/pdf/2205.10487"]}
-{"year":"2022","title":"Scaling Laws Beyond Backpropagation","authors":["MJ Filipovich, A Cappelli, D Hesslow, J Launay - arXiv preprint arXiv:2210.14593, 2022"],"snippet":"… The models are trained on 30B tokens of English CommonCrawl data filtered with CCNet [41], with hyper-parameters adapted from GPT-3 [29], but with a context size of 512 for increased training speed. We chose different optimization hyper-parameters …","url":["https://arxiv.org/pdf/2210.14593"]}
-{"year":"2022","title":"SDW-ASL: A Dynamic System to Generate Large Scale Dataset for Continuous American Sign Language","authors":["Y Jiang - arXiv preprint arXiv:2210.06791, 2022"],"snippet":"… For example, the GPT-3 model with 175 billion parameters was trained using the ever-growing Common Crawl dataset with close to 1 trillion words. The largest dataset for ASL is dwarfed in comparison — so far it is only around 10-thousand …","url":["https://arxiv.org/pdf/2210.06791"]}
-{"year":"2022","title":"Second place solution of Amazon KDD Cup 2022: ESCI Challenge for Improving Product Search","authors":["X Qin, N Liang, H Zhang, W Zou, W Zhang"],"snippet":"How to improve the search experience is a hot topic that has been studied for decades in both academia and industry. KDD Cup 2022 ESCI Challenge organized by Amazon provides a large dataset with four categories of ESCI to improve …","url":["https://amazonkddcup.github.io/papers/8408.pdf"]}
-{"year":"2022","title":"Securing the Next Generation Web","authors":["B Eriksson - 2022"],"snippet":"… We evaluate Black Ostrich on a set of 8 821 unique validation patterns gathered from over 21 667 978 forms from a combination of the July 2021 Common Crawl and Tranco top 100K. For these forms and reconstructions of input elements …","url":["https://search.proquest.com/openview/086d85c81a8dd4762211543c916a6235/1.pdf?pq-origsite=gscholar&cbl=2026366&diss=y"]}
-{"year":"2022","title":"Security and Privacy Challenges for Intelligent Internet of Things Devices 2022 TADW: Traceable and Antidetection Dynamic Watermarking of Deep Neural Networks","authors":["J Dong, H Wang, Z He, J Niu, X Zhu, G Wu - Security and Communication Networks, 2022"],"snippet":"Deep neural networks (DNN) with incomparably advanced performance have been extensively applied in diverse fields (eg, image recognition, natural language processing, and speech recognition). Training a high-performance DNN model …","url":["https://www.hindawi.com/journals/scn/2022/9505808/"]}
-{"year":"2022","title":"Seeing the advantage: visually grounding word embeddings to better capture human semantic knowledge","authors":["D Merkx, SL Frank, M Ernestus - arXiv preprint arXiv:2202.10292, 2022"],"snippet":"Distributional semantic models capture word-level meaning that is useful in many natural language processing tasks and have even been shown to capture cognitive aspects of word meaning. The majority of these models are purely text based, even …","url":["https://arxiv.org/pdf/2202.10292"]}
-{"year":"2022","title":"SEHC: A Benchmark Setup to Identify Online Hate Speech in English","authors":["S Ghosh, A Ekbal, P Bhattacharyya, T Saha, A Kumar… - IEEE Transactions on …, 2022"],"snippet":"… The embeddings are fetched from GloVe (300-dimension) pre-trained word embedding, which was trained on the Common Crawl corpus (840 billion tokens). We pad input arrays with zeros to make input sequences the same length. On our …","url":["https://ieeexplore.ieee.org/abstract/document/9738838/"]}
-{"year":"2022","title":"Self-admitted technical debt classification using natural language processing word embeddings","authors":["AF Sabbah, AA Hanani - International Journal of Electrical and Computer …, 2023"],"snippet":"Recent studies show that it is possible to detect technical dept automatically from source code comments intentionally created by developers, a phenomenon known as self-admitted technical debt. This study proposes a system by which a comment …","url":["https://www.researchgate.net/profile/Ahmed-Sabbah/publication/366204787_Self-admitted_technical_debt_classification_using_natural_language_processing_word_embeddings/links/63977b01e42faa7e75b9f25c/Self-admitted-technical-debt-classification-using-natural-language-processing-word-embeddings.pdf"]}
-{"year":"2022","title":"SEMANTIC ACCOUNTS OF RISK PERCEPTION","authors":["Z Hussaina, R Mataa, DU Wulffa - life"],"snippet":"… Common Crawl, 1011 tokens …","url":["https://psychologie.unibas.ch/fileadmin/user_upload/psychologie/Beacon/SAoRP_Poster_Final.pdf"]}
-{"year":"2022","title":"Semantic Annotation of Numerical Data in Web Tables","authors":["Y Su - 2021"],"snippet":"A large portion of quantitative information about entities mentioned in Web pages is expressed as Web tables, and these tables often lack proper schema and annotation, which introduces challenges for the purpose of querying and further analysis. In this …","url":["https://scholar.archive.org/work/bb4fkx7uzzbi7pnelydtz4nnsy/access/wayback/https://era.library.ualberta.ca/items/b25fe525-b33c-4954-a5d4-3066f797cd34/view/a1788204-c1a8-4a67-be55-57005a93cabc/Su_Yuchen_202109_MSc.pdf"]}
-{"year":"2022","title":"Semantic Comparisons for Natural Language Processing Applications","authors":["L Lin - 2021"],"snippet":"For social scientists and other data practitioners, the abundance of available digital text data is a rich potential source for understanding social phenomena. As a result, practitioners have increasingly used text analysis methods on relevant corpora to …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/48232/Lin_washington_0250E_23655.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"Semantic Cross Attention for Few-shot Learning","authors":["B Xiao, CL Liu, WH Hsaio - arXiv preprint arXiv:2210.06311, 2022"],"snippet":"Few-shot learning (FSL) has attracted considerable attention recently. Among existing approaches, the metric-based method aims to train an embedding network that can make similar samples close while dissimilar samples as far as possible and …","url":["https://arxiv.org/pdf/2210.06311"]}
-{"year":"2022","title":"Semantic Network: A Brief Review of its Datasets","authors":["M Trovati, S Awan - International Conference on Intelligent Networking and …, 2022"],"snippet":"Semantic networks are graphical representations, in terms of nodes and edges, of words and phrases from the linguistics vocabulary to form a meaning and relation between them to describe the intended target or object. It is part of the computer …","url":["https://link.springer.com/chapter/10.1007/978-3-031-14627-5_21"]}
-{"year":"2022","title":"Semantic projection recovers rich human knowledge of multiple object features from word embeddings","authors":["G Grand, IA Blank, F Pereira, E Fedorenko - Nature Human Behaviour, 2022"],"snippet":"How is knowledge about word meaning represented in the mental lexicon? Current computational models infer word meanings from lexical co-occurrence patterns. They learn to represent words as vectors in a multidimensional space, wherein …","url":["https://www.nature.com/articles/s41562-022-01316-8"]}
-{"year":"2022","title":"Semantics-aware Dataset Discovery from Data Lakes with Contextualized Column-based Representation Learning","authors":["G Fan, J Wang, Y Li, D Zhang, R Miller - arXiv preprint arXiv:2210.01922, 2022"],"snippet":"Dataset discovery from data lakes is essential in many real application scenarios. In this paper, we propose Starmie, an end-to-end framework for dataset discovery from data lakes (with table union search as the main use case). Our proposed framework …","url":["https://web7.arxiv.org/pdf/2210.01922"]}
-{"year":"2022","title":"Semantics-driven Attentive Few-shot Learning over Clean and Noisy Samples","authors":["OB Baran, RG Cinbiş - arXiv preprint arXiv:2201.03043, 2022"],"snippet":"Over the last couple of years few-shot learning (FSL) has attracted great attention towards minimizing the dependency on labeled training examples. An inherent difficulty in FSL is the handling of ambiguities resulting from having too few training …","url":["https://arxiv.org/pdf/2201.03043"]}
-{"year":"2022","title":"SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding","authors":["HT Madabushi, E Gow-Smith, M Garcia, C Scarton… - arXiv preprint arXiv …, 2022"],"snippet":"This paper presents the shared task on Multilingual Idiomaticity Detection and Sentence Embedding, which consists of two subtasks: (a) a binary classification one aimed at identifying whether a sentence contains an idiomatic expression, and (b) a …","url":["https://arxiv.org/pdf/2204.10050"]}
-{"year":"2022","title":"Semi-Supervised Lifelong Language Learning","authors":["Y Zhao, Y Zheng, B Yu, Z Tian, D Lee, J Sun, H Yu, Y Li… - arXiv preprint arXiv …, 2022"],"snippet":"Lifelong learning aims to accumulate knowledge and alleviate catastrophic forgetting when learning tasks sequentially. However, existing lifelong language learning methods only focus on the supervised learning setting. Unlabeled data …","url":["https://arxiv.org/pdf/2211.13050"]}
-{"year":"2022","title":"Sentence Simplification Capabilities of Transfer-Based Models","authors":["S Štajner, KC Sheang, H Saggion - 2022"],"snippet":"… T5 is trained on Colossal Clean Crawled Corpus (C4), a dataset created by applying a set of filters to English-language text sourced from the public Common Crawl web scrape. • mT5 (Xue et al. 2021): a multilingual model based on T5 (Raffel …","url":["https://www.aaai.org/AAAI22Papers/AISI-7740.StajnerS.pdf"]}
-{"year":"2022","title":"SEntFiN 1.0: Entity‐aware sentiment analysis for financial news","authors":["A Sinha, S Kedas, R Kumar, P Malo - Journal of the Association for Information Science and …"],"snippet":"Fine‐grained financial sentiment analysis on news headlines is a challenging task requiring human‐annotated datasets to achieve high performance. Limited studies have tried to address the sentiment extraction task in a setting where multiple …","url":["https://asistdl.onlinelibrary.wiley.com/doi/abs/10.1002/asi.24634"]}
-{"year":"2022","title":"Sentiment Analysis of COVID-19 Vaccination Responses From Twitter Using Ensemble Learning","authors":["Q Ismail, R Obeidat, K Alissa, E Al-Sobh - 2022 13th International Conference on …, 2022"],"snippet":"… As an alternative to BERT, we also use RoBERTa, a robust pre-trained language model for English, learned from 160GB of texts covering books, Wikipedia, CommonCrawl news, CommonCrawl stories, and web text contents [11]. Our SA …","url":["https://ieeexplore.ieee.org/abstract/document/9811132/"]}
-{"year":"2022","title":"Sentiment Analysis of Russian Reviews to Estimate the Usefulness of Drugs Using the Domain-Specific XLM-RoBERTa Model","authors":["A Sboev, A Naumov, I Moloshnikov, R Rybka - Biologically Inspired Cognitive …, 2022"],"snippet":"This paper considers the problem of classifying Russian-language drug reviews into five classes (corresponding to the authors’ rating scores) and into two classes (the drug is helpful or useless) in terms of the sentiment analysis task. The dataset of …","url":["https://link.springer.com/chapter/10.1007/978-3-030-96993-6_49"]}
-{"year":"2022","title":"Sentiment Analysis with Linguistic Knowledge","authors":["P KLIMEŠOVÁ"],"snippet":"… This thesis employs FastText CBOW word and text vectors with dimensionality 300 pre-trained on Wikipedia and the Common Crawl1 web corpus with negative sampling and n-gram length 52. The SVM, Logistic Regression, and Naïve Bayes …","url":["https://is.muni.cz/th/n0lnb/Sentiment_Analysis_cz.pdf"]}
-{"year":"2022","title":"Sentiment Analysis: A comparative study of Deep Learning and Machine Learning","authors":["R Manshani, T Thatte, K Suryawanshi - 2022"],"snippet":"… using the word vectors trained on Common Crawl and one hot encoding our y variable or training set. Our model contains a commencing layer of LSTM that will collect all the word embeddings corresponding to each token as an input. Our main …","url":["https://www.academia.edu/download/93879140/IRJET_V9I1121.pdf"]}
-{"year":"2022","title":"SentSpace: Large-Scale Benchmarking and Evaluation of Text using Cognitively Motivated Lexical, Syntactic, and Semantic Features","authors":["G Tuckute, A Sathe, M Wang, H Yoder, C Shain… - Proceedings of the 2022 …, 2022"],"snippet":"SentSpace is a modular framework for streamlined evaluation of text. SentSpacecharacterizes textual input using diverse lexical, syntactic, and semantic features derivedfrom corpora and psycholinguistic experiments. Core sentence …","url":["https://aclanthology.org/2022.naacl-demo.11.pdf"]}
-{"year":"2022","title":"Sequence Labeling Architectures in Diglossia","authors":["M Weidlich"],"snippet":"… FastText is a lightweight library pretrained on the Common Crawl dataset18 and Wikipedia in 157 languages including Arabic19 “using [Continuous Bag of Words] with position-weights, in 300 dimensions, with character n-grams of length 5, a …","url":["https://www.researchgate.net/profile/Mohamed-Megahed-2/publication/358956953_Sequence_Labeling_Architectures_in_Diglossia_-_a_case_study_of_Arabic_and_its_dialects/links/621f2684ef04e66eb74d6e08/Sequence-Labeling-Architectures-in-Diglossia-a-case-study-of-Arabic-and-its-dialects.pdf"]}
-{"year":"2022","title":"SEScore2: Retrieval Augmented Pretraining for Text Generation Evaluation","authors":["W Xu, X Qian, M Wang, L Li, WY Wang - arXiv preprint arXiv:2212.09305, 2022"],"snippet":"Is it possible to leverage large scale raw and raw parallel corpora to build a general learned metric? Existing learned metrics have gaps to human judgements, are model-dependent or are limited to the domains or tasks where human ratings are available. In this …","url":["https://arxiv.org/pdf/2212.09305"]}
-{"year":"2022","title":"SEUPD@ CLEF: Team Hextech on argument retrieval for comparative questions. the importance of adjectives in documents quality evaluation","authors":["A Chimetto, D Peressoni, E Sabbatini, G Tommasin… - Working Notes Papers of the …, 2022"],"snippet":"This report explains our approach to solve the Task 2 challenge about Argument Retrieval for Comparative Questions proposed by the third Touché lab on argument retrieval at CLEF 2022. Given a comparative topic, the task is to retrieve relevant …","url":["http://ceur-ws.org/Vol-3180/paper-256.pdf"]}
-{"year":"2022","title":"SexWEs: Domain-Aware Word Embeddings via Cross-lingual Semantic Specialisation for Chinese Sexism Detection in Social Media","authors":["A Jiang, A Zubiaga - arXiv preprint arXiv:2211.08447, 2022"],"snippet":"The goal of sexism detection is to mitigate negative online content targeting certain gender groups of people. However, the limited availability of labeled sexism-related datasets makes it problematic to identify online sexism for low-resource languages …","url":["https://arxiv.org/pdf/2211.08447"]}
-{"year":"2022","title":"Shedding Light on the Dark Web: Authorship Attribution in Radical Forums","authors":["L Ranaldi, F Ranaldi, F Fallucchi, FM Zanzotto - Information, 2022"],"snippet":"Online users tend to hide their real identities by adopting different names on the Internet. On Facebook or LinkedIn, for example, people usually appear with their real names. On other standard websites, such as forums, people often use …","url":["https://www.mdpi.com/2078-2489/13/9/435/pdf?version=1663167115"]}
-{"year":"2022","title":"Simple measures of bridging lexical divergence help unsupervised neural machine translation for low-resource languages","authors":["J Khatri, R Murthy, T Banerjee, P Bhattacharyya - Machine Translation, 2022"],"snippet":"… We consider CommonCrawl and the BigEst Estonian Corpus from the WMT18 shared task (Bojar et al. ) to create the monolingual corpus for Estonian. For English, we consider News Crawl 2017 and News Discussions 2017 from the WMT17 shared …","url":["https://link.springer.com/article/10.1007/s10590-021-09292-y"]}
-{"year":"2022","title":"Simultaneous Translation for Unsegmented Input: A Sliding Window Approach","authors":["S Sen, O Bojar, B Haddow - arXiv preprint arXiv:2210.09754, 2022"],"snippet":"In the cascaded approach to spoken language translation (SLT), the ASR output is typically punctuated and segmented into sentences before being passed to MT, since the latter is typically trained on written text. However, erroneous segmentation …","url":["https://arxiv.org/pdf/2210.09754"]}
-{"year":"2022","title":"SketchNE: Embedding Billion-Scale Networks Accurately in One Hour","authors":["Y Xie, Y Dong, J Qiu, W Yu, X Feng, J Tang"],"snippet":"We study large-scale network embedding with the goal of generating high-quality embeddings for networks with more than 1 billion vertices and 100 billion edges. Recent attempts LightNE and NetSMF propose to sparsify and factorize the (dense) …","url":["https://keg.cs.tsinghua.edu.cn/yuxiao/papers/2022.02-Xie-et-al-SketchNE.pdf"]}
-{"year":"2022","title":"Sliced at SemEval-2022 Task 11: Bigger, Better? Massively Multilingual LMs for Multilingual Complex NER on an Academic GPU Budget","authors":["B Plank - Proceedings of the 16th International Workshop on …, 2022"],"snippet":"Massively multilingual language models (MMLMs) have become a widely-used representation method, and multiple large MMLMs were proposed in recent years. A trend is to train MMLMs on larger text corpora or with more layers. In this paper we …","url":["https://aclanthology.org/2022.semeval-1.205.pdf"]}
-{"year":"2022","title":"SMILE: Scaling Mixture-of-Experts with Efficient Bi-level Routing","authors":["C He, S Zheng, A Zhang, G Karypis, T Chilimbi… - arXiv preprint arXiv …, 2022"],"snippet":"… We evaluate the performance of SMILE by pre-training on the “Colossal Clean Crawled Corpus” (C4), a collection of English-language text sourced from the public Common Crawl web scrape. It includes heuristics to extract only natural language (as …","url":["https://arxiv.org/pdf/2212.05191"]}
-{"year":"2022","title":"Smooth inverse frequency based text data selection for medical dictation","authors":["D Bálint, P Mihajlik"],"snippet":"Under-resourced domain problem is significant in automatic speech recognition, especially in small languages such as Hungarian or in fields where data is often confidential such as finance and medicine. We introduce a method using word …","url":["http://acta.bibl.u-szeged.hu/73371/1/msznykonf_017_233-242.pdf"]}
-{"year":"2022","title":"SMTCE: A Social Media Text Classification Evaluation Benchmark and BERTology Models for Vietnamese","authors":["LT Nguyen, K Van Nguyen, NLT Nguyen - arXiv preprint arXiv:2209.10482, 2022"],"snippet":"Text classification is a typical natural language processing or computational linguistics task with various interesting applications. As the number of users on social media platforms increases, data acceleration promotes emerging studies on …","url":["https://arxiv.org/pdf/2209.10482"]}
-{"year":"2022","title":"Social and Web presence of Cultural Heritage Organisations in India","authors":["H Singh, M Gupta - 2022"],"snippet":"The present study focuses on the Social and Web presence of 27 Cultural Heritage Organisations in India. The purpose of this study is to investigate the domain authority, number of webpages, links, calculate the web impact factors and link-mentions …","url":["https://www.researchgate.net/profile/Mansi-Gupta-45/publication/362076832_Social_and_Web_presence_of_Cultural_Heritage_Organisations_in_India/links/62d583c8bf4b98532231ac8e/Social-and-Web-presence-of-Cultural-Heritage-Organisations-in-India.pdf"]}
-{"year":"2022","title":"SoK: On the Impossible Security of Very Large Foundation Models","authors":["EM El-Mhamdi, S Farhadkhani, R Guerraoui, N Gupta… - arXiv preprint arXiv …, 2022"],"snippet":"Large machine learning models, or so-called foundation models, aim to serve as base-models for application-oriented machine learning. Although these models showcase impressive performance, they have been empirically found to pose …","url":["https://arxiv.org/pdf/2209.15259"]}
-{"year":"2022","title":"Solving Hungarian natural language processing tasks with multilingual generative models","authors":["ZG Yang, LJ Laki"],"snippet":"Generative ability is a crucial need for artificial intelligence applications, such as chatbots, virtual assistants, machine translation systems etc. In recent years, the transformer-based neural architectures gave a huge boost to generate human-like …","url":["https://ami.uni-eszterhazy.hu/uploads/papers/finalpdf/AMI_online_1322.pdf"]}
-{"year":"2022","title":"Some Languages are More Equal than Others: Probing Deeper into the Linguistic Disparity in the NLP World","authors":["S Ranathunga, N de Silva - arXiv preprint arXiv:2210.08523, 2022"],"snippet":"Linguistic disparity in the NLP world is a problem that has been widely acknowledged recently. However, different facets of this problem, or the reasons behind this disparity are seldom discussed within the NLP community. This paper …","url":["https://arxiv.org/pdf/2210.08523"]}
-{"year":"2022","title":"SOS: Systematic Offensive Stereotyping Bias in Word Embeddings","authors":["F Elsafoury, SR Wilson, S Katsigiannis, N Ramzan"],"snippet":"Systematic Offensive stereotyping (SOS) in word embeddings could lead to associating marginalised groups with hate speech and profanity, which might lead to blocking and silencing those groups, especially on social media platforms. In this …","url":["https://efatmae.github.io/files/publications/2022/SOS_2022/SOS_bias_paper.pdf"]}
-{"year":"2022","title":"SPARQL querying for validating the usage of automatically georeferenced social media data as human sensors for air quality","authors":["S Andreadis, T Mavropoulos, N Pantelidis, S Vrochidis… - 2022 IEEE 14th Image …, 2022"],"snippet":"… original XLM model, XLM-R drew inspiration from RoBERTa [19], in the sense that it was trained for a longer time on more data, ie more than 2TBs of filtered CommonCrawl data. Since the tweets collection relates to the German language, a …","url":["https://2022.ivmsp.org/wp-content/uploads/2022/06/2022101087_IVMSP2022_CR_Copyright.pdf"]}
-{"year":"2022","title":"SPBERTQA: A Two-Stage Question Answering System Based on Sentence Transformers for Medical Texts","authors":["NTH Nguyen, PPD Ha, LT Nguyen, K Van Nguyen… - arXiv preprint arXiv …, 2022"],"snippet":"Question answering (QA) systems have gained explosive attention in recent years. However, QA tasks in Vietnamese do not have many datasets. Significantly, there is mostly no dataset in the medical domain. Therefore, we built a Vietnamese …","url":["https://arxiv.org/pdf/2206.09600"]}
-{"year":"2022","title":"Speculative Propositions for Digital Writing Under the New Autonomous Model of Literacy","authors":["B Robinson - Postdigital Science and Education, 2022"],"snippet":"The proliferation of powerful new forms of automated assistive writing technologies, natural language generation technologies in particular, raises crucial questions about the future of literacy living and learning. This article situates such technologies …","url":["https://link.springer.com/article/10.1007/s42438-022-00358-5"]}
-{"year":"2022","title":"Speech-to-Speech Translation For A Real-world Unwritten Language","authors":["PJ Chen, K Tran, Y Yang, J Du, J Kao, YA Chung… - arXiv preprint arXiv …, 2022"],"snippet":"… With the trained text and speech encoders, we perform data mining between Hokkien speech from Hokkien dramas and English Common Crawl text, and between the former and Librivox English audio7. We post-process the mined data in …","url":["https://arxiv.org/pdf/2211.06474"]}
-{"year":"2022","title":"SpeechMatrix: A Large-Scale Mined Corpus of Multilingual Speech-to-Speech Translations","authors":["PA Duquenne, H Gong, N Dong, J Du, A Lee… - arXiv preprint arXiv …, 2022"],"snippet":"We present SpeechMatrix, a large-scale multilingual corpus of speech-to-speech translations mined from real speech of European Parliament recordings. It contains speech alignments in 136 language pairs with a total of 418 thousand hours of …","url":["https://arxiv.org/pdf/2211.04508"]}
-{"year":"2022","title":"Speeding up Inference Time of Neural Machine Translation","authors":["M GELETKA"],"snippet":"Large qualitative gains were recently made in machine translation tasks thanks to Transformers models. However, in practice, these models suffer from high latency, such that they often are hardly usable in practical applications. This thesis study …","url":["https://is.muni.cz/th/if8vh/speeding_up_NMT_final.pdf"]}
-{"year":"2022","title":"Stability of a Multilingual Sentiment Analysis based on Word-to-Word Translations","authors":["N Horibe, K Fujihira - International Journal of Service and Knowledge …, 2022"],"snippet":"People’s sentiments are known to have a large impact on changes in stock prices, products sales, and trends. Since web users generally state their opinion in various languages, it is important to develop a method of multilingual sentiment analysis for …","url":["https://iaiai.org/journals/index.php/IJSKM/article/download/664/531"]}
-{"year":"2022","title":"Stacked Model based Argument Extraction and Stance Detection using Embedded LSTM model","authors":["P Rajula, CC Hung, SP Ponzetto - Working Notes Papers of the CLEF, 2022"],"snippet":"In this paper, we present our submission approach for the third Touché lab at CLEF 2022 [1], shared task 2 on Argument Retrieval for Comparative Questions, which tackles answering comparative questions based on argument retrieval of text …","url":["http://ceur-ws.org/Vol-3180/paper-258.pdf"]}
-{"year":"2022","title":"Stance Detection of Political Tweets with Transformer Architectures","authors":["P Gunhal, A Bashyam, K Zhang, A Koster, J Huang…"],"snippet":"The online actions and words of a person can reveal their political sentiments and how they may vote at the polls. For decades, the dominant strategy of determining voter sentiment on policies relied on slow and often inaccurate polling. The creation …","url":["https://journal-home.s3.ap-northeast-2.amazonaws.com/site/ictc2022/abs/EW4-21.pdf"]}
-{"year":"2022","title":"State-of-the-art in Open-domain Conversational AI: A Survey","authors":["T Adewumi, F Liwicki, M Liwicki - arXiv preprint arXiv:2205.00965, 2022"],"snippet":"We survey SoTA open-domain conversational AI models with the purpose of presenting the prevailing challenges that still exist to spur future research. In addition, we provide statistics on the gender of conversational AI in order to guide the ethics …","url":["https://arxiv.org/pdf/2205.00965"]}
-{"year":"2022","title":"Stateful Memory-Augmented Transformers for Dialogue Modeling","authors":["Q Wu, Z Yu - arXiv preprint arXiv:2209.07634, 2022"],"snippet":"Transformer encoder-decoder models have shown impressive performance in dialogue modeling. However, as Transformers are inefficient in processing long sequences, dialogue history length often needs to be truncated. To address this …","url":["https://arxiv.org/pdf/2209.07634"]}
-{"year":"2022","title":"Statistical Dataset Evaluation: Reliability, Difficulty, and Validity","authors":["C Wang, Q Dong, X Wang, H Wang, Z Sui - arXiv preprint arXiv:2212.09272, 2022"],"snippet":"Datasets serve as crucial training resources and model performance trackers. However, existing datasets have exposed a plethora of problems, inducing biased models and unreliable evaluation results. In this paper, we propose a model-agnostic …","url":["https://arxiv.org/pdf/2212.09272"]}
-{"year":"2022","title":"Statistical detection of format dialects using the weighted Dowker complex","authors":["M Robinson, LW Li, C Anderson, S Huntsman - arXiv preprint arXiv:2201.08267, 2022"],"snippet":"… The good files were largely sourced from Common Crawl [15], while the bad files were drawn from various … sources: some were found in the wild (from Common Crawl), some were malicious files created by the Test and Evaluation Team, and …","url":["https://arxiv.org/pdf/2201.08267"]}
-{"year":"2022","title":"StoryNet: A 5W1H-Based Knowledge Graph to Connect Stories","authors":["SR Nagireddy - 2021"],"snippet":"Stories are a powerful medium through which the human community has exchanged information since the dawn of the information age. They have taken multiple forms like articles, movies, books, plays, short films, magazines, mythologies, etc. With the …","url":["https://search.proquest.com/openview/19566ca4aa369437c6fc323d788f8739/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"Strategies for Adapting Multilingual Pre-training for Domain-Specific Machine Translation","authors":["N Verma, K Murray, K Duh"],"snippet":"Pretrained multilingual sequence-to-sequence models have been successful in improving translation performance for mid-and lower-resourced languages. However, it is unclear if these models are helpful in the domain adaptation setting, and if so …","url":["https://www.cs.jhu.edu/~kevinduh/papers/verma22adapt.pdf"]}
-{"year":"2022","title":"Streaming neural machine translation systems from English into European languages","authors":["G Calabuig Doménech - 2022"],"snippet":"[EN] Machine translation is one of the most active areas within Artificial Intelligence, particularly in the field of Machine Learning. Recently, this area has been the focus of attention by major technology figures such as Google, Facebook, Microsoft, etc …","url":["https://riunet.upv.es/bitstream/handle/10251/187628/Calabuig%20-%20Streaming%20neural%20machine%20translation%20systems%20from%20English%20into%20European%20languages.pdf?sequence=1"]}
-{"year":"2022","title":"Streaming neural machine translation systems from European languages into English","authors":["AM Sarvazyan - 2022"],"snippet":"[EN] Machine translation is one of the most active areas within Artificial Intelligence, particularly in the field of Machine Learning. Recently, this area has been the focus of attention by major technology figures such as Google, Facebook, Microsoft, etc …","url":["https://riunet.upv.es/bitstream/handle/10251/185271/Sarvazyan%20-%20Streaming%20neural%20machine%20translation%20systems%20from%20European%20languages%20into%20English.pdf?sequence=1"]}
-{"year":"2022","title":"Streaming, fast and accurate on-device Inverse Text Normalization for Automatic Speech Recognition","authors":["Y Gaur, N Kibre, J Xue, K Shu, Y Wang, I Alphanso, J Li… - arXiv preprint arXiv …, 2022"],"snippet":"… The data is drawn from a coprora of email text, a collection of email addresses, common crawl data, and search queries. The selection of data from common crawl is loosely constrained to ITN-relevant strings, with some heuristics to avoid “mis-formatted” …","url":["https://arxiv.org/pdf/2211.03721"]}
-{"year":"2022","title":"Stress Detection from Social Media Articles: New Dataset Benchmark and Analytical Study","authors":["A Rastogi, Q Liu, E Cambria"],"snippet":"Stress detection is a basic and essential task for examining the mental health of a given population. With the rapid digitalization leading to text-based forms of communication gaining dominance over spoken ones, there is now the chance to …","url":["https://sentic.net/stress-detection-from-social-media.pdf"]}
-{"year":"2022","title":"Subspace-based Set Operations on a Pre-trained Word Embedding Space","authors":["Y Ishibashi, S Yokoi, K Sudoh, S Nakamura - arXiv preprint arXiv:2210.13034, 2022"],"snippet":"Word embedding is a fundamental technology in natural language processing. It is often exploited for tasks using sets of words, although standard methods for representing word sets and set operations remain limited. If we can leverage the …","url":["https://arxiv.org/pdf/2210.13034"]}
-{"year":"2022","title":"Subword-based Cross-lingual Transfer of Embeddings from Hindi to Marathi and Nepali","authors":["N Bafna, Z Žabokrtský - Proceedings of the 19th SIGMORPHON Workshop on …, 2022"],"snippet":"Word embeddings are growing to be a crucial resource in the field of NLP for any language. This work introduces a novel technique for static subword embeddings transfer for Indic languages from a relatively higher resource language to a …","url":["https://aclanthology.org/2022.sigmorphon-1.7.pdf"]}
-{"year":"2022","title":"SummVD: An efficient approach for unsupervised topic-based text summarization","authors":["G Shenouda, A Bossard, O Ayoub, C Rodrigues - … of the 2nd Conference of the Asia …, 2022"],"snippet":"This paper introduces a new method, SummVD, for automatic unsupervised extractive summarization. This method is based on singular value decomposition, a linear method in the number of words, in order to reduce the dimensionality of word …","url":["https://aclanthology.org/2022.aacl-main.38.pdf"]}
-{"year":"2022","title":"SumREN: Summarizing Reported Speech about Events in News","authors":["RG Reddy, H Elfardy, HP Chan, K Small, H Ji - arXiv preprint arXiv:2212.01146, 2022"],"snippet":"… We then collected a list of news articles discussing these events and retained articles that are present in Common Crawl (CC) News.We ended up with a total of 633 news articles corresponding to 132 major events. …","url":["https://arxiv.org/pdf/2212.01146"]}
-{"year":"2022","title":"Survey of NLP in Pharmacology: Methodology, Tasks, Resources, Knowledge, and Tools","authors":["D Trajanov, V Trajkovski, M Dimitrieva, J Dobreva… - arXiv preprint arXiv …, 2022"],"snippet":"Natural language processing (NLP) is an area of artificial intelligence that applies information technologies to process the human language, understand it to a certain degree, and use it in various applications. This area has rapidly developed in the …","url":["https://arxiv.org/pdf/2208.10228"]}
-{"year":"2022","title":"Survey on bimodal speech emotion recognition from acoustic and linguistic information fusion","authors":["BT Atmaja, A Sasou, M Akagi - Speech Communication, 2022"],"snippet":"Speech emotion recognition (SER) is traditionally performed using merely acoustic information. Acoustic features, commonly are extracted per frame, are mapped into emotion labels using classifiers such as support vector machines for machine …","url":["https://www.sciencedirect.com/science/article/pii/S0167639322000413"]}
-{"year":"2022","title":"Symptom or culprit? Social media, air pollution, and violence","authors":["X Du - 2022"],"snippet":"This paper provides the first causal evidence that hostile activities online lead to physical violence. Given the recently documented relationship between pollution and social media, I exploit exogenous variation in local air quality as the first step to …","url":["https://www.sipa.columbia.edu/sites/default/files/2022-11/draft20_1104.pdf"]}
-{"year":"2022","title":"SYNONYM DETECTION USING SYNTACTIC DEPENDENCY AND NEURAL EMBEDDINGS","authors":["D Yang, P Wang, X Sun, N Li"],"snippet":"Recent advances on the Vector Space Model have significantly improved some NLP applications such as neural machine translation and natural language generation. Although word co-occurrences in context have been widely used in counting-/predicting-based …","url":["http://www.iadisportal.org/ijwi/papers/202220102.pdf"]}
-{"year":"2022","title":"Synopses of Movie Narratives: a Video-Language Dataset for Story Understanding","authors":["Y Sun, Q Chao, B Li - arXiv preprint arXiv:2203.05711, 2022"],"snippet":"Despite recent advances of AI, story understanding remains an open and under-investigated problem. We collect, preprocess, and publicly release a video-language story dataset, Synopses of Movie Narratives(SyMoN), containing 5,193 video summaries …","url":["https://arxiv.org/pdf/2203.05711"]}
-{"year":"2022","title":"Synthesis and Evaluation of a Domain-specific Large Data Set for Dungeons & Dragons","authors":["A Peiris, N de Silva - arXiv preprint arXiv:2212.09080, 2022"],"snippet":"This paper introduces the Forgotten Realms Wiki (FRW) data set and domain specific natural language generation using FRW along with related analyses. Forgotten Realms is the de-facto default setting of the popular open ended tabletop …","url":["https://arxiv.org/pdf/2212.09080"]}
-{"year":"2022","title":"Table Pretraining: A Survey on Model Architectures, Pretraining Objectives, and Downstream Tasks","authors":["H Dong, Z Cheng, X He, M Zhou, A Zhou, F Zhou, A Liu… - arXiv preprint arXiv …, 2022"],"snippet":"Since a vast number of tables can be easily collected from web pages, spreadsheets, PDFs, and various other document types, a flurry of table pretraining frameworks have been proposed following the success of text and images, and they have …","url":["https://arxiv.org/pdf/2201.09745"]}
-{"year":"2022","title":"Tackling Social Value Tasks with Multilingual NLP","authors":["MR Awal - 2022"],"snippet":"In recent years, deep learning applications have shown promise in tackling social value tasks such as hate speech and misinformation in social media. Neural networks provide an efficient automated solution that has replaced hand-engineered …","url":["https://harvest.usask.ca/bitstream/handle/10388/14394/AWAL-THESIS-2022.pdf?sequence=1&isAllowed=y"]}
-{"year":"2022","title":"TAG: Learning Circuit Spatial Embedding From Layouts","authors":["K Zhu, H Chen, WJ Turner, GF Kokai, PH Wei, DZ Pan… - arXiv preprint arXiv …, 2022"],"snippet":"Analog and mixed-signal (AMS) circuit designs still rely on human design expertise. Machine learning has been assisting circuit design automation by replacing human experience with artificial intelligence. This paper presents TAG, a new paradigm of …","url":["https://arxiv.org/pdf/2209.03465"]}
-{"year":"2022","title":"Tagging terms in text","authors":["AR Terryn, V Hoste, E Lefever"],"snippet":"… We used the embeddings that are pre-trained on Common Crawl (for all languages). Finally, the hugely successful transformer-based architectures are supported in FlairNLP as well, through HuggingFace (Wolf et al. …","url":["https://www.researchgate.net/profile/Ayla_Rigouts_Terryn2/publication/356283802_Tagging_terms_in_text_A_supervised_sequential_labelling_approach_to_automatic_term_extraction/links/61f00c02c5e3103375bd750b/Tagging-terms-in-text-A-supervised-sequential-labelling-approach-to-automatic-term-extraction.pdf"]}
-{"year":"2022","title":"Talk to me: Database Vocalization Summaries using BART and PEGASUS","authors":["A Elkhouly, P Joshi, S Rathod, S Aziz, V Kalra…"],"snippet":"Zeta bytes of data are generated on a daily basis and this is growing continuously. Naturally, it is imperative for all kinds of stakeholders to have tools that help them gain insights into this data. So far text summarization work has been done using …","url":["https://www.academia.edu/download/78533097/TalkToMe1620511162956.pdf"]}
-{"year":"2022","title":"TamilEmo: Finegrained Emotion Detection Dataset for Tamil","authors":["C Vasantharajan, S Benhur, PK Kumarasen… - arXiv preprint arXiv …, 2022"],"snippet":"Emotional Analysis from textual input has been considered both a challenging and interesting task in Natural Language Processing. However, due to the lack of datasets in low-resource languages (ie Tamil), it is difficult to conduct research of …","url":["https://arxiv.org/pdf/2202.04725"]}
-{"year":"2022","title":"Tasks Using the Hugging Face Library","authors":["SM Jain - Introduction to Transformers for NLP, 2022"],"snippet":"… It produces a tidier version of the enormous Common Crawl dataset, which is referred to as the Colossal Cleaned Common Crawl (C4) . This dataset is approximately 100,000 times more extensive than Wikipedia. … It prepares the body …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-8844-3_5"]}
-{"year":"2022","title":"TaTa: A Multilingual Table-to-Text Dataset for African Languages","authors":["S Gehrmann, S Ruder, V Nikolaev, JA Botha… - arXiv preprint arXiv …, 2022"],"snippet":"Existing data-to-text generation datasets are mostly limited to English. To address this lack of data, we create Table-to-Text in African languages (TaTa), the first large multilingual table-to-text dataset with a focus on African languages. We created …","url":["https://arxiv.org/pdf/2211.00142"]}
-{"year":"2022","title":"Teaching AI when to care about gender","authors":["J Powell, K Sentz, E Moyer, M Klein - Code4Lib Journal, 2022"],"snippet":"… For many deep learning/NLP tasks, it is standard practice to download pre-trained models such as GoogleNews, Common Crawl, and wikipedia word embeddings models and use them for deep learning tasks. Since pretrained models are trained …","url":["https://journal.code4lib.org/articles/16718"]}
-{"year":"2022","title":"Technical Report on Web-based Visual Corpus Construction for Visual Document Understanding","authors":["D Kim, T Hong, M Yim, Y Kim, G Kim - arXiv preprint arXiv:2211.03256, 2022"],"snippet":"We present a dataset generator engine named Web-based Visual Corpus Builder (Webvicob). Webvicob can readily construct a large-scale visual corpus (ie, images with text annotations) from a raw Wikipedia HTML dump. In this report, we validate that …","url":["https://arxiv.org/pdf/2211.03256"]}
-{"year":"2022","title":"Technology behind text to image generators","authors":["P Fernandez - Library Hi Tech News, 2022"],"snippet":"… Common Crawl, which has petabytes of data taken by scraping websites. Copyright law in the USA can be frustratingly ambiguous, but factors in Common Crawl’s … In other words, Common Crawl creates large data sets used for …","url":["https://www.emerald.com/insight/content/doi/10.1108/LHTN-10-2022-0116/full/html"]}
-{"year":"2022","title":"Technology, Vintage-Specific Human Capital, and Labor Displacement: Evidence from Linking Patents with Occupations","authors":["L Kogan, D Papanikolaou, LDW Schmidt, B Seegmiller"],"snippet":"We develop a granular, occupation-specific measure of technological progress that relies only on textual descriptions of patent documents and the tasks performed by workers in an occupation. Our measure primarily identifies labor-saving innovations …","url":["https://www.bryanseegmiller.com/files/Draft_v2022-07.pdf"]}
-{"year":"2022","title":"Test collections for web-scale datasets using Dynamic Sampling","authors":["A Singh - 2022"],"snippet":"… Other large scale web collections, like the Common Crawl dataset, have also been used in various TREC tracks. It might be interesting to study the performance of Dynamic Sampling on these alternate datasets like Common Crawl1. Additionally, in …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/17889/Singh_Anmol.pdf?sequence=3"]}
-{"year":"2022","title":"TeSum: Human-Generated Abstractive Summarization Corpus for Telugu","authors":["A Urlana, N Surange, P Baswani, P Ravva…"],"snippet":"Expert human annotation for summarization is definitely an expensive task, and can not be done on huge scales. But with this work, we show that even with a crowd sourced summary generation approach, quality can be controlled by aggressive …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.614.pdf"]}
-{"year":"2022","title":"Text Algorithms in Economics","authors":["E Ash, S Hansen - 2022"],"snippet":"This paper provides an overview of the methods used for algorithmic text analysis in economics, with a focus on three key contributions. First, the paper introduces methods for representing documents as high-dimensional count vectors over …","url":["https://elliottash.com/wp-content/uploads/2022/08/annual_reviews_chapter-2022-08-16.pdf"]}
-{"year":"2022","title":"Text Analysis of Airline Tweets","authors":["E ALTamimi - 2022"],"snippet":"… For the FastText approach, we used gensim to load the vector file from the common crawl models downloaded from fasttext (FastText, 2020) and converted it to a bin model because the loading time of the vector was more. We then continued to …","url":["https://scholarworks.rit.edu/cgi/viewcontent.cgi?article=12309&context=theses"]}
-{"year":"2022","title":"Text Characterization Toolkit (TCT)","authors":["D Simig, T Wang, V Dankers, P Henderson, K Batsuren… - … of the 2nd Conference of the …, 2022"],"snippet":"We present a tool, Text Characterization Toolkit (TCT), that researchers can use to study characteristics of large datasets. Furthermore, such properties can lead to understanding the influence of such attributes on models’ behaviour. Traditionally, in …","url":["https://aclanthology.org/2022.aacl-demo.9.pdf"]}
-{"year":"2022","title":"Text Characterization Toolkit","authors":["D Simig, T Wang, V Dankers, P Henderson, K Batsuren… - arXiv preprint arXiv …, 2022"],"snippet":"In NLP, models are usually evaluated by reporting single-number performance scores on a number of readily available benchmarks, without much deeper analysis. Here, we argue that - especially given the well-known fact that benchmarks often …","url":["https://web7.arxiv.org/pdf/2210.01734"]}
-{"year":"2022","title":"Text Embeddings by Weakly-Supervised Contrastive Pre-training","authors":["L Wang, N Yang, X Huang, B Jiao, L Yang, D Jiang… - arXiv preprint arXiv …, 2022"],"snippet":"… data sources such as CommunityQA, Common Crawl and Scientific papers, and perform … Simple heuristic rules are applied to filter data from Reddit and Common Crawl. For example, … Reddit and Common Crawl. For more details and examples …","url":["https://arxiv.org/pdf/2212.03533"]}
-{"year":"2022","title":"Text Representations and Word Embeddings","authors":["R Egger - Applied Data Science in Tourism, 2022"],"snippet":"Today, a vast amount of unstructured text data is consistently at our disposal. Owing to the rapid increase in user-generated content on the one hand and powerful, ready-to-use machine learning algorithms on the other hand, automated text analysis can now be …","url":["https://link.springer.com/chapter/10.1007/978-3-030-88389-8_16"]}
-{"year":"2022","title":"Text to Image GANs with RoBERTa and Fine-grained Attention Networks","authors":["M Siddharth, R Aarthi"],"snippet":"… The additional data included CommonCrawl News dataset, Web text corpus and Stories from Common Crawl. The RoBERTa makes use of similar architecture as BERT Model but uses the byte-level BPE as the tokenizer [4]. The ’roberta-base’ is …","url":["https://www.researchgate.net/profile/Siddharth-M/publication/357450869_Text_to_Image_GANs_with_RoBERTa_and_Fine-grained_Attention_Networks/links/61d2bb43e669ee0f5c8185bb/Text-to-Image-GANs-with-RoBERTa-and-Fine-grained-Attention-Networks.pdf"]}
-{"year":"2022","title":"Text Vectorization Method Based on Concept Mining Using Clustering Techniques","authors":["A Mansour, J Mohammad, Y Kravchenko - 2022 VI International Conference on …, 2022"],"snippet":"… word vectors trained with sub-word information on Wikipedia 2017, UMBC webbase corpus, and statmt.org news data set (16B tokens); word2vec model2 which was trained with Google News corpus (3 billion words) and Glove model …","url":["https://ieeexplore.ieee.org/abstract/document/9782908/"]}
-{"year":"2022","title":"Text-to-Text Transfer Transformer Phrasing Model Using Enriched Text Input","authors":["M Řezáčková, J Matoušek - International Conference on Text, Speech, and …, 2022"],"snippet":"… In our experiments, we used the Text-to-Text Transfer Transformer (T5) model (following the architecture presented in [16, 25]) pre-trained from a huge amount of unlabeled text from the Czech CommonCrawl corpus [27]. For training the model itself, we used …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16270-1_32"]}
-{"year":"2022","title":"Textual Inference Identification in the Malayalam Language Using Convolutional Neural Network","authors":["S Renjit, SM Idicula - Advanced Computing and Intelligent Technologies, 2022"],"snippet":"… fastText [11] has a collection of pre-trained word vectors in 157 languages, where each language word collection is from Wikipedia and common crawl. Such collections provide a good start for language processing tasks in low-resource …","url":["https://link.springer.com/chapter/10.1007/978-981-19-2980-9_20"]}
-{"year":"2022","title":"The (Moral) Language of Hate","authors":["B Kennedy, P Golazizian, J Trager, M Atari, J Hoover… - 2022"],"snippet":"… In the present study, we extract the FastText embeddings — via the pre-trained set of embeddings10, which are trained on a combination of Wikipedia and Common Crawl data — of terms in the Weaponized Word lexicon, for the 19 …","url":["https://psyarxiv.com/eqp34/download?format=pdf"]}
-{"year":"2022","title":"THE ADVANCE TECHNIQUES USED IN CYBER SECURITY FOR PHISHING DETECTION","authors":["P Chate, MS Maske, MS Maske"],"snippet":"The Internet has become a necessary part of our lives; however, it has also provided opportunities to carry out malicious activities anonymously like Phishing. Phishers try to trick their victims through social engineering or create mock-up websites to …","url":["https://www.researchgate.net/profile/Parinita-Chate-2/publication/362539921_THE_ADVANCE_TECHNIQUES_USED_IN_CYBER_SECURITY_FOR_PHISHING_DETECTION/links/62efc6874532247693889dd0/THE-ADVANCE-TECHNIQUES-USED-IN-CYBER-SECURITY-FOR-PHISHING-DETECTION.pdf"]}
-{"year":"2022","title":"The AISP-SJTU Translation System for WMT 2022","authors":["G Liu, Q Zhu, X Chen, R Feng, J Ren, R Wu, Q Miao… - Proceedings of the Seventh …, 2022","GLQZX Chen, RFJRR Wu, QMRWK Yu"],"snippet":"… For monolingual data, we select data from News Crawl, Common Crawl and Extended Common Crawl, and the amount of data after pro… Crawl and Common Crawl. Then we used the JA-EN ensemble model to generate the hypotheses as the …","url":["https://aclanthology.org/2022.wmt-1.24.pdf","https://www.statmt.org/wmt22/pdf/2022.wmt-1.24.pdf"]}
-{"year":"2022","title":"The case for 4-bit precision: k-bit Inference Scaling Laws","authors":["T Dettmers, L Zettlemoyer - arXiv preprint arXiv:2212.09720, 2022"],"snippet":"… Furthermore, we find that across more than 35,000 zero-shot experiments, the Pearson correlation coefficient between The Pile Common Crawl perplexity and zero-shot performance is -0.94. … In this section, we present data for evaluation on The Pile …","url":["https://arxiv.org/pdf/2212.09720"]}
-{"year":"2022","title":"The Causal News Corpus: Annotating Causal Relations in Event Sentences from News","authors":["FA Tan, A Hürriyetoğlu, T Caselli, N Oostdijk, T Nomoto… - arXiv preprint arXiv …, 2022"],"snippet":"Despite the importance of understanding causality, corpora addressing causal relations are limited. There is a discrepancy between existing annotation guidelines of event causality and conventional causality corpora that focus more on linguistics …","url":["https://arxiv.org/pdf/2204.11714"]}
-{"year":"2022","title":"The Curious Case of Control","authors":["E Stengel-Eskin, B Van Durme - arXiv preprint arXiv:2205.12113, 2022"],"snippet":"… The training data is based on Common Crawl, though similarly to GPT-3 Davinci, the details of the training data filtering process are unclear. Relevant differences to GPT-3 are in the tokenization (which includes multi-word expressions) and use of …","url":["https://arxiv.org/pdf/2205.12113"]}
-{"year":"2022","title":"The Dark Side of the Language: Pre-trained Transformers in the DarkNet","authors":["L Ranaldi, A Nourbakhsh, A Patrizi, ES Ruzzetti… - arXiv preprint arXiv …, 2022"],"snippet":"Pre-trained Transformers are challenging human performances in many natural language processing tasks. The gigantic datasets used for pre-training seem to be the key for their success on existing tasks. In this paper, we explore how a range of …","url":["https://arxiv.org/pdf/2201.05613"]}
-{"year":"2022","title":"The Effect of Pre-trained Language Models on Critical Case Detection from Radiology Reports","authors":["G BAYRAK, MS TOPRAK, MC GANIZ, H KODAZ…"],"snippet":"… As the embedding layer of the bi-LSTM we use following alternatives: 1) fastText pre-trained model for Turkish on common crawl 3 2) fastText model trained from scratch using our unsupervised dataset of 190 thousand radiology reports 3) BERT …","url":["https://www.researchgate.net/profile/Murat-Ganiz/publication/363413813_The_Effect_of_Pre-trained_Language_Models_on_Critical_Case_Detection_from_Radiology_Reports/links/631b4ce8873eca0c007514fd/The-Effect-of-Pre-trained-Language-Models-on-Critical-Case-Detection-from-Radiology-Reports.pdf"]}
-{"year":"2022","title":"The emergence of gender associations in child language development","authors":["B Prystawski, E Grant, A Nematzadeh, SWS Lee…"],"snippet":"Gender associations have been a long-standing research topic in psychological and social sciences. Although it is known that children learn aspects of gender association at a young age, it is not well understood how they might emerge through …","url":["https://www.researchgate.net/profile/Yang-Xu-34/publication/360554719_The_emergence_of_gender_associations_in_child_language_development/links/627d55beb1ad9f66c8b8563c/The-emergence-of-gender-associations-in-child-language-development.pdf"]}
-{"year":"2022","title":"The fujitsu dmath submissions for wmt21 news translation and biomedical translation tasks","authors":["A Martínez - Proceedings of the Sixth Conference on Machine …, 2021"],"snippet":"… For example, we noted that the Hausa Extended Common Crawl corpus published for WMT21 contained a large number of Japanese … Despite its noisy nature, we decided to use the Extended Common Crawl Hausa corpus. The results …","url":["https://aclanthology.org/2021.wmt-1.13.pdf"]}
-{"year":"2022","title":"The Ghost in the Machine has an American accent: value conflict in GPT-3","authors":["RL Johnson, G Pistilli, N Menédez-González… - arXiv preprint arXiv …, 2022"],"snippet":"The alignment problem in the context of large language models must consider the plurality of human values in our world. Whilst there are many resonant and overlapping values amongst the world's cultures, there are also many conflicting, yet …","url":["https://arxiv.org/pdf/2203.07785"]}
-{"year":"2022","title":"The hitchhiker's guide Method handbook for quantification of online lin-guistic data in a country-specific context Official research report, Linguistic Explorations of …","authors":["J Andersson Schwarz - 2022"],"snippet":"… A very significant non-profit provider to consider alongside these commercial actors is CommonCrawl (USA). As for CrowdTangle and DataSift… The CommonCrawl corpus contains petabytes of data including raw web page data …","url":["https://gupea.ub.gu.se/bitstream/handle/2077/70890/2022_1_Andersson%20Schwarz.pdf?sequence=1"]}
-{"year":"2022","title":"The hitchhiker's guide to web-mediated text. Method handbook for quantification of online linguistic data in a country-specific context. Official research report …","authors":["J Andersson Schwarz - 2022"],"snippet":"… While a data provider could be any entity, also nonprofit or government-funded ones (CommonCrawl is one such example, described in more detail below), a vendor is typically a company operating in sectors like market intelligence, social …","url":["https://gupea.ub.gu.se/bitstream/handle/2077/70866/2022_1_Andersson%20Schwarz.pdf?sequence=1"]}
-{"year":"2022","title":"The IARPA BETTER Program Abstract Task Four New Semantically Annotated Corpora from IARPA's BETTER Program","authors":["C Rubino, T McKinnon"],"snippet":"… In Phase I, sentences were randomly chosen from newswire texts in the target languages harvested from the Common Crawl. An Amazon Mechanical Turk pipeline was set up to confirm the suitability of the extracted sentences according to …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.384.pdf"]}
-{"year":"2022","title":"THE IMPACT OF ONLINE AFFILIATE MARKETING ON WEB SEARCH","authors":["J Bevendorff, M Wiegmann, M Potthast, B Stein"],"snippet":"… Based on several pageand domain-level text quality features, which we calculated at scale on four different Common Crawl versions, we … number of pages crawled from domains that fall into the “affiliate spam” genre might improve the quality of …","url":["https://webis.de/downloads/publications/papers/bevendorff_2022c.pdf"]}
-{"year":"2022","title":"The Increasing Frequency of Terms Denoting Political Extremism in US and UK News Media","authors":["D Rozado, E Kaufmann - Social Sciences, 2022"],"snippet":"The term political extremism is commonly used to refer to political attitudes considered to be outside the ideological mainstream. This study leverages computational content analysis of big data to longitudinally examine (1970–2019) …","url":["https://www.mdpi.com/2076-0760/11/4/167/pdf"]}
-{"year":"2022","title":"The Indeterminate Self and Large Language Models: A Nietzschean Critique of GPT-3","authors":["S Fischer - 2022"],"snippet":"… For GPT-3, the largest part of the training data (60%) comes from the web scraping repository Common Crawl12 (Brown et al., 2020, p. 9). The exact sources of the Common Crawl data set are not disclosed, and given the sheer amount it is …","url":["http://essay.utwente.nl/89754/1/Fischer_MA_BMS.pdf"]}
-{"year":"2022","title":"The Infinite Index: Information Retrieval on Generative Text-To-Image Models","authors":["N Deckers, M Fröbe, J Kiesel, G Pandolfo, C Schröder… - arXiv preprint arXiv …, 2022"],"snippet":"The text-to-image model Stable Diffusion has recently become very popular. Only weeks after its open source release, millions are experimenting with image generation. This is due to its ease of use, since all it takes is a brief description of the …","url":["https://arxiv.org/pdf/2212.07476"]}
-{"year":"2022","title":"The language of opinion change on social media under the lens of communicative action","authors":["C Monti, LM Aiello, G De Francisci Morales, F Bonchi - Scientific Reports, 2022"],"snippet":"Which messages are more effective at inducing a change of opinion in the listener? We approach this question within the frame of Habermas’ theory of communicative action, which posits that the illocutionary intent of the message (its pragmatic …","url":["https://www.nature.com/articles/s41598-022-21720-4"]}
-{"year":"2022","title":"The Minimum Wage as an Anchor: Effects on Determinations of Fairness by Humans and AI","authors":["DG Soatto - arXiv preprint arXiv:2210.10585, 2022"],"snippet":"I study the role of the minimum wage as an anchor for perceptions of the fairness of wages by both human subjects and AI. Through surveys on human subjects enrolled in the crowdsourcing platform Prolific.co and queries submitted to the large …","url":["https://arxiv.org/pdf/2210.10585"]}
-{"year":"2022","title":"The mininglamp machine translation system for wmt21","authors":["S Zhao, X Li, M Wu, J Hao - Proceedings of the Sixth Conference on Machine …, 2021"],"snippet":"This paper describes Mininglamp neural machine translation systems of the WMT2021 news translation tasks. We have participated in eight directions translation tasks for news text including Chinese to/from English, Hausa to/from …","url":["https://aclanthology.org/2021.wmt-1.25.pdf"]}
-{"year":"2022","title":"The MORAL INTEGRITY CORPUS: A Benchmark for Ethical Dialogue Systems","authors":["C Ziems, AY Jane, YC Wang, A Halevy, D Yang"],"snippet":"Conversational agents have come increasingly closer to human competence in open-domain dialogue settings; however, such models often reflect insensitive, hurtful, or entirely incoherent viewpoints that erode a user’s trust in the moral integrity of the system …","url":["https://faculty.cc.gatech.edu/~dyang888/docs/acl22_moral.pdf"]}
-{"year":"2022","title":"The multiplex relations between cities: a lexicon-based approach to detect urban systems","authors":["W Tongjing, E Meijers, H Wang - Regional Studies, 2022"],"snippet":"… Common Crawl is one of the largest publicly available web archives, a … the Common Crawl web archive as our preliminary data source to avoid selection bias. We extracted a 139 Gigabyte text corpus containing 91 million Chinese webpages …","url":["https://www.tandfonline.com/doi/pdf/10.1080/00343404.2022.2120978"]}
-{"year":"2022","title":"The NiuTrans Machine Translation Systems for WMT22","authors":["W Shan, Z Cao, Y Han, S Wu, Y Hu, T Xiao, A Ma…"],"snippet":"This paper describes the NiuTrans neural machine translation systems of the WMT22 General MT constrained task. We participate in four directions, including Chinese→ English, English→ Croatian, and Livonian↔ English. Our models are …","url":["https://www.statmt.org/wmt22/pdf/2022.wmt-1.32.pdf"]}
-{"year":"2022","title":"The Norwegian Colossal Corpus: A Text Corpus for Training Large Norwegian Language Models","authors":["PE Kummervold, F Wetjen, J de la Rosa"],"snippet":"Norwegian has been one of many languages lacking sufficient available text to train quality language models. In an attempt to bridge this gap, we introduce the Norwegian Colossal Corpus (NCC), which comprises 49GB of clean Norwegian …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.410.pdf"]}
-{"year":"2022","title":"The only chance to understand: machine translation of the severely endangered low-resource languages of Eurasia","authors":["A Mossolova, K Smaïli - The Fifth Workshop on Technologies for Machine …, 2022"],"snippet":"Numerous machine translation systems have been proposed since the appearance of this task. Nowadays, new large language modelbased algorithms show results that sometimes overcome human ones on the rich-resource languages …","url":["https://hal.archives-ouvertes.fr/hal-03774644/file/final_loresmt_paper.pdf"]}
-{"year":"2022","title":"The Problem with XSD Binary Floating Point Datatypes in RDF","authors":["JM Keil, M Gänßinger"],"snippet":"… in the September 2020 Common Crawl archive,13 a freely available web crawl archive. We selected it because of its large size, an expected large proportion of literals, the uniform access of the whole corpus, its heterogeneous original sources (15e6domains) …","url":["https://2022.eswc-conferences.org/wp-content/uploads/2022/05/paper_98_Keil_et_al.pdf"]}
-{"year":"2022","title":"The Role of negative information when learning dense word vectors","authors":["AT Salle - 2021"],"snippet":"… Figure 1.1 shows a 2-dimensional PCA projection of a set of words vectors drawn from our LexVec Common Crawl vectors (the LexVec model is presented in Chapter 3), illustrating how a vector space model represents meaning. Words that are …","url":["https://www.lume.ufrgs.br/bitstream/handle/10183/234537/001136324.pdf?sequence=1"]}
-{"year":"2022","title":"The semantics of-ee and-ation: a distributional semantic approach","authors":["V Schneider"],"snippet":"… Common Crawl subword model • 2 million pre-trained word vectors • Contains subword information to create new vectors based on …","url":["https://viktoria-schneider.phil.hhu.de/wp-content/uploads/2022/11/Ingo-Birthday-22-09-01.pdf"]}
-{"year":"2022","title":"The Seventh Workshop on Search-Oriented Conversational Artificial Intelligence (SCAI'22)","authors":["G Penha, S Vakulenko, O Dusek, L Clark, V Pal… - Proceedings of the 45th …, 2022"],"snippet":"… The two datasets also differ with respect to the information source — QReCC has a larger and more diverse collection of 54M passages based on Commoncrawl, whereas TopiOCQA has 26M passages based on Wikipedia. While the corpus of …","url":["https://dl.acm.org/doi/pdf/10.1145/3477495.3531700"]}
-{"year":"2022","title":"The sins of the parents are to be laid upon the children: biased humans, biased data, biased models","authors":["M Osborne, A Omrani, M Dehghani - 2022"],"snippet":"Technological innovations have become a key driver of societal advancements. Nowhere is this more evident than in the field of machine learning (ML), which has developed algorithmic models that shape our decisions, behaviors, and outcomes …","url":["https://psyarxiv.com/4eqnk/download?format=pdf"]}
-{"year":"2022","title":"The State of Profanity Obfuscation in Natural Language Processing","authors":["D Nozza, D Hovy - arXiv preprint arXiv:2210.07595, 2022"],"snippet":"Work on hate speech has made the consideration of rude and harmful examples in scientific publications inevitable. This raises various problems, such as whether or not to obscure profanities. While science must accurately disclose what it does, the …","url":["https://arxiv.org/pdf/2210.07595"]}
-{"year":"2022","title":"The UMD Neural Machine Translation Systems at WMT17 Bandit Learning Task","authors":["ASSFK Nguyen, KBH Daumé III"],"snippet":"We describe the University of Maryland machine translation systems submitted to the WMT17 German-English Bandit Learning Task. The task is to adapt a translation system to a new domain, using only bandit feedback: the system receives a German …","url":["https://ar5iv.labs.arxiv.org/html/1708.01318"]}
-{"year":"2022","title":"The usefulness of NLP techniques for predicting peaks in firefighter interventions due to rare events","authors":["S Cerna, C Guyeux, D Laiymani - Neural Computing and Applications, 2022"],"snippet":"… This is mainly because the LSTM and CNN models were trained only with the vocabulary of the bulletins while the transformers were pre-trained with an extensive vocabulary of the French language (Common Crawl Oscar corpus). Thus, this set of …","url":["https://link.springer.com/article/10.1007/s00521-022-06996-x"]}
-{"year":"2022","title":"The VolcTrans System for WMT22 Multilingual Machine Translation Task","authors":["X Qian, K Hu, J Wang, Y Liu, X Pan, J Cao, M Wang - arXiv preprint arXiv:2210.11599, 2022"],"snippet":"This report describes our VolcTrans system for the WMT22 shared task on large-scale multilingual machine translation. We participated in the unconstrained track which allows the use of external resources. Our system is a transformerbased multilingual …","url":["https://arxiv.org/pdf/2210.11599"]}
-{"year":"2022","title":"The YiTrans End-to-End Speech Translation System for IWSLT 2022 Offline Shared Task","authors":["Z Zhang, J Ao - IWSLT 2022, 2022"],"snippet":"This paper describes the submission of our end-to-end YiTrans speech translation system for the IWSLT 2022 offline task, which translates from English audio to German, Chinese, and Japanese. The YiTrans system is built on large-scale pre-trained …","url":["https://aclanthology.org/2022.iwslt-1.pdf#page=168"]}
-{"year":"2022","title":"ThEconSum: an Economics-domained Dataset for Thai Text Summarization and Baseline Models","authors":["S Jumpathong, A Takhom, P Boonkwan… - 2022 17th International Joint …, 2022"],"snippet":"Language resources as datasets are an essential component in developing an effective automatic text summarization (ATS) system. Some public datasets are relatively uncommon when compared with popular languages, due to the complexity …","url":["https://ieeexplore.ieee.org/abstract/document/9960271/"]}
-{"year":"2022","title":"Thirumurai: A Large Dataset of Tamil Shaivite Poems and Classification of Tamil Pann","authors":["S Mahadevan, R Ponnusamy, PK Kumaresan…"],"snippet":"… Such models are trained on petabytes of data, such as the Common Crawl data, which has over 12 years of internet data. Due to the size of the data they are being trained on, this not only improves the accuracy of the models, but it also allows them …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.704.pdf"]}
-{"year":"2022","title":"Three-order normalized PMI and other lessons in tensor analysis of verbal selectional preferences","authors":["M Makrai"],"snippet":"We investigate several questions in transitive verb structure representation by decomposing tensors populated with different subject-verb-object association measures, including a novel generalization of normalized pointwise mutual …","url":["https://hlt.bme.hu/media/pdf/verbtensor_guxggK5.pdf"]}
-{"year":"2022","title":"TL; DR: Mining Reddit to Learn Automatic Summarization","authors":["R Logan"],"snippet":"Recent advances in automatic text summarization have used deep neural networks to generate high-quality abstractive summaries, but the performance of these models strongly depends on large amounts of suitable training data. We propose a …","url":["https://zdoc.pub/tldr-mining-reddit-to-learn-automatic-summarization.html"]}
-{"year":"2022","title":"To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering","authors":["D Dua, E Strubell, S Singh, P Verga - arXiv preprint arXiv:2212.10381, 2022"],"snippet":"… To understand the impact of the pre-trainining vs fine-tuning corpus, we also compare the performance of the FiD reader initialized from T5 pretrained on common-crawl dataset(C4) compared to one that was pre-trained on pubmed articles. After …","url":["https://arxiv.org/pdf/2212.10381"]}
-{"year":"2022","title":"Topic Classification in Indonesian-language Tweets using Fast-Text Feature Expansion with Support Vector Machine (SVM)","authors":["IM Fadhil, Y Sibaroni - 2022 International Conference on Data Science and Its …, 2022"],"snippet":"… The word vector used in this study uses a pretrained Indonesian word vector that can be used from research [7] where the corpus used to train the model comes from Wikipedia and Common Crawl with the number of words contained in the word …","url":["https://ieeexplore.ieee.org/abstract/document/9862899/"]}
-{"year":"2022","title":"Towards a Cleaner Document-Oriented Multilingual Crawled Corpus","authors":["J Abadji, PO Suarez, L Romary, B Sagot - arXiv preprint arXiv:2201.06642, 2022"],"snippet":"… Table 1: Comparison of occurrences of news-related terms between OSCAR and our corpus in a sample of 100 CommonCrawl shards. *: For the Burmese language, we use the whole 21.09 and 22.XX corpus since it is a low resource language …","url":["https://arxiv.org/pdf/2201.06642"]}
-{"year":"2022","title":"Towards Analyzing the Bias of News Recommender Systems Using Sentiment and Stance Detection","authors":["M Alam, A Iana, A Grote, K Ludwig, P Müller… - arXiv preprint arXiv …, 2022"],"snippet":"… More specifically, we use a pre-trained German word2vec model trained on the Common Crawl and Wikipedia dataset [12] to learn latent representations of the words in an article. The article’s vector representation is computed as the average of …","url":["https://arxiv.org/pdf/2203.05824"]}
-{"year":"2022","title":"Towards Arabic Sentence Simplification via Classification and Generative Approaches","authors":["N Khallaf, S Sharoff - arXiv preprint arXiv:2204.09292, 2022"],"snippet":"This paper presents an attempt to build a Modern Standard Arabic (MSA) sentence-level simplification system. We experimented with sentence simplification using two approaches: (i) a classification approach leading to lexical simplification pipelines …","url":["https://arxiv.org/pdf/2204.09292"]}
-{"year":"2022","title":"Towards Automatic Generation of Messages Countering Online Hate Speech and Microaggressions","authors":["M Ashida, M Komachi - Proceedings of the Sixth Workshop on Online Abuse …, 2022"],"snippet":"With the widespread use of social media, online hate is increasing, and microaggressions are receiving attention. We explore the potential for using pretrained language models to automatically generate messages that combat the …","url":["https://aclanthology.org/2022.woah-1.2.pdf"]}
-{"year":"2022","title":"Towards automatic generation of Piping and Instrumentation Diagrams (P&IDs) with Artificial Intelligence","authors":["E Hirtreiter, LS Balhorn, AM Schweidtmann - arXiv preprint arXiv:2211.05583, 2022"],"snippet":"Developing Piping and Instrumentation Diagrams (P&IDs) is a crucial step during the development of chemical processes. Currently, this is a tedious, manual, and time-consuming task. We propose a novel, completely data-driven method for the …","url":["https://arxiv.org/pdf/2211.05583"]}
-{"year":"2022","title":"Towards better structured and less noisy Web data: Oscar with Register annotations","authors":["V Laippala, A Salmela, S Rönnqvist, AF Aji, LH Chang… - Proceedings of the Eighth …, 2022"],"snippet":"… The documents for the annotation were randomly sampled from a recent Common Crawl2 dataset. The annotation was done using a custom … The documents were retrieved from Common Crawl using the same pipeline as the …","url":["https://aclanthology.org/2022.wnut-1.23.pdf"]}
-{"year":"2022","title":"Towards Controllable Protein design with Conditional Transformers","authors":["N Ferruz, B Höcker - arXiv preprint arXiv:2201.07338, 2022"],"snippet":"The 21st century is presenting humankind with unprecedented environmental and medical challenges. The ability to design novel proteins tailored for specific purposes could transform our ability to respond timely to these issues. Recent …","url":["https://arxiv.org/pdf/2201.07338"]}
-{"year":"2022","title":"Towards fairness AI: A data-centric approach","authors":["U Ojha - 2022"],"snippet":"Title: Towards fairness AI: A data-centric approach Subtitle: Assessment and mitigation techniques to tackle bias in datasets The consequences of bias and injustice have received more attention, even though AI is increasingly employed in …","url":["https://webthesis.biblio.polito.it/secure/24666/1/tesi.pdf"]}
-{"year":"2022","title":"Towards Fine (r)-grained Identification of Event Coreference Resolution Types","authors":["L De Langhe, O De Clercq, V Hoste - Computational Linguistics in the Netherlands …, 2022"],"snippet":"… RobBERT on the other hand was pretrained on 6.6B tokens of Commoncrawl webdata (Suárez et al. 2019). Since the Commoncrawl data consists of individual lines and not every line contains more than one sentence, we anticipate that this …","url":["https://www.clinjournal.org/clinj/article/download/154/162"]}
-{"year":"2022","title":"Towards Latvian WordNet","authors":["P Paikens, M Grasmanis, A Klints, I Lokmane…"],"snippet":"In this paper we describe our current work on creating a WordNet for Latvian based on the principles of the Princeton WordNet. The chosen methodology for word sense definition and sense linking is based on corpus evidence and the existing Tezaurs …","url":["https://wordnet.ailab.lv/data/documents/2022/LREC_WordNet.pdf"]}
-{"year":"2022","title":"Towards Lithuanian grammatical error correction","authors":["L Stankevičius, M Lukoševičius - arXiv preprint arXiv:2203.09963, 2022"],"snippet":"Everyone wants to write beautiful and correct text, yet the lack of language skills, experience, or hasty typing can result in errors. By employing the recent advances in transformer architectures, we construct a grammatical error correction model for …","url":["https://arxiv.org/pdf/2203.09963"]}
-{"year":"2022","title":"Towards Multi-Lingual Visual Question Answering","authors":["S Changpinyo, L Xue, I Szpektor, AV Thapliyal… - arXiv preprint arXiv …, 2022"],"snippet":"Visual Question Answering (VQA) has been primarily studied through the lens of the English language. Yet, tackling VQA in other languages in the same manner would require considerable amount of resources. In this paper, we propose scalable …","url":["https://arxiv.org/pdf/2209.05401"]}
-{"year":"2022","title":"Towards Performance of NLP Transformers on URL-Based Phishing Detection for Mobile Devices","authors":["H Shirazia, K Haynesb, I Raya - 2022"],"snippet":"… , and the legitimate webpage sources are Alexa and CommonCrawl.org. In 2020, Shirazi et al. … .com and 10,955 legitimate URLs from CommonCrawl.org. The phishing URLs include sites … Since the CommonCrawl.org corpus contains …","url":["https://iasks.org/articles/juspn-v17-i1-pp-35-42.pdf"]}
-{"year":"2022","title":"Towards Simple and Efficient Task-Adaptive Pre-training for Text Classification","authors":["A Ladkat, A Miyajiwala, S Jagadale, R Kulkarni… - arXiv preprint arXiv …, 2022"],"snippet":"Language models are pre-trained using large corpora of generic data like book corpus, common crawl and Wikipedia, which is essential for the model to understand the linguistic characteristics of the language. New studies suggest using Domain …","url":["https://arxiv.org/pdf/2209.12943"]}
-{"year":"2022","title":"Towards the Next 1000 Languages in Multilingual Machine Translation: Exploring the Synergy Between Supervised and Self-Supervised Learning","authors":["A Siddhant, A Bapna, O Firat, Y Cao, MX Chen… - arXiv preprint arXiv …, 2022"],"snippet":"Achieving universal translation between all human language pairs is the holy-grail of machine translation (MT) research. While recent progress in massively multilingual MT is one step closer to reaching this goal, it is becoming evident that …","url":["https://arxiv.org/pdf/2201.03110"]}
-{"year":"2022","title":"Towards Trustworthy AutoGrading of Short, Multi-lingual, Multi-type Answers","authors":["J Schneider, R Richner, M Riser"],"snippet":"Autograding short textual answers has become much more feasible due to the rise of NLP and the increased availability of question-answer pairs brought about by a shift to online education. Autograding performance is still inferior to human grading …","url":["https://www.researchgate.net/profile/Johannes-Schneider-5/publication/357514804_Towards_Trustworthy_AutoGrading_of_Short_Multi-lingual_Multi-type_Answers/links/61d19825b6b5667157c0640f/Towards-Trustworthy-AutoGrading-of-Short-Multi-lingual-Multi-type-Answers.pdf"]}
-{"year":"2022","title":"Towards Understanding and Practices of Ethical Artificial Intelligence","authors":["J Chi - 2022"],"snippet":"The successes of machine learning (ML) and artificial intelligence (AI) models encourage their widespread deployments in high-stakes domains--from public transportation to social decision-making such as autonomous driving, criminal justice …","url":["https://search.proquest.com/openview/10119af5960676393b0db80567014b74/1.pdf?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2022","title":"Toxicity Detection for Indic Multilingual Social Media Content","authors":["M Jhaveri, D Ramaiya, HS Chadha - arXiv preprint arXiv:2201.00598, 2022"],"snippet":"… • XLM-RoBERTa - It is a transformer-based masked language model trained on 100 languages, using more than two terabytes of filtered CommonCrawl data. [3] • MuRIL - A multilingual language model specifically built for Indic languages trained …","url":["https://arxiv.org/pdf/2201.00598"]}
-{"year":"2022","title":"Toxicity detection in online Georgian discussions","authors":["N Lashkarashvili, M Tsintsadze - … Journal of Information Management Data Insights, 2022"],"snippet":"… They trained models using Wikipedia and Common Crawl dataset. They used character n-grams with a size equal to 5 and the dimension of embeddings was set to 300. We found that 8,385, about 1 / 4 of the total of 38,733 raw unique words were …","url":["https://www.sciencedirect.com/science/article/pii/S2667096822000064"]}
-{"year":"2022","title":"Tradeoff Options for Bipartite Graph Partitioning","authors":["J Mackenzie, M Petri, A Moffat - IEEE Transactions on Knowledge and Data …, 2022","JMMPA Moffat"],"snippet":"… CC-News-En: A snapshot of English news documents from the Common Crawl between 2016 and 2018 [32]. As was also the case with other work on reordering of inverted indexes, short postings lists (fewer than 4096 elements) and long postings …","url":["https://ieeexplore.ieee.org/abstract/document/9900428/","https://jmmackenzie.io/pdf/mpm22-tkde.pdf"]}
-{"year":"2022","title":"Traditional Machine Learning and Deep Learning-based Text Classification for Turkish Law Documents using Transformers and Domain Adaptation","authors":["O Akça, G Bayrak, AM Issifu, MC Ganіz - … on INnovations in Intelligent SysTems and …, 2022"],"snippet":"… We use their models which are pre-trained on a general common crawl corpus in Turkish. We than fine-tune this general domain model using our corpus that consists of a collection of Turkish legal texts to leverage the power of transfer learning. For …","url":["https://ieeexplore.ieee.org/abstract/document/9894051/"]}
-{"year":"2022","title":"Trainability and real-world knowledge","authors":["A Kornai - Vector Semantics, 2023"],"snippet":"Until this point, we concentrated on the lexicon, conceived of as the repository of shared linguistic information. In 8.1 we take on the problem of integrating real-world knowledge, nowadays typically stored in knowledge graphs as billions of RDF triples …","url":["https://link.springer.com/content/pdf/10.1007/978-981-19-5607-2_8.pdf"]}
-{"year":"2022","title":"Training a Deep Contextualized Language Model for International Classification of Diseases, 10th Revision Classification via Federated Learning: Model …","authors":["PF Chen, TL He, SC Lin, YC Chu, CT Kuo, F Lai… - JMIR Medical Informatics, 2022"],"snippet":"Background: The automatic coding of clinical text documents by using the International Classification of Diseases, 10th Revision (ICD-10) can be performed for statistical analyses and reimbursements. With the development of natural …","url":["https://medinform.jmir.org/2022/11/e41342/"]}
-{"year":"2022","title":"Training a T5 Using Lab-sized Resources","authors":["MR Ciosici, L Derczynski - arXiv preprint arXiv:2208.12097, 2022"],"snippet":"Training large neural language models on large datasets is resourceand time-intensive. These requirements create a barrier to entry, where those with fewer resources cannot build competitive models. This paper presents various techniques for making …","url":["https://arxiv.org/pdf/2208.12097"]}
-{"year":"2022","title":"Training language models for deeper understanding improves brain alignment","authors":["KL Aw, M Toneva - arXiv preprint arXiv:2212.10898, 2022"],"snippet":"… sentences on the C4 dataset, a collection of roughly 750 GB of English texts sourced from the public Common Crawl open repository. … , a collection of roughly 750 GB of English texts sourced from the public Common Crawl open repository …","url":["https://arxiv.org/pdf/2212.10898"]}
-{"year":"2022","title":"TRANS-KBLSTM: An External Knowledge Enhanced Transformer BiLSTM model for Tabular Reasoning","authors":["Y Varun, A Sharma, V Gupta"],"snippet":"Natural language inference on tabular data is a challenging task. Existing approaches lack the world and common sense knowledge required to perform at a human level. While massive amounts of KG data exist, approaches to integrate them …","url":["https://vgupta123.github.io/docs/TransKBLSTM.pdf"]}
-{"year":"2022","title":"Transcormer: Transformer for Sentence Scoring with Sliding Language Modeling","authors":["K Song, Y Leng, X Tan, Y Zou, T Qin, D Li - arXiv preprint arXiv:2205.12986, 2022"],"snippet":"… WMT14 English-German comprises 4.5M bilingual data collected from Europarl v7, Common Crawl corpus and News Commentary. We concatenate newstest2012 and newstest2013 as the valid set, and choose newstest2014 as the test set for WMT14 …","url":["https://arxiv.org/pdf/2205.12986"]}
-{"year":"2022","title":"Transfer Effects in Scandinavian Languages","authors":["A Fredriksen - 2022"],"snippet":"The field of natural language processing with machine learning has gone through a quantum leap in the past decade. Giants like Google and Amazon have paved the way for powerful models trained on a vast amount of data. Even though the …","url":["https://www.duo.uio.no/bitstream/handle/10852/97679/1/AnetteFredriksenThesis.pdf"]}
-{"year":"2022","title":"Transfer language selection for zero-shot cross-lingual abusive language detection","authors":["J Eronen, M Ptaszynski, F Masui, M Arata, G Leliwa… - Information Processing & …, 2022"],"snippet":"We study the selection of transfer languages for automatic abusive language detection. Instead of preparing a dataset for every language, we demonstrate the effectiveness of cross-lingual transfer learning for zero-shot abusive language …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322000978"]}
-{"year":"2022","title":"Transfer Learning Approach to Prediction of Rate of Penetration in Drilling","authors":["A Ambrus, T Wiktorski","FJ Pacis, S Alyaev, A Ambrus, T Wiktorski - International Conference on …, 2022"],"snippet":"The rate of penetration (ROP) is a key performance indicator in the oil and gas drilling industry as it directly translates to cost savings and emission reductions. A prerequisite for a drilling optimization algorithm is a predictive model that provides …","url":["https://link.springer.com/chapter/10.1007/978-3-031-08754-7_44","https://www.iccs-meeting.org/archive/iccs2022/papers/133510330.pdf"]}
-{"year":"2022","title":"Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models","authors":["S Nair, E Yang, D Lawrie, K Duh, P McNamee… - arXiv preprint arXiv …, 2022"],"snippet":"… We also conducted experiments using the new CLIR Common Crawl Collection (HC4) [14], where the documents are newswire articles from Common Crawl in Chinese or Persian. Throughout, English queries are used to search a collection in a non-English …","url":["https://arxiv.org/pdf/2201.08471"]}
-{"year":"2022","title":"Transfer Learning for Automatic Sexism Detection with Multilingual Transformer Models","authors":["D Liakhovets, M Schütz, J Böck, M Andresel… - 2022"],"snippet":"… • XLM-R is also a multilingual model and, similarly to mBERT, is trained on 100 languages with a dataset containing CommonCrawl data. The architecture consists of a combination of the XLM [24] and RoBERTa [25] transformer models. The latter is …","url":["http://ceur-ws.org/Vol-3202/exist-paper1.pdf"]}
-{"year":"2022","title":"Transfer Learning in Natural Language Processing through Interactive Feedback","authors":["M Yuan - 2022"],"snippet":"Machine learning models cannot easily adapt to new domains and applications. This drawback becomes detrimental for natural language processing (NLP) because language is perpetually changing. Across disciplines and languages, there are …","url":["https://drum.lib.umd.edu/bitstream/handle/1903/29333/Yuan_umd_0117E_22783.pdf?sequence=2"]}
-{"year":"2022","title":"Transfer Learning of Transformers for Spoken Language Understanding","authors":["J Švec, A Frémund, M Bulín, J Lehečka - … Conference on Text, Speech, and Dialogue, 2022"],"snippet":"… For the Czech language, we have collected the CommonCrawl corpus at the end of August 2020. It contains 47.9 GB of clean text, 20.5 M unique URLs and 6.7 B running words. The Czech T5 training procedure followed the original procedure …","url":["https://link.springer.com/chapter/10.1007/978-3-031-16270-1_40"]}
-{"year":"2022","title":"Transformer Language Models without Positional Encodings Still Learn Positional Information","authors":["A Haviv, O Ram, O Press, P Izsak, O Levy - arXiv preprint arXiv:2203.16634, 2022"],"snippet":"Transformers typically require some form of positional encoding, such as positional embeddings, to process natural language sequences. Surprisingly, we find that transformer language models without any explicit positional encoding are still …","url":["https://arxiv.org/pdf/2203.16634"]}
-{"year":"2022","title":"Transformer models used for text-based question answering systems","authors":["K Nassiri, M Akhloufi - Applied Intelligence, 2022"],"snippet":"The question answering system is frequently applied in the area of natural language processing (NLP) because of the wide variety of applications. It consists of answering questions using natural language. The problem is, in general, solved by …","url":["https://link.springer.com/article/10.1007/s10489-022-04052-8"]}
-{"year":"2022","title":"Transformer-Based Abstractive Summarization for Reddit and Twitter: Single Posts vs. Comment Pools in Three Languages","authors":["IS Blekanov, N Tarasov, SS Bodrunova - Future Internet, 2022"],"snippet":"… One of the major contributions of the T5 model’s authors was the process of collecting and preprocessing data based on the CommonCrawl initial dataset. As a result of multiple steps of processing, including duplicate, stopwords, and special …","url":["https://www.mdpi.com/1999-5903/14/3/69/pdf"]}
-{"year":"2022","title":"Translation between Molecules and Natural Language","authors":["C Edwards, T Lai, K Ros, G Honke, H Ji - arXiv preprint arXiv:2204.11817, 2022"],"snippet":"Joint representations between images and text have been deeply investigated in the literature. In computer vision, the benefits of incorporating natural language have become clear for enabling semantic-level control of images. In this work, we present …","url":["https://arxiv.org/pdf/2204.11817"]}
-{"year":"2022","title":"Tree-based Search Graph for Approximate Nearest Neighbor Search","authors":["X Fan, X Wang, K Lu, L Xue, J Zhao - arXiv preprint arXiv:2201.03237, 2022"],"snippet":"Nearest neighbor search supports important applications in many domains, such as database, machine learning, computer vision. Since the computational cost for accurate search is too high, the community turned to the research of approximate …","url":["https://arxiv.org/pdf/2201.03237"]}
-{"year":"2022","title":"TrollsWithOpinion: A taxonomy and dataset for predicting domain-specific opinion manipulation in troll memes","authors":["S Suryawanshi, BR Chakravarthi, M Arcan, P Buitelaar - Multimedia Tools and …, 2022"],"snippet":"Memes have become a de-facto media device in online communication. Unfortunately, memes are also used for trolling, which intends to demean, harass, or bully targeted individuals. As a result of which, the targeted individual could fall prey …","url":["https://link.springer.com/article/10.1007/s11042-022-13796-x"]}
-{"year":"2022","title":"Trustworthiness of Health-Related Information on Arabic Social Media","authors":["Y Albalawi"],"snippet":"Social media (SM) platforms play a vital role in disseminating health-related information. However, evidence suggests that Twitter posts (ie, tweets) are often inaccurate; for example, research from Saudi Arabia indicates that 50% of health-related …","url":["https://researchrepository.ul.ie/articles/thesis/Trustworthiness_of_health-related_information_on_Arabic_social_media/21666269/1/files/38408135.pdf"]}
-{"year":"2022","title":"TSMind: Alibaba and Soochow University's Submission to the WMT22 Translation Suggestion Task","authors":["X Ge, K Wang, J Wang, N Xiao, X Duan, Y Zhao… - arXiv preprint arXiv …, 2022"],"snippet":"This paper describes the joint submission of Alibaba and Soochow University, TSMind, to the WMT 2022 Shared Task on Translation Suggestion (TS). We participate in the English-German and English-Chinese tasks. Basically, we utilize …","url":["https://arxiv.org/pdf/2211.08987"]}
-{"year":"2022","title":"Tune in: The afrl wmt21 news-translation systems","authors":["G Erdmann, J Gwinnup, T Anderson - Proceedings of the Sixth Conference on …, 2021"],"snippet":"… The corpus used for the initial model consisted of commoncrawl, paracrawl v1, and newscommentary-v13 from wmt19 and was processed … Dirt cheap web-scale parallel text from the common crawl. In Proceedings of the 51st Annual Meeting of …","url":["https://aclanthology.org/2021.wmt-1.5.pdf"]}
-{"year":"2022","title":"Turkish abstractive text summarization using pretrained sequence-to-sequence models","authors":["B Baykara, T Güngör - Natural Language Engineering, 2022"],"snippet":"The tremendous amount of increase in the number of documents available on the Web has turned finding the relevant piece of information into a challenging, tedious, and time-consuming activity. Accordingly, automatic text summarization has become …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/turkish-abstractive-text-summarization-using-pretrained-sequencetosequence-models/B2A0C3F5A7EE2A4AA2844B3AD3A66748"]}
-{"year":"2022","title":"TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks","authors":["R Hu, D Zhang, D Tao, T Hartvigsen, H Feng… - arXiv preprint arXiv …, 2022"],"snippet":"Foodborne illness is a serious but preventable public health problem -- with delays in detecting the associated outbreaks resulting in productivity loss, expensive recalls, public safety hazards, and even loss of life. While social media is a promising source …","url":["https://arxiv.org/pdf/2205.10726"]}
-{"year":"2022","title":"TweetNLP: Cutting-Edge Natural Language Processing for Social Media","authors":["J Camacho-Collados, K Rezaee, T Riahi, A Ushio… - arXiv preprint arXiv …, 2022"],"snippet":"In this paper we present TweetNLP, an integrated platform for Natural Language Processing (NLP) in social media. TweetNLP supports a diverse set of NLP tasks, including generic focus areas such as sentiment analysis and named entity …","url":["https://arxiv.org/pdf/2206.14774"]}
-{"year":"2022","title":"TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations","authors":["X Zhang, Y Malkov, O Florez, S Park, B McWilliams… - arXiv preprint arXiv …, 2022"],"snippet":"We present TwHIN-BERT, a multilingual language model trained on in-domain data from the popular social network Twitter. TwHIN-BERT differs from prior pre-trained language models as it is trained with not only text-based self-supervision, but also …","url":["https://arxiv.org/pdf/2209.07562"]}
-{"year":"2022","title":"Two-Stream Network for Sign Language Recognition and Translation","authors":["Y Chen, R Zuo, F Wei, Y Wu, S Liu, B Mak - arXiv preprint arXiv:2211.01367, 2022"],"snippet":"Sign languages are visual languages using manual articulations and non-manual elements to convey information. For sign language recognition and translation, the majority of existing approaches directly encode RGB videos into hidden …","url":["https://arxiv.org/pdf/2211.01367"]}
-{"year":"2022","title":"Uncertainty Estimation for Language Reward Models","authors":["A Gleave, G Irving - arXiv preprint arXiv:2203.07472, 2022"],"snippet":"Language models can learn a range of capabilities from unsupervised training on text corpora. However, to solve a particular problem (such as text summarization) it is typically necessary to fine-tune them on a task-specific dataset. It is often easier for …","url":["https://arxiv.org/pdf/2203.07472"]}
-{"year":"2022","title":"Uncertainty-Aware Cross-Lingual Transfer with Pseudo Partial Labels","authors":["S Lei, X Zhang, J He, F Chen, CT Lu - Findings of the Association for Computational …, 2022"],"snippet":"… 2020) improves over mBERT by training longer with more data from CommonCrawl, and without the NSP objective. Recently, two self-learning based methods were proposed for cross-lingual transfer. Dong and de Melo …","url":["https://aclanthology.org/2022.findings-naacl.153.pdf"]}
-{"year":"2022","title":"Understanding HTML with Large Language Models","authors":["I Gur, O Nachum, Y Miao, M Safdari, A Huang… - arXiv preprint arXiv …, 2022"],"snippet":"… For this task, we derive a dataset from CommonCrawlCommonCrawl does not include renderings or annotations that would reveal what text in the HTML is associated with which elements. Instead, we infer descriptions of various elements …","url":["https://arxiv.org/pdf/2210.03945"]}
-{"year":"2022","title":"UniCon: Unidirectional Split Learning with Contrastive Loss for Visual Question Answering","authors":["Y Sun, H Ochiai - arXiv preprint arXiv:2208.11435, 2022"],"snippet":"Visual question answering (VQA) that leverages multi-modality data has attracted intensive interest in real-life applications, such as home robots and clinic diagnoses. Nevertheless, one of the challenges is to design robust learning for different client …","url":["https://arxiv.org/pdf/2208.11435"]}
-{"year":"2022","title":"Unified Pretraining Framework for Document Understanding","authors":["J Gu, J Kuen, VI Morariu, H Zhao, N Barmpalios, R Jain… - arXiv preprint arXiv …, 2022"],"snippet":"Document intelligence automates the extraction of information from documents and supports many business applications. Recent self-supervised learning methods on large-scale unlabeled document datasets have opened up promising directions …","url":["https://arxiv.org/pdf/2204.10939"]}
-{"year":"2022","title":"Unified-IO: A Unified Model for Vision, Language, and Multi-Modal Tasks","authors":["J Lu, C Clark, R Zellers, R Mottaghi, A Kembhavi - arXiv preprint arXiv:2206.08916, 2022"],"snippet":"We propose Unified-IO, a model that performs a large variety of AI tasks spanning classical computer vision tasks, including pose estimation, object detection, depth estimation and image generation, vision-and-language tasks such as region …","url":["https://arxiv.org/pdf/2206.08916"]}
-{"year":"2022","title":"Universal Conditional Masked Language Pre-training for Neural Machine Translation","authors":["P Li, L Li, M Zhang, M Wu, Q Liu - arXiv preprint arXiv:2203.09210, 2022"],"snippet":"Pre-trained sequence-to-sequence models have significantly improved Neural Machine Translation (NMT). Different from prior works where pre-trained models usually adopt an unidirectional decoder, this paper demonstrates that pre-training a …","url":["https://arxiv.org/pdf/2203.09210"]}
-{"year":"2022","title":"UNLT: Urdu Natural Language Toolkit","authors":["J Shafi, HR Iqbal, RMA Nawab, P Rayson - Natural Language Engineering, 2022"],"snippet":"This study describes a Natural Language Processing (NLP) toolkit, as the first contribution of a larger project, for an under-resourced language—Urdu. In previous studies, standard NLP toolkits have been developed for English and many other …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/unlt-urdu-natural-language-toolkit/66306F671F7CB1056A004F1A166E8E30"]}
-{"year":"2022","title":"Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval","authors":["N Wu, Y Liang, H Ren, L Shou, N Duan, M Gong… - arXiv preprint arXiv …, 2022"],"snippet":"Recent research demonstrates the effectiveness of using pretrained language models (PLM) to improve dense retrieval and multilingual dense retrieval. In this work, we present a simple but effective monolingual pretraining task called …","url":["https://arxiv.org/pdf/2206.03281"]}
-{"year":"2022","title":"Unsupervised Dense Retrieval Deserves Better Positive Pairs: Scalable Augmentation with Query Extraction and Generation","authors":["R Meng, Y Liu, S Yavuz, D Agarwal, L Tu, N Yu… - arXiv preprint arXiv …, 2022"],"snippet":"… In this section, we introduce several data argumentation methods to create pseudo queries given a document (eg, a passage from a Wikipedia article or a web document from CommonCrawl), without using any annotated queries or questions …","url":["https://arxiv.org/pdf/2212.08841"]}
-{"year":"2022","title":"Unsupervised Extreme Multi Label Classification of Stack Overflow Posts","authors":["P Devine, K Blincoe - 2022"],"snippet":"Knowing the topics of a software forum post, such as those on StackOverflow, allows for greater analysis and understanding of the large amounts of data that come from these communities. One approach to this problem is using extreme multi label …","url":["https://kblincoe.github.io/publications/2022_NLBSE_StackOverflow.pdf"]}
-{"year":"2022","title":"Unsupervised Sentence Textual Similarity with Compositional Phrase Semantics","authors":["Z Wang, J Dou, Y Zhang - arXiv preprint arXiv:2210.02284, 2022"],"snippet":"… 2014): We use the 300D GloVe vectors trained on Common Crawl (840B tokens, 2.2M vocabulary) 15. • fastText (Bojanowski et al.… 2017): We use the 300D fastText vectors trained on Common Crawl (600B tokens) without subword information 16. …","url":["https://web7.arxiv.org/pdf/2210.02284"]}
-{"year":"2022","title":"Unsupervised Visual Domain Adaptation by Self-Guided Learning","authors":["J Gao - 2022"],"snippet":"… video action understanding Common Crawl 2020 … In the field of natural language processing, the training datasets used by the leading model GPT-3 [16] include the 410 billion token Common Crawl archive 1 and 86 billion tokens from …","url":["https://pure.qub.ac.uk/files/381689911/corrected_thesis_jian_1107_v3.pdf"]}
-{"year":"2022","title":"UoR-NCL at SemEval-2022 Task 3: Fine-Tuning the BERT-Based Models for Validating Taxonomic Relations","authors":["T Markchom, H Liang, J Chen - Proceedings of the 16th International Workshop on …, 2022"],"snippet":"In human languages, there are many presuppositional constructions that impose a constrain on the taxonomic relations between two nouns depending on their order. These constructions create a challenge in validating taxonomic relations in real-world …","url":["https://aclanthology.org/2022.semeval-1.33.pdf"]}
-{"year":"2022","title":"UPV at TREC Health Misinformation Track 2021","authors":["IB Schlicht, AFM de Paula, P Rosso"],"snippet":"Health misinformation on search engines is a significant problem that could negatively affect individuals or public health. To mitigate the problem, TREC organizes a health misinformation track. This paper presents our submissions to this …","url":["https://trec.nist.gov/pubs/trec30/papers/UPV-HM.pdf"]}
-{"year":"2022","title":"Use the Metadata, Luke!–An Experimental Joint Metadata Search and N-gram Trend Viewer for Personal Web Archives","authors":["B Indig, Z Sárközi-Lindner, M Nagy - Proceedings of the 2nd International Workshop …, 2022"],"snippet":"… This puts pressure on website operators, as everyone is forced to create an archive of their own, the very issue that was intended to be avoided by shared archives such as Common Crawl that have become trapped in a rivalry of quantity …","url":["https://aclanthology.org/2022.nlp4dh-1.7.pdf"]}
-{"year":"2022","title":"Using a Pre-trained SimpleT5 Model for Text Simplification in a limited Corpus","authors":["J Monteiro, M Aguiar, S Araújo - Proceedings of the Working Notes of CLEF, 2022"],"snippet":"In this paper, we describe our approach for solving Task 3 of the SimpleText Lab, organized as part of the Clef 2022 conference. The SimpleText Lab addresses issues of automatic text simplification of scientific texts in order to make scientific …","url":["http://ceur-ws.org/Vol-3180/paper-241.pdf"]}
-{"year":"2022","title":"Using Context-Free Grammar to Generate Synthetic Technical Short Texts","authors":["T Bikaun, M Stewart, M Hodkiewicz - Australasian Joint Conference on Artificial …, 2022"],"snippet":"… Pre-trained language models take advantage of hundreds of millions of open-domain training examples derived from sources such as the English Wikipedia, Toronto BookCorpus, and Common Crawl Corpus to learn powerful representations over …","url":["https://link.springer.com/chapter/10.1007/978-3-031-22695-3_23"]}
-{"year":"2022","title":"Using Contextual Information to Process Out-of-Vocabulary Words in Spoken Dialog Systems","authors":["A Horndasch - 2022"],"snippet":"Speech is a very efficient channel for communication, but it is a challenge to cope with words which are unknown to one of the dialogue partners. Human beings are very good at dealing with words that are not in their vocabulary, for example by …","url":["https://opus4.kobv.de/opus4-fau/files/20700/AxelHorndaschDissertation.pdf"]}
-{"year":"2022","title":"Using Deep Learning Techniques, A Framework for Estimating the Nutritional Value of Food in Real TIME","authors":["S Bahadur, R Kushwaha, S Sharma, SG Anuradha - International Journal of Health Sciences"],"snippet":"… The HTML format is used to store the raw text data acquired from Google and Common Crawl. HTML tags, CSS, JavaScript code, and comments have been removed during the preprocessing process. To extract individual words, such meta-data …","url":["https://www.neliti.com/publications/430147/using-deep-learning-techniques-a-framework-for-estimating-the-nutritional-value"]}
-{"year":"2022","title":"Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model","authors":["S Smith, M Patwary, B Norick, P LeGresley… - arXiv preprint arXiv …, 2022"],"snippet":"… Other Datasets: In addition to Common Crawl data, we leveraged a number of other previously generated datasets. From The Pile, we … To compound this issue, the URLs scraped in different Common Crawl snapshots are not necessarily unique …","url":["https://arxiv.org/pdf/2201.11990"]}
-{"year":"2022","title":"Using distributional thesaurus to enhance transformer-based contextualized representations for low resource languages","authors":["G Venkatesh, A Jana, S Remus, Ö Sevgili… - Proceedings of the 37th …, 2022"],"snippet":"… XLM-RoBERTa [8] is a large multilingual model, based on the RoBERTa architecture, pretrained on 2.5TB of filtered CommonCrawl data. Experiments confirm that it outperforms mBERT on a wide range of cross-lingual tasks. Alongside …","url":["https://dl.acm.org/doi/abs/10.1145/3477314.3507077"]}
-{"year":"2022","title":"Using Emotion Embeddings to Transfer Knowledge Between Emotions, Languages, and Annotation Formats","authors":["G Chochlakis, G Mahajan, S Baruah, K Burghardt… - arXiv preprint arXiv …, 2022"],"snippet":"… It decreases α to 0.3 and switches to the CommonCrawl dataset, which has a more balanced language distribution. It also disposes of language embeddings and TLM. XLM-T [2] extends XLM-R by finetuning it on tweets to perform multilingual …","url":["https://arxiv.org/pdf/2211.00171"]}
-{"year":"2022","title":"Using Information-Seeking Argument Mining to Improve Service","authors":["B Skiera, S Yan, J Daxenberger, M Dombois… - Journal of Service Research, 2022"],"snippet":"If service providers can identify reasons users are in favor of or against a service, they have insightful information that can help them understand user behavior and what they need to do to change such behavior. This article argues that the novel text-mining …","url":["https://journals.sagepub.com/doi/pdf/10.1177/10946705221110845"]}
-{"year":"2022","title":"Using Informative Data Subsets for Efficient Training of Large Language Models: An Initial Study","authors":["HK Renduchintala, K Killamsetty, S Bhatia, M Aggarwal…"],"snippet":"Abstract Language Models (LMs) are pretrained on large unlabeled corpora through selfsupervision tasks and have become ubiquitous to several NLP applications. Recent trends indicate that the generalization capability of Large LMs (LLMs) …","url":["http://sumitbhatia.net/papers/ingenious-enlsp.pdf"]}
-{"year":"2022","title":"Using Keyqueries to Reduce Misinformation in Health-Related Search Results","authors":["M Fröbe, S Günther, A Bondarenko, J Huck, M Hagen - 2022"],"snippet":"In the scenario of health-related searches, we investigate whether explicit relevance feedback by experts can guide query expansion methods to formulate queries that return fewer misleading or wrong results. In contrast to standard query expansion …","url":["https://webis.de/downloads/publications/papers/froebe_2022c.pdf"]}
-{"year":"2022","title":"Using Natural Language Processing Techniques to Improve Manual Test Case Descriptions","authors":["M Viggiato, D Paas, C Buzon, CP Bezemer"],"snippet":"Despite the recent advancements in test automation, software testing often remains a manual, and costly, activity in many industries. Manual test cases, often described only in natural language, consist of one or more test steps, which are instructions …","url":["http://asgaard.ece.ualberta.ca/papers/Conference/ICSE-SEIP_2022_Viggiato_Using_Natural_Language_Processing_Techniques_to_Improve_Manual_Test_Case_Descriptions.pdf"]}
-{"year":"2022","title":"Using Transformer models for gender attribution in Polish","authors":["K Kaczmarek, J Pokrywka, F Graliński - 2022 17th Conference on Computer Science …, 2022"],"snippet":"… We searched the contents of CommonCrawl 2019 (as provided to us by the authors of [6]2) for the six-gram fragments of the HSSS test set, obviously taking into account the fact that feminine gender-specific forms were modified during the …","url":["https://ieeexplore.ieee.org/abstract/document/9908765/"]}
-{"year":"2022","title":"Utilizing Deep Learning for Detecting Adverse Drug Events in Structured and Unstructured Regulatory Drug Data Sets","authors":["BM Knisely, Q Hatim, M Vaughn-Cooke - Pharmaceutical Medicine, 2022"],"snippet":"Background The US Food and Drug Administration (FDA) collects and retains several data sets on post-market drugs and associated adverse events (AEs). The FDA Adverse Event Reporting System (FAERS) contains millions of AE reports …","url":["https://link.springer.com/article/10.1007/s40290-022-00434-y"]}
-{"year":"2022","title":"Utilizing subjectivity level to mitigate identity term bias in toxic comments classification","authors":["Z Zhao, Z Zhang, F Hopfgartner - Online Social Networks and Media, 2022"],"snippet":"Toxic comment classification models are often found biased towards identity terms, ie, terms characterizing a specific group of people such as “Muslim” and “black”. Such bias is commonly reflected in false positive predictions, ie, non-toxic comments with …","url":["https://www.sciencedirect.com/science/article/pii/S246869642200009X"]}
-{"year":"2022","title":"UTSA NLP at SemEval-2022 Task 4: An Exploration of Simple Ensembles of Transformers, Convolutional, and Recurrent Neural Networks","authors":["X Zhao, A Rios - arXiv preprint arXiv:2203.14920, 2022"],"snippet":"The act of appearing kind or helpful via the use of but having a feeling of superiority condescending and patronizing language can have have serious mental health implications to those that experience it. Thus, detecting this condescending and …","url":["https://arxiv.org/pdf/2203.14920"]}
-{"year":"2022","title":"UWaterlooMDS at the TREC 2021 Health Misinformation Track","authors":["M ABUALSAUD, IX CHEN, K GHAJAR, LNHI PHAN…"],"snippet":"… Using the hosts in M as a base, we expanded this list using the common crawl host graph 8. The hosts graph contains roughly 4 million nodes … We do this by calculating PageRank scores in a subset of the common crawl host-level graph. The …","url":["https://trec.nist.gov/pubs/trec30/papers/UwaterlooMDS-HM.pdf"]}
-{"year":"2022","title":"Vega-MT: The JD Explore Academy Translation System for WMT22","authors":["C Zan, K Peng, L Ding, B Qiu, B Liu, S He, Q Lu… - arXiv preprint arXiv …, 2022","C Zanℜ, K Peng, L Dingℜ, B Qiu, B Liu, S He, Q Lu…"],"snippet":"We describe the JD Explore Academy's submission of the WMT 2022 shared general translation task. We participated in all high-resource tracks and one medium-resource track, including Chinese-English, German-English, Czech-English, Russian-English …","url":["https://arxiv.org/pdf/2209.09444","https://www.statmt.org/wmt22/pdf/2022.wmt-1.37.pdf"]}
-{"year":"2022","title":"Vicomtech at DA-VINCIS: Detection of Aggressive and Violent Incidents from Social Media in Spanish","authors":["P Turón, N Perez, A García-Pablos, E Zotova… - 2022"],"snippet":"This paper describes the participation of the Vicomtech NLP team in the DA-VINCIS shared task. This shared task is focused on mentions of violent events in Spanish tweets, and proposes two subtasks: first, detecting whether a violent incident is …","url":["http://ceur-ws.org/Vol-3202/davincis-paper4.pdf"]}
-{"year":"2022","title":"Video Games as a Corpus: Sentiment Analysis using Fallout New Vegas Dialog","authors":["M Hämäläinen, K Alnajjar, T Poibeau - 2022"],"snippet":"We present a method for extracting a multilingual sentiment annotated dialog data set from Fallout New Vegas. The game developers have preannotated every line of dialog in the game in one of the 8 different sentiments: anger, disgust, fear, happy …","url":["https://www.researchgate.net/profile/Mika-Haemaelaeinen/publication/363367422_Video_Games_as_a_Corpus_Sentiment_Analysis_using_Fallout_New_Vegas_Dialog/links/6319cc1870cc936cd3f1ae29/Video-Games-as-a-Corpus-Sentiment-Analysis-using-Fallout-New-Vegas-Dialog.pdf"]}
-{"year":"2022","title":"Vietnamese Hate and Offensive Detection using PhoBERT-CNN and Social Media Streaming Data","authors":["K Quoc Tran, A Trong Nguyen, PG Hoang, CD Luu… - Neural Computing and …, 2022","KQ Tran, AT Nguyen, PG Hoang, CD Luu, TH Do… - arXiv preprint arXiv …, 2022"],"snippet":"… XLM-RoBERTa (XLM-R) [28]: is a multilingual model trained using over two terabytes of cleaned and filtered CommonCrawl data. Upsampling low-resource languages during training and vocabulary generation, generating a more extensive …","url":["https://arxiv.org/pdf/2206.00524","https://link.springer.com/article/10.1007/s00521-022-07745-w"]}
-{"year":"2022","title":"Visualization of 2D fractal structures associated with the Riemann zeta function","authors":["I Belovas, M Sabaliauskas, L Kuzma - DAMSS: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:147807019/147807019.pdf"]}
-{"year":"2022","title":"Visuelle Exploration von indirekten Befangenheiten bei der Verarbeitung natürlicher Sprachen durch Transformer Modelle","authors":["JLAD Petit-Frere"],"snippet":"… Common Crawl corpora are composed of text dataset collected from web pages and contains several billion tokens … This metric was used to measure the biases within the Common Crawl pre-trained GloVe model, an ELMo model, and the bert-base …","url":["https://www.cg.tuwien.ac.at/research/publications/2022/louis-alexandre_dit_petit-frere-2022-veo/louis-alexandre_dit_petit-frere-2022-veo-thesis.pdf"]}
-{"year":"2022","title":"ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation","authors":["L Phan, H Tran, H Nguyen, TH Trinh - arXiv preprint arXiv:2205.06457, 2022"],"snippet":"We present ViT5, a pretrained Transformer-based encoder-decoder model for the Vietnamese language. With T5-style self-supervised pretraining, ViT5 is trained on a large corpus of high-quality and diverse Vietnamese texts. We benchmark ViT5 on …","url":["https://arxiv.org/pdf/2205.06457"]}
-{"year":"2022","title":"VLT: Vision-Language Transformer and Query Generation for Referring Segmentation","authors":["H Ding, C Liu, S Wang, X Jiang - IEEE Transactions on Pattern Analysis and Machine …, 2022"],"snippet":"We propose a Vision-Language Transformer (VLT) framework for referring segmentation to facilitate deep interactions among multi-modal information and enhance the holistic understanding to vision-language features. There are different …","url":["https://ieeexplore.ieee.org/abstract/document/9932025/"]}
-{"year":"2022","title":"Vocabulary Volume: A New Metric for Assessing Vocabulary Knowledge","authors":["D Tellols, T Tokunaga, H Yokono"],"snippet":"This paper presents Vocabulary Volume, a new metric to assess vocabulary knowledge. The existing metrics for vocabulary knowledge assessment rely on word difficulty, which is often defined in terms of the use frequency of words. In addition to …","url":["https://www.cl.c.titech.ac.jp/tokunaga/_media/publication/csedu_2022_76_cr.pdf"]}
-{"year":"2022","title":"Voices of First Responders—Nationwide Public Safety Communication Survey Findings","authors":["A Pintar, K Buchanan, YY Choong - 2022"],"snippet":"Public safety is in the midst of a major transition in the communication technology that is used due to the ongoing development and deployment of the Nationwide Public Safety Broadband Network (NPSBN). Once established, the NPSBN will …","url":["https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=935335"]}
-{"year":"2022","title":"Voicing challenges: GDPR and AI research","authors":["K Quezada-Tavarez, L Dutkiewicz, N Krack - Open Research Europe, 2022"],"snippet":"EU data protection rules could be difficult for researchers to navigate, particularly when processing massive datasets containing personal data for Artificial Intelligence (AI) developments. This article examines how data protection intersects with AI …","url":["https://open-research-europe.ec.europa.eu/articles/2-126"]}
-{"year":"2022","title":"WarpGate: A Semantic Join Discovery System for Cloud Data Warehouses","authors":["T Cong, J Gale, J Frantz, HV Jagadish, Ç Demiralp"],"snippet":"… In the database community, Web table corpora [11, 18] extracted from the Common Crawl contribute the largest publicly accessible relational table datasets. Efforts exploring representation learning for relational tables [8, 17] have trained …","url":["https://www.cidrdb.org/cidr2023/papers/p75-cong.pdf"]}
-{"year":"2022","title":"Web Data Commons-Schema. org Table Annotation Benchmark","authors":["K Korini, R Peeters, C Bizer"],"snippet":"… The Web Data Commons project regularly extracts such data from the Common Crawl and provides it for public download. The Schema.org Table Corpus was created using schema.org data from the December 2020 version of the Web Data …","url":["https://webdatacommons.org/structureddata/sotab/"]}
-{"year":"2022","title":"Web-Based Communication of Wooden Sport Equipment: An Analysis Based on Six Olympic Sports","authors":["F Negro, S Blanc, S Bruzzese, A Falaschi, F Ruffinatto… - Forests, 2022"],"snippet":"Wood has traditionally been used to make sports equipment and playing surfaces. While its use is outdated in several sports, in many others, wood remains well-established or even the material of choice, eg, to make basketball floors or table tennis rackets …","url":["https://www.mdpi.com/1999-4907/13/9/1364/pdf?version=1661587607"]}
-{"year":"2022","title":"Webformer: Pre-training with Web Pages for Information Retrieval","authors":["Y Guo, Z Ma, J Mao, H Qian, X Zhang, H Jiang, Z Cao… - Proceedings of the 45th …, 2022"],"snippet":"Pre-trained language models (PLMs) have achieved great success in the area of Information Retrieval. Studies show that applying these models to ad-hoc document ranking can achieve better retrieval effectiveness. However, on the Web, most …","url":["https://dl.acm.org/doi/abs/10.1145/3477495.3532086"]}
-{"year":"2022","title":"WebFormer: The Web-page Transformer for Structure Information Extraction","authors":["Q Wang, Y Fang, A Ravula, F Feng, X Quan, D Liu - arXiv preprint arXiv:2202.00217, 2022"],"snippet":"… We evaluate WebFormer on SWDE and Common Crawl benchmarks, which shows superior performance over several state-of-the-art methods. The experimental results also demonstrate the effectiveness of WebFormer in modeling …","url":["https://arxiv.org/pdf/2202.00217"]}
-{"year":"2022","title":"Webis at TREC 2021: Deep Learning, Health Misinformation, and Podcasts Tracks","authors":["A Bondarenko, M Fröbe, M Gohsen, S Günther…"],"snippet":"… Mean and PageRank of the domain provided by the Common Crawl,2 as well as six query … up to 1000 anchor texts extracted from six Common Crawl snapshots from the years 2016 to … Here, we use only anchor texts extracted from the …","url":["https://webis.de/downloads/publications/papers/bondarenko_2021f.pdf"]}
-{"year":"2022","title":"WeLM: A Well-Read Pre-trained Language Model for Chinese","authors":["H Su, X Zhou, H Yu, Y Chen, Z Zhu, Y Yu, J Zhou - arXiv preprint arXiv:2209.10372, 2022"],"snippet":"… monthly shards released by Common Crawl to construct a general… common crawl. In Figure 2, we visualize the document length and topic distribution in the training data. Topics are detected with pre-trained topic classification models. We …","url":["https://arxiv.org/pdf/2209.10372"]}
-{"year":"2022","title":"What do Toothbrushes do in the Kitchen? How Transformers Think our World is Structured","authors":["A Henlein, A Mehler - arXiv preprint arXiv:2204.05673, 2022"],"snippet":"Transformer-based models are now predominant in NLP. They outperform approaches based on static models in many respects. This success has in turn prompted research that reveals a number of biases in the language models …","url":["https://arxiv.org/pdf/2204.05673"]}
-{"year":"2022","title":"What is it like to program with artificial intelligence?","authors":["A Sarkar, AD Gordon, C Negreanu, C Poelitz… - arXiv preprint arXiv …, 2022"],"snippet":"… For example, the Common Crawl project1 produces around 20 TB of text data (from web pages) monthly, but labelled task-specific data is less prevalent. This makes unsupervised training appealing which leads to the concept of pre-trained LMs (J. Li …","url":["https://arxiv.org/pdf/2208.06213"]}
-{"year":"2022","title":"What Is Love?: Text Analytics on Romance Literature From the Perspective of Authors","authors":["CH Naing, X Zhao, KH Gan, NH Samsudin - … of Research on Opinion Mining and Text …, 2022"],"snippet":"Descriptions of love can be found in a wide range of literature. The meaning of love that a reader grasps from reading a literary work is mostly the result of self-understanding and is very likely different from the one that the author tried to express. Therefore, it …","url":["https://www.igi-global.com/chapter/what-is-love/298871"]}
-{"year":"2022","title":"What Language Model to Train if You Have One Million GPU Hours?","authors":["T Le Scao, T Wang, D Hesslow, L Saulnier, S Bekman… - Challenges {\\&, 2022"],"snippet":"… crawls with curated highquality sources significantly improves zeroshot generalization over pretraining datasets constructed from Common Crawl only. … First, we have found that complimenting Common Crawl data with high-quality cross-domain …","url":["https://openreview.net/pdf?id=rI7BL3fHIZq"]}
-{"year":"2022","title":"WHAT NEURAL NETWORKS KNOW ABOUT LINGUISTIC COMPLEXITY","authors":["SA Sharoff - Russian Journal of Linguistics, 2022","SS Aleksandrovich - Russian Journal of Linguistics, 2022"],"snippet":"Linguistic complexity is a complex phenomenon, as it manifests itself on different levels (complexity of texts to sentences to words to subword units), through different features (genres to syntax to semantics), and also via different tasks (language …","url":["https://cyberleninka.ru/article/n/what-neural-networks-know-about-linguistic-complexity","https://journals.rudn.ru/linguistics/article/view/31329"]}
-{"year":"2022","title":"What Really Matters? Evaluating the Importance of Skills for Data Analysts","authors":["CA Collier, AL Powell - 2022"],"snippet":"… First, the job postings utilized in Dong and Triche’s study were not comprehensive but rather only those captured by the Common Crawl tool to facilitate the longitudinal nature of their study. Second, the wildcard searches used by Dong and Triche …","url":["https://aisel.aisnet.org/amcis2022/sig_ed/sig_ed/20/"]}
-{"year":"2022","title":"When danger strikes: A linguistic tool for tracking America's collective response to threats","authors":["VK Choi, S Shrestha, X Pan, MJ Gelfand - Proceedings of the National Academy of …, 2022"],"snippet":"In today’s vast digital landscape, people are constantly exposed to threatening language, which attracts attention and activates the human brain’s fear circuitry. However, to date, we have lacked the tools needed to identify threatening language …","url":["https://www.pnas.org/content/pnas/119/4/e2113891119.full.pdf"]}
-{"year":"2022","title":"When Pairs Meet Triplets: Improving Low-Resource Captioning via Multi-Objective Optimization","authors":["Y Wu, S Zhao, Y Zhang, X Yuan, Z Su - ACM Transactions on Multimedia Computing …, 2022"],"snippet":"Image captioning for low-resource languages has attracted much attention recently. Researchers propose to augment the low-resource caption dataset into (image, rich-resource language, and low-resource language) triplets and develop the dual attention …","url":["https://dl.acm.org/doi/abs/10.1145/3492325"]}
-{"year":"2022","title":"Where do I Belong in Six Centuries of Literature?","authors":["J Silva, S Grilo, M Bolrinha, R Santos, L Gomes…"],"snippet":"Enhancing the availability of corpora and processing tools for language research is a central endeavour of the CLARIN research infrastructure. In this chapter we report on how PORTULAN CLARIN, with the support of the national institute for the …","url":["http://www.di.fc.ul.pt/~ahb/pubs/2022SilvaGriloEtAl.pdf"]}
-{"year":"2022","title":"Where Is My Training Bottleneck? Hidden Trade-Offs in Deep Learning Preprocessing Pipelines","authors":["A Isenko, R Mayer, J Jedele, HA Jacobsen - arXiv preprint arXiv:2202.08679, 2022"],"snippet":"Preprocessing pipelines in deep learning aim to provide sufficient data throughput to keep the training processes busy. Maximizing resource utilization is becoming more challenging as the throughput of training processes increases with hardware …","url":["https://arxiv.org/pdf/2202.08679"]}
-{"year":"2022","title":"Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection","authors":["S Gururangan, D Card, SK Drier, EK Gade, LZ Wang… - arXiv preprint arXiv …, 2022"],"snippet":"… Web dumps like Common Crawl offer the promise of more diverse text than what is available in curated resources. However, much of the web consists of frequently replicated boilerplate (eg, privacy policies), code (eg, HTML and Javascript) …","url":["https://arxiv.org/pdf/2201.10474"]}
-{"year":"2022","title":"Why Do Neural Language Models Still Need Commonsense Knowledge to Handle Semantic Variations in Question Answering?","authors":["S Kwon, C Kang, J Han, J Choi - arXiv preprint arXiv:2209.00599, 2022"],"snippet":"… Finally, RoBERTa is pretrained with approximately 160GB of data including the BERT pretraining corpora as well as three additional corpora (CommonCrawl News dataset27, open-source recreation of the WebText corpus28 and STORIES corpus29) …","url":["https://arxiv.org/pdf/2209.00599"]}
-{"year":"2022","title":"Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning","authors":["TT Nguyen, F Trahay, J Domke, A Drozd, E Vatai… - IEEE International Parallel & …, 2022"],"snippet":"Stochastic gradient descent (SGD) is the most prevalent algorithm for training Deep Neural Networks (DNN). SGD iterates the input data set in each training epoch processing data samples in a random access fashion. Because this puts enormous …","url":["https://hal.archives-ouvertes.fr/hal-03599740/document"]}
-{"year":"2022","title":"WikiMulti: a Corpus for Cross-Lingual Summarization","authors":["P Tikhonov, V Malykh - arXiv preprint arXiv:2204.11104, 2022"],"snippet":"Cross-lingual summarization (CLS) is the task to produce a summary in one particular language for a source document in a different language. We introduce WikiMulti - a new dataset for cross-lingual summarization based on Wikipedia …","url":["https://arxiv.org/pdf/2204.11104"]}
-{"year":"2022","title":"Will we run out of data? An analysis of the limits of scaling datasets in Machine Learning","authors":["P Villalobos, J Sevilla, L Heim, T Besiroglu… - arXiv preprint arXiv …, 2022"],"snippet":"… 5) CommonCrawl CommonCrawl releases monthly crawls which for the past four years have contained 5-10TB of compressed plaintext.Half of the URLs in … At 200M words per GB of text, CommonCrawl produces between 8.3e12 and 4.4e13 …","url":["https://arxiv.org/pdf/2211.04325"]}
-{"year":"2022","title":"Within-pair factors might explain the inconsistent effects of animacy on paired-associates recall","authors":["MJ Serra, CM DeYoung - Psychonomic Bulletin & Review, 2022"],"snippet":"The tendency for people to have better memory for animate (living) concepts than inanimate (nonliving) concepts in memory tasks involving free recall and recognition suggests that animacy status can be an important predictor of memory. To date …","url":["https://link.springer.com/article/10.3758/s13423-022-02184-z"]}
-{"year":"2022","title":"Witscript 2: A System for Generating Improvised Jokes Without Wordplay","authors":["J Toplyn"],"snippet":"A previous paper presented Witscript, a system for generating conversational jokes that rely on wordplay. This paper extends that work by presenting Witscript 2, which uses a large language model to generate conversational jokes that rely on common …","url":["https://computationalcreativity.net/iccc22/wp-content/uploads/2022/06/ICCC-2022_3S_Toplyn.pdf"]}
-{"year":"2022","title":"Word Embeddings for Automatic Equalization in Audio Mixing","authors":["S Venkatesh, D Moffat, ER Miranda - arXiv preprint arXiv:2202.08898, 2022"],"snippet":"… It trains on the World Wide Web using Common Crawl, which is a larger corpus of text. Tok2Vec is a word embedding model provided by a company called spaCy [31]. We did not find the entire details regarding its implementation, but the model is …","url":["https://arxiv.org/pdf/2202.08898"]}
-{"year":"2022","title":"Word formation supports efficient communication: The case of compounds","authors":["A Xu, C Kemp, L Frermann, Y Xu"],"snippet":"Compounding is a common type of word formation extensively studied in linguistics and cognitive psychology. A growing line of research suggests that the lexicon supports efficient communication by balancing informativeness and simplicity. We …","url":["http://www.charleskemp.com/papers/xukfx_wordformationsupportsefficientcommunicationthecaseofcompounds.pdf"]}
-{"year":"2022","title":"Work-in-Progress: Computing Sentence Similarity for Short Texts using Transformer models","authors":["V Ramnarain-Seetohul, V Bassoo, Y Rosunally - 2022 IEEE Global Engineering …, 2022"],"snippet":"… The OpenAI GPT-3, an autoregressive language model with 175 billion parameters, is trained with the Common Crawl corpus of data, web text, books, and Wikipedia [10]. The OpenAI offers an API to use the GPT-3 model for registered users …","url":["https://ieeexplore.ieee.org/abstract/document/9766649/"]}
-{"year":"2022","title":"WuDaoMM: A large-scale Multi-Modal Dataset for Pre-training models","authors":["S Yuan, Z Shuai, L Jiahong, X Zhao, Z Hanyu, T Jie - arXiv preprint arXiv:2203.11480, 2022"],"snippet":"… LAION-400M is a larger-scale vision-language corpus, which uses Common Crawl as the data source and applies a series of exquisite data cleaning rules. In contrast, Chinese-based multi-modal datasets are relatively rare and the scale of …","url":["https://arxiv.org/pdf/2203.11480"]}
-{"year":"2022","title":"XDoc: Unified Pre-training for Cross-Format Document Understanding","authors":["J Chen, T Lv, L Cui, C Zhang, F Wei - arXiv preprint arXiv:2210.02849, 2022"],"snippet":"… 2022a), we take advantage of the large-scale dataset Common Crawl3, which contains petabytes of web pages in raw formats. Specifically, text contents and HTML tags are both available for each web page. According to (Li et al., 2022a), the …","url":["https://arxiv.org/pdf/2210.02849"]}
-{"year":"2022","title":"XLCNN: pre-trained transformer model for malware detection","authors":["Κ Γιαπαντζής - 2022"],"snippet":"The present thesis describes a Transformer-based neural network model that was developed in order to detect malicious software. We believe that the scientific community should take advantage of the contribution of Transformer models in the …","url":["https://dspace.lib.uom.gr/bitstream/2159/26452/1/GiapantzisKonstantinosMsc2022.pdf"]}
-{"year":"2022","title":"XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond","authors":["F Barbieri, LE Anke, J Camacho-Collados"],"snippet":"Abstract Language models are ubiquitous in current NLP, and their multilingual capacity has recently attracted considerable attention. However, current analyses have almost exclusively focused on (multilingual variants of) standard benchmarks …","url":["http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.27.pdf"]}
-{"year":"2022","title":"XTREME-S: Evaluating Cross-lingual Speech Representations","authors":["A Conneau, A Bapna, Y Zhang, M Ma, P von Platen… - arXiv preprint arXiv …, 2022"],"snippet":"We introduce XTREME-S, a new benchmark to evaluate universal cross-lingual speech representations in many languages. XTREME-S covers four task families: speech recognition, classification, speech-to-text translation and retrieval. Covering …","url":["https://arxiv.org/pdf/2203.10752"]}
-{"year":"2022","title":"Ynu-hpcc at semeval-2022 task 2: Representing multilingual idiomaticity based on contrastive learning","authors":["K Liu, J Wang, X Zhang - Proceedings of the 16th International Workshop on …, 2022"],"snippet":"This paper will present the methods we use as the YNU-HPCC team in the SemEval-2022 Task 2, Multilingual Idiomaticity Detection and Sentence Embedding. We are involved in two subtasks, including four settings. In subtask B of sentence …","url":["https://aclanthology.org/2022.semeval-1.26.pdf"]}
-{"year":"2022","title":"You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual Settings","authors":["Z Talat, A Névéol, S Biderman, M Clinciu, M Dey… - Challenges {\\&, 2022"],"snippet":"Evaluating bias, fairness, and social impact in monolingual language models is a difficult task. This challenge is further compounded when language modeling occurs in a multilingual context. Considering the implication of evaluation biases for large …","url":["https://openreview.net/pdf?id=rK-7NhfSIW5"]}
-{"year":"2022","title":"Zero Shot Crosslingual Eye-Tracking Data Prediction using Multilingual Transformer Models","authors":["H Srivastava - 2022"],"snippet":"Eye tracking data during reading is a useful source of information to understand the cognitive processes that take place during language comprehension processes. Different languages account for different brain triggers, however there seems to be …","url":["https://openreview.net/pdf?id=HZxe1KUug5"]}
-{"year":"2022","title":"Zero-shot Commonsense Question Answering with Cloze Translation and Consistency Optimization","authors":["ZY Dou, N Peng - arXiv preprint arXiv:2201.00136, 2022"],"snippet":"… Concretely, first, they create a cloze question corpus by masking noun phrases and named entities in statements sampled from Wikipedia, and a natural question corpus by mining questions containing some common wh-words from CommonCrawl …","url":["https://arxiv.org/pdf/2201.00136"]}
-{"year":"2022","title":"Zero-Shot Ranking Socio-Political Texts with Transformer Language Models to Reduce Close Reading Time","authors":["K Akdemir, A Hürriyetoğlu - arXiv preprint arXiv:2210.09179, 2022"],"snippet":"We approach the classification problem as an entailment problem and apply zero-shot ranking to socio-political texts. Documents that are ranked at the top can be considered positively classified documents and this reduces the close reading time …","url":["https://arxiv.org/pdf/2210.09179"]}
-{"year":"2022","title":"Zhichunroad at semeval-2022 task 2: Adversarial training and contrastive learning for multiword representations","authors":["X Cui, W Xiong, S Wang - Proceedings of the 16th International Workshop on …, 2022"],"snippet":"This paper presents our contribution to the SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding. We explore the impact of three different pre-trained multilingual language models in the SubTaskA. By enhancing …","url":["https://aclanthology.org/2022.semeval-1.24.pdf"]}
-{"year":"2023","title":"''Fifty Shades of Bias'': Normative Ratings of Gender Bias in GPT Generated English Text","authors":["R Hada, A Seth, H Diddee, K Bali - arXiv preprint arXiv:2310.17428, 2023"],"snippet":"Language serves as a powerful tool for the manifestation of societal belief systems. In doing so, it also perpetuates the prevalent biases in our society. Gender bias is one of the most pervasive biases in our society and is seen in online and offline …","url":["https://arxiv.org/pdf/2310.17428"]}
-{"year":"2023","title":"12 The Future of","authors":["P Chundi, V Bommanapally, V Gadhamshetty - Machine Learning in 2D Materials …, 2023"],"snippet":"… GPT-3 is an autoregressive model built with 96 layers [31], increased embedding vector dimension of 12888, trained with 175B parameters on five datasets including Common crawl, WebText2, Books1, Books2, and Wikipedia. Though GPT-3 has …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=vcrYEAAAQBAJ&oi=fnd&pg=PA217&dq=commoncrawl&ots=ECheeM6s-k&sig=7ob0zjXEaKZNMVUPtMJFlTgQIJ0"]}
-{"year":"2023","title":"14 Augmenting and Informing the Translation Process through Workflow-Enabled CALT Tools","authors":["SM Rudan, E Kelbert, L Kovacevic, M Reynolds… - Computer-Assisted Literary …, 2023"],"snippet":"CALT is an emerging field in the process of defining itself, but it is already, we feel, a misnomer. Adding an ‘L’(Literary) to the pre-existing notion of Computer-Assisted Translation (CAT) creates continuity with CAT research; Machine Translation (MT) is …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=P13bEAAAQBAJ&oi=fnd&pg=PA258&dq=commoncrawl&ots=IYhfg3_tre&sig=NkpRTu0wMw5egO-e58ZBb2KiLs0"]}
-{"year":"2023","title":"19. Assessing collective identity (non-) verification with social media data through web scraping, sentiment analysis, and qualitative coding","authors":["TP Love, JL Davis, RE Davis, WG Fisher, RM Barczak - Handbook of Research …, 2023"],"snippet":"… Perhaps the most prolific example of these techniques is Common Crawl, a non-profit organization that employs a web crawling and web scraping program to harvest information across the Internet. Common Crawl has been web crawling and web …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=0rHLEAAAQBAJ&oi=fnd&pg=PA261&dq=commoncrawl&ots=tWK4u0Huom&sig=wYMvXZZg4c53jdLKG8OSCDd_LRs"]}
-{"year":"2023","title":"22 Forward Thinking on GeoAI","authors":["S Newsam - Handbook of Geospatial Artificial Intelligence, 2023"],"snippet":"… Second, is the unsupervised pre-training on large corpora of text such as the Common Crawl archive of the Internet. This pre-training does not require manually labeled data since it largely involves simply determining whether the model correctly …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=liXpEAAAQBAJ&oi=fnd&pg=PA427&dq=commoncrawl&ots=CO48Jg0Q06&sig=R9edTPxNRPHWUThKp3EEhieFIe4"]}
-{"year":"2023","title":"3.3 On Information and Interactions on the Web","authors":["V Charpenay - Agents on the Web"],"snippet":"… In natural language processing, large language models such as BERT or GPT are trained on large corpi found on the Web, including Wikipedia and CommonCrawl 4 data. … php 4 https://commoncrawl. org/ 5 https://pedantic-web. org/ …","url":["https://drops.dagstuhl.de/opus/volltexte/2023/19182/pdf/dagrep_v013_i002_p071_23081.pdf#page=10"]}
-{"year":"2023","title":"6 Author-Tailored Neural Machine Translation Systems for Literary Works","authors":["A Oliver - Computer-Assisted Literary Translation, 2023"],"snippet":"Literature is one of the areas where machine translation (MT) has not been used until very recent times. Nevertheless, the impressive increase in quality obtained with neural machine translation (NMT) systems has led some authors to start …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=P13bEAAAQBAJ&oi=fnd&pg=PA126&dq=commoncrawl&ots=IYhfg3_tre&sig=TRar6iD7Fq7PUah62jFiPmhOQuM"]}
-{"year":"2023","title":"6 Distributed computational models of intervention effects: A study on cleft structures in French","authors":["G Samo, P Merlo - It-Clefts: Empirical and Theoretical Surveys and …, 2023"],"snippet":"… Briefly, the uncompressed 270 GB of French text corpus consists of 24 sub-corpora gathered from different sources,(eg Wikipedia and books, random text crawled from the Internet (eg Common Crawl). 6 We use the code discussed in Renaud (2020) …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=WLbiEAAAQBAJ&oi=fnd&pg=PA157&dq=commoncrawl&ots=XupU0tqLh2&sig=fuFlpLZq-Un0elMSOiWBllsnaPI"]}
-{"year":"2023","title":"6 Persian Named Entity Recognition with Structural Prediction Methods","authors":["H Poostchi, M Piccardi - Persian Computational Linguistics and NLP, 2023"],"snippet":"… As the standard word embedding we have downloaded and used the 300D Farsi fastText embeddings trained on Common Crawl and … Our initial experiments showed that the combination of the fastText embeddings trained on Common Crawl …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=mmu8EAAAQBAJ&oi=fnd&pg=PA149&dq=commoncrawl&ots=IT4Mfr3GhG&sig=SGTXp5guThr4EXwAn-KvibAk5yc"]}
-{"year":"2023","title":"\" Get a Higher Return on Your Savings!\": Comparing Adverts for Cryptocurrency Investment Scams Across Platforms","authors":["GA Siu, A Hutchings - 2023 IEEE European Symposium on Security and …, 2023"],"snippet":"This work compares machine learning methods using supervised, semi-supervised and unsupervised learning, to classify advertisements for cryptocurrency related investment scams found in the online forum Bitcointalk, and the social media …","url":["https://www.computer.org/csdl/proceedings-article/eurospw/2023/272000a158/1OFtfhsKFVu"]}
-{"year":"2023","title":"\" I wouldn't say offensive but...\": Disability-Centered Perspectives on Large Language Models","authors":["V Gadiraju, S Kane, S Dev, A Taylor, D Wang… - 2023"],"snippet":"Large language models (LLMs) trained on real-world data can inadvertently reflect harmful societal biases, particularly toward historically marginalized communities. While previous work has primarily focused on harms related to age and race …","url":["https://research.google/pubs/pub52358.pdf"]}
-{"year":"2023","title":"\" Kelly is a Warm Person, Joseph is a Role Model\": Gender Biases in LLM-Generated Reference Letters","authors":["Y Wan, G Pu, J Sun, A Garimella, KW Chang, N Peng - arXiv preprint arXiv …, 2023"],"snippet":"… 2019a), which is sourced from online biographies in the Common Crawl corpus. The dataset also includes metadata across several occupations and gender indicators. We prompt ChatGPT to rephrase this initial biography into two versions …","url":["https://arxiv.org/pdf/2310.09219"]}
-{"year":"2023","title":"\" Paraphrasing The Original Text\" Makes High Accuracy Long-Context QA","authors":["Y Yu - arXiv preprint arXiv:2312.11193, 2023"],"snippet":"Although LLMs continue to iterate and improve, most open-source models still have a context window of no more than 4k, limiting their ability to handle long-context problems. Most existing open-source models for long-context chat still lack …","url":["https://arxiv.org/pdf/2312.11193"]}
-{"year":"2023","title":"\\texttt {IngesTables}: Scalable and Efficient Training of LLM-Enabled Tabular Foundation Models","authors":["S Yak, Y Dong, J Gonzalvo, S Arik - NeurIPS 2023 Second Table Representation …, 2023"],"snippet":"There is a massive amount of tabular data that can be taken advantage of via `foundation models' to improve prediction performance for downstream tabular prediction tasks. However, numerous challenges constitute bottlenecks in building tabular foundation …","url":["https://openreview.net/pdf?id=EocsZtcA7P"]}
-{"year":"2023","title":"Özgeçmişlerde varlık isimlerinin tanınması Named entity recognition in resumes","authors":["E Kesim, S Tanberk - 2023 Innovations in Intelligent Systems and …, 2023"],"snippet":"Named entity recognition (NER) is used to extract information from various documents and texts such as names and dates. It is important to extract education and work experience information from resumes in order to filter them. Considering …","url":["https://ieeexplore.ieee.org/abstract/document/10296807/"]}
-{"year":"2023","title":"“Source?”“I Made It Up”: The Ethics of Citing ChatGPT in Academia","authors":["C DeKay - 2023"],"snippet":"… This should not be necessarily surprising as we do know that most LLMs are trained using the CommonCrawl dataset, a collection of twelve years’ worth of publicly available Internet pages, where sites like AO3 with over 11 million freely …","url":["https://ir.lib.uwo.ca/cgi/viewcontent.cgi?article=1009&context=fims_evolvingtech_finalproj_summer2023"]}
-{"year":"2023","title":"A Benchmark Analysis of Few-Shot Biomedical Named Entity Recognition","authors":["M Postiglione, I Iodice"],"snippet":"… This led to the development of pretrained systems such as BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer), which were trained with large language datasets, such as Wikipedia …","url":["https://picuslab.dieti.unina.it/images/pdfs/_TESI__IVANO_IODICE.pdf"]}
-{"year":"2023","title":"A benchmark for evaluating Arabic contextualized word embedding models","authors":["A Elnagar, S Yagi, Y Mansour, L Lulu, S Fareh - Information Processing & …, 2023"],"snippet":"… It was pre-trained on a 2.5 TB of clean CommonCrawl dataset in 100 languages. … Amassing huge amounts of non-financial data as in the Common Crawl dilutes the patterns found in financial texts. That is the most likely explanation for why so many …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323001899"]}
-{"year":"2023","title":"A Benchmark for Text Expansion: Datasets, Metrics, and Baselines","authors":["Y Chen, H Jiang, W Bi, R Wang, L Wang, S Shi, R Xu - arXiv preprint arXiv …, 2023"],"snippet":"… We use CommonCrawl2 as the data source. Based on the four complementary approaches in §3, we further conduct data filtering (Appendix D) and construct a large-scale TE corpus with 12M pairs for both English and Chinese. Detailed …","url":["https://arxiv.org/pdf/2309.09198"]}
-{"year":"2023","title":"A benchmark for toxic comment classification on Civil Comments dataset","authors":["C Duchene, H Jamet, P Guillaume, R Dehak - arXiv preprint arXiv:2301.11125, 2023"],"snippet":"Toxic comment detection on social media has proven to be essential for content moderation. This paper compares a wide set of different models on a highly skewed multi-label hate speech dataset. We consider inference time and several metrics to …","url":["https://arxiv.org/pdf/2301.11125"]}
-{"year":"2023","title":"A BERT-Based Model for Financial Social Media Sentiment Analysis","authors":["J Delgadillo, J Kinyua, C Mutigwe - International Journal of Cognitive and Language …, 2023"],"snippet":"The purpose of sentiment analysis is to determine the sentiment strength (eg, positive, negative, neutral) from a textual source for good decision-making. Natural Language Processing (NLP) in domains such as financial markets requires …","url":["https://publications.waset.org/10012944/a-bert-based-model-for-financial-social-media-sentiment-analysis"]}
-{"year":"2023","title":"A Brief Overview of ChatGPT: The History, Status Quo and Potential Future Development","authors":["T Wu, S He, J Liu, S Sun, K Liu, QL Han, Y Tang - IEEE/CAA Journal of Automatica …, 2023"],"snippet":"ChatGPT, an artificial intelligence generated content (AIGC) model developed by OpenAI, has attracted world-wide attention for its capability of dealing with challenging language understanding and generation tasks in the form of …","url":["https://www.ieee-jas.net/en/article/doi/10.1109/JAS.2023.123618"]}
-{"year":"2023","title":"A Case Study Analysis of Google Smart Compose and Its Effects on the Student Writing Process From the Student and Teacher Perspectives","authors":["H Bryant - 2023"],"snippet":"This qualitative case study addresses the rise in popularity of the use of predictive text programs within the K-12 educational environment. A problem exists in the discrepancy between the widespread availability of Google Smart Compose within …","url":["https://search.proquest.com/openview/f62cdbf5839f7b94d7eaf8f39e8cdf1a/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"A Cohesive Distillation Architecture for Neural Language Models","authors":["JP Wahle - arXiv preprint arXiv:2301.08130, 2023","LR Terry - 2023"],"snippet":"A recent trend in Natural Language Processing is the exponential growth in Language Model (LM) size, which prevents research groups without a necessary hardware infrastructure from participating in the development process. This study …","url":["https://arxiv.org/pdf/2301.08130","https://www.authorea.com/doi/pdf/10.22541/au.167528147.79728645"]}
-{"year":"2023","title":"A Comparative Performance Evaluation of Algorithms for the Analysis and Recognition of Emotional Content","authors":["K Kyritsis, N Spatiotis, I Perikos, M Paraskevas - 2023"],"snippet":"Sentiment Analysis is highly valuable in Natural Language Processing (NLP) across domains, processing and evaluating sentiment in text for emotional understanding. This technology has diverse applications, including social media monitoring, brand …","url":["https://www.intechopen.com/online-first/87923"]}
-{"year":"2023","title":"A Comparative Study of Code Generation using ChatGPT 3.5 across 10 Programming Languages","authors":["A Buscemi - arXiv preprint arXiv:2308.04477, 2023"],"snippet":"… OpenAI employed a dataset known as the Common Crawl [24], a publicly accessible collection of billions of web pages, making it as one of the most extended text databases currently accessible. It is to be noted that the selection of the dataset …","url":["https://arxiv.org/pdf/2308.04477"]}
-{"year":"2023","title":"A Comparative Study of Pre-trained Language Models to Filter Informative Code-mixed Data on Social Media during Disasters","authors":["H Salemi, Y Senarath, H Purohit"],"snippet":"… A multi-lingual language model trained using masked language modeling on 2.5 TB of newly created and cleaned CommonCrawl data. … XLM-R: A multilingual version of RoBERTa that is pre-trained on 2.5TB of filtered CommonCrawl data …","url":["https://idl.iscram.org/files/salemi/2023/2576_Salemi_etal2023.pdf"]}
-{"year":"2023","title":"A Comparative Study of Sentence Embedding Models for Assessing Semantic Variation","authors":["DM Mistry, AA Minai - arXiv preprint arXiv:2308.04625, 2023"],"snippet":"… XLM-R [14] is a transformer trained using masked language modeling on one hundred languages using over two terabytes of filtered CommonCrawl data. The trained model shows significant performance improvement over multilingual BERT (mBERT) …","url":["https://arxiv.org/pdf/2308.04625"]}
-{"year":"2023","title":"A Comparative Study of Text Embedding Models for Semantic Text Similarity in Bug Reports","authors":["A Patil, K Han, S Mukhopadhyay - arXiv preprint arXiv:2308.09193, 2023"],"snippet":"… For Fasttext, we employed the ”crawl-300d2M-subword” model, which consisted of 2 million word vectors trained with subword information on the Common Crawl dataset, encompassing 600 billion tokens. In the case of Doc2Vec, we used the ”GoogleNews-vectors-negative300…","url":["https://arxiv.org/pdf/2308.09193"]}
-{"year":"2023","title":"A Comparative Study of Text Representations for French Real-Estate Classified Advertisements Information Extraction","authors":["L Cadorel, AGB Tettamanzi - 2023"],"snippet":"Text representations are widely used in NLP tasks such as text classification. Very powerful models have emerged and been trained on huge corpora for different languages. However, most of the pre-trained models are domain-agnostic and fail …","url":["https://ceur-ws.org/Vol-3495/paper_06.pdf"]}
-{"year":"2023","title":"A Comparative Study of Transformer Based Pretrained AI Models for Content Summarization","authors":["ASA Rasheed, MM Masud, M Abduljabbar - 2023 15th International Conference on …, 2023"],"snippet":"In this study, we examine different transformer based pretrained Artificial Intelligence (AI) models on their ability to summarize text content from different sources. AI has emerged as a powerful tool in this context, offering the potential to automate and …","url":["https://ieeexplore.ieee.org/abstract/document/10366411/"]}
-{"year":"2023","title":"A Comparitive Study on Abstractive Text Summarization Techniques Using Deep Learning (ATS-DL)","authors":["S Adhithyan, AR Nirupama, S Sri Akshya… - Soft Computing: Theories …, 2023"],"snippet":"… It is trained using Common Crawl’s web crawl corpus (C4), a very large corpus of data for all NLP tasks. T5 comes in 5 variants such as T5-small, T5-big, T5-large, T5-3B and T5-11B, where each is trained with 60 million, 220 million, 770 million, 3 billion …","url":["https://link.springer.com/chapter/10.1007/978-981-19-9858-4_80"]}
-{"year":"2023","title":"A compendium of data sources for data science, machine learning, and artificial intelligence","authors":["P Bilokon, O Bilokon, S Amen - arXiv preprint arXiv:2309.05682, 2023"],"snippet":"Recent advances in data science, machine learning, and artificial intelligence, such as the emergence of large language models, are leading to an increasing demand for data that can be processed by such models. While data sources are application-specific …","url":["https://arxiv.org/pdf/2309.05682"]}
-{"year":"2023","title":"A Comprehensive Analysis of the Effectiveness of Large Language Models as Automatic Dialogue Evaluators","authors":["C Zhang, LF D'Haro, Y Chen, M Zhang, H Li - arXiv preprint arXiv:2312.15407, 2023"],"snippet":"Automatic evaluation is an integral aspect of dialogue system research. The traditional reference-based NLG metrics are generally found to be unsuitable for dialogue assessment. Consequently, recent studies have suggested various unique …","url":["https://arxiv.org/pdf/2312.15407"]}
-{"year":"2023","title":"A Comprehensive Overview of Large Language Models","authors":["H Naveed, AU Khan, S Qiu, M Saqib, S Anwar… - arXiv preprint arXiv …, 2023"],"snippet":"… The dataset is extracted from the public common crawl scrape. The model uses GeGLU activation and trains with a vocab size of 250,000 … 3) PanGu-α [78]: An autoregressive model trained on 1.1TB Chinese data collected from Common Crawl …","url":["https://arxiv.org/pdf/2307.06435"]}
-{"year":"2023","title":"A Comprehensive Study of ChatGPT: Advancements, Limitations, and Ethical Considerations in Natural Language Processing and Cybersecurity","authors":["M Alawida, S Mejri, A Mehmood, B Chikhaoui… - Information, 2023"],"snippet":"This paper presents an in-depth study of ChatGPT, a state-of-the-art language model that is revolutionizing generative text. We provide a comprehensive analysis of its architecture, training data, and evaluation metrics and explore its …","url":["https://www.mdpi.com/2078-2489/14/8/462"]}
-{"year":"2023","title":"A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT","authors":["Y Cao, S Li, Y Liu, Z Yan, Y Dai, PS Yu, L Sun - arXiv preprint arXiv:2303.04226, 2023"],"snippet":"Recently, ChatGPT, along with DALL-E-2 and Codex,has been gaining significant attention from society. As a result, many individuals have become interested in related resources and are seeking to uncover the background and secrets behind its …","url":["https://arxiv.org/pdf/2303.04226"]}
-{"year":"2023","title":"A Comprehensive Survey of ChatGPT: Advancements, Applications, Prospects, and Challenges","authors":["A Nazir, Z Wang - Meta-Radiology, 2023"],"snippet":"Large Language Models (LLMs) especially when combined with Generative Pre-trained Transformers (GPT) represent a groundbreaking in natural language processing. In particular, ChatGPT, a state-of-the-art conversational language model with a user-friendly …","url":["https://www.sciencedirect.com/science/article/pii/S295016282300022X"]}
-{"year":"2023","title":"A Comprehensive Survey on Applications of Transformers for Deep Learning Tasks","authors":["S Islam, H Elmekki, A Elsebai, J Bentahar, N Drawel… - arXiv preprint arXiv …, 2023"],"snippet":"Transformer is a deep neural network that employs a self-attention mechanism to comprehend the contextual relationships within sequential data. Unlike conventional neural networks or updated versions of Recurrent Neural Networks (RNNs) such as …","url":["https://arxiv.org/pdf/2306.07303"]}
-{"year":"2023","title":"A Computational Analysis on the Role of Social Relationships in Online Communication and Information Diffusion","authors":["M Choi - 2023"],"snippet":"… 2014] embeddings with 300 dimensions, trained on the Common Crawl corpus (42B tokens) performed best in the tasks we addressed. In addition to considering a word’s local context, GloVe uses also global co-occurrence statistics across the whole text …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/177746/minje_1.pdf?sequence=1"]}
-{"year":"2023","title":"A Conversational Breakdown Detector for a Motivational Interviewing Conversational Agent","authors":["ZL Qin - The iJournal: Student Journal of the University of …, 2023"],"snippet":"… The first is pre-training a large language model on a general corpus, such as Wikipedia or Common Crawl. The next step is adding a classification layer and fine-tuning the model on new data so this model can be used in downstream tasks. They …","url":["https://theijournal.ca/index.php/ijournal/article/download/42237/32259"]}
-{"year":"2023","title":"A Cross-Attention Augmented Model for Event-Triggered Context-Aware Story Generation","authors":["C Tang, T Loakman, C Lin - arXiv preprint arXiv:2311.11271, 2023"],"snippet":"Despite recent advancements, existing story generation systems continue to encounter difficulties in effectively incorporating contextual and event features, which greatly influence the quality of generated narratives. To tackle these …","url":["https://arxiv.org/pdf/2311.11271"]}
-{"year":"2023","title":"A Data-driven Understanding of Left-Wing Extremists on Social Media","authors":["U Balcı, M Sirivianos, J Blackburn - arXiv preprint arXiv:2307.06981, 2023"],"snippet":"Social media's role in the spread and evolution of extremism is a focus of intense study. Online extremists have been involved in the spread of online hate, mis/disinformation, and real-world violence. However, the overwhelming majority of existing work has …","url":["https://arxiv.org/pdf/2307.06981"]}
-{"year":"2023","title":"A Dataset and Strong Baselines for Classification of Czech News Texts","authors":["H Kydlíček, J Libovický - arXiv preprint arXiv:2307.10666, 2023"],"snippet":"… We create the CZE-NEC by crawling Czech news websites from CommonCrawl (§ 2.1) and use the available metadata to define classification tasks (§ 2.3). … Instead of crawling the pages directly, we used the CommonCrawl archive to extract the articles. …","url":["https://arxiv.org/pdf/2307.10666"]}
-{"year":"2023","title":"A deep learning framework for the detection of Malay hate speech","authors":["K Maity, S Bhattacharya, S Saha, M Seera - IEEE Access, 2023"],"snippet":"Although social media can efficiently disseminate information, they also facilitate the dissemination of online abuse, harassment, and hate speech. In 2019, United Nations Secretary-General introduced the United Nations Strategy and Plan of …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10192900.pdf"]}
-{"year":"2023","title":"A Deep Learning-Based Phishing Detection System Using CNN, LSTM, and LSTM-CNN","authors":["Z Alshingiti, R Alaqel, J Al-Muhtadi, QEU Haq… - Electronics, 2023"],"snippet":"… Around one million legitimate and phishing URLs were used on the dataset collected from PhishTank and Common Crawl. To build the IPDS, the LSTM and CNN classifier used over 10,000 images and one million URLs for training. The …","url":["https://www.mdpi.com/2046874"]}
-{"year":"2023","title":"A Deep Neural Network Architecture for Extracting Contextual Information","authors":["Z Alami Merrouni, B Frikh, B Ouhbi - The 3rd International Conference on Artificial …, 2023"],"snippet":"… However, existing datasets for AKE are quite small, so we use Stanford's GloVe Embeddings, which are trained on either Wikipedia 2014 + Gigaword 5 (approximately 6 billion tokens) or Common Crawl (approximately 6 billion tokens) (about 840 …","url":["https://link.springer.com/chapter/10.1007/978-3-031-27762-7_10"]}
-{"year":"2023","title":"A deep neural network-based data-driven model for evaluating the recognition of ADR mentions in the texts of the PsyTAR corpus","authors":["A Sboev, G Rylkov, A Selivanov, I Moloshnikov… - AIP Conference …, 2023"],"snippet":"In this paper, for the first time, the accuracy of solving the problem of recognizing named entities of the ADR type for the PsyTAR corpus was evaluated. Initially, the corpus contained markup for solving the problems of detecting entities, classifying …","url":["https://pubs.aip.org/aip/acp/article/2849/1/400008/2909198"]}
-{"year":"2023","title":"A Detailed Study on Preventing the Malicious URLs from Cyber Attacks","authors":["S Adnaan, G Tejasri, AVP Krishna, MGS Reddy - 2023 Third International …, 2023"],"snippet":"Today, there are more malicious URLs and cyber-attacks than ever. Cybercrimes are developing along with the software system’s progress. If we are able to stop one attack, then another one will follow in a different direction. These URLs were given …","url":["https://ieeexplore.ieee.org/abstract/document/10073865/"]}
-{"year":"2023","title":"A Fast Method to Filter Noisy Parallel Data WMT2023 Shared Task on Parallel Data Curation","authors":["MC Nguyen-Hoang, VN Van, LM Nguyen"],"snippet":"The effectiveness of a machine translation (MT) system is intricately linked to the quality of its training dataset. In an era where websites offer an extensive repository of translations such as movie subtitles, stories, and TED Talks, the fundamental …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.37.pdf"]}
-{"year":"2023","title":"A Few Words about ChatGPT","authors":["P Nag, S Mondal, A Sinha, S Mullick, R Mondal…"],"snippet":"ChatGPT is an artificial intelligence chatbot that uses natural language processing to generate human-like conversational talk. The language model can respond to inquiries and generate a wide range of written materials, including articles, social …","url":["https://www.researchgate.net/profile/Siddhartha-Chatterjee-3/publication/376488705_A_Few_Words_about_ChatGPT/links/657ac8a9fc4b416622c60f92/A-Few-Words-about-ChatGPT.pdf"]}
-{"year":"2023","title":"A Formal Perspective on Byte-Pair Encoding","authors":["V Zouhar, C Meister, JL Gastaldi, L Du, T Vieira… - arXiv preprint arXiv …, 2023"],"snippet":"Byte-Pair Encoding (BPE) is a popular algorithm used for tokenizing data in NLP, despite being devised initially as a compression method. BPE appears to be a greedy algorithm at face value, but the underlying optimization problem that BPE …","url":["https://arxiv.org/pdf/2306.16837"]}
-{"year":"2023","title":"A Framework for Responsible Development of Automated Student Feedback with Generative AI","authors":["ED Lindsay, A Johri, J Bjerva - arXiv preprint arXiv:2308.15334, 2023"],"snippet":"… roughly made up of 500 billion words of training data from Common Crawl, constituting a good chunk of the internet [7], rather than on a curated sample of similar assignments, with corresponding expert feedback. It is a generalized model …","url":["https://arxiv.org/pdf/2308.15334"]}
-{"year":"2023","title":"A Golden Age: Conspiracy Theories' Relationship with Misinformation Outlets, News Media, and the Wider Internet","authors":["HWA Hanley, D Kumar, Z Durumeric - arXiv preprint arXiv:2301.10880, 2023"],"snippet":"… For each website in our dataset, we collect all the domain’s HTML pages that were indexed by Common Crawl before August 2021. In addition to Common Crawl data, we further utilize our own website scrapes. We utilize our own crawls, in …","url":["https://arxiv.org/pdf/2301.10880"]}
-{"year":"2023","title":"A Graphical Approach to Document Layout Analysis","authors":["J Wang, M Krumdick, B Tong, H Halim, M Sokolov… - arXiv preprint arXiv …, 2023"],"snippet":"Document layout analysis (DLA) is the task of detecting the distinct, semantic content within a document and correctly classifying these items into an appropriate category (eg, text, title, figure). DLA pipelines enable users to convert documents into structured …","url":["https://arxiv.org/pdf/2308.02051"]}
-{"year":"2023","title":"A Hierarchical Encoding-Decoding Scheme for Abstractive Multi-document Summarization","authors":["C Shen, L Cheng, Y You, L Bing - arXiv preprint arXiv:2305.08503, 2023"],"snippet":"Pre-trained language models (PLMs) have accomplished impressive achievements in abstractive single-document summarization (SDS). However, such benefits may not be readily extended to muti-document summarization (MDS), where the …","url":["https://arxiv.org/pdf/2305.08503"]}
-{"year":"2023","title":"A Hybrid Extractive-Abstractive Framework with Pre & Post-Processing Techniques To Enhance Text Summarization","authors":["R Habu, R Ratnaparkhi, A Askhedkar, S Kulkarni - 2023 13th International …, 2023"],"snippet":"The goal of this paper is to enhance text summarization using a hybrid methodology. The process of producing a condensed version of a text while keeping its essential details is known as text summarization. In this study, we have presented a method …","url":["https://ieeexplore.ieee.org/abstract/document/10275584/"]}
-{"year":"2023","title":"A Hybrid Method on Emotion Detection for Indonesian Tweets of COVID-19","authors":["D Purwitasari, ASS Ansyah, AP Kurniawan… - Jurnal RESTI (Rekayasa …, 2023"],"snippet":"As a result of the COVID-19 pandemic, there have been restrictions on activities outside the home which has caused people to interact more and express their emotions through social media platforms, one of which is Twitter. Previous studies …","url":["https://www.jurnal.iaii.or.id/index.php/RESTI/article/download/4816/735"]}
-{"year":"2023","title":"A Hybrid Model for Multilingual OCR","authors":["D Etter, C Carpenter, N King - International Conference on Document Analysis and …, 2023"],"snippet":"… This large multilingual set is filtered from the Common Crawl corpus and is often used for the pretraining of large language models. The fonts to render the line images are selected from Google Fonts, Noto Fonts, and GNU Unifont. Table 1 …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41676-7_27"]}
-{"year":"2023","title":"A Hybrid Transformer Ensemble Approach for Phishing Website Detection","authors":["KS Mandapati, S Meesala, D Maddela, K Ponnada… - … International Conference on …, 2023"],"snippet":"The internet has developed into a veritable informational gold mine in the era of the digital age, and URLs (Uniform Resource Locator) act as access points to enormous volumes of material. For a variety of applications, including web content classification …","url":["https://ieeexplore.ieee.org/abstract/document/10331880/"]}
-{"year":"2023","title":"A Large Language Model Classification Framework (LLMCF)","authors":["K Khan"],"snippet":"The rapid advancement of Large Language Models (LLMs) has necessitated a comprehensive framework for categorizing and understanding their diverse characteristics. In response, this paper introduces the\" Large Language Model …","url":["http://ijmrap.com/wp-content/uploads/2023/09/IJMRAP-V6N4P38Y23.pdf"]}
-{"year":"2023","title":"A LARGE-SCALE BENCHMARK TWITTER DATASETS FOR COVID-19 SENTIMENT ANALYSIS","authors":["P Rajaram, V Dhavamani"],"snippet":"… Similarly, for word embeddings, pretrained Word2Vec, GloVe, and fastText embeddings trained on Common Crawl and Wikipedia are used and have 300-D vectors. In addition, we used hybrid models, such as hybrid ranking (HyRank) and …","url":["https://www.irjmets.com/uploadedfiles/paper/issue_10_october_2023/45125/final/fin_irjmets1696734430.pdf"]}
-{"year":"2023","title":"A Large-Scale Pretrained Deep Model for Phishing URL Detection","authors":["Y Wang, W Zhu, H Xu, Z Qin, K Ren, W Ma - ICASSP 2023-2023 IEEE International …, 2023"],"snippet":"Phishing attacks have always been a security issue that has attracted great attention in the cyber security community. Recently, the famous pre-trained models is being used as an anti-phishing solution. However, existing studies either simply transfer …","url":["https://ieeexplore.ieee.org/abstract/document/10095719/"]}
-{"year":"2023","title":"A large-scale web accessibility analysis considering technology adoption","authors":["B Martins, C Duarte - Universal Access in the Information Society, 2023"],"snippet":"… To collect a sample fit for a large-scale accessibility evaluation, we obtained individual URLs from the CommonCrawl Footnote 6 set. We used the crawl data from November and December 2020. We removed possibly duplicated URLs, as …","url":["https://link.springer.com/article/10.1007/s10209-023-01010-0"]}
-{"year":"2023","title":"A lightweight deep learning architecture for text embedding: Comparison between the usage of Transformers and Mixers for textual embedding","authors":["C Royer - 2023"],"snippet":"… These datasets contain all kinds of data, from Wikipedia which contains factual information to Common Crawl which is a collection of diverse websites. However, this demands considerable computing resources and long training times. To keep …","url":["https://www.diva-portal.org/smash/get/diva2:1799726/FULLTEXT01.pdf"]}
-{"year":"2023","title":"A linear time approximation of Wasserstein distance with word embedding selection","authors":["S Otao, M Yamada - Proceedings of the 2023 Conference on Empirical …, 2023"],"snippet":"Wasserstein distance, which can be computed by solving the optimal transport problem, is a powerful method for measuring the dissimilarity between documents. In the NLP community, it is referred to as word mover’s distance (WMD). One of the …","url":["https://aclanthology.org/2023.emnlp-main.935.pdf"]}
-{"year":"2023","title":"A low-resource approach to the grammatical error correction of Ukrainian","authors":["F Gomez, A Rozovskaya, D Roth - Proceedings of the Second Ukrainian Natural …, 2023"],"snippet":"We present our system that participated in the shared task on the grammatical error correction of Ukrainian. We have implemented two approaches that make use of large pre-trained language models and synthetic data, that have been used for error …","url":["https://aclanthology.org/2023.unlp-1.14.pdf"]}
-{"year":"2023","title":"A Machine Learning Approach to Government Business Process Re-engineering","authors":["A Riyadi, M Kovacs, U Serdült, V Kryssanov - … Conference on Big Data and Smart …, 2023"],"snippet":"Governments around the world accumulate large amounts of data but rarely use them to make their daily work more effective. For example, data classification tasks are typically performed manually or with systems that utilize rules created by humans …","url":["https://ieeexplore.ieee.org/abstract/document/10066589/"]}
-{"year":"2023","title":"A map of words: Retrieving the spatial layout of underground stations from natural","authors":["G Anceresi, D Gatti, T Vecchi, M Marelli, L Rinaldi"],"snippet":"Recent evidence has indicated that spatial representations, such as large-scale geographical maps, can be retrieved from natural language alone through cognitively plausible distributional-semantic models based on non-spatial …","url":["https://www.researchgate.net/profile/Giorgia-Anceresi/publication/370943870_A_map_of_words_Retrieving_the_spatial_layout_of_underground_stations_from_natural_language/links/646b6fc77b575d49292a039f/A-map-of-words-Retrieving-the-spatial-layout-of-underground-stations-from-natural-language.pdf"]}
-{"year":"2023","title":"A meaningful learning method for zero-shot semantic segmentation","authors":["X Liu, S Bai, S An, S Wang, W Liu, X Zhao, Y Ma - Science China Information …, 2023"],"snippet":"Zero-shot semantic segmentation, which is developed to segment unseen categories, has attracted increasing attention due to its strong practicability. Previous approaches usually applied semantic-visual mapping based on seen categories to …","url":["https://link.springer.com/article/10.1007/s11432-022-3748-5"]}
-{"year":"2023","title":"A Measurement-Based Quantum-Like Language Model for Text Matching","authors":["W Zhang, G Gan, H Gao, P Zhang, W Hui, Z Fan - … 22–26, 2022, Proceedings, Part III, 2023"],"snippet":"… The initialization method of word embeddings in the word representation utilizes the 300-dimensional GloVe word vectors pretrained from the 840B Common Crawl corpus [20]. Meanwhile, the word embeddings for the out-of-vocabulary words were …","url":["https://link.springer.com/chapter/10.1007/978-3-031-30111-7_4"]}
-{"year":"2023","title":"A Multi-Modal Multilingual Benchmark for Document Image Classification","authors":["Y Fujinuma, S Varia, N Sankaran, S Appalaraju, B Min… - arXiv preprint arXiv …, 2023"],"snippet":"… LayoutXLM is also pretrained on documents from Common Crawl (CC) and Donut on synthetic Wikipedia documents (Syn. Wiki). InfoXLM … LayoutXLM is pretrained on PDFs from 53 languages extracted from Common Crawl6, thus …","url":["https://arxiv.org/pdf/2310.16356"]}
-{"year":"2023","title":"A Multi-solution Study on GDPR AI-enabled Completeness Checking of DPAs","authors":["MI Azeem, S Abualhaija - arXiv preprint arXiv:2311.13881, 2023"],"snippet":"Specifying legal requirements for software systems to ensure their compliance with the applicable regulations is a major concern to requirements engineering (RE). Personal data which is collected by an organization is often shared with other …","url":["https://arxiv.org/pdf/2311.13881"]}
-{"year":"2023","title":"A Multi-Task Multi-Stage Transitional Training Framework for Neural Chat Translation","authors":["C Zhou, Y Liang, F Meng, J Zhou, J Xu, H Wang… - IEEE Transactions on …, 2022"],"snippet":"Neural chat translation (NCT) aims to translate a cross-lingual chat between speakers of different languages. Existing context-aware NMT models cannot achieve satisfactory performances due to the following inherent problems: 1) limited …","url":["https://www.computer.org/csdl/journal/tp/5555/01/10003654/1JwLorw3TFK"]}
-{"year":"2023","title":"A multimodal turn in Digital Humanities. Using contrastive machine learning models to explore, enrich, and analyze digital visual historical collections","authors":["T Smits, M Wevers - Digital Scholarship in the Humanities, 2023"],"snippet":"Until recently, most research in the Digital Humanities (DH) was monomodal, meaning that the object of analysis was either textual or visual. Seeking to integrate multimodality theory into the DH, this article demonstrates that recently developed …","url":["https://academic.oup.com/dsh/advance-article/doi/10.1093/llc/fqad008/7078540"]}
-{"year":"2023","title":"A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity","authors":["Y Bang, S Cahyawijaya, N Lee, W Dai, D Su, B Wilie… - arXiv preprint arXiv …, 2023"],"snippet":"… Based on the percentage of data in the CommonCrawl8, we group languages into 3 8CommonCrawl (http://commoncrawl.org) is the primary source of language pre-training data used in GPT3 … The languages are sorted based on the language …","url":["https://arxiv.org/pdf/2302.04023"]}
-{"year":"2023","title":"A Neighbourhood-Aware Differential Privacy Mechanism for Static Word Embeddings","authors":["D Bollegala, S Otake, T Machide, K Kawarabayashi - arXiv preprint arXiv:2309.10551, 2023"],"snippet":"We propose a Neighbourhood-Aware Differential Privacy (NADP) mechanism considering the neighbourhood of a word in a pretrained static word embedding space to determine the minimal amount of noise required to guarantee a specified …","url":["https://arxiv.org/pdf/2309.10551"]}
-{"year":"2023","title":"A New Era of Artificial Intelligence in Education: A Multifaceted Revolution","authors":["F Kamalov, I Gurrib - arXiv preprint arXiv:2305.18303, 2023"],"snippet":"The recent high performance of ChatGPT on several standardized academic test has thrust the topic of artificial intelligence (AI) into the mainstream conversation about the future of education. The objective of the present study is to investigate the …","url":["https://arxiv.org/pdf/2305.18303"]}
-{"year":"2023","title":"A New Frontier: AI and Ancient Language Pedagogy","authors":["EAS Ross - Journal of Classics Teaching, 2023"],"snippet":"… OpenAI notes, and ChatGPT also reiterates when prompted, that the AI model was trained using a blend of filtered Common Crawl data, WebText, ebooks, and Wikipedia articles from before Q4 2021, so it is unable to answer questions or …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/A63EF69F5FE5529F0F45FB1EB655A9F7/S2058631023000430a.pdf/div-class-title-a-new-frontier-ai-and-ancient-language-pedagogy-div.pdf"]}
-{"year":"2023","title":"A new phishing-website detection framework using ensemble classification and clustering","authors":["M Alsharaiah, A Abu-Shareha, M Abualhaj, L Baniata… - International Journal of Data …, 2023"],"snippet":"… The phishing samples were collected from the OpenPhish and Phish Tank, while the legitimate samples were gathered from different resources such as Common Crawl and Alexa. These samples were collected from January to May 2015 and May …","url":["http://growingscience.com/ijds/Vol7/ijdns_2023_8.pdf"]}
-{"year":"2023","title":"A novel application of machine learning and zero-shot classification methods for automated abstract screening in systematic reviews","authors":["CF Moreno-Garcia, C Jayne, E Elyan… - Decision Analytics Journal, 2023"],"snippet":"… examples of pre-trained transformer-based NLP systems are Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformers (GPT), which were trained with large language datasets, such as the …","url":["https://www.sciencedirect.com/science/article/pii/S2772662223000024"]}
-{"year":"2023","title":"A novel Data and Model Centric artificial intelligence based approach in developing high-performance Named Entity Recognition for Bengali Language","authors":["KA Lima, K Md Hasib, S Azam, A Karim, S Montaha… - Plos one, 2023"],"snippet":"Named Entity Recognition (NER) plays a significant role in enhancing the performance of all types of domain specific applications in Natural Language Processing (NLP). According to the type of application, the goal of NER is to identify …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0287818"]}
-{"year":"2023","title":"A PhD Student's Perspective on Research in NLP in the Era of Very Large Language Models","authors":["O Ignat, Z Jin, A Abzaliev, L Biester, S Castro, N Deng… - arXiv preprint arXiv …, 2023"],"snippet":"Recent progress in large language models has enabled the deployment of many generative NLP applications. At the same time, it has also led to a misleading public discourse that ``it's all been solved.'' Not surprisingly, this has in turn made many …","url":["https://arxiv.org/pdf/2305.12544"]}
-{"year":"2023","title":"A PHISHING DETECTION SYSTEM BASED ON INTELLIGENT DEEP LEARNING TECHNIQUES","authors":["GC Uzoaru, G Nwamuruamu, C Johnson-Okoronkwo - Int'l Journal of Education …, 2023"],"snippet":"… Approximately one million authentic and fraudulent URLs were employed in the dataset gathered from PhishTank and Common Crawl. Over 10,000 images and one million URLs were used in training for the CNN classifier and LSTM to create the …","url":["https://ijresd.org/index.php/IJRESD/article/download/61/42"]}
-{"year":"2023","title":"A Predictive Factor Analysis of Social Biases and Task-Performance in Pretrained Masked Language Models","authors":["Y Zhou, J Camacho-Collados, D Bollegala - arXiv preprint arXiv:2310.12936, 2023"],"snippet":"… Domain: Full-text biomedical papers from the Semantic Scholar Open Research Corpus (S2ORC), PubMed Abstracts (PMed), PMC Fulltext articles and the Medical Information Mart for Intensive Care III (MIMIC3); Finally, we also consider a …","url":["https://arxiv.org/pdf/2310.12936"]}
-{"year":"2023","title":"A Preference Judgment Interface for Authoritative Assessment","authors":["M Seifikar - 2023"],"snippet":"… of Common Crawl4. There is more information about document collection on the Track website. Each document in the collection that is provided for the 2https://huggingface.co/datasets/allenai/c4 3https://www.tensorflow.org/datasets/catalog/c4 4https://commoncrawl.org …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19151/Seifikar_Mahsa.pdf?sequence=1&isAllowed=y"]}
-{"year":"2023","title":"A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity","authors":["S Longpre, G Yauney, E Reif, K Lee, A Roberts, B Zoph… - arXiv preprint arXiv …, 2023"],"snippet":"… For each version we begin with Common Crawl data and remove all data that was scraped after the cutoff year. Following Luu et al. (2021), we measure the effect of temporal misalignment by using evaluation tasks (from News, Twitter, and …","url":["https://arxiv.org/pdf/2305.13169"]}
-{"year":"2023","title":"A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis","authors":["I Gur, H Furuta, A Huang, M Safdari, Y Matsuo, D Eck… - arXiv preprint arXiv …, 2023"],"snippet":"… For HTML-denoising, we prepare the corpus from CommonCrawl with (Extracted) or without (Raw) subtree extraction around label elements on the documents. We also compare the initialization of base architectures before HTML-denoising; from …","url":["https://arxiv.org/pdf/2307.12856"]}
-{"year":"2023","title":"A RelEntLess Benchmark for Modelling Graded Relations between Named Entities","authors":["A Ushio, JC Collados, S Schockaert - arXiv preprint arXiv:2305.15002, 2023"],"snippet":"Relations such as \"is influenced by\", \"is known for\" or \"is a competitor of\" are inherently graded: we can rank entity pairs based on how well they satisfy these relations, but it is hard to draw a line between those pairs that satisfy them and those …","url":["https://arxiv.org/pdf/2305.15002"]}
-{"year":"2023","title":"A Research On The New Generation Artificial Intelligence Technology Generative Pretraining Transformer 3","authors":["N Aydın, OA Erdem - 2022 3rd International Informatics and Software …, 2022"],"snippet":"In the digitalizing world, Artificial Intelligence (AI) paves the way for the automation of routine work done by humans and makes life easier. Recently, there is no area where AI and its applications are not used in daily life, from health to education, from …","url":["https://ieeexplore.ieee.org/abstract/document/9998298/"]}
-{"year":"2023","title":"A Review of Conversational Agents in Education","authors":["C Rodrigues, A Reis, R Pereira, P Martins, J Sousa… - International Conference on …, 2022"],"snippet":"The use of mobile conversations is increasing all around the world. A conversational agent (CA) is mostly useful due to the fast response times and their simple nature. Recently, we have seen the development and increasing use of dialog systems on …","url":["https://link.springer.com/chapter/10.1007/978-3-031-22918-3_37"]}
-{"year":"2023","title":"A Review of Generative AI from Historical Perspectives","authors":["D Dasgupta, D Venugopal, KD Gupta"],"snippet":"Many applications of Generative AI (such as DALLE, GPT-3, ChatGPT, etc.) are making headline news in recent months and have been receiving both praise and criticism for their far reaching implications. Some of these applications include query …","url":["https://www.researchgate.net/profile/Kishor-Datta-Gupta/publication/368543465_A_Review_of_Generative_AI_from_Historical_Perspectives/links/63edde7f19130a1a4a82a316/A-Review-of-Generative-AI-from-Historical-Perspectives.pdf"]}
-{"year":"2023","title":"A review of the approaches to neural machine translation","authors":["PK Buttar, MK Sachan - Natural Language Processing and Information …, 2023"],"snippet":"… (2019b) is a collection of 4.5 billion parallel sentences in 576 language pairs pulled from the snapshots of the CommonCrawl public dataset. WikiMatrix (Schwenk et al., 2019a) is another parallel collection of 135 million parallel sentences for 1,620 …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781003244332-4/review-approaches-neural-machine-translation-preetpal-kaur-buttar-manoj-kumar-sachan"]}
-{"year":"2023","title":"A review on big data based on deep neural network approaches","authors":["M Rithani, RP Kumar, S Doss - Artificial Intelligence Review, 2023"],"snippet":"… The highest recall and accuracy scores for Common Crawl (94.98 and 97.97, respectively) were linked with the highest F-measure score (96.46). There is no denying that this is an exciting piece of research, however the strategy used to …","url":["https://link.springer.com/article/10.1007/s10462-023-10512-5"]}
-{"year":"2023","title":"A Review on Large Language Models: Architectures, Applications, Taxonomies, Open Issues and Challenges","authors":["MAK Raiaan, MSH Mukta, K Fatema, NM Fahad… - 2023"],"snippet":"… Besides, several corpus including the Common Crawl web corpus, the BooksCorpus dataset, and the English Wikipedia are also used … ) Books (Dec 2015) Books (Dec 2021) CommonCrawl (Sep 2019) CommonCrawl (Feb 2019) …","url":["https://www.techrxiv.org/articles/preprint/A_Review_on_Large_Language_Models_Architectures_Applications_Taxonomies_Open_Issues_and_Challenges/24171183/1/files/42414054.pdf"]}
-{"year":"2023","title":"A Review on Malicious URLs Detection Using Machine Learning Methods","authors":["T Tabassum, MM Alam, MS Ejaz, MK Hasan - Journal of Engineering Research and …, 2023"],"snippet":"Malicious URLs are a serious threat to cybersecurity because they can compromise user security and inflict large financial losses. The extensiveness and adaptability of traditional detection approaches which rely on blacklists are limited when it comes to …","url":["http://archive.article4submit.com/id/eprint/2544/1/Alam25122023JERR110634.pdf"]}
-{"year":"2023","title":"A Sentence Alignment Approach to Document Alignment and Multi-faceted Filtering for Curating Parallel Sentence Pairs from Web-crawled Data","authors":["S Steingrímsson"],"snippet":"This paper describes the AST submission to the WMT23 Shared Task on Parallel Data Curation. We experiment with two approaches for curating data from the provided web-scraped texts. We use sentence alignment to identify document …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.38.pdf"]}
-{"year":"2023","title":"A Simple Baseline for Knowledge-Based Visual Question Answering","authors":["A Xenos, T Stafylakis, I Patras, G Tzimiropoulos - arXiv preprint arXiv:2310.13570, 2023"],"snippet":"This paper is on the problem of Knowledge-Based Visual Question Answering (KB-VQA). Recent works have emphasized the significance of incorporating both explicit (through external databases) and implicit (through LLMs) knowledge to answer questions …","url":["https://arxiv.org/pdf/2310.13570"]}
-{"year":"2023","title":"A Study of Continual Learning Under Language Shift","authors":["E Gogoulou, T Lesort, M Boman, J Nivre - arXiv preprint arXiv:2311.01200, 2023"],"snippet":"The recent increase in data and model scale for language model pre-training has led to huge training costs. In scenarios where new data become available over time, updating a model instead of fully retraining it would therefore provide significant …","url":["https://arxiv.org/pdf/2311.01200"]}
-{"year":"2023","title":"A Study of Multilingual versus Meta-Learning for Language Model Pre-Training for Adaptation to Unseen Low Resource Languages","authors":["J Khatri, R Murthy, AP Azad, P Bhattacharyya"],"snippet":"In this paper, we compare two approaches to train a multilingual language model:(i) simple multilingual learning using data-mixing, and (ii) meta-learning. We examine the performance of these models by extending them to unseen language pairs and …","url":["https://www.cse.iitb.ac.in/~pb/papers/mts23-maml.pdf"]}
-{"year":"2023","title":"A Study on Bias Detection and Classification in Natural Language Processing","authors":["AS Evans, M Helena, C Luisa - 2023"],"snippet":"… An example of this is the work done by Luccioni and Viviano [19] on the Common Crawl Corpus1, with a focus on finding instances of Hate Speech and sexually explicit content. The Common Crawl is a multilingual corpus, composed of 200 to …","url":["https://www.researchsquare.com/article/rs-3351695/latest.pdf"]}
-{"year":"2023","title":"A Study on the Utilization of OpenAI ChatGPT as a Second Language Learning Tool","authors":["S Kim, J Shim, J Shim - Journal of Multimedia Information System, 2023"],"snippet":"In November 2022, ChatGPT was introduced and caused a sensation, gathering 100 million users only within two months. ChatGPT’s capability of generating high-quality sentences demonstrated potential to be applied in a wide range of fields. In this …","url":["http://www.jmis.org/archive/view_article?pid=jmis-10-1-79"]}
-{"year":"2023","title":"A Survey of Large Language Models in Medicine: Progress, Application, and Challenge","authors":["H Zhou, B Gu, X Zou, Y Li, SS Chen, P Zhou, J Liu… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs), such as ChatGPT, have achieved substantial attention due to their impressive human language understanding and generation capabilities. Therefore, the application of LLMs in medicine to assist physicians and …","url":["https://arxiv.org/pdf/2311.05112"]}
-{"year":"2023","title":"A Survey of Large Language Models","authors":["WX Zhao, K Zhou, J Li, T Tang, X Wang, Y Hou, Y Min… - arXiv preprint arXiv …, 2023"],"snippet":"… Based on CommonCrawl, there are four filtered datasets that are commonly used in existing work: C4 [71], CCStories [102], CC-News [27], and RealNews [103]. The Colossal Clean Crawled Corpus (C4) includes five variants10, namely en (806G), en.noclean …","url":["https://arxiv.org/pdf/2303.18223"]}
-{"year":"2023","title":"A Survey of Text Representation and Embedding Techniques in NLP","authors":["R Patil, S Boit, V Gudivada, J Nandigam - IEEE Access, 2023"],"snippet":"Natural Language Processing (NLP) is a research field where a language in consideration is processed to understand its syntactic, semantic, and sentimental aspects. The advancement in the NLP area has helped solve problems in the …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10098736.pdf"]}
-{"year":"2023","title":"A Survey on Arabic Named Entity Recognition: Past, Recent Advances, and Future Trends","authors":["X Qu, Y Gu, Q Xia, Z Li, Z Wang, B Huai - arXiv preprint arXiv:2302.03512, 2023"],"snippet":"As more and more Arabic texts emerged on the Internet, extracting important information from these Arabic texts is especially useful. As a fundamental technology, Named entity recognition (NER) serves as the core component in information …","url":["https://arxiv.org/pdf/2302.03512"]}
-{"year":"2023","title":"A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware","authors":["S Zhang, A Sohrabizadeh, C Wan, Z Huang, Z Hu… - arXiv preprint arXiv …, 2023"],"snippet":"… -dimensional vectors concatenating the average embedding of the post title and that of all the post’s comments, the post’s score, and the number of comments made on the post, where the average embedding is obtained by averaging the 300-dimensional …","url":["https://arxiv.org/pdf/2306.14052"]}
-{"year":"2023","title":"A Survey on Large Language Models: Applications, Challenges, Limitations, and Practical Usage","authors":["MU Hadi, R Qureshi, A Shah, M Irfan, A Zafar… - 2023"],"snippet":"Within the vast expanse of computerized language processing, a revolutionary entity known as Large Language Models (LLMs) has emerged, wielding immense power in its capacity to comprehend intricate linguistic patterns and conjure coherent and …","url":["https://www.techrxiv.org/articles/preprint/A_Survey_on_Large_Language_Models_Applications_Challenges_Limitations_and_Practical_Usage/23589741/1/files/41501037.pdf"]}
-{"year":"2023","title":"A Survey on LLM-gernerated Text Detection: Necessity, Methods, and Future Directions","authors":["J Wu, S Yang, R Zhan, Y Yuan, DF Wong, LS Chao - arXiv preprint arXiv:2310.14724, 2023"],"snippet":"The powerful ability to understand, follow, and generate complex language emerging from large language models (LLMs) makes LLM-generated text flood many areas of our daily lives at an incredible speed and is widely accepted by …","url":["https://arxiv.org/pdf/2310.14724"]}
-{"year":"2023","title":"A Systematic Literature Review on Phishing Website Detection Techniques","authors":["A Safi, S Singh - Journal of King Saud University-Computer and …, 2023"],"snippet":"Phishing is a fraud attempt in which an attacker acts as a trusted person or entity to obtain sensitive information from an internet user. In this Systematic Literature Survey (SLR), different phishing detection approaches, namely Lists Based, Visual …","url":["https://www.sciencedirect.com/science/article/pii/S1319157823000034"]}
-{"year":"2023","title":"A systematic review of applications of natural language processing and future challenges with special emphasis in text-based emotion detection","authors":["S Kusal, S Patil, J Choudrie, K Kotecha, D Vora… - Artificial Intelligence Review, 2023"],"snippet":"Artificial Intelligence (AI) has been used for processing data to make decisions, Interact with humans, and understand their feelings and emotions. With the advent of the Internet, people share and express their thoughts on day-to-day activities and …","url":["https://link.springer.com/article/10.1007/s10462-023-10509-0"]}
-{"year":"2023","title":"A Systematic Review of Transformer-Based Pre-Trained Language Models through Self-Supervised Learning","authors":["E Kotei, R Thirunavukarasu - Information, 2023"],"snippet":"… A typical example is the CommonCrawl corpus [75]. Models such as IndoNLG [76], MuRIL [77], IndicNLPSuite [78], mT5 [79], mT6 [80], XLM… derived from Common Crawl corpus [75] Introduced the mT5 multilingual variant of the T5 model pretrained …","url":["https://www.mdpi.com/2078-2489/14/3/187"]}
-{"year":"2023","title":"A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets","authors":["MTR Laskar, MS Bari, M Rahman, MAH Bhuiyan… - arXiv preprint arXiv …, 2023"],"snippet":"The development of large language models (LLMs) such as ChatGPT has brought a lot of attention recently. However, their evaluation in the benchmark academic datasets remains under-explored due to the difficulty of evaluating the generative …","url":["https://arxiv.org/pdf/2305.18486"]}
-{"year":"2023","title":"A T5-based interpretable reading comprehension model with more accurate evidence training","authors":["B Guan, X Zhu, S Yuan - Information Processing & Management, 2024"],"snippet":"Pre-trained language models (PLMs) have achieved outstanding performance on Machine Reading Comprehension (MRC) tasks, but these models’ interpretability remains uncertain. In this paper, we exploit the strengths of the pre-trained T5 (Text-to-Text …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323003217"]}
-{"year":"2023","title":"A Thorough Analysis of E-commerce Customer Reviews in Arabic Language Using Deep Learning Techniques for Successful Marketing Decisions","authors":["N Hicham, H Nassera, S Karim"],"snippet":"… AraVec provides six-word embedding models that have already been pretrained, and these models use data from Twitter, Wikipedia, and Common Crawl. The overall quantity of tokens that were utilized in the creation of the models is more remarkable …","url":["https://www.iaeng.org/IJAM/issues_v53/issue_4/IJAM_53_4_42.pdf"]}
-{"year":"2023","title":"A Tool Kit for Relation Induction in Text Analysis","authors":["DS Stoltz, MA Taylor, JSK Dudley - 2023"],"snippet":"Distances derived from word embeddings can measure a range of gradational relations—similarity, hierarchy, entailment, and stereotype—and can be used at the document-and author-level in ways that overcome some of the limitations of …","url":["https://osf.io/preprints/socarxiv/9bwzr/download"]}
-{"year":"2023","title":"A transformer-based deep learning model for Persian moral sentiment analysis","authors":["B Karami, F Bakouie, S Gharibzadeh - Journal of Information Science, 2023"],"snippet":"Moral expressions in online communications can have a serious impact on framing discussions and subsequent online behaviours. Despite research on extracting moral sentiment from English text, other low-resource languages, such as Persian …","url":["https://journals.sagepub.com/doi/abs/10.1177/01655515231188344"]}
-{"year":"2023","title":"A Transformer-based Generative Adversarial Learning to Detect Sarcasm from Bengali Text with Correct Classification of Confusing Text","authors":["SK Lora, I Jahan, R Hussain, R Shahriyar… - Heliyon"],"snippet":"Sarcasm detection research in Bengali is still limited due to a lack of relevant resources. In this context, getting high-quality annotated data is costly and time-consuming. Therefore, in this paper, we present a transformer-based generative adversarial …","url":["https://www.cell.com/heliyon/pdf/S2405-8440(23)09739-6.pdf"]}
-{"year":"2023","title":"A transformer-based multi-task framework for joint detection of aggression and hate on social media data","authors":["S Ghosh, A Priyankar, A Ekbal, P Bhattacharyya - Natural Language Engineering, 2023"],"snippet":"… It is a massive multi-lingual model that was trained on 2.5 TB of CommonCrawl data in 100 distinct languages. It outperforms other transformer models, such as Bidirectional Encoder Representations from Transformers (BERT) and Multi-lingual …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/C551F3E0504E5595762037691EE27271/S1351324923000104a.pdf/div-class-title-a-transformer-based-multi-task-framework-for-joint-detection-of-aggression-and-hate-on-social-media-data-div.pdf"]}
-{"year":"2023","title":"A User-Centered Evaluation of Spanish Text Simplification","authors":["A de Wynter, A Hevia, SQ Chen - arXiv preprint arXiv:2308.07556, 2023"],"snippet":"We present an evaluation of text simplification (TS) in Spanish for a production system, by means of two corpora focused in both complex-sentence and complex-word identification. We compare the most prevalent Spanish-specific readability scores …","url":["https://arxiv.org/pdf/2308.07556"]}
-{"year":"2023","title":"A Vision for Semantically Enriched Data Science","authors":["U Khurana, K Srinivas, S Galhotra, H Samulowitz - arXiv preprint arXiv:2303.01378, 2023"],"snippet":"The recent efforts in automation of machine learning or data science has achieved success in various tasks such as hyper-parameter optimization or model selection. However, key areas such as utilizing domain knowledge and data semantics are …","url":["https://arxiv.org/pdf/2303.01378"]}
-{"year":"2023","title":"ABCD Team at FinancES 2023: An Unified Generative Framework for the Financial Targeted Sentiment Analysis in Spanish","authors":["NLT Nguyen - 2023"],"snippet":"This paper presents our participation in the IBERLEF 2023 Task-FinancES in Spanish, focusing on two sub-tasks: Financial targeted sentiment analysis and Financial Sentiment Analysis at the document level for companies and consumers …","url":["https://ceur-ws.org/Vol-3496/finances-paper2.pdf"]}
-{"year":"2023","title":"Abstractive summarization with deep reinforcement learning using semantic similarity rewards","authors":["FB Fikri, K Oflazer, B Yanıkoğlu - Natural Language Engineering, 2023"],"snippet":"Abstractive summarization is an approach to document summarization that is not limited to selecting sentences from the document but can generate new sentences as well. We address the two main challenges in abstractive summarization: how to …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/740B4B5903AE80FE14709F5DAEE7AD41/S1351324923000505a.pdf/abstractive_summarization_with_deep_reinforcement_learning_using_semantic_similarity_rewards.pdf"]}
-{"year":"2023","title":"Abstractive Text Summarization based on Transformer Deep Neural Networks","authors":["V Davidović - 2023"],"snippet":"… GPT-3 (Generative Pre-trained Transformers) [32] is large autoregressive language model (LLM) with 175 billion of parameters that is trained on 300 billion tokens of text (570GB in total Common Crawl dataset) and tested in the fewshot …","url":["https://www.inf.uniri.hr/images/studiji/poslijediplomski/kvalifikacijski/Davidovic_Vlatka_Kvalifikacijski_rad.pdf"]}
-{"year":"2023","title":"ABSTRACTIVE TEXT SUMMARIZATION FOR MORPHOLOGICALLY RICH LANGUAGES","authors":["B Baykara - 2023"],"snippet":"The exponential growth in the number of documents available on the Web has turned finding the relevant piece of information into a challenging, tedious, and timeconsuming activity. Accordingly, automatic text summarization has become an …","url":["https://www.cmpe.boun.edu.tr/~gungort/theses/Abstractive%20Text%20Summarization%20for%20Morphologically%20Rich%20Languages.pdf"]}
-{"year":"2023","title":"Abstractive Text Summarization for Tamil Language Using m-T5","authors":["C Saraswathi, V Prinitha, J Briskilal - Inventive Systems and Control: Proceedings of …, 2023"],"snippet":"Summarization is the act of reducing a long form of text to a shorter version by lowering the length of the original text while retaining and keeping the summary’s core and the informational parts which conveys the content’s meaning. Summarizing …","url":["https://link.springer.com/chapter/10.1007/978-981-99-1624-5_35"]}
-{"year":"2023","title":"Abstractive Text Summarization of Hindi Corpus Using Transformer Encoder-Decoder Model","authors":["R Bhansali, A Bhave, G Bharat, V Mahajan, ML Dhore - International Symposium on …, 2023"],"snippet":"… FastText has been trained on Hindi text procured from Wikipedia and Common Crawl using positional weights with a Continuous Bag-of-Words (CBOW) model giving word representations of dimension 300. This model is known to give efficient …","url":["https://link.springer.com/chapter/10.1007/978-981-19-8094-7_13"]}
-{"year":"2023","title":"Abusive Span Detection for Vietnamese Narrative Texts","authors":["NT Nguyen, K Thi-Kim Phan, DV Nguyen… - Proceedings of the 12th …, 2023"],"snippet":"Abuse in its various forms, including physical, psychological, verbal, sexual, financial, and cultural, has a negative impact on mental health. However, there are limited studies on applying natural language processing (NLP) in this field in Vietnam …","url":["https://dl.acm.org/doi/abs/10.1145/3628797.3628921"]}
-{"year":"2023","title":"AcademicGPT: Empowering Academic Research","authors":["S Wei, X Xu, X Qi, X Yin, J Xia, J Ren, P Tang, Y Zhong… - arXiv preprint arXiv …, 2023"],"snippet":"… for classification using the obtained 200K data; (4) we conduct classification on the common crawl data and clean out 12.7B tokens from CC. … Please assess the provided CommonCrawl sample based on the following criteria and return the …","url":["https://arxiv.org/pdf/2311.12315"]}
-{"year":"2023","title":"Accelerating the integration of ChatGPT and other large‐scale AI models into biomedical research and healthcare","authors":["DQ Wang, LY Feng, JG Ye, JG Zou, YF Zheng - MedComm–Future Medicine, 2023"],"snippet":"… For example, GPT-3 was trained on 300B tokens, with 60% coming from the filtered Common Crawl data set, and the rest from webtext2 (used to train GPT-2), Books1, Books2, Wikipedia, and code datasets (such as GitHub Code). The …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1002/mef2.43"]}
-{"year":"2023","title":"Accessing Higher Dimensions for Unsupervised Word Translation","authors":["SI Wang - arXiv preprint arXiv:2305.14200, 2023"],"snippet":"The striking ability of unsupervised word translation has been demonstrated with the help of word vectors / pretraining; however, they require large amounts of data and usually fails if the data come from different domains. We propose coocmap, a …","url":["https://arxiv.org/pdf/2305.14200"]}
-{"year":"2023","title":"Accurate and Reliable Classification of Unstructured Reports on Their Diagnostic Goal Using BERT Models","authors":["MT Rietberg, VB Nguyen, J Geerdink, O Vijlbrief… - Diagnostics, 2023"],"snippet":"Understanding the diagnostic goal of medical reports is valuable information for understanding patient flows. This work focuses on extracting the reason for taking an MRI scan of Multiple Sclerosis (MS) patients using the attached free-form reports …","url":["https://www.mdpi.com/2075-4418/13/7/1251"]}
-{"year":"2023","title":"Accurate Knowledge Distillation with n-best Reranking","authors":["H Setiawan - arXiv preprint arXiv:2305.12057, 2023"],"snippet":"We propose extending the Sequence-level Knowledge Distillation (Kim and Rush, 2016) with n-best reranking to consider not only the top-1 hypotheses but also the top n-best hypotheses of teacher models. Our approach leverages a diverse set of …","url":["https://arxiv.org/pdf/2305.12057"]}
-{"year":"2023","title":"Acoustic and linguistic representations for speech continuous emotion recognition in call center conversations","authors":["M Macary, M Tahon, Y Estève, D Luzzati - arXiv preprint arXiv:2310.04481, 2023"],"snippet":"The goal of our research is to automatically retrieve the satisfaction and the frustration in real-life call-center conversations. This study focuses an industrial application in which the customer satisfaction is continuously tracked down to …","url":["https://arxiv.org/pdf/2310.04481"]}
-{"year":"2023","title":"ADA: An Attention-Based Data Augmentation Approach to Handle Imbalanced Textual Datasets","authors":["AK Sah, M Abulaish - … : 29th International Conference, ICONIP 2022, Virtual …, 2023"],"snippet":"… For classification tasks throughout this work, we have used \\(300-\\)dimensional GloVe embeddings trained on the Common Crawl dataset with 840B tokens. For BERT-related tasks, we have used the BERT base uncased pre-trained model …","url":["https://link.springer.com/chapter/10.1007/978-981-99-1639-9_40"]}
-{"year":"2023","title":"Adaptation of Enterprise Modeling Methods for Large Language Models","authors":["BS Barn, S Barat, K Sandkuhl - IFIP Working Conference on The Practice of …, 2023"],"snippet":"… GPT-3 uses 175 billion parameters and is trained on data from the Common Crawl data set Footnote 1 comprising nearly a trillion words. The development in large language models and their evolution has been widely documented and the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-48583-1_1"]}
-{"year":"2023","title":"Adapting an English Corpus and a Question Answering System for Slovene","authors":["U Šmajdek, M Zupanič, M Zirkelbach, M Jazbinšek - Slovenščina 2.0: empirične …, 2023"],"snippet":"Pomanjkanje ustreznih podatkov za učenje je ena od ključnih težav pri razvoju slovenskih modelov za odgovarjanje na vprašanja (QA). Sodobna orodja za strojno prevajanje lahko to težavo rešijo, vendar pa se pri njihovi uporabi soočimo z novih …","url":["https://journals.uni-lj.si/slovenscina2/article/download/12064/13780"]}
-{"year":"2023","title":"Adapting Grounded Visual Question Answering Models to Low Resource Languages","authors":["Y Wang, J Pfeiffer, N Carion, Y LeCun, A Kamath - … of the IEEE/CVF Conference on …, 2023"],"snippet":"… by classifying and filtering the Common Crawl dataset by languages. The statistics for different languages in OSCAR are shown in Table 1. Compared to unimodal datasets, multilingual multimodal datasets are much harder to obtain and …","url":["https://openaccess.thecvf.com/content/CVPR2023W/MULA/papers/Wang_Adapting_Grounded_Visual_Question_Answering_Models_to_Low_Resource_Languages_CVPRW_2023_paper.pdf"]}
-{"year":"2023","title":"Adaptive Training Distributions with Scalable Online Bilevel Optimization","authors":["D Grangier, P Ablin, A Hannun - arXiv preprint arXiv:2311.11973, 2023"],"snippet":"Large neural networks pretrained on web-scale corpora are central to modern machine learning. In this paradigm, the distribution of the large, heterogeneous pretraining data rarely matches that of the application domain. This work considers …","url":["https://arxiv.org/pdf/2311.11973"]}
-{"year":"2023","title":"Adding guardrails to advanced chatbots","authors":["Y Wang, L Singh - arXiv preprint arXiv:2306.07500, 2023"],"snippet":"… According to OpenAI, 60% of the training data come from Common Crawl, a large data set consisting of web pages, extracted metadata and text extractions through a big web crawler since 2008. Another 22% of data are from WebText2, containing all …","url":["https://arxiv.org/pdf/2306.07500"]}
-{"year":"2023","title":"Adding Instructions during Pretraining: Effective Way of Controlling Toxicity in Language Models","authors":["S Prabhumoye, M Patwary, M Shoeybi, B Catanzaro - arXiv preprint arXiv …, 2023"],"snippet":"Pretrained large language models have become indispensable for solving various natural language processing (NLP) tasks. However, safely deploying them in real world applications is challenging because they generate toxic content. To address …","url":["https://arxiv.org/pdf/2302.07388"]}
-{"year":"2023","title":"Addressing Controversial Topics in Search Engines","authors":["Y Ajjour - 2023"],"snippet":"… top 500 documents from the Common Crawl Index1 on eight controversial topics. Then, several sequence-to-sequence classifiers were developed to perform the task both in a cross-topic and in-topic settings. The results of the experiments show very …","url":["https://e-pub.uni-weimar.de/opus4/files/6403/diss-ajjour-frame.pdf"]}
-{"year":"2023","title":"ADM+ S submission to the Safe and responsible AI in Australia discussion paper","authors":["K Weatherall - 2023"],"snippet":"The ADM+ S is pleased to have this opportunity to engage with an important and complex question which confronts Australia: how should the Australian federal government take actionregulatory or otherwise-to promote artificial intelligence (and …","url":["https://apo.org.au/node/323896"]}
-{"year":"2023","title":"Adopting machine translation in the healthcare sector: A methodological multi-criteria review","authors":["M Zappatore, G Ruggieri - Computer Speech & Language, 2023"],"snippet":"Background: The recent advances in machine translation (MT) offer an appealing and low-cost solution to overcome language barriers in multiple contexts (eg, travelling, cultural interaction, digital content localisation). However, highly-technical …","url":["https://www.sciencedirect.com/science/article/pii/S0885230823001018"]}
-{"year":"2023","title":"Advanced Methods to Audit Online Web Services","authors":["P Vallina - 2023"],"snippet":"Online web services have grown dramatically in size and diversity in the last years, becoming essential components of our daily life and allowing us to conduct elementary tasks like working, getting informed, or keeping in contact with relatives …","url":["https://dspace.networks.imdea.org/bitstream/handle/20.500.12761/1668/Pelayo_Vallina_Thesis.pdf?sequence=1"]}
-{"year":"2023","title":"Advanced Network Technologies and Intelligent Computing: Second International Conference, ANTIC 2022, Varanasi, India, December 22–24, 2022, Proceedings …","authors":["I Woungang, SK Dhurandher, KK Pattanaik, A Verma… - 2023"],"snippet":"The 2nd International Conference on Advanced Network Technologies and Intelligent Computing (ANTIC-2022) was organized by Department of Computer Science, Institute of Science, Banaras Hindu University, Varanasi, India in hybrid …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=uhm1EAAAQBAJ&oi=fnd&pg=PR6&dq=commoncrawl&ots=Cw825CR0q7&sig=4GzV7hu-Io1Be66sWi1KTmgmssc"]}
-{"year":"2023","title":"Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers","authors":["S Bengesi, H El-Sayed, MK Sarker, Y Houkpati… - arXiv preprint arXiv …, 2023"],"snippet":"… CommonCrawl was used to train the model, which was tested on all domains of NLP, and it had promising few-short and zero-shot performance. This version was further improved to GPT 3.5, which was used to develop ChatGPT. Considerable …","url":["https://arxiv.org/pdf/2311.10242"]}
-{"year":"2023","title":"Advances in apparent conceptual physics reasoning in ChatGPT-4","authors":["CG West - arXiv preprint arXiv:2303.17012, 2023"],"snippet":"… While the exact details of the text which was used to “train” ChatGPT are a proprietary secret, it is known that its reading material was largely drawn from the “Common Crawl” corpus [18], an open repository of data scraped from text found on the public …","url":["https://arxiv.org/pdf/2303.17012"]}
-{"year":"2023","title":"Advances in monolingual and crosslingual automatic disability annotation in Spanish","authors":["I Goenaga Azcarate, E Andrés Santamaría… - 2023"],"snippet":"Background Unlike diseases, automatic recognition of disabilities has not received the same attention in the area of medical NLP. Progress in this direction is hampered by obstacles like the lack of annotated corpus. Neural architectures learn …","url":["https://addi.ehu.es/bitstream/handle/10810/63451/s12859-023-05372-3.pdf?sequence=1"]}
-{"year":"2023","title":"Advancing Medical Imaging with Language Models: A Journey from N-grams to ChatGPT","authors":["M Hu, S Pan, Y Li, X Yang - arXiv preprint arXiv:2304.04920, 2023"],"snippet":"In this paper, we aimed to provide a review and tutorial for researchers in the field of medical imaging using language models to improve their tasks at hand. We began by providing an overview of the history and concepts of language models, with a …","url":["https://arxiv.org/pdf/2304.04920"]}
-{"year":"2023","title":"Advancing Neural Encoding of Portuguese with Transformer Albertina PT","authors":["J Rodrigues, L Gomes, J Silva, A Branco, R Santos… - arXiv preprint arXiv …, 2023"],"snippet":"To advance the neural encoding of Portuguese (PT), and a fortiori the technological preparation of this language for the digital age, we developed a Transformer-based foundation model that sets a new state of the art in this respect for two of its variants …","url":["https://arxiv.org/pdf/2305.06721"]}
-{"year":"2023","title":"Adversarial Capsule Networks for Romanian Satire Detection and Sentiment Analysis","authors":["SV Echim, RA Smădu, AM Avram, DC Cercel, F Pop - International Conference on …, 2023"],"snippet":"Satire detection and sentiment analysis are intensively explored natural language processing (NLP) tasks that study the identification of the satirical tone from texts and extracting sentiments in relationship with their targets. In languages with fewer …","url":["https://arxiv.org/pdf/2306.07845"]}
-{"year":"2023","title":"AfriCLIRMatrix: Enabling Cross-Lingual Information Retrieval for African Languages","authors":["O Ogundepo, X Zhang, S Sun, K Duh, J Lin - Proceedings of the 2022 Conference on …, 2022"],"snippet":"… is to exploit existing large multilingual corpora, eg, the Common Crawl1 and Wikipedia. For example, the HC4 corpus for cross-lingual information retrieval was created from Common Crawl data (Lawrie et al.… 1https://commoncrawl.org 2https://www.elastic.co/elasticsearch/ …","url":["https://aclanthology.org/2022.emnlp-main.597.pdf"]}
-{"year":"2023","title":"Aggregating Users' Online Opinions Attributes and News Influence for Cryptocurrencies Reputation Generation","authors":["A Boumhidi, A Benlahbib - Journal of Universal Computer Science, 2023"],"snippet":"… The model was pre-trained on the Common Crawl’s web crawl corpus (C4) and it achieved state-of-the-art results on many natural language processing tasks while being flexible enough to be fine-tuned to a variety of important downstream tasks …","url":["https://search.proquest.com/openview/7239ef0ee44e31cc2e498915e4b2d0fc/1?pq-origsite=gscholar&cbl=6474026"]}
-{"year":"2023","title":"Agile Modeling: From Concept to Classifier in Minutes","authors":["O Stretcu, E Vendrow, K Hata, K Viswanathan, V Ferrari… - Proceedings of the IEEE …, 2023"],"snippet":"… Since our prototype requires an unlabeled source of images from which to source training labels, we use the LAION-400M dataset [53], due to its large size and comprehensive construction based on the large Common Crawl web corpus. We …","url":["https://openaccess.thecvf.com/content/ICCV2023/papers/Stretcu_Agile_Modeling_From_Concept_to_Classifier_in_Minutes_ICCV_2023_paper.pdf"]}
-{"year":"2023","title":"Agile Modeling: Image Classification with Domain Experts in the Loop","authors":["O Stretcu, E Vendrow, K Hata, K Viswanathan, V Ferrari… - arXiv preprint arXiv …, 2023"],"snippet":"Machine learning is not readily accessible to domain experts from many fields, blocked by issues ranging from data mining to model training. We argue that domain experts should be at the center of the modeling process, and we introduce the \"Agile …","url":["https://arxiv.org/pdf/2302.12948"]}
-{"year":"2023","title":"AGNETHA FLORE AND RÜDIGER LANG","authors":["APMKIN LARGE, H NUHN, A OSWALD - … Future of Project Management: Adapting to …, 2023"],"snippet":"Digital Transformation seems to be ubiquitous, and it is radically changing humans’ lives. Artificial Intelligence (AI) and Machine Learning (ML) are two very effective drivers of this transformation. Following Vial (2019), we understand Digital …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=tFTlEAAAQBAJ&oi=fnd&pg=PA40&dq=commoncrawl&ots=2iCcz5tepo&sig=Y81TEcpnEW8sxQC82hsdvF_XKzM"]}
-{"year":"2023","title":"AI and Law: The Next Generation","authors":["K Lee, AF Cooper, J Grimmelman, D Ippolito - 2023"],"snippet":"It’s impossible to read about technological innovation right now without hearing the term “generative AI.” We are in a moment of seemingly nonstop excitement (and seemingly nonstop lawsuits) about the future of AI-assisted content creation, and the …","url":["https://www.researchgate.net/profile/A-Cooper-2/publication/372251056_AI_and_Law_The_Next_Generation_An_explainer_series/links/64ad12b7b9ed6874a51152ec/AI-and-Law-The-Next-Generation-An-explainer-series.pdf"]}
-{"year":"2023","title":"AI and the Creative Process: Part Two","authors":["J Hutson - JSTOR Daily, 2023"],"snippet":"… Stable Difusion by Stability AI, for example, was developed using image and caption pairs from the LAION-5B dataset, a publicly accessible collection derived from Common Crawl data gathered from the web. This vas dataset consiss of 5 …","url":["https://digitalcommons.lindenwood.edu/cgi/viewcontent.cgi?article=1514&context=faculty-research-papers"]}
-{"year":"2023","title":"AI and the FCI: Can ChatGPT Project an Understanding of Introductory Physics?","authors":["CG West - arXiv preprint arXiv:2303.01067, 2023"],"snippet":"… While the exact details of the text which was used to “train” ChatGPT are a proprietary secret, it is known that its reading material was largely drawn from the “Common Crawl” corpus [13], an open repository of data scraped from text found on the public …","url":["https://arxiv.org/pdf/2303.01067"]}
-{"year":"2023","title":"AI as a License Review Assistant","authors":["N Gustafson-Sundell - 2023"],"snippet":"I will present the steps we have taken to develop a prototype AI assistant for license review. I’ll explain our criteria for the selection of an AI tool for this project. We reviewed ChatGPT, Claude 2, Bard, and PDF readers. My goal was to develop an …","url":["https://cornerstone.lib.mnsu.edu/cgi/viewcontent.cgi?article=1209&context=lib_services_fac_pubs"]}
-{"year":"2023","title":"AI Design Issues in Education","authors":["J Adams, KL Riddle - ITP Research Symposium 2022 30 November–2 …"],"snippet":"… CommonCOW: Massively huge web corpora from CommonCrawl data and a method to distribute them freely under restrictive EU copyright laws. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)(pp …","url":["http://www.unitec.ac.nz/epress/wp-content/uploads/2023/11/ITP2022-Proceedings.pdf#page=119"]}
-{"year":"2023","title":"AI Ethics and Critique for Robotics","authors":["W Agnew - 2023"],"snippet":"In this thesis I consider using 3D computer vision for social good. In particular, I present a broad and deep array of AI ethics methodologies and practices necessary to assess the harms and benefits of a particular AI technology or application. Many …","url":["https://search.proquest.com/openview/d83ea4d6762d3472dfa408c410e6d5a3/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"AI for social good: social media mining of migration discourse","authors":["A Khatua - 2023"],"snippet":"The number of international migrants has steadily increased over the years, and it has become one of the pressing issues in today’s globalized world. Our bibliometric review of around 400 articles on Scopus platform indicates an increased interest in …","url":["https://www.repo.uni-hannover.de/bitstream/handle/123456789/15018/Thesis_10%20Oct%202023.pdf?sequence=1&isAllowed=y"]}
-{"year":"2023","title":"AI model GPT-3 (dis) informs us better than humans","authors":["G Spitale, N Biller-Andorno, F Germani - arXiv preprint arXiv:2301.11924, 2023"],"snippet":"Artificial intelligence is changing the way we create and evaluate information, and this is happening during an infodemic, which has been having dramatic effects on global health. In this paper we evaluate whether recruited individuals can …","url":["https://arxiv.org/pdf/2301.11924"]}
-{"year":"2023","title":"AI Transparency in the Age of LLMs: A Human-Centered Research Roadmap","authors":["QV Liao, JW Vaughan - arXiv preprint arXiv:2306.01941, 2023"],"snippet":"The rise of powerful large language models (LLMs) brings about tremendous opportunities for innovation but also looming risks for individuals and society at large. We have reached a pivotal moment for ensuring that LLMs and LLM-infused …","url":["https://arxiv.org/pdf/2306.01941"]}
-{"year":"2023","title":"AI, Large Language Models and University Education","authors":["D Psarras, Z Sotireli, I Valsamara, I Pitas"],"snippet":"… [FOU] The Common Crawl Foundation. Common crawl. URL http://commoncrawl.org. [ALE2019] Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. Language models are unsupervised multitask learners, 2019. …","url":["https://www.i-aida.org/wp-content/uploads/2023/09/AI-Large-Language-Models-and-Un-Educat-v1.0.pdf"]}
-{"year":"2023","title":"AI-Assisted Tasks and Materials Development for Language Instruction","authors":["X Kou - Center for Language Technology, 2023"],"snippet":"• Multilingual compacity• Comprehension of Text• Generating Text• Engaging in Conversation with ChatGPT• ChatGPT-based Writing Task• Prompt engineering• An example of Lesson Plan generation• Cautions (errors, etc.)• Alternative tools• Role of …","url":["https://celt.indiana.edu/resources/pedagogical/workshop/ChatGPT-Assisted-Task-Development-2023-September.pdf"]}
-{"year":"2023","title":"AI-Augmented Surveys: Leveraging Large Language Models for Opinion Prediction in Nationally Representative Surveys","authors":["J Kim, B Lee - arXiv preprint arXiv:2305.09620, 2023"],"snippet":"How can we use large language models (LLMs) to augment surveys? This paper investigates three distinct applications of LLMs fine-tuned by nationally representative surveys for opinion prediction -- missing data imputation, retrodiction …","url":["https://arxiv.org/pdf/2305.09620"]}
-{"year":"2023","title":"AI-based novelty detection in crowdsourced idea spaces","authors":["J Just, T Ströhle, J Füller, K Hutter - Innovation, 2023"],"snippet":"Processing large and heterogeneous numbers of ideas submitted to crowdsourcing contests is a regular challenge for idea evaluators. The aim of this study is to investigate a potential use case for AI-based innovation management and to extend …","url":["https://www.tandfonline.com/doi/pdf/10.1080/14479338.2023.2215740"]}
-{"year":"2023","title":"AI-Driven Confidential Computing across Edge-to-Cloud Continuum","authors":["S Zobaed - arXiv preprint arXiv:2301.00928, 2023"],"snippet":"With the meteoric growth of technology, individuals and organizations are widely adopting cloud services to mitigate the burdens of maintenance. Despite its scalability and ease of use, many users who own sensitive data refrain from fully …","url":["https://arxiv.org/pdf/2301.00928"]}
-{"year":"2023","title":"AI-Generated Content (AIGC) for Various Data Modalities: A Survey","authors":["LING FOO, JUN LIU - 2023"],"snippet":"Amidst the rapid advancement of artificial intelligence (AI), the development of content generation techniques stands out as one of the most captivating and widely discussed topics in the field. AI-generated content (AIGC) encompasses the …","url":["https://www.researchgate.net/profile/Lin-Geng-Foo/publication/373450974_AI-Generated_Content_AIGC_for_Various_Data_Modalities_A_Survey/links/656ac2b8ce88b87031281ca4/AI-Generated-Content-AIGC-for-Various-Data-Modalities-A-Survey.pdf"]}
-{"year":"2023","title":"AI-generated vs human-authored texts: A Multidimensional comparison","authors":["TB Sardinha - Applied Corpus Linguistics, 2023"],"snippet":"The goal of this study is to assess the degree of resemblance between texts generated by artificial intelligence (GPT) and (written and spoken) texts produced by human individuals in real-world settings. A comparative analysis was conducted …","url":["https://www.sciencedirect.com/science/article/pii/S2666799123000436"]}
-{"year":"2023","title":"AI-POWERED TEXT ANALYSIS TOOL FOR SENTIMENT ANALYSIS","authors":["D Kebede, N Tesfai - 2023"],"snippet":"In today’s digital era, text data plays a ubiquitous role across various domains. This bachelor’s thesis focuses on the field of sentiment analysis, specifically addressing the task of classifying text into positive, negative, or neutral sentiments with the help …","url":["https://www.diva-portal.org/smash/get/diva2:1765294/FULLTEXT01.pdf"]}
-{"year":"2023","title":"AIGC Empowering Telecom Sector White Paper","authors":["Y Ouyang, Y Zhang, X Ye, Y Liu, Y Song, Y Liu, S Bian… - arXiv preprint arXiv …, 2023"],"snippet":"In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future world …","url":["https://arxiv.org/pdf/2307.11449"]}
-{"year":"2023","title":"ALEXSIS+: Improving Substitute Generation and Selection for Lexical Simplification with Information Retrieval","authors":["K North, A Dmonte, T Ranasinghe, M Shardlow… - … on Innovative Use of NLP for …, 2023"],"snippet":"… We retrieve instances from the CommonCrawl News (CC-News) dataset2 by searching for the 386 English, 381 Spanish, and 386 Portuguese complex words given to the original participants of TSAR-2022. The CC-News dataset contains …","url":["https://aclanthology.org/2023.bea-1.33.pdf"]}
-{"year":"2023","title":"Algorithmic bias and discrimination through digitalisation in education","authors":["R Eynon - World Yearbook of Education 2024: Digitalisation of …, 2023"],"snippet":"… One example is the Common-Crawl data set, created by a San Francisco-based non-profit organisation that regularly crawls the web. The size of this and similar data sets is vast: as of April 2021, the Common-Crawl archive was around 320 TB in …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=v67dEAAAQBAJ&oi=fnd&pg=RA10-PA2018-IA3&dq=commoncrawl&ots=FcFZZEVvbX&sig=S1jPzwWzHwuMS6v0BblL76u_tI8"]}
-{"year":"2023","title":"Algorithms learn and propagate gender‐biased representations of consumers","authors":["S Rathee, S Banker, A Mishra, H Mishra - Journal of Consumer Psychology"],"snippet":"… In an analysis based on billions of documents from Common Crawl, we build on prior research to illustrate that algorithms can learn gender-biased associations with marketplace-relevant psychographic attributes even when there is no psychological …","url":["https://myscp.onlinelibrary.wiley.com/doi/abs/10.1002/jcpy.1351"]}
-{"year":"2023","title":"Algorithms propagate gender bias in the marketplace—with consumers' cooperation","authors":["S Rathee, S Banker, A Mishra, H Mishra"],"snippet":"… In an analysis based on billions of documents from Common Crawl, we build on prior research to illustrate that algorithms can learn genderbiased associations with marketplacerelevant psychographic attributes even when there is no psychological …","url":["https://sachinbanker.com/publications/rathee%20banker%20mishra%20mishra%202023%20algorithms%20propagate%20gender%20bias%20in%20the%20marketplace.pdf"]}
-{"year":"2023","title":"Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses","authors":["L Gómez-Zaragozá, S Wills, C Tejedor-Garcia… - arXiv preprint arXiv …, 2023"],"snippet":"… Then, the pre-trained FastText embedding trained on Common Crawl [32] was used to convert the transcriptions of the participants’ responses into word vectors. These representations then were fed into a neural network (NN), composed of a …","url":["https://arxiv.org/pdf/2306.03443"]}
-{"year":"2023","title":"AMOE: A Tool to Automatically Extract and Assess Organizational Evidence for Continuous Cloud Audit","authors":["F Deimling, M Fazzolari - IFIP Annual Conference on Data and Applications …, 2023"],"snippet":"The recent spread of cloud services has enabled many companies to take advantage of them. Nevertheless, the main concern about the adoption of cloud services remains the lack of transparency perceived by customers regarding security …","url":["https://link.springer.com/chapter/10.1007/978-3-031-37586-6_22"]}
-{"year":"2023","title":"Amplifying Limitations, Harms and Risks of Large Language Models","authors":["M O'Neill, M Connor - arXiv preprint arXiv:2307.04821, 2023"],"snippet":"… We know that GPT-3 was trained on a combination of sources drawn from the wilds of the internet, including Common Crawl data from 2016 to 2019, Webtext, Books and Wikipedia [10]. Analysis of Common Crawl data has shown that it …","url":["https://arxiv.org/pdf/2307.04821"]}
-{"year":"2023","title":"An Ambient Intelligence-based Approach For Longitudinal Monitoring of Verbal and Vocal Depression Symptoms","authors":["A Othmani, M Muzammel - arXiv preprint arXiv:2308.08472, 2023"],"snippet":"… For word embedding, we utilize the fastText pretrained network [15], which was trained on Common Crawl 1 and incorporates sub-word information. This network produces word vectors of size 300. In cases where certain words are not present in …","url":["https://arxiv.org/pdf/2308.08472"]}
-{"year":"2023","title":"An Analysis on the Basic Technologies of ChatGPT","authors":["Q Li, L Yi, Z Zhixiong, L Xuesi, X Jing, X Qinya, L Yang… - Data Analysis and …, 2023"],"snippet":"[Objective] Review and analyze the corpus, algorithms and models related to ChatGPT, and provide a systematic reference for peer research.[Methods] This paper systematically reviewed the relevant literature and materials since the release …","url":["https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/article/downloadArticleFile.do?attachType=PDF&id=5654"]}
-{"year":"2023","title":"An Empirical Comparison of Web Content Extraction Algorithms","authors":["J Bevendorff, S Gupta, J Kiesel, B Stein - 2023"],"snippet":"… Ungoliant uses a FastText [19] language classifier to identify natural-language text in large amounts of web data from the Common Crawl. Although extraction precision is a concern, the focus is clearly on recall. A more specific task than main …","url":["https://webis.de/downloads/publications/papers/bevendorff_2023b.pdf"]}
-{"year":"2023","title":"An Empirical Study of Consistency Regularization for End-to-End Speech-to-Text Translation","authors":["P Gao, R Zhang, Z He, H Wu, H Wang - arXiv preprint arXiv:2308.14482, 2023"],"snippet":"Consistency regularization methods, such as R-Drop (Liang et al., 2021) and CrossConST (Gao et al., 2023), have achieved impressive supervised and zero-shot performance in the neural machine translation (NMT) field. Can we also boost end-to-end …","url":["https://arxiv.org/pdf/2308.14482"]}
-{"year":"2023","title":"An Ensemble Method to Classify Telugu Idiomatic Sentences using Deep Learning Models","authors":["J Briskilal, CVMS Praneeth, C Chaitanya, MJ Karthik… - … International Conference on …, 2023"],"snippet":"… the English Wikipedia that is utilized in BERT, The extra data included the Common Crawl News dataset, which has 63 million items and 76 gigabytes, the Web text corpus, and the Common Crawl Stories dataset (31 GB) makes the simple …","url":["https://ieeexplore.ieee.org/abstract/document/10134038/"]}
-{"year":"2023","title":"An Ensemble-Based Approach for Generative Language Model Attribution","authors":["H Abburi, M Suesserman, N Pudota, B Veeramani… - International Conference on …, 2023"],"snippet":"… xlm-roberta-large-finetuned-conll03-english is XLM-RoBERTa based model [2] which is a large multi-lingual language model trained on 2.5TB of filtered Common Crawl data. The conll03-english model is fine-tuned on the XLM-RoBERTa model …","url":["https://link.springer.com/chapter/10.1007/978-981-99-7254-8_54"]}
-{"year":"2023","title":"An Evaluation of Persian-English Machine Translation Datasets with Transformers","authors":["A Sartipi, M Dehghan, A Fatemi - arXiv preprint arXiv:2302.00321, 2023"],"snippet":"Nowadays, many researchers are focusing their attention on the subject of machine translation (MT). However, Persian machine translation has remained unexplored despite a vast amount of research being conducted in languages with high resources …","url":["https://arxiv.org/pdf/2302.00321"]}
-{"year":"2023","title":"An Evaluation on Large Language Model Outputs: Discourse and Memorization","authors":["A de Wynter, X Wang, A Sokolov, Q Gu, SQ Chen - arXiv preprint arXiv:2304.08637, 2023"],"snippet":"We present an empirical evaluation of various outputs generated by nine of the most widely-available large language models (LLMs). Our analysis is done with off-the-shelf, readily-available tools. We find a correlation between percentage of memorized text …","url":["https://arxiv.org/pdf/2304.08637"]}
-{"year":"2023","title":"An Explainable Ensemble of Multi-View Deep Learning Model for Fake Review Detection","authors":["R Mohawesh, S Xu, M Springer, Y Jararweh… - Journal of King Saud …, 2023"],"snippet":"Online reviews significantly impact consumers who are purchasing or seeking services via the Internet. Businesses and review platforms need to manage these online reviews to avoid misleading customers through fake ones. This necessitates …","url":["https://www.sciencedirect.com/science/article/pii/S1319157823001982"]}
-{"year":"2023","title":"An Extractive Question Answering System for the Tamil Language","authors":["A Krishnan, SR Sriram, BVR Ganesan, S Sridhar - Advances in Science and …, 2023"],"snippet":"… This model has been trained on a huge amount of cleaned common crawl data. For low resource languages, new unlabeled corpora were generated. XLM-R is a variant of RoBERTa, which in turn is a variant of BERT [6]. …","url":["https://www.scientific.net/AST.124.312"]}
-{"year":"2023","title":"An Improved Framework for Scaling Party Positions from Texts using Transformer and Supervised Dimension Reduction","authors":["HHV Nguyen - 2023"],"snippet":"Previous research in both Natural Language Processing (NLP) and political science has proven the superiority of the Transformer architecture compared to word frequencies and word embeddings on multiple text analysis tasks. In this article, I …","url":["https://osf.io/8sha3/download"]}
-{"year":"2023","title":"An improved sentiment classification model based on data quality and word embeddings","authors":["A Siagh, FZ Laallam, O Kazar, H Salem - The Journal of Supercomputing, 2023"],"snippet":"User-generated content on social media platforms has reached big data levels. Sentiment analysis of this data provides opportunities to gain valuable insights into any domain. However, analyzing real-world data may confront the challenge of class …","url":["https://link.springer.com/article/10.1007/s11227-023-05099-1"]}
-{"year":"2023","title":"An Integrated Analysis of Multilingual Texts Spanning Dual Alphabets","authors":["FT Аdilova, RR Davronov, RA Safarov - INTERNATIONAL JOURNAL OF …, 2023"],"snippet":"Abstract Language recognition in natural language processing (NLP) aims to determine the specific language of a text or document. As the number of languages increases, this task becomes more complex. This study introduces a detailed model …","url":["http://ijdt.uz/index.php/ijdt/article/download/110/75"]}
-{"year":"2023","title":"An Investigation Into Supervision for Seq2Seq Techniques for Natural Language to Code Translation","authors":["MS Yeditha - 2022"],"snippet":"… The dataset that was used to train this was called “Common Crawl”, an open source dataset consisting of nearly a trillion words. On top of this, the authors filtered a version of Common Crawl that was most similar to a range of high-quality corpora …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/49699/Yeditha_washington_0250O_25027.pdf?sequence=1"]}
-{"year":"2023","title":"An Investigation of Preference Judging Consistency","authors":["LN Phan Minh - 2023"],"snippet":"Preference judging has been proposed as an effective method to identify the most relevant documents for a given search query. In this thesis, we investigate the degree to which assessors using a preference judging system are able to …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19272/PhanMinh_LinhNhi.pdf?sequence=3&isAllowed=y"]}
-{"year":"2023","title":"An Investigation of Representation and Allocation Harms in Contrastive Learning","authors":["S Maity, M Agarwal, M Yurochkin, Y Sun - arXiv preprint arXiv:2310.01583, 2023"],"snippet":"… In this experiment, we study the potential harms of CL applied to data obtained from Common Crawl, a popular source of text data for self-… 2019) which consists of around 400k online biographies in English extracted from the Common Crawl data …","url":["https://arxiv.org/pdf/2310.01583"]}
-{"year":"2023","title":"An Open Source Data Contamination Report for Llama Series Models","authors":["Y Li - arXiv preprint arXiv:2310.17589, 2023"],"snippet":"… Our approach utilises a search engine and the Common Crawl index, avoiding the need to host the full 2017-2020 Common Crawl dumps locally. This massive training data would incur prohibitive computational requirements. However, relying …","url":["https://arxiv.org/pdf/2310.17589"]}
-{"year":"2023","title":"An Urgency for Inclusivity: Redesigning Datasets for Improved Representation of LGBTQ+ Identity Terms in Artificial Intelligence (AI)","authors":["L Wang - 2023"],"snippet":"… The Common Crawl Dataset stands as a vital resource in the realm of AI model training, … However, despite the Common Crawl's prominence, handling LGBTQ+ identity terms in AI … ’s C4 dataset, a filtered version of the Common Crawl.The …","url":["https://laniwang.com/LaniWangFinalPaper.CORRECTFORMATTING.pdf"]}
-{"year":"2023","title":"Analogical Proportions and Creativity: A Preliminary Study","authors":["S Afantenos, H Prade, LC Bernardes - arXiv preprint arXiv:2310.13500, 2023"],"snippet":"Analogical proportions are statements of the form \"$a$ is to $b$ as $c$ is to $d$\", which expresses that the comparisons of the elements in pair $(a, b)$ and in pair $(c, d)$ yield similar results. Analogical proportions are creative in the sense that given 3 …","url":["https://arxiv.org/pdf/2310.13500"]}
-{"year":"2023","title":"ANALOGICAL--A New Benchmark for Analogy of Long Text for Large Language Models","authors":["T Wijesiriwardene, R Wickramarachchi, BG Gajera… - arXiv preprint arXiv …, 2023"],"snippet":"… In addition three other corpora containing news articles, web content, and a filtered subset of the CommonCrawl corpus were used. The training approach of RoBERTa differs from BERT as follows. RoBERTa modifies the MLM task by moving …","url":["https://arxiv.org/pdf/2305.05050"]}
-{"year":"2023","title":"Analysing Cross-Lingual Transfer in Low-Resourced African Named Entity Recognition","authors":["M Beukman, M Fokam - arXiv preprint arXiv:2309.05311, 2023"],"snippet":"Transfer learning has led to large gains in performance for nearly all NLP tasks while making downstream models easier and faster to train. This has also been extended to low-resourced languages, with some success. We investigate the …","url":["https://arxiv.org/pdf/2309.05311"]}
-{"year":"2023","title":"ANALYSIS OF A DECISION SUPPORT SYSTEM USING AHP FOR FOOD AND RESTAURANT SELECTION BASED ON THE USER'S FOOD CRAVINGS AND …","authors":["D Dyondra, J Purnama, M Galinium - SGU Online Thesis Submission, 2023"],"snippet":"The purpose of this research is to develop a decision support system (DSS) using the AHP algorithm for selecting restaurants based on the user's food cravings and location in Jakarta. The data for the DSS was gathered by scraping restaurant data …","url":["https://thesis.sgu.ac.id/index.php/ots/article/download/4498/832"]}
-{"year":"2023","title":"Analysis of ChatGPT as a Question-Answering Tool","authors":["P Pichappan, M Krishnamurthy, P Vijayakumar - Journal of Digital Information …, 2023"],"snippet":"… Its data sources are drawn from Common Crawl (a non-profit organisation that crawls the web data and makes it available to open the stored information and data volume open), WebText2, Books and Wikipedia. WebText2 is the extraction of the …","url":["https://www.researchgate.net/profile/Pit-Pichappan/publication/371686172_Analysis_of_ChatGPT_as_a_Question-Answering_Tool/links/6490113f8de7ed28ba3c1c38/Analysis-of-ChatGPT-as-a-Question-Answering-Tool.pdf"]}
-{"year":"2023","title":"Analysis of Deep Learning Model Combinations and Tokenization Approaches in Sentiment Classification","authors":["A Erkan, T Güngör - IEEE Access, 2023"],"snippet":"Sentiment classification is a natural language processing task to identify opinions expressed in texts such as product or service reviews. In this work, we analyze the effects of different deep-learning model combinations, embedding methods, and …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10332170.pdf"]}
-{"year":"2023","title":"Analysis of Digital Information in Storage Devices Using Supervised and Unsupervised Natural Language Processing Techniques","authors":["LA Martínez Hernández, AL Sandoval Orozco… - Future Internet, 2023"],"snippet":"… Sources supplementing the training data include news data (CommonCrawl news, 76 GB), text from websites (38 GB), and stories (31 GB). The training of this data is performed over the course of a day using the latest generation graphics card. This …","url":["https://www.mdpi.com/1999-5903/15/5/155"]}
-{"year":"2023","title":"Analysis of Fake News Detection Methods","authors":["M Amjad, O Vitman, G Sidorov, A Zhila, A Gelbukh - … : Selected Papers of the 8th World …, 2023"],"snippet":"The fact that it might be difficult to distinguish between real news and fake news is of the utmost significance. It is difficult, time-consuming, and expensive to manually review enormous volumes of digital data in order to detect false news, which is …","url":["https://link.springer.com/chapter/10.1007/978-3-031-23476-7_13"]}
-{"year":"2023","title":"Analysis of Machine Learning and Deep Learning Algorithms for Text Sentiment Detection","authors":["S Dimitrijević"],"snippet":"Sentiment analysis or opinion mining is the task of automatically extracting and classifying the sentiment of the text. It can be applied in numerous fields such as marketing, customer service, etc. Sentiment analysis has gained much attention in …","url":["https://matematika.pmf.uns.ac.rs/wp-content/uploads/2023/02/StefanDimitrijevic.pdf"]}
-{"year":"2023","title":"Analysis of the Evolution of Advanced Transformer-Based Language Models: Experiments on Opinion Mining","authors":["NE Zekaoui, S Yousfi, M Rhanoui, M Mikram - arXiv preprint arXiv:2308.03235, 2023"],"snippet":"… However, the multilingual version of RoBERTa [15] called XLM-RoBERTa [21], pre-trained on the newly created 2.5TB multilingual CommonCrawl corpus containing 100 different languages, has further pushed the performance. It has shown strong …","url":["https://arxiv.org/pdf/2308.03235"]}
-{"year":"2023","title":"Analysis of the Performance Impact of Fine-Tuned Machine Learning Model for Phishing URL Detection","authors":["SR Abdul Samad, S Balasubaramanian, AS Al-Kaabi… - Electronics, 2023"],"snippet":"… Alexa and Common Crawl are used to compile lists of legitimate websites; whereas Phish-Tank and OpenPhish are used to compile lists of malicious ones. Binary labels, such as 0 for legitimate and 1 for phishing, are present in this dataset …","url":["https://www.mdpi.com/2079-9292/12/7/1642/pdf"]}
-{"year":"2023","title":"Analysis of the Semantic Shift in Diachronic Word Embeddings for Spanish Before and After COVID-19","authors":["ER Betancourt, EC Murillo - CLEI Electronic Journal, 2023"],"snippet":"… In this work, we analyzed millions of Spanish web pages collected by the CommonCrawl … The documents were downloaded from CommonCrawl, discarding the documents with less … 2018 and week 25 of 2021 were downloaded …","url":["https://clei.org/cleiej/index.php/cleiej/article/download/593/455"]}
-{"year":"2023","title":"Analysis of the Technical Principles of ChatGPT and Prospects for Pre-trained Large Models","authors":["Z Jin - 2023 IEEE 3rd International Conference on Information …, 2023"],"snippet":"ChatGPT is a pre-trained model in the field of natural language processing. As a generative model, the technical foundation of ChatGPT is a deep learning model called the \"Generative Adversarial Network\". The pre-trained large model …","url":["https://ieeexplore.ieee.org/abstract/document/10165540/"]}
-{"year":"2023","title":"Analyzing and Improving the Scalability of In-Memory Indices for Managed Search Engines","authors":["A Chilukuri, S Akram - 2023"],"snippet":"… We create indices of various sizes using the January 2022 CommonCrawl data set [43], a large repository of web crawl data. Index size in Lucene is difficult to control precisely. We, therefore, index … https://commoncrawl.org/2022/06/may-2022-crawl-archivenow-available/ …","url":["https://shbakram.github.io/assets/papers/ismm2023-lucene.pdf"]}
-{"year":"2023","title":"Analyzing Failure Modes of Inscrutable Machine Learning Models","authors":["A Olmo Hernandez - 2022"],"snippet":"ABSTRACT Machine learning models and in specific, neural networks, are well known for being inscrutable in nature. From image classification tasks and generative techniques for data augmentation, to general purpose natural language …","url":["https://keep.lib.asu.edu/_flysystem/fedora/c7/OlmoHernandez_asu_0010E_22349.pdf"]}
-{"year":"2023","title":"Analyzing Syntactic Generalization Capacity of Pre-trained Language Models on Japanese Honorific Conversion","authors":["R Sekizawa, H Yanaka - arXiv preprint arXiv:2306.03055, 2023"],"snippet":"Using Japanese honorifics is challenging because it requires not only knowledge of the grammatical rules but also contextual information, such as social relationships. It remains unclear whether pre-trained large language models (LLMs) can flexibly …","url":["https://arxiv.org/pdf/2306.03055"]}
-{"year":"2023","title":"Analyzing Text Representations by Measuring Task Alignment","authors":["C Gonzalez-Gutierrez, A Primadhanty, F Cazzaro… - arXiv preprint arXiv …, 2023"],"snippet":"Textual representations based on pre-trained language models are key, especially in few-shot learning scenarios. What makes a representation good for text classification? Is it due to the geometric properties of the space or because it is well …","url":["https://arxiv.org/pdf/2305.19747"]}
-{"year":"2023","title":"Analyzing the Impact of Tokenization on Multilingual Epidemic Surveillance in Low-Resource Languages","authors":["S Mutuvi, E Boros, A Doucet, G Lejeune, A Jatowt… - International Conference on …, 2023"],"snippet":"… On the other hand, XLM-RoBERTa is pre-trained on 2.5TB of CommonCrawl data covering 100 languages. As a result, when compared to Wikipedia data, CommonCrawl data is significantly larger, effectively increasing the available …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41682-8_2"]}
-{"year":"2023","title":"Analyzing the unrestricted web: The finnish corpus of online registers","authors":["V Skantsi, V Laippala - Nordic Journal of Linguistics, 2023"],"snippet":"… Second, Finnish documents were identified and retrieved from Common Crawl, an organization that crawls the Internet providing its archives and datasets for public use (https://commoncrawl.org/). Texts were cleaned from menus and listings with …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/BDCA0FE03ABD9087CC5652533880C8C0/S0332586523000021a.pdf/div-class-title-analyzing-the-unrestricted-web-the-finnish-corpus-of-online-registers-div.pdf"]}
-{"year":"2023","title":"and JR Orozco-ArroyaveD","authors":["D Escobar-Grisales, SA Moreno-Acevedo… - Applied Computer Sciences in …"],"snippet":"… This model was pre-trained with 2.5 TB of text data from the Common Crawl corpus [17], which includes text in 100 different languages. This extensive pre-training has allowed RoBERTa to compute text representations in multiple languages …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=fJ3fEAAAQBAJ&oi=fnd&pg=PA173&dq=commoncrawl&ots=Sbvy8lnigr&sig=WChAuY_i09PQ0f7N959Xx1wlsB4"]}
-{"year":"2023","title":"Annotation for computational argumentation analysis: Issues and perspectives","authors":["A Lindahl, L Borin - Language and Linguistics Compass, 2024"],"snippet":"Abstract Argumentation has long been studied in a number of disciplines, including several branches of linguistics. In recent years, computational processing of argumentation has been added to the list, reflecting a general interest from the field …","url":["https://compass.onlinelibrary.wiley.com/doi/pdf/10.1111/lnc3.12505"]}
-{"year":"2023","title":"Anonymity at Risk? Assessing Re-Identification Capabilities of Large Language Models","authors":["A Nyffenegger, M Stürmer, J Niklaus - arXiv preprint arXiv:2308.11103, 2023"],"snippet":"Anonymity of both natural and legal persons in court rulings is a critical aspect of privacy protection in the European Union and Switzerland. With the advent of LLMs, concerns about large-scale re-identification of anonymized persons are growing. In …","url":["https://arxiv.org/pdf/2308.11103"]}
-{"year":"2023","title":"ANSEL Photobot: A Robot Event Photographer with Semantic Intelligence","authors":["D Rivkin, G Dudek, N Kakodkar, D Meger, O Limoyo… - arXiv preprint arXiv …, 2023"],"snippet":"Our work examines the way in which large language models can be used for robotic planning and sampling, specifically the context of automated photographic documentation. Specifically, we illustrate how to produce a photo-taking robot with …","url":["https://arxiv.org/pdf/2302.07931"]}
-{"year":"2023","title":"App2Check at EMit: Large Language Models for Multilabel Emotion Classification","authors":["G Cageggi, E Di Rosa, A Uboldi - 2023"],"snippet":"In this paper we compare the performance of three state-of-the-art LLM-based approaches for multilabel emotion classification: fine-tuned multilingual T5 and two few shot prompting approaches: plain FLAN and ChatGPT. In our experimental …","url":["https://ceur-ws.org/Vol-3473/paper3.pdf"]}
-{"year":"2023","title":"Applications of Natural Language Processing for the Management of Stroke Disorders: Scoping Review","authors":["H De Rosario, S Pitarch-Corresa, I Pedrosa… - JMIR Medical Informatics, 2023"],"snippet":"… maturity of more complex representations of language data, such as the word embeddings into large-dimensional numeric vectors and their effective processing through deep neural networks, as well as the exploitation of huge databases of texts …","url":["https://medinform.jmir.org/2023/1/e48693"]}
-{"year":"2023","title":"Ar-PuFi: A Short-Text Dataset to Identify the Offensive Messages Towards Public Figures in the Arabian Community","authors":["M Abdelhakim, B Liu, C Sun - Expert Systems with Applications, 2023"],"snippet":"The fight against offensive speech on the Internet necessitates increased efforts from linguistic analysis and artificial intelligence perspectives to develop countermeasures and preventive methods. Reliable predictions can only be …","url":["https://www.sciencedirect.com/science/article/pii/S0957417423013908"]}
-{"year":"2023","title":"Arabic Mini-ClimateGPT: A Climate Change and Sustainability Tailored Arabic LLM","authors":["S Mullappilly, A Shaker, O Thawakar, H Cholakkal… - Findings of the Association …, 2023"],"snippet":"Climate change is one of the most significant challenges we face together as a society. Creating awareness and educating policy makers the wide-ranging impact of climate change is an essential step towards a sustainable future. Recently, Large …","url":["https://aclanthology.org/2023.findings-emnlp.941.pdf"]}
-{"year":"2023","title":"Arabic Tweets-Based Sentiment Analysis to Investigate the Impact of COVID-19 in KSA: A Deep Learning Approach","authors":["A Alqarni, A Rahman - Big Data and Cognitive Computing, 2023"],"snippet":"… The FastText model was also trained by [68] on Wikipedia and common crawl used the CBOW architecture. The results of the comparison between all pre-trained word embeddings for all datasets in two periods are shown in Table 7 and Table 8. …","url":["https://www.mdpi.com/2070176"]}
-{"year":"2023","title":"AraMUS: Pushing the Limits of Data and Model Scale for Arabic Natural Language Processing","authors":["A Alghamdi, X Duan, W Jiang, Z Wang, Y Wu, Q Xia… - arXiv preprint arXiv …, 2023"],"snippet":"Developing monolingual large Pre-trained Language Models (PLMs) is shown to be very successful in handling different tasks in Natural Language Processing (NLP). In this work, we present AraMUS, the largest Arabic PLM with 11B parameters trained …","url":["https://arxiv.org/pdf/2306.06800"]}
-{"year":"2023","title":"AraProp at WANLP 2022 Shared Task: Leveraging Pre-Trained Language Models for Arabic Propaganda Detection","authors":["GS Tomar - Proceedings of the The Seventh Arabic Natural …, 2022"],"snippet":"This paper presents the approach taken for the shared task on Propaganda Detection in Arabic at the Seventh Arabic Natural Language Processing Workshop (WANLP 2022). We participated in Sub-task 1 where the text of a tweet is provided, and the …","url":["https://aclanthology.org/2022.wanlp-1.56.pdf"]}
-{"year":"2023","title":"Are Large Language Models Fit For Guided Reading?","authors":["P Ochieng - arXiv preprint arXiv:2305.10645, 2023"],"snippet":"This paper looks at the ability of large language models to participate in educational guided reading. We specifically, evaluate their ability to generate meaningful questions from the input text, generate diverse questions both in terms of content …","url":["https://arxiv.org/pdf/2305.10645"]}
-{"year":"2023","title":"Are Large Language Models Geospatially Knowledgeable?","authors":["P Bhandari, A Anastasopoulos, D Pfoser - arXiv preprint arXiv:2310.13002, 2023"],"snippet":"… [29] by processing Commoncrawl 6 snapshots. Given that the LLaMA model was trained directly on Commoncrawl snapshots, we believe that CC100 is a good approximation of the training data. We conduct an analysis similar to Elazar et al. [7] …","url":["https://arxiv.org/pdf/2310.13002"]}
-{"year":"2023","title":"Argot as a Trust Signal: Slang, Jargon & Reputation on a Large Cybercrime Forum","authors":["J Hughes, A Caines, A Hutchings"],"snippet":"… Using the FastText models trained on CommonCrawl and HackForums data, we obtain word embeddings for all tokens in the HackForums dataset which have over 100 occurrences across all posts (including multiple usage in a post). We threshold …","url":["https://weis2023.econinfosec.org/wp-content/uploads/sites/11/2023/06/weis23-hughes.pdf"]}
-{"year":"2023","title":"ArgU: A Controllable Factual Argument Generator","authors":["S Saha, R Srihari - arXiv preprint arXiv:2305.05334, 2023"],"snippet":"Effective argumentation is essential towards a purposeful conversation with a satisfactory outcome. For example, persuading someone to reconsider smoking might involve empathetic, well founded arguments based on facts and expert …","url":["https://arxiv.org/pdf/2305.05334"]}
-{"year":"2023","title":"ArguGPT: evaluating, understanding and identifying argumentative essays generated by GPT models","authors":["Y Liu, Z Zhang, W Zhang, S Yue, X Zhao, X Cheng… - arXiv preprint arXiv …, 2023"],"snippet":"AI generated content (AIGC) presents considerable challenge to educators around the world. Instructors need to be able to detect such text generated by large language models, either with the naked eye or with the help of some tools. There is …","url":["https://arxiv.org/pdf/2304.07666"]}
-{"year":"2023","title":"Argumentation Element Annotation Modeling using XLNet","authors":["C Ormerod, A Burkhardt, M Young, S Lottridge - arXiv preprint arXiv:2311.06239, 2023"],"snippet":"This study demonstrates the effectiveness of XLNet, a transformer-based language model, for annotating argumentative elements in persuasive essays. XLNet's architecture incorporates a recurrent mechanism that allows it to model long-term …","url":["https://arxiv.org/pdf/2311.06239"]}
-{"year":"2023","title":"Artificial cheerleading in IEO: Marketing campaign or pump and dump scheme","authors":["Y Tian, Y Xie - Information Processing & Management, 2024"],"snippet":"… XLM-R, on the other hand, was trained on a newly curated and clean CommonCrawl dataset spanning 2.5 TB in 100 different languages. The model has surpassed previous multilingual models like mBERT and XLM in tasks such as …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323002741"]}
-{"year":"2023","title":"Artificial Intelligence (AI) Art Generators in the Architectural Design Curricula","authors":["KE Hedges - 2023 ASEE Annual Conference & Exposition, 2023"],"snippet":"… A web crawler, such as the non-profit Common Crawl, is a bot that trolls and scrapes the web for … Schäfer, “CommonCOW: Massively Huge Web Corpora from CommonCrawl Data and a Method to Distribute them Freely under Restrictive EU …","url":["https://peer.asee.org/artificial-intelligence-ai-art-generators-in-the-architectural-design-curricula.pdf"]}
-{"year":"2023","title":"Artificial Intelligence and Librarianship","authors":["M Frické - 2023"],"snippet":"Artificial Intelligence and Librarianship: Page 1 Martin Frické Artificial Intelligence and Librarianship: Notes for Teaching Page 2 2 Martin Frické, Professor Emeritus School of Information The University of Arizona, Tucson, AZ, USA mfricke@arizona.edu …","url":["https://softoption.us/sites/default/files/AIinLibrariesContentsBibliography.pdf"]}
-{"year":"2023","title":"Artificial intelligence applications in technical communication for the optimization of content management processes","authors":["KB Hanczaryk, W Ziegler - AIP Conference Proceedings, 2023"],"snippet":"… The training was done on texts from Wikipedia and Common Crawl. The vocabulary of the model includes nearly 4,947,000 words, each represented by a vector of length 100 [21, 22]. The similarity of words can be determined by the …","url":["https://pubs.aip.org/aip/acp/article/2909/1/100007/2924885"]}
-{"year":"2023","title":"Artificial intelligence as a tool in social media content moderation","authors":["E Lagren - 2023"],"snippet":"On social media, users engage with each other through consuming and creating user-generated content, the amount of which has increased alongside the growth of the userbase. This presents challenges to social media companies as some …","url":["https://jyx.jyu.fi/bitstream/handle/123456789/92439/1/URN%3ANBN%3Afi%3Ajyu-202312218433.pdf"]}
-{"year":"2023","title":"Artificial Intelligence for Business Creativity","authors":["M Pagani, R Champion - 2023"],"snippet":"Artificial Intelligence for Business Creativity provides an in-depth examination of the integration of Artificial Intelligence (AI) into the business sector to foster creativity. The book explores the interplay between micro-level individual creativity and macro-level …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=zMDGEAAAQBAJ&oi=fnd&pg=PA1928&dq=commoncrawl&ots=VIVepH3-f5&sig=Ka_aQtw10I2vx6OcRaFvgzBeiWw"]}
-{"year":"2023","title":"Artificial intelligence literacy for the language industry–with particular emphasis on recent large language models such as GPT-4","authors":["R Krüger - Lebende Sprachen, 2023"],"snippet":"This article explores the concept of artificial intelligence (AI) literacy in the context of the language industry, placing particular emphasis on recent large language models such as GPT-4. After a brief introduction in which the relevance of AI literacy in the …","url":["https://www.degruyter.com/document/doi/10.1515/les-2023-0024/html"]}
-{"year":"2023","title":"Artificial Intelligent based Models for Event Extraction using Customer Support Applications","authors":["M Mayuranathan, G Akilandasowmya, B Jayaram… - 2023 Second International …, 2023"],"snippet":"… text corpora like Wikipedia and Common Crawl are popular options for computer vision and natural language processing jobs, respectively. Prepare for pretrained models by designing the architecture of the base network. Common choices include …","url":["https://ieeexplore.ieee.org/abstract/document/10250679/"]}
-{"year":"2023","title":"Artificial Neural Networks: A Noticeable Evolution in AI","authors":["P Sarang - Thinking Data Science: A Data Science Practitioner's …, 2023"],"snippet":"Artificial neural networks (ANN) surely brought a noticeable evolution to the AI field. A data scientist has now a choice between the two techniques—GOFAI and ANN, while designing a machine learning model. In this chapter, I introduce you to this …","url":["https://link.springer.com/chapter/10.1007/978-3-031-02363-7_17"]}
-{"year":"2023","title":"Artificially Intelligent Billing in Spine Surgery: An Analysis of a Large Language Model","authors":["B Zaidat, YS Lahoti, A Yu, KS Mohamed, SK Cho… - Global Spine Journal, 2023"],"snippet":"Study Design Retrospective cohort study. Objectives This study assessed the effectiveness of a popular large language model, ChatGPT-4, in predicting Current Procedural Terminology (CPT) codes from surgical operative notes. By employing a …","url":["https://journals.sagepub.com/doi/full/10.1177/21925682231224753"]}
-{"year":"2023","title":"Asking Questions: an Innovative Way to Interact with Oral History Archives","authors":["A Fr��mund, M Bulín, J Švec, F Polák - 2023"],"snippet":"… As a speech recognizer, we trained the recent Wav2Vec 2.0 end-to-end model with a lower-case n-gram language model estimated from CommonCrawl data. In addition, the raw output of the speech recognizer was post-processed using …","url":["https://dspace5.zcu.cz/bitstream/11025/54621/1/proceedings_svk_2023-42-43.pdf"]}
-{"year":"2023","title":"Aspect-Category based Sentiment Analysis with Unified Sequence-To-Sequence Transfer Transformers","authors":["D Van Thin, NLT Nguyen - VNU Journal of Science: Computer Science and …, 2023"],"snippet":"… While the BARTPho and its variants were trained on 20GB of news data, the viT5 models were trained on 71GB of Common Crawl data (a subset of CC100 corpus [19]) for Vietnamese language. Moreover, the text in the CC100 corpus is crawled in the …","url":["https://jcsce.vnu.edu.vn/index.php/jcsce/article/view/662/182"]}
-{"year":"2023","title":"Assessing LLMs for Moral Value Pluralism","authors":["N Benkler, D Mosaphir, S Friedman, A Smart… - arXiv preprint arXiv …, 2023"],"snippet":"The fields of AI current lacks methods to quantitatively assess and potentially alter the moral values inherent in the output of large language models (LLMs). However, decades of social science research has developed and refined widely-accepted …","url":["https://arxiv.org/pdf/2312.10075"]}
-{"year":"2023","title":"Assessing the Ability of ChatGPT to Screen Articles for Systematic Reviews","authors":["E Syriani, I David, G Kumar - arXiv preprint arXiv:2307.06464, 2023"],"snippet":"… ChatGPT is a Generative Pretrained Transformer that employs an auto-regressive language model trained on large datasets with billions of tokens from CommonCrawl, Wikipedia, and other publicly available text sources. It relies on a deep neural …","url":["https://arxiv.org/pdf/2307.06464"]}
-{"year":"2023","title":"Assessing the Importance of Frequency versus Compositionality for Subword-based Tokenization in NMT","authors":["B Wolleb, R Silvestri, G Vernikos, LDA Popescu-Belis - arXiv preprint arXiv …, 2023"],"snippet":"Subword tokenization is the de facto standard for tokenization in neural language models and machine translation systems. Three advantages are frequently cited in favor of subwords: shorter encoding of frequent tokens, compositionality of subwords …","url":["https://arxiv.org/pdf/2306.01393"]}
-{"year":"2023","title":"Assessing the research landscape and clinical utility of large language models: A scoping review","authors":["YJ Park, A Pillai, J Deng, E Guo, M Gupta, M Paget… - 2023"],"snippet":"… Introduced in November 2022, ChatGPT was trained using large web corpora, including CommonCrawl, WebText, and Wikipedia, as well as internet-based book corpora spanning multiple languages [3]. GPT, along with other popular LLMs such …","url":["https://www.researchsquare.com/article/rs-3472000/latest.pdf"]}
-{"year":"2023","title":"Assessing the Value of ChatGPT for Clinical Decision Support Optimization","authors":["S Liu, AP Wright, BL Patterson, JP Wanderer, RW Turer… - medRxiv, 2023"],"snippet":"Objective: To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions. Methods: We supplied summaries of CDS logic to …","url":["https://www.medrxiv.org/content/medrxiv/early/2023/02/23/2023.02.21.23286254.full.pdf"]}
-{"year":"2023","title":"Assessing Translation capabilities of Large Language Models involving English and Indian Languages","authors":["V Mujadia, A Urlana, Y Bhaskar, PA Pavani, K Shravya… - arXiv preprint arXiv …, 2023"],"snippet":"Generative Large Language Models (LLMs) have achieved remarkable advancements in various NLP tasks. In this work, our aim is to explore the multilingual capabilities of large language models by using machine translation as a …","url":["https://arxiv.org/pdf/2311.09216"]}
-{"year":"2023","title":"Assessing Vulnerability from Its Description","authors":["Z Zhang, V Kumar, M Mayo, A Bifet - … , UbiSec 2022, Zhangjiajie, China, December 28 …, 2023"],"snippet":"This paper shows an end-to-end Artificial Intelligence (AI) system to estimate the severity level and the various Common Vulnerability Scoring System (CVSS) components from natural language descriptions without reproducing the vulnerability …","url":["https://link.springer.com/chapter/10.1007/978-981-99-0272-9_9"]}
-{"year":"2023","title":"Assessment on trial? ChatGPT and the new frontiers of learning and assessment in higher education","authors":["O Kolade, A Owoseni, A Egbetokun"],"snippet":"ChatGPT, a state-of-the-art chatbot built upon Open AI’s generative pre-trained transformer (GPT-3), has generated a major public interest and caused quite a stir in the higher education sector, where reactions have ranged from excitement to …","url":["https://www.researchgate.net/profile/Oluwaseun-Kolade/publication/369974458_Assessment_on_trial_ChatGPT_and_the_new_frontiers_of_learning_and_assessment_in_higher_education/links/64376dc720f25554da29ad9f/Assessment-on-trial-ChatGPT-and-the-new-frontiers-of-learning-and-assessment-in-higher-education.pdf"]}
-{"year":"2023","title":"At the intersection of humanity and technology: a technofeminist intersectional critical discourse analysis of gender and race biases in the natural language processing …","authors":["P Barea, D Boeren, JF Ferreira Goncalves - AI & SOCIETY, 2023"],"snippet":"Algorithmic biases, or algorithmic unfairness, have been a topic of public and scientific scrutiny for the past years, as increasing evidence suggests the pervasive assimilation of human cognitive biases and stereotypes in such systems. This …","url":["https://link.springer.com/article/10.1007/s00146-023-01804-z"]}
-{"year":"2023","title":"AT WHICH TRAINING STAGE DOES CODE DATA HELP LLMS REASONING?","authors":["Y Ma, Y Liu, Y Yu, Y Zhang, Y Jiang, C Wang, S Li"],"snippet":"… For example, LLaMA was trained with 1.4 trillion tokens consisting of texts (CommonCrawl, C4) and codes (GitHub). These large-scale data with … To improve the data quality, we adopt the following rule-based text cleaning strategies over the raw web pages …","url":["https://arxiv.org/pdf/2309.16298"]}
-{"year":"2023","title":"ATLANTIC: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science","authors":["S Munikoti, A Acharya, S Wagle, S Horawalavithana - arXiv preprint arXiv:2311.12289, 2023"],"snippet":"… We took the original ATLAS model as a baseline, which is pretrained with common crawl (CC) and Wikipedia on top of the T5 model. In addition to this pretrained ATLAS, we also leverage ATLAS-Science model from scratch with the …","url":["https://arxiv.org/pdf/2311.12289"]}
-{"year":"2023","title":"Attribute Ambiguity Discovery: A Deep Learning Approach via Unsupervised Learning","authors":["E Veltri, G Badaro, M Saeed, P Papotti - 2023"],"snippet":"… Typically, these models are pre-trained on large text corpora such as articles from Wikipedia, news articles, or Common Crawl. The model is pre-trained in an unsupervised manner, for example by predicting a missing token or the next-sentence …","url":["https://ceur-ws.org/Vol-3478/paper40.pdf"]}
-{"year":"2023","title":"Audio is all in one: speech-driven gesture synthetics using WavLM pre-trained model","authors":["F Zhang, N Ji, F Gao, S Zhao, Z Wang, S Li - arXiv preprint arXiv:2308.05995, 2023"],"snippet":"… [30] obtain the word embeddings using the GloVe model pre-trained on the Common Crawl corpus [31]. This method marginally outperformed other similar-dimensional embedding models, such as Word2Vec [32] and FastText [33], and had similar …","url":["https://arxiv.org/pdf/2308.05995"]}
-{"year":"2023","title":"Augmenters at SemEval-2023 Task 1: Enhancing CLIP in Handling Compositionality and Ambiguity for Zero-Shot Visual WSD through Prompt Augmentation and Text …","authors":["J Li, YT Shiue, YS Shih, J Geiping - Proceedings of the The 17th International …, 2023"],"snippet":"This paper describes our zero-shot approachesfor the Visual Word Sense Disambiguation (VWSD) Task in English. Our preliminarystudy shows that the simple approach of match-ing candidate images with the phrase usingCLIP suffers …","url":["https://aclanthology.org/2023.semeval-1.5.pdf"]}
-{"year":"2023","title":"Augmenting interpretable models with large language models during training","authors":["C Singh, A Askari, R Caruana, J Gao - Nature Communications, 2023"],"snippet":"… We compare Aug-Linear to four interpretable baseline models: Bag of ngrams, TF-IDF (Term frequency-inverse document frequency) 23 , GloVE 24 (we use the pre-trained Glove embeddings trained on Common Crawl containing 840 billion tokens, 2.2 …","url":["https://www.nature.com/articles/s41467-023-43713-1"]}
-{"year":"2023","title":"Augmenting product knowledge graphs with subjective information","authors":["JM SILVA - 2023"],"snippet":"… The authors scale the pre-training of the models either by increasing the number of parameters (up to 11 Billion) and with a large heuristically cleaned corpus from the Common Crawl web dump3. This final pre-trained dataset, called Colossal …","url":["https://repositorio.ufpe.br/bitstream/123456789/49464/1/TESE%20Johny%20Moreira%20da%20Silva.pdf"]}
-{"year":"2023","title":"AugTriever: Unsupervised Dense Retrieval by Scalable Data Augmentation","authors":["R Meng, Y Liu, S Yavuz, D Agarwal, L Tu, N Yu…"],"snippet":"… We apply those methods on Wikipedia passages and CommonCrawl web documents to obtain two large augmented AUGQ datasets. Then we train bi-encoder dense retrievers (using either InBatch or MoCo architecture) using AUGQ and we …","url":["https://openreview.net/pdf?id=-XaFHEKaUJ"]}
-{"year":"2023","title":"AUTOCAST++: ENHANCING WORLD EVENT PREDIC","authors":["Q Yan, R Seraj, J He, L Meng, T Sylvain - arXiv preprint arXiv:2310.01880, 2023"],"snippet":"… news articles from the Common Crawl corpus1 spanning 2016 to 2022 for retrieval purpose. For performance evaluation, we use accuracy metrics for T/F and MCQ questions and absolute 1Common Crawl - Open Repository of Web Crawl Data …","url":["https://arxiv.org/pdf/2310.01880"]}
-{"year":"2023","title":"Autoencoder for fraudulent transactions data feature engineering","authors":["D Breskuvienė, G Dzemyda - DAMSS: 13th conference on data analysis methods for …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:150999090/150999090.pdf"]}
-{"year":"2023","title":"Automated Interpretation of Place Descriptions: Determining Entity Types for Querying OSM","authors":["M Yousaf, T Schwartz, D Wolter - KI-Künstliche Intelligenz, 2023"],"snippet":"This paper is concerned with interpretation of natural language place descriptions, as they are a rich source of geographic information. A place description is interpreted by matching geographic entities occurring in the text against the …","url":["https://link.springer.com/article/10.1007/s13218-022-00798-y"]}
-{"year":"2023","title":"Automated programming, symbolic computation, machine learning: my personal view","authors":["B Buchberger - Annals of Mathematics and Artificial Intelligence, 2023"],"snippet":"In this note, I present my personal view on the interaction of the three areas Automated Programming, Symbolic Computation, and Machine Learning. Programming is the activity of finding a (hopefully) correct program (algorithm) for a …","url":["https://link.springer.com/content/pdf/10.1007/s10472-023-09894-7.pdf"]}
-{"year":"2023","title":"Automated Short Answer Grading using BERT on German datasets","authors":["S Nath, B Parsaeifard, E Werlen"],"snippet":"Owing to a growth in online learning, the interest in automated grading has intensified, especially due to scoring time reduction. The aim of automated grading is to approximate human level scoring. Automated Short Answer Grading (ASAG) is …","url":["https://www.researchgate.net/profile/Egon-Werlen/publication/373556564_Automated_Short_Answer_Grading_using_BERT_on_German_datasets/links/64f1b6cc4a2a2214db2f1f45/Automated-Short-Answer-Grading-using-BERT-on-German-datasets.pdf"]}
-{"year":"2023","title":"Automated Testing and Improvement of Named Entity Recognition Systems","authors":["B Yu, Y Hu, Q Mang, W Hu, P He - arXiv preprint arXiv:2308.07937, 2023"],"snippet":"… Common Crawl,1 a nonprofit organization that crawls the web and freely provides its archives and datasets to the public, has collected 380 TB of data and 3.15 billion pages by October 2022. As of 30 December 2022, there are 6,594,544 articles in the …","url":["https://arxiv.org/pdf/2308.07937"]}
-{"year":"2023","title":"Automated Text Identification: Multilingual Transformer-based Models Approach","authors":["G Gritsay, A Grabovoy, A Kildyakov, Y Chekhovich - 2023"],"snippet":"This paper describes our solution approach for the AuTexTification (Automated Text Identification) competition held as part of the IberLEF 2023 conference. Generated text is an increasing problem nowadays. Due to the spread of large volumes of …","url":["https://ceur-ws.org/Vol-3496/autextification-paper15.pdf"]}
-{"year":"2023","title":"Automatic Analysis of Peer Feedback using Machine Learning and Explainable Artificial Intelligence","authors":["K Huang - 2023"],"snippet":"Peer assessment is a process where learners evaluate and provide feedback on one another’s performance, which is critical to the student learning process. Earlier research has shown that it can improve student learning outcomes in various settings …","url":["https://www.diva-portal.org/smash/get/diva2:1763088/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Automatic Anonymization of Swiss Federal Supreme Court Rulings","authors":["J Niklaus, R Mamié, M Stürmer, D Brunner, M Gygli - arXiv preprint arXiv:2310.04632, 2023"],"snippet":"Releasing court decisions to the public relies on proper anonymization to protect all involved parties, where necessary. The Swiss Federal Supreme Court relies on an existing system that combines different traditional computational methods with …","url":["https://arxiv.org/pdf/2310.04632"]}
-{"year":"2023","title":"Automatic classification and prioritisation of actionable BI-RADS categories using natural language processing models","authors":["P López-Úbeda, T Martín-Noguerol, A Luna - Clinical Radiology, 2023"],"snippet":"Aim To facilitate the routine tasks performed by radiologists in their evaluation of breast radiology reports, by enhancing the communication of relevant results to referring physicians via a natural language processing (NLP)-based system to …","url":["https://www.sciencedirect.com/science/article/pii/S0009926023004233"]}
-{"year":"2023","title":"Automatic Construction Hazard Identification Integrating On-Site Scene Graphs with Information Extraction in Outfield Test","authors":["X Liu, X Jing, Q Zhu, W Du, X Wang - Buildings, 2023"],"snippet":"… We initialize the word embeddings for the objects and predicates with pre-trained two million word vectors fastText learned on Common Crawl [45]. The word embedding is computed by representing a word as a bag of n-grams [46]. This word-internal …","url":["https://www.mdpi.com/2075-5309/13/2/377/pdf"]}
-{"year":"2023","title":"Automatic Detection in Twitter of Non-Traumatic Grief due to Deaths by COVID-19. A Deep Learning Approach","authors":["J Mata-Vázquez, V Pachón-Álvarez, E Gualda… - IEEE Access, 2023"],"snippet":"Non-traumatic grief can be defined as, a complex process that includes emotional, physical, spiritual, social, and intellectual behaviors and responses through which individuals, families, and communities incorporate actual, anticipated, or perceived …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10360118.pdf"]}
-{"year":"2023","title":"Automatic Extraction of Conversation Flows from Human Dialogues: Understanding Their Impact to Refine NLP Models","authors":["MF Sanches, JMC de Sá, RR de Souza, AM de Souza… - SN Computer Science, 2023"],"snippet":"… Similarly, Common Crawl [23] is a continuously updated collection of Web pages. Due to its similarity to the BrWaC, the Common Crawl is … Smith JR, Saint-Amand H, Plamada M, Koehn P, Callison-Burch C, Lopez A, Dirt cheap web-scale parallel text …","url":["https://link.springer.com/article/10.1007/s42979-023-02148-7"]}
-{"year":"2023","title":"Automatic Extractive Text Summarization for Text in Nepali Language with Bidirectional Encoder Representation Transformers and K-Mean Clustering","authors":["C Pokhrel, R Adhikari"],"snippet":"… Pre-trained in over 104 diffiferent language of 2.5TB of filtered common crawl data corpus, XLMRoBERTa or XLM-R is a multilingual version of RoBERTa. It is a transformer based multilingual model which has been pretrained on large corpus of …","url":["https://www.researchgate.net/profile/Chitran-Pokhrel/publication/372221925_Automatic_Extractive_Text_Summarization_for_Text_in_Nepali_Language_with_Bidirectional_Encoder_Representation_Transformers_and_K-Mean_Clustering/links/64aa7f1dc41fb852dd60d232/Automatic-Extractive-Text-Summarization-for-Text-in-Nepali-Language-with-Bidirectional-Encoder-Representation-Transformers-and-K-Mean-Clustering.pdf"]}
-{"year":"2023","title":"Automatic generation of definitions: Exploring if GPT is useful for defining words","authors":["F Eriksson - 2023"],"snippet":"When reading a text, it is common to get stuck on unfamiliar words that are difficult to understand in the local context. In these cases, we use dictionaries or similar online resources to find the general meaning of the word. However, maintaining a …","url":["https://www.diva-portal.org/smash/get/diva2:1791309/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Automatic Generation of German Drama Texts Using Fine Tuned GPT-2 Models","authors":["M Bangura, K Barabashova, A Karnysheva, S Semczuk… - arXiv preprint arXiv …, 2023"],"snippet":"This study is devoted to the automatic generation of German drama texts. We suggest an approach consisting of two key steps: fine-tuning a GPT-2 model (the outline model) to generate outlines of scenes based on keywords and fine-tuning a …","url":["https://arxiv.org/pdf/2301.03119"]}
-{"year":"2023","title":"Automatic Genre Identification for Robust Enrichment of Massive Text Collections: Investigation of Classification Methods in the Era of Large Language Models","authors":["T Kuzman, I Mozetič, N Ljubešić - Machine Learning and Knowledge Extraction, 2023"],"snippet":"… The XLM-RoBERTa model was pre-trained on the CommonCrawl multilingual data [52], which comprise 167 billion tokens in 100 languages, out of which Slovenian is represented by 1.7 billion tokens. We use the base-sized model that …","url":["https://www.mdpi.com/2504-4990/5/3/59"]}
-{"year":"2023","title":"Automatic information extraction in business document","authors":["SA Moreno Acevedo - 2023"],"snippet":"… This model was pre-trained with 2.5 TB of text data from the Common Crawl corpus [67], which includes text in 100 different languages. This extensive pre-training has allowed RoBERTa to compute text representations in multiple languages …","url":["https://bibliotecadigital.udea.edu.co/bitstream/10495/37581/1/MorenoSantiago_2023_InformationExtractionDeepLearningNaturalLanguageProcessing.pdf"]}
-{"year":"2023","title":"Automatic login form leakage detection for website administrators","authors":["SW de Vries, G Acar, E Poll - 2023"],"snippet":"… We crawled a list of 30K web pages with login forms from a list composed by Roefs [56] using the the Tranco top 100K domains from a Common Crawl snapshot from November/December 2021. The Common Crawl dataset consists of a large …","url":["https://www.ru.nl/publish/pages/769526/steven_wallis_de_vries.pdf"]}
-{"year":"2023","title":"Automatic Methods for Extracting Taxonomic Relationships from Texts","authors":["NV Loukachevitch - Pattern Recognition and Image Analysis, 2023"],"snippet":"… Fasttext embeddings [5], which were calculated on the Internet corpus of Common Crawl and Wikipedia, Footnote 1 turned out to be the best vector representation for predicting hypernyms. The best method in this testing was the …","url":["https://link.springer.com/article/10.1134/S1054661823030276"]}
-{"year":"2023","title":"Automatic Multilingual Question Generation for Health Data Using LLMs","authors":["R Ackerman, R Balyan - International Conference on AI-generated Content, 2023"],"snippet":"Question Generation (QG) involves automatic generation of yes/no, factual and Wh-questions created from data sources such as a database, raw text or semantic representation. QG can be used in an adaptive intelligent tutoring system or a dialog system for …","url":["https://link.springer.com/chapter/10.1007/978-981-99-7587-7_1"]}
-{"year":"2023","title":"Automatic pull request title generation.(2022)","authors":["T ZHANG, IC IRSAN, F THUNG, DG HAN, D LO… - 2022 IEEE International …"],"snippet":"… Unlike BART, T5 was pre-trained with the Colossal Clean Crawled Corpus (C4) dataset, which consists of 750GB of English text from the public Common Crawl web scrape. T5 was reported to achieve state-of-the-art results on many benchmarks …","url":["https://ink.library.smu.edu.sg/context/sis_research/article/8702/viewcontent/automatic.pdf"]}
-{"year":"2023","title":"Automatic Scoring of Creative Problem-Solving with Large Language Models: A Comparison of Originality and Quality Ratings","authors":["S Luchini, NT Maliakkal, PV DiStefano, JD Patterson… - 2023"],"snippet":"… a collection of data from the Toronto BookCorpus (800M words), the English portion of Wikipedia (2,500M words), the CCNews English dataset (63M news articles), the OpenWebText dataset of Reddit posts, and the Stories dataset which …","url":["https://psyarxiv.com/g5qvf/download?format=pdf"]}
-{"year":"2023","title":"Automatic Subjective Answer Grading Software Using Machine Learning","authors":["R Kothari, B Rangwala, K Patel - 2023 7th International Conference on Trends in …, 2023"],"snippet":"One of the major challenges during online examinations is the assessment of answers, particularly of the subjective type. Subjective answers test a student's ability to retain information and express it in natural language. While objective …","url":["https://ieeexplore.ieee.org/abstract/document/10125786/"]}
-{"year":"2023","title":"Automatic Summarization of Validated Intelligence Events","authors":["TEO BECERRA, L JOHANSSON - 2023"],"snippet":"… Fortunately there exists one very large dataset, which is the Common Crawl dataset that consist of nearly a trillion words. Common Crawl is a dataset that has been obtained by crawling the web and therefore the quality of data is quite low …","url":["https://odr.chalmers.se/bitstreams/67a971d6-44e2-435c-bab7-8ed1a6899915/download"]}
-{"year":"2023","title":"Automatically Assembling a Custom-Built Training Corpus for Improving the Learning of In-Domain Word/Document Embeddings","authors":["Y Blanco-Fernández, A Gil-Solla, JJ Pazos-Arias… - Informatica, 2023"],"snippet":"Embedding models turn words/documents into real-number vectors via co-occurrence data from unrelated texts. Crafting domain-specific embeddings from general corpora with limited domain vocabulary is challenging. Existing solutions retrain …","url":["https://informatica.vu.lt/journal/INFORMATICA/article/1304/text"]}
-{"year":"2023","title":"Automatically Preventing, Detecting and Repairing Crucial Errors in Programs","authors":["J Zhang - 2023"],"snippet":"Today, high-impact errors in programs result in huge money losses, are notoriously expensive for programmers to repair, and affect millions of real-world users. This dissertation highlights the need to move beyond our post-mortem manual error …","url":["https://search.proquest.com/openview/7de4fd51ae4ca079578859561188cd2b/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Automating democracy: Generative AI, journalism, and the future of democracy","authors":["AR Arguedas, FM Simon - 2023"],"snippet":"Sophisticated AI systems are increasingly everywhere. In many ways, we have already been affected by the rollout of AI systems into more and more areas of life, from insurance and law to healthcare and the media – often without really noticing …","url":["https://ora.ox.ac.uk/objects/uuid:0965ad50-b55b-4591-8c3b-7be0c587d5e7/download_file?file_format=application%2Fpdf&safe_filename=Arguedas_and_Simon_2023_Automating_democracy__Generative.pdf&type_of_work=Report"]}
-{"year":"2023","title":"AutoPCF: Efficient Product Carbon Footprint Accounting with Large Language Models","authors":["Z Deng, J Liu, B Luo, C Yuan, Q Yang, L Xiao, W Zhou… - arXiv preprint arXiv …, 2023"],"snippet":"… The GPT3.5 and GPT-4 training datasets include the Common Crawl dataset, the Webtext2 dataset, two internet-based book corpora, and Wikipedia7. The Common Crawl dataset, which contributes 60% of the total weight in the training mix, contains …","url":["https://arxiv.org/pdf/2308.04241"]}
-{"year":"2023","title":"B\\\"{u} y\\\"{u} k dil modellerinin T\\\"{u} rk\\c {c} e verisetleri ile e\\u {g} itilmesi ve ince ayarlanmas\\i","authors":["AT Arslan - arXiv preprint arXiv:2306.03978, 2023"],"snippet":"Large language models have advanced enormously, gained vast attraction and are having a phase of intensed research. Some of the developed models and training datasets have been made open-accessible. Hence these may be further fine-tuned …","url":["https://arxiv.org/pdf/2306.03978"]}
-{"year":"2023","title":"Bachelor Thesis Emergent Theory of Mind in Large Language Models","authors":["M Terentev"],"snippet":"… The emergence of transformers, known for their reduced training time compared to older long short-term memory (LSTM) models, has enabled utilizing large language datasets like the Wikipedia Corpus and Common Crawl for training …","url":["https://bnaic2023.tudelft.nl/static/media/BNAICBENELEARN_2023_paper_129.7ab7694ad3fe7122da37.pdf"]}
-{"year":"2023","title":"Bachelor's Thesis Assignment","authors":["C Perone"],"snippet":"When it comes to language learning apps that allow sentence-like answers, accurately estimating the correctness score is crucial. A possible approach is to compute the semantic similarity of input sentences and predefined correct answers …","url":["https://dspace.vutbr.cz/bitstream/handle/11012/211150/final-thesis.pdf?sequence=-1"]}
-{"year":"2023","title":"Back to common sense: Oxford dictionary descriptive knowledge augmentation for aspect-based sentiment analysis","authors":["W Jin, B Zhao, L Zhang, C Liu, H Yu - Information Processing & Management, 2023"],"snippet":"Aspect-based Sentiment Analysis (ABSA) is a crucial natural language understanding (NLU) research field which aims to accurately recognize reviewers’ opinions on different aspects of products and services. Despite the prominence of …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322003612"]}
-{"year":"2023","title":"Back Transcription as a Method for Evaluating Robustness of Natural Language Understanding Models to Speech Recognition Errors","authors":["M Kubis, P Skórzewski, M Sowański, T Ziętkiewicz - arXiv preprint arXiv:2310.16609, 2023"],"snippet":"In a spoken dialogue system, an NLU model is preceded by a speech recognition system that can deteriorate the performance of natural language understanding. This paper proposes a method for investigating the impact of speech recognition …","url":["https://arxiv.org/pdf/2310.16609"]}
-{"year":"2023","title":"Back Translation for Speech-to-text Translation Without Transcripts","authors":["Q Fang, Y Feng - arXiv preprint arXiv:2305.08709, 2023"],"snippet":"… Specifically, we use europarl v78, commoncrawl9, news commentary v1210 subsets for all three languages. The source text is never used … 8http://statmt.org/wmt13/ training-parallel-europarl-v7.tgz 9http://statmt.org/wmt13/ training-parallel-commoncrawl.tgz …","url":["https://arxiv.org/pdf/2305.08709"]}
-{"year":"2023","title":"Backdoor Learning on Sequence to Sequence Models","authors":["L Chen, M Cheng, H Huang - arXiv preprint arXiv:2305.02424, 2023"],"snippet":"Backdoor learning has become an emerging research area towards building a trustworthy machine learning system. While a lot of works have studied the hidden danger of backdoor attacks in image or text classification, there is a limited …","url":["https://arxiv.org/pdf/2305.02424"]}
-{"year":"2023","title":"BacklinkDB: A Purpose-Built Backlink Database Management System","authors":["ML Jørgensen - 2023"],"snippet":"… Common Crawl is a non-profit organization that periodically crawls the web and publicizes data. For the experiments … Common Crawl provides data on all the indexable webpages. This data is provided in a series of warc files found in their …","url":["https://munin.uit.no/bitstream/handle/10037/28861/thesis.pdf?sequence=2&isAllowed=y"]}
-{"year":"2023","title":"Bag of Words and Embedding Text Representation Methods for Medical Article Classification","authors":["P Cichosz - International Journal of Applied Mathematics and …, 2023"],"snippet":"… vectors pre-trained on the Common Crawl corpus were used.For training custom fastText vectors, the fasttext Python library10 was used (Bojanowski et al., 2020), with vector dimensionality set to 100, SG training mode, and other parameters left at …","url":["https://sciendo.com/pdf/10.34768/amcs-2023-0043"]}
-{"year":"2023","title":"Baichuan 2: Open Large-scale Language Models","authors":["A Yang, B Xiao, B Wang, B Zhang, C Yin, C Lv, D Pan… - arXiv preprint arXiv …, 2023"],"snippet":"… For instance, the main data source for LLaMA is Common Crawl1, which comprises 67% of LLaMA’s pre-training data but is filtered to English content only. Other open source LLMs such as MPT (MosaicML… 1https://commoncrawl.org/ …","url":["https://arxiv.org/pdf/2309.10305"]}
-{"year":"2023","title":"Balancing of tourist opinions for sentiment analysis task","authors":["AB García-Gutiérrez, PE López-Ávila… - 2023"],"snippet":"This article presents a proposal for the treatment of an unbalanced tourist database with emphasis on minority classes for its classification, in this case, one based on BERT, called BETO. This methodology originally forms part of the thesis project of …","url":["https://ceur-ws.org/Vol-3496/restmex-paper8.pdf"]}
-{"year":"2023","title":"BanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla","authors":["A Bhattacharjee, T Hasan, W Ahmad, R Shahriyar - Findings of the Association for …, 2023"],"snippet":"This work presents ‘BanglaNLG,’a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language. We aggregate six challenging conditional text generation tasks under the …","url":["https://aclanthology.org/2023.findings-eacl.54.pdf"]}
-{"year":"2023","title":"Basic Principles of Cross-Lingual Models","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"When we start working across languages, we need to determine ways of measuring similarity of entities (such as a word, a phrase, a sentence or a link between entities) within each language and across languages. Modern approaches usually rely on …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_2"]}
-{"year":"2023","title":"Behind the Scenes: Examining Efficacy of Race Classification Models with a Focus on TV","authors":["J WANG - 2023"],"snippet":"This thesis explores the use of web scraping and machine learning to enhance the predictive power of current race classification models. With the rise of online data as an important source for research, the availability of race labels typically acquired …","url":["https://www.jennywang.me/files/undergrad-thesis.pdf"]}
-{"year":"2023","title":"BELT: Bootstrapping Electroencephalography-to-Language Decoding and Zero-Shot Sentiment Classification by Natural Language Supervision","authors":["J Zhou, Y Duan, YC Chang, YK Wang, CT Lin - arXiv preprint arXiv:2309.12056, 2023"],"snippet":"This paper presents BELT, a novel model and learning framework for the pivotal topic of brain-to-language translation research. The translation from noninvasive brain signals into readable natural language has the potential to promote the …","url":["https://arxiv.org/pdf/2309.12056"]}
-{"year":"2023","title":"Benchmark for Evaluation of Danish Clinical Word Embeddings","authors":["MS Laursen, JS Pedersen, PJ Vinholt, RS Hansen… - Northern European Journal …, 2023"],"snippet":"In natural language processing, benchmarks are used to track progress and identify useful models. Currently, no benchmark for Danish clinical word embeddings exists. This paper describes the development of a Danish benchmark for clinical word …","url":["https://nejlt.ep.liu.se/article/download/4132/3825"]}
-{"year":"2023","title":"Benchmark tasks for evaluation of language models","authors":["S Hamotskyi"],"snippet":"Language models (LMs) are an integral part of NLP, with their importance sharply increasing in recent years with the advent of large generalized LMs (such as OpenAI GPT and BERT) that reach and in some cases surpass the level of nonexpert …","url":["https://serhii.net/s/SerhiiHamotskyiBenchmarks.pdf"]}
-{"year":"2023","title":"Benchmarking and Analyzing In-context Learning, Fine-tuning and Supervised Learning for Biomedical Knowledge Curation: a focused study on chemical entities of …","authors":["E Groves, M Wang, Y Abdulle, H Kunz… - arXiv preprint arXiv …, 2023"],"snippet":"Automated knowledge curation for biomedical ontologies is key to ensure that they remain comprehensive, high-quality and up-to-date. In the era of foundational language models, this study compares and analyzes three NLP paradigms for …","url":["https://arxiv.org/pdf/2312.12989"]}
-{"year":"2023","title":"Benchmarking Arabic AI with Large Language Models","authors":["A Abdelali, H Mubarak, SA Chowdhury, M Hasanain… - arXiv preprint arXiv …, 2023"],"snippet":"… GPT-3 is trained mainly using a filtered version of Common Crawl dataset. The filtering is based on similarity to high-quality reference corpora. Fuzzy deduplication at document level is performed to remove redundancy and avoid contamination of …","url":["https://arxiv.org/pdf/2305.14982"]}
-{"year":"2023","title":"Benchmarking Large Language Model Capabilities for Conditional Generation","authors":["J Maynez, P Agrawal, S Gehrmann - arXiv preprint arXiv:2306.16793, 2023"],"snippet":"Pre-trained large language models (PLMs) underlie most new developments in natural language processing. They have shifted the field from application-specific model pipelines to a single model that is adapted to a wide range of tasks …","url":["https://arxiv.org/pdf/2306.16793"]}
-{"year":"2023","title":"Benchmarking Multilabel Topic Classification in the Kyrgyz Language","authors":["A Alekseev, SI Nikolenko, G Kabaeva - arXiv preprint arXiv:2308.15952, 2023"],"snippet":"Kyrgyz is a very underrepresented language in terms of modern natural language processing resources. In this work, we present a new public benchmark for topic classification in Kyrgyz, introducing a dataset based on collected and annotated …","url":["https://arxiv.org/pdf/2308.15952"]}
-{"year":"2023","title":"Benchmarking Procedural Language Understanding for Low-Resource Languages: A Case Study on Turkish","authors":["A Uzunoğlu, GG Şahin - arXiv preprint arXiv:2309.06698, 2023"],"snippet":"Understanding procedural natural language (eg, step-by-step instructions) is a crucial step to execution and planning. However, while there are ample corpora and downstream tasks available in English, the field lacks such resources for most …","url":["https://arxiv.org/pdf/2309.06698"]}
-{"year":"2023","title":"Bengali Text Classification: A New multi-class Dataset and Performance Evaluation of Machine Learning and Deep Learning Models","authors":["A Roy, K Sarkar, CK Mandal - 2023"],"snippet":"This study focuses on Bengali text classification using machine learning and deep learning techniques. Text classification is a fundamental task in natural language processing (NLP) that involves categorizing text documents into predefined …","url":["https://www.researchsquare.com/article/rs-3129157/latest.pdf"]}
-{"year":"2023","title":"BERT Goes Off-Topic: Investigating the Domain Transfer Challenge using Genre Classification","authors":["D Roussinov, S Sharoff - arXiv preprint arXiv:2311.16083, 2023"],"snippet":"While performance of many text classification tasks has been recently improved due to Pre-trained Language Models (PLMs), in this paper we show that they still suffer from a performance gap when the underlying distribution of topics changes. For …","url":["https://arxiv.org/pdf/2311.16083"]}
-{"year":"2023","title":"BERT-based ensemble learning for multi-aspect hate speech detection","authors":["AC Mazari, N Boudoukhani, A Djeffal - Cluster Computing, 2023"],"snippet":"… After testing FastText embedding pre-trained on Wikipedia texts and those pre-trained on Common Crawl corpus, Footnote 2 we choose to use the FastText vectors pre-trained on Common Crawl data because they provide us the best results for all the …","url":["https://link.springer.com/article/10.1007/s10586-022-03956-x"]}
-{"year":"2023","title":"BERTinchamps: Cost-Effective Training of Large Language Models for Medical Tasks in French","authors":["A Fierens, S Jodogne - 2023"],"snippet":"… The OSCAR dataset is an extensive multilingual corpus acquired through language classification and filtering of the Common Crawl corpus employing the goclassy architecture. A subset of 17GB of the French part of the OSCAR dataset …","url":["http://sag.art.uniroma2.it/NL4AI/wp-content/uploads/2023/10/paper1.pdf"]}
-{"year":"2023","title":"BERTuit: Understanding Spanish language in Twitter with transformers","authors":["J Huertas‐Tato, A Martín, D Camacho - Expert Systems, 2023"],"snippet":"The appearance of complex attention‐based language models such as BERT, RoBERTa or GPT‐3 has allowed to address highly complex tasks in a plethora of scenarios. However, when applied to specific domains, these models encounter …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/exsy.13404"]}
-{"year":"2023","title":"Better conditioning on context for natural language processing","authors":["Q Liu - 2022"],"snippet":"… T5 introduces a new pre-training dataset, Colossal Clean Crawled Corpus by cleaning the web pages from Common Crawl. T5 also systematically compares previous methods in terms of pre-training objectives, architectures, pre-training …","url":["https://ora.ox.ac.uk/objects/uuid:abaab43c-638d-444a-b172-2a1abbb17a2d/download_file?file_format=application%2Fpdf&safe_filename=Liu_2022_Better_conditioning_on.pdf&type_of_work=Thesis"]}
-{"year":"2023","title":"Better Language Support and Pragmatic System Designs for Automatic Text Summarization","authors":["D Varab - 2023"],"snippet":"… Common approaches to acquiring large amounts of text data usually involve filtering large snapshots of the internet distributed by online archives like CommonCrawl3. Such approaches provide virtually endless amounts of text data …","url":["https://en.itu.dk/-/media/EN/Research/PhD-Programme/PhD-defences/2023/PhD-Thesis-Temporary-Version-Daniel-Varab-pdf.pdf"]}
-{"year":"2023","title":"Better Quality Pre-training Data and T5 Models for African Languages","authors":["A Oladipo, M Adeyemi, O Ahia, A Owodunni… - Proceedings of the 2023 …, 2023"],"snippet":"… 2019), Wikipedia and Common Crawl archive. The latter often has significant quality issues (Kreutzer et al.… noisier common crawl data. Obtaining such highquality data is tedious since it involved curating several verified sources manually. Thus …","url":["https://aclanthology.org/2023.emnlp-main.11.pdf"]}
-{"year":"2023","title":"Better Translation+ Split and Generate for Multilingual RDF-to-Text (WebNLG 2023)","authors":["N Kumar, SOU Islam, O Dušek - Proceedings of the Workshop on Multimodal …, 2023"],"snippet":"This paper presents system descriptions of our submitted outputs for WebNLG Challenge 2023. We use mT5 in multi-task and multilingual settings to generate more fluent and reliable verbalizations of the given RDF triples. Furthermore, we …","url":["https://aclanthology.org/2023.mmnlg-1.8.pdf"]}
-{"year":"2023","title":"Beyond Document Page Classification: Design, Datasets, and Challenges","authors":["J Van Landeghem, S Biswas, MB Blaschko, MF Moens - arXiv preprint arXiv …, 2023"],"snippet":"This paper highlights the need to bring document classification benchmarking closer to real-world applications, both in the nature of data tested ($X$: multi-channel, multi-paged, multi-industry; $Y$: class distributions and label set variety) and in classification …","url":["https://arxiv.org/pdf/2308.12896"]}
-{"year":"2023","title":"Beyond Extractive: Advancing Abstractive Automatic Text Summarization in Norwegian with Transformers","authors":["JJ Navjord, JMR Korsvik - 2023"],"snippet":"Automatic summarization is a key area in natural language processing (NLP) and machine learning which attempts to generate informative summaries of articles and documents. Despite its evolution since the 1950s, research on automatically …","url":["https://nmbu.brage.unit.no/nmbu-xmlui/bitstream/handle/11250/3079868/no.nmbu:wiseflow:6839553:54763253.pdf?sequence=1"]}
-{"year":"2023","title":"Beyond Fish and Bicycles: Exploring the Varieties of Online Women's Ideological Spaces","authors":["U Balci, C Ling, E De Cristofaro, M Squire, G Stringhini… - arXiv preprint arXiv …, 2023"],"snippet":"The Internet has been instrumental in connecting under-represented and vulnerable groups of people. Platforms built to foster social interaction and engagement have enabled historically disenfranchised groups to have a voice. One such vulnerable …","url":["https://arxiv.org/pdf/2303.07099"]}
-{"year":"2023","title":"Beyond quantity of experience: Exploring the role of semantic consistency in Chinese character knowledge.","authors":["CY Hsieh, M Marelli, K Rastle - … of Experimental Psychology: Learning, Memory, and …, 2023"],"snippet":"Most printed Chinese words are compounds built from the combination of meaningful characters. Yet, there is a poor understanding of how individual characters contribute to the recognition of compounds. Using a megastudy of …","url":["https://psycnet.apa.org/record/2024-20164-001"]}
-{"year":"2023","title":"Beyond Scale: the Diversity Coefficient as a Data Quality Metric Demonstrates LLMs are Pre-trained on Formally Diverse Data","authors":["A Lee, B Miranda, S Koyeyo"],"snippet":"… more stringent preprocessing method applied to the Common Crawl corpus for Pile-CC, which contributes to enhanced data diversity. … Since many canonical datasets already exist and are publicly available (eg Common Crawl, Wikipedia) …","url":["https://brando90.github.io/brandomiranda/professional_documents/ICML_2023_DeployGenAI_Workshop__Diversity_Coefficient___LLMs__6pg_.pdf"]}
-{"year":"2023","title":"bgGLUE: A Bulgarian General Language Understanding Evaluation Benchmark","authors":["M Hardalov, P Atanasova, T Mihaylov, G Angelova… - arXiv preprint arXiv …, 2023"],"snippet":"We present bgGLUE (Bulgarian General Language Understanding Evaluation), a benchmark for evaluating language models on Natural Language Understanding (NLU) tasks in Bulgarian. Our benchmark includes NLU tasks targeting a variety of NLP …","url":["https://arxiv.org/pdf/2306.02349"]}
-{"year":"2023","title":"Bhagavad Geeta Based ChatBot","authors":["A Karekar, S Limaye, A Nara, S Panchal - 2023 3rd International Conference on …, 2023"],"snippet":"… By merging data from Common Crawl and WebText, a significantly larger and more varied dataset was used to train the model. … A wide variety of data sources, including BookCorpus, Common Crawl, and Wikipedia, are used to train the GPT-3 …","url":["https://ieeexplore.ieee.org/iel7/10205372/10205375/10205716.pdf"]}
-{"year":"2023","title":"Bias Against 93 Stigmatized Groups in Masked Language Models and Downstream Sentiment Classification Tasks","authors":["KX Mei, S Fereidooni, A Caliskan - arXiv preprint arXiv:2306.05550, 2023"],"snippet":"The rapid deployment of artificial intelligence (AI) models demands a thorough investigation of biases and risks inherent in these models to understand their impact on individuals and society. This study extends the focus of bias evaluation in extant …","url":["https://arxiv.org/pdf/2306.05550"]}
-{"year":"2023","title":"Bias Detection for Customer Interaction Data: A Survey on Datasets, Methods, and Tools","authors":["A Donald, A Galanopoulos, E Curry, E Muñoz, I Ullah… - IEEE Access, 2023"],"snippet":"… It is important to highlight that these embedders, though often built on Wikipedia or CommonCrawl, can be trained on a vast variety of text … on CommonCrawl, and trained on Twitter tweets. They found Twitter embeddings to produce the greatest …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10126086.pdf"]}
-{"year":"2023","title":"Biases in Large Language Models: Origins, Inventory and Discussion","authors":["R Navigli, S Conia, B Ross - ACM Journal of Data and Information Quality, 2023"],"snippet":"In this paper, we introduce and discuss the pervasive issue of bias in the large language models that are currently at the core of mainstream approaches to Natural Language Processing (NLP). We first introduce data selection bias, that is, the bias …","url":["https://dl.acm.org/doi/pdf/10.1145/3597307"]}
-{"year":"2023","title":"Bidirectional Contrastive Split Learning for Visual Question Answering","authors":["Y Sun, H Ochiai"],"snippet":"Visual Question Answering (VQA) based on multi-modal data facilitates real-life applications such as home robots and medical diagnoses. One significant challenge is to devise a robust decentralized learning framework for various client models …","url":["https://www.researchgate.net/profile/Yuwei-Sun-14/publication/362908270_Bidirectional_Contrastive_Split_Learning_for_Visual_Question_Answering/links/64d44adf1290c33cce7dbf0f/Bidirectional-Contrastive-Split-Learning-for-Visual-Question-Answering.pdf"]}
-{"year":"2023","title":"Bilingual Terminology Alignment Using Contextualized Embeddings","authors":["I Setha, H Aliane - Proceedings of the Workshop on Computational …, 2023","S Imene, A Algeria, A Hassina - Computational Terminology in NLP and Translation …, 2023"],"snippet":"… In our work, we choose to use the Multilingual Elmo embeddings2, which was pre-trained on 20 million words data randomly sampled from the raw text released by the shared task wiki dump + common crawl, (github…","url":["https://aclanthology.org/2023.contents-1.1.pdf","https://aclanthology.org/2023.contents-1.pdf#page=7"]}
-{"year":"2023","title":"Binary Code Summarization: Benchmarking ChatGPT/GPT-4 and Other Large Language Models","authors":["X Jin, J Larson, W Yang, Z Lin - arXiv preprint arXiv:2312.09601, 2023"],"snippet":"Binary code summarization, while invaluable for understanding code semantics, is challenging due to its labor-intensive nature. This study delves into the potential of large language models (LLMs) for binary code comprehension. To this end, we …","url":["https://arxiv.org/pdf/2312.09601"]}
-{"year":"2023","title":"Biologically Plausible Sparse Temporal Word Representations","authors":["Y Liu, W Chen, H Liu, Y Zhang, M Zhang, H Qu - IEEE Transactions on Neural …, 2023"],"snippet":"… In our experiment, we use the pretrained GloVe10(“Common Crawl” version with 2.2M vocabulary) and Word2Vec11(“Google News” version with 3.0M vocabulary) of 300 dimensions, as well as BERT-mini(256 dimensions and four layers) and BERT-base(768 …","url":["https://ieeexplore.ieee.org/abstract/document/10173851/"]}
-{"year":"2023","title":"BIOptimus: Pre-training an Optimal Biomedical Language Model with Curriculum Learning for Named Entity Recognition","authors":["P Vera, M Makhlouf - arXiv preprint arXiv:2308.08625, 2023","V Pavlova, M Makhlouf - The 22nd Workshop on Biomedical Natural Language …, 2023"],"snippet":"Using language models (LMs) pre-trained in a self-supervised setting on large corpora and then fine-tuning for a downstream task has helped to deal with the problem of limited label data for supervised learning tasks such as Named Entity …","url":["https://aclanthology.org/2023.bionlp-1.31.pdf","https://arxiv.org/pdf/2308.08625"]}
-{"year":"2023","title":"Bipolar Sentiment Analysis of Japanese Social Media Posts: A Semantic Similarity Based Approach","authors":["MFF Khan, N Oi, K Sakamura - 2023 Sixth International Symposium on Computer …, 2023"],"snippet":"… These vectors are trained on Common Crawl and Wikipedia using fastText with the following configuration: CBOW (continuous bag of words) with position-weights, in dimension 300, with character n-grams of length 5, a window of size 5 and 10 …","url":["https://ieeexplore.ieee.org/abstract/document/10219460/"]}
-{"year":"2023","title":"BiSync: A Bilingual Editor for Synchronized Monolingual Texts","authors":["J Crego, J Xu, F Yvon - arXiv preprint arXiv:2306.00400, 2023"],"snippet":"In our globalized world, a growing number of situations arise where people are required to communicate in one or several foreign languages. In the case of written communication, users with a good command of a foreign language may find …","url":["https://arxiv.org/pdf/2306.00400"]}
-{"year":"2023","title":"Bit Cipher--A Simple yet Powerful Word Representation System that Integrates Efficiently with Language Models","authors":["H Zhao, JR Williams - arXiv preprint arXiv:2311.11012, 2023"],"snippet":"While Large Language Models (LLMs) become ever more dominant, classic pre-trained word embeddings sustain their relevance through computational efficiency and nuanced linguistic interpretation. Drawing from recent studies demonstrating that the …","url":["https://arxiv.org/pdf/2311.11012"]}
-{"year":"2023","title":"BiTimeBERT: Extending Pre-Trained Language Representations with Bi-Temporal Information","authors":["J Wang, A Jatowt, M Yoshikawa, Y Cai - Proceedings of the 46th International ACM …, 2023"],"snippet":"Time is an important aspect of documents and is used in a range of NLP and IR tasks. In this work, we investigate methods for incorporating temporal information during pre-training to further improve the performance on time-related tasks. Compared …","url":["https://dl.acm.org/doi/pdf/10.1145/3539618.3591686"]}
-{"year":"2023","title":"BitNet: Scaling 1-bit Transformers for Large Language Models","authors":["H Wang, S Ma, L Dong, S Huang, H Wang, L Ma… - arXiv preprint arXiv …, 2023"],"snippet":"The increasing size of large language models has posed challenges for deployment and raised concerns about environmental impact due to high energy consumption. In this work, we introduce BitNet, a scalable and stable 1-bit Transformer …","url":["https://arxiv.org/pdf/2310.11453"]}
-{"year":"2023","title":"Black Ostrich: Web Application Scanning with String Solvers","authors":["B Eriksson, A Stjerna, R De Masellis, P Rüemmer… - Proceedings of the 2023 …, 2023"],"snippet":"… We evaluate Black Ostrich on a set of 8,820 unique validation patterns gathered from over 21,667,978 forms from a combination of the July 2021 Common~Crawl and Tranco top 100K. For these forms and reconstructions of input elements …","url":["https://dl.acm.org/doi/abs/10.1145/3576915.3616582"]}
-{"year":"2023","title":"Blacks is to Anger as Whites is to Joy? Understanding Latent Affective Bias in Large Pre-trained Neural Language Models","authors":["A Kadan, S Bhadra, MP Gangan - arXiv preprint arXiv:2301.09003, 2023"],"snippet":"… Details of training corpora used for corpus level affective bias analysis (†Giga5, ClueWeb, & Common Crawl used to pre-train XLNet are … We omit Giga5 and ClueWeb due to their unavailability as open-source corpora and Common Crawl as …","url":["https://arxiv.org/pdf/2301.09003"]}
-{"year":"2023","title":"BloombergGPT: A Large Language Model for Finance","authors":["S Wu, O Irsoy, S Lu, V Dabravolski, M Dredze… - arXiv preprint arXiv …, 2023"],"snippet":"The use of NLP in the realm of financial technology is broad and complex, with applications ranging from sentiment analysis and named entity recognition to question answering. Large Language Models (LLMs) have been shown to be …","url":["https://arxiv.org/pdf/2303.17564"]}
-{"year":"2023","title":"BongHope: An Annotated Corpus for Bengali Hope Speech Detection","authors":["T Nath, VK Singh, V Gupta - 2023"],"snippet":"… It is pretrained on 2.5TB data from CommonCrawl corpus, consisting of 100 languages. XLMRoberta tokenizer is used to tokenize the tweets, which are then fed to the ‘xlm-robertabase’ encoder to obtain the word embeddings (Conneau et al …","url":["https://www.researchsquare.com/article/rs-2819284/latest.pdf"]}
-{"year":"2023","title":"Bootstrapped nDCG Estimation in the Presence of Unjudged Documents","authors":["M Fröbe, L Gienapp, M Potthast, M Hagen - … , ECIR 2023, Dublin, Ireland, April 2–6 …, 2023"],"snippet":"Retrieval studies often reuse TREC collections after the corresponding tracks have passed. Yet, a fair evaluation of new systems that retrieve documents outside the original judgment pool is not straightforward. Two common ways of dealing with …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28244-7_20"]}
-{"year":"2023","title":"Bots Behaving Badly: A Products Liability Approach to Chatbot-Generated Defamation","authors":["N Brown - J. FREE SPEECH L., 2023"],"snippet":"Within two months of its launch, ChatGPT became the fastest-growing consumer application in history with more than 100 million monthly active users. 1 Created by OpenAI, a private company backed by Microsoft, ChatGPT is just one * Associate …","url":["https://www.journaloffreespeechlaw.org/brown.pdf"]}
-{"year":"2023","title":"Breaking the Bias: Gender Fairness in LLMs Using Prompt Engineering and In-Context Learning","authors":["S Dwivedi, S Ghosh, S Dwivedi - 2023"],"snippet":"Large Language Models (LLMs) have been identified as carriers of societal biases, particularly in gender representation. This study introduces an innovative approach employing prompt engineering and incontext learning to rectify these biases in LLMs …","url":["https://rupkatha.com/V15/n4/v15n410.pdf"]}
-{"year":"2023","title":"Bridging the Resource Gap in Cross-Lingual Embedding Space","authors":["K Bhowmik, A Ralescu - Modelling and Development of Intelligent Systems: 8th …, 2023"],"snippet":"… XLM-R uses CommonCrawl as the source of data instead of Wikipedia. The larger amount of data available through CommonCrawl has resulted in performance improvement for low-resource languages. We intend to explore these models in the future. …","url":["https://link.springer.com/chapter/10.1007/978-3-031-27034-5_8"]}
-{"year":"2023","title":"Bringing legal knowledge to the public by constructing a legal question bank using large-scale pre-trained language model","authors":["M Yuan, B Kao, TH Wu, MMK Cheung, HWH Chan… - Artificial Intelligence and …, 2023"],"snippet":"Access to legal information is fundamental to access to justice. Yet accessibility refers not only to making legal documents available to the public, but also rendering legal information comprehensible to them. A vexing problem in bringing legal …","url":["https://link.springer.com/article/10.1007/s10506-023-09367-6"]}
-{"year":"2023","title":"Bringing order into the realm of Transformer-based language models for artificial intelligence and law","authors":["CM Greco, A Tagarelli - arXiv preprint arXiv:2308.05502, 2023"],"snippet":"… The training data is obtained from a filtered and cleaned version of CommonCrawl and consists of more than 2TB of data in 100 languages. Sub-word tokenization is directly applied on the raw text for all languages using a …","url":["https://arxiv.org/pdf/2308.05502"]}
-{"year":"2023","title":"Broader and Deeper: A Multi-Features with Latent Relations BERT Knowledge Tracing Model","authors":["J Wang - Responsive and Sustainable Educational Futures: 18th …, 2023"],"snippet":"Knowledge tracing aims to estimate students’ knowledge state or skill mastering level over time, which is evolving into an essential task in educational technology. Traditional knowledge tracing algorithms generally use one or a few features to …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=E_3TEAAAQBAJ&oi=fnd&pg=PA183&dq=commoncrawl&ots=wvqwSbXE_y&sig=vfUdeSoEi4hjXSWnN2P9caJRy0M"]}
-{"year":"2023","title":"BTLM-3B-8K: 7B Parameter Performance in a 3B Parameter Model","authors":["N Dey, D Soboleva, F Al-Khateeb, B Yang, R Pathria… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce the Bittensor Language Model, called \"BTLM-3B-8K\", a new state-of-the-art 3 billion parameter open-source language model. BTLM-3B-8K was trained on 627B tokens from the SlimPajama dataset with a mixture of 2,048 and 8,192 context …","url":["https://arxiv.org/pdf/2309.11568"]}
-{"year":"2023","title":"Bug Localization Model in Source Code using Ontologies","authors":["AS Da Silva, RE Garcia, LC Botega - IEEE Access, 2023"],"snippet":"… For this step, the GloVe model is pre-trained with 300dimensional vectors using the Common Crawl knowledge base [39]. As the vectors are pre-trained, the similarity is only checked for decomposed concept patterns that generate a token in …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10246255.pdf"]}
-{"year":"2023","title":"Building and Using Comparable Corpora for Multilingual Natural Language Processing","authors":["S Sharoff, R Rapp, P Zweigenbaum - 2023"],"snippet":"… [25] or the use of filtered Common Crawl data [26] with the assumption that different cultures use the Web for broadly similar purposes. … For example, the multilingual BERT is trained on Wikipedias, while XLM-Roberta is trained on the …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=47zSEAAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=-pQeIA_j8S&sig=CRJNraYlCx6hEb-VzxFIFPRgM_w"]}
-{"year":"2023","title":"Building Comparable Corpora","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"In a parallel corpus we know which document is a translation of what by design. If the link between documents in different languages is not known, it needs to be established. In this chapter we will discuss methods for measuring document …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_3"]}
-{"year":"2023","title":"BUILDING FLEXIBLE, SCALABLE, AND MACHINE LEARNING-READY MULTIMODAL ONCOLOGY DATASETS","authors":["A Tripathi, A Waqas, K Venkatesan, Y Yilmaz, G Rasool - arXiv preprint arXiv …, 2023"],"snippet":"… For example, the rise of large general-purpose datasets like Common Crawl [6] for natural language processing (NLP) has fueled advances in language models and Artificial Intelligence (AI) assistants. One may hope that extensive, standardized …","url":["https://arxiv.org/pdf/2310.01438"]}
-{"year":"2023","title":"Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models (Vision Paper)","authors":["J Rao, S Gao, G Mai, K Janowicz - 2023"],"snippet":"… For example, GPT-3 was pre-trained on a huge language corpus consisting of around 500 billion tokens from Web resources (eg, CommonCrawl, Wikipedia) and books. BLIP-2 and DINOv2 were pre-trained on 129 million images (with captions) …","url":["https://sigspatial2023.sigspatial.org/papers/paper_2437.pdf"]}
-{"year":"2023","title":"Building Privacy-Preserving and Secure Geospatial Artificial Intelligence Foundation Models","authors":["J Rao, S Gao, G Mai, K Janowicz - arXiv preprint arXiv:2309.17319, 2023"],"snippet":"In recent years we have seen substantial advances in foundation models for artificial intelligence, including language, vision, and multimodal models. Recent studies have highlighted the potential of using foundation models in geospatial artificial …","url":["https://arxiv.org/pdf/2309.17319"]}
-{"year":"2023","title":"Building Programmable Commons","authors":["P Terzis - 2023"],"snippet":"First, we asked ‘who shall govern the Internet?’as its decentralised and open nature promised a public sphere free from the manipulation and fragmentation of the ad-driven mass media.‘Commons’ was an omnipresent theme in this discourse. These …","url":["https://osf.io/preprints/socarxiv/yuef5/download"]}
-{"year":"2023","title":"Building Web-Based Subject-Specific Corpora on the Desktop: Evaluation of Search Metrics","authors":["JP Van Belle - … Intelligence: Select Proceedings of InCITe 2022, 2023"],"snippet":"Building subject-specific or domain corpora from Web data is well-researched. However, most approaches start by using seed articles as inputs to Web crawlers and take document similarity algorithms for selection. We take a different lean …","url":["https://link.springer.com/chapter/10.1007/978-981-19-7346-8_6"]}
-{"year":"2023","title":"BureauBERTo: adapting UmBERTo to the Italian bureaucratic language","authors":["S Auriemma, M Madeddu, M Miliani, A Bondielli… - 2023"],"snippet":"In this work, we introduce BureauBERTo, the first transformer-based language model adapted to the Italian Public Administration (PA) and technical-bureaucratic domains. We further pre-trained the general-purpose Italian model UmBERTo on a …","url":["https://colinglab.fileli.unipi.it/wp-content/uploads/2023/04/Ital_IA_2023_BureauBERTo.pdf"]}
-{"year":"2023","title":"calamanCy: A Tagalog Natural Language Processing Toolkit","authors":["LJV Miranda - arXiv preprint arXiv:2311.07171, 2023"],"snippet":"We introduce calamanCy, an open-source toolkit for constructing natural language processing (NLP) pipelines for Tagalog. It is built on top of spaCy, enabling easy experimentation and integration with other frameworks. calamanCy addresses the …","url":["https://arxiv.org/pdf/2311.07171"]}
-{"year":"2023","title":"Calibrating a Transformer-Based Model's Confidence on Community-Engaged Research Studies: Decision Support Evaluation Study","authors":["B Ferrell, SE Raskin, EB Zimmerman - JMIR Formative Research, 2023"],"snippet":"… This type of model was made for cross-lingual transfer learning tasks and is trained on >2 terabytes of the Common Crawl corpus. It differs from BERT in terms of its tokenization and masking pattern, thus making it an interesting model with which …","url":["https://formative.jmir.org/2023/1/e41516/"]}
-{"year":"2023","title":"CamPros at CASE 2022 Task 1: Transformer-based Multilingual Protest News Detection","authors":["N Kumari, M Anand, T Mohan, P Kumaraguru… - Proceedings of the 5th …, 2022"],"snippet":"Socio-political protests often lead to grave consequences when they occur. The early detection of such protests is very important for taking early precautionary measures. However, the main shortcoming of protest event detection is the scarcity …","url":["https://aclanthology.org/2022.case-1.24.pdf"]}
-{"year":"2023","title":"Can ChatGPT Replace Traditional KBQA Models? An In-Depth Analysis of the Question Answering Performance of the GPT LLM Family","authors":["Y Tan, D Min, Y Li, W Li, N Hu, Y Chen, G Qi - International Semantic Web …, 2023"],"snippet":"ChatGPT is a powerful large language model (LLM) that covers knowledge resources such as Wikipedia and supports natural language question answering using its own knowledge. Therefore, there is growing interest in exploring whether …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47240-4_19"]}
-{"year":"2023","title":"Can Large Language Models Capture Dissenting Human Voices?","authors":["N Lee, N An, J Thorne - Proceedings of the 2023 Conference on Empirical …, 2023"],"snippet":"Large language models (LLMs) have shown impressive achievements in solving a broad range of tasks. Augmented by instruction fine-tuning, LLMs have also been shown to generalize in zero-shot settings as well. However, whether LLMs closely …","url":["https://aclanthology.org/2023.emnlp-main.278.pdf"]}
-{"year":"2023","title":"Can Large Language Models Generate Outpatient Clinic Letters at First Consultation That Incorporate Complication Profiles From UK and USA Aesthetic Plastic …","authors":["RHR Roberts, SR Ali, TD Dobbs, IS Whitaker - Aesthetic Surgery Journal Open …, 2023","TD Dobbs, IS Whitaker, MA Cantab - Aesthetic Surgery Journal, 2024"],"snippet":"Background The importance of written communication between clinicians and patients, especially in the wake of the Supreme Court case of Montgomery vs Lanarkshire, has led to a shift towards patient-centric care in the UK. This study …","url":["https://academic.oup.com/asjopenforum/advance-article/doi/10.1093/asjof/ojad109/7459516","https://www.researchgate.net/profile/Rich-Roberts-2/publication/376374844_Can_Large_Language_Models_Generate_Outpatient_Clinic_Letters_at_First_Consultation_That_Incorporate_Complication_Profiles_From_UK_and_USA_Aesthetic_Plastic_Surgery_Associations/links/659c25f96f6e450f19d775da/Can-Large-Language-Models-Generate-Outpatient-Clinic-Letters-at-First-Consultation-That-Incorporate-Complication-Profiles-From-UK-and-USA-Aesthetic-Plastic-Surgery-Associations.pdf"]}
-{"year":"2023","title":"Can Peanuts Fall in Love with Distributional Semantics?","authors":["JA Michaelov, S Coulson, BK Bergen - arXiv preprint arXiv:2301.08731, 2023"],"snippet":"The context in which a sentence appears can drastically alter our expectations about upcoming words - for example, following a short story involving an anthropomorphic peanut, experimental participants are more likely to expect the sentence 'the peanut …","url":["https://arxiv.org/pdf/2301.08731"]}
-{"year":"2023","title":"Can we Debunk Disinformation by Leveraging SpeakerCredibility and Perplexity Measures?","authors":["AFUR Khilji, A Sachan, D Lachi, AV Singh, TD Singh - 2023"],"snippet":"In the present age, őghting disinformation is the main concern after pandemic. The exponential growth of fake news and its role in deteriorating general public trust and democratic standards certainly calls for counter-combat approaches. The prediction …","url":["https://www.researchsquare.com/article/rs-2764182/latest.pdf"]}
-{"year":"2023","title":"cantnlp@ LT-EDI-2023: Homophobia/Transphobia Detection in Social Media Comments using Spatio-Temporally Retrained Language Models","authors":["S Wong, M Durward, B Adams, J Dunn - Proceedings of the Third Workshop on …, 2023"],"snippet":"This paper describes our multiclass classification system developed as part of the LT-EDI@ RANLP-2023 shared task. We used a BERT-based language model to detect homophobic and transphobic content in social media comments across five …","url":["https://aclanthology.org/2023.ltedi-1.15.pdf"]}
-{"year":"2023","title":"cantnlp@ LT-EDI@ RANLP-2023: Homophobia/Transphobia Detection in Social Media Comments using Spatio-Temporally Retrained Language Models","authors":["SGJ Wong, M Durward, B Adams, J Dunn - arXiv preprint arXiv:2308.10370, 2023"],"snippet":"This paper describes our multiclass classification system developed as part of the LTEDI@RANLP-2023 shared task. We used a BERT-based language model to detect homophobic and transphobic content in social media comments across five …","url":["https://arxiv.org/pdf/2308.10370"]}
-{"year":"2023","title":"CAPS: A Practical Partition Index for Filtered Similarity Search","authors":["G Gupta, J Yi, B Coleman, C Luo, V Lakshman… - arXiv preprint arXiv …, 2023"],"snippet":"With the surging popularity of approximate near-neighbor search (ANNS), driven by advances in neural representation learning, the ability to serve queries accompanied by a set of constraints has become an area of intense interest. While …","url":["https://arxiv.org/pdf/2308.15014"]}
-{"year":"2023","title":"Cataloging of Internet resources","authors":["TV Eremenko"],"snippet":"… Common crawl en A large resource that contains a lot of information of a high scientific level, covering not only human biology, but also a number of issues of general biology (in particular, molecular and cellular biology). Relatively …","url":["https://technerium.ru/en/katalogizaciya-resursov-internet-internet-katalogizaciya/"]}
-{"year":"2023","title":"CCpdf: Building a High Quality Corpus for Visually Rich Documents from Web Crawl Data","authors":["M Turski, T Stanisławek, K Kaczmarek, P Dyda… - arXiv preprint arXiv …, 2023"],"snippet":"… The spike for the year 2021 was probably caused by the use of the Common Crawl dump from May 2022. We assume that crawlers from Common Crawl usually tend to find files that are a few months old, which often means that they are from the …","url":["https://arxiv.org/pdf/2304.14953"]}
-{"year":"2023","title":"CEIA-NLP at CASE 2022 Task 1: Protest News Detection for Portuguese","authors":["D Fernandes, A Junior, G Marques, A Soares… - Proceedings of the 5th …, 2022"],"snippet":"This paper summarizes our work on the document classification subtask of Multilingual protest news detection of the CASE@ ACL-IJCNLP 2022 workshok. In this context, we investigate the performance of monolingual and multilingual …","url":["https://aclanthology.org/2022.case-1.26.pdf"]}
-{"year":"2023","title":"Center for Artificial Intelligence Challenge on Conversational AI Correctness","authors":["M Kubis, P Skórzewski, M Sowanski, T Zietkiewicz - 2023"],"snippet":"This paper describes a challenge on Conversational AI correctness with the goal to develop Natural Language Understanding models that are robust against speech recognition errors. The data for the competition consist of natural language …","url":["https://annals-csis.org/proceedings/2023/pliks/6058.pdf"]}
-{"year":"2023","title":"Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster","authors":["N Dey, G Gosal, H Khachane, W Marshall, R Pathria… - arXiv preprint arXiv …, 2023"],"snippet":"We study recent research advances that improve large language models through efficient pre-training and scaling, and open datasets and tools. We combine these advances to introduce Cerebras-GPT, a family of open compute-optimal language …","url":["https://arxiv.org/pdf/2304.03208"]}
-{"year":"2023","title":"CFDA & CLIP at TREC 2022 NeuCLIR Track","authors":["JH Ju, WC Chen, HT Chang, CW Lin, MF Tsai…"],"snippet":"In this notebook paper, we report our methods for NeuCLIR track in TREC 2022. We adopt the common multistage pipeline for cross-language information retrieval task (CLIR). The pipeline includes the machine translation, sparse passage retrieval and the …","url":["https://dylanjoo.github.io/files/trec.neuclir.2022.paper.pdf"]}
-{"year":"2023","title":"Challenges and Applications of Large Language Models","authors":["J Kaddour, J Harris, M Mozes, H Bradley, R Raileanu… - arXiv preprint arXiv …, 2023"],"snippet":"Large Language Models (LLMs) went from non-existent to ubiquitous in the machine learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify the remaining challenges and already fruitful application areas. In this paper …","url":["https://arxiv.org/pdf/2307.10169"]}
-{"year":"2023","title":"Challenges of Large Language Models for Mental Health Counseling","authors":["NC Chung, G Dyer, L Brocki - arXiv preprint arXiv:2311.13857, 2023"],"snippet":"… One of the largest data sources for LLMs is the CommonCrawl [19, 20] which contains 390 TB with more than 3.1 billion pages of websites. 46% of documents are in English followed by German and Russian. This focus on sources emanating from …","url":["https://arxiv.org/pdf/2311.13857"]}
-{"year":"2023","title":"Challenging News Media Narratives on Refugees","authors":["RE Trulsson, V Sundelin"],"snippet":"… The model used for this project is the GloVe embeddings model that has been trained on the Common Crawl dataset. It consists of a vast collection of web pages and related metadata. (Common Crawl Foundation, nd). Training GloVe …","url":["https://research.cbs.dk/files/98734167/1646774_Challenging_News_Media_Narratives_on_Refugees.pdf"]}
-{"year":"2023","title":"Challenging specialized transformers on zero-shot classification","authors":["S Auriemma, M Madeddu, M Miliani, A Bondielli… - 2023"],"snippet":"… We may suppose that this is due to the fact that UmBERTo was trained on Common-Crawl, which also contains legal and administrative texts in its Italian section. Very high results are obtained by UmBERTo for PER entities, reaching …","url":["https://clic2023.ilc.cnr.it/wp-content/uploads/2023/11/paper6.pdf"]}
-{"year":"2023","title":"Change is Hard: A Closer Look at Subpopulation Shift","authors":["Y Yang, H Zhang, D Katabi, M Ghassemi - arXiv preprint arXiv:2302.12254, 2023"],"snippet":"Machine learning models often perform poorly on subgroups that are underrepresented in the training data. Yet, little is understood on the variation in mechanisms that cause subpopulation shifts, and how algorithms generalize across …","url":["https://arxiv.org/pdf/2302.12254"]}
-{"year":"2023","title":"ChaPat at SemEval-2023 Task 9: Text Intimacy Analysis using Ensembles of Multilingual Transformers","authors":["T Chavan, V Patwardhan - Proceedings of the The 17th International Workshop on …, 2023"],"snippet":"Intimacy estimation of a given text has recently gained importance due to the increase in direct interaction of NLP systems with humans. Intimacy is an important aspect of natural language and has a substantial impact on our everyday …","url":["https://aclanthology.org/2023.semeval-1.181.pdf"]}
-{"year":"2023","title":"Character, Word, or Both? Revisiting the Segmentation Granularity for Chinese Pre-trained Language Models","authors":["X Liang, Z Zhou, H Huang, S Wu, T Xiao, M Yang, Z Li… - arXiv preprint arXiv …, 2023"],"snippet":"Pretrained language models (PLMs) have shown marvelous improvements across various NLP tasks. Most Chinese PLMs simply treat an input text as a sequence of characters, and completely ignore word information. Although Whole Word Masking …","url":["https://arxiv.org/pdf/2303.10893"]}
-{"year":"2023","title":"Characterizing Bias in Word Embeddings Towards Analyzing Gender Associations in Philippine Texts","authors":["LCL Gamboa, MRJE Estuar - 2023 IEEE World Conference on Applied Intelligence …, 2023"],"snippet":"The steady increase in computational gender bias research has been mostly done on languages for which reliable NLP packages are readily available—such as English, Chinese, and Spanish. This study expands on this area of research by …","url":["https://ieeexplore.ieee.org/abstract/document/10263949/"]}
-{"year":"2023","title":"Chat GPT: A magical tool or the end of traditional language learning and teaching approach","authors":["HDA Chi - KHOA HỌC VÀ CÔNG NGHỆ GIAO THÔNG VẬN TẢI"],"snippet":"… GPT-3 was trained on hundreds of billions of words around 45 terabytes of text and its dataset mostly comes from Common Crawl, WebText2, and Wikipedia [7],[4]. Furthermore, GPT3has more than 175 billion machine learning parameters that are …","url":["https://www.researchgate.net/profile/Hiep-Nguyen-36/publication/376355267_Opportunities_and_Chellenges_for_exporting_agricultural_food_to_Middle_East_market_-_From_World_Logistics_Passport'_perspectives/links/6573e2666610947889aef1c9/Opportunities-and-Chellenges-for-exporting-agricultural-food-to-Middle-East-market-From-World-Logistics-Passport-perspectives.pdf#page=295"]}
-{"year":"2023","title":"Chatbots to ChatGPT in a Cybersecurity Space: Evolution, Vulnerabilities, Attacks, Challenges, and Future Recommendations","authors":["A Qammar, H Wang, J Ding, A Naouri, M Daneshmand… - arXiv preprint arXiv …, 2023"],"snippet":"Chatbots shifted from rule-based to artificial intelligence techniques and gained traction in medicine, shopping, customer services, food delivery, education, and research. OpenAI developed ChatGPT blizzard on the Internet as it crossed one …","url":["https://arxiv.org/pdf/2306.09255"]}
-{"year":"2023","title":"ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge","authors":["Y Li, Z Li, K Zhang, R Dan, S Jiang, Y Zhang - Cureus, 2023"],"snippet":"Objective The primary aim of this research was to address the limitations observed in the medical knowledge of prevalent large language models (LLMs) such as ChatGPT, by creating a specialized language model with enhanced accuracy in …","url":["https://www.cureus.com/articles/152858-chatdoctor-a-medical-chat-model-fine-tuned-on-a-large-language-model-meta-ai-llama-using-medical-domain-knowledge.pdf"]}
-{"year":"2023","title":"ChatDoctor: A Medical Chat Model Fine-tuned on LLaMA Model using Medical Domain Knowledge","authors":["L Yunxiang, L Zihan, Z Kai, D Ruilong, Z You - arXiv preprint arXiv:2303.14070, 2023"],"snippet":"Recent large language models (LLMs) in the general domain, such as ChatGPT, have shown remarkable success in following instructions and producing human-like responses. However, such language models have not been learned individually and …","url":["https://arxiv.org/pdf/2303.14070"]}
-{"year":"2023","title":"ChatGPT 101: Introduction to Generative AI","authors":["JY Kung - 2023"],"snippet":"The slides accompany a ChatGPT workshop that is intended for university students to learn more about generative AI and in the context of ChatGPT. This work is licensed under a Creative Commons license so that others may share and adapt the …","url":["https://era.library.ualberta.ca/items/9575d988-27c4-4387-ae5a-c48feca16f07/download/6fe1a0b7-5d1f-4c6a-9c46-3a7d01cea630"]}
-{"year":"2023","title":"ChatGPT and Big Data: Enhancing Text-to-Speech Conversion","authors":["HA Dida, DSK Chakravarthy, F Rabbi - Mesopotamian Journal of Big Data, 2023"],"snippet":"Text-to-speech (TTS) conversion is a crucial technology for various applications, including accessibility, education, and entertainment. With the rapid growth of big data, TTS conversion systems face new challenges in terms of data size and diversity …","url":["https://mesopotamian.press/journals/index.php/bigdata/article/download/47/64"]}
-{"year":"2023","title":"ChatGPT and Environmental Research","authors":["JJ Zhu, J Jiang, M Yang, ZJ Ren - Environmental Science & Technology, 2023"],"snippet":"ChatGPT, the latest text-based artificial intelligence (AI) tool, has quickly gained popularity and is poised to revolutionize various aspects of our lives, including education and research. With its advanced natural language processing (NLP) …","url":["https://pubs.acs.org/doi/full/10.1021/acs.est.3c01818"]}
-{"year":"2023","title":"ChatGPT backend: A comprehensive analysis","authors":["A Belgacem, A BRADAI, K Beghdad-Bey - 2023 International Symposium on …, 2023"],"snippet":"… Some of the significant datasets used in training different versions of ChatGPT models include booksCorpus, common crawl, english … Some of the most popular types of such datasets are omageNet, common crawl, openstreetMap, million song …","url":["https://ieeexplore.ieee.org/abstract/document/10323792/"]}
-{"year":"2023","title":"ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning","authors":["VD Lai, NT Ngo, APB Veyseh, H Man, F Dernoncourt… - arXiv preprint arXiv …, 2023"],"snippet":"… Regarding the classification of high-, medium-, low-, and extremely low-resource languages, our work currently relies on data ratios for the languages in the CommonCrawl corpus. According to our experiments, it is interesting that the performance …","url":["https://arxiv.org/pdf/2304.05613"]}
-{"year":"2023","title":"ChatGPT in Education","authors":["D Psarras, I Valsamara, I Pitas"],"snippet":"• ChatGPT is a Large Language Model (LLM) that is finetuned from a Generative Pre-Trained Transformer-3.5 (GPT-3.5) series LLM, produced by OpenAI.• An LLM is a Deep Neural Network (DNN) trained to generate text similar to human language.• The fine-tuning …","url":["https://icarus.csd.auth.gr/wp-content/uploads/2023/02/ChatGPT-in-Education-v1.0.pdf"]}
-{"year":"2023","title":"ChatGPT Makes Medicine Easy to Swallow: An Exploratory Case Study on Simplified Radiology Reports","authors":["K Jeblick, B Schachtner, J Dexl, A Mittermeier… - arXiv preprint arXiv …, 2022"],"snippet":"The release of ChatGPT, a language model capable of generating text that appears human-like and authentic, has gained significant attention beyond the research community. We expect that the convincing performance of ChatGPT incentivizes …","url":["https://arxiv.org/pdf/2212.14882"]}
-{"year":"2023","title":"ChatGPT Needs SPADE (Sustainability, PrivAcy, Digital divide, and Ethics) Evaluation: A Review.","authors":["K Dev"],"snippet":"ChatGPT is another large language model (LLM) inline but due to its performance and ability to converse effectively, it has gained a huge popularity amongst research as well as industrial community. Recently, many studies have been published to …","url":["https://www.researchgate.net/profile/Sunder-Khowaja/publication/369901757_ChatGPT_Needs_SPADE_Sustainability_PrivAcy_Digital_divide_and_Ethics_Evaluation_A_Review/links/64328faead9b6d17dc46ae1f/ChatGPT-Needs-SPADE-Sustainability-PrivAcy-Digital-divide-and-Ethics-Evaluation-A-Review.pdf"]}
-{"year":"2023","title":"ChatGPT Prompting Cannot Estimate Predictive Uncertainty in High-Resource Languages","authors":["M Pelucchi, M Valdenegro-Toro - arXiv preprint arXiv:2311.06427, 2023"],"snippet":"… in web content [19] or in the Common Crawl dataset [7] can give an estimation of the distribution of language in ChatGPT’s training data. Table 1 gives an overview of the percentage of web content and of the Common Crawl dataset in different …","url":["https://arxiv.org/pdf/2311.06427"]}
-{"year":"2023","title":"ChatGPT versus the neurosurgical written boards: a comparative analysis of artificial intelligence/machine learning performance on neurosurgical board–style …","authors":["BS Hopkins, VN Nguyen, J Dallas, P Texakalidis… - Journal of Neurosurgery, 2023"],"snippet":"… These same models are further trained on extremely large databases of books, articles, websites, and more through common crawl data extraction, a method of broadly web scraping the internet for incredibly wide variety and depth of available …","url":["https://thejns.org/view/journals/j-neurosurg/aop/article-10.3171-2023.2.JNS23419/article-10.3171-2023.2.JNS23419.xml"]}
-{"year":"2023","title":"ChatGPT versus Traditional Question Answering for Knowledge Graphs: Current Status and Future Directions Towards Knowledge Graph Chatbots","authors":["R Omar, O Mangukiya, P Kalnis, E Mansour - arXiv preprint arXiv:2302.06466, 2023"],"snippet":"… It was trained on massive datasets from different open-access scientific sources, such as papers and filtered common crawl. Its training datasets also included some general knowledge, such as Wikipedia. Traditional QASs for KGs divide the question-answering …","url":["https://arxiv.org/pdf/2302.06466"]}
-{"year":"2023","title":"ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?","authors":["H Chen, F Jiao, X Li, C Qin, M Ravaut, R Zhao, C Xiong… - arXiv preprint arXiv …, 2023"],"snippet":"Upon its release in late 2022, ChatGPT has brought a seismic shift in the entire landscape of AI, both in research and commerce. Through instruction-tuning a large language model (LLM) with supervised fine-tuning and reinforcement learning from …","url":["https://arxiv.org/pdf/2311.16989"]}
-{"year":"2023","title":"ChatGPT, Let Us Chat Sign Language: Experiments, Architectural Elements, Challenges and Research Directions","authors":["N Shahin, L Ismail - … International Symposium on Networks, Computers and …, 2023"],"snippet":"ChatGPT is a language model based on Generative AI. Existing research work on ChatGPT focused on its use in various domains. However, its potential for Sign Language Translation (SLT) is yet to be explored. This paper addresses this void …","url":["https://ieeexplore.ieee.org/abstract/document/10323974/"]}
-{"year":"2023","title":"ChatGPT/AIGC and Educational Innovation: Opportunities, Challenges, and the Future","authors":["Y Zhu, F Yang - Journal of East China Normal University (Educational …, 2023"],"snippet":"… 尤其到 GPT-3 时,数 据已经空前庞大,综合了 Common Crawl(约占 60%),WebText2(约 占 21%),Books1(约占 8%), Books2(约占 8%),Wikipedia(约占 3%)等不同来源的资料,囊括 了基于 3 000 亿单词语料的 1 750 亿参 数量和 45TB 数据量.在海量的数据支撑之下,ChatGPT …","url":["https://xbjk.ecnu.edu.cn/EN/article/downloadArticleFile.do?attachType=PDF&id=10962"]}
-{"year":"2023","title":"ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope","authors":["PP Ray - Internet of Things and Cyber-Physical Systems, 2023"],"snippet":"… C4 Corpus: T5 is pretrained on a large-scale dataset called Colossal Clean Crawled Corpus (C4), which is a cleaned and deduplicated version of the Common Crawl dataset. This large-scale pretraining helps T5 learn general language …","url":["https://www.sciencedirect.com/science/article/pii/S266734522300024X"]}
-{"year":"2023","title":"ChatGPT: promise and challenges for deployment in low-and middle-income countries","authors":["X Wang, HM Sanders, Y Liu, K Seang, BX Tran… - The Lancet Regional Health …, 2023"],"snippet":"In lowand middle-income countries (LMICs), the fields of medicine and public health grapple with numerous challenges that continue to hinder patients' access to healthcare services. ChatGPT, a publicly accessible chatbot, has emerged as a …","url":["https://www.thelancet.com/journals/lanwpc/article/PIIS2666-6065(23)00223-7/fulltext"]}
-{"year":"2023","title":"ChatGPT: towards an AI subjectivity","authors":["K D'Amato"],"snippet":"Motivated by the question of responsible AI and value alignment, I seek to offer a uniquely Foucauldian reconstruction of the problem as the emergence of an ethical subject in a disciplinary setting. This reconstruction contrasts with the strictly human-oriented …","url":["https://philarchive.org/archive/DAMCTA"]}
-{"year":"2023","title":"ChatGPT–the quintessence of neural networks","authors":["DS Andronchik, NS Denisyuk - 2023"],"snippet":"Andronchik, DS ChatGPT–the quintessence of neural networks/DS Andronchik, NS Denisyuk; sci. sup. IY Vanik//Знание иностранного языка как основной фактор для работы в инновационных условиях [Электронный ресурс]: сборник …","url":["https://rep.bntu.by/bitstream/handle/data/128956/44-45.pdf?sequence=1"]}
-{"year":"2023","title":"ChatPLUG: Open-Domain Generative Dialogue System with Internet-Augmented Instruction Tuning for Digital Human","authors":["J Tian, H Chen, G Xu, M Yan, X Gao, J Zhang, C Li… - arXiv preprint arXiv …, 2023"],"snippet":"In this paper, we present ChatPLUG, a Chinese open-domain dialogue system for digital human applications that instruction finetunes on a wide range of dialogue tasks in a unified internet-augmented format. Different from other open-domain …","url":["https://arxiv.org/pdf/2304.07849"]}
-{"year":"2023","title":"Check for Adaptation of Enterprise Modeling Methods for Large Language Models Balbir S. Barn¹, Souvik Barat2, and Kurt Sandkuhl³ (~) 2","authors":["BS Barn¹, S Barat, K Sandkuhl - The Practice of Enterprise Modeling: 16th IFIP Working …"],"snippet":"… GPT-3 uses 175 billion parameters and is trained on data from the Common Crawl data set1 comprising nearly a trillion words. The development in large language models and their evolution has been widely documented and the reader is …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=x33lEAAAQBAJ&oi=fnd&pg=PA3&dq=commoncrawl&ots=yZjIB74VvW&sig=iXBwedEgwfVyM9NjjqVO5uU0Gm0"]}
-{"year":"2023","title":"Check for Matching Production and Test Files: A Comparison of Filename and Statement-Based Approaches Gerald Kipruto Kirui and Stephen Phillip Levitt ()℗","authors":["GK Kirui - South African Institute of Computer Scientists and …"],"snippet":"Accurate matching of test and production files plays a critical role in the analysis and evaluation of Test-Driven Development (TDD). However, current approaches often yield unsatisfactory results due to their reliance on filename-based matching. The …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=5RrOEAAAQBAJ&oi=fnd&pg=PA3&dq=commoncrawl&ots=AWT_pDhy-Y&sig=ogepcXvqhd82yay_4CyuSQijtEk"]}
-{"year":"2023","title":"Check for updates","authors":["D Chernyshev¹, B Dobrov - Analysis of Images, Social Networks and Texts: 11th …","F de Wet¹, R Eiselen, E Schillack¹, M Puttkammer - … South Africa, December 4–8, 2023 …, 2023"],"snippet":"… The Common Crawl (CC) data set is likely the largest text data set currently available consisting of (bi-) monthly crawls of the web, and is … Part of the common crawl collection process is language identification to categorise the predominant …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=S2D8EAAAQBAJ&oi=fnd&pg=PA64&dq=commoncrawl&ots=Tcmrm2XA42&sig=YOsm8gJWgUfejEUxVK6gVlcs67U","https://books.google.de/books?hl=en&lr=lang_en&id=qGrmEAAAQBAJ&oi=fnd&pg=PA120&dq=commoncrawl&ots=En5ltGlbKd&sig=bvZREoMhuoYUncoNIhO0br41Nlc"]}
-{"year":"2023","title":"Check for","authors":["F Deimling, M Fazzolari - Data and Applications Security and Privacy XXXVII …, 2023"],"snippet":"… These models are trained with data from Wikipedia and Common Crawl and evaluated on word analogy tasks. For a triplet of words A: B:: C, the goal is to guess D. For example, for the triplet Paris France:: Berlin:?, the answer would be Germany. …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=jfzKEAAAQBAJ&oi=fnd&pg=PA367&dq=commoncrawl&ots=TvPgHbh8hv&sig=1OVZEq3e_0e-fcN13D2wSBbvDY4"]}
-{"year":"2023","title":"CheckIT!: A Corpus of Expert Fact-checked Claims for Italian","authors":["J Gili, L Passaro, T Caselli - 2023"],"snippet":"This paper introduces CheckIT!, a resource of expert fact-checked claims, filling a gap for the development of fact-checking pipelines in Italian. We further investigate the use of three state-of-the-art generative text models to create variations of claims …","url":["https://clic2023.ilc.cnr.it/wp-content/uploads/2023/11/paper28.pdf"]}
-{"year":"2023","title":"ChessGPT: Bridging Policy Learning and Language Modeling","authors":["X Feng, Y Luo, Z Wang, H Tang, M Yang, K Shao… - arXiv preprint arXiv …, 2023"],"snippet":"… Existing dataset Numerous existing datasets comprise general internet crawl data from platforms like CommonCrawl or Wikipedia. We establish a filtering pipeline to extract only chess-related language corpus from pre-existing language corpus …","url":["https://arxiv.org/pdf/2306.09200"]}
-{"year":"2023","title":"Chinesewebtext: Large-scale high-quality Chinese web text extracted with effective evaluation model","authors":["J Chen, P Jian, T Xi, Y Yi, C Ding, Q Du, G Zhu, C Zong… - arXiv preprint arXiv …, 2023"],"snippet":"… Training Data Composition While the evaluation in our current experiment targets CommonCrawl data, we believe the positive training samples … Since CommonCrawl data has a relatively high noise level overall, we directly sampled …","url":["https://arxiv.org/pdf/2311.01149"]}
-{"year":"2023","title":"CHORUS: Foundation Models for Unified Data Discovery and Exploration","authors":["M Kayali, A Lykov, I Fountalis, N Vasiloglou, D Olteanu… - arXiv preprint arXiv …, 2023"],"snippet":"We explore the application of foundation models to data discovery and exploration tasks. Foundation models are large language models (LLMs) that show promising performance on a range of diverse tasks unrelated to their training. We show that …","url":["https://arxiv.org/pdf/2306.09610"]}
-{"year":"2023","title":"Chuweb21D: A Deduped English Document Collection for Web Search Tasks","authors":["Z Chu, T Sakai, Q Ai, Y Liu - 2023"],"snippet":"… The Chuweb21 collection is constructed based on the 2021-17 (April, 2021) block of the Common Crawl dataset 3. We choose Common Crawl as the cornerstone corpus mainly due to its timeliness and accessibility. As a non-profit project …","url":["http://www.thuir.cn/group/~YQLiu/publications/SIGIR-AP2023Chu.pdf"]}
-{"year":"2023","title":"Cicognini at ACTI: Analysis of techniques for conspiracies individuation in Italian","authors":["G Cignoni, A Bucci - 2023"],"snippet":"This report illustrates methods and results for solving SubtaskA (conspiracy detection) and SubtaskB (conspiracy topic classification) of EVALITA 2023 ACTI challenge. We employed different transformer-based models and an original method based on tf-idf …","url":["https://ceur-ws.org/Vol-3473/paper40.pdf"]}
-{"year":"2023","title":"CiT: Curation in Training for Effective Vision-Language Data","authors":["H Xu, S Xie, PY Huang, L Yu, R Howes, G Ghosh… - arXiv preprint arXiv …, 2023"],"snippet":"Large vision-language models are generally applicable to many downstream tasks, but come at an exorbitant training cost that only large institutions can afford. This paper trades generality for efficiency and presents Curation in Training (CiT), a …","url":["https://arxiv.org/pdf/2301.02241"]}
-{"year":"2023","title":"CKingCoder at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis","authors":["B Harish, D Naveen, P Balasubramanian, S Aarthi - Proceedings of the The 17th …, 2023"],"snippet":"The SemEval 2023 Task 9 Multilingual Tweet Intimacy Analysis, is a shared task for analysing the intimacy in the tweets posted on Twitter. The dataset was provided by Pei and Jurgens, who are part of the task organisers, for this task consists of tweets …","url":["https://aclanthology.org/2023.semeval-1.276.pdf"]}
-{"year":"2023","title":"CLAD-ST: Contrastive Learning with Adversarial Data for Robust Speech Translation","authors":["SR Indurthi, S Chollampatt, R Agrawal, M Turchi - Proceedings of the 2023 …, 2023"],"snippet":"The cascaded approach continues to be the most popular choice for speech translation (ST). This approach consists of an automatic speech recognition (ASR) model and a machine translation (MT) model that are used in a pipeline to translate …","url":["https://aclanthology.org/2023.emnlp-main.560.pdf"]}
-{"year":"2023","title":"CLAMP: Contrastive LAnguage Model Prompt-tuning","authors":["P Teterwak, X Sun, BA Plummer, K Saenko, SN Lim - arXiv preprint arXiv:2312.01629, 2023"],"snippet":"Large language models (LLMs) have emerged as powerful general-purpose interfaces for many machine learning problems. Recent work has adapted LLMs to generative visual tasks like image captioning, visual question answering, and visual …","url":["https://arxiv.org/pdf/2312.01629"]}
-{"year":"2023","title":"Clarifying the Dialogue-Level Performance of GPT-3.5 and GPT-4 in Task-Oriented and Non-Task-Oriented Dialogue Systems","authors":["S Iizuka, S Mochizuki, A Ohashi, S Yamashita, A Guo… - 2023"],"snippet":"… It has been pre-trained on the Wikipedia and Common Crawl datasets. In this experiment, we utilized a model with 3B parameters4, which is more than the Japanese-dialog-transformers model. We built the system by LoRA-tuning (Hu et al …","url":["https://ai-hri.github.io/2023/papers/FSS-23_paper_632_cr.pdf"]}
-{"year":"2023","title":"Class Cardinality Comparison as a Fermi Problem","authors":["S Ghosh, S Razniewski, G Weikum - arXiv preprint arXiv:2303.04532, 2023"],"snippet":"… The common crawl [3] is another massive dataset of textual information, almost 50 times greater than Wikipedia (around 5.6 TB) and the BookCorpus (6 GB). It requires significant processing before it can be used for pre-training large LMs [18]. A case …","url":["https://arxiv.org/pdf/2303.04532"]}
-{"year":"2023","title":"ClassBases at CASE-2022 Multilingual Protest Event Detection Tasks: Multilingual Protest News Detection and Automatically Replicating Manually Created Event …","authors":["P Wiriyathammabhum - arXiv preprint arXiv:2301.06617, 2023"],"snippet":"In this report, we describe our ClassBases submissions to a shared task on multilingual protest event detection. For the multilingual protest news detection, we participated in subtask-1, subtask-2, and subtask-4, which are document …","url":["https://arxiv.org/pdf/2301.06617"]}
-{"year":"2023","title":"Classifying European Court of Human Rights Cases Using Transformer-Based Techniques","authors":["AS Imran, H Hodnefjeld, Z Kastrati, N Fatima… - IEEE Access, 2023"],"snippet":"In the field of text classification, researchers have repeatedly shown the value of transformer-based models such as Bidirectional Encoder Representation from Transformers (BERT) and its variants. Nonetheless, these models are expensive in …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10130544.pdf"]}
-{"year":"2023","title":"Clever little tricks: A socio-technical history of text-to-image generative models","authors":["K Steinfeld - International Journal of Architectural Computing, 2023"],"snippet":"The emergence of text-to-image generative models (eg, Midjourney, DALL-E 2, Stable Diffusion) in the summer of 2022 impacted architectural visual culture suddenly, severely, and seemingly out of nowhere. To contextualize this …","url":["https://journals.sagepub.com/doi/pdf/10.1177/14780771231168230"]}
-{"year":"2023","title":"Clustering of Monolingual Embedding Spaces","authors":["K Bhowmik, A Ralescu - Digital, 2023"],"snippet":"Suboptimal performance of cross-lingual word embeddings for distant and low-resource languages calls into question the isomorphic assumption integral to the mapping-based methods of obtaining such embeddings. This paper investigates the comparative …","url":["https://www.mdpi.com/2673-6470/3/1/4"]}
-{"year":"2023","title":"CNN-Fusion: An Effective and Lightweight Phishing Detection Method Based on Multi-Variant ConvNet","authors":["M Hussain, C Cheng, R Xu, M Afzal - Information Sciences, 2023"],"snippet":"Phishing scams are increasing as the technical skills and costs of phishing attacks diminish, emphasizing the need for rapid, precise, and low-cost prevention measures. Based on a character-level convolutional neural network (CNN), we present CNN-Fusion …","url":["https://www.sciencedirect.com/science/article/pii/S0020025523002281"]}
-{"year":"2023","title":"Co $^ 2$ PT: Mitigating Bias in Pre-trained Language Models through Counterfactual Contrastive Prompt Tuning","authors":["X Dong, Z Zhu, Z Wang, M Teleki, J Caverlee - arXiv preprint arXiv:2310.12490, 2023"],"snippet":"… cupation classification from the Common Crawl corpus. We report the overall accuracy of the task as well as the accuracy breakdown based on gender. To quantify gender bias, we compute the difference in true positive rates (TPR) between …","url":["https://arxiv.org/pdf/2310.12490"]}
-{"year":"2023","title":"COCKATIEL: COntinuous Concept ranKed ATtribution with Interpretable ELements for explaining neural net classifiers on NLP tasks","authors":["F Jourdan, A Picard, T Fel, L Risser, JM Loubes… - arXiv preprint arXiv …, 2023"],"snippet":"Transformer architectures are complex and their use in NLP, while it has engendered many successes, makes their interpretability or explainability challenging. Recent debates have shown that attention maps and attribution …","url":["https://arxiv.org/pdf/2305.06754"]}
-{"year":"2023","title":"CODAMOSA: Escaping Coverage Plateaus in Test Generation with Pre-trained Large Language Models","authors":["C Lemieux, JP Inala, SK Lahiri, S Sen - 45th International Conference on Software …, 2023"],"snippet":"… For instance, GPT-3 [16] was trained on almost 700 GB of data collected from CommonCrawl [21]. Following the success of LLMs at natural language tasks, there has been tremendous interest in applying LLMs to code. This led to the development …","url":["https://www.carolemieux.com/codamosa_icse23.pdf"]}
-{"year":"2023","title":"Code-switching input for machine translation: a case study of Vietnamese–English data","authors":["L Nguyen, O Mayeux, Z Yuan - International Journal of Multilingualism, 2023"],"snippet":"Multilingualism presents both a challenge and an opportunity for Natural Language Processing, with code-switching representing a particularly interesting problem for computational models trained on monolingual datasets. In this paper, we explore …","url":["https://www.tandfonline.com/doi/full/10.1080/14790718.2023.2224013"]}
-{"year":"2023","title":"CodeFuse-13B: A Pretrained Multi-lingual Code Large Language Model","authors":["P Di, J Li, H Yu, W Jiang, W Cai, Y Cao, C Chen… - arXiv preprint arXiv …, 2023"],"snippet":"… The Chinese corpus is sourced from CommonCrawl, computer-related websites, documentation of programming languages and their third-party libraries, etc. The English corpus is sampled from various categories in Pile including StackExchange, …","url":["https://arxiv.org/pdf/2310.06266"]}
-{"year":"2023","title":"CogAgent: A Visual Language Model for GUI Agents","authors":["W Hong, W Wang, Q Lv, J Xu, W Yu, J Ji, Y Wang… - arXiv preprint arXiv …, 2023"],"snippet":"… To facilitate robust training in GUI grounding, we have constructed the CCS400K (Common Crawl Screenshot 400K) dataset. This extensive dataset is formed by extracting URLs from the latest Common Crawl data, followed by capturing 400,000 web page …","url":["https://arxiv.org/pdf/2312.08914"]}
-{"year":"2023","title":"Collaborative Graph Neural Networks for Attributed Network Embedding","authors":["Q Tan, X Zhang, X Huang, H Chen, J Li, X Hu - arXiv preprint arXiv:2307.11981, 2023"],"snippet":"… The posts are preprocessed into 602-dimensional feature vectors via Glove CommonCrawl world embedding [122]. Hence, node attributes refer to the 602 latent dimensions. We use the communities or ‘subreddit’ that the post belongs to a target label. …","url":["https://arxiv.org/pdf/2307.11981"]}
-{"year":"2023","title":"Collecting and Predicting Neurocognitive Norms for Mandarin Chinese","authors":["YYH Le Qiu, E Chersoni"],"snippet":"… The results in Table 4 reveal that embedding models based on FastText and Skip Gram had highly significant correlations with human scores, and that the FastText vectors trained on Common Crawl achieved higher scores than did any of the ones …","url":["https://iwcs.pimoid.fr/7.pdf"]}
-{"year":"2023","title":"COLLIE: Systematic Construction of Constrained Text Generation Tasks","authors":["S Yao, H Chen, AW Hanjie, R Yang, K Narasimhan - arXiv preprint arXiv:2307.08689, 2023"],"snippet":"Text generation under constraints have seen increasing interests in natural language processing, especially with the rapidly improving capabilities of large language models. However, existing benchmarks for constrained generation usually …","url":["https://arxiv.org/pdf/2307.08689"]}
-{"year":"2023","title":"Combating Hate: How Multilingual Transformers Can Help Detect Topical Hate Speech","authors":["T Srikissoon, V Marivate - EPiC Series in Computing, 2023"],"snippet":"Automated hate speech detection is important to protecting people’s dignity, online experiences, and physical safety in Society 5.0. Transformers are sophisticated pretrained language models that can be fine-tuned for multilingual hate speech …","url":["https://login.easychair.org/publications/download/28NM"]}
-{"year":"2023","title":"Common Crawl : Data Collection and Use Cases for NLP","authors":["S Nagel"],"snippet":"Crawler Politeness Implications •(with well-written robots. txt) less of• private/personal content• duplicated content• significant parts of the web (eg. social media) are not included• links in disallowed content are not visible to the crawler• easy-to-adapt …","url":["http://nlpl.eu/skeikampen23/nagel.230206.pdf"]}
-{"year":"2023","title":"CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images","authors":["A Gokaslan, AF Cooper, J Collins, L Seguin… - arXiv preprint arXiv …, 2023"],"snippet":"We assemble a dataset of Creative-Commons-licensed (CC) images, which we use to train a set of open diffusion models that are qualitatively competitive with Stable Diffusion 2 (SD2). This task presents two challenges: (1) high-resolution CC images …","url":["https://arxiv.org/pdf/2310.16825"]}
-{"year":"2023","title":"Community Competition and Political Extremism","authors":["C Henry"],"snippet":"… Second, the LLaMa 1 foundational models are trained on publicly available data sources including the CommonCrawl. The … the 30 seed users used to build the community dataset is present in the CommonCrawl corpus. Accuracy, precision, and …","url":["https://henryhenryhenry.com/Henry_JMP_915.pdf"]}
-{"year":"2023","title":"Company Similarity using Large Language Models","authors":["D Vamvourellis, M Toth, S Bhagat, D Desai, D Mehta… - arXiv preprint arXiv …, 2023"],"snippet":"… It has been trained on multiple data sources like Common crawl dataset (around 600 billion words of text), GitHub dataset (100 million code repository), Stack overflow dataset (170 million questions and answers) on the task of next word …","url":["https://arxiv.org/pdf/2308.08031"]}
-{"year":"2023","title":"Comparative Analysis of Balanced Code Smell Detection Using Machine Learning Check for updates","authors":["M Sabharwal, A Gupta, R Gandhi, I Khan - … : Proceedings of the International Conference on …"],"snippet":"… Any website which enables API calls to it can be used to collect data or for a more comprehensive analysis, Common Crawl by AWS can be used [5]. The scraped data will be extracted using a local script ran using the python requests library from the …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=033lEAAAQBAJ&oi=fnd&pg=PA371&dq=commoncrawl&ots=06-pLbuKv9&sig=8qoh4Hy7QynXXofSNrnXdYyDkrE"]}
-{"year":"2023","title":"Comparative Analysis of Machine Learning and Deep Learning Models for Sentiment Analysis in Somali","authors":["AA Abdirahman, AO Hashi, MA Elmi, OER Rodriguez"],"snippet":"Understanding and analysing sentiment in user-generated content has become crucial with the increasing use of social media and online platforms. However, sentiment analysis in less-resourced languages like Somali poses unique …","url":["https://simad.edu.so/wp-content/uploads/2023/08/IJEEE-V10I7P104.pdf"]}
-{"year":"2023","title":"Comparing different search methods for the open access journal recommendation tool B! SON","authors":["E Entrup, A Eppelin, R Ewerth, J Hartwig, M Tullney… - International Journal on …, 2023"],"snippet":"Finding a suitable open access journal to publish academic work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of predatory publishers …","url":["https://link.springer.com/article/10.1007/s00799-023-00372-3"]}
-{"year":"2023","title":"Comparing Different Transformer Models' Performance for Identifying Toxic Language Online","authors":["C Sundelin - 2023"],"snippet":"There is a growing use of the internet and alongside that, there has been an increase in the use of toxic language towards other people that can be harmful to those that it targets. The usefulness of artificial intelligence has exploded in recent …","url":["https://www.diva-portal.org/smash/get/diva2:1784346/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Comparing the Similarity of OpenAPI-Based Microservices","authors":["Z Lu, DT Delaney, D Lillis - 2024"],"snippet":"Microservices constitute the state of the art for implementing distributed systems and have been seen as a potential solution towards open systems. The characteristics of open systems require structured microservice management, including grouping …","url":["https://lill.is/pubs/Lu2024.pdf"]}
-{"year":"2023","title":"Comparison of Pre-trained vs Custom-trained Word Embedding Models for Word Sense Disambiguation","authors":["MF Ullah, A Saeed, N Hussain - ADCAIJ: Advances in Distributed Computing and …, 2023"],"snippet":"… First, the pre-trained model by Facebook1, trained on Common Crawl with vector dimension size 300, and a context window of size 5. Second, pre-trained by Khurram (Kanwal et al., 2019) with a vector dimension size of 300, and a context …","url":["https://revistas.usal.es/cinco/index.php/2255-2863/article/download/31084/29918"]}
-{"year":"2023","title":"Comparison of the Three Algorithms for Concreteness Rating Estimation of English Words","authors":["VV Bochkarev, SV Khristoforov, AV Shevlyakova… - Acta Polytechnica …, 2022"],"snippet":"… In our case, the size of the CommonCrawl corpus that was used to obtain fastText vector … If we used a corpus which 3 times exceeds the size of CommonCrawl, we would probably … and the use of fastText vectors obtained on the CommonCrawl …","url":["http://acta.uni-obuda.hu/Bochkarev_Khristoforov_Shevlyakova_Solovyev_128.pdf"]}
-{"year":"2023","title":"Comparison of Websites Employing Search Engine Optimization and Live Data","authors":["S Maitra, L Sahoo, S Sen, K Tiwary - Journal of Computer Science Research, 2023"],"snippet":"This study compares websites that take live data into account using search engine optimization (SEO). A series of steps called search engine optimization can help a website rank highly in search engine results. Static websites and dynamic websites …","url":["https://journals.bilpubgroup.com/index.php/jcsr/article/download/5536/4811"]}
-{"year":"2023","title":"Complementing Scale: Novel Guidance Methods for Improving Language Models","authors":["O Press - 2023"],"snippet":"Abstract Language models (LMs) are at the core of almost all state of the art natural language processing systems. Recent papers, such as Brown et al.[2020] and Hoffmann et al.[2022] have shown that scaling up the size of these models leads to …","url":["https://search.proquest.com/openview/8d271a761db01c7dedf8f2619eff8b75/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Complex business ecosystem intelligence using AI-powered visual analytics","authors":["RC Basole, H Park, CD Seuss - Decision Support Systems, 2023"],"snippet":"Business ecosystems are complex, dynamic systems characterized by a multitude of entities, including companies, ventures, and technologies, as well as activities and trends. Understanding the state of business ecosystems is an increasingly critical …","url":["https://www.sciencedirect.com/science/article/pii/S0167923623002087"]}
-{"year":"2023","title":"Comprehensive Evaluation of ChatGPT Reliability Through Multilingual Inquiries","authors":["PCR Puttaparthi, SS Deo, H Gul, Y Tang, W Shang… - arXiv preprint arXiv …, 2023"],"snippet":"… First, we recorded languages included in the Common Crawl [8] documentation—a pivotal open-source dataset widely used in the training of ChatGPT. Then, we built a list of languages supported by Google Cloud Translation, which is our chosen …","url":["https://arxiv.org/pdf/2312.10524"]}
-{"year":"2023","title":"Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt","authors":["T PROMPT","Z Xu, Z Liu, B Chen, Y Tang, J Wang, K Zhou, X Hu… - arXiv preprint arXiv …, 2023"],"snippet":"While the numerous parameters in Large Language Models (LLMs) contribute to their superior performance, this massive scale makes them inefficient and memory-hungry. Thus, they are hard to deploy on the commodity hardware, such as one single GPU …","url":["https://arxiv.org/pdf/2305.11186","https://openreview.net/pdf?id=Gdm87rRjep"]}
-{"year":"2023","title":"Computational Models for Understanding Narrative","authors":["N Montfort, RP y Pérez - Revista de Comunicação e Linguagens, 2023"],"snippet":"Descrevemos como a modelagem computacional da narrativa serve como um método de investigação e ajuda a aprofundar a compreensão humanística neste domínio. O nosso foco está em nossos próprios sistemas, MEXICA e Curveship …","url":["https://rcl.fcsh.unl.pt/index.php/rcl/article/download/247/199"]}
-{"year":"2023","title":"Computational Study of News Systems: Embracing the Complexity Paradigm","authors":["N Hagar - 2023"],"snippet":"The production and spread of digital news involves a wide range of actors: journalists and the organizations that employ them, social media platforms, audiences, and myriad commentators, citizen journalists, bloggers, and other actors …","url":["https://search.proquest.com/openview/d07c9c4398e56c771c48792717cbd223/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Conclusions and Future Research","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"… The developers of XLM-Roberta and mT5 used different strategies to create “clean” subsets of the Common Crawl, while the two models are also based on different architectures. What is the impact of the difference in the architectures versus the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_8"]}
-{"year":"2023","title":"Configuration Validation with Large Language Models","authors":["X Lian, Y Chen, R Cheng, J Huang, P Thakkar, T Xu"],"snippet":"Misconfigurations are the major causes of software failures. Existing configuration validation techniques rely on manually written rules or test cases, which are expensive to implement and maintain, and are hard to be comprehensive …","url":["https://yinfangchen.github.io/assets/pdf/ciri_paper.pdf"]}
-{"year":"2023","title":"Constructing Multilingual Code Search Dataset Using Neural Machine Translation","authors":["R Sekizawa, N Duan, S Lu, H Yanaka - arXiv preprint arXiv:2306.15604, 2023"],"snippet":"Code search is a task to find programming codes that semantically match the given natural language queries. Even though some of the existing datasets for this task are multilingual on the programming language side, their query data are only in English …","url":["https://arxiv.org/pdf/2306.15604"]}
-{"year":"2023","title":"Constructing Temporal Dynamic Knowledge Graphs from Interactive Text-based Games","authors":["KP Yu - arXiv preprint arXiv:2311.01928, 2023"],"snippet":"… embedding layer, which is initialized using the 300-dimensional fastText [6] word embeddings pretrained on Common Crawl (600B tokens). Lintext is a linear layer that reduces the dimension of the word embeddings to H, which is the dimension of …","url":["https://arxiv.org/pdf/2311.01928"]}
-{"year":"2023","title":"Content still matters. A machine learning model for predicting news longevity from textual and context features","authors":["K Rybinski - Information Processing & Management, 2023"],"snippet":"There is an ongoing debate about what is more important in the modern online media newsroom, whether it is the news content and worthiness, or the audience clicks. Using a dataset of over one million articles from five countries (Belarus …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323001358"]}
-{"year":"2023","title":"CONTENT-BASED CHARACTERIZATION OF THE END OF TERM WEB ARCHIVE","authors":["ME Phillips, KK Phillips, S Alam - iPRES 2023, 2023"],"snippet":"… This work is expected to continue to leverage existing tools and processes developed by Common Crawl for graph generation. With the … Likewise, this project leaned heavily upon the prior work of the Common Crawl team and adopted their …","url":["https://www.ideals.illinois.edu/items/128295/bitstreams/428955/data.pdf"]}
-{"year":"2023","title":"Context Sensitive Tamil Language Spellchecker Using RoBERTa","authors":["R Rajalakshmi, V Sharma - Speech and Language Technologies for Low …, 2023"],"snippet":"… In our spellchecker model, we have used xlm-roberta-base model which is a pre-trained model on 2.5 TB of filtered CommonCrawl data containing 100 languages. Our spellchecker takes an input text, finds out the misspelled word and lists out the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-33231-9_4"]}
-{"year":"2023","title":"CONTEXT-AND/OR FREQUENCY","authors":["R Delmonte, N Busetto"],"snippet":"… We used BERT – with the Italian model taken from UWAC corpus, Umberto-commoncrawl - and examined the output of the first or projection layer3. In this way we intended to check the predicting ability of BERT on the masked word, by selecting in turn one …","url":["https://www.csitcp.org/paper/12/1218csit18.pdf"]}
-{"year":"2023","title":"Context-aware Swedish Lexical Simplification: Using pre-trained language models to propose contextually fitting synonyms","authors":["E Graichen - 2023"],"snippet":"This thesis presents the development and evaluation of context-aware Lexical Simplification (LS) systems for the Swedish language. In total three versions of LS models, LäsBERT, LäsBERT-baseline, and LäsGPT, were created and evaluated on …","url":["https://www.diva-portal.org/smash/get/diva2:1767273/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Contextualizing the Limits of Model & Evaluation Dataset Curation on Semantic Similarity Classification Tasks","authors":["D Theron - arXiv preprint arXiv:2311.04927, 2023"],"snippet":"This paper demonstrates how the limitations of pre-trained models and open evaluation datasets factor into assessing the performance of binary semantic similarity classification tasks. As (1) end-user-facing documentation around the …","url":["https://arxiv.org/pdf/2311.04927"]}
-{"year":"2023","title":"Contextually Enriched Meta-Learning Ensemble Model for Urdu Sentiment Analysis","authors":["K Ahmed, MI Nadeem, D Li, Z Zheng, N Al-Kahtani… - Symmetry, 2023"],"snippet":"… On the other hand, this model makes use of pre-trained word vectors that were trained on “common crawl” and “Wikipedia” through the use of the fastText model [82]. The CBOW algorithm with position-weighting is used to train this word vector. After …","url":["https://www.mdpi.com/2073-8994/15/3/645/pdf"]}
-{"year":"2023","title":"Continual Pre-Training of Large Language Models: How to (re) warm your model?","authors":["K Gupta, B Thérien, A Ibrahim, ML Richter, Q Anthony…"],"snippet":"Large language models (LLMs) are routinely pretrained on billions of tokens, only to restart the process over again once new data becomes available. A much cheaper and more efficient solution would be to enable the continual pre-training of these …","url":["https://openreview.net/pdf?id=pg7PUJe0Tl"]}
-{"year":"2023","title":"Contributions to Neural Theorem Proving","authors":["JM Han - 2023"],"snippet":"In this dissertation we present several contributions to the nascent field of neural theorem proving, deep learning-driven automated theorem proving over large libraries of formalized mathematics. We work primarily with the Lean theorem prover …","url":["http://d-scholarship.pitt.edu/43969/19/Han%20-%20ETD%20-%202.pdf"]}
-{"year":"2023","title":"Contributions to the video captioning in an open-world scenario using deep learning techniques","authors":["AS Inácio - 2023"],"snippet":"Video captioning poses a significant challenge within the Computer Vision and Artificial Intelligence domains. It involves the challenging task of translating the visual content of videos into natural language descriptions. Despite significant …","url":["http://repositorio.utfpr.edu.br/jspui/bitstream/1/32638/1/contributionsvideocaptioningopenworld.pdf"]}
-{"year":"2023","title":"Controllable sentence simplification in Swedish: Automatic simplification of sentences using control prefixes and mined Swedish paraphrases","authors":["J Monsen - 2023"],"snippet":"… snapshots using CC-Net [62], an open-source repository with tools to download and clean Common Crawl snapshots. Common Crawl is a non-profit organization that collects and freely provides vast amounts of data from the web, including web …","url":["https://www.diva-portal.org/smash/get/diva2:1766696/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Conversation Analysis for Computational Modelling of Task-oriented Dialogue","authors":["N Duran - 2023"],"snippet":"Current methods of dialogue modelling for Conversational AI (CAI) bear little resemblance to the manner in which humans organise conversational interactions. The way utterances are represented, interpreted, and generated are determined by …","url":["https://uwe-repository.worktribe.com/preview/10485570/Conversation%20Analysis%20for%20Computational%20Modelling%20of%20%20Task-oriented%20Dialogue.pdf"]}
-{"year":"2023","title":"Convolutional neural network approach for anomaly-based intrusion detection on IoT-enabled smart space orchestration system","authors":["V Upman, N Goranin, A Čenys - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:148980058/148980058.pdf"]}
-{"year":"2023","title":"Corpus Modeling and the Geometries of Text: Meaning Spaces as Metaphor and Method","authors":["DS Stoltz, MA Taylor, MA Combs - 2023"],"snippet":"We explore the theoretical implications of spatial metaphors in the field of computational text analysis and inspect how the properties of topologies aid and inhibit our theories of textual meaning. Rather than mining for “ground truth” …","url":["https://osf.io/z4eyw/download"]}
-{"year":"2023","title":"Countering Malicious Content Moderation Evasion in Online Social Networks: Simulation and Detection of Word Camouflage","authors":["Á Huertas-García, A Martín, JH Tato, D Camacho - arXiv preprint arXiv:2212.14727, 2022"],"snippet":"Content moderation is the process of screening and monitoring user-generated content online. It plays a crucial role in stopping content resulting from unacceptable behaviors such as hate speech, harassment, violence against specific groups …","url":["https://arxiv.org/pdf/2212.14727"]}
-{"year":"2023","title":"CPG-LS: Causal Perception Guided Linguistic Steganography","authors":["L Xiang, J Xia, Y Liu, Y Gui - IEEE Signal Processing Letters, 2023"],"snippet":"… Experimental Settings 1) Dataset: A total of 10000 original English texts are randomly selected from the CC-100[27] corpus, which comprises a vast collection of high-quality datasets extracted from the Common Crawl. Each text treated as a cover …","url":["https://ieeexplore.ieee.org/abstract/document/10315184/"]}
-{"year":"2023","title":"Creating Web-Scale, Annotated Document Understanding Datasets Tailored to Downstream Tasks: An Extension and Validation Study of the WordScape Data …","authors":["V Thanner - 2023"],"snippet":"… As the WordScape pipeline utilizes CommonCrawl purely to find URLs to downloadable Word documents, only .WAT files (containing … ) are extracted from the CommonCrawl metadata. This initial phase requires the downloading of up to …","url":["https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/634893/Thanner_Valdemar.pdf?sequence=1"]}
-{"year":"2023","title":"Creative Use of OpenAI in Education: Case Studies from Game Development","authors":["F French, D Levi, C Maczo, A Simonaityte… - Multimodal Technologies …, 2023"],"snippet":"… A similar problem occurs with text output because many large generative AI models (LGAIMs), including GPT, have been trained on a vast amount of historical Internet data drawn from the ‘Common Crawl’ publicly available dataset [25], as well …","url":["https://www.mdpi.com/2414-4088/7/8/81"]}
-{"year":"2023","title":"CreoleVal: Multilingual Multitask Benchmarks for Creoles","authors":["H Lent, K Tatariya, R Dabre, Y Chen, M Fekete… - arXiv preprint arXiv …, 2023"],"snippet":"Creoles represent an under-explored and marginalized group of languages, with few available resources for NLP research. While the genealogical ties between Creoles and other highly-resourced languages imply a significant potential for …","url":["https://arxiv.org/pdf/2310.19567"]}
-{"year":"2023","title":"Critical Perspectives: A Benchmark Revealing Pitfalls in PerspectiveAPI","authors":["L Piedras, L Rosenblatt, J Wilkins - arXiv preprint arXiv:2301.01874, 2023","L Rosenblatt, L Piedras, J Wilkins - Proceedings of the Second Workshop on NLP for …, 2022"],"snippet":"Detecting “toxic” language in internet content is a pressing social and technical challenge. In this work, we focus on Perspective API from Jigsaw, a state-of-the-art tool that promises to score the “toxicity” of text, with a recent model update that …","url":["https://aclanthology.org/2022.nlp4pi-1.2.pdf","https://arxiv.org/pdf/2301.01874"]}
-{"year":"2023","title":"Critical Theory of AI","authors":["S Lindgren - 2023"],"snippet":"We live in an age of artificial intelligence. Machines think and act in ever more complex ways, making suggestions and decisions on our behalf. While AI might be seen as practical and profitable, issues of data surveillance, algorithmic control, and …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=u7LdEAAAQBAJ&oi=fnd&pg=PA11&dq=commoncrawl&ots=aPc0Le2ohZ&sig=LRNUtvHxDy_gad1wDnEgOmp6wkA"]}
-{"year":"2023","title":"Cross-Genre Argument Mining: Can Language Models Automatically Fill in Missing Discourse Markers?","authors":["G Rocha, HL Cardoso, J Belouadi, S Eger - arXiv preprint arXiv:2306.04314, 2023"],"snippet":"Available corpora for Argument Mining differ along several axes, and one of the key differences is the presence (or absence) of discourse markers to signal argumentative content. Exploring effective ways to use discourse markers has …","url":["https://arxiv.org/pdf/2306.04314"]}
-{"year":"2023","title":"Cross-Lingual Approaches for Text Generation Tasks in Low-Resource Languages","authors":["S Sagare - 2023"],"snippet":"… A challenge to this approach is that such web content is itself very sparse in low-resource languages, as can be observed in publicly available large dumps like CommonCrawl [69]. Hence, it is impossible to build monolingual parallel datasets in …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.b381ab529cae1ddb.736869767072617361645f7468657369732e706466.pdf"]}
-{"year":"2023","title":"Cross-lingual Aspect-level Sentiment Classification with Graph Neural Network","authors":["鲍小异， 姜晓彤， 王中卿， 周国栋 - Journal of Software, 2023"],"snippet":": 目前, 在属性级情感分类任务上较为成熟的有标注数据集均为英文数据集, 而有标注的 中文数据集较少. 为了能够更好地利用规模庞大但却缺乏成熟标注数据的中文语言数据 集, 针对跨语言属性级情感分类任务进行了研究. 在跨语言属性级情感分类中, 一个核心 …","url":["http://www.jos.org.cn/josen/article/pdf/6667"]}
-{"year":"2023","title":"Cross-lingual Classification of Crisis-related Tweets Using Machine Translation","authors":["S Al Amer, M Lee, P Smith - Proceedings of the 14th International Conference on …, 2023"],"snippet":"Utilisation of multilingual language models such as mBERT and XLM-RoBERTa has increasingly gained attention in recent work by exploiting the multilingualism of such models in different downstream tasks across different languages. However …","url":["https://aclanthology.org/2023.ranlp-1.3.pdf"]}
-{"year":"2023","title":"Cross-lingual Machine Translation","authors":["GB Mohan, RP Kumar, NL Keerthana, D Mukesh… - Proceedings of Third …, 2023"],"snippet":"… There are 2.5 TB of unlabeled text in 100 languages extracted from the Common Crawl databases. Based on the ROBERTa methodology, … language model, and it has 2.5 TB of freshly constructed clean Common Crawl data in 100 languages. It …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=8DTYEAAAQBAJ&oi=fnd&pg=PA80&dq=commoncrawl&ots=whOf1YuF1W&sig=3RLgLGMCe-IZfoyDfrL1qt8Vjwk"]}
-{"year":"2023","title":"Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across Languages","authors":["L Qin, Q Chen, F Wei, S Huang, W Che - arXiv preprint arXiv:2310.14799, 2023"],"snippet":"… Therefore, we examine the language distribution (refer to Figure 8) in the widely used multilingual pretraining dataset, Common Crawl 2021. Based on the proportions, we incrementally integrated languages in descending and ascending …","url":["https://arxiv.org/pdf/2310.14799"]}
-{"year":"2023","title":"Cross-lingual Sentence Embedding for Low-resource Chinese-Vietnamese Based on Contrastive Learning","authors":["Y Huang, Y Liang, Z Wu, E Zhu, Z Yu - ACM Transactions on Asian and Low …, 2023"],"snippet":"… And it was pre-trained on a new Common Crawl-based dataset covering 101 languages. mT5 inherits all of the benefits of T5 , such as its general-purpose text-to-text format, its design based on insights from a large-scale empirical study, and its scale. …","url":["https://dl.acm.org/doi/pdf/10.1145/3589341"]}
-{"year":"2023","title":"Cross-Lingual Sentiment Analysis: A Survey","authors":["X Yuemei, C Han, W Wenqing, D Wanze, X Chengyang - Data Analysis and …, 2023"],"snippet":"[Objective] This paper teases out the research context of cross-lingual sentiment analysis (CLSA).[Coverage] We searched “TS= cross lingual sentiment OR cross lingual word embedding” in Web of Science database and 90 representative papers …","url":["https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/article/downloadArticleFile.do?attachType=PDF&id=5556"]}
-{"year":"2023","title":"Cross-Lingual Text Reuse Detection at Document Level for English-Urdu Language Pair","authors":["M Sharjeel, I Muneer, S Nosheen, RMA Nawab… - ACM Transactions on Asian …, 2023"],"snippet":"In recent years, the problem of Cross-Lingual Text Reuse Detection (CLTRD) has gained the interest of the research community due to the availability of large digital repositories and automatic Machine Translation (MT) systems. These systems are …","url":["https://dl.acm.org/doi/pdf/10.1145/3592761"]}
-{"year":"2023","title":"Cross-lingual Transfer Can Worsen Bias in Sentiment Analysis","authors":["S Goldfarb-Tarrant, B Ross, A Lopez - arXiv preprint arXiv:2305.12709, 2023"],"snippet":"… Since our pre-training data is from Wikipedia and CommonCrawl, Paracrawl, or the target language equivalent, there is a domain shift between pre-training and fine-tuning data, and between fine-tuning and evaluation data, which are more similar to the pretraining; …","url":["https://arxiv.org/pdf/2305.12709"]}
-{"year":"2023","title":"Cross-Lingual Transfer Learning for Misinformation Detection: Investigating Performance Across Multiple Languages","authors":["O Ozcelik, AS Yenicesu, O Yildirim, DS Haliloglu… - Proceedings of the 4th …, 2023"],"snippet":"… Indeed, 100 languages from 2.5TB of filtered CommonCrawl data were used as its pre-training material. In order to learn embedded representations of multilingual texts, XLM-R employs an unsupervised learning technique. This makes it possible to …","url":["https://aclanthology.org/2023.ldk-1.59.pdf"]}
-{"year":"2023","title":"Cross-lingual Transfer Learning with Persian","authors":["S Mollanorozy, M Tanti, M Nissim"],"snippet":"The success of cross-lingual transfer learning for POS tagging has been shown to be strongly dependent, among other factors, on the (typological and/or genetic) similarity of the lowresource language used for testing and the language (s) used in …","url":["https://sigtyp.github.io/workshops/2023/sigtyp/papers/17_cross_lingual_transfer_learnin.pdf"]}
-{"year":"2023","title":"Cross-Lingual Transfer of Cognitive Processing Complexity","authors":["C Pouw, N Hollenstein, L Beinborn - arXiv preprint arXiv:2302.12695, 2023"],"snippet":"When humans read a text, their eye movements are influenced by the structural complexity of the input sentences. This cognitive phenomenon holds across languages and recent studies indicate that multilingual language models utilize …","url":["https://arxiv.org/pdf/2302.12695"]}
-{"year":"2023","title":"Cross-Modal Reasoning with Event Correlation for Video Question Answering","authors":["C Yin, Z Che, K Wu, Z Xu, Q Qiu, J Tang - arXiv preprint arXiv:2312.12721, 2023"],"snippet":"Video Question Answering (VideoQA) is a very attractive and challenging research direction aiming to understand complex semantics of heterogeneous data from two domains, ie, the spatio-temporal video content and the word sequence in question …","url":["https://arxiv.org/pdf/2312.12721"]}
-{"year":"2023","title":"Cross-modal Transformer with Language Query for Referring Image Segmentation","authors":["W Zhang, Q Tan, P Li, Q Zhang, R Wang - Neurocomputing, 2023"],"snippet":"… As shown in row 2 in Table 5, we use Glove [65] pre-trained on Common Crawl 840B tokens instead of the randomly initialized word embeddings. We found that Glove improves the performance of CMT more than LSTM. …","url":["https://www.sciencedirect.com/science/article/pii/S0925231223002321"]}
-{"year":"2023","title":"Cross-Multilingual, Cross-Lingual and Monolingual Transfer Learning For Arabic Dialect Sentiment Classification","authors":["N Boudad, R Faizi, ROH Thami - 2023"],"snippet":"Transfer learning have recently proven to be very powerful in diverse Natural language processing (NLP) tasks such as Machine translation, Sentiment Analysis, Question/Answering. In this work, we investigate the use of transfer learning (TL) in …","url":["https://www.researchsquare.com/article/rs-3167222/latest.pdf"]}
-{"year":"2023","title":"Cross-portal metadata alignment-connecting open data portals through means of formal concept analysis","authors":["M Bogdanović, MF Gligorijević, N Veljković, D Puflović… - Information Sciences, 2023"],"snippet":"… The GloVe model we used in this research contains word vector space with meaningful substructure generated and trained on Common Crawl data. Training resulted in 840 billion generated tokens and vocabulary containing 2.2 million …","url":["https://www.sciencedirect.com/science/article/pii/S0020025523005273"]}
-{"year":"2023","title":"Cross‐domain sentiment classification using decoding‐enhanced bidirectional encoder representations from transformers with disentangled attention","authors":["RK Singh, MK Sachan, RB Patel - Concurrency and Computation: Practice and …"],"snippet":"Cross‐domain sentiment classification is a significant task of sentiment analysis that objectives to predict the opinion orientation of text documents in the target domain by using the source domain's learned classifier. Most of the existing approaches of …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.7589"]}
-{"year":"2023","title":"Crystal Ball for the Impact of Anthropogenic Climate Change on Global Air Quality PM 2.5","authors":["S Shan - Authorea Preprints, 2023"],"snippet":"Air pollution caused by PM2. 5 particles is a major global concern, particularly for human health. 19 This study used machine learning tools to uncover the social factors influencing PM2. 5 emissions. 20 Text mining techniques were employed to …","url":["https://www.authorea.com/doi/pdf/10.22541/essoar.169008274.43911108"]}
-{"year":"2023","title":"CS 5968/6968: Data Str Alg Scalable Comp Spring 2023","authors":["PP Scribe, S Singh"],"snippet":"In this lecture, we will focus only on static graphs, where no insertions/deletions to the vertices would be made. An example of such a graph would be the SRA graph of a reference human genome. In the next lecture, we will extend our discussion to …","url":["https://users.cs.utah.edu/~pandey/courses/cs6968/spring23/notes/ScribeLec14.pdf"]}
-{"year":"2023","title":"Cultural Adaptation of Recipes","authors":["Y Cao, Y Kementchedjhieva, R Cui, A Karamolegkou… - arXiv preprint arXiv …, 2023"],"snippet":"Building upon the considerable advances in Large Language Models (LLMs), we are now equipped to address more sophisticated tasks demanding a nuanced understanding of cross-cultural contexts. A key example is recipe adaptation, which …","url":["https://arxiv.org/pdf/2310.17353"]}
-{"year":"2023","title":"CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages","authors":["T Nguyen, C Van Nguyen, VD Lai, H Man, NT Ngo… - arXiv preprint arXiv …, 2023"],"snippet":"The driving factors behind the development of large language models (LLMs) with impressive learning capabilities are their colossal model sizes and extensive training datasets. Along with the progress in natural language processing, LLMs …","url":["https://arxiv.org/pdf/2309.09400"]}
-{"year":"2023","title":"Curricular Transfer Learning for Sentence Encoded Tasks","authors":["JMC de Sá, MF Sanches, RR de Souza, JC Reis… - arXiv preprint arXiv …, 2023"],"snippet":"Fine-tuning language models in a downstream task is the standard approach for many state-of-the-art methodologies in the field of NLP. However, when the distribution between the source task and target task drifts, \\textit{eg}, conversational …","url":["https://arxiv.org/pdf/2308.01849"]}
-{"year":"2023","title":"Cyberbullying Detection in Social Networks: A Comparison between Machine Learning and Transfer Learning Approaches","authors":["TH Teng, KD Varathan - IEEE Access, 2023"],"snippet":"… For comparison purposes, this research employed pre-trained word vectors trained from tokens in Common Crawl, Wikipedia, and Twitter which come with several dimensions (100, 200). The word vectors are publicly available in the …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10122521.pdf"]}
-{"year":"2023","title":"Czech-ing the News: Article Trustworthiness Dataset for Czech","authors":["M Bohacek, M Bravansky, F Trhlík, V Moravec - Proceedings of the 13th Workshop on …, 2023"],"snippet":"We present the Verifee dataset: a multimodal dataset of news articles with fine-grained trustworthiness annotations. We bring a diverse set of researchers from social, media, and computer sciences aboard to study this interdisciplinary problem holistically and …","url":["https://aclanthology.org/2023.wassa-1.10.pdf"]}
-{"year":"2023","title":"D4: Improving LLM Pretraining via Document De-Duplication and Diversification","authors":["K Tirumala, D Simig, A Aghajanyan, A Morcos"],"snippet":"… We start with 5 CommonCrawl dumps 3 which range from 2017 to 2020. We then use CC-net (Wenzek … We note that since our dataset is curated from CommonCrawl dumps, there is risk that our training set … (2023), since we use the …","url":["https://dmlr.ai/assets/accepted-papers/131/CameraReady/LLM_Data_Pruning_Paper_Camera_Ready.pdf"]}
-{"year":"2023","title":"Danish Foundation Models","authors":["K Enevoldsen, L Hansen, DS Nielsen, RAF Egebæk… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models, sometimes referred to as foundation models, have transformed multiple fields of research. However, smaller languages risk falling behind due to high training costs and small incentives for large companies to train …","url":["https://arxiv.org/pdf/2311.07264"]}
-{"year":"2023","title":"Data Acquisition: A New Frontier in Data-centric AI","authors":["L Chen, B Acun, N Ardalani, Y Sun, F Kang, H Lyu… - arXiv preprint arXiv …, 2023"],"snippet":"As Machine Learning (ML) systems continue to grow, the demand for relevant and comprehensive datasets becomes imperative. There is limited study on the challenges of data acquisition due to ad-hoc processes and lack of consistent …","url":["https://arxiv.org/pdf/2311.13712"]}
-{"year":"2023","title":"Data augmentation and generation for natural language processing","authors":["H Boulanger - 2023"],"snippet":"Natural Language Processing (NLP) is a rapidly growing field that deals with the interaction between computers and human language. One of the major challenges in NLP is dealing with low-resource scenarios, where limited amounts of labeled …","url":["https://www.theses.fr/2023UPASG019.pdf"]}
-{"year":"2023","title":"Data Cartography for Low-Resource Neural Machine Translation","authors":["A Richburg, M Carpuat - Findings of the Association for Computational …, 2022"],"snippet":"While collecting or generating more parallel data is necessary to improve machine translation (MT) in low-resource settings, we lack an understanding of how the limited amounts of existing data are actually used to help guide the collection of …","url":["https://aclanthology.org/2022.findings-emnlp.410.pdf"]}
-{"year":"2023","title":"Data Dialogue with ChatGPT: Using Code Interpreter to Simulate and Analyse Experimental Data","authors":["A Low, ZY Kalender - arXiv preprint arXiv:2311.12415, 2023"],"snippet":"Artificial intelligence (AI) has the potential to revolutionise many aspects of physics education, including introductory laboratory courses. In this study, we explored the capability of OpenAI's ChatGPT-4 to interpret and complete an introductory …","url":["https://arxiv.org/pdf/2311.12415"]}
-{"year":"2023","title":"Data Distillation: A Survey","authors":["N Sachdeva, J McAuley - arXiv preprint arXiv:2301.04272, 2023"],"snippet":"… Textual data is available in large amounts from sources like websites, news articles, academic manuscripts, etc., and is also readily accessible with datasets like the common crawl1 which sizes up to almost 541TB. Furthermore, with the advent of …","url":["https://arxiv.org/pdf/2301.04272"]}
-{"year":"2023","title":"Data Filtering Networks","authors":["A Fang, AM Jose, A Jain, L Schmidt, A Toshev… - arXiv preprint arXiv …, 2023"],"snippet":"… ), and gradually replace it with unfiltered data from Common Crawl until this pool only contains Common Crawl. We train DFNs on these data mixes, and use these DFNs to CLIP filter a separate pool of 128 million Common Crawl samples from …","url":["https://arxiv.org/pdf/2309.17425"]}
-{"year":"2023","title":"Data Management For Large Language Models: A Survey","authors":["Z Wang, W Zhong, Y Wang, Q Zhu, F Mi, B Wang… - arXiv preprint arXiv …, 2023"],"snippet":"Data plays a fundamental role in the training of Large Language Models (LLMs). Effective data management, particularly in the formulation of a well-suited training dataset, holds significance for enhancing model performance and improving training …","url":["https://arxiv.org/pdf/2312.01700"]}
-{"year":"2023","title":"Data Portraits: Recording Foundation Model Training Data","authors":["M Marone, B Van Durme - arXiv preprint arXiv:2303.03919, 2023"],"snippet":"Foundation models are trained on increasingly immense and opaque datasets. Even while these models are now key in AI system building, it can be difficult to answer the straightforward question: has the model already encountered a given …","url":["https://arxiv.org/pdf/2303.03919"]}
-{"year":"2023","title":"Data Pruning for Efficient Model Pruning in Neural Machine Translation","authors":["A Azeemi, I Qazi, A Raza - Findings of the Association for Computational …, 2023"],"snippet":"… We use the T5-small variant pre-trained on the 750 GB C4 dataset containing text from the public web scrape of the common crawl. This variant has 60 million parameters, 6 layers in the encoder and decoder each, and 8-headed attention. …","url":["https://aclanthology.org/2023.findings-emnlp.18.pdf"]}
-{"year":"2023","title":"Data Selection for Language Models via Importance Resampling","authors":["SM Xie, S Santurkar, T Ma, P Liang - arXiv preprint arXiv:2302.03169, 2023"],"snippet":"Selecting a suitable training dataset is crucial for both general-domain (eg, GPT-3) and domain-specific (eg, Codex) language models (LMs). We formalize this data selection problem as selecting a subset of a large raw unlabeled dataset to match a …","url":["https://arxiv.org/pdf/2302.03169"]}
-{"year":"2023","title":"Data-Centric Debugging: mitigating model failures via targeted image retrieval","authors":["S Singla, AM Chegini, M Moayeri, S Feizi - Proceedings of the IEEE/CVF Winter …, 2024"],"snippet":"Deep neural networks can be unreliable in the real world when the training set does not adequately cover all the settings where they are deployed. Focusing on image classification, we consider the setting where we have an error distribution E …","url":["https://openaccess.thecvf.com/content/WACV2024/papers/Singla_Data-Centric_Debugging_Mitigating_Model_Failures_via_Targeted_Image_Retrieval_WACV_2024_paper.pdf"]}
-{"year":"2023","title":"Data-Driven Approach to Automated Hypernym Hierarchy Construction for the Ukrainian WordNet","authors":["N Romanyshyn - 2023"],"snippet":"… The authors used publicly available data sources such as web pages scraped by CommonCrawl (67%), open source code repositories from GitHub, Wikipedia in 20 different languages, including Ukrainian, public domain books from Project …","url":["https://www.researchgate.net/profile/Nataliia-Romanyshyn/publication/372133776_Data-Driven_Approach_to_Automated_Hypernym_Hierarchy_Construction_for_the_Ukrainian_WordNet/links/64a5c44d8de7ed28ba7abad7/Data-Driven-Approach-to-Automated-Hypernym-Hierarchy-Construction-for-the-Ukrainian-WordNet.pdf"]}
-{"year":"2023","title":"DATA-EFFICIENT LEARNING FOR HEALTHCARE QUERIES IN LOW-RESOURCE AND CODE MIXED LANGUAGE SETTINGS","authors":["S Mwongela, J Patel, S Rajasekharan, L Wotton…"],"snippet":"… MT5 is a multilingual variant of T5 that was pre-trained on a new Common Crawl-based dataset covering 101 languages (Xue et al., 2020). … It is pre-trained on 2.5TB of filtered Common Crawl data containing 100 languages. It was introduced in the …","url":["https://pml4dc.github.io/iclr2023/pdf/PML4DC_ICLR2023_40.pdf"]}
-{"year":"2023","title":"Data-Juicer: A One-Stop Data Processing System for Large Language Models","authors":["D Chen, Y Huang, Z Ma, H Chen, X Pan, C Ge, D Gao… - arXiv preprint arXiv …, 2023"],"snippet":"… As an illustrative example, we describe our text quality classifier for culling high-quality text from heterogeneous data sources like CommonCrawl. This tool is a reproduced model based on the closed-source GPT-3 quality scorer [10]. Moreover, we have …","url":["https://arxiv.org/pdf/2309.02033"]}
-{"year":"2023","title":"Data: A Critical Element for AI","authors":["T Taulli - ChatGPT and Bard for Business Automation: Achieving …, 2023"],"snippet":"… CommonCrawl News: This is a dataset of news stories from websites across the globe. …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-9852-7_8"]}
-{"year":"2023","title":"Data: The Fuel for Generative AI","authors":["T Taulli - Generative AI: How ChatGPT and Other AI Tools Will …, 2023"],"snippet":"A large language model (LLM) processes huge amounts of data for its generative AI systems. They are on the scale of petabytes. Consider that a petabyte is 1000 terabytes. This would hold about 500 billion pages of standard text. No doubt, the …","url":["https://link.springer.com/chapter/10.1007/978-1-4842-9367-6_2"]}
-{"year":"2023","title":"Databases, Search Engines","authors":["BVV Martens - Keywords In and Out of Context, 2023"],"snippet":"… (2019) at OpenAI and pre-trained with the Common Crawl dataset, forms the current backbone of the Bing search engine. …","url":["https://link.springer.com/chapter/10.1007/978-3-031-32530-4_9"]}
-{"year":"2023","title":"DataComp: In search of the next generation of multimodal datasets","authors":["S Yitzhak Gadre, G Ilharco, A Fang, J Hayase… - arXiv e-prints, 2023","SY Gadre, G Ilharco, A Fang, J Hayase, G Smyrnis… - arXiv preprint arXiv …, 2023"],"snippet":"… We provide a testbed for dataset experiments centered around a new candidate pool of 12.8B image-text pairs from Common Crawl. Participants in our benchmark design new filtering techniques or curate new data sources and then evaluate their …","url":["https://arxiv.org/pdf/2304.14108","https://ui.adsabs.harvard.edu/abs/2023arXiv230414108Y/abstract"]}
-{"year":"2023","title":"Dataset Factory: A Toolchain For Generative Computer Vision Datasets","authors":["D Kharitonov, R Turner - arXiv preprint arXiv:2309.11608, 2023"],"snippet":"… As an illustrative example, the prestigious DataComp competition built around the Common Crawl data features four scale tracks (12.8M, 128M, 1.28B, and 12.8B samples [3]), but in the first few months, the leaderboard for the top two tracks have …","url":["https://arxiv.org/pdf/2309.11608"]}
-{"year":"2023","title":"Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data","authors":["Y Yang, AK Singh, M Elhoushi, A Mahmoud… - arXiv preprint arXiv …, 2023"],"snippet":"… In this race for higher performance, some training datasets have swelled to petabyte size, sourced from extensive repositories like the Common Crawl. While significant effort has gone into optimizing the computational aspects of training LLMs …","url":["https://arxiv.org/pdf/2312.02418"]}
-{"year":"2023","title":"Decomposing geographical judgments into spatial, temporal and linguistic components","authors":["D Gatti, G Anceresi, M Marelli, T Vecchi, L Rinaldi - 2023"],"snippet":"When mentally exploring large-scale maps, humans are assumed to mainly rely on spatial information derived from direct perceptual experience (eg, prior visual experience with the geographical map itself). In the present study, we rather tested …","url":["https://osf.io/preprints/psyarxiv/3a6tr/download"]}
-{"year":"2023","title":"Deep Learning Algorithms for Cybersecurity Applications","authors":["S Takale, S Pawar, V Khot, VS Gutte, A Acharya"],"snippet":"… Around one million legitimate and phishing URLs were used on the dataset collected from PhishTank and Common Crawl. To build the IPDS, the LSTM and CNN classifier used over 10,000 images and one million URLs for training. The …","url":["https://www.researchgate.net/profile/Sayli-Takale/publication/374419058_Deep_Learning_Algorithms_for_Cybersecurity_Applications/links/651d010fb0df2f20a20e89f6/Deep-Learning-Algorithms-for-Cybersecurity-Applications.pdf"]}
-{"year":"2023","title":"Deep learning and low-resource languages: How much data is enough? A case study of three linguistically distinct South African languages","authors":["R Eiselen, T Gaustad"],"snippet":"… data like Common Crawl or Wikipedia, which have some inherent limitations (as discussed later in this paper), but also have limited availability for South African languages. For instance, isiNdebele has no Wikipedia data and is therefore not …","url":["https://www.researchgate.net/profile/Tanja-Gaustad/publication/370953302_Deep_learning_and_low-resource_languages_How_much_data_is_enough_A_case_study_of_three_linguistically_distinct_South_African_languages/links/646c7da8ce39a956fbd02ca8/Deep-learning-and-low-resource-languages-How-much-data-is-enough-A-case-study-of-three-linguistically-distinct-South-African-languages.pdf"]}
-{"year":"2023","title":"Deep Learning Benchmark Studies on an Advanced AI Engineering Testbed from the Open Compass Project","authors":["MY Wang, J Uran, P Buitrago - Practice and Experience in Advanced Research …, 2023"],"snippet":"We present the Open Compass project’s pilot deep learning benchmark results with various AI accelerators. Those accelerators are NVIDIA V-100 and A-100, AMD MI100, as well as emerging novel accelerators such as Cerebras CS-2 and …","url":["https://dl.acm.org/doi/pdf/10.1145/3569951.3597596"]}
-{"year":"2023","title":"Deep learning for clinical texts in low-data regimes","authors":["D Chopard - 2023"],"snippet":"… noticed that FastText embeddings trained on Wikipedia performed worse than GloVe embeddings trained on the Common Crawl corpus. … Third, RoBERTa is trained on an about ten times larger dataset, which includes the Common Crawl-News …","url":["https://orca.cardiff.ac.uk/id/eprint/157748/1/PhD_Thesis_DaphneChopard_corrected_final_submission.pdf"]}
-{"year":"2023","title":"Deep Learning Model for Automated Trainee Assessment During High-Fidelity Simulation","authors":["MD Siddiqui Asad, Z Zhoujie, P Chuer"],"snippet":"Problem: Implementation of competency-based medical education has necessitated more frequent trainee assessments. Use of simulation as an assessment tool is limited by access to trained examiners, cost, and concerns with interrater reliability …","url":["https://journals.lww.com/academicmedicine/_layouts/15/oaks.journals/downloadpdf.aspx?an=00001888-990000000-00469"]}
-{"year":"2023","title":"Deep learning model for Mongolian Citizens Feedback Analysis using Word Vector Embeddings","authors":["Z Dashdorj, T Munkhbayar, S Grigorev - arXiv preprint arXiv:2302.12069, 2023"],"snippet":"… The vector model of words taught in Mongolian text on Wikipedia and Common Crawl, is 300-dimensional and contains 600,000 Mongolian words. The model was trained using CBOW with position weights with character n-grams of length 5, a …","url":["https://arxiv.org/pdf/2302.12069"]}
-{"year":"2023","title":"Deep Learning Transformer Models for Building a Comprehensive and Real-time Trauma Observatory: Development and Validation Study","authors":["G Chenais, C Gil-Jardiné, H Touchais, MA Fernandez… - JMIR AI, 2023"],"snippet":"… BelGPT2 was the first GPT-2 model fine-tuned on a French heterogeneous corpus (CommonCrawl, French Wikipedia, and EuroParl) released on the Hugging Face platform. The self-supervised training of transformers in a specific domain can …","url":["https://ai.jmir.org/2023/1/e40843/"]}
-{"year":"2023","title":"Deep Learning-based POS Tagger and Chunker for Odia Language Using Pre-trained Transformers","authors":["T Dalai, TK Mishra, PK Sa - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"Developing effective natural language processing (NLP) tools for low-resourced languages poses significant challenges. This article centers its attention on the task of Part-of-speech (POS) tagging and chunking, which pertains to the identification …","url":["https://dl.acm.org/doi/pdf/10.1145/3637877"]}
-{"year":"2023","title":"Deepfake Detection on Social Media: Leveraging Deep Learning and FastText Embeddings for Identifying Machine-Generated Tweets","authors":["S Sadiq, T Aljrees, S Ullah - IEEE Access, 2023"],"snippet":"… 2) FastText Subword FastText Subword has 2 million word vectors that were learned using Common Crawl’s subword information (600B tokens). By breaking down each word into its component words, subword embedding gives us more …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10229120.pdf"]}
-{"year":"2023","title":"Defeasible Reasoning with Large Language Models–Initial Experiments and Future Directions","authors":["G Antoniou, S Batsakis - 2023"],"snippet":"As Large Language Models gain prominence in the AI landscape, it is essential to understand their capabilities and limitations, among others in terms of reasoning. This paper is a first step towards understanding the capabilities in terms of …","url":["https://ceur-ws.org/Vol-3485/paper7687.pdf"]}
-{"year":"2023","title":"Demystifying CLIP Data","authors":["H Xu, S Xie, XE Tan, PY Huang, R Howes, V Sharma… - arXiv preprint arXiv …, 2023"],"snippet":"Contrastive Language-Image Pre-training (CLIP) is an approach that has advanced research and applications in computer vision, fueling modern recognition systems and generative models. We believe that the main ingredient to the success of CLIP …","url":["https://arxiv.org/abs/2309.16671"]}
-{"year":"2023","title":"Dense Information Retrieval on a Latin digital library via LaBSE and LatinBERT embeddings","authors":["FA Galatolo, G Martino, MGCA Cimino, CO Tommasi"],"snippet":"… The authors also demonstrated the effectiveness of the LaBSE model by mining parallel data from CommonCrawl repository and using it to train competitive Neural Machine Translation (NMT) models for English-Chinese and English-German. One …","url":["https://pubs.galatolo.me/galatololatin.pdf"]}
-{"year":"2023","title":"Densest Subhypergraph: Negative Supermodular Functions and Strongly Localized Methods","authors":["Y Huang, DF Gleich, N Veldt - arXiv preprint arXiv:2310.13792, 2023"],"snippet":"Dense subgraph discovery is a fundamental primitive in graph and hypergraph analysis which among other applications has been used for real-time story detection on social media and improving access to data stores of social networking systems …","url":["https://arxiv.org/pdf/2310.13792"]}
-{"year":"2023","title":"Deobfuscating Leetspeak With Deep Learning to Improve Spam Filtering","authors":["I Vélez de Mendizabal, X Vidriales, V Basto-Fernandes… - 2023"],"snippet":"The evolution of anti-spam filters has forced spammers to make greater efforts to bypass filters in order to distribute content over networks. The distribution of content encoded in images or the use of Leetspeak are concrete and clear examples of …","url":["https://reunir.unir.net/bitstream/handle/123456789/15131/ip2023_07_003.pdf?sequence=1&isAllowed=y"]}
-{"year":"2023","title":"DEPARTMENT OF COMPUTER ENGINEERING","authors":["PCE Trust's"],"snippet":"Introduction to Web. Information Retrieval and Web Search.: Basic Concepts of Information Retrieval, Information Retrieval Methods–Boolean Model, Vector Space Model and Statistical Language Model, Relevance Feedback, Evaluation Measures …","url":["http://www.pccoepune.com/pdf/syllabi/M-Tech-Computer-syllabus.pdf"]}
-{"year":"2023","title":"Depression clinical detection model based on social media: a federated deep learning approach","authors":["Y Liu - 2023"],"snippet":"… Specifically, a pre-processed Common Crawl dataset of more than 2TB based on 100 languages is used to train cross-language representations in a self-supervised manner. This includes generating new unlabeled corpora for low-resource …","url":["https://www.researchsquare.com/article/rs-2910523/latest"]}
-{"year":"2023","title":"Design and Data Mining Techniques for Large-Scale Scholarly Digital Libraries and Search Engines","authors":["S Rohatgi - 2023"],"snippet":"The exponential growth of digital libraries and the proliferation of scholarly content in electronic formats have made data mining and information retrieval essential tools for effectively managing, organizing, and disseminating knowledge. This thesis …","url":["https://etda.libraries.psu.edu/files/final_submissions/28910"]}
-{"year":"2023","title":"Designing a Multilingual Fact-Checking Dataset from Existing Question-Answering Data","authors":["D Kamenicky"],"snippet":"… To create a dataset, Common Crawl was used as a source of text. Due to the scraped text data a significant portion of it is not natural language. It consists of gibberish, duplicate text, menus, error messages, and other non-useful content. To …","url":["https://dspace.vutbr.cz/bitstream/handle/11012/211905/final-thesis.pdf?sequence=-1"]}
-{"year":"2023","title":"Designing with Language: Wireframing UI Design Intent with Generative Large Language Models","authors":["S Feng, M Yuan, J Chen, Z Xing, C Chen - arXiv preprint arXiv:2312.07755, 2023"],"snippet":"… Since the training samples of LLMs are typically scraped from the raw web page data, eg, GPT was trained on 410 billion tokens from the Common Crawl web corpus, we use HTML syntax as the domain-specific language to convert the UI screens into …","url":["https://arxiv.org/pdf/2312.07755"]}
-{"year":"2023","title":"Detecting Human Emotion by Text Classification.","authors":["U Brunda, P Akhilesh, K Kalaiselvi - Grenze International Journal of Engineering & …, 2023"],"snippet":"… Using more than two terabytes of filtered CommonCrawl data, we train a Transformer-based masked language model on 100 different languages. On a number of cross-lingual benchmarks, including +14.6% average accuracy on XNLI, +13 …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=23955287&AN=171360357&h=d%2F1IkrkL7uOWJhT1gMRrfuzsXlF%2BcB84%2B3mheYLZ33wHF9ijxRMsh5eJ52tl3CdG7qYQw%2FdcGArzp1oVlQjI6A%3D%3D&crl=c"]}
-{"year":"2023","title":"Detecting Human Rights Violations on Social Media during Russia-Ukraine War","authors":["P Nemkova, S Ubani, SO Polat, N Kim, RD Nielsen - arXiv preprint arXiv:2306.05370, 2023"],"snippet":"… We also evaluated XLM-RoBERTa20, a transformer model pretrained on a large corpus in a self-supervised fashion on 2.5TB of filtered CommonCrawl data spanning 100 languages [12]. Finally, we also tried RuBERT, a BERT-based model …","url":["https://arxiv.org/pdf/2306.05370"]}
-{"year":"2023","title":"Detecting Kids Cyberbullying Using Transfer Learning Approach: Transformer Fine-Tuning Models","authors":["WMS Yafooz, A Al-Dhaqm, A Alsaeedi - Kids Cybersecurity Using Computational …, 2023"],"snippet":"… XLMRoBERTa: This is a pertained model trained on 2.5 TB of text collected from Wikipedia and Common Crawl data of 100 languages including the Arabic language [38]. It is developed by Facebook and it contains a vocabulary size of 250 k. It has …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21199-7_18"]}
-{"year":"2023","title":"Detecting Modern Maldocs: An Analytical Study of PDF Feature Importance Using KDD Cup 99 as the Process Framework","authors":["CA Streun - 2024"],"snippet":"… For instance, the Govdocs1 PDF corpus (Govdocs1 – Digital Corpora, nd) was the seminal corpus that laid the groundwork for future web crawls, and Common Crawl (Common Crawl - Open Repository of Web Crawl Data, nd) and SafeDocs (Allison et …","url":["https://search.proquest.com/openview/9d14303f969f105a5660ddbd9f4b64e6/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Detecting Natural Language Biases with Prompt-based Learning","authors":["MA Aowal, MT Islam, PM Mammen, S Shetty - arXiv preprint arXiv:2309.05227, 2023"],"snippet":"In this project, we want to explore the newly emerging field of prompt engineering and apply it to the downstream task of detecting LM biases. More concretely, we explore how to design prompts that can indicate 4 different types of biases: (1) …","url":["https://arxiv.org/pdf/2309.05227"]}
-{"year":"2023","title":"Detecting Personal Information in Training Corpora: an Analysis","authors":["N Subramani, AS Luccioni, J Dodge, M Mitchell"],"snippet":"… This corpus consists of text taken from Common Crawl then passed through a number of filters with the intention of retaining high-quality English text The C4-en validation set of the C4 dataset that we analyzed was created by taking the April …","url":["https://trustnlpworkshop.github.io/papers/28.pdf"]}
-{"year":"2023","title":"Detecting Phishing URLs through Deep Learning Models","authors":["S Noor, SU Bazai, S Tareen, S Ullah - … Applications: Volume One: Image Security and …, 2024"],"snippet":"… Kaggle Common Crawl, Common Crawl 2 Phish Tank, Alexa … PhishTank, ALEXA, and Common Crawl data sets are mostly used by authors for training models. For evaluating the model, the authors mostly used accuracy, precision, recall, and F1-score …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=BubpEAAAQBAJ&oi=fnd&pg=PA176&dq=commoncrawl&ots=r45P1BXabe&sig=kWgzaIy3lrVSqLjKTm5iTfnDxYE"]}
-{"year":"2023","title":"Detecting Salient Antimetaboles in English Texts Using Deep and Transfer Learning","authors":["G Berthomet - 2023"],"snippet":"… In our case, we opted for GloVe24 in its Common Crawl (48B) version as our embedding software. We decided to use it because of its high result in other NLP tasks while being easy to access and use directly thanks to the existence of several …","url":["https://ca-roll.github.io/downloads/Berthomet_Masterarbeit___Deep___Transfer_Learning_for_Antimetabole_Detection.pdf"]}
-{"year":"2023","title":"Detection and Mitigation of Gender Bias in Natural Language Processing","authors":["H Dawkins - 2023"],"snippet":"This thesis contributes to our collective understanding of how gender bias arises in natural language processing systems, provides new detection and measurement tools, and develops mitigation methods. More specifically, we quantify and reduce …","url":["https://atrium.lib.uoguelph.ca/xmlui/bitstream/handle/10214/27467/Dawkins_Hillary_202302_Phd.pdf?sequence=1&isAllowed=y"]}
-{"year":"2023","title":"Detection of Privacy-Harming Social Media Posts in Italian","authors":["F Peiretti, RG Pensa - International Symposium on Security and Privacy in …, 2023"],"snippet":"As many psychological and sociological study reveal, many people disclose too much privacy-harming information in social media in the form of text and multimedia posts, thus exposing themselves and other persons to several security risks …","url":["https://www.researchgate.net/profile/Ruggero-Pensa/publication/372869652_Detection_of_Privacy-Harming_Social_Media_Posts_in_Italian/links/64cdff1540a524707b983e80/Detection-of-Privacy-Harming-Social-Media-Posts-in-Italian.pdf"]}
-{"year":"2023","title":"Detection of Propagandistic Techniques in Text using Pretrained Language Models","authors":["K HUDCOVICOVÁ"],"snippet":"… mC4 consists of natural text in 101 languages extracted from the public Common Crawl web scrape. However, pre-trained generative multilingual language models can exhibit problematic behavior in the zero-shot setting. They may translate a …","url":["https://is.muni.cz/th/o7nqq/Propaganda_Detection.pdf"]}
-{"year":"2023","title":"Detection of Truthful, Semi-Truthful, False and Other News with Arbitrary Topics Using BERT-Based Models","authors":["E Shushkevich, J Cardiff, A Boldyreva - 2023 33rd Conference of Open Innovations …, 2023"],"snippet":"Easy and uncontrolled access to the Internet provokes the wide propagation of false information, which freely circulates in the Internet. Researchers usually solve the problem of fake news detection (FND) in the framework of a known topic and binary …","url":["https://ieeexplore.ieee.org/abstract/document/10143004/"]}
-{"year":"2023","title":"Determining sentiment views of verbal multiword expressions using linguistic features","authors":["M Wiegand, M Schulder, J Ruppenhofer - Natural Language Engineering, 2023"],"snippet":"We examine the binary classification of sentiment views for verbal multiword expressions (MWEs). Sentiment views denote the perspective of the holder of some opinion. We distinguish between MWEs conveying the view of the speaker of the …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/B992222E564C948CE90EA7238C0E9195/S1351324923000153a.pdf/determining-sentiment-views-of-verbal-multiword-expressions-using-linguistic-features.pdf"]}
-{"year":"2023","title":"DeTexD: A Benchmark Dataset for Delicate Text Detection","authors":["A Chernodub, S Yavnyi, O Sliusarenko, J Razzaghi… - The 7th Workshop on Online …, 2023"],"snippet":"… For our DeTexD Benchmark dataset (Table 3), we extracted data from various websites in CommonCrawl5, where we specifically targeted news websites, forums discussing sensitive topics (eg, Mental Health Forum6, and able2know7 which …","url":["https://aclanthology.org/2023.woah-1.2.pdf"]}
-{"year":"2023","title":"Developing a Flexible System for a Friendly Robot to Ease Dementia (FRED) Using Cloud Technologies and Software Design Patterns","authors":["RJ Bray - 2023"],"snippet":"In this work, we designed two prototypes for a friendly robot to ease dementia (FRED). This affordable social robot is designed to provide company to older adults with cognitive decline, create reminders for important events and tasks, like taking …","url":["https://trace.tennessee.edu/cgi/viewcontent.cgi?article=9197&context=utk_gradthes"]}
-{"year":"2023","title":"Developing a Named Entity Recognition Dataset for Tagalog","authors":["LJV Miranda - arXiv preprint arXiv:2311.07161, 2023"],"snippet":"We present the development of a Named Entity Recognition (NER) dataset for Tagalog. This corpus helps fill the resource gap present in Philippine languages today, where NER resources are scarce. The texts were obtained from a pretraining …","url":["https://arxiv.org/pdf/2311.07161"]}
-{"year":"2023","title":"Developing an Incivility Dictionary for German Online Discussions–a Semi-Automated Approach Combining Human and Artificial Knowledge","authors":["A Stoll, L Wilms, M Ziegele - Communication Methods and Measures, 2023"],"snippet":"… of Common Crawl and Wikipedia, consisting of over 67 billion tokens (Bojanowski et al., 2017; Grave et al., 2018). The common crawl project … In addition to common crawl, the German Wikipedia dump 15 was considered to train the embedding …","url":["https://www.tandfonline.com/doi/pdf/10.1080/19312458.2023.2166028"]}
-{"year":"2023","title":"Developing Hybrid Model for Analyzing Sentiment of Textual Data for Amazon Product Reviews Using Deep Learning","authors":["MAM Ali, DRSN Lokhande, SAS Alshaibani - Harbin Gongcheng Daxue Xuebao …, 2023"],"snippet":"… Common Crawl and Wikipedia, has also contributed to the progress of NLP [8]. These resources enable researchers and practitioners to leverage transfer learning techniques, where models pre-trained on vast amounts of unlabeled text can be fine-tuned …","url":["https://harbinengineeringjournal.com/index.php/journal/article/download/651/484"]}
-{"year":"2023","title":"Development of a web service for creating tests based on text analysis using natural language processing technologies","authors":["TA Vakaliuk, OV Chyzhmotria, SO Didkivska, I Linevych - International Journal of …, 2023"],"snippet":"… small in size, while the Common Crawl dataset (Common crawl) is huge and very diverse but has a relatively low quality. So, to satisfy all requirements, Google developed the Colossal Clean Crawled Corpus (C4), a cleaned version of Common …","url":["https://journals.us.edu.pl/index.php/IJREL/article/download/15762/12504"]}
-{"year":"2023","title":"Diagnostic Accuracy of Differential-Diagnosis Lists Generated by Generative Pretrained Transformer 3 Chatbot for Clinical Vignettes with Common Chief Complaints …","authors":["T Hirosawa, Y Harada, M Yokose, T Sakamoto… - International Journal of …, 2023"],"snippet":"The diagnostic accuracy of differential diagnoses generated by artificial intelligence (AI) chatbots, including the generative pretrained transformer 3 (GPT-3) chatbot (ChatGPT-3) is unknown. This study evaluated the accuracy of differential-diagnosis lists …","url":["https://www.mdpi.com/2137560"]}
-{"year":"2023","title":"Diagnostic and Management Performance of ChatGPT in Obstetrics and Gynecology","authors":["LAMMG Afrooz, MHSI Alkatoute - 2023"],"snippet":"… ChatGPT is one of the largest AI models, with over 175 billion model parameters and 570 gigabytes of training data from the “common crawl” dataset, which contains almost all unstructured text on the internet. The Common Crawl corpus constitutes …","url":["https://karger.com/goi/article-pdf/doi/10.1159/000533177/3979362/000533177.pdf"]}
-{"year":"2023","title":"DIATOPIT: A Corpus of Social Media Posts for the Study of Diatopic Language Variation in Italy","authors":["A Ramponi, C Casula - Tenth Workshop on NLP for Similar Languages …, 2023"],"snippet":"We introduce DiatopIt, the first corpus specifically focused on diatopic language variation in Italy for language varieties other than Standard Italian. DiatopIt comprises over 15K geolocated social media posts from Twitter over a period of two …","url":["https://aclanthology.org/2023.vardial-1.19.pdf"]}
-{"year":"2023","title":"Did the Neurons Read your Book? Document-level Membership Inference for Large Language Models","authors":["M Meeus, S Jain, M Rei, YA de Montjoye - arXiv preprint arXiv:2310.15007, 2023"],"snippet":"… Finding members is typically easy as most LLMs today have seen sources such as Common Crawl [15] or Project Gutenberg [24]. Given … Data retrieved from the frequently updated Common Crawl [15] has for instance been the majority of the …","url":["https://arxiv.org/pdf/2310.15007"]}
-{"year":"2023","title":"Digital humanities and web archives: Possible new paths for","authors":["N Brügger - International Journal"],"snippet":"This article discusses the importance of web archives making their collections available as data and not only as sources seen through the Wayback Machine’s interface where only individual web pages are displayed. This will help unlock the …","url":["https://pure.au.dk/portal/files/301137949/Digital_humanities_and_web_archives_Possible_new_paths_for_combining_datasets_Accepted_manuscript.pdf"]}
-{"year":"2023","title":"DiLoCo: Distributed Low-Communication Training of Language Models","authors":["A Douillard, Q Feng, AA Rusu, R Chhaparia… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLM) have become a critical component in many applications of machine learning. However, standard approaches to training LLM require a large number of tightly interconnected accelerators, with devices …","url":["https://arxiv.org/pdf/2311.08105"]}
-{"year":"2023","title":"Disambiguating Italian homographic heterophones with SoundChoice and testing ChatGPT as a data-generating tool","authors":["M Nanni - 2023"],"snippet":"Text-To-Speech systems are challenged by the presence of homographs, words that have more than one possible pronunciation. Rule-based approaches are often still the preferred solution to this issue in the industry. However, there have been …","url":["https://www.diva-portal.org/smash/get/diva2:1769395/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Disaster Tweets: Analysis from the Metaphor Perspective and Classification Using LLM's","authors":["T Alcántara, O García-Vázquez, H Calvo… - … International Conference on …, 2023"],"snippet":"Nowadays, social networks, specially Twitter (now X), allow the spread of information about all topics; since this platform is completely open, there is little to none restriction on what a user can post, hence, creating a lack of confidence and …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47640-2_9"]}
-{"year":"2023","title":"Discerning mental illnesses from social media posts using machine and deep learning algorithms","authors":["R Harish, A Vaid, SS Byakod, A Kumar, A Arya - AIP Conference Proceedings, 2023"],"snippet":"Deep learning has played a pivotal role in solving a wide array of problems. These powerful models can also be used for detecting mental illness. Knowing this in advance shall help individuals to utilize appropriate prophylactic measures and …","url":["https://pubs.aip.org/aip/acp/article/2745/1/020017/2901885"]}
-{"year":"2023","title":"DISCO-10M: A Large-Scale Music Dataset","authors":["LA Lanzendörfer, F Grötschla, E Funke, R Wattenhofer - arXiv preprint arXiv …, 2023"],"snippet":"… In the field of text processing, datasets such as CommonCrawl [1] and the Pile [13] have made substantial amounts of written content available for training large language models. For instance, the Pile contains an extensive dataset of 825 …","url":["https://arxiv.org/pdf/2306.13512"]}
-{"year":"2023","title":"Disco-Bench: A Discourse-Aware Evaluation Benchmark for Language Modelling","authors":["L Wang, Z Du, D Liu, C Deng, D Yu, H Jiang, Y Wang… - arXiv preprint arXiv …, 2023"],"snippet":"Modeling discourse -- the linguistic phenomena that go beyond individual sentences, is a fundamental yet challenging aspect of natural language processing (NLP). However, existing evaluation benchmarks primarily focus on the evaluation of inter-sentence …","url":["https://arxiv.org/pdf/2307.08074"]}
-{"year":"2023","title":"Disentangling Transformer Language Models as Superposed Topic Models","authors":["J Lim, H Lauw - Proceedings of the 2023 Conference on Empirical …, 2023"],"snippet":"Topic Modelling is an established research area where the quality of a given topic is measured using coherence metrics. Often, we infer topics from Neural Topic Models (NTM) by interpreting their decoder weights, consisting of top-activated words projected …","url":["https://aclanthology.org/2023.emnlp-main.534.pdf"]}
-{"year":"2023","title":"DistilGREEK-BERT: A distilled version of the GREEK-BERT model","authors":["EA Karavangeli, DA Pantazi, M Iliakis - 2023"],"snippet":"ABSTRACT Language Models for Natural Language Processing (NLP) have constituted subject of engagement and endless research for over two decades. All models, having been introduced through the years, have the tendency to increase in …","url":["https://pergamos.lib.uoa.gr/uoa/dl/object/3338746/file.pdf"]}
-{"year":"2023","title":"Distilling semantic concept embeddings from contrastively fine-tuned language models","authors":["N Li, H Kteich, Z Bouraoui, S Schockaert - 2023"],"snippet":"Learning vectors that capture the meaning of concepts remains a fundamental challenge. Somewhat surprisingly, perhaps, pretrained language models have thus far only enabled modest improvements to the quality of such concept embeddings …","url":["https://orca.cardiff.ac.uk/id/eprint/159300/7/_SIGIR_2023__BERT_contrastive_properties-4.pdf"]}
-{"year":"2023","title":"Distinguishing Romanized Hindi from Romanized Urdu","authors":["E Nielsen, C Kirov, B Roark - Proceedings of the Workshop on Computation and …, 2023"],"snippet":"We examine the task of distinguishing between Hindi and Urdu when those languages are romanized, ie, written in the Latin script. Both languages are widely informally romanized, and to the extent that they are identified in the Latin script by …","url":["https://aclanthology.org/2023.cawl-1.5.pdf"]}
-{"year":"2023","title":"Distributed Marker Representation for Ambiguous Discourse Markers and Entangled Relations","authors":["D Ru, L Qiu, X Qiu, Y Zhang, Z Zhang - arXiv preprint arXiv:2306.10658, 2023"],"snippet":"Discourse analysis is an important task because it models intrinsic semantic structures between sentences in a document. Discourse markers are natural representations of discourse in our daily language. One challenge is that the …","url":["https://arxiv.org/pdf/2306.10658"]}
-{"year":"2023","title":"Diverse Paraphrase Generation for Evaluating Model Robustness","authors":["D Verma - 2023"],"snippet":"… The BoW model consisted of GloVe (300 dimension embeddings trained on 840B CommonCrawl tokens) [49] vectors as the embedding layer. The average of all word vectors for the input sequence is treated as its final representation. The …","url":["https://search.proquest.com/openview/a7af10226e95a379cdc4b02c51ee293e/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"DiverseVul: A New Vulnerable Source Code Dataset for Deep Learning Based Vulnerability Detection","authors":["Y Chen, Z Ding, X Chen, D Wagner - arXiv preprint arXiv:2304.00409, 2023"],"snippet":"We propose and release a new vulnerable source code dataset. We curate the dataset by crawling security issue websites, extracting vulnerability-fixing commits and source codes from the corresponding projects. Our new dataset contains 150 …","url":["https://arxiv.org/pdf/2304.00409"]}
-{"year":"2023","title":"Diving into Deep Learning: On Reading and Interpreting Black Boxes","authors":["J Dobson - 2023"],"snippet":"The deep neural networks used in computer vision and in recent large language models are widely recognized as black boxes, a term that describes their complicated architectures and opaque decision-making mechanisms. This essay …","url":["https://www.researchsquare.com/article/rs-2643580/latest.pdf"]}
-{"year":"2023","title":"DNS Dependencies as an Expression of the Digital Divide: the Example of Australia","authors":["N Nazemi, O Tavallaie, AY Zomaya, R Holz"],"snippet":"This paper investigates the relationship between the digital divide, Internet transparency, and DNS dependencies. The term “digital divide” refers to a gap between how different population groups can access and use digital technology …","url":["https://ralphholz.science/publications/DnsDependenciesAsAnExpressionOfTheDigitalDivideTheExampleOfAustralia.pdf"]}
-{"year":"2023","title":"Do AIs dream of electric comics? Generative AI models, digital memory, and creativity","authors":["G Busi Rizzi - La memoria digitale. Forme del testo e organizzazione …, 2023"],"snippet":"… called LAION, that processes through a CLIP model image-text pairs obtained from another non-profit organization called Common CrawlCommon Crawl, in turn, gets its images by scraping billions of web pages monthly and releasing them as …","url":["https://biblio.ugent.be/publication/01H89X6FR6HNJ1HHH6BHFAS6EM/file/01H89XBMS7QTD4MH3YVXR6ADS8.pdf"]}
-{"year":"2023","title":"Do large language models solve verbal analogies like children do?","authors":["CE Stevenson, M ter Veen, R Choenni… - arXiv preprint arXiv …, 2023"],"snippet":"Analogy-making lies at the heart of human cognition. Adults solve analogies such as \\textit{Horse belongs to stable like chicken belongs to ...?} by mapping relations (\\textit{kept in}) and answering \\textit{chicken coop}. In contrast, children often use association …","url":["https://arxiv.org/pdf/2310.20384"]}
-{"year":"2023","title":"Do Localization Methods Actually Localize Memorized Data in LLMs?","authors":["TY Chang, J Thomason, R Jia - arXiv preprint arXiv:2311.09060, 2023"],"snippet":"Large language models (LLMs) can memorize many pretrained sequences verbatim. This paper studies if we can locate a small set of neurons in LLMs responsible for memorizing a given sequence. While the concept of localization is often mentioned …","url":["https://arxiv.org/pdf/2311.09060"]}
-{"year":"2023","title":"Do Not Discard–Extracting Useful Fragments from Low-Quality Parallel Data to Improve Machine Translation","authors":["S Steingrímsson, P Lohar, H Loftsson, A Way - CoCo4MT 2023, 2023"],"snippet":"When parallel corpora are preprocessed for machine translation (MT) training, a part of the parallel data is commonly discarded and deemed non-parallel due to odd-length ratio, overlapping text in source and target sentences or failing some other form of a …","url":["https://files.sciconf.cn/upload/file/20230903/20230903151747_19845.pdf#page=13"]}
-{"year":"2023","title":"DocEdit: Language-Guided Document Editing","authors":["P Mathur, R Jain, J Gu, F Dernoncourt, D Manocha… - Proceedings of the AAAI …, 2023"],"snippet":"Professional document editing tools require a certain level of expertise to perform complex edit operations. To make editing tools accessible to increasingly novice users, we investigate intelligent document assistant systems that can make or …","url":["https://ojs.aaai.org/index.php/AAAI/article/download/25282/25054"]}
-{"year":"2023","title":"Document Entity Retrieval with Massive and Noisy Pre-training","authors":["L Yu, J Miao, X Sun, J Chen, AG Hauptmann, H Dai… - arXiv preprint arXiv …, 2023"],"snippet":"Visually-Rich Document Entity Retrieval (VDER) is a type of machine learning task that aims at recovering text spans in the documents for each of the entities in question. VDER has gained significant attention in recent years thanks to its broad …","url":["https://arxiv.org/pdf/2306.08937"]}
-{"year":"2023","title":"DOES CLIP'S GENERALIZATION PERFORMANCE MAINLY STEM FROM HIGH TRAIN-TEST SIMILARITY?","authors":["P Mayilvahanan, T Wiedemer, E Rusak, M Bethge… - arXiv preprint arXiv …, 2023"],"snippet":"… In comparison, LAION-400M comprises roughly 400 million samples scraped from the Common Crawl dataset*. The Common Crawl dataset comprises petabytes of data collected over more than a decade of web crawling; LAION-400M, therefore …","url":["https://arxiv.org/pdf/2310.09562"]}
-{"year":"2023","title":"Does fine-tuning GPT-3 with the OpenAI API leak personally-identifiable information?","authors":["AY Sun, E Zemour, A Saxena, U Vaidyanathan, E Lin… - arXiv preprint arXiv …, 2023"],"snippet":"… For these half of these generations, we use prompts from randomly select strings with character length 100 from an English-only subset of Common Crawl to serve as naive prompts to probe our model, inspired by the naive prompting strategy used by (Diera …","url":["https://arxiv.org/pdf/2307.16382"]}
-{"year":"2023","title":"Does GPT-3 qualify as a co-author of a scientific paper publishable in peer-review journals according to the ICMJE criteria? A case study","authors":["A Osmanovic-Thunström, S Steingrimsson - Discover Artificial Intelligence, 2023"],"snippet":"This paper explores the potential for a system to be a co-author on an academic paper based on the criteria proposed by the International Committee of Medical Journal Editors (ICMJE). We used a third generation generative pretrained …","url":["https://link.springer.com/article/10.1007/s44163-023-00055-7"]}
-{"year":"2023","title":"Does GPT-3 qualify as a co-author of a scientific paper publishable in peer-review journals according to the ICMJE criteria?-A Case Study.","authors":["AO Thunström, S Steingrimsson - 2022"],"snippet":"This paper explores the potential for a system to be a co-author on an academic paper based on the criteria proposed by the International Committee of Medical Journal Editors (ICMJE). We used a third generation generative pretrained …","url":["https://www.researchsquare.com/article/rs-2404314/latest.pdf"]}
-{"year":"2023","title":"Does Masked Language Model Pre-training with Artificial Data Improve Low-resource Neural Machine Translation?","authors":["H Tamura, T Hirasawa, H Kim, M Komachi - Findings of the Association for …, 2023"],"snippet":"Pre-training masked language models (MLMs) with artificial data has been proven beneficial for several natural language processing tasks such as natural language understanding and summarization; however, it has been less explored for neural …","url":["https://aclanthology.org/2023.findings-eacl.166.pdf"]}
-{"year":"2023","title":"Does the first letter of one's name affect life decisions? A natural language processing examination of nominative determinism.","authors":["P Chatterjee, H Mishra, A Mishra - Journal of Personality and Social Psychology, 2023"],"snippet":"… That is, when running the analysis using the Common Crawl corpus, we obtained the embedding of person name, profession name, and city name from the Common Crawl corpus. This helped us test for nominative determinism using the millions of co-occurrences …","url":["https://psycnet.apa.org/record/2023-75670-001"]}
-{"year":"2023","title":"DoGE: Domain Reweighting with Generalization Estimation","authors":["S Fan, M Pagliardini, M Jaggi - arXiv preprint arXiv:2310.15393, 2023"],"snippet":"… We see how DOGE seem to upweights significantly the common-crawl (cc) domain. In (b) we show DOGE domain weights for out-of-domain generalization. Those domain weights obtained by training on various training mixtures consisting …","url":["https://arxiv.org/pdf/2310.15393"]}
-{"year":"2023","title":"Dolphin: A Challenging and Diverse Benchmark for Arabic NLG","authors":["EMB Nagoudi, A El-Shangiti, AR Elmadany… - arXiv preprint arXiv …, 2023"],"snippet":"We present Dolphin, a novel benchmark that addresses the need for an evaluation framework for the wide collection of Arabic languages and varieties. The proposed benchmark encompasses a broad range of 13 different NLG tasks, including text …","url":["https://arxiv.org/pdf/2305.14989"]}
-{"year":"2023","title":"Don't Just Clean It, Proxy Clean It: Mitigating Bias by Proxy in Pre-Trained Models","authors":["S Panda, A Kobren, M Wick, Q Shen - Findings of the Association for Computational …, 2022"],"snippet":"Transformer-based pre-trained models are known to encode societal biases not only in their contextual representations, but also in downstream predictions when fine-tuned on task-specific data. We present D-Bias, an approach that selectively eliminates …","url":["https://aclanthology.org/2022.findings-emnlp.372.pdf"]}
-{"year":"2023","title":"Don't Worry Accountants, ChatGPT Won't Be Taking Your Job... Yet","authors":["S Taylor, V Keselj"],"snippet":"ChatGPT has demonstrated the ability to generate plausible human-like text and research is underway to evaluate and benchmark its current performance in various domains. The research we present here provides a preliminary benchmark on …","url":["https://web.cs.dal.ca/~vlado/papers/cai23s.pdf"]}
-{"year":"2023","title":"DONOTTRAIN: A Metadata Standard for Indicating Consent for Machine Learning","authors":["D Ippolito, YW Yu"],"snippet":"… take the Common Crawl, a publicly available crawl of the internet, as their starting point, and filter and process it into a training dataset. The Common Crawl currently respects robots.txt. For the learners.txt protocol to be useful, we would work with the Common …","url":["https://genlaw.github.io/CameraReady/42.pdf"]}
-{"year":"2023","title":"DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining","authors":["SM Xie, H Pham, X Dong, N Du, H Liu, Y Lu, P Liang… - arXiv preprint arXiv …, 2023"],"snippet":"The mixture proportions of pretraining data domains (eg, Wikipedia, books, web text) greatly affect language model (LM) performance. In this paper, we propose Domain Reweighting with Minimax Optimization (DoReMi), which first trains a small proxy …","url":["https://arxiv.org/pdf/2305.10429"]}
-{"year":"2023","title":"Dr ChatGPT tell me what I want to hear: How different prompts impact health answer correctness","authors":["B Koopman, G Zuccon"],"snippet":"This paper investigates the significant impact different prompts have on the behaviour of ChatGPT when used for health information seeking. As people more and more depend on generative large language models (LLMs) like ChatGPT, it is …","url":["https://ielab.io/files/emnlp2023-healthgpt.pdf"]}
-{"year":"2023","title":"Dr ChatGPT, tell me what I want to hear: How prompt knowledge impacts health answer correctness","authors":["G Zuccon, B Koopman - arXiv preprint arXiv:2302.13793, 2023"],"snippet":"… The actual documents are web pages from the noclean version of the C4 dataset: ≈1B English text extracts from the April 2019 snapshot of Common Crawl. Some passages are long and exceed the maximum token limit of ChatGPT. We trimmed …","url":["https://arxiv.org/pdf/2302.13793"]}
-{"year":"2023","title":"Dream the Impossible: Outlier Imagination with Diffusion Models","authors":["X Du, Y Sun, X Zhu, Y Li - arXiv preprint arXiv:2309.13415, 2023"],"snippet":"… The model was trained on 5 billion pairs of images and captions taken from LAION-5B [87], a publicly available dataset derived from Common Crawl data scraped from the web. Given a class name y, the generation process can be mathematically denoted …","url":["https://arxiv.org/pdf/2309.13415"]}
-{"year":"2023","title":"DreamShot: Teaching Cinema Shots to Latent Diffusion Models","authors":["T Cerquitelli, B Vacchetti, T Massaglia - 2023"],"snippet":"This thesis work presents a comprehensive overview of recent advancements in image synthesis models, exploring the recent developments of Diffusion Models [1] and their finetuning. The primary contribution consists in a novel approach that …","url":["https://webthesis.biblio.polito.it/27718/1/tesi.pdf"]}
-{"year":"2023","title":"Dynamic Masking Rate Schedules for MLM Pretraining","authors":["Z Ankner, N Saphra, D Blalock, J Frankle, ML Leavitt - arXiv preprint arXiv …, 2023"],"snippet":"Most works on transformers trained with the Masked Language Modeling (MLM) objective use the original BERT model's fixed masking rate of 15%. Our work instead dynamically schedules the masking ratio throughout training. We found that linearly …","url":["https://arxiv.org/pdf/2305.15096"]}
-{"year":"2023","title":"Dzongkha to English translation using the neural machine translation approach","authors":["K Wangchuk, SC Navaneethakrishnan, Y Jamtsho… - Indonesian Journal of …, 2023"],"snippet":"… The word embeddings were trained using the continuous bag of words (CBOW) model on common crawl and Wikipedia. Word vectors were trained using CBOW with position-weights, embedding dimension of 300, ngram characters of length five …","url":["https://www.researchgate.net/profile/Karma-Wangchuk/publication/371685952_Dzongkha_to_English_translation_using_the_neural_machine_translation_approach/links/649d87ccc41fb852dd3e5ddf/Dzongkha-to-English-translation-using-the-neural-machine-translation-approach.pdf"]}
-{"year":"2023","title":"EcomGPT-CT: Continual Pre-training of E-commerce Large Language Models with Semi-structured Data","authors":["S Ma, S Huang, S Huang, X Wang, Y Li, HT Zheng… - arXiv preprint arXiv …, 2023"],"snippet":"… Generally, commonly used data for LLM pretraining is obtained from organized long text on web pages, such as CommonCrawl and Wikipedia. However, in some specific domains including ecommerce domain, a substantial amount of text data is …","url":["https://arxiv.org/pdf/2312.15696"]}
-{"year":"2023","title":"Ecosystem Graphs: The Social Footprint of Foundation Models","authors":["R Bommasani, D Soylu, TI Liao, KA Creel, P Liang - arXiv preprint arXiv:2303.15772, 2023"],"snippet":"Foundation models (eg ChatGPT, StableDiffusion) pervasively influence society, warranting immediate social attention. While the models themselves garner much attention, to accurately characterize their impact, we must consider the broader …","url":["https://arxiv.org/pdf/2303.15772"]}
-{"year":"2023","title":"EDSA-Ensemble: an Event Detection Sentiment Analysis Ensemble Architecture","authors":["A Petrescu, CO Truică, ES Apostol, A Paschke - arXiv preprint arXiv:2301.12805, 2023"],"snippet":"… The additional data included CommonCrawl News dataset (63 million articles, 76 GB), Web text corpus (38 GB), and Stories from Common Crawl (31 GB). This coupled with a whopping 1024 V100 Tesla GPUs running for a day, led to pre-training …","url":["https://arxiv.org/pdf/2301.12805"]}
-{"year":"2023","title":"Educational data augmentation in physics education research using ChatGPT","authors":["F Kieser, P Wulff, J Kuhn, S Küchemann - arXiv preprint arXiv:2307.14475, 2023"],"snippet":"… [22] Early LLM were trained based on large text corpora such as the Common Crawl (ie, dump of the Internet, 60%[23]), WebText2 (22%), or Wikipedia (3%) with the training objective to predict next words in a sequence (a sort of Cloze test, [18]) …","url":["https://arxiv.org/pdf/2307.14475"]}
-{"year":"2023","title":"Effective Long-Context Scaling of Foundation Models","authors":["W Xiong, J Liu, I Molybog, H Zhang, P Bhargava… - arXiv preprint arXiv …, 2023"],"snippet":"We present a series of long-context LLMs that support effective context windows of up to 32,768 tokens. Our model series are built through continual pretraining from Llama 2 with longer training sequences and on a dataset where long texts are …","url":["https://arxiv.org/pdf/2309.16039"]}
-{"year":"2023","title":"Effects of paraphrasing and demographic metadata on NLI classification performance","authors":["M Marx Larre - 2023"],"snippet":"… It is a neural network that has been pre-trained on a large dataset of texts made up from a filtered version of CommonCrawl, WebText2, Books1, Books2 (two internet-based books corpora) and Wikipedia. GPT-3 can generate human-like text in a variety of …","url":["https://elib.uni-stuttgart.de/bitstream/11682/13674/1/Thesis_MiguelMarxLarre.pdf"]}
-{"year":"2023","title":"Efficient Approximate Nearest Neighbor Search in Multi-dimensional Databases","authors":["YUN PENG, B CHOI, T CHAN, J YANG, J XU - 2023"],"snippet":"Approximate nearest neighbor (ANN) search in multi-dimensional databases is a fundamental search and has many applications, such as image retrieval [28, 44], recommendation [12], entity resolution [21], and sequence matching [10]. Many ANN …","url":["https://www.comp.hkbu.edu.hk/~edisonchan/publication/tau-MNG.pdf"]}
-{"year":"2023","title":"Efficient Continual Pre-training for Building Domain Specific Large Language Models","authors":["Y Xie, K Aggarwal, A Ahmad - arXiv preprint arXiv:2311.08545, 2023"],"snippet":"… We use two sources of data for the financial corpus: the financial news common crawl and SEC filings. Financial News CommonCrawl is curated by filtering out financial news from the public CommonCrawl data. We follow the de-duplication …","url":["https://arxiv.org/pdf/2311.08545"]}
-{"year":"2023","title":"Efficient Language Model Training through Cross-Lingual and Progressive Transfer Learning","authors":["M Ostendorff, G Rehm - arXiv preprint arXiv:2301.09626, 2023"],"snippet":"Most Transformer language models are primarily pretrained on English text, limiting their use for other languages. As the model sizes grow, the performance gap between English and other languages with fewer compute and data resources …","url":["https://arxiv.org/pdf/2301.09626"]}
-{"year":"2023","title":"Efficient Phishing Detection and Prevention Using Support Vector Machine (SVM) Algorithm","authors":["M Arivukarasi, A Manju, R Kaladevi, S Hariharan… - 2023 IEEE 12th …, 2023"],"snippet":"Phishing issues influence the electronic trade in light of the fact that web-based clients trust the Internet climate less. Phishers use procedures that advance to bait online clients, making new phishing sites and spreading messages that attempt to …","url":["https://ieeexplore.ieee.org/abstract/document/10134735/"]}
-{"year":"2023","title":"Efficient Pre-training for Localized Instruction Generation of Videos","authors":["A Batra, D Moltisanti, L Sevilla-Lara, M Rohrbach… - arXiv preprint arXiv …, 2023"],"snippet":"Procedural videos show step-by-step demonstrations of tasks like recipe preparation. Understanding such videos is challenging, involving the precise localization of steps and the generation of textual instructions. Manually annotating steps and writing …","url":["https://arxiv.org/pdf/2311.15964"]}
-{"year":"2023","title":"Efficient, Adaptable and Interpretable NLP","authors":["N Rethmeier"],"snippet":"In natural language processing (NLP), a central concern is how to develop and evaluate language model pretraining that better transfers and adapts to downstream tasks. Due to their black box character, it is hard to understand how models transfers …","url":["https://di.ku.dk/english/research/phd/phd-theses/2023/PhD_Thesis_Nils_Rethmeier.pdf"]}
-{"year":"2023","title":"Efficiently Adapting Pretrained Language Models To New Languages","authors":["Z Csaki, P Pawakapan, U Thakker, Q Xu - arXiv preprint arXiv:2311.05741, 2023"],"snippet":"… For the Thai pre-training corpus, we combine the Thai subsets of OSCAR [41], MC4 [42], and CCNet [43], which are all derived from Common Crawl. The entire combined corpus was processed with MinHash deduplication [44, 45] with 1-grams …","url":["https://arxiv.org/pdf/2311.05741"]}
-{"year":"2023","title":"Einsatzbereiche semantisch strukturierter Daten bei der Unternehmensanalyse","authors":["J Gruemmer - 2023"],"snippet":"This dissertation consists of 6 papers. The papers investigate the areas of application of semantically structured data in company analysis. The first paper examines the extent to which alternative data can support tax audits. It is also …","url":["https://opus4.kobv.de/opus4-fau/files/22361/20230209_JG_Dissertation.pdf"]}
-{"year":"2023","title":"Email Spam Detection Using Multi-head CNN-BiGRU Network","authors":["A Gupta, J Patil, S Soni, A Rajan - … , ANTIC 2022, Varanasi, India, December 22–24 …, 2023"],"snippet":"Spam emails refer to unsolicited email messages, usually sent in bulk to a large list of recipients with the purpose of marketing, or luring individuals to download malware or click on phishing links. Although much research has been done on this …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28180-8_3"]}
-{"year":"2023","title":"Embedded Lexica","authors":["PJ Chester - 2023"],"snippet":"Researchers oftentimes find themselves in positions where they need to extract information, such as events or target topics, from large corpora. One common solution involves applying semantically-related keywords to identify tweets, news …","url":["https://patrickjchester.com/publication/chprop3/chprop3.pdf"]}
-{"year":"2023","title":"EMit at EVALITA 2023: Overview of the Categorical Emotion Detection in Italian Social Media Task","authors":["O Araque, S Frenda, R Sprugnoli, D Nozza, V Patti - Proceedings of the Eighth …, 2023"],"snippet":"The Emotions in Italian (EMit) task is the first edition of a shared task on emotion analysis and opinion mining in Italian messages at EVALITA 2023. EMit presents two subtasks:(i) Subtask A, that consists in an emotion detection challenge, and (ii) …","url":["https://ceur-ws.org/Vol-3473/paper1.pdf"]}
-{"year":"2023","title":"EMMA-X: An EM-like Multilingual Pre-training Algorithm for Cross-lingual Representation Learning","authors":["P Guo, X Wei, Y Hu, B Yang, D Liu, F Huang, J Xie - arXiv preprint arXiv:2310.17233, 2023"],"snippet":"Expressing universal semantics common to all languages is helpful in understanding the meanings of complex and culture-specific sentences. The research theme underlying this scenario focuses on learning universal …","url":["https://arxiv.org/pdf/2310.17233"]}
-{"year":"2023","title":"Emotion Hunters at EMit: Categorical Emotion Detection combining BERT and ChatGPT models","authors":["G Calò, F Massafra, B De Carolis, C Loglisci - 2023"],"snippet":"Emotion detection in text plays a crucial role in various applications, such as customer feedback analysis, social media monitoring, or for the analysis of the verbal part of human communication. Deep learning techniques have shown …","url":["https://ceur-ws.org/Vol-3473/paper2.pdf"]}
-{"year":"2023","title":"Emotion recognition in italian political language for prefiguring crisis in the balance of the parties' coalitions","authors":["A Forciniti, E Zavarrone, M Paolillo - Quality & Quantity, 2023"],"snippet":"The purpose of this study is to describe the emotions that dominated the political vocabulary used on Twitter during the Covid-19 epidemic by the leaders of the major Italian political parties, including Forza Italia, Movimento 5 Stelle, Fratelli d’Italia …","url":["https://link.springer.com/article/10.1007/s11135-023-01729-1"]}
-{"year":"2023","title":"Empirical Analysis of Beam Search Curse and Search Errors with Model Errors in Neural Machine Translation","authors":["J He, S Sun, X Jia, W Li - Proceedings of the 24th Annual Conference of the …, 2023"],"snippet":"Beam search is the most popular decoding method for Neural Machine Translation (NMT) and is still a strong baseline compared with the newly proposed sampling-based methods. To better understand beam search, we investigate its two well-recognized …","url":["https://aclanthology.org/2023.eamt-1.10.pdf"]}
-{"year":"2023","title":"Empirical evaluation of Uncertainty Quantification in Retrieval-Augmented Language Models for Science","authors":["S Wagle, S Munikoti, A Acharya, S Smith… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs) have shown remarkable achievements in natural language processing tasks, producing high-quality outputs. However, LLMs still exhibit limitations, including the generation of factually incorrect information. In safety-critical …","url":["https://arxiv.org/pdf/2311.09358"]}
-{"year":"2023","title":"Empirical study of pretrained multilingual language models for zero-shot cross-lingual generation","authors":["N Chirkova, S Liang, V Nikoulina - arXiv preprint arXiv:2310.09917, 2023"],"snippet":"Zero-shot cross-lingual generation assumes finetuning the multilingual pretrained language model (mPLM) on a generation task in one language and then using it to make predictions for this task in other languages. Previous works notice a frequent …","url":["https://arxiv.org/pdf/2310.09917"]}
-{"year":"2023","title":"Empowering Short Answer Grading: Integrating Transformer-Based Embeddings and BI-LSTM Network","authors":["WH Gomaa, AE Nagib, MM Saeed, A Algarni, E Nabil - Big Data and Cognitive …, 2023"],"snippet":"… The T5 model was trained on the 700 GB Colossal Clean Crawled Corpus dataset, a cleaned version of the Common Crawl dataset that included only English text. It achieved state-of-the-art performance on several NLP benchmarks and could be …","url":["https://www.mdpi.com/2504-2289/7/3/122"]}
-{"year":"2023","title":"Enabling Cross-lingual Information Retrieval for African Languages","authors":["O Ogundepo - 2023"],"snippet":"… Another common approach is to exploit existing large multilingual corpora, eg, the Common Crawl5 and Wikipedia. For example, the HC4 corpus for cross-lingual information retrieval was created from Common Crawl data [30]. Examples of …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19361/Ogundepo_Odunayo.pdf?sequence=1&isAllowed=y"]}
-{"year":"2023","title":"Encoding the Enemy: The Politics Within and Around Ethical Algorithmic War","authors":["J Moses, G Ford - Global Society, 2023"],"snippet":"This article develops a critique of the politics of algorithmic war and autonomous weapons systems. While much of the existing debate is focused on whether algorithmic weapons technologies can satisfy the ethics and laws of war, we argue …","url":["https://www.tandfonline.com/doi/full/10.1080/13600826.2023.2234395"]}
-{"year":"2023","title":"End-to-End Speech-to-Text Translation: A Survey","authors":["N Sethiya, CK Maurya - arXiv preprint arXiv:2312.01053, 2023"],"snippet":"… Finally, a language model (LM) is trained on CommonCrawl data and combined with the ST model to generate text via beam-search decoding. Following along, for training E2E model, (Wang et al., 2021b) produces pseudo-labels by cascading ASR …","url":["https://arxiv.org/pdf/2312.01053"]}
-{"year":"2023","title":"Energy Estimates Across Layers of Computing: From Devices to Large-Scale Applications in Machine Learning for Natural Language Processing, Scientific …","authors":["S Shankar - arXiv preprint arXiv:2310.07516, 2023"],"snippet":"… These AI/ML methods depend on training on a large corpus, namely significant amounts of data using words, phrases, part-of speech requirements, existing collections of text from academic journals, books, social network websites, Wikipedia …","url":["https://arxiv.org/pdf/2310.07516"]}
-{"year":"2023","title":"Engineering a Distributed-Memory Triangle Counting Algorithm","authors":["P Sanders, TN Uhl - arXiv preprint arXiv:2302.11443, 2023"],"snippet":"Counting triangles in a graph and incident to each vertex is a fundamental and frequently considered task of graph analysis. We consider how to efficiently do this for huge graphs using massively parallel distributed-memory machines …","url":["https://arxiv.org/pdf/2302.11443"]}
-{"year":"2023","title":"Engineering the Best In-Context Input for GPT-3 in the OpenQA Task","authors":["K Huang, G Sullan, O Ebhomielen"],"snippet":"GPT-3, since its release, has garnered the attention of the NLP community due to its versatility across a wide range of NLP tasks. In this work, we use GPT-3 to approach the OpenQA task, where the model needs to answer input questions without being …","url":["https://kailihuang.com/assets/pdf/cs224u.pdf"]}
-{"year":"2023","title":"Enhanced Emotion and Sentiment Recognition for Empathetic Dialogue System Using Big Data and Deep Learning Methods","authors":["M Kozłowski, K Gabor-Siatkowska, I Stefaniak… - International Conference on …, 2023","M Sowański, A Janicki"],"snippet":"… The process of using the Common Crawl web archive to create an enlarged corpus, named CORTEX+ pCC, is presented. An empathetic dialogue system named Terabot, incorporating the elaborated method, is also described. The system …","url":["https://link.springer.com/chapter/10.1007/978-3-031-35995-8_33","https://www.iccs-meeting.org/archive/iccs2023/papers/140730475.pdf"]}
-{"year":"2023","title":"Enhanced Phishing URL Detection Using Leveraging BERT with Additional URL Feature Extraction","authors":["KS Jishnu, B Arthi - 2023 5th International Conference on Inventive …, 2023"],"snippet":"… Their heuristic-based deep learning technique made use of RNN models and datasets including PhishTank, Alexa, and Common Crawl. … Their research used the PhishTank and Common Crawl databases, which contain legal and phishing …","url":["https://ieeexplore.ieee.org/abstract/document/10220647/"]}
-{"year":"2023","title":"Enhancing Customer Support with Knowledge Graph-Based Question Answering","authors":["N Stampe - 2023"],"snippet":"Many companies don’t utilize the huge amount of unstructured data they possess. Old issue tickets are one example. A company that possesses a lot of old issue tickets are Stibo Systems. Meanwhile, customer support staff receive issues that has …","url":["https://www.stiboaccelerator.com/s/Master_Thesis_Niels_Stampe_201708197.pdf"]}
-{"year":"2023","title":"Enhancing EFL reading and writing through AI-powered tools: design, implementation, and evaluation of an online course","authors":["JC Hsiao, JS Chang - Interactive Learning Environments, 2023"],"snippet":"During the Covid-19 pandemic, global teachers gained extensive experiences with teaching online courses. To design quality online courses in the post-pandemic era, the impact of the latest technology, such as artificial intelligence (AI), must be …","url":["https://www.tandfonline.com/doi/abs/10.1080/10494820.2023.2207187"]}
-{"year":"2023","title":"Enhancing Neural Text Detector Robustness with µAttacking and RR-Training. Electronics 2023, 12, 1948","authors":["G Liang, J Guerrero, F Zheng, I Alsmadi - 2023"],"snippet":"With advanced neural network techniques, language models can generate content that looks genuinely created by humans. Such advanced progress benefits society in numerous ways. However, it may also bring us threats that we have not seen …","url":["https://www.academia.edu/download/102918903/pdf.pdf"]}
-{"year":"2023","title":"Enhancing RDF Verbalization with Descriptive and Relational Knowledge","authors":["F Zhang, M Zhang, S Liu, Y Sun, N Duan - ACM Transactions on Asian and Low …, 2023"],"snippet":"… T5 is pre-trained on a large and clean unlabeled text dataset named C4 from Common Crawl (about 750 GB) and achieves state-of-the-art performance on various benchmarks such as CNN/Daily Mail [4] and SuperGLUE [33]. T5 has ive …","url":["https://dl.acm.org/doi/pdf/10.1145/3595293"]}
-{"year":"2023","title":"Enhancing Search Engine Results: A Comparative Study of Graph and Timeline Visualizations for Semantic and Temporal Relationship Discovery","authors":["MS Qureshi - 2023"],"snippet":"… Examples of open source data sets for search engine data are Common Crawl (CC) 10 which provides a large-scale data set of the crawled web, providing easy access to such data which is typically not made available for commercial search engines …","url":["https://search.proquest.com/openview/31cf7b284117b060a924c3a56299d09f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Enhancing Speaker Diarization with Large Language Models: A Contextual Beam Search Approach","authors":["TJ Park, K Dhawan, N Koluguri, J Balam - arXiv preprint arXiv:2309.05248, 2023"],"snippet":"Large language models (LLMs) have shown great promise for capturing contextual information in natural language processing tasks. We propose a novel approach to speaker diarization that incorporates the prowess of LLMs to exploit contextual cues …","url":["https://arxiv.org/pdf/2309.05248"]}
-{"year":"2023","title":"Enhancing Text Summarization for Indian Languages: Mono, Multi and Cross-lingual Approaches","authors":["A URLANA - 2023"],"snippet":"The internet serves as a vast repository of information covering a diverse array of topics, ranging from blogs and articles to websites. However, it is important to note that not all of this information is valuable or relevant. Navigating through the plethora …","url":["https://www.researchgate.net/profile/Ashok-Urlana-2/publication/373989668_Enhancing_Text_Summarization_for_Indian_Languages_Mono_Multi_and_Cross-lingual_Approaches/links/65072d6e0142892697247d46/Enhancing-Text-Summarization-for-Indian-Languages-Mono-Multi-and-Cross-lingual-Approaches.pdf"]}
-{"year":"2023","title":"Enhancing Traceability Link Recovery with Fine-Grained Query Expansion Analysis","authors":["T Peng, K She, Y Shen, X Xu, Y Yu - Information, 2023"],"snippet":"… The training datasets were Wikipedia and CommonCrawl datasets [16], which contain texts from various domains. Using common domain datasets for training enabled the model to better represent different software terminologies and vocabularies. …","url":["https://www.mdpi.com/2078-2489/14/5/270"]}
-{"year":"2023","title":"EnML: Multi-label Ensemble Learning for Urdu Text Classification","authors":["F Mehmood, R Shahzadi, H Ghafoor, MN Asim… - ACM Transactions on Asian …, 2023"],"snippet":"… Crawl News Dataset (63 million articles, 76 GB), Web text corpus (38 GB), and Stories from Common Crawl were among the supplementary data (31 GB). We have utilized RoBERTa-Large-Multilingual with 12 attention heads and 12 hidden layers …","url":["https://dl.acm.org/doi/pdf/10.1145/3616111"]}
-{"year":"2023","title":"ENTITY LINKING IN LOW-ANNOTATION DATA SETTINGS","authors":["E Schumacher - 2022"],"snippet":"… While these LMs were originally trained on standard NLP domain texts such as Wikipedia and CommonCrawl, the unsupervised nature of their training means that models tailored to specific domains can be produced. This is especially useful in the …","url":["https://www.cs.jhu.edu/~mdredze/publications/elliot_schumacher_thesis.pdf"]}
-{"year":"2023","title":"Entity Matching using Large Language Models","authors":["R Peeters, C Bizer - arXiv preprint arXiv:2310.11244, 2023"],"snippet":"… The benchmark was built by extracting schema.org data from the Common Crawl We use the most difficult version of the benchmark including 80% corner-cases (hard positives and hard negatives) and use the following attributes: brand, title, currency …","url":["https://arxiv.org/pdf/2310.11244"]}
-{"year":"2023","title":"ERATE: Efficient Retrieval Augmented Text Embeddings","authors":["V Raina, N Kassner, K Popat, P Lewis, N Cancedda… - The Fourth Workshop on …, 2023"],"snippet":"… An additional 100 million sentences sampled from common crawl (CC)5 are included in an expanded datastore to investigate the impact of increasing the datastore size. Table 1 details the statistics for each of these subsets. Sentences …","url":["https://aclanthology.org/2023.insights-1.2.pdf"]}
-{"year":"2023","title":"Escaping the sentence-level paradigm in machine translation","authors":["M Post, M Junczys-Dowmunt - arXiv preprint arXiv:2304.12959, 2023"],"snippet":"It is well-known that document context is vital for resolving a range of translation ambiguities, and in fact the document setting is the most natural setting for nearly all translation. It is therefore unfortunate that machine translation -- both research and …","url":["https://arxiv.org/pdf/2304.12959"]}
-{"year":"2023","title":"Essays in Environmental Economics","authors":["X Du - 2023"],"snippet":"This dissertation consists of three essays in the field of environmental economics. The first chapter provides the first causal evidence that hostile activities online lead to physical violence. Given the recently documented relationship between pollution …","url":["https://search.proquest.com/openview/8df778615d87a395701f3e18f35ed1a3/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Establishing An Optimal Online Phishing Detection Method: Evaluating Topological NLP Transformers on Text Message Data","authors":["H Milner, M Baron - Journal of Data Science and Intelligent Systems, 2023"],"snippet":"This research establishes an optimal classification model for online SMS spam detection by utilizing topological sentence transformer methodologies. The study is a response to the increasing sophisticated and disruptive activities of malicious actors …","url":["http://ojs.bonviewpress.com/index.php/jdsis/article/download/1131/568"]}
-{"year":"2023","title":"Estimating Contamination via Perplexity: Quantifying Memorisation in Language Model Evaluation","authors":["Y Li - arXiv preprint arXiv:2309.10677, 2023"],"snippet":"… For example, if the model M was trained on a Common Crawl dataset spanning 2016-2019, we would gather web pages specifically from this period. Similarly, if the model was trained on a 2019 dump of Wikipedia, we would collect articles from …","url":["https://arxiv.org/pdf/2309.10677"]}
-{"year":"2023","title":"Ethical challenges of large language models-a systematic literature review","authors":["A Laakso - 2023"],"snippet":"… Current LLMs are by and large trained on massive datasets collected from the internet often the Common Crawl -material, a collection of vast amounts of internet content [S111]. However, just because private data is available online does not …","url":["https://helda.helsinki.fi/server/api/core/bitstreams/e507d025-8c84-4789-a043-f185fa51eb0a/content"]}
-{"year":"2023","title":"Evading Text Based Emotion Detection Mechanism via Adversarial Attacks","authors":["A Bajaj, DK Vishwakarma - Neurocomputing, 2023"],"snippet":"Textual Emotion Analysis (TEA) seeks to extract and assess the emotional states of users from the text. Various Deep Learning (DL) algorithms have emerged rapidly and demonstrated success in numerous disciplines, including audio, image, and …","url":["https://www.sciencedirect.com/science/article/pii/S0925231223009104"]}
-{"year":"2023","title":"Evaluating Biased Attitude Associations of Language Models in an Intersectional Context","authors":["SO Sabbaghi, R Wolfe, A Caliskan - arXiv preprint arXiv:2307.03360, 2023"],"snippet":"… Models trained on the Pile have been shown to outperform models trained on both raw and filtered versions of the Common Crawl on many benchmarks and downstream evaluations [23]. Prior work finds that GPT-Neo most strongly encodes …","url":["https://arxiv.org/pdf/2307.03360"]}
-{"year":"2023","title":"Evaluating Cross Lingual Transfer for Morphological Analysis: a Case Study of Indian Languages","authors":["S Pawar, P Bhattacharyya, P Talukdar - … of the 20th SIGMORPHON workshop on …, 2023"],"snippet":"… It is pre-trained on the Common Crawl-based dataset and covers 101 languages. It is an encoder-decoder sequence generation model, unlike mBERT, which is an encoder-only multilingual model. Our task of root word extraction requires the …","url":["https://aclanthology.org/2023.sigmorphon-1.3.pdf"]}
-{"year":"2023","title":"Evaluating Event Embeddings on Commodity Future Prices","authors":["B Steel, D Ruths - 2023"],"snippet":"… We developed a library for pulling and filtering websites from the Common Crawl Index, accessible here: github.com/networkdynamics/seldonite. We pulled Reuters news articles from Common Crawl from 2006 to 2021. We only keep articles that are …","url":["https://www.researchsquare.com/article/rs-3457976/latest.pdf"]}
-{"year":"2023","title":"Evaluating Gender Bias in Pre-trained Filipino FastText Embeddings","authors":["LC Gamboa, MRJ Estuar - 2023 International Conference on IT Innovation and …, 2023"],"snippet":"… This embedding was trained on Common Crawl and Wikipedia data written in Filipino, the Philippine national language based primarily on Tagalog (a regional language in the country) but also containing words from foreign (eg, …","url":["https://ieeexplore.ieee.org/abstract/document/10100022/"]}
-{"year":"2023","title":"Evaluating Knowledge Graphs with Hybrid Intelligence","authors":["S Tsaneva"],"snippet":"… WebIsALOD is a large KG containing 400M hypernymy relations, automatically extracted from the CommonCrawl web corpus, describing generic knowledge [6]. The current verification of the resource relies on machine learning models trained …","url":["https://2023.eswc-conferences.org/wp-content/uploads/2023/05/paper_Tsaneva_2023_Evaluating.pdf"]}
-{"year":"2023","title":"Evaluating Large Language Models on a Highly-specialized Topic, Radiation Oncology Physics","authors":["J Holmes, Z Liu, L Zhang, Y Ding, TT Sio, LA McGee… - arXiv preprint arXiv …, 2023"],"snippet":"We present the first study to investigate Large Language Models (LLMs) in answering radiation oncology physics questions. Because popular exams like AP Physics, LSAT, and GRE have large test-taker populations and ample test …","url":["https://arxiv.org/pdf/2304.01938"]}
-{"year":"2023","title":"Evaluating Paraphrastic Robustness in Textual Entailment Models","authors":["D Verma, YK Lal, S Sinha, B Van Durme, A Poliak"],"snippet":"We presentˆP aRT E, a collection of 1,126 pairs of Recognizing Textual Entailment (RTE) examples to evaluate whether models are robust to paraphrasing. We posit that if RTE models understand language, their predictions should be consistent across …","url":["https://www3.cs.stonybrook.edu/~ylal/files/papers/acl2023.pdf"]}
-{"year":"2023","title":"Evaluating Prompt-based Question Answering for Object Prediction in the Open Research Knowledge Graph","authors":["J D'Souza, M Hrou, S Auer - arXiv preprint arXiv:2305.12900, 2023"],"snippet":"There have been many recent investigations into prompt-based training of transformer language models for new text genres in low-resource settings. The prompt-based training approach has been found to be effective in generalizing pre-trained …","url":["https://arxiv.org/pdf/2305.12900"]}
-{"year":"2023","title":"Evaluating Rule-Based and Neural Merging Strategies of Entity Clusters for Coreference Resolution","authors":["J Mägdefrau - 2023"],"snippet":"Coreference resolution is an essential pre-processing step for many natural language processing tasks. In the past, there has been a shift from rule-based approaches to machinelearning-based approaches. A recent approach that focuses …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/teaching/theses/completed-theses/2023-ba-maegdefrau.pdf"]}
-{"year":"2023","title":"Evaluating Supervised Machine Learning Models for Zero-Day Phishing Attack Detection: A Comprehensive Study","authors":["Z Lotfi, S Valipourebrahimi, T Tran - 2023"],"snippet":"To have highly secure e-commerce websites, detecting and preventing cyber-attacks is of high importance. Among diverse types of cyber-attacks, identifying zero-day attacks is problematic since they are unknown to the security system. It is because …","url":["https://www.researchsquare.com/article/rs-3204260/latest.pdf"]}
-{"year":"2023","title":"Evaluating synthesized speech: the cognitive approach","authors":["G Navickas, GA Melnik-Leroy - DAMSS: 13th conference on data analysis methods …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://epublications.vu.lt/object/elaba:148640608/148640608.pdf"]}
-{"year":"2023","title":"Evaluating Temporal Persistence Using Replicability Measures","authors":["J Keller, T Breuer, P Schaer - arXiv preprint arXiv:2308.10549, 2023"],"snippet":"In real-world Information Retrieval (IR) experiments, the Evaluation Environment (EE) is exposed to constant change. Documents are added, removed, or updated, and the information need and the search behavior of users is evolving. Simultaneously …","url":["https://arxiv.org/pdf/2308.10549"]}
-{"year":"2023","title":"Evaluating the Capabilities of Large Language Models for Spatial and Situational Understanding","authors":["S Das"],"snippet":"… With the advent of new generation compute platforms1, curation of large scale datasets like the CommonCrawl2, and the formal verification of the power scaling, development of larger and larger language models boomed. In Table 2.1 we give a …","url":["https://www.researchgate.net/profile/Sowmen-Das/publication/374724794_Evaluating_the_Capabilities_of_Large_Language_Models_for_Spatial_and_Situational_Understanding/links/652ae1b01a05311a23ff0941/Evaluating-the-Capabilities-of-Large-Language-Models-for-Spatial-and-Situational-Understanding.pdf"]}
-{"year":"2023","title":"Evaluating the Effectiveness of Pre-trained Language Models in Predicting the Helpfulness of Online Product Reviews","authors":["A Boluki, JPR Sharami, D Shterionov - arXiv preprint arXiv:2302.10199, 2023"],"snippet":"Businesses and customers can gain valuable information from product reviews. The sheer number of reviews often necessitates ranking them based on their potential helpfulness. However, only a few reviews ever receive any helpfulness votes on …","url":["https://arxiv.org/pdf/2302.10199"]}
-{"year":"2023","title":"Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning","authors":["S Munikoti, A Acharya, S Wagle, S Horawalavithana - arXiv preprint arXiv:2311.04348, 2023"],"snippet":"… In addition to the ATLAS model pretrained with common crawl (CC) and Wikipedia, we also train ATLAS-Science (220M) model from scratch with the S2ORC scientific text datasets. For a fair comparison with ATLAS, we initialize the ATLAS-Science …","url":["https://arxiv.org/pdf/2311.04348"]}
-{"year":"2023","title":"Evaluating the Efficiency of Quantum Simulators Using Practical Application Benchmarks","authors":["RS Kumar - 2023"],"snippet":"Quantum computing holds the potential to revolutionize various industries by solving problems that classical computers cannot solve efficiently. However, building quantum computers is still in its infancy, and simulators are currently the best …","url":["https://search.proquest.com/openview/a187e3790915945e91d6d2d987a6faa8/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Evaluating the Moral Beliefs Encoded in LLMs","authors":["N Scherrer, C Shi, A Feder, DM Blei - arXiv preprint arXiv:2307.14324, 2023"],"snippet":"This paper presents a case study on the design, administration, post-processing, and evaluation of surveys on large language models (LLMs). It comprises two components: (1) A statistical method for eliciting beliefs encoded in LLMs. We …","url":["https://arxiv.org/pdf/2307.14324"]}
-{"year":"2023","title":"Evaluation of African American Language Bias in Natural Language Generation","authors":["N Deas, J Grieser, S Kleiner, D Patton, E Turcan… - arXiv preprint arXiv …, 2023"],"snippet":"We evaluate how well LLMs understand African American Language (AAL) in comparison to their performance on White Mainstream English (WME), the encouraged \"standard\" form of English taught in American classrooms. We measure …","url":["https://arxiv.org/pdf/2305.14291"]}
-{"year":"2023","title":"Evaluation of ChatGPT Applicability to Learning Quantum Physics","authors":["A Stefńnska, TP Stefański, M Czubenko - 2023 16th International Conference on …, 2023"],"snippet":"ChatGPT is an application that uses a large language model. Its purpose is to generate answers to various questions as well as provide information, help solve problems and participate in conversations on a wide range of topics. This …","url":["https://ieeexplore.ieee.org/abstract/document/10261132/"]}
-{"year":"2023","title":"Evaluation of ChatGPT as a Question Answering System for Answering Complex Questions","authors":["Y Tan, D Min, Y Li, W Li, N Hu, Y Chen, G Qi - arXiv preprint arXiv:2303.07992, 2023"],"snippet":"… FLAN-T5 FLAN-T5 (Text-to-Text Transfer Transformer, 11B [8])is an encoderdecoder Transformer language model that is trained on a filtered variant of CommonCrawl (C4) [34]. The release date and model size for this model are also based on [34]. …","url":["https://arxiv.org/pdf/2303.07992"]}
-{"year":"2023","title":"Evaluation of Different Machine Learning, Deep Learning and Text Processing Techniques for Hate Speech Detection","authors":["N Shawkat - 2023"],"snippet":"Social media has become a domain that involves a lot of hate speech. Some users feel entitled to engage in abusive conversations by sending abusive messages, tweets, or photos to other users. It is critical to detect hate speech and prevent …","url":["https://bearworks.missouristate.edu/cgi/viewcontent.cgi?article=4958&context=theses"]}
-{"year":"2023","title":"Evaluation of Estimating Preschool Children's Verbal Communication Skills in Group Discussions","authors":["H Yamaguchi, K Horio - 2022 Joint 12th International Conference on Soft …, 2022"],"snippet":"In recent years, “First grade problem”, in which first graders who have just entered elementary school are unable to adjust to school life, has been occurring. One of the causes of this problem is a lack of communication skills. Since children have more …","url":["https://ieeexplore.ieee.org/abstract/document/10002023/"]}
-{"year":"2023","title":"Evaluation of GPT and BERT-based models on identifying protein-protein interactions in biomedical text","authors":["H Rehana, NB Çam, M Basmaci, Y He, A Özgür, J Hur - arXiv preprint arXiv …, 2023"],"snippet":"Detecting protein-protein interactions (PPIs) is crucial for understanding genetic mechanisms, disease pathogenesis, and drug design. However, with the fast-paced growth of biomedical literature, there is a growing need for automated and accurate …","url":["https://arxiv.org/pdf/2303.17728"]}
-{"year":"2023","title":"Evaluation of Language Models on Romanian XQuAD and RoITD datasets","authors":["CD Nicolae, RK Yadav, D Tufiş - INTERNATIONAL JOURNAL OF COMPUTERS …, 2023"],"snippet":"… This multi-language corpus was extracted via language classification, filtered, and cleaned from Common Crawl. Additionally, the latest version of the Wikipedia Dumps for Romanian was obtained, parliamentary debates from 1996-2017 were …","url":["https://fsja.univagora.ro/jour/index.php/ijccc/article/download/5111/1886"]}
-{"year":"2023","title":"Evaluation of strategies for the adaptation of large neural models to the task of machine translation in constrained scenarios","authors":["J Iranzo Sánchez - 2023"],"snippet":"[EN] Historically, machine translation (MT) has been one of the most active areas within artificial intelligence and more precisely, within the field of machine learning. Thanks to the significant progress in training large neural networks on massive …","url":["https://riunet.upv.es/bitstream/handle/10251/198517/Iranzo%20-%20Evaluation%20of%20strategies%20for%20the%20adaptation%20of%20large%20neural%20models%20to%20the%20task%20of%20machin....pdf?sequence=1"]}
-{"year":"2023","title":"Evidence retrieval for causal questions using query expansion and reranking","authors":["A Gaden, B Reinhold, L Zeit-Altpeter, N Rausch - Working Notes of CLEF, 2023"],"snippet":"We present our runs to the Touché Lab on Argument and Causal Retrieval at CLEF 2023, aiming to retrieve relevant documents for given causal questions. Our approaches rely heavily on query expansions. Both a transformer-based and a …","url":["https://www.dei.unipd.it/~faggioli/temp/CLEF2023-proceedings/paper-262.pdf"]}
-{"year":"2023","title":"Examining the effect of whitening on static and contextualized word embeddings","authors":["S Sasaki, B Heinzerling, J Suzuki, K Inui - Information Processing & Management, 2023"],"snippet":"… GloVe840B is trained on the Common Crawl dataset containing 840 billion tokens, while GloVe6B is trained on the Wikipedia and Gigaward dataset containing 6 billion tokens. GNews is trained by using a CBOW algorithm (Mikolov, Chen, et al., 2013) …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323000092"]}
-{"year":"2023","title":"Examining the Text-to-Image Community of Practice: Why and How do People Prompt Generative AIs?","authors":["T Sanchez - Proceedings of the 15th Conference on Creativity and …, 2023"],"snippet":"Image generation gained popularity with machine learning (ML) models generating images from text, fuelling new online communities of practices. This work explores the sociology, motivations, and usages of AI art hobbyists. We analyzed an online …","url":["https://hal.science/hal-04127516/document"]}
-{"year":"2023","title":"Examining User-Friendly and Open-Sourced Large GPT Models: A Survey on Language, Multimodal, and Scientific GPT Models","authors":["K Gao, S He, Z He, J Lin, QZ Pei, J Shao, W Zhang - arXiv preprint arXiv:2308.14149, 2023"],"snippet":"… GPT-3 [2] devised an automated filtering method to effectively eliminate low-quality documents from the Common Crawl dataset. It used a … Moreover, GPT-3 adopted fuzzy deduplication of documents within each dataset and the removal of WebText …","url":["https://arxiv.org/pdf/2308.14149"]}
-{"year":"2023","title":"ExpertQA: Expert-Curated Questions and Attributed Answers","authors":["C Malaviya, S Lee, S Chen, E Sieber, M Yatskar… - arXiv preprint arXiv …, 2023","SL ChaitanyaMalaviya, ES SihaoChen, M Yatskar…"],"snippet":"As language models are adapted by a more sophisticated and diverse set of users, the importance of guaranteeing that they provide factually correct information supported by verifiable sources is critical across fields of study & professions. This is …","url":["https://arxiv.org/pdf/2309.07852","https://cogcomp.seas.upenn.edu/papers/MLCSYR24.pdf"]}
-{"year":"2023","title":"Explainable clinical coding with in-domain adapted transformers","authors":["G López-García, JM Jerez, N Ribelles, E Alba… - Journal of Biomedical …, 2023"],"snippet":"Background and Objective Automatic clinical coding is a crucial task in the process of extracting relevant information from unstructured medical documents contained in Electronic Health Records (EHR). However, most of the existing computer-based …","url":["https://www.sciencedirect.com/science/article/pii/S1532046423000448"]}
-{"year":"2023","title":"Explainable Crowd Decision Making methodology guided by expert natural language opinions based on Sentiment Analysis with Attention-based Deep Learning and …","authors":["C Zuheros, E Martínez-Cámara, E Herrera-Viedma… - Information Fusion, 2023"],"snippet":"There exist a high demand to provide explainability to artificial intelligence systems, where decision making models are included. This paper focuses on crowd decision making using natural language evaluations from social media with the aim to …","url":["https://www.sciencedirect.com/science/article/pii/S1566253523001379"]}
-{"year":"2023","title":"Explainable multi-task convolutional neural network framework for electronic petition tag recommendation","authors":["Z Yang, J Feng - Electronic Commerce Research and Applications, 2023"],"snippet":"Electronic petition (e-petition) is an electronic government (e-government) service that allows citizens to file petitions to governments via the internet. The complexity of the e-petition filing process and the unexplainable e-government tools would reduce …","url":["https://www.sciencedirect.com/science/article/pii/S1567422323000285"]}
-{"year":"2023","title":"Explaining Sarcasm of Tweets using Attention Mechanism","authors":["RL Keerthana, AK Singh, P Saini, D Malhotra - Scalable Computing: Practice and …, 2023"],"snippet":"Emotion identification from text can help boost the effectiveness of sentiment analysis models. Sarcasm is one of the more difficult emotions to detect, particularly in textual data. Even though several models for detecting sarcasm have been …","url":["https://www.scpe.org/index.php/scpe/article/view/2166/820"]}
-{"year":"2023","title":"Explanatory Argument Extraction of Correct Answers in Resident Medical Exams","authors":["I Goenaga, A Atutxa, K Gojenola, M Oronoz, R Agerri - arXiv preprint arXiv …, 2023"],"snippet":"Developing the required technology to assist medical experts in their everyday activities is currently a hot topic in the Artificial Intelligence research field. Thus, a number of large language models (LLMs) and automated benchmarks have recently …","url":["https://arxiv.org/pdf/2312.00567"]}
-{"year":"2023","title":"Exploration of transfer learning capability of multilingual models for text classification","authors":["M Bhargava, K Vijayan, O Anand, G Raina - Proceedings of the 2023 5th International …, 2023"],"snippet":"The use of multilingual models for natural language processing is becoming increasingly popular in industrial and business applications, particularly in multilingual societies. In this study, we investigate the transfer learning capabilities …","url":["https://dl.acm.org/doi/abs/10.1145/3609703.3609711"]}
-{"year":"2023","title":"Exploring acceptance of autonomous vehicle policies using KeyBERT and SNA: Targeting engineering students","authors":["J Ha, D Kim - arXiv preprint arXiv:2307.09014, 2023"],"snippet":"This study aims to explore user acceptance of Autonomous Vehicle (AV) policies with improved text-mining methods. Recently, South Korean policymakers have viewed Autonomous Driving Car (ADC) and Autonomous Driving Robot (ADR) as …","url":["https://arxiv.org/pdf/2307.09014"]}
-{"year":"2023","title":"Exploring and Repairing Gender Fairness Violations in Word Embedding-based Sentiment Analysis Model through Adversarial Patches","authors":["LS Khoo, JQ Bay, MLK Yap, MK Lim, CY Chong…"],"snippet":"With the advancement of sentiment analysis (SA) models and their incorporation into our daily lives, fairness testing on these models is crucial, since unfair decisions can cause discrimination to a large population. Nevertheless, some challenges in …","url":["https://yangzhou6666.github.io/Files/SANER-Adv-Debiasing.pdf"]}
-{"year":"2023","title":"Exploring Applications of NLP to Create Deceptive Sandbox Environments with Honeyfiles","authors":["A Ravi, T Surve - 2023"],"snippet":"Various techniques are in practice to create a sandboxed environment to study malicious actors and/or divert them from gaining access to critical assets. Honeypots and honeynets have long been used to create decoy systems that lure adversaries …","url":["https://osf.io/qpdjw/download"]}
-{"year":"2023","title":"Exploring ChatGPT's accuracy and confidence in high-resource languages","authors":["M Pelucchi - 2023"],"snippet":"… web content and of the Common Crawl dataset in different European languages. Although, for example, 1.6% might seem like a very small percentage, all the languages listed are still commonly considered high-resource, which is usually …","url":["https://fse.studenttheses.ub.rug.nl/30857/1/Thesis_MartinoPelucchi.pdf"]}
-{"year":"2023","title":"Exploring Divergent Thinking for Cyber Soldier Selection","authors":["PA Albinsson, P Lif"],"snippet":"The Swedish Defence Research Agency is developing a test battery (CyberTest Future Soldiers—CTFS) to select conscript cyber soldier candidates for the Swedish Armed Forces since 2019. Comprising knowledge and ability components, CTFS …","url":["https://www.researchgate.net/profile/Paer-Anders-Albinsson/publication/376190168_Exploring_Divergent_Thinking_for_Cyber_Soldier_Selection/links/656d7e30b1398a779dd960d9/Exploring-Divergent-Thinking-for-Cyber-Soldier-Selection.pdf"]}
-{"year":"2023","title":"Exploring Instagram Messages on the Right to Abortion: User Profiling and Natural Language Processing Tasks","authors":["L López Cuerva - 2023"],"snippet":"… [25] presents XLM-R, a Transformer based masked language model on one hundred languages, using more than two terabytes of filtered CommonCrawl data, and it provides substantial gains over previous multilingual models like mBERT [26] …","url":["https://riunet.upv.es/bitstream/handle/10251/197643/Lopez%20-%20Exploring%20Instagram%20Messages%20on%20the%20Right%20to%20Abortion%20User%20Profiling%20and%20Natural%20Language....pdf?sequence=4"]}
-{"year":"2023","title":"Exploring natural language processing in mechanical engineering education: Implications for academic integrity","authors":["J Lesage, R Brennan, SE Eaton, B Moya, B McDermott… - International Journal of …, 2023"],"snippet":"In this paper, the authors review extant natural language processing models in the context of undergraduate mechanical engineering education. These models have advanced to a stage where it has become increasingly more difficult to discern …","url":["https://journals.sagepub.com/doi/pdf/10.1177/03064190231166665"]}
-{"year":"2023","title":"Exploring Register Variation in Turkish Web Corpus","authors":["S Erten - 14–15 September 2023, University of Mannheim …"],"snippet":"… collected by Common Crawl (commoncrawl. org) and cleaned and pre-processed within Massively Multilingual Modelling of Registers in Web-scale Corpora project run by TurkuNLP team at the University of Turku, Finland. Altogether, the corpus …","url":["https://ids-pub.bsz-bw.de/files/12095/CMC_Corpora_2023_Proceedings_2023.pdf#page=72"]}
-{"year":"2023","title":"Exploring Semantic Word Representations for Recognition-Free NLP on Handwritten Document Images","authors":["O Tüselmann, GA Fink - International Conference on Document Analysis and …, 2023"],"snippet":"A semantic analysis of documents offers a wide range of practical application scenarios. Thereby, the combination of handwriting recognizer and textual NLP models constitutes an intuitive solution. However, due to the difficulty of recognizing …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41685-9_6"]}
-{"year":"2023","title":"Exploring the Constructicon: Linguistic Analysis of a Computational CxG","authors":["J Dunn - arXiv preprint arXiv:2301.12642, 2023"],"snippet":"Recent work has formulated the task for computational construction grammar as producing a constructicon given a corpus of usage. Previous work has evaluated these unsupervised grammars using both internal metrics (for example, Minimum …","url":["https://arxiv.org/pdf/2301.12642"]}
-{"year":"2023","title":"Exploring the Conversations of a Motivational Interviewing Chatbot: A Topic Modeling Approach","authors":["RA Mazloomi"],"snippet":"… GPT-3, alongside the mentioned datasets, was also trained on CommonCrawl, a collection of webpages containing 410 billion words [31]. These models gained state-of-the-art performance on many language task benchmarks, including machine translation …","url":["https://tspace.library.utoronto.ca/bitstream/1807/130535/3/Mazloomi_Rod_Ali_202311_MIS_thesis.pdf"]}
-{"year":"2023","title":"Exploring the Cookieverse: A Multi-Perspective Analysis of Web Cookies","authors":["A Rasaii, S Singh, D Gosain, O Gasser - arXiv preprint arXiv:2302.05353, 2023"],"snippet":"Web cookies have been the subject of many research studies over the last few years. However, most existing research does not consider multiple crucial perspectives that can influence the cookie landscape, such as the client's location, the impact of …","url":["https://arxiv.org/pdf/2302.05353"]}
-{"year":"2023","title":"Exploring the impact of intermediate languages on machine translation","authors":["AS Oliveira, RS Fernandes - 2023"],"snippet":"The field of translation predates the computer, and as technology has advanced, it has evolved and adapted to new discoveries, constantly striving to become more efficient and precise. Machine translation, an integral part of Natural Language …","url":["https://pantheon.ufrj.br/bitstream/11422/21591/1/ASOliveira.pdf"]}
-{"year":"2023","title":"Exploring the limits of early predictive maintenance applying anomaly detection technique","authors":["A Serackis, M Jankauskas - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:148981672/148981672.pdf"]}
-{"year":"2023","title":"Exploring the Potential of Large Language models in Traditional Korean Medicine: A Foundation Model Approach to Culturally-Adapted Healthcare","authors":["D Jang, CE Kim - arXiv preprint arXiv:2303.17807, 2023"],"snippet":"… In fact, the pre-training dataset for GPT-3, a model released in 2020 that ChatGPT is based on, is mainly derived from a modified version of Common Crawl (19) in which English-based data accounts for about 50%, while Korean data accounts for …","url":["https://arxiv.org/pdf/2303.17807"]}
-{"year":"2023","title":"Exploring the Trade-Offs: Unified Large Language Models vs Local Fine-Tuned Models for Highly-Specific Radiology NLI Task","authors":["Z Wu, L Zhang, C Cao, X Yu, H Dai, C Ma, Z Liu… - arXiv preprint arXiv …, 2023"],"snippet":"… GPT-3 has a massive 175 billion parameters and was trained on a diverse collection of internet data, including Common Crawl3 and Wikipedia4. GPT-4 is the most powerful LLM to date, a successor of GPT-3. Although the technical details of …","url":["https://arxiv.org/pdf/2304.09138"]}
-{"year":"2023","title":"Exploring the Why in AI: Investigating how Visual Question Answering models can be interpreted by post-hoc linguistic and visual explanations","authors":["ECG Strømsvåg - 2023"],"snippet":"With the increase in accuracy and usability of Artificial Intelligence (AI), especially deep neural networks, there has been a big demand for these networks. These methods are implemented in various domains to increase productivity, create new …","url":["https://www.duo.uio.no/bitstream/handle/10852/104443/ecstroms_master_thesis_2023_with_appendix.pdf?sequence=5"]}
-{"year":"2023","title":"Exploring zero-shot and joint training cross-lingual strategies for aspect-based sentiment analysis based on contextualized multilingual language models","authors":["D Van Thin, H Quoc Ngo, D Ngoc Hao… - Journal of Information and …, 2023"],"snippet":"Aspect-based sentiment analysis (ABSA) has attracted many researchers' attention in recent years. However, the lack of benchmark datasets for specific languages is a common challenge because of the prohibitive cost of manual annotation. The zero-shot …","url":["https://www.tandfonline.com/doi/pdf/10.1080/24751839.2023.2173843"]}
-{"year":"2023","title":"Extended context for InstructGPT with LlamaIndex","authors":["B Zirnstein"],"snippet":"… To train the extensive amount of parameters, a refined version of the Common Crawl dataset1 was used, consisting of almost a trillion … 1https://commoncrawl.org/the-data/ 2The modifications include a “modified initialization, pre-normalization, and …","url":["https://www.researchgate.net/profile/Bruno-Zirnstein/publication/371911146_Extended_context_for_InstructGPT_with_LlamaIndex/links/649bd64e95bbbe0c6efc1345/Extended-context-for-InstructGPT-with-LlamaIndex.pdf"]}
-{"year":"2023","title":"Extended Hell (o): A Comprehensive Large-Scale Study on Email Confidentiality and Integrity Mechanisms in the Wild","authors":["B Blechschmidt, B Stock"],"snippet":"The core specifications of electronic mail as used today date back as early as the 1970s. At that time, security did not play a significant role in developing communication protocols. These shortcomings still manifest themselves today in the …","url":["https://swag.cispa.saarland/papers/blechschmidt2023extendedhello.pdf"]}
-{"year":"2023","title":"Extracting Geographic Knowledge from Large Language Models: An Experiment","authors":["K Salmas, DA Pantazi, M Koubarakis - … on Knowledge Base Construction from Pre …, 2023"],"snippet":"We perform a thorough analysis of how the inner architecture of large language models behaves whilst extracting geographic knowledge. Our aim is to conclude on whether models actually incorporate geospatial information or simply follow …","url":["https://openreview.net/pdf?id=SqR8UgZXNl"]}
-{"year":"2023","title":"Extracting Intersectional Stereotypes from Static and Contextualized Embeddings","authors":["TES Charlesworth, K Ghate, A Caliskan, MR Banaji - 2023"],"snippet":"… text corpora, ranging from static GloVe embeddings trained on 840 billion words from the Common Crawl to contextualized BERT embeddings trained on a combination of Wikipedia and Common Crawl text. For the simplest case of static …","url":["https://osf.io/preprints/psyarxiv/tbuqh/download"]}
-{"year":"2023","title":"Extracting Key-Value Pairs in Business Documents","authors":["E Thomas, DS Kafle, IS Mahamoud, A Joseph… - International Conference on …, 2023"],"snippet":"Key-value extraction is a challenging task in document AI, particularly in business documents such as invoices. Accurately extracting key-value pairs from such documents is crucial for downstream tasks like accounting, analytics, and decision-making …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41501-2_3"]}
-{"year":"2023","title":"Extracting Mental Health Indicators From English and Spanish Social Media: A Machine Learning Approach","authors":["ME Villa-Pérez, LA Trejo, MB Moin, E Stroulia - IEEE Access, 2023"],"snippet":"… For the English Twitter dataset, we used word vectors trained on Common Crawl from the … The Common Crawl corpus contains petabytes of data collected over 12 years of web … Available: https://commoncrawl.org/the-data/ [56] O. Loyola-González …","url":["https://ieeexplore.ieee.org/iel7/6287639/10005208/10315126.pdf"]}
-{"year":"2023","title":"Extracting relations from texts using vector language models and a neural network classifier","authors":["M Shishaev, V Dikovitsky, V Pimeshkov, N Kuprikov… - PeerJ Computer Science, 2023"],"snippet":"The article investigates the possibility of identifying the presence of SKOS (Simple Knowledge Organization System) relations between concepts represented by terms on the base of their vector representation in general natural language models …","url":["https://peerj.com/articles/cs-1636/"]}
-{"year":"2023","title":"Extracting representative subset from extensive text data for training pre-trained language models","authors":["J Suzuki, H Zen, H Kazawa - Information Processing & Management, 2023"],"snippet":"This paper investigates the existence of a representative subset obtained from a large original dataset that can achieve the same performance level obtained using the entire dataset in the context of training neural language models. We employ the …","url":["https://www.sciencedirect.com/science/article/pii/S0306457322003508"]}
-{"year":"2023","title":"Extracting Training Data from GPT-2","authors":["J Borkar"],"snippet":"… We collect tokens from the Common Crawl dataset and use them (5-10 tokens) as prefixes to prompt GPT-2 to generate samples. … Common Crawl dataset has all the data that has been crawled from the public internet. So if we prompt GPT-2 using …","url":["https://jaydeepborkar.github.io/7150_project_report.pdf"]}
-{"year":"2023","title":"Extraction of microservices from monolithic software based on the database model","authors":["D Mažeika, EK Kazlauskas - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:147344326/147344326.pdf"]}
-{"year":"2023","title":"Extraction of Parallel Sentences","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"… billion parallel sentences in 90 languages from CommonCrawl snapshots, among which less than … This system, trained from parallel sentences collected from CommonCrawl as explained … sentence embeddings to extract parallel sentences …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_4"]}
-{"year":"2023","title":"Extractive Summarization of Telugu Text Using Modified Text Rank and Maximum Marginal Relevance","authors":["A Babu Gl, S Badugu - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"With the rapid growth of digital content, the need for the automatic text summarizer is arising to provide short text from the long text document. Many research works have been presented for extractive text summarization (ETS). This paper mainly focuses …","url":["https://dl.acm.org/doi/pdf/10.1145/3600224"]}
-{"year":"2023","title":"Förenkla nyhetssammanfattning med hjälp av AI: En analys av GPT-3 modellers förmåga och begränsningar","authors":["J Pålsmark, TA Viklund - 2023"],"snippet":"Everyday we are flooded with news from all around the world and this information can be overwhelming. In our study we analyze the possibilities to implement GPT-3 models in the work of news summarization in swedish and automize this process. In …","url":["https://www.diva-portal.org/smash/get/diva2:1760660/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Face Recognition in the age of CLIP & Billion image datasets","authors":["A Bhat, S Jain - arXiv preprint arXiv:2301.07315, 2023"],"snippet":"… LAION-5B was collected by parsing files in the Common Crawl dataset to find image tags with alt-text values. The corresponding images were downloaded and filtered using CLIP to keep only those images whose content resembled their alt-text …","url":["https://arxiv.org/pdf/2301.07315"]}
-{"year":"2023","title":"Factors Affecting the Reliability of Information: The Case of ChatGPT","authors":["J Morato, JM Diaz-Nafria, S Sanchez-Cuadrado - International Conference on …, 2023"],"snippet":"The abundance of current information makes it necessary to select the highest quality documents. For this purpose, it is necessary to deepen the knowledge of information quality systems. The different dimensions of quality are analyzed, and …","url":["https://link.springer.com/chapter/10.1007/978-3-031-48930-3_12"]}
-{"year":"2023","title":"Fairness and Bias in Algorithmic Hiring","authors":["A Fabris, N Baranowska, MJ Dennis, P Hacker… - arXiv preprint arXiv …, 2023"],"snippet":"… Bias in Bios, [60] is composed of textual biographies written in English and extracted from the Common Crawl dataset. It was initially proposed to study fairness in occupation classification. Gender is automatically extracted based on the use of …","url":["https://arxiv.org/pdf/2309.13933"]}
-{"year":"2023","title":"Fairness and Fair Use in Generative AI","authors":["M Sag - 2023"],"snippet":"Although we are still a long way from the science fiction version of artificial general intelligence that thinks, feels, and refuses to “open the pod bay doors”, 1 recent advances in machine learning and artificial intelligence (“AI”) have captured the …","url":["https://digitalcommons.wcl.american.edu/cgi/viewcontent.cgi?article=1120&context=research"]}
-{"year":"2023","title":"Fairness in Language Models Beyond English: Gaps and Challenges","authors":["K Ramesh, S Sitaram, M Choudhury - arXiv preprint arXiv:2302.12578, 2023"],"snippet":"With language models becoming increasingly ubiquitous, it has become essential to address their inequitable treatment of diverse demographic groups and factors. Most research on evaluating and mitigating fairness harms has been concentrated on …","url":["https://arxiv.org/pdf/2302.12578"]}
-{"year":"2023","title":"Fake News Detection via Deep Learning Approaches","authors":["M Li - 2023 4th International Symposium on Computer …, 2023"],"snippet":"… RealNews: RealNews is a corpus of news articles whose data is taken from Common Crawl. The body and metadata in each news article is extracted by the Newspaper Python library. The training data uses news data from December 2016 to March 2019. …","url":["https://ieeexplore.ieee.org/abstract/document/10271110/"]}
-{"year":"2023","title":"Fake news detection: Taxonomy and comparative study","authors":["F Farhangian, RMO Cruz, GDC Cavalcanti - Information Fusion, 2023"],"snippet":"The proliferation of social networks has presented a significant challenge in combating the pervasive issue of fake news within modern societies. Due to the large amount of information and news produced daily in text, audio, and video, the …","url":["https://www.sciencedirect.com/science/article/pii/S1566253523004566"]}
-{"year":"2023","title":"Faking It: Artificial Intelligence in a Human World","authors":["T Walsh - 2023"]}
-{"year":"2023","title":"Fast and Energy-Efficient Inference for Attention-Based Natural Language Processing Models","authors":["A Hadi Zadeh - 2023","AH Zadeh - 2023"],"snippet":"Creating machines that can ``understand’’ our language and ``interact’’ with us as we interact with each other has been a dream that motivated many and captured the imaginations of even more. Attention-Based Transformer models have demonstrated …","url":["https://search.proquest.com/openview/8ef0b6a759aff7cf22bf26f40affd1bd/1?pq-origsite=gscholar&cbl=18750&diss=y","https://tspace.library.utoronto.ca/bitstream/1807/128003/3/Hadi_Zadeh_Ali_202306_PhD_thesis.pdf"]}
-{"year":"2023","title":"Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature","authors":["G Bao, Y Zhao, Z Teng, L Yang, Y Zhang - arXiv preprint arXiv:2310.05130, 2023"],"snippet":"Large language models (LLMs) have shown the ability to produce fluent and cogent content, presenting both productivity opportunities and societal risks. To build trustworthy AI systems, it is imperative to distinguish between machine-generated …","url":["https://arxiv.org/pdf/2310.05130"]}
-{"year":"2023","title":"Feature Learning in Infinite-Depth Neural Networks","authors":["G Yang, D Yu, C Zhu, S Hayou - NeurIPS 2023 Workshop on Mathematics of Modern …, 2023"],"snippet":"… block is deeper (such as modern transformers), then we find fundamental limitations in all possible infinite-depth limits of such parametrizations, which we illustrate both theoretically and empirically on simple networks as well as Megatron …","url":["https://openreview.net/forum?id=xxYfmRTwyX"]}
-{"year":"2023","title":"Feature-Level Ensemble Learning for Robust Synthetic Text Detection with DeBERTaV3 and XLM-RoBERTa","authors":["SS Joy, TD Aishi - Proceedings of ALTA, 2023"],"snippet":"As large language models, or LLMs, continue to advance in recent years, they require the development of a potent system to detect whether a text was created by a human or an LLM in order to prevent the unethical use of LLMs. To address this …","url":["https://alta2023.alta.asn.au/files/st_04.pdf"]}
-{"year":"2023","title":"Federated Learning with Client-Exclusive Classes","authors":["J Zhang, X Zhang, X Zhang, D Hong, RK Gupta… - arXiv preprint arXiv …, 2023"],"snippet":"Existing federated classification algorithms typically assume the local annotations at every client cover the same set of classes. In this paper, we aim to lift such an assumption and focus on a more general yet practical non-IID setting where every …","url":["https://arxiv.org/pdf/2301.00489"]}
-{"year":"2023","title":"Few-Shot Learning for Identification of COVID-19 Symptoms Using Generative Pre-trained Transformer Language Models","authors":["K Jiang, M Zhu, GR Bernard - Machine Learning and Principles and Practice of …, 2023"],"snippet":"Since the onset of the COVID-19 pandemic, social media users have shared their personal experiences related to the viral infection. Their posts contain rich information of symptoms that may provide useful hints to advancing the knowledge …","url":["https://link.springer.com/chapter/10.1007/978-3-031-23633-4_21"]}
-{"year":"2023","title":"Few-shot Learning with Multilingual Generative Language Models","authors":["XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen… - Proceedings of the 2022 …, 2022"],"snippet":"… As such we also note the potential difference in genres between CommonCrawl and the genres used in GPT-3 comprising in addition to CommonCrawl, corpora such as BookCorpus and Wikipedia. Moreover, GPT-3 is trained on 118 languages …","url":["https://aclanthology.org/2022.emnlp-main.616.pdf"]}
-{"year":"2023","title":"Filtering and Extended Vocabulary based Translation for Low-resource Language pair of Sanskrit-Hindi","authors":["P Jha, R Kumar, V Sahula - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"… We used the reported Model 3 (Hindi to Sanskrit) and fed it with a small fraction of monolingual Hindi data (about 10k small sentences from CommonCrawl6 as used by [29]) to generate Sanskrit translations. We used a small fraction of the data to …","url":["https://dl.acm.org/doi/pdf/10.1145/3580495"]}
-{"year":"2023","title":"Filtering, Distillation, and Hard Negatives for Vision-Language Pre-Training","authors":["F Radenovic, A Dubey, A Kadian, T Mihaylov… - arXiv preprint arXiv …, 2023"],"snippet":"Vision-language models trained with contrastive learning on large-scale noisy data are becoming increasingly popular for zero-shot recognition problems. In this paper we improve the following three aspects of the contrastive pre-training pipeline …","url":["https://arxiv.org/pdf/2301.02280"]}
-{"year":"2023","title":"FIMO: A Challenge Formal Dataset for Automated Theorem Proving","authors":["C Liu, J Shen, H Xin, Z Liu, Y Yuan, H Wang, W Ju… - arXiv preprint arXiv …, 2023"],"snippet":"We present FIMO, an innovative dataset comprising formal mathematical problem statements sourced from the International Mathematical Olympiad (IMO) Shortlisted Problems. Designed to facilitate advanced automated theorem proving at the IMO …","url":["https://arxiv.org/pdf/2309.04295"]}
-{"year":"2023","title":"Financial Machine Learning with Alternative Data","authors":["J Jiang - 2023"],"snippet":"In the first chapter, we reconsider the idea of trend-based predictability using methods that flexibly learn price patterns that are most predictive of future returns, rather than testing hypothesized or pre-specified patterns (eg, momentum and …","url":["https://search.proquest.com/openview/98f583e53d755e34bc8666ecf40c317f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Findings of the 2023 Conference on Machine Translation (WMT23): LLMs Are Here But Not Quite There Yet","authors":["K Tom, E Avramidis, R Bawden, O Bojar, A Dvorkovich… - WMT23-Eighth Conference …, 2023"],"snippet":"This paper presents the results of the General Machine Translation Task organised as part of the 2023 Conference on Machine Translation (WMT). In the general MT task, participants were asked to build machine translation systems for any of 8 …","url":["https://hal.science/hal-04300702/document"]}
-{"year":"2023","title":"Findings of the CoCo4MT 2023 Shared Task on Corpus Construction for Machine Translation","authors":["A Ganesh, M Carpuat, W Chen, K Kann, C Lignos… - CoCo4MT 2023, 2023"],"snippet":"This paper provides an overview of the first shared task on choosing beneficial instances for machine translation, conducted as part of the CoCo4MT 2023 Workshop at MTSummit. This shared task was motivated by the need to make the …","url":["https://files.sciconf.cn/upload/file/20230903/20230903151747_19845.pdf#page=34"]}
-{"year":"2023","title":"Findings of the Second WMT Shared Task on Sign Language Translation","authors":["M Müller, M Alikhani, E Avramidis, R Bowden, A Braffort…"],"snippet":"This paper presents the results of the Second WMT Shared Task on Sign Language Translation (WMT-SLT23) 1. This shared task is concerned with automatic translation between signed and spoken 2 languages. The task is unusual in the …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.4.pdf"]}
-{"year":"2023","title":"Findings of the WMT 2023 shared task on parallel data curation","authors":["S Sloto, B Thompson, H Khayrallah, T Domhan… - Proceedings of the Eighth …, 2023"],"snippet":"… We release processed Common Crawl data, along with various intermediate states from a strong baseline system, which we believe will … All of our inputs were derived from the 2023-06 snapshot of Common Crawl. We extracted the plain text …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.5.pdf"]}
-{"year":"2023","title":"Fine Tuning Transformer Models for Domain Specific Feature Extraction","authors":["C Campàs Gené - 2023"],"snippet":"The nature of Natural Language Processing has drastically changed in the past years. The implementation of Large Language Models pre-trained on thousands of unlabelled data has opened the door to a new layer of comprehension of text …","url":["https://upcommons.upc.edu/bitstream/handle/2117/384726/173985.pdf?sequence=2"]}
-{"year":"2023","title":"Fine-Grained Language Relatedness for Zero-Shot Silesian-English Translation","authors":["E Signoroni - RASLAN 2023 Recent Advances in Slavonic Natural …, 2023"],"snippet":"… -cleaned version of the Common Crawl web dump containing about 750GB of English text. T5 uses a unified” text-to-text” format for all text-based NLP problems. Xue et al.(2021)[29] present mT5, a multilingual variant of T5 trained on a Common …","url":["http://nlp.fi.muni.cz/raslan/raslan23.pdf#page=153"]}
-{"year":"2023","title":"Fine-tuning MBART-50 with French and Farsi data to improve the translation of Farsi dislocations into English and French","authors":["B Namdarzadeh, S Mohseni, L Zhu, G Wisniewski… - Proceedings of Machine …, 2023"],"snippet":"In this paper, we discuss the improvements brought by the fine-tuning of mBART50 for the translation of a specific Farsi dataset of dislocations. Given our BLEU scores, our evaluation is mostly qualitative: we assess the improvements of our fine-tuning …","url":["https://aclanthology.org/2023.mtsummit-users.14.pdf"]}
-{"year":"2023","title":"FinGPT: Large Generative Models for a Small Language","authors":["R Luukkonen, V Komulainen, J Luoma, A Eskelinen… - arXiv preprint arXiv …, 2023"],"snippet":"… Common Crawl and a targeted Internet crawl seeded by the .fi domain registry content and all URLs of Finnish material in Common Crawl. … CC-Fi To maximize coverage of Finnish text in Common Crawl resources, we applied a custom …","url":["https://arxiv.org/pdf/2311.05640"]}
-{"year":"2023","title":"Finnish Internet Parsebank","authors":["J Luotolahti, J Kanerva, J Luoma, V Skantsi, S Pyysalo… - 2023"],"snippet":"… The Common Crawl dataset includes both plain text and raw HTML files, at the time without … plain text from the Amazon cloud service that hosts Common Crawl As shown in Table 2, this … of all Finnish text pages we gathered from Common …","url":["https://www.researchsquare.com/article/rs-3138153/latest.pdf"]}
-{"year":"2023","title":"Focused Crawling for Automated IsiXhosa Corpus Building","authors":["C Marquard, H Suleman - Annual Conference of South African Institute of …, 2023"],"snippet":"IsiXhosa is a low-resource language, which means that it does not have many large, high-quality corpora. This makes it difficult to perform many kinds of research with the language. This paper examines the use of focused Web crawling for automatic …","url":["https://link.springer.com/chapter/10.1007/978-3-031-39652-6_2"]}
-{"year":"2023","title":"Form to meaning mapping and the impact of explicit morpheme combination in novel word processing","authors":["R Bonandrini, S Amenta, S Sulpizio, M Tettamanti… - Cognitive Psychology, 2023"],"snippet":"In the present study, we leveraged computational methods to explore the extent to which, relative to direct access to semantics from orthographic cues, the additional appreciation of morphological cues is advantageous while inducing the meaning of …","url":["https://www.sciencedirect.com/science/article/pii/S001002852300052X"]}
-{"year":"2023","title":"Foundation Models and Fair Use","authors":["P Henderson, X Li, D Jurafsky, T Hashimoto… - arXiv preprint arXiv …, 2023"],"snippet":"… 2021), rely on CommonCrawl data which is crawled only if users explicitly allow it through their robots.txt file. CommonCrawl is able to host a snapshot of the internet largely because of fair use arguments. As the organization’s director argues, there is …","url":["https://arxiv.org/pdf/2303.15715"]}
-{"year":"2023","title":"Foundation models and the privatization of public knowledge","authors":["F Ferrari, J van Dijck, A van den Bosch - Nature Machine Intelligence, 2023"],"snippet":"… This translates to approximately 300 billion words extracted from sources such as Wikipedia, CommonCrawl and GitHub. Overall, the training procedure involved the learning of 175 billion parameters. ChatGPT relies on GPT-4 as well as on a specific …","url":["https://www.nature.com/articles/s42256-023-00695-5"]}
-{"year":"2023","title":"Foundation Models in Robotics: Applications, Challenges, and the Future","authors":["R Firoozi, J Tucker, S Tian, A Majumdar, J Sun, W Liu… - arXiv preprint arXiv …, 2023"],"snippet":"… GPT-3 is trained on the Common Crawl dataset. Common Crawl contains petabytes of publicly available data over 12 years of web crawling and includes raw web page data, metadata, and text extracts. LLMs can also be multilingual. For …","url":["https://arxiv.org/pdf/2312.07843"]}
-{"year":"2023","title":"Foundational Models Defining a New Era in Vision: A Survey and Outlook","authors":["M Awais, M Naseer, S Khan, RM Anwer, H Cholakkal… - arXiv preprint arXiv …, 2023"],"snippet":"… common crawl. Schuhmann et al. [227] further scaled it up and released a multilingual, multi-modal dataset called LAION-5B which contains 5.8 billion data points curated from Common Crawl after filtering through existing CLIP model. Utilizing largescale …","url":["https://arxiv.org/pdf/2307.13721"]}
-{"year":"2023","title":"FP8-LM: Training FP8 Large Language Models","authors":["H Peng, K Wu, Y Wei, G Zhao, Y Yang, Z Liu, Y Xiong… - arXiv preprint arXiv …, 2023"],"snippet":"… 2022) across CommonCrawl snapshots to enhance data quality. Tab. 10 in Appendix A.3 provides details of our pre-training data, including … 2023) to distinguish documents similar to Wikipedia pages from randomly sampled …","url":["https://arxiv.org/pdf/2310.18313"]}
-{"year":"2023","title":"From Base to Conversational: Japanese Instruction Dataset and Tuning Large Language Models","authors":["M Suzuki, M Hirano, H Sakaji - arXiv preprint arXiv:2309.03412, 2023"],"snippet":"Instruction tuning is essential for large language models (LLMs) to become interactive. While many instruction tuning datasets exist in English, there is a noticeable lack in other languages. Also, their effectiveness has not been well …","url":["https://arxiv.org/pdf/2309.03412"]}
-{"year":"2023","title":"From Characters to Words: Hierarchical Pre-trained Language Model for Open-vocabulary Language Understanding","authors":["L Sun, F Luisier, K Batmanghelich, D Florencio… - arXiv preprint arXiv …, 2023"],"snippet":"… Most generic language models are pre-trained on web-crawled text corpora including Wikipedia and Common Crawl. But in real world deployments, models are often used in a different domain, an issue referred to as domain shift. In order to …","url":["https://arxiv.org/pdf/2305.14571"]}
-{"year":"2023","title":"From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy","authors":["M Gupta, CK Akiri, K Aryal, E Parker, L Praharaj - arXiv preprint arXiv:2307.00691, 2023"],"snippet":"… Initially, GPT-1 was trained with the Common Crawl dataset, made up of web pages, and the BookCorpus dataset, which contained over … GPT-2: GPT-2 was trained on Common Crawl just like GPT-1 but combined that with WebText, which …","url":["https://arxiv.org/pdf/2307.00691"]}
-{"year":"2023","title":"From chocolate bunny to chocolate crocodile: Do Language Models Understand Noun Compounds?","authors":["J Coil, V Shwartz - arXiv preprint arXiv:2305.10568, 2023"],"snippet":"Noun compound interpretation is the task of expressing a noun compound (eg chocolate bunny) in a free-text paraphrase that makes the relationship between the constituent nouns explicit (eg bunny-shaped chocolate). We propose modifications …","url":["https://arxiv.org/pdf/2305.10568"]}
-{"year":"2023","title":"From GPT to AutoGPT: a Brief Attention in NLP Processing using DL","authors":["M Fezari, AAD Ali-Al-Dahoud"],"snippet":"in this paper, we intend to present the evolution of the so called “Generative Pre-Training (GPT) models”. Starting from GPT-1 to the new one GPt-4 and AutoGPT, Generative Pre-Training (GPT) models are trained on unlabeled dataset (which are available in …","url":["https://www.researchgate.net/profile/Mohamed-Fezari-2/publication/370107237_From_GPT_to_AutoGPT_a_Brief_Attention_in_NLP_Processing_using_DL/links/643fd87a2eca706c8b6d151b/From-GPT-to-AutoGPT-a-Brief-Attention-in-NLP-Processing-using-DL.pdf"]}
-{"year":"2023","title":"From Pre-training to Meta-Learning: A journey in Low-Resource-Language Representation Learning","authors":["D Zaikis, I Vlahavas - IEEE Access, 2023"],"snippet":"Language representation learning is a vital field in Natural Language Processing (NLP) that aims to capture the intricate semantics and contextual information of text. With the advent of deep learning and neural network architectures, representation …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10288436.pdf"]}
-{"year":"2023","title":"From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models","authors":["S Feng, CY Park, Y Liu, Y Tsvetkov - arXiv preprint arXiv:2305.08283, 2023"],"snippet":"Large language models (LMs) are pretrained on diverse data sources: news, discussion forums, books, online encyclopedias. A significant portion of this data includes facts and opinions which, on one hand, celebrate democracy and diversity …","url":["https://arxiv.org/pdf/2305.08283"]}
-{"year":"2023","title":"From task to evaluation: an automatic text summarization review","authors":["L Lu, Y Liu, W Xu, H Li, G Sun - Artificial Intelligence Review, 2023"],"snippet":"Automatic summarization is attracting increasing attention as one of the most promising research areas. This technology has been tried in various real-world applications in recent years and achieved a good response. However, the …","url":["https://link.springer.com/article/10.1007/s10462-023-10582-5"]}
-{"year":"2023","title":"From Text to Source: Results in Detecting Large Language Model-Generated Content","authors":["W Antoun, B Sagot, D Seddah - arXiv preprint arXiv:2309.13322, 2023"],"snippet":"The widespread use of Large Language Models (LLMs), celebrated for their ability to generate human-like text, has raised concerns about misinformation and ethical implications. Addressing these concerns necessitates the development of robust …","url":["https://arxiv.org/pdf/2309.13322"]}
-{"year":"2023","title":"From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inference","authors":["S Samsi, D Zhao, J McDonald, B Li, A Michaleas… - arXiv preprint arXiv …, 2023"],"snippet":"… Like other LLMs, LLaMA was pre-trained on a large collection of data including but not limited to CommonCrawl, Github, Wikipedia, etc. As of spring 2023, alongside other recently timed releases of state-of-the-art LLMs such as Google’s …","url":["https://arxiv.org/pdf/2310.03003"]}
-{"year":"2023","title":"From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning","authors":["Q Liu, F Zhou, Z Jiang, L Dou, M Lin - arXiv preprint arXiv:2304.07995, 2023"],"snippet":"Fine-tuning language models on tasks with instructions has demonstrated potential in facilitating zero-shot generalization to unseen tasks. In this paper, we introduce a straightforward yet effective method for enhancing instruction tuning by employing …","url":["https://arxiv.org/pdf/2304.07995"]}
-{"year":"2023","title":"FSTP Project Report AID2030–ArtificialIn-telligenceDataKit2030","authors":["S Koeva, V Stefanova - 2023"],"snippet":"… CommonCrawl29 creates and maintains an open web crawl data collection. Petabytes of data have been collected by Common Crawl since 2008, including … RealNews33 is a dataset of news articles from Common Crawl. The text and the …","url":["https://european-language-equality.eu/wp-content/uploads/2023/06/ELE2_Project_Report_AID_2030.pdf"]}
-{"year":"2023","title":"Fundamentals of Generative Large Language Models and Perspectives in Cyber-Defense","authors":["A Kucharavy, Z Schillaci, L Maréchal, M Würsch… - arXiv preprint arXiv …, 2023"],"snippet":"… to train GPT-2, along with a filtered and deduplicated version of the Common Crawl, a dataset of all the text that can be found by a crawl on … from Wikipedia is likely to be seen on average 3.4 times during the training compared to 0.44 times for …","url":["https://arxiv.org/pdf/2303.12132"]}
-{"year":"2023","title":"GAIA Search: Hugging Face and Pyserini Interoperability for NLP Training Data Exploration","authors":["A Piktus, O Ogundepo, C Akiki, A Oladipo, X Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"… Rather than investing in scraping the Web on their own, dataset creators typically turn to Common Crawl1 as the main source of text to include in their corpora. A repository of Web snapshots dating back to 2011, Common Crawl contains various …","url":["https://arxiv.org/pdf/2306.01481"]}
-{"year":"2023","title":"GEM: Gestalt Enhanced Markup Language Model for Web Understanding via Render Tree","authors":["Z Shao, F Gao, Z Qi, H Xing, J Bu, Z Yu, Q Zheng, X Liu - Proceedings of the 2023 …, 2023"],"snippet":"… Our corpora are built from the Common Crawl12 dataset. We derive approximately 2 million training samples from 100k renderable web pages by pre-processing. Details of the data pre-processing are available in Section 3.1. … 12https://commoncrawl.org/ …","url":["https://aclanthology.org/2023.emnlp-main.375.pdf"]}
-{"year":"2023","title":"Gender stereotypes embedded in natural language are stronger in more economically developed and individualistic countries","authors":["C Napp - PNAS Nexus, 2023"],"snippet":"… Relying on two different sources (Wikipedia and Common Crawl), we found that these gender stereotypes are all significantly more pronounced in the text corpora of more economically developed and more individualistic countries. Our analysis …","url":["https://academic.oup.com/pnasnexus/article/2/11/pgad355/7429364"]}
-{"year":"2023","title":"Gender stereotypes in neural sentence representations","authors":["A Al Ali - 2023"],"snippet":"Neural networks have seen a spike in popularity in natural language processing in re- cent years. They consistently outperform the traditional methods and require less human labor to perfect as they are trained unsupervised on large text corpora …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/184287/130369737.pdf?sequence=1"]}
-{"year":"2023","title":"Gender Stereotypes in User-Generated Content","authors":["A Kerkhof, V Reich - 2023"],"snippet":"Gender stereotypes pose an important hurdle on the way to gender equality. It is difficult to quantify the problem, though, as stereotypical beliefs are often subconscious or not openly expressed. User-generated content (UGC) opens up …","url":["https://www.cesifo.org/DocDL/cesifo1_wp10578.pdf"]}
-{"year":"2023","title":"Generating a Large Web Traffic Dataset","authors":["BC Simmonds - 2023"],"snippet":"… Resource Locators) from the Common Crawl dataset as a foundational … the Common Crawl dataset, by requesting each website of the collection to measure the required server response time. Nonetheless, this solution has its drawbacks …","url":["https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/632737/Simmonds_Benjamin.pdf?sequence=1"]}
-{"year":"2023","title":"Generating abstract art using artificial neural networks","authors":["H Norrman"],"snippet":"Articial intelligence (AI) tools are slowly becoming integral to our everyday lives. Today we already rely on AI for much of our navigation and security. In the near future, much like the internet today, AI and machine learning tools are likely to assist …","url":["https://lup.lub.lu.se/student-papers/record/9142136/file/9142137.pdf"]}
-{"year":"2023","title":"Generating plumitifs descriptions using neural networks","authors":["N Garneau - 2023"],"snippet":"Comme dans de nombreuses autres démocraties, il existe au Canada un droit d'accès à l'information judiciaire. Il s' agit d'un élément fondamental de tout processus judiciaire. Ce droit a deux objectifs principaux: offrir une fenêtre sur le système de …","url":["https://corpus.ulaval.ca/bitstreams/34518b78-5505-40c4-8d13-8bec62840aa6/download"]}
-{"year":"2023","title":"Generating Query Focused Summaries without Fine-tuning the Transformer-based Pre-trained Models","authors":["D Abdullah, S Nayak, G Suri, Y Chali - arXiv preprint arXiv:2303.06230, 2023"],"snippet":"Fine-tuning the Natural Language Processing (NLP) models for each new data set requires higher computational time associated with increased carbon footprint and cost. However, fine-tuning helps the pre-trained models adapt to the latest data sets; …","url":["https://arxiv.org/pdf/2303.06230"]}
-{"year":"2023","title":"Generating Synthetic Data from Large Language Models","authors":["S Choenni, T Busker, MS Bargh - 2023 15th International Conference on Innovations …, 2023"],"snippet":"Data collection for studying social phenomena is not only costly but is also, at best, a time-consuming and tedious task. Therefore, tools that may ease the task of data collection will speed up these studies and improve their efficiency. In this contribution …","url":["https://ieeexplore.ieee.org/abstract/document/10366424/"]}
-{"year":"2023","title":"Generation of Synthetic Responses to Survey Questions Using GPT-3: A Case of Hard-to-Reach Members of Russian Elites (based on the Survey of Russian Elites)","authors":["K Kalinin"],"snippet":"The goal of this study is to use a large language model, such as GPT-3, to generate responses from hard-to-reach elite members to multiple-choice questions. The most relevant or data-consistent responses can then be used to infer potential responses …","url":["https://kirillkalinin.com/files/paper_gpt3.pdf"]}
-{"year":"2023","title":"Generations: Creative Computation, Community, and the Rhetorical Canon","authors":["C Schnitzler - 2023"],"snippet":"“Generations: Creative Computation, Community, and the Rhetorical Canon” investigates how computational poets and artists use the intrinsic rhetoricity of generative computational processes for social critique and community-building …","url":["https://cdr.lib.unc.edu/downloads/794087356"]}
-{"year":"2023","title":"Generative AI and Lexicography: The Current State of the Art Using ChatGPT","authors":["GM de Schryver - International Journal of Lexicography, 2023"],"snippet":"In this article, all ten papers and talks that have been devoted to the use of ChatGPT in lexicography so far are critically analysed, their results tabulated and cross-compared, from which the leading trends are determined. Extrapolating from the trendlines, a …","url":["https://academic.oup.com/ijl/advance-article/doi/10.1093/ijl/ecad021/7288213"]}
-{"year":"2023","title":"Generative AI and the Digital Commons","authors":["S Huang, D Siddarth - arXiv preprint arXiv:2303.11074, 2023"],"snippet":"… They also rely on nonprofits like Common Crawl (which build and maintain open repositories of web crawl data), Creative Commons (for open licenses for the data used), open source libraries, and other digital infrastructure. They also take …","url":["https://arxiv.org/pdf/2303.11074"]}
-{"year":"2023","title":"Generative AI Considered Harmful","authors":["JE Fischer - 2023"],"snippet":"The recent months have seen an explosion of interest, hype, and concern about generative AI, driven by the release of ChatGPT. In this article I seek to explicate some potential and actual harms of the engineering and use of generative AI such …","url":["https://www.cs.nott.ac.uk/~pszjf1/papers/Fischer_CUI23.pdf"]}
-{"year":"2023","title":"Generative AI for Medical Imaging: extending the MONAI Framework","authors":["WHL Pinaya, MS Graham, E Kerfoot, PD Tudosiu… - arXiv preprint arXiv …, 2023"],"snippet":"… -hungry, they have thrived in fields with large publicly available datasets, such as computer vision, with datasets like ImageNet [8] and LAION [43], as well as natural language processing (with access to large textual corpora, like the Wikipedia Text …","url":["https://arxiv.org/pdf/2307.15208"]}
-{"year":"2023","title":"Generative AI for Semantic Communication: Architecture, Challenges, and Outlook","authors":["L Xia, Y Sun, C Liang, L Zhang, MA Imran, D Niyato - arXiv preprint arXiv:2308.15483, 2023"],"snippet":"… Through pretraining on large datasets (like Wikipedia and Common Crawl) and fine-tuning on user data (to be more personalized and customized), GPT-Neo is capable to be directly installed into TDs to precisely extract keywords of source …","url":["https://arxiv.org/pdf/2308.15483"]}
-{"year":"2023","title":"Generative AI in Academic Writing, Ethical Recommendations","authors":["C Forrester, K Boothe"],"snippet":"As the use of Artificial Intelligence (AI) tools such as Generative Pre-trained Transformers (GPTs) becomes more prevalent in academic writing, there are growing concerns about the ethical implications of their use. This article addresses …","url":["https://www.researchgate.net/profile/Clive-Forrester/publication/369858017_Generative_AI_in_Academic_Writing_Ethical_Recommendations/links/64c27798cda2775c03c9d0a2/Generative-AI-in-Academic-Writing-Ethical-Recommendations.pdf"]}
-{"year":"2023","title":"Generative approach for gender-rewriting task with ArabicT5","authors":["S Alrowili, K Vijay-Shanker - Proceedings of the The Seventh Arabic Natural …, 2022"],"snippet":"… 2021) is a multilingual variant of T5, which was pre-trained on the new Common Crawl-based dataset that consists of 6.3T tokens covering 101 languages. The mT5 model also uses a large vocabulary file that consists of 250K tokens. …","url":["https://aclanthology.org/2022.wanlp-1.55.pdf"]}
-{"year":"2023","title":"Generative Artificial Intelligence through ChatGPT and Other Large Language Models in Ophthalmology: Clinical Applications and Challenges","authors":["TF Tan, AJ Thirunavukarasu, JP Campbell, PA Keane… - Ophthalmology Science"],"snippet":"The rapid progress of large language models (LLMs) driving generative artificial intelligence applications heralds the potential of opportunities in healthcare. We conducted a review up to April 2023 on Google Scholar, Embase, MEDLINE, and …","url":["https://www.ophthalmologyscience.org/article/S2666-9145(23)00126-4/fulltext"]}
-{"year":"2023","title":"Generative Artificial Intelligence: A Double-Edged Sword","authors":["K Kuck - 2023 World Engineering Education Forum-Global …, 2023"],"snippet":"… Stable Diffusion was trained with three massive image datasets collected by the nonprofit LAION, which built their datasets from CommonCrawl, another nonprofit that scrapes through the internet monthly and releases datasets of what they …","url":["https://ieeexplore.ieee.org/abstract/document/10343638/"]}
-{"year":"2023","title":"Generative Artificial Intelligence: Fundamentals","authors":["JM Corchado, S López, R Garcia, P Chamoso - ADCAIJ: Advances in Distributed …, 2023"],"snippet":"Generative language models have witnessed substantial traction, notably with the introduction of refined models aimed at more coherent user-AI interactions—principally conversational models. The epitome of this public attention has arguably been the …","url":["https://revistas.usal.es/cinco/index.php/2255-2863/article/download/31704/29998"]}
-{"year":"2023","title":"Generative Benchmark Creation for Table Union Search","authors":["K Pal, A Khatiwada, R Shraga, RJ Miller - arXiv preprint arXiv:2308.03883, 2023"],"snippet":"Data management has traditionally relied on synthetic data generators to generate structured benchmarks, like the TPC suite, where we can control important parameters like data size and its distribution precisely. These benchmarks were …","url":["https://arxiv.org/pdf/2308.03883"]}
-{"year":"2023","title":"Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations By admin 6 Comments","authors":["JA Goldstein, G Sastry, M Musser, R DiResta… - 2023"],"snippet":"In recent years, artificial intelligence (AI) systems have significantly improved and their capabilities have expanded. In particular, AI systems called “generative models” have made great progress in automated content creation, such as images generated …","url":["https://your-restaurant-ai.com/generative-language-models-and-automated-influence-operations-emerging-threats-and-potential-mitigations/"]}
-{"year":"2023","title":"Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations","authors":["JA Goldstein, G Sastry, M Musser, R DiResta… - arXiv preprint arXiv …, 2023"],"snippet":"Generative language models have improved drastically, and can now produce realistic text outputs that are difficult to distinguish from human-written content. For malicious actors, these language models bring the promise of automating the …","url":["https://arxiv.org/pdf/2301.04246"]}
-{"year":"2023","title":"Generative Language Models Exhibit Social Identity Biases","authors":["T Hu, Y Kyrychenko, S Rathje, N Collier… - arXiv preprint arXiv …, 2023"],"snippet":"The surge in popularity of large language models has given rise to concerns about biases that these models could learn from humans. In this study, we investigate whether ingroup solidarity and outgroup hostility, fundamental social biases known …","url":["https://arxiv.org/pdf/2310.15819"]}
-{"year":"2023","title":"Generative Language Models for Automated Programming Feedback","authors":["L Hedberg Segeholm, E Gustafsson - 2023"],"snippet":"In recent years, Generative Language Models have exploded into the mainstream with household names like BERT and ChatGPT, proving that text generation could have the potential to solve a variety of tasks. As the number of students enrolled into …","url":["https://www.diva-portal.org/smash/get/diva2:1784396/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Generative Pre-trained Transformer: A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions","authors":["G Yenduri, G Srivastava, PKR Maddikunta, RH Jhaveri… - arXiv preprint arXiv …, 2023"],"snippet":"… 500 billion words called ”Common Crawl” that was gathered from a sizable content archive and the internet [30]. Its other noteworthy and unexpected capability is its ability to carry out basic mathematical operations, write bits of code, and carry …","url":["https://arxiv.org/pdf/2305.10435"]}
-{"year":"2023","title":"Generative Pretraining in Multimodality","authors":["Q Sun, Q Yu, Y Cui, F Zhang, X Zhang, Y Wang, H Gao… - arXiv preprint arXiv …, 2023"],"snippet":"We present Emu, a Transformer-based multimodal foundation model, which can seamlessly generate images and texts in multimodal context. This omnivore model can take in any single-modality or multimodal data input indiscriminately (eg …","url":["https://arxiv.org/pdf/2307.05222"]}
-{"year":"2023","title":"Geoparsing at Web-scale-Challenges and Opportunities","authors":["SM Farzana, T Hecking - 2023"],"snippet":"The increasing amount of web data being generated and stored along with geographic information is of great importance to enrich future search applications in science, news, economics, etc.. In addition to location information provided by users …","url":["https://ceur-ws.org/Vol-3385/paper6.pdf"]}
-{"year":"2023","title":"Geopolitical Forecasting Analysis of the Russia-Ukraine War Using the Expert's Survey, Predictioneer's Game and GPT-3","authors":["K Kalinin - Predictioneer's Game and GPT-3 (April 8, 2023), 2023"],"snippet":"The Russia-Ukraine war that began on February 24th has resulted in significant geopolitical upheaval, sending shockwaves that reverberated around the globe. This extended and highly destructive war continues to rage on without any apparent …","url":["https://kirillkalinin.com/files/paper_forecasting.pdf"]}
-{"year":"2023","title":"German Compounds in Transformer Models","authors":["K Neumannová - 2023"],"snippet":"German is known for its highly productive word formation processes, particularly in the area of compounding and derivation. In this thesis, we focus on German nominal compounds and their representation in machine translation (MT) outputs. Despite …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/181571/120445862.pdf?sequence=1"]}
-{"year":"2023","title":"German Question Tags: A Computational Analysis","authors":["Y Clausen - Proceedings http://ceur-ws. org ISSN, 2023"],"snippet":"The German language exhibits a range of question tags that can typically, but not always, be substituted for one another. Moreover, the same words can have other meanings while occurring in the sentence-昀椀 nal position. The tags’ felicity …","url":["https://ceur-ws.org/Vol-3558/paper5269.pdf"]}
-{"year":"2023","title":"GERNERMED++: Semantic annotation in German medical NLP through transfer-learning, translation and word alignment","authors":["J Frei, L Frei-Stuber, F Kramer - Journal of Biomedical Informatics, 2023"],"snippet":"We present a statistical model, GERNERMED++, for German medical natural language processing trained for named entity recognition (NER) as an open, publicly available model. We demonstrate the effectiveness of combining multiple …","url":["https://www.sciencedirect.com/science/article/pii/S1532046423002344"]}
-{"year":"2023","title":"Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs","authors":["F Kang, HA Just, Y Sun, H Jahagirdar, Y Zhang, R Du…"],"snippet":"This work focuses on leveraging and selecting from vast, unlabeled, open data to pre-fine-tune a pre-trained language model. The goal is to minimize the need for costly domain-specific data for subsequent fine-tuning while achieving desired performance levels …","url":["https://neurips2023-enlsp.github.io/papers/paper_35.pdf"]}
-{"year":"2023","title":"GetPt: Graph-enhanced General Table Pre-training with Alternate Attention Network","authors":["R Jia, H Guo, X Jin, C Yan, L Du, X Ma, T Stankovic… - Proceedings of the 29th …, 2023"],"snippet":"… However, the dataset mainly contains small and medium size tables [16] from the Common Crawl, and we observe that the tables have a relatively simple structure. Additionally, the dataset only contains 386 samples, leading to high variance in its …","url":["https://dl.acm.org/doi/abs/10.1145/3580305.3599366"]}
-{"year":"2023","title":"GIO: Gradient Information Optimization for Training Dataset Selection","authors":["D Everaert, C Potts - arXiv preprint arXiv:2306.11670, 2023"],"snippet":"… [4] develop a heuristic method to filter CommonCrawl based on a trained classifier’s probability that datapoints are high quality. Similarly, … an analysis of undesirable content in the Common Crawl corpus. In Proceedings of the 59th Annual Meeting of …","url":["https://arxiv.org/pdf/2306.11670"]}
-{"year":"2023","title":"GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks","authors":["S Gupta, C Rosenbaum, ER Elenberg - arXiv preprint arXiv:2311.09606, 2023"],"snippet":"Large language models (LLMs) have the ability to perform in-context learning (ICL) of new tasks by conditioning on prompts comprising a few task examples. This work studies the problem of selecting the best examples given a candidate pool to …","url":["https://arxiv.org/pdf/2311.09606"]}
-{"year":"2023","title":"GiusBERTo: Italy's AI-Based Judicial Transformation: A Teaching Case","authors":["P Datta, BJ Zahn, L Attias, G Salierno, R Bertè… - Communications of the …, 2023"],"snippet":"In an age when open access to law enforcement files and judicial documents can erode individual privacy and confidentiality, miscreants can abuse this open access to personal information for blackmail, misinformation, and even social engineering …","url":["https://aisel.aisnet.org/cais/vol53/iss1/33/"]}
-{"year":"2023","title":"Gloss Alignment using Word Embeddings","authors":["H Walsh, OM Sincan, B Saunders, R Bowden - 2023 IEEE International Conference …, 2023"],"snippet":"… The models are trained on the Common Crawl and Wikipedia datasets and have an output dimension of 300. For the following experiments we use the English implementation when testing our approach on the BOBSL dataset and the German …","url":["https://ieeexplore.ieee.org/abstract/document/10193013/"]}
-{"year":"2023","title":"GlotScript: A Resource and Tool for Low Resource Writing System Identification","authors":["AH Kargaran, F Yvon, H Schütze - arXiv preprint arXiv:2309.13320, 2023"],"snippet":"We present GlotScript, an open resource and tool for low resource writing system identification. GlotScript-R is a resource that provides the attested writing systems for more than 7,000 languages. It is compiled by aggregating information from existing …","url":["https://arxiv.org/pdf/2309.13320"]}
-{"year":"2023","title":"GMNLP at SemEval-2023 Task 12: Sentiment Analysis with Phylogeny-Based Adapters","authors":["MMI Alam, R Xie, F Faisal, A Anastasopoulos - arXiv preprint arXiv:2304.12979, 2023"],"snippet":"This report describes GMU's sentiment analysis system for the SemEval-2023 shared task AfriSenti-SemEval. We participated in all three sub-tasks: Monolingual, Multilingual, and Zero-Shot. Our approach uses models initialized with AfroXLMR-large …","url":["https://arxiv.org/pdf/2304.12979"]}
-{"year":"2023","title":"GNN-based retrieval and recommadation system: A semantic enhenced graph model","authors":["L Wang, X Li, H Zhang, Y Dai, S Zhang - 2022 IEEE 5th Advanced Information …, 2022"],"snippet":"As a general method that captures knowledge from relation, graph modeling has been widely used in many fields including recommendation in Internet applications. A typical graph based system must be provided with a nodes and edges. To get …","url":["https://ieeexplore.ieee.org/abstract/document/10019945/"]}
-{"year":"2023","title":"Google Bard Artificial Intelligence versus the 2022 Self-Assessment Study Program for Urology","authors":["LM Huynh, BT Bonebrake, K Schultis, A Quach… - Urology Practice, 2023"],"snippet":"… While Bard’s training dataset has been largely undisclosed by its Google developers, a 2022 paper discussing the underlying LaMDA model [5] found its training set composition to be 50% from online public forums, 12.5% from Wikipedia …","url":["https://www.auajournals.org/doi/abs/10.1097/UPJ.0000000000000453"]}
-{"year":"2023","title":"GPT (Generative Pre-trained Transformer)–A Comprehensive Review on Enabling Technologies, Potential Applications, Emerging Challenges, and Future Directions","authors":["G Yenduri, M Ramalingam, G Chemmalar Selvi…"],"snippet":"… It is taught using a corpus of 500 billion words called ”Common Crawl” that was gathered from a sizable content archive and the internet [26]. Its other noteworthy and unexpected capability is its ability to carry out basic mathematical operations …","url":["https://www.researchgate.net/profile/Gokul-Yenduri/publication/370869544_Generative_Pre-trained_Transformer_A_Comprehensive_Review_on_Enabling_Technologies_Potential_Applications_Emerging_Challenges_and_Future_Directions/links/646b4adf2d0a4c58bef111cd/Generative-Pre-trained-Transformer-A-Comprehensive-Review-on-Enabling-Technologies-Potential-Applications-Emerging-Challenges-and-Future-Directions.pdf"]}
-{"year":"2023","title":"GPT is an effective tool for multilingual psychological text analysis","authors":["S Rathje, DM Mirea, I Sucholutsky, R Marjieh… - 2023"],"snippet":"… Our analyses so far have focused on widely-spoken languages that are relatively highly represented in CommonCrawl – a large repository … eight of these languages, some of which had less than 20 million speakers (Table 1) and relatively little …","url":["https://psyarxiv.com/sekf5/download?format=pdf"]}
-{"year":"2023","title":"GPT takes the Bar Exam","authors":["MJB IIa, DM Katza"],"snippet":"… As reported in [19], OpenAI’s models are trained on a combination of curated CommonCrawl data and high-quality reference data that, if we consider The Pile V1 as reference [24], may have included some material from public legal sources …","url":["https://smallake.kr/wp-content/uploads/2023/01/SSRN-id4314839.pdf"]}
-{"year":"2023","title":"GPT-3 for Education; Benefits and Concerns","authors":["MIZ Abidin, A Alkhalidi, F Mustaffa - … Conference on Creative Multimedia 2023 (ICCM …, 2023"],"snippet":"… It was trained on publicly available data, including the Common Crawl dataset, which contains a vast amount of text from the web. GPT-3 excels in language translation, question answering, and human-like text generation. Compared to …","url":["https://www.atlantis-press.com/article/125994266.pdf"]}
-{"year":"2023","title":"GPT-3 Models are Few-Shot Financial Reasoners","authors":["RS de Padua, I Qureshi, MU Karakaplan - arXiv preprint arXiv:2307.13617, 2023"],"snippet":"… GPT-3 is a 175B parameter autoregressive language model trained on 45TB from CommonCrawl, Wikipedia and others, showing state-of-the-art performance on many NLP-related tasks. Often these tasks can be performed by providing a relevant …","url":["https://arxiv.org/pdf/2307.13617"]}
-{"year":"2023","title":"GPT-3 vs Object Oriented Programming Assignments: An Experience Report","authors":["BP Cipriano, P Alves - Proceedings of the 2023 Conference on Innovation …, 2023"],"snippet":"… We were also curious about GPT’s capacity to reply to prompts written in a language other than English, since it gathers information from the Common Crawl dataset which is primarily comprised of English content (46% as of 2022) [9]. All of …","url":["https://dl.acm.org/doi/pdf/10.1145/3587102.3588814"]}
-{"year":"2023","title":"GPT-4 can pass the Korean National Licensing Examination for Korean Medicine Doctors","authors":["D Jang, TR Yun, CY Lee, YK Kwon, CE Kim - PLOS Digital Health, 2023"],"snippet":"… For example, the pre-training dataset for GPT-3, a model released in 2020 that GPT-3.5 is based on and the technical details have been officially reported, is mainly derived from a modified version of Common Crawl [19] in which English-based data …","url":["https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000416"]}
-{"year":"2023","title":"GPT-4 For Developers","authors":["O Campesato - 2024"],"snippet":"This resource is designed to bridge the gap between theoretical understanding and practical application, making it a useful tool for software developers, data scientists, AI researchers, and tech enthusiasts interested in harnessing the power of GPT-4 in …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=98_qEAAAQBAJ&oi=fnd&pg=PP13&dq=commoncrawl&ots=kALFZg_NdN&sig=ZBrEFhqJsDOAfqb1zDuAUVwbpPY"]}
-{"year":"2023","title":"Gradient Ascent Post-training Enhances Language Model Generalization","authors":["D Yoon, J Jang, S Kim, M Seo - arXiv preprint arXiv:2306.07052, 2023"],"snippet":"… We consider OPT LMs to be familiar (in-domain) to Common Crawl, as it was included in their pretraining corpora. As OPT LMs were not explicitly trained on the Github corpora we consider OPT to be unfamiliar (out-ofdistribution) with Github …","url":["https://arxiv.org/pdf/2306.07052"]}
-{"year":"2023","title":"Grammatical Error Correction with byte-level language models","authors":["M Jentoft - 2023"],"snippet":"… It is pre-trained on over a hundred languages on the multilingual dataset named mC4: multilingual Colossal Cleaned Common Crawl. The training of the model mirrors that of t5 closely, but differs both in that is was trained on a multilingual …","url":["https://www.duo.uio.no/bitstream/handle/10852/103885/5/jentoft_masteroppgave_2023.pdf"]}
-{"year":"2023","title":"GreekBART: The First Pretrained Greek Sequence-to-Sequence Model","authors":["I Evdaimon, H Abdine, C Xypolopoulos, S Outsios… - arXiv preprint arXiv …, 2023"],"snippet":"The era of transfer learning has revolutionized the fields of Computer Vision and Natural Language Processing, bringing powerful pretrained models with exceptional performance across a variety of tasks. Specifically, Natural Language Processing …","url":["https://arxiv.org/pdf/2304.00869"]}
-{"year":"2023","title":"GreekT5: A Series of Greek Sequence-to-Sequence Models for News Summarization","authors":["N Giarelis, C Mastrokostas, N Karacapilidis - arXiv preprint arXiv:2311.07767, 2023"],"snippet":"Text summarization (TS) is a natural language processing (NLP) subtask pertaining to the automatic formulation of a concise and coherent summary that covers the major concepts and topics from one or multiple documents. Recent advancements in …","url":["https://arxiv.org/pdf/2311.07767"]}
-{"year":"2023","title":"GRI: Graph-based Relative Isomorphism of Word Embedding Spaces","authors":["MA Ali, Y Hu, J Qin, D Wang - arXiv preprint arXiv:2310.12360, 2023"],"snippet":"… In order to validate these claims for GRI, we re-run the experiments using target embeddings trained on 33.8 million lines of web-crawl data from the English Common Crawl data. The embeddings for the source languages (“bn\", “uk\" and “ta\") …","url":["https://arxiv.org/pdf/2310.12360"]}
-{"year":"2023","title":"GRILLBot-v2: Generative Models for Multi-Modal Task-Oriented Assistance","authors":["S Fischer, N Tecklenburg, P Zubel, E Kupcova…"],"snippet":"… Figure 2 shows how our pipeline converts raw textual task sources (Common Crawl, Wikipedia, WikiHow) into an augmented TaskGraph corpus using LLMs, external knowledge sources, and multi-modal content. Specifically for Common …","url":["https://assets.amazon.science/f3/75/cbd31079434eaf0c171a1ae0c8a8/grill-tb2-final-2023.pdf"]}
-{"year":"2023","title":"GTCOM and DLUT's Neural Machine Translation Systems for WMT23","authors":["H Zong, C Bei, C Yuan, W Chen, H Liu, D Huang"],"snippet":"This paper presents the submission by Global Tone Communication Co., Ltd. and Dalian Univeristy of Technology for the WMT23 shared general Machine Translation (MT) task at the Conference on Empirical Methods in Natural Language Processing (EMNLP) …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.20.pdf"]}
-{"year":"2023","title":"Hallucinating Machines: Exploring the ethical implications of generative language models","authors":["M Hill - 2023"],"snippet":"… OpenAI utilised a filtered version of the Common Crawl dataset as the foundation of the training dataset for GPT-3 (Brown et al., 2020). The Common Crawl dataset comprises petabytes of web data collected since 2008 (So You’re Ready to Get …","url":["https://openaccess.wgtn.ac.nz/articles/thesis/Hallucinating_Machines_Exploring_the_ethical_implications_of_generative_language_models/24180456/1/files/42424206.pdf"]}
-{"year":"2023","title":"Hallucinations in Large Multilingual Translation Models","authors":["NM Guerreiro, D Alves, J Waldendorf, B Haddow… - arXiv preprint arXiv …, 2023"],"snippet":"Large-scale multilingual machine translation systems have demonstrated remarkable ability to translate directly between numerous languages, making them increasingly appealing for real-world applications. However, when deployed in the …","url":["https://arxiv.org/pdf/2303.16104"]}
-{"year":"2023","title":"HARMONY@ DravidianLangTech: Transformer-based Ensemble Learning for Abusive Comment Detection","authors":["A Murugappan, LP RS, M Deivamani - Proceedings of the Third Workshop on …, 2023"],"snippet":"Millions of posts and comments are created every minute as a result of the widespread use of social media and easy access to the internet. It is essential to create an inclusive environment and forbid the use of abusive language against any …","url":["https://aclanthology.org/2023.dravidianlangtech-1.21.pdf"]}
-{"year":"2023","title":"Hate Speech Detection in Hindi","authors":["PP Bansod - 2023"],"snippet":"Social media is a great place to share one’s thoughts and to express oneself. Very often the same social media platforms become a means for spewing hatred. The large amount of data being shared on these platforms make it difficult to moderate …","url":["https://scholarworks.sjsu.edu/cgi/viewcontent.cgi?article=2265&context=etd_projects"]}
-{"year":"2023","title":"Hate speech: semi-automatic recognition in Slovak texts","authors":["L HORNÍKOVÁ"],"snippet":"… This could be caused by the data on which was the FastText model trained (texts from Wikipedia – which primarily represent scientific language style – and Common Crawl). Hate speech is likely underrepresented in the training data; perhaps the data …","url":["https://is.muni.cz/th/ncomq/Hate_speech_semi-automatic_recognition_in_Slovak_texts.pdf"]}
-{"year":"2023","title":"HatEmoTweet: Low Level Emotion Classifications and Spatio-Temporal Trends of Hate and Offensive COVID-19 Tweets","authors":["A Adesokan, S Madria, L Nguyen - 2023"],"snippet":"Social media platforms (like Twitter) positively and negatively impact users in diverse societies; one of Twitter’s negative effects is the usage of hate and offensive language. Hate speech fosters prejudice; it also harms the vulnerable. There are …","url":["https://www.researchsquare.com/article/rs-2696349/latest.pdf"]}
-{"year":"2023","title":"HC3: A Suite of Test Collections for CLIR Evaluation over Informal Text","authors":["D Lawrie, J Mayfield, DW Oard, E Yang, S Nair… - Proceedings of the 46th …, 2023"],"snippet":"While there are many test collections for Cross-Language Information Retrieval (CLIR), none of the large public test collections focus on short informal text documents. This paper introduces a new pair of CLIR test collections with millions of Chinese or …","url":["https://user.eng.umd.edu/~oard/pdf/sigir23-hc3.pdf"]}
-{"year":"2023","title":"HeRo: RoBERTa and Longformer Hebrew Language Models","authors":["V Shalumov, H Haskey - arXiv preprint arXiv:2304.11077, 2023"],"snippet":"In this paper, we fill in an existing gap in resources available to the Hebrew NLP community by providing it with the largest so far pre-train dataset HeDC4, a state-of-the-art pre-trained language model HeRo for standard length inputs and an efficient …","url":["https://arxiv.org/pdf/2304.11077"]}
-{"year":"2023","title":"HHLD: Hateful posts Identification in Hindi Language leveraging multi task learning","authors":["P Kapil, G Kumari, A Ekbal, S Pal, A Chatterjee… - IEEE Access, 2023"],"snippet":"… 2.5 TB of common crawl data in 100 languages are used to train it. It outperforms M-BERT across cross-lingual classification, especially for low-resource languages. To apply sub-word tokenization on the raw input, sentence piece [50] with unigram …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10243565.pdf"]}
-{"year":"2023","title":"Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus","authors":["A Piergentili, B Savoldi, D Fucci, M Negri, L Bentivogli - arXiv preprint arXiv …, 2023"],"snippet":"Gender inequality is embedded in our communication practices and perpetuated in translation technologies. This becomes particularly apparent when translating into grammatical gender languages, where machine translation (MT) often defaults to …","url":["https://arxiv.org/pdf/2310.05294"]}
-{"year":"2023","title":"Hierarchical Representations From Large Mathematical Corpora","authors":["L Berlioz - 2023"],"snippet":"… Examples of common corpora used in NLP include Project Gutenberg1, which is an online library of more that 60,000 free ebooks [83]; the Common Crawl data set2 is a large collection of data from internet websites. And, of particular importance to …","url":["http://d-scholarship.pitt.edu/43650/1/Berlioz%20-%20PhD%20-%20ETD%20-%20v1.3.pdf"]}
-{"year":"2023","title":"High-Efficiency Device-Cloud Collaborative Transformer Model","authors":["P Jiang, K Xin, C Li, Y Zhou - Proceedings of the IEEE/CVF Conference on Computer …, 2023"],"snippet":"Natural Language Processing (NLP) experts have had significant success with unsupervised language pre-training techniques. However, compared to typical NLP models, modern self-attention models require far more computational and memory …","url":["https://openaccess.thecvf.com/content/CVPR2023W/MobileAI/papers/Jiang_High-Efficiency_Device-Cloud_Collaborative_Transformer_Model_CVPRW_2023_paper.pdf"]}
-{"year":"2023","title":"HODI at EVALITA 2023: Overview of the first Shared Task on Homotransphobia Detection in Italian","authors":["D Nozza, AT Cignarella, G Damo, T Caselli, V Patti - Proceedings of EVALITA, 2023"],"snippet":"HODI is a new shared task for the automatic detection of homotransphobia in Italian presented at EVALITA 2023. The challenge is organized into two subtasks: Subtask A focuses on the binary textual classification of homotransphobic tweets, while …","url":["https://ceur-ws.org/Vol-3473/paper26.pdf"]}
-{"year":"2023","title":"Home Evolving Standards of Care Demystifying AI: Current Insights on Artificial Intelligence in Thoracic Oncology","authors":["RH Mak, F Haugg"],"snippet":"… ChatGPT was trained on a diverse mix of datasets, including a dataset known as Common Crawl,4 which alone contains nearly a trillion words before filtering. It is worth noting that this model learns in an unsupervised manner—it does not rely on …","url":["https://www.ilcn.org/demystifying-ai-current-insights-on-artificial-intelligence-in-thoracic-oncology/"]}
-{"year":"2023","title":"HOMOCHAR: A novel adversarial attack framework for exposing the vulnerability of text based neural sentiment classifiers","authors":["A Bajaj, DK Vishwakarma - Engineering Applications of Artificial Intelligence, 2023"],"snippet":"… In addition, RoBERTa had also been trained on datasets which include CC-News (Common Crawl-News), Open WebText, and others. These datasets have a combined size of about 160 GB. RoBERTa used a batch size of 8000 with 300,000 …","url":["https://www.sciencedirect.com/science/article/pii/S0952197623009995"]}
-{"year":"2023","title":"Homophobia and transphobia detection for low-resourced languages in social media comments","authors":["PK Kumaresan, R Ponnusamy, R Priyadharshini… - Natural Language …, 2023"],"snippet":"… It’sa multilingual language model with 2.5 TB of filtered Common Crawl data that was trained. XLM-RoBERTa was fine-tuned for evaluation and inference on a range of downstream tasks using Wikipedia data in over 100 languages. XLM-RoBERTa …","url":["https://www.sciencedirect.com/science/article/pii/S2949719123000389"]}
-{"year":"2023","title":"Honey, I Shrunk the Language: Language Model Behavior at Reduced Scale","authors":["V Deshpande, D Pechi, S Thatte, V Lialin, A Rumshisky - arXiv preprint arXiv …, 2023"],"snippet":"In recent years, language models have drastically grown in size, and the abilities of these models have been shown to improve with scale. The majority of recent scaling laws studies focused on high-compute high-parameter count settings, leaving the …","url":["https://arxiv.org/pdf/2305.17266"]}
-{"year":"2023","title":"HOW CHATGPT CAN BE USED FOR A CONTRACT DRAFTING CLASS","authors":["BL Fernandez, K Hardy - 2023"],"snippet":"… • The Common Crawl dataset (https://commoncrawl.org), …","url":["https://scholarship.law.wm.edu/cgi/viewcontent.cgi?article=1014&context=incorporating_chatgpt"]}
-{"year":"2023","title":"How Deep Contextualized Representation and Attention Mechanism Justifies Explainable Cross-lingual Sentiment Analysis","authors":["R Ghasemi, S Momtazi - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"… It has been pre-trained on the CommonCrawl Corpus, containing 100 languages with 2.5TB of data. Considering the advantages of LSTM models in capturing words’ sequential behavior, we build an LSTM-based classiier on the top of XLM-RoBERTa …","url":["https://dl.acm.org/doi/pdf/10.1145/3626094"]}
-{"year":"2023","title":"How Does Calibration Data Affect the Post-training Pruning and Quantization of Large Language Models?","authors":["M Williams, N Aletras - arXiv preprint arXiv:2311.09755, 2023"],"snippet":"… This consists of English web text from Common Crawl, filtered with heuristics that form a “… This mainly consists of web text (Common Crawl and C4), in addition to high-quality sources … was created from stringent filtering and deduplication of …","url":["https://arxiv.org/pdf/2311.09755"]}
-{"year":"2023","title":"How far can we get in creating a digital replica of a philosopher?","authors":["A Strasser, E Schwitzgebel, M Crosby - 2023"],"snippet":"Can we build machines with which we can have interesting conversations? Observing the new optimism of AI regarding deep learning and new language models, we set ourselves an ambitious goal: We want to find out how far we can get …","url":["https://philpapers.org/archive/STRHFC.pdf"]}
-{"year":"2023","title":"How Language-Dependent is Emotion Detection? Evidence from Multilingual BERT","authors":["L De Bruyne, P Singh, O De Clercq, E Lefever, V Hoste - 2nd Workshop on Multi …, 2022"],"snippet":"As emotion analysis in text has gained a lot of attention in the field of natural language processing, differences in emotion expression across languages could have consequences for how emotion detection models work. We evaluate the …","url":["https://biblio.ugent.be/publication/01GPDJHVE9ESH8GJ8ABEA50S2J/file/01GPDJR6BDK37SDZ15VTQS7Z81"]}
-{"year":"2023","title":"How optimal transport can tackle gender biases in multi-class neural-network classifiers for job recommendations?","authors":["F Jourdan, TT Kaninku, N Asher, JM Loubes, L Risser - arXiv preprint arXiv …, 2023"],"snippet":"… Note that to build this dataset, its authors used Common Crawl and identified online biographies written in English. Then, they filtered the biographies starting with a name-like pattern followed by the string “is a(n) (xxx) title,” where title is an …","url":["https://arxiv.org/pdf/2302.14063"]}
-{"year":"2023","title":"How Prevalent is Gender Bias in ChatGPT?--Exploring German and English ChatGPT Responses","authors":["S Urchs, V Thurner, M Aßenmacher, C Heumann… - arXiv preprint arXiv …, 2023"],"snippet":"… It is unclear from the documentation on which data the system was trained exactly, but since it includes training data from CommonCrawl4 it is likely to reflect many of the biases and stereotypes common to internet content. Furthermore, the model is …","url":["https://arxiv.org/pdf/2310.03031"]}
-{"year":"2023","title":"How to deploy security mechanisms online (consistently)","authors":["S Roth - 2023"],"snippet":"To mitigate a myriad of Web attacks, modern browsers support client-side security policies shipped through HTTP response headers. To enforce these policies, the operator can set response headers that the server then communicates to the client …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/35991/1/thesis.pdf"]}
-{"year":"2023","title":"How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases","authors":["A Mueller, T Linzen - arXiv preprint arXiv:2305.19905, 2023"],"snippet":"… All of these models are trained on approximately 34B words from the Colossal Cleaned Common Crawl (C4) web text corpus. … , which we included in the previous experiment, we also pre-train models on the Colossal Cleaned Common …","url":["https://arxiv.org/pdf/2305.19905"]}
-{"year":"2023","title":"How User Language Affects Conflict Fatality Estimates in ChatGPT","authors":["D Kazenwadel, CV Steinert - arXiv preprint arXiv:2308.00072, 2023"],"snippet":"OpenAI's ChatGPT language model has gained popularity as a powerful tool for complex problem-solving and information retrieval. However, concerns arise about the reproduction of biases present in the language-specific training data. In this study …","url":["https://arxiv.org/pdf/2308.00072"]}
-{"year":"2023","title":"How well do language models understand grammar?: a case study on Japanese","authors":["GC Breul - 2022"],"snippet":"Modern attention-based language models such as BERT and GPT have been shown to outperform previous state-of-the-art models on many NLP tasks. This performance implies a level of understanding of grammatical structures. This work …","url":["http://elib.uni-stuttgart.de/bitstream/11682/12803/1/Masterarbeit%20Gerhard%20Breul.pdf"]}
-{"year":"2023","title":"HPLT: High Performance Language Technologies","authors":["M Aulamo, N Bogoychev, S Ji, G Nail… - Proceedings of the 24th …, 2023"],"snippet":"We describe the High Performance Language Technologies project (HPLT), a 3-year EU-funded project started in September 2022. HPLT will build a space combining petabytes of natural language data with large-scale model training. It will derive …","url":["https://aclanthology.org/2023.eamt-1.61.pdf"]}
-{"year":"2023","title":"HTTP header based phishing attack detection using machine learning","authors":["S Shukla, M Misra, G Varshney - Transactions on Emerging Telecommunications …"],"snippet":"In the past, many techniques like blacklisting/whitelisting, third‐party, search engine, visual similarity, heuristic, URL features, and website content were used for anti‐phishing. Search engine‐based, third‐party assisted tools and blacklist/whitelist fail to identify …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/ett.4872"]}
-{"year":"2023","title":"HUAWEI NOAH'S ARK LAB AT TREC NEUCLIR 2022","authors":["E Kamalloo, D Alfonso-Hermelo, M Rezagholizadeh"],"snippet":"… Both corpora are collected from the Common Crawl news collection. To identify documents in Chinese, Persian, and Russian, the language of documents were determined via automated language identification. HC4 comprises documents within …","url":["https://trec.nist.gov/pubs/trec31/papers/huaweimtl.N.pdf"]}
-{"year":"2023","title":"HULAT at SemEval-2023 Task 10: Data augmentation for pre-trained transformers applied to the detection of sexism in social media","authors":["I Segura-Bedmar - arXiv preprint arXiv:2302.12840, 2023"],"snippet":"This paper describes our participation in SemEval-2023 Task 10, whose goal is the detection of sexism in social media. We explore some of the most popular transformer models such as BERT, DistilBERT, RoBERTa, and XLNet. We also study …","url":["https://arxiv.org/pdf/2302.12840"]}
-{"year":"2023","title":"HULAT at SemEval-2023 Task 9: Data augmentation for pre-trained transformers applied to Multilingual Tweet Intimacy Analysis","authors":["I Segura-Bedmar - arXiv preprint arXiv:2302.12794, 2023"],"snippet":"This paper describes our participation in SemEval-2023 Task 9, Intimacy Analysis of Multilingual Tweets. We fine-tune some of the most popular transformer models with the training dataset and synthetic data generated by different data augmentation …","url":["https://arxiv.org/pdf/2302.12794"]}
-{"year":"2023","title":"Human intelligence-based metaverse for co-learning of students and smart machines","authors":["CS Lee, MH Wang, M Reformat, SH Huang - Journal of Ambient Intelligence and …, 2023"],"snippet":"This paper proposes a Human Intelligence (HI)-based Computational Intelligence (CI) and Artificial Intelligence (AI) Fuzzy Markup Language (CI&AI-FML) Metaverse as an educational environment for co-learning of students and machines. The HI-based …","url":["https://link.springer.com/article/10.1007/s12652-023-04580-2"]}
-{"year":"2023","title":"Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment","authors":["A Peña, I Serna, A Morales, J Fierrez, A Ortega… - arXiv preprint arXiv …, 2023"],"snippet":"… In the study of demographic bias in NLP technologies,4 we can cite the Common Crawl Bios dataset [31], which contains nearly 400K short biographies collected from Common Crawl. The goal of the dataset is to predict the occupation from these …","url":["https://arxiv.org/pdf/2302.10908"]}
-{"year":"2023","title":"Humanoid Robot as a Debate Partner","authors":["HS Yun, H Hübert, A Sardogan, N Pinkwart, VV Hafner… - International Conference on …, 2023"],"snippet":"In this paper, we describe our design and development process of a humanoid robot, Pepper, as a debate partner by integrating open-source, offline Generative Pre-trained Transformer models, namely GPT-J 6B and BLOOM. We used our tool flow, which …","url":["https://link.springer.com/chapter/10.1007/978-3-031-36004-6_74"]}
-{"year":"2023","title":"HunSum-1: an Abstractive Summarization Dataset for Hungarian","authors":["B Barta, D Lakatos, A Nagy, MK Nyist, J Ács - arXiv preprint arXiv:2302.00455, 2023"],"snippet":"… In Section 3 we discuss in detail how we extracted the data from CommonCrawl and performed a number of preprocessing steps to arrive at the current version of HunSum-1. We also train three baseline models on the dataset and evaluate the results both …","url":["https://arxiv.org/pdf/2302.00455"]}
-{"year":"2023","title":"HW-TSC's Neural Machine Translation System for CCMT 2023","authors":["Z Wu, Z Yu, Z Li, D Wei, Y Xie, X Chen, H Shang, J Guo… - China Conference on …, 2023"],"snippet":"This paper presents Huawei Translation Service Center (HW-TSC)’s submission to the machine translation tasks of the 19th China Conference on Machine Translation (CCMT 2023). We participate in all machine translation tasks, including five bilingual …","url":["https://link.springer.com/chapter/10.1007/978-981-99-7894-6_2"]}
-{"year":"2023","title":"HyperGraphDis: Leveraging Hypergraphs for Contextual and Social-Based Disinformation Detection","authors":["N Salamanos, P Leonidou, N Laoutaris, M Sirivianos… - 2023"],"snippet":"In light of the growing impact of disinformation on social, economic, and political landscapes, accurate and efficient identification methods are increasingly critical. This paper introduces HyperGraphDis, a novel approach for detecting disinformation …","url":["https://arxiv.org/pdf/2310.01113"]}
-{"year":"2023","title":"HYTREL: Hypergraph-enhanced Tabular Data Representation Learning","authors":["P Chen, S Sarkar, L Lausen, B Srinivasan, S Zha… - arXiv preprint arXiv …, 2023"],"snippet":"… HYTREL pretrained with tables from Wikipedia and Common Crawl could not transfer well to the medical domain PMC dataset. As for the improvement observed from the contrastive objective, the reason could be that contrastive learning that uses …","url":["https://arxiv.org/pdf/2307.08623"]}
-{"year":"2023","title":"I-WAS: a Data Augmentation Method with GPT-2 for Simile Detection","authors":["Y Chang, R Zhang, J Pu - arXiv preprint arXiv:2308.04109, 2023"],"snippet":"… For the sentence completion stage, we apply the GPT-2 [35] model, which is trained on a large corpus of novels and common crawl and has 5 billion parameters. The model uses a transformer architecture and consists of a 45-layer decoder with …","url":["https://arxiv.org/pdf/2308.04109"]}
-{"year":"2023","title":"ICON: A Linguistically-Motivated Large-Scale Benchmark Indonesian Constituency Treebank","authors":["ES Lim, WQ Leong, NT Nguyen, WM Kng, WC Tjhi… - ACM Transactions on Asian …, 2023"],"snippet":"Constituency parsing is an important task of informing how words are combined to form sentences. While constituency parsing in English has seen significant progress in the last few years, tools for constituency parsing in Indonesian remain few and far …","url":["https://dl.acm.org/doi/pdf/10.1145/3609798"]}
-{"year":"2023","title":"Identification and Correction of Grammatical Errors in Ukrainian Texts Based on Machine Learning Technology","authors":["V Lytvyn, P Pukach, V Vysotska, M Vovk, N Kholodna - Mathematics, 2023"],"snippet":"A machine learning model for correcting errors in Ukrainian texts has been developed. It was established that the neural network has the ability to correct simple sentences written in Ukrainian; however, the development of a full-fledged …","url":["https://www.mdpi.com/2128886"]}
-{"year":"2023","title":"Identifying and Eliminating CSAM in Generative ML Training Data and Models","authors":["D Thiel - 2023"],"snippet":"… Thisdataset was built by taking a snapshot of the Common Crawl5 repository, downloading images referenced in the HTML, reading the “alt” attributes of the images and using CLIP6 interrogation to discard images that did not sufficiently …","url":["https://stacks.stanford.edu/file/druid:kh752sm9123/ml_training_data_csam_report-2023-12-20.pdf"]}
-{"year":"2023","title":"Identifying and Mitigating Privacy Risks Stemming from Language Models: A Survey","authors":["V Smith, AS Shamsabadi, C Ashurst, A Weller - arXiv preprint arXiv:2310.01424, 2023"],"snippet":"Rapid advancements in language models (LMs) have led to their adoption across many sectors. Alongside the potential benefits, such models present a range of risks, including around privacy. In particular, as LMs have grown in size, the potential to …","url":["https://arxiv.org/pdf/2310.01424"]}
-{"year":"2023","title":"Identifying and predicting stereotype change in large language corpora: 72 groups, 115 years (1900–2015), and four text sources.","authors":["TES Charlesworth, N Sanjeev, ML Hatzenbuehler… - Journal of Personality and …, 2023"],"snippet":"… yearly corpus of New York Times (NYT) articles since 1990; and (d) although not diachronic or time-stamped, the most widely used of any corpus, the Common Crawl (CC), a massive corpus argued to reflect all internet text from the 2000s and before …","url":["https://psycnet.apa.org/record/2024-02028-001"]}
-{"year":"2023","title":"Identifying Duplicate Questions Leveraging Recurrent Neural Network","authors":["MB Baby, B Ankhari, M Shajalal, M Atabuzzaman… - Proceedings of the Fourth …, 2023"],"snippet":"Community Question Answering (CQA) forums are the predominant platform where the users can respond to others’ questions and share acquainted insights. The influx of new questions with linguistic expression variability and ambiguity leads to a …","url":["https://link.springer.com/chapter/10.1007/978-981-19-9483-8_28"]}
-{"year":"2023","title":"Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space","authors":["F Klubička, V Nedumpozhimana, JD Kelleher - arXiv preprint arXiv:2304.14333, 2023"],"snippet":"The goal of this paper is to learn more about how idiomatic information is structurally encoded in embeddings, using a structural probing method. We repurpose an existing English verbal multi-word expression (MWE) dataset to suit the probing …","url":["https://arxiv.org/pdf/2304.14333"]}
-{"year":"2023","title":"If I Say the Word Out Loud, It Will Be More Real","authors":["J Claus, Y Schütte"],"snippet":"… The training set for GPT-3 was a filtered version of the Common Crawl dataset, developed by training a classifier to pick out those documents most similar to the ones used in GPT-2’s training data, ie documents linked to from Reddit, plus …","url":["https://www.transcript-open.de/pdf_chapter/bis%206699/9783839466605/9783839466605-010.pdf"]}
-{"year":"2023","title":"Iimas-unam team entry: Transformers adapters for the sentiment analysis rest-mex 2023","authors":["EY Baez-Reyes, I Barrón-Jiménez, H Becerril-Pizarro… - IberLEF@ SEPLN, 2023"],"snippet":"… The transformers model we used is the \"xlm-roberta-base\" model, which is pre-trained with 2.5 TB of data filtered by CommonCrawl. And as an adapter and fine-tuned an adapter. When training a pre-trained model of Huggingface, the first thing we did …","url":["https://ceur-ws.org/Vol-3496/restmex-paper9.pdf"]}
-{"year":"2023","title":"Image Synthesis from Themes Captured in Poems using Latent Diffusion Models","authors":["M Virmani, AM Michael, M Pathak, KS Pai, VRB Prasad - 2023 2nd International …, 2023"],"snippet":"… Additionally, MUSS offers an approach that does not require labelled data and uses semantic sentence embeddings to mine paraphrase data from Common Crawl in any language. As a result, MUSS can shorten phrases in any language without …","url":["https://ieeexplore.ieee.org/abstract/document/10141274/"]}
-{"year":"2023","title":"Imitating Task and Motion Planning with Visuomotor Transformers","authors":["M Dalal, A Mandlekar, C Garrett, A Handa… - arXiv preprint arXiv …, 2023"],"snippet":"… Large models at the scale of billions of parameters, trained on massive corpi such as Common Crawl, WebText2 [2], JFT-300M [3] and LAION-5B [4], exhibit powerful capabilities. These models can write coherently [2…","url":["https://arxiv.org/pdf/2305.16309"]}
-{"year":"2023","title":"Impact and development of an Open Web Index for open web search","authors":["M Granitzer, S Voigt, NA Fathima, M Golasowski… - Journal of the Association …, 2023"],"snippet":"Web search is a crucial technology for the digital economy. Dominated by a few gatekeepers focused on commercial success, however, web publishers have to optimize their content for these gatekeepers, resulting in a closed ecosystem of …","url":["https://asistdl.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/asi.24818"]}
-{"year":"2023","title":"Impact of ChatGPT on Interdisciplinary Nursing Education and Research","authors":["H Miao, H Ahn - Asian/Pacific Island Nursing Journal, 2023"],"snippet":"… To train GPT-3, which laid the foundation for ChatGPT, the 2016-2019 Common Crawl data set [6] of 45 TB of compressed plain text was used. Nowadays the data set used for training ChatGPT consists of more than 145 million dialogues scraped …","url":["https://apinj.jmir.org/2023/1/e48136/"]}
-{"year":"2023","title":"Impact of Transformers on Multilingual Fake News Detection for Tamil and Malayalam","authors":["RILA Hariharan, M Anand Kumar - Speech and Language Technologies for Low …, 2023"],"snippet":"… XLM-RoBERTa is a multilingual RoBERTa model, an improved version of BERT, and pre-trained on 2.5 TB of filtered CommonCrawl data containing 100 languages. … They trained on monolingual data too, which are publicly available corpora from …","url":["https://link.springer.com/chapter/10.1007/978-3-031-33231-9_13"]}
-{"year":"2023","title":"Implications of the Convergence of Language and Vision Model Geometries","authors":["J Li, Y Kementchedjhieva, A Søgaard - arXiv preprint arXiv:2302.06555, 2023"],"snippet":"Large-scale pretrained language models (LMs) are said to ``lack the ability to connect [their] utterances to the world'' (Bender and Koller, 2020). If so, we would expect LM representations to be unrelated to representations in computer vision …","url":["https://arxiv.org/pdf/2302.06555"]}
-{"year":"2023","title":"Implicit information extraction from news stories","authors":["H Kydlíček - 2023"],"snippet":"… We used Common Crawl2 as a data source, as crawling live websites would be infeasible. For extraction, we developed a custom tool C’monCrawl3, which allows end-to-end extraction of Common Crawl data. We then deployed it in distributed …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/183054/130358961.pdf?sequence=1"]}
-{"year":"2023","title":"Improvements in Language Modeling, Voice Activity Detection, and Lexicon in OpenASR21 Low Resource Languages","authors":["V Gupta, G Boulianne - International Conference on Speech and Computer, 2023"],"snippet":"OpenASR21 evaluation was on 15 low resource languages and 3 case sensitive languages. During the evaluation, participants got significant reduction in word error rates (WER) with text downloaded from the internet for only the case sensitive …","url":["https://link.springer.com/chapter/10.1007/978-3-031-48312-7_6"]}
-{"year":"2023","title":"Improving accuracy of GPT-3/4 results on biomedical data using a retrieval-augmented language model","authors":["D Soong, S Sridhar, H Si, JS Wagner, ACC Sá, CY Yu… - arXiv preprint arXiv …, 2023"],"snippet":"… Popular LLMs with billions of parameters such as GPT-3 [4] , PaLM [15], OPT [16], and LLaMA [17] are typically trained on vast amounts of information collected from the Internet (eg the Common Crawl dataset [18]) and capture a diverse range of …","url":["https://arxiv.org/pdf/2305.17116"]}
-{"year":"2023","title":"Improving Bug Severity Prediction with Domain-Specific Representation Learning","authors":["Y Wei, C Zhang, T Ren - IEEE Access, 2023"],"snippet":"… Typically, these language models are trained on colossal datasets, such as Wikipedia or Common Crawl, which facilitates their understanding of the intricacies and complexities of natural language. Once trained, these models can be fine-tuned …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10131903.pdf"]}
-{"year":"2023","title":"Improving Cascaded Systems in Spoken Language Processing","authors":["Y Lu - 2023"],"snippet":"Spoken language processing encompasses a broad range of speech production and perception tasks. One of the central challenges in building spoken language systems is the lack of end-to-end training corpora. For example in spoken language …","url":["https://www.repository.cam.ac.uk/bitstream/handle/1810/348309/thesis_digital.pdf?sequence=3"]}
-{"year":"2023","title":"Improving CLIP Training with Language Rewrites","authors":["L Fan, D Krishnan, P Isola, D Katabi, Y Tian - arXiv preprint arXiv:2305.20088, 2023"],"snippet":"Contrastive Language-Image Pre-training (CLIP) stands as one of the most effective and scalable methods for training transferable vision models using paired image and text data. CLIP models are trained using contrastive loss, which typically relies …","url":["https://arxiv.org/pdf/2305.20088"]}
-{"year":"2023","title":"Improving Domain-Specific Retrieval by NLI Fine-Tuning","authors":["R Dušek, A Wawer, C Galias, L Wojciechowska - arXiv preprint arXiv:2308.03103, 2023"],"snippet":"The aim of this article is to investigate the fine-tuning potential of natural language inference (NLI) data to improve information retrieval and ranking. We demonstrate this for both English and Polish languages, using data from one of the largest Polish …","url":["https://arxiv.org/pdf/2308.03103"]}
-{"year":"2023","title":"Improving Gender-Related Fairness in Sentence Encoders: A Semantics-Based Approach","authors":["T Dolci, F Azzalini, M Tanelli - Data Science and Engineering, 2023"],"snippet":"… Finally, as underlying word-level representations, we select the biggest and more powerful GloVe model available, trained on Common Crawl 840B. Footnote 5 For the retraining, we used a Linux machine with Ubuntu 18.04, 78GB of RAM and a …","url":["https://link.springer.com/article/10.1007/s41019-023-00211-0"]}
-{"year":"2023","title":"Improving Generalization of Adapter-Based Cross-lingual Transfer with Scheduled Unfreezing","authors":["CC Liu, J Pfeiffer, I Vulić, I Gurevych - arXiv preprint arXiv:2301.05487, 2023"],"snippet":"Standard fine-tuning of language models typically performs well on in-distribution data, but suffers with generalization to distribution shifts. In this work, we aim to improve generalization of adapter-based cross-lingual task transfer where such …","url":["https://arxiv.org/pdf/2301.05487"]}
-{"year":"2023","title":"Improving Log-Based Anomaly Detection by Pre-Training Hierarchical Transformers","authors":["S Huang, Y Liu, C Fung, H Wang, H Yang, Z Luan - IEEE Transactions on Computers, 2023"],"snippet":"… For example, LogRobust [8] leverages word vectors pre-trained on the Common Crawl Corpus [10] dataset to extract the log event’s semantic information and transforms each log event into a semantic vector. It then utilizes an attention-based …","url":["https://ieeexplore.ieee.org/abstract/document/10070784/"]}
-{"year":"2023","title":"Improving Low-Resource Languages in Pre-Trained Multilingual Language Models","authors":["V Hangya, HS Saadi, A Fraser - Proceedings of the 2022 Conference on Empirical …, 2022"],"snippet":"… However, multilingual LMs mainly focus on high resource languages, eg, mBERT supports the top 104 languages based on Wikipedia sizes, while XLM-R supports the top 100 based on CommonCrawl data. Additionally, many of these languages …","url":["https://aclanthology.org/2022.emnlp-main.822.pdf"]}
-{"year":"2023","title":"Improving Machine Translation in the E-commerce Luxury Space. A case study","authors":["JM De-la-Torre-Vilariño, JL García-Mendoza… - Proceedings of the 24th …, 2023"],"snippet":"This case study presents a Multilingual e-commerce Project, which principal aim is to create an improved system that translates product titles and descriptions, plus other content in multiple languages. The project consisted of two main phases; a …","url":["https://aclanthology.org/2023.eamt-1.43.pdf"]}
-{"year":"2023","title":"Improving Multiclass Classification of Fake News Using BERT-Based Models and ChatGPT-Augmented Data","authors":["E Shushkevich, M Alexandrov, J Cardiff - Inventions, 2023"],"snippet":"Given the widespread accessibility of content creation and sharing, false information proliferation is a growing concern. Researchers typically tackle fake news detection (FND) in specific topics using binary classification. Our study addresses a more practical …","url":["https://www.mdpi.com/2411-5134/8/5/112"]}
-{"year":"2023","title":"Improving Multimodal Datasets with Image Captioning","authors":["T Nguyen, SY Gadre, G Ilharco, S Oh, L Schmidt - arXiv preprint arXiv:2307.10350, 2023"],"snippet":"… We also work with raw Common Crawl data instead of preprocessed datasets to study the trade-offs between raw and generated captions in a systematic manner. Finally, Gadre et al. [18] introduces DataComp, a benchmark for designing better pre-training …","url":["https://arxiv.org/pdf/2307.10350"]}
-{"year":"2023","title":"Improving Natural Language Inference in Arabic using Transformer Models and Linguistically Informed Pre-Training","authors":["MMSA Deen, M Pielka, J Hees, BS Abdou, R Sifa - arXiv preprint arXiv:2307.14666, 2023"],"snippet":"This paper addresses the classification of Arabic text data in the field of Natural Language Processing (NLP), with a particular focus on Natural Language Inference (NLI) and Contradiction Detection (CD). Arabic is considered a resource-poor language …","url":["https://arxiv.org/pdf/2307.14666"]}
-{"year":"2023","title":"Improving network intrusion detection applying hybrid machine learning algorithms","authors":["K Čiurlienė, D Stankevičius - DAMSS 2022: 13th conference on data analysis …, 2022"],"snippet":"DAMSS-2022 is the 13th International Conference on Data Analysis Methods for Software Systems, held in Druskininkai, Lithuania. Every year at the same place and time. The exception was in 2020, when the world was gripped by the Covid-19 …","url":["https://vb.vgtu.lt/object/elaba:147315981/147315981.pdf"]}
-{"year":"2023","title":"Improving predictive models for rate of penetration in real drilling operations through transfer learning","authors":["FJ Pacis, A Ambrus, S Alyaev, R Khosravanian… - Journal of Computational …, 2023"],"snippet":"The rate of penetration (ROP) is a key performance indicator in the oil and gas drilling industry as it directly translates to cost savings and emission reductions. A prerequisite for a drilling optimization algorithm is a predictive model that provides …","url":["https://www.sciencedirect.com/science/article/pii/S1877750323001606"]}
-{"year":"2023","title":"Improving Subword Tokenization Methods for Multilingual Models","authors":["J Balhar"],"snippet":"… This unlabeled, multilingual dataset was created from the Common Crawl corpus using an automatic pipeline. The data was deduplicated and languageidentified. Then for each monolingual corpus the data was filtered using KneserNey language …","url":["https://jirkabalhar.cz/diplomka/diplomka.pdf"]}
-{"year":"2023","title":"Improving Word Embedding Using Variational Dropout","authors":["Z Albujasim, D Inkpen, X Han, Y Guo - The International FLAIRS Conference …, 2023"],"snippet":"Pre-trained word embeddings are essential in natural language processing (NLP). In recent years, many post-processing algorithms have been proposed to improve the pre-trained word embeddings. We present a novel method-Orthogonal Auto …","url":["https://journals.flvc.org/FLAIRS/article/download/133326/137934"]}
-{"year":"2023","title":"Improving Word Sense Disambiguation in Neural Machine Translation with Salient Document Context","authors":["E Rippeth, M Carpuat, K Duh, M Post - arXiv preprint arXiv:2311.15507, 2023"],"snippet":"Lexical ambiguity is a challenging and pervasive problem in machine translation (\\mt). We introduce a simple and scalable approach to resolve translation ambiguity by incorporating a small amount of extra-sentential context in neural \\mt. Our approach …","url":["https://arxiv.org/pdf/2311.15507"]}
-{"year":"2023","title":"In search of founding era registers: automatic modeling of registers from the corpus of Founding Era American English","authors":["L Repo, B Hashimoto, V Laippala - Digital Scholarship in the Humanities, 2023"],"snippet":"Registers are situationally defined text varieties, such as letters, essays, or news articles, that are considered to be one of the most important predictors of linguistic variation. Often historical databases of language lack register information, which …","url":["https://academic.oup.com/dsh/advance-article/doi/10.1093/llc/fqad049/7293015"]}
-{"year":"2023","title":"In What Languages are Generative Language Models the Most Formal? Analyzing Formality Distribution across Languages","authors":["A Ersoy, G Vizcarra, TT Mayeesha, B Muller - arXiv preprint arXiv:2302.12299, 2023"],"snippet":"… BLOOM was trained from a collection of multiple sources such as Huggingface datasets, Github code, and Web Common Crawl. The data sources were then preprocessed to reduce non-natural language and anonymize personal identifiable …","url":["https://arxiv.org/pdf/2302.12299"]}
-{"year":"2023","title":"In-Context Pretraining: Language Modeling Beyond Document Boundaries","authors":["W Shi, S Min, M Lomeli, C Zhou, M Li, V Lin, NA Smith… - arXiv preprint arXiv …, 2023"],"snippet":"… For example, less than 5% of documents in CommonCrawl have longer than 2k tokens. In this work, we focus on constructing meaningful long-context data, making language models better leverage its context-window. Our sorted data can be used …","url":["https://arxiv.org/pdf/2310.10638"]}
-{"year":"2023","title":"IN-ORDER TRANSITION-BASED PARSING FOR VIETNAMESE","authors":["J Bauer, H Bui, V Thai, C Manning - Journal of Computer Science and Cybernetics, 2023"],"snippet":"In this paper, we implement a general neural constituency parser based on an in-order parser. We apply this parser to the VLSP 2022 Vietnamese treebank, obtaining a test score of. 8393 F1, top of the private test leaderboard. Earlier versions of the …","url":["https://vjs.ac.vn/index.php/jcc/article/download/18363/2543255143"]}
-{"year":"2023","title":"Incorporating Natural Language Processing into Virtual Assistants: An Intelligent Assessment Strategy for Enhancing Language Comprehension","authors":["F Antonius, PR Alapati, M Ritonga, I Patra… - International Journal of …, 2023"],"snippet":"… The process starts with the selection of diverse pretraining datasets, including the multilingual Colossal Clean Common Crawl (mC4), CC100 dataset, and Wikipedia data. These datasets encompass various domains, languages, and tones …","url":["https://search.proquest.com/openview/8a5aff1d8b440faaecab2bed684db6c1/1?pq-origsite=gscholar&cbl=5444811"]}
-{"year":"2023","title":"IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages","authors":["J Gala, PA Chitale, R AK, S Doddapaneni, V Gumma… - arXiv preprint arXiv …, 2023"],"snippet":"India has a rich linguistic landscape with languages from 4 major language families spoken by over a billion people. 22 of these languages are listed in the Constitution of India (referred to as scheduled languages) are the focus of this work. Given the …","url":["https://arxiv.org/pdf/2305.16307"]}
-{"year":"2023","title":"IndiSocialFT: Multilingual Word Representation for Indian languages in code-mixed environment","authors":["S Kumar, R Sanasam, S Nandi - Findings of the Association for Computational …, 2023"],"snippet":"The increasing number of Indian language users on the internet necessitates the development of Indian language technologies. In response to this demand, our paper presents a generalized representation vector for diverse text characteristics …","url":["https://aclanthology.org/2023.findings-emnlp.252.pdf"]}
-{"year":"2023","title":"IndoToD: A Multi-Domain Indonesian Benchmark For End-to-End Task-Oriented Dialogue Systems","authors":["MDA Kautsar, RK Nurdini, S Cahyawijaya, GI Winata… - arXiv preprint arXiv …, 2023"],"snippet":"… Specifically, we incorporate common crawl4 English and Indonesian fastText word vectors for monolingual English and Indonesian experiment settings respectively. Meanwhile, we use bilingual English-Indonesian word vectors (Conneau et al.…","url":["https://arxiv.org/pdf/2311.00958"]}
-{"year":"2023","title":"Influence of the duration of training a deep neural network model on the quality of text summarization task","authors":["A Gryaznov, R Rybka, I Moloshnikov, A Selivanov… - AIP Conference …, 2023"],"snippet":"In this paper we apply the generative deep learning language model to text summarization task. Because such large language models require a lot of resources to train, it is interesting to study how much long training affects the final result and at …","url":["https://pubs.aip.org/aip/acp/article/2849/1/400006/2909197"]}
-{"year":"2023","title":"Information Access Using Neural Networks For Diverse Domains And Sources","authors":["Y Xie - 2023"],"snippet":"The ever-increasing volume of web-based documents poses a challenge in efficiently accessing specialized knowledge from domain-specific sources, requiring a profound understanding of the domain and substantial comprehension effort …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19837/Xie_Yuqing.pdf?sequence=3&isAllowed=y"]}
-{"year":"2023","title":"Information Extraction and Knowledge Graph Development for Manufacturing Science Domain using Natural Language Processing.","authors":["A Kumar - 2023"],"snippet":"KUMAR, AMAN. Information Extraction and Knowledge Graph Development for Manufacturing Science Domain using Natural Lang Page 1 ABSTRACT KUMAR, AMAN. Information Extraction and Knowledge Graph Development for …","url":["https://repository.lib.ncsu.edu/bitstream/handle/1840.20/40758/etd.pdf?sequence=1"]}
-{"year":"2023","title":"Information Extraction from Polish Radiology Reports using Language Models","authors":["A Obuchowski, B Klaudel, P Jasik - Proceedings of the 9th Workshop on Slavic …, 2023"],"snippet":"… All the models were pre-trained using a Polish subset of the Common Crawl corpus. The model’s pre-training details are shown in (Dadas … 2019) embeddings for the Polish language trained on the Polish part of the Common Crawl dataset …","url":["https://aclanthology.org/2023.bsnlp-1.14.pdf"]}
-{"year":"2023","title":"Information resource management researchers' thinking about the opportunities and challenges of AIGC","authors":["Z ZHANG, Z Jianxun, XIA Cuijuan, W Dongbo… - Journal of Library and …, 2023"],"snippet":"With the explosive popularity of ChatGPT and the development of AI generated content (AIGC), the new generation of artificial intelligence (AI) technology has triggered people's imagination and discussion about the production mode of digital …","url":["https://search.proquest.com/openview/c6d31b7b2204519d42c799e9faeab34b/1?pq-origsite=gscholar&cbl=6524071"]}
-{"year":"2023","title":"infoVerse: A Universal Framework for Dataset Characterization with Multidimensional Meta-information","authors":["J Kim, Y Kim, K de Langis, J Shin, D Kang - arXiv preprint arXiv:2305.19344, 2023"],"snippet":"The success of NLP systems often relies on the availability of large, high-quality datasets. However, not all samples in these datasets are equally valuable for learning, as some may be redundant or noisy. Several methods for characterizing …","url":["https://arxiv.org/pdf/2305.19344"]}
-{"year":"2023","title":"INGENIOUS: Using Informative Data Subsets for Efficient Pre-Training of Large Language Models","authors":["HK Renduchintala, K Killamsetty, S Bhatia, M Aggarwal… - arXiv preprint arXiv …, 2023"],"snippet":"A salient characteristic of large pre-trained language models (PTLMs) is a remarkable improvement in their generalization capability and emergence of new capabilities with increasing model capacity and pre-training dataset size …","url":["https://arxiv.org/pdf/2305.06677"]}
-{"year":"2023","title":"Inria-ALMAnaCH at WMT 2022: Does Transcription Help Cross-Script Machine Translation?","authors":["J Alabi, L Nishimwe, B Muller, C Rey, B Sagot… - Proceedings of the Seventh …, 2022"],"snippet":"This paper describes the Inria ALMAnaCH team submission to the WMT 2022 general translation shared task. Participating in the language directions {cs, ru, uk}→ en and cs↔ uk, we experiment with the use of a dedicated Latin-script transcription …","url":["https://aclanthology.org/2022.wmt-1.15.pdf"]}
-{"year":"2023","title":"Insincere Questions Classification Using CNN with Increased Vocabulary Coverage of GloVe Embedding","authors":["S Mishra, N Kumar - Journal of The Institution of Engineers (India): Series B, 2023"],"snippet":"… word embedding used in training the model is the GloVe word embedding from Stanford NLP [9], the GloVe stands for “Global Vectors for Word Representation”, it is a pre-trained embedding and has different options, so for this study, the authors …","url":["https://link.springer.com/article/10.1007/s40031-023-00858-3"]}
-{"year":"2023","title":"Instance-Based Domain Adaptation for Improving Terminology Translation","authors":["P Nayak, J Kelleher, R Haque, A Way - … of Machine Translation Summit XIX, Vol. 1 …, 2023"],"snippet":"Terms are essential indicators of a domain, and domain term translation is dealt with priority in any translation workflow. Translation service providers who use machine translation (MT) expect term translation to be unambiguous and consistent with the …","url":["https://aclanthology.org/2023.mtsummit-research.19.pdf"]}
-{"year":"2023","title":"InstructIE: A Chinese Instruction-based Information Extraction Dataset","authors":["H Gui, J Zhang, H Ye, N Zhang - arXiv preprint arXiv:2305.11527, 2023"],"snippet":"We introduce a new Information Extraction (IE) task dubbed Instruction-based IE, which aims to ask the system to follow specific instructions or guidelines to extract information. To facilitate research in this area, we construct a dataset called InstructIE …","url":["https://arxiv.org/pdf/2305.11527"]}
-{"year":"2023","title":"Instruction-tuning Aligns LLMs to the Human Brain","authors":["KL Aw, S Montariol, B AlKhamissi, M Schrimpf… - arXiv preprint arXiv …, 2023"],"snippet":"… T5 models are encoder-decoder LLMs pretrained on the Colossal Common Crawl Corpus (C4), a corpus of 356 billion tokens, using a masked infilling objective, and then further finetuned on multi-task mixture of unsupervised and supervised …","url":["https://arxiv.org/pdf/2312.00575"]}
-{"year":"2023","title":"InstructRetro: Instruction Tuning post Retrieval-Augmented Pretraining","authors":["B Wang, W Ping, L McAfee, P Xu, B Li, M Shoeybi… - arXiv preprint arXiv …, 2023"],"snippet":"Pretraining auto-regressive large language models (LLMs) with retrieval demonstrates better perplexity and factual accuracy by leveraging external databases. However, the size of existing pretrained retrieval-augmented LLM is still …","url":["https://arxiv.org/pdf/2310.07713"]}
-{"year":"2023","title":"Integrating artificial intelligence-based methods into qualitative research in physics education research: A case for computational grounded theory","authors":["P Tschisgale, P Wulff, M Kubsch - Physical Review Physics Education Research, 2023"],"snippet":"[This paper is part of the Focused Collection on Qualitative Methods in PER: A Critical Examination.] Qualitative research methods have provided key insights in physics education research (PER) by drawing on non-numerical data such as text or …","url":["https://link.aps.org/pdf/10.1103/PhysRevPhysEducRes.19.020123"]}
-{"year":"2023","title":"Integrating Offline Reinforcement Learning with Transformers for Sequential Recommendation","authors":["X Xi, Y Zhao, Q Liu, L Ouyang, Y Wu - arXiv preprint arXiv:2307.14450, 2023"],"snippet":"We consider the problem of sequential recommendation, where the current recommendation is made based on past interactions. This recommendation task requires efficient processing of the sequential data and aims to provide …","url":["https://arxiv.org/pdf/2307.14450"]}
-{"year":"2023","title":"Intelligent Phishing Website Detection before and after Multiple Informative Feature Selection Techniques: Machine Learning Approach","authors":["K Adane, B Beyene, M Abebe - International Journal of Information, 2024"],"snippet":"Individuals and Organizations that rely on the Internet for communication, collaboration, and daily tasks regularly encounter security and privacy issues unless interventions of intelligent Cybersecurity defense systems have been made to …","url":["https://ijism.ricest.ac.ir/article_709483_9565ffb496f4a333610af887bfea03ca.pdf"]}
-{"year":"2023","title":"Intent Detection in Urdu Queries using Fine-tuned BERT models","authors":["S Shams, B Sadia, M Aslam - 2022 16th International Conference on Open Source …, 2022"],"snippet":"User's intent detection provides essential cues in query understanding and accurate information retrieval through search engines and task-oriented dialogue systems. Intent detection from user queries is challenging due to short query length and lack …","url":["https://ieeexplore.ieee.org/abstract/document/10016834/"]}
-{"year":"2023","title":"Interactive Natural Language Processing","authors":["Z Wang, G Zhang, K Yang, N Shi, W Zhou, S Hao… - arXiv preprint arXiv …, 2023"],"snippet":"… 2008), PubMed Corpus4, and CommonCrawl Corpus5, among others. Most previous research has focused on corpus knowledge due to its controllability and efficiency. RetrievalAugmented Language Models (Guu et … 4https://pubmed.ncbi.nlm.nih.gov …","url":["https://arxiv.org/pdf/2305.13246"]}
-{"year":"2023","title":"Interactive writing systems and why small (er) could be more beautiful","authors":["I Olatunji"],"snippet":"ABSTRACT Machine learning models can support human creativity, including tasks such as writing. This position paper explorers and critiques the design of writing systems based on big data. The paper proposes small data as way to think about …","url":["https://cdn.glitch.global/d058c114-3406-43be-8a3c-d3afff35eda2/paper8_2023.pdf"]}
-{"year":"2023","title":"Intercity networks and urban performance: a geographical text mining approach","authors":["W Tongjing, E Meijers, Z Bao, H Wang - International Journal of Urban Sciences, 2023"],"snippet":"… While it is possible to search for toponym occurrences using a search engine like google, results returned are vulnerable to bias (Meijers & Peris, Citation2019), and like Meijers and Peris we prefer using corpora from the CommonCrawl Archive of …","url":["https://www.tandfonline.com/doi/pdf/10.1080/12265934.2023.2253193"]}
-{"year":"2023","title":"Interconnecting Advanced Networks with AI Applications","authors":["A Luntovskyy - Preprints of Position Papers of the 18th Conference on …, 2023"],"snippet":"… org as a text’s source can also be specified as the so-called C4 (Common Crawl Cultural Context). Furthermore, the sources of texts can be differentiated as follows: search engines, online forums and communities, social media, blogs, newspapers …","url":["https://annals-csis.org/proceedings/2023/pliks/position.pdf#page=83"]}
-{"year":"2023","title":"INTERPRETING THE RELEVANCE OF READABILITY PREDICTION FEATURES","authors":["S Berrichi, N Nassiri, A Mazroui, A Lakhouaja - Jordanian Journal of Computers and …, 2023"],"snippet":"… from “Common Crawl” and a dump of Arabic Wikipedia totaling 8.2 billion words. Different pretrained BERT models are used. We have selected in this study, the bert-base-Arabic model. 3) XLM-R [29]: is a multi-lingual version of BERT model, trained on “Common …","url":["https://search.proquest.com/openview/1ac2e34f30c82362dd25d671ecfad14a/1?pq-origsite=gscholar&cbl=5500744"]}
-{"year":"2023","title":"Into the LAION's Den: Investigating Hate in Multimodal Datasets","authors":["A Birhane, S Han, V Boddeti, S Luccioni - Thirty-seventh Conference on Neural …, 2023"],"snippet":"… -2B-en are extracted from the Common Crawl dataset, we hypothesize that during the race to expand the dataset to 5 billion samples, the dataset scraping module might have sampled from the lower-quality sub-parts of the Common Crawl at a rate …","url":["https://openreview.net/pdf?id=6URyQ9QhYv"]}
-{"year":"2023","title":"Intriguing Properties of Quantization at Scale","authors":["A Ahmadian, S Dash, H Chen, B Venkitesh, S Gou… - arXiv preprint arXiv …, 2023"],"snippet":"Emergent properties have been widely adopted as a term to describe behavior not present in smaller models but observed in larger models. Recent work suggests that the trade-off incurred by quantization is also an emergent property, with sharp drops …","url":["https://arxiv.org/pdf/2305.19268"]}
-{"year":"2023","title":"Introducing UberText 2.0: a corpus of modern Ukrainian at scale","authors":["D Chaplynskyi - Proceedings of the Second Ukrainian Natural …, 2023"],"snippet":"This paper addresses the need for massive corpora for a low-resource language and presents the publicly available UberText 2.0 corpus for the Ukrainian language and discusses the methodology of its construction. While the collection and …","url":["https://aclanthology.org/2023.unlp-1.1.pdf"]}
-{"year":"2023","title":"Introduction to ChatGPT: A new revolution of artificial intelligence with machine learning algorithms and cybersecurity","authors":["MA Hadi, MN Abdulredha, E Hasan"],"snippet":"ChatGPTis an innovative natural language processing (NLP) technology developed by OpenAI. It has revolutionized humancomputer interactions by utilizing Machine Learning (ML) and Deep Learning (DL) algorithms. ChatGPT generates a …","url":["https://www.researchgate.net/profile/Mohammed-Najm/publication/376391507_Introduction_to_ChatGPT_A_new_revolution_of_artificial_intelligence_with_machine_learning_algorithms_and_cybersecurity/links/6576a230cbd2c535ea157e98/Introduction-to-ChatGPT-A-new-revolution-of-artificial-intelligence-with-machine-learning-algorithms-and-cybersecurity.pdf"]}
-{"year":"2023","title":"Investigating Biases in Rules Extracted from Language Models","authors":["SM Blum - 2023"],"snippet":"We investigate an approach for extracting occupational gender bias in the form of logical rules from Large Language Models (LLM)s based on Angluin's exact learning model with membership and equivalence queries to an oracle. In our …","url":["https://bora.uib.no/bora-xmlui/bitstream/handle/11250/3086287/Master_Thesis_Sophie_Blum.pdf?sequence=1"]}
-{"year":"2023","title":"Investigating parallelograms inside word embedding space using various analogy test sets in various languages","authors":["R Fam, Y Lepage"],"snippet":"The idea of using analogy to assess the quality of word embedding spaces implies the existence of parallelograms between the four terms of an analogy. We investigate the presence of analogy parallelograms in various word embedding …","url":["https://www.anlp.jp/proceedings/annual_meeting/2023/pdf_dir/P3-3.pdf"]}
-{"year":"2023","title":"Investigating the Extent and Usability of Webtext Available in South Africa's Official Languages","authors":["F de Wet, R Eiselen, E Schillack, M Puttkammer - Southern African Conference for …, 2023"],"snippet":"… The Common Crawl (CC) data set is likely the largest text data set currently available consisting of (bi-)monthly crawls of the web, and is … Part of the common crawl collection process is language identification to categorise the predominant …","url":["https://link.springer.com/chapter/10.1007/978-3-031-49002-6_9"]}
-{"year":"2023","title":"Investigating Vision Foundational Models for Tactile Representation Learning","authors":["B Zandonati, R Wang, R Gao, Y Wu - arXiv preprint arXiv:2305.00596, 2023"],"snippet":"… In particular, foundational models [11] are trained on massive datasets such as ImageNet [12] and CommonCrawl [13] to derive general representational knowledge, which can be specialized to diverse downstream tasks, such as semantic …","url":["https://arxiv.org/pdf/2305.00596"]}
-{"year":"2023","title":"Investigation of quantum-inspired modelling in interactive search based on information foraging theory","authors":["AK Jaiswal - 2023"],"snippet":"This thesis investigates the use of the mathematical formalism of quantum mechanics for modelling users’ information needs from the viewpoint of Information Foraging Theory (IFT). IFT has been successfully applied to model user behaviours …","url":["https://uobrep.openrepository.com/bitstream/handle/10547/625945/JAISWAL%20Amit%201808389%20QUARTZ%20FULL%20REPOSITORY%20COPY.pdf?sequence=1"]}
-{"year":"2023","title":"IOL Research Machine Translation Systems for WMT23 General Machine Translation Shared Task","authors":["W Zhang, Z Yan, Q Deng, J Cai, H Mao - Proceedings of the Eighth Conference on …, 2023"],"snippet":"This paper describes the IOL Research team’s submission systems for the WMT23 general machine translation shared task. We participated in two language translation directions, including English→ Chinese and Chinese→ English. Our final …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.19.pdf"]}
-{"year":"2023","title":"IPARO: INTERPLANETARY ARCHIVAL RECORD OBJECT FOR DECENTRALIZED WEB ARCHIVING AND REPLAY","authors":["S Alam - iPRES 2023, 2023"],"snippet":"We proposed a decentralized version tracking system using the existing primitives of IPFS and IPNS. While our description talks primarily about archived web pages, we proposed the concept of IPMT and namespacing so that it can be used in other …","url":["https://www.ideals.illinois.edu/items/128294/bitstreams/428953/object"]}
-{"year":"2023","title":"Irreducible Curriculum for Language Model Pretraining","authors":["S Fan, M Jaggi - arXiv preprint arXiv:2310.15389, 2023"],"snippet":"… 5, IRREDUCIBLE CURRICULUM reduce the validation perplexity on 4 domains (C4, CommonCrawl, Book and Wikipedia), while showing the … Figure 4 shows that most of the globally top-ranked samples are from Wikipedia, C4 and CommonCrawl …","url":["https://arxiv.org/pdf/2310.15389"]}
-{"year":"2023","title":"Is GPT-3 all you need for low-data discovery in chemistry?","authors":["KM Jablonka, P Schwaller, A Ortega-Guerrero, B Smit - 2023"],"snippet":"… The version of GPT-3 we utilized in this work has been trained on data up to Oct 2019 that mostly comes from web scraping (Common Crawl47 and WebText48) along with books corpora and Wikipedia. Structured datasets, however, have not …","url":["https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/63eb5a669da0bc6b33e97a35/original/is-gpt-3-all-you-need-for-low-data-discovery-in-chemistry.pdf"]}
-{"year":"2023","title":"IS IT POSSIBLE TO RE-EDUCATE ROBERTA? EXPERT-DRIVEN MACHINE LEARNING FOR PUNCTUATION CORRECTION","authors":["JMH ŽIŽKOVÁ, AFJAN ŠVEC - JAZYKOVEDNÝ ČASOPIS"],"snippet":"… As the training data set used for fine-tuning, we used 10 GB of raw text extracted from the Czech CommonCrawl data set. Because RoBERTa’s output is related to input tokens (not words), we assigned the target label (‟,” for comma,“0” for no …","url":["https://www.researchgate.net/profile/Michal-Mistecky-2/publication/374698410_Appellativization_of_Proper_Names_-_In_the_Perspective_of_Corpus_Analysis/links/6529c94a06bdd619c48c15ed/Appellativization-of-Proper-Names-In-the-Perspective-of-Corpus-Analysis.pdf#page=359"]}
-{"year":"2023","title":"Is More Always Better? Testing the Addition Bias for German Language Statistics","authors":["S Wolfer - Cognitive Science, 2023"],"snippet":"This replication study aims to investigate a potential bias toward addition in the German language, building upon previous findings of Winter and colleagues who identified a similar bias in English. Our results confirm a bias in word frequencies …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/cogs.13339"]}
-{"year":"2023","title":"Issues Surrounding the Use of ChatGPT in Similar Languages: The Case of Malay and Indonesian","authors":["H Nomoto - Malay"],"snippet":"We report a problem that one faces when using ChatGPT in similar languages, taking Malay and Indonesian as examples: ChatGPT often responds to prompts in Malay (the language with fewer speakers) in Indonesian (the language with more …","url":["http://www.afnlp.org/conferences/ijcnlp2023/proceedings/main-short/cdrom/pdf/2023.ijcnlp-short.9.pdf"]}
-{"year":"2023","title":"Its All Graph To Me: Foundational Topology Models with Contrastive Learning on Multiple Domains","authors":["AO Davies, R Green, NS Ajmeri, TM Silva Filho - arXiv preprint arXiv:2311.03976, 2023"],"snippet":"Abstract Representations and embeddings of graph data have been essential in many domains of research. The principle benefit of learning such representations is that the pretrained model can be fine-tuned on smaller datasets where data or labels …","url":["https://arxiv.org/pdf/2311.03976"]}
-{"year":"2023","title":"IussNets at DisCo-Tex: A fine-tuned approach to coherence","authors":["E Zanoli, M Barbini, C Chesi - Proceedings of the Eighth Evaluation Campaign of …, 2023"],"snippet":"We present our submission to the DisCoTex shared task of the EVALITA 2023 evaluation campaign, which focuses on modeling discourse coherence for Italian texts. We highlight the importance of coherence modeling in natural language …","url":["https://ceur-ws.org/Vol-3473/paper50.pdf"]}
-{"year":"2023","title":"Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models","authors":["N Sengupta, SK Sahu, B Jia, S Katipomu, H Li, F Koto… - arXiv preprint arXiv …, 2023"],"snippet":"… • Pile-CC: A subset of The Pile dataset, derived from the Common Crawl, a collection of website crawls from 2008 onwards. The dataset includes raw web pages, metadata, and text extractions from diverse domains. Due to the varying …","url":["https://arxiv.org/pdf/2308.16149"]}
-{"year":"2023","title":"Jake Glendenning","authors":["IIM LEARNING - AIPLA QUARTERLY JOURNAL, 2023"],"snippet":"… sentence and understand that machine learning models like GPT-3 don't \"read\" like humans do, but rather ingest data sets like Common Crawl, which is made up of many written works … 2020) (explaining the use of the Common Crawl dataset in …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/aiplaqj51&section=5"]}
-{"year":"2023","title":"Japanese SimCSE Technical Report","authors":["H Tsukagoshi, R Sasano, K Takeda - arXiv preprint arXiv:2310.19349, 2023"],"snippet":"We report the development of Japanese SimCSE, Japanese sentence embedding models fine-tuned with SimCSE. Since there is a lack of sentence embedding models for Japanese that can be used as a baseline in sentence embedding …","url":["https://arxiv.org/pdf/2310.19349"]}
-{"year":"2023","title":"JCoLA: Japanese Corpus of Linguistic Acceptability","authors":["T Someya, Y Sugimoto, Y Oseki - arXiv preprint arXiv:2309.12676, 2023"],"snippet":"Neural language models have exhibited outstanding performance in a range of downstream tasks. However, there is limited understanding regarding the extent to which these models internalize syntactic knowledge, so that various datasets have …","url":["https://arxiv.org/pdf/2309.12676"]}
-{"year":"2023","title":"Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documents","authors":["M Günther, J Ong, I Mohr, A Abdessalem, T Abel… - arXiv preprint arXiv …, 2023"],"snippet":"Text embedding models have emerged as powerful tools for transforming sentences into fixed-sized feature vectors that encapsulate semantic information. While these models are essential for tasks like information retrieval, semantic clustering, and text …","url":["https://arxiv.org/pdf/2310.19923"]}
-{"year":"2023","title":"KASYS at the TREC 2022 NeuCLIR Track","authors":["K Abe, K Shinden, MP Kato"],"snippet":"This paper describes the KASYS team’s participation in the TREC 2022 NeuCLIR track. Our approach is One-for-All, which employs a single multilingual pre-trained language model to retrieve documents of any languages in response to an English …","url":["https://trec.nist.gov/pubs/trec31/papers/KASYS.N.pdf"]}
-{"year":"2023","title":"KaustubhSharedTask@ LT-EDI 2023: Homophobia-Transphobia Detection in Social Media Comments with NLPAUG-driven Data Augmentation","authors":["K Lande, R Ponnusamy, PK Kumaresan… - Proceedings of the Third …, 2023"],"snippet":"Our research in Natural Language Processing (NLP) aims to detect hate speech comments specifically targeted at the LGBTQ+ community within the YouTube platform shared task conducted by LTEDI workshop. The dataset provided by the …","url":["https://aclanthology.org/2023.ltedi-1.10.pdf"]}
-{"year":"2023","title":"Keyword Embeddings for Query Suggestion","authors":["J Gabín, ME Ares, J Parapar - arXiv preprint arXiv:2301.08006, 2023"],"snippet":"Nowadays, search engine users commonly rely on query suggestions to improve their initial inputs. Current systems are very good at recommending lexical adaptations or spelling corrections to users' queries. However, they often struggle to …","url":["https://arxiv.org/pdf/2301.08006"]}
-{"year":"2023","title":"Know Where to Go: Make LLM a Relevant, Responsible, and Trustworthy Searcher","authors":["X Shi, J Liu, Y Liu, Q Cheng, W Lu - arXiv preprint arXiv:2310.12443, 2023"],"snippet":"The advent of Large Language Models (LLMs) has shown the potential to improve relevance and provide direct answers in web searches. However, challenges arise in validating the reliability of generated results and the credibility of contributing …","url":["https://arxiv.org/pdf/2310.12443"]}
-{"year":"2023","title":"Knowledge and Pre-trained Language Models: a deep-dive into datasets and external knowledge","authors":["C Lyu - 2023"],"snippet":"Recent years have witnessed the emergence of Pre-trained Language Models (PLMs), such as ELMo, GPT, BERT, XLNet, GPT-3 and InstructGPT [11, 12, 13, 14, 15, 16, 17, 18, 19], which have been widely used in many NLP tasks and have shown superior …","url":["https://www.researchgate.net/profile/Chenyang-Lyu-4/publication/373632826_Knowledge_and_Pre-trained_Language_Models_a_deep-dive_into_datasets_and_external_knowledge/links/64f445b94c70687b8ecbdac9/Knowledge-and-Pre-trained-Language-Models-a-deep-dive-into-datasets-and-external-knowledge.pdf"]}
-{"year":"2023","title":"Knowledge Informed Fake News Detection Using Large Language Models","authors":["JJ Benny - 2023"],"snippet":"The spread of false or misleading information as news has been a significant threat to governments, organizations and the economy for a long time. However, it has become more prevalent and influential in recent years due to the growing popularity …","url":["https://search.proquest.com/openview/0041daa59cded0bc477e27a17af5500e/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Knowledge of cultural moral norms in large language models","authors":["A Ramezani, Y Xu - arXiv preprint arXiv:2306.01857, 2023"],"snippet":"Moral norms vary across cultures. A recent line of work suggests that English large language models contain human-like moral biases, but these studies typically do not examine moral variation in a diverse cultural setting. We investigate the extent to …","url":["https://arxiv.org/pdf/2306.01857"]}
-{"year":"2023","title":"Knowledge-Based and Generative-AI-Driven Pedagogical Conversational Agents: A Comparative Study of Grice's Cooperative Principles and Trust","authors":["M Wölfel, MB Shirzad, A Reich, K Anderer - Big Data and Cognitive Computing, 2023"],"snippet":"The emergence of generative language models (GLMs), such as OpenAI’s ChatGPT, is changing the way we communicate with computers and has a major impact on the educational landscape. While GLMs have great potential to support education, their …","url":["https://www.mdpi.com/2504-2289/8/1/2"]}
-{"year":"2023","title":"KoBigBird-large: Transformation of Transformer for Korean Language Understanding","authors":["K Yang, Y Jang, T Lee, J Seong, H Lee, H Jang, H Lim - arXiv preprint arXiv …, 2023"],"snippet":"This work presents KoBigBird-large, a large size of Korean BigBird that achieves state-of-the-art performance and allows long sequence processing for Korean language understanding. Without further pretraining, we only transform the …","url":["https://arxiv.org/pdf/2309.10339"]}
-{"year":"2023","title":"Kosmos-2.5: A Multimodal Literate Model","authors":["T Lv, Y Huang, J Chen, L Cui, S Ma, Y Chang, S Huang… - arXiv preprint arXiv …, 2023"],"snippet":"We present Kosmos-2.5, a multimodal literate model for machine reading of text-intensive images. Pre-trained on large-scale text-intensive images, Kosmos-2.5 excels in two distinct yet cooperative transcription tasks: (1) generating spatially-aware text blocks …","url":["https://arxiv.org/pdf/2309.11419"]}
-{"year":"2023","title":"Kosmos-G: Generating Images in Context with Multimodal Large Language Models","authors":["X Pan, L Dong, S Huang, Z Peng, W Chen, F Wei - arXiv preprint arXiv:2310.02992, 2023"],"snippet":"Recent advancements in text-to-image (T2I) and vision-language-to-image (VL2I) generation have made significant strides. However, the generation from generalized vision-language inputs, especially involving multiple images, remains under-explored …","url":["https://arxiv.org/pdf/2310.02992"]}
-{"year":"2023","title":"KTRL+ F: Knowledge-Augmented In-Document Search","authors":["H Oh, H Shin, M Ko, H Lee, M Seo - arXiv preprint arXiv:2311.08329, 2023"],"snippet":"We introduce a new problem KTRL+F, a knowledge-augmented in-document search task that necessitates real-time identification of all semantic targets within a document with the awareness of external sources through a single natural query …","url":["https://arxiv.org/pdf/2311.08329"]}
-{"year":"2023","title":"Lagniappe: Exploring the Pros and Cons of ChatGPT","authors":["J Daugherty - North Carolina Libraries, 2023"],"snippet":"… It trained on a dataset taken from Common Crawl, a nonprofit that scrapes text from websites and offers it for free download, Wikipedia, and other web texts, all from 2021.The ChatGPT Plus paid subscription offered web searching capabilities with a …","url":["http://www.ncl.ecu.edu/index.php/NCL/article/view/5420/4989"]}
-{"year":"2023","title":"Language Aligned Visual Representations Predict Human Behavior in Naturalistic Learning Tasks","authors":["C Demircan, T Saanum, L Pettini, M Binz… - arXiv preprint arXiv …, 2023"],"snippet":"Humans possess the ability to identify and generalize relevant features of natural objects, which aids them in various situations. To investigate this phenomenon and determine the most effective representations for predicting human behavior, we …","url":["https://arxiv.org/pdf/2306.09377"]}
-{"year":"2023","title":"Language and Task Arithmetic with Parameter-Efficient Layers for Zero-Shot Summarization","authors":["A Chronopoulou, J Pfeiffer, J Maynez, X Wang… - arXiv preprint arXiv …, 2023"],"snippet":"… This corpus has been created using a Common Crawl-based dataset covering 101 languages. All languages considered in our experiments are covered by mC4. For the language vectors, we finetune the LLM using LoRA on prefix-LM for only 5k …","url":["https://arxiv.org/pdf/2311.09344"]}
-{"year":"2023","title":"Language Is Not All You Need: Aligning Perception with Language Models","authors":["S Huang, L Dong, W Wang, Y Hao, S Singhal, S Ma… - arXiv preprint arXiv …, 2023"],"snippet":"… We also include the Common Crawl snapshots (2020-50 and 2021-04) datasets, CC-Stories… are collected from web pages of the Common Crawl web data by extracting image sources … Interleaved Image-Text Data We collect interleaved …","url":["https://arxiv.org/pdf/2302.14045"]}
-{"year":"2023","title":"Language Models and Power Laws","authors":["Ł Dębowski"],"snippet":"… Training data: Common Crawl (410 bln, 60%), WebText2 (19 bln, 22%), books (67 bln, 16%), Wikipedia (3 bln, 3%). …","url":["https://www.researchgate.net/profile/Lukasz-Debowski/publication/368757770_Language_Models_and_Power_Laws/links/63f8a32057495059453e7102/Language-Models-and-Power-Laws.pdf"]}
-{"year":"2023","title":"Language Models are Drummers: Drum Composition with Natural Language Pre-Training","authors":["L Zhang, C Callison-Burch - arXiv preprint arXiv:2301.01162, 2023"],"snippet":"Automatic music generation with artificial intelligence typically requires a large amount of data which is hard to obtain for many less common genres and musical instruments. To tackle this issue, we present ongoing work and preliminary findings …","url":["https://arxiv.org/pdf/2301.01162"]}
-{"year":"2023","title":"Language Models for German Text Simplification: Overcoming Parallel Data Scarcity through Style-specific Pre-training","authors":["M Anschütz, J Oehms, T Wimmer, B Jezierski, G Groh - arXiv preprint arXiv …, 2023"],"snippet":"Automatic text simplification systems help to reduce textual information barriers on the internet. However, for languages other than English, only few parallel data to train these systems exists. We propose a two-step approach to overcome this data …","url":["https://arxiv.org/pdf/2305.12908"]}
-{"year":"2023","title":"Language Report French","authors":["G Adda, I Vasilescu, F Yvon - European Language Equality: A Strategic Agenda for …, 2023"],"snippet":"… The CommonCrawl project aggregates Web data that is orders of magnitude larger than these resources; and it is updated on a regular basis. Using French subsets of CommonCrawl, it has been possible to train large language models (LMs) …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-28819-7_16.pdf"]}
-{"year":"2023","title":"Language Report Slovenian","authors":["S Krek - European Language Equality: A Strategic Agenda for …, 2023"],"snippet":"Around 2.5 million people around the world speak or understand Slovene, with the vast majority of them living in the Republic of Slovenia where it is the official language. The constitution grants the right to use their mother tongue to Italian and …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-28819-7_34.pdf"]}
-{"year":"2023","title":"Language Resources for Dutch Large Language Modelling","authors":["B Vanroy - arXiv preprint arXiv:2312.12852, 2023"],"snippet":"Despite the rapid expansion of types of large language models, there remains a notable gap in models specifically designed for the Dutch language. This gap is not only a shortage in terms of pretrained Dutch models but also in terms of data, and …","url":["https://arxiv.org/pdf/2312.12852"]}
-{"year":"2023","title":"Language Variety Identification with True Labels","authors":["M Zampieri, K North, T Jauhiainen, M Felice, N Kumari… - arXiv preprint arXiv …, 2023"],"snippet":"Language identification is an important first step in many IR and NLP applications. Most publicly available language identification datasets, however, are compiled under the assumption that the gold label of each instance is determined by where …","url":["https://arxiv.org/pdf/2303.01490"]}
-{"year":"2023","title":"Language-Aware Spatial-Temporal Collaboration for Referring Video Segmentation","authors":["T Hui, S Liu, Z Ding, S Huang, G Li, W Wang, L Liu…"],"snippet":"… The GloVe word embedding [66] pretrained on the Common Crawl with 840B tokens is used to embed input words. The maximum sequence length of the input referring expression is set as 20. The height and width of the input frames are …","url":["http://www.colalab.net/media/paper/CSTM_TPAMI_Paper.pdf"]}
-{"year":"2023","title":"Language-Family Adapters for Low-Resource Multilingual Neural Machine Translation","authors":["A Chronopoulou, D Stojanovski, A Fraser - Proceedings of the The Sixth Workshop …, 2023"],"snippet":"Large multilingual models trained with self-supervision achieve state-of-the-art results in a wide range of natural language processing tasks. Self-supervised pretrained models are often fine-tuned on parallel data from one or multiple …","url":["https://aclanthology.org/2023.loresmt-1.5.pdf"]}
-{"year":"2023","title":"Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior","authors":["A Khandelwal, A Agrawal, A Bhattacharyya, YK Singla… - arXiv preprint arXiv …, 2023"],"snippet":"… Consider the Common Crawl project1, one common source of data included in most language models; it produces more than 20TB of text … Similarly, while a lot of public blogs and user forums are included in major text corpora used in training …","url":["https://arxiv.org/pdf/2309.00359"]}
-{"year":"2023","title":"Large Data-to-Text Generation","authors":["V Sarangian - 2023"],"snippet":"This thesis presents a domain-driven approach to sports game summarization, a specific instance of large data-to-text generation (DTG). We first address the data fidelity issue in the Rotowire dataset by supplementing existing input records and …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19451/Sarangian_Varnan.pdf?sequence=1&isAllowed=y"]}
-{"year":"2023","title":"Large Graph Models: A Perspective","authors":["Z Zhang, H Li, Z Zhang, Y Qin, X Wang, W Zhu - arXiv preprint arXiv:2308.14522, 2023"],"snippet":"… This massive amount of data for NLP and CV tasks is typically sourced from publicly accessible human-generated content, such as web pages in CommonCrawl or user-posted photos in social media, which are easily collected from the web. …","url":["https://arxiv.org/pdf/2308.14522"]}
-{"year":"2023","title":"Large Language Models (LLM): Need, Methods, And Research Trends","authors":["RM Pir"],"snippet":"… Pre-training and fine-tuning: This technique involves pre-training a large model on a massive dataset, such as Wikipedia or Common Crawl, and then fine-tuning the model on a specific task, such as sentiment analysis or question answering. This …","url":["https://www.ijcspub.org/papers/IJCSP23A1262.pdf"]}
-{"year":"2023","title":"Large Language Models and Control Mechanisms Improve Text Readability of Biomedical Abstracts","authors":["Z Li, S Belkadi, N Micheletti, L Han, M Shardlow… - arXiv preprint arXiv …, 2023"],"snippet":"… The authors used the common crawl corpus and filtered to keep only natural text and de-duplication processing. They extracted 750GB of clean English data to feed into the model for multi-task pre-training. Different masking strategies are integrated …","url":["https://arxiv.org/pdf/2309.13202"]}
-{"year":"2023","title":"Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset","authors":["S Alavi Naeini, R Saqur, M Saeidi, J Giorgi, B Taati - Advances in Neural Information …, 2024","S Naeini, R Saqur, M Saeidi, J Giorgi, B Taati - arXiv preprint arXiv:2306.11167, 2023"],"snippet":"… We used two FastText models, one pre-trained on the Common Crawl corpus and another on Wikipedia. Approximately 10% of the total clues encountered in the dataset were out-of-vocabulary (OOV). A significant portion (~80%) of the OOV …","url":["https://arxiv.org/pdf/2306.11167","https://proceedings.neurips.cc/paper_files/paper/2023/file/11e3e0f1b29dcd31bd0952bfc1357f68-Paper-Datasets_and_Benchmarks.pdf"]}
-{"year":"2023","title":"Large Language Models Can Be Used to Estimate the Ideologies of Politicians in a Zero-Shot Learning Setting","authors":["PY Wu, JA Tucker, J Nagler, S Messing - arXiv preprint arXiv:2303.12057, 2023"],"snippet":"The mass aggregation of knowledge embedded in large language models (LLMs) holds the promise of new solutions to problems of observability and measurement in the social sciences. We examine the utility of one such model for a particularly …","url":["https://arxiv.org/pdf/2303.12057"]}
-{"year":"2023","title":"Large Language Models Can Be Used to Estimate the Latent Positions of Politicians","authors":["PY Wu, J Nagler, JA Tucker, S Messing"],"snippet":"Existing approaches to estimating politicians’ latent positions along specific dimensions often fail when relevant data is limited. We leverage the embedded knowledge in generative large language models (LLMs) to address this challenge …","url":["https://www.patrickywu.com/PatrickYWu_JMP1_LaMPscores.pdf"]}
-{"year":"2023","title":"Large language models in medicine","authors":["AJ Thirunavukarasu, DSJ Ting, K Elangovan… - Nature Medicine, 2023"],"snippet":"Large language models (LLMs) can respond to free-text queries without being specifically trained in the task in question, causing excitement and concern about their use in healthcare settings. ChatGPT is a generative artificial intelligence (AI) …","url":["https://www.nature.com/articles/s41591-023-02448-8"]}
-{"year":"2023","title":"Large Language Models Need Symbolic AI","authors":["K Hammond, D Leake - 2023"],"snippet":"… GPT-3 was trained on an extensive dataset, based on a version of the CommonCrawl dataset (with almost a trillion words) and additional reference sources. Given tasks and few-shot demonstrations provided to the system as text …","url":["https://ceur-ws.org/Vol-3432/paper17.pdf"]}
-{"year":"2023","title":"Large Language Models","authors":["M McTear, M Ashurkina - Transforming Conversational AI: Exploring the Power …, 2024","MR Douglas - arXiv preprint arXiv:2307.05782, 2023"],"snippet":"… The model was trained on the Common Crawl, a dataset of billions of words from web pages, and the Bookcorpus dataset, consisting of … The model was trained on a diverse dataset, including Common Crawl and WebText. GPT-2 was able to …","url":["https://arxiv.org/pdf/2307.05782","https://link.springer.com/chapter/10.1007/979-8-8688-0110-5_4"]}
-{"year":"2023","title":"Large Language Models' Understanding of Math: Source Criticism and Extrapolation","authors":["R Yousefzadeh, X Cao - arXiv preprint arXiv:2311.07618, 2023"],"snippet":"… Common Crawl is particularly interesting. The GPT-f model developed for mathematical learning was trained on 300 billion tokens from CommonCrawl… The size of the most recent CommonCrawl is 390 TiB including the contents of 3.1 billion …","url":["https://arxiv.org/pdf/2311.07618"]}
-{"year":"2023","title":"Large Language Models, scientific knowledge and factuality: A systematic analysis in antibiotic discovery","authors":["M Wysocka, O Wysocki, M Delmas, V Mutel, A Freitas - arXiv preprint arXiv …, 2023"],"snippet":"Inferring over and extracting information from Large Language Models (LLMs) trained on a large corpus of scientific literature can potentially drive a new era in biomedical research, reducing the barriers for accessing existing medical evidence …","url":["https://arxiv.org/pdf/2305.17819"]}
-{"year":"2023","title":"Large Scale Fine-Tuned Transformers Models Application for Business Names Generation","authors":["M Lukauskas, T Rasymas, M Minelga, D Vaitmonas - Computing and Informatics, 2023"],"snippet":"… on larger datasets, leading to pre-trained systems such as BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer), which have been trained on large language datasets such as the …","url":["https://www.cai.sk/ojs/index.php/cai/article/download/2023_3_525/1228"]}
-{"year":"2023","title":"Large Sentiment Dictionary of Russian Words","authors":["VV Bochkarev, AA Achkeev, AV Savinkov… - … International Conference on …, 2023"],"snippet":"… Vector sets for 157 languages, trained on the Common Crawl corpus using the most advanced word embedding algorithms at the time, were made publicly available in 2018. The great advantage of this dataset in terms of the tasks set in our …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47640-2_6"]}
-{"year":"2023","title":"Large Web Archive Collection Infrastructure and Services","authors":["X Wang - 2023"],"snippet":"… We use Common Crawl’s web archiving data crawled from May 20 to 23, 2018. The data set consists of 1219 Gzip compressed WARC files totaling 0.98 TB, and contains 53,324,440 records. The WARC files are organized by crawling time, each …","url":["https://vtechworks.lib.vt.edu/bitstream/handle/10919/113345/Wang_X_D_2023.pdf?sequence=1&isAllowed=y"]}
-{"year":"2023","title":"Large-scale Security Analysis of HTTP Responses","authors":["J Carbol, H Stegrell - 2023"],"snippet":"… In order to find vulnerabilities on a large scale, this thesis utilizes the crawl data from Common Crawl, an open repository of web crawl data. In this data, indicators of specific programs, software, or libraries are visible, allowing us to find vulnerable …","url":["http://odr.chalmers.se/bitstreams/8f327562-4385-4640-a3eb-ae07818230a5/download"]}
-{"year":"2023","title":"LASTING IMPACT: WHY YOU SHOULD CARE ABOUT COURT OF CUSTOMS AND PATENT APPEAL CASES","authors":["J Glendenning - 2023"],"snippet":"… sentence and understand that machine learning models like GPT-3 don't \"read\" like humans do, but rather ingest data sets like Common Crawl, which is made up of many written works … 2020) (explaining the use of the Common Crawl dataset in …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/aiplaqj51&section=3"]}
-{"year":"2023","title":"Lawyer LLaMA Technical Report","authors":["Q Huang, M Tao, Z An, C Zhang, C Jiang, Z Chen… - arXiv preprint arXiv …, 2023"],"snippet":"… On one hand, current LLMs are primarily trained on general corpora such as Common Crawl and Wikipedia, with limited exposure to domainspecific resources. Therefore, they lack the necessary knowledge required for specific domains. On the …","url":["https://arxiv.org/pdf/2305.15062"]}
-{"year":"2023","title":"LCTs at HODI: Homotransphobic Speech Detection on Italian Tweets","authors":["D Locatelli, L Locatelli - Proceedings of the Eighth Evaluation Campaign of …, 2023"],"snippet":"… -Commoncrawl-Cased version. Using the HuggingFace Transformers library [11], we applied a classification head on top of the model outputs, which enabled us to fine-tune the base model on the HODI data for Subtask A. The selection of the …","url":["https://ceur-ws.org/Vol-3473/paper30.pdf"]}
-{"year":"2023","title":"Learning Human-Human Interactions in Images from Weak Textual Supervision","authors":["M Alper, H Averbuch-Elor - arXiv preprint arXiv:2304.14104, 2023"],"snippet":"Interactions between humans are diverse and context-dependent, but previous works have treated them as categorical, disregarding the heavy tail of possible interactions. We propose a new paradigm of learning human-human interactions as …","url":["https://arxiv.org/pdf/2304.14104"]}
-{"year":"2023","title":"Learning Language-Specific Layers for Multilingual Machine Translation","authors":["TP Pires, RM Schmidt, YH Liao, S Peitz - arXiv preprint arXiv:2305.02665, 2023"],"snippet":"Multilingual Machine Translation promises to improve translation quality between non-English languages. This is advantageous for several reasons, namely lower latency (no need to translate twice), and reduced error cascades (eg, avoiding …","url":["https://arxiv.org/pdf/2305.02665"]}
-{"year":"2023","title":"Learning word embeddings for Ukrainian: A comparative study of fastText hyperparameters","authors":["N Romanyshyn, D Chaplynskyi, K Zakharov - Proceedings of the Second Ukrainian …, 2023"],"snippet":"… noisy data from the Common Crawl (CC) project4 for learning their word vectors. Another shortcoming is that they did not optimize subword … It was a deliberate decision not to include Common Crawl or Oscar13 corpora data into UberText because …","url":["https://aclanthology.org/2023.unlp-1.3.pdf"]}
-{"year":"2023","title":"Legal Governance of Internet Information Content in AIGC Era Taking Large Language Model as an Example","authors":["LI Mingxuan, WEN Jirong - Journal of Beijing Institute of Technology (Social …, 2023"],"snippet":"… 以 GPT-3,PaLM 和 LLaMa 这三个具有代表性的大语言模型为例,GPT-3 的预训练 数据包含 Common Crawl,WebText 2 和维基百科,PaLM 的预训练数据包含社交媒体 对话,过滤后的网页,Github, 多语言维基百科和新闻,LLaMa 的预训练数据包含 Common …","url":["http://journal.bit.edu.cn/sk/en/article/pdf/preview/10.15918/j.jbitss1009-3370.2023.1592.pdf"]}
-{"year":"2023","title":"Lemur: Harmonizing Natural Language and Code for Language Agents","authors":["Y Xu, H Su, C Xing, B Mi, Q Liu, W Shi, B Hui, F Zhou… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce Lemur and Lemur-Chat, openly accessible language models optimized for both natural language and coding capabilities to serve as the backbone of versatile language agents. The evolution from language chat models to …","url":["https://arxiv.org/pdf/2310.06830"]}
-{"year":"2023","title":"Let's Chat to Find the APIs: Connecting Human, LLM and Knowledge Graph through AI Chain","authors":["Q Huang, Z Wan, Z Xing, C Wang, J Chen, X Xu, Q Lu - arXiv preprint arXiv …, 2023"],"snippet":"… an analysis of undesirable content in the common crawl corpus. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2 …","url":["https://arxiv.org/pdf/2309.16134"]}
-{"year":"2023","title":"Let's Discover More API Relations: A Large Language Model-based AI Chain for Unsupervised API Relation Inference","authors":["Q Huang, Y Sun, Z Xing, Y Cao, J Chen, X Xu, H Jin… - arXiv preprint arXiv …, 2023"],"snippet":"… are pre-trained on the corpus of the entire Internet (Common Crawl [11]), which are referred to as foundation models [12]. As such foundation LLMs pack the knowledge of the entire Web, we are no longer limited to the scope of API text corpus …","url":["https://arxiv.org/pdf/2311.01266"]}
-{"year":"2023","title":"Leveraging Auxiliary Domain Parallel Data in Intermediate Task Fine-tuning for Low-resource Translation","authors":["S Nayak, S Ranathunga, S Thillainathan, R Hung… - arXiv preprint arXiv …, 2023"],"snippet":"NMT systems trained on Pre-trained Multilingual Sequence-Sequence (PMSS) models flounder when sufficient amounts of parallel data is not available for fine-tuning. This specifically holds for languages missing/under-represented in these models …","url":["https://arxiv.org/pdf/2306.01382"]}
-{"year":"2023","title":"Leveraging Closed-Access Multilingual Embedding for Automatic Sentence Alignment in Low Resource Languages","authors":["I Abdulmumin, AA Khalid, SH Muhammad, IS Ahmad… - arXiv preprint arXiv …, 2023"],"snippet":"… Using a similarity metric in that multimodal embedding space, they performed mining of audio in German, French, Spanish, and English from Librivox against billions of sentences from Common Crawl. This yielded more than twenty thousand …","url":["https://arxiv.org/pdf/2311.12179"]}
-{"year":"2023","title":"Leveraging Diffusion Perturbations for Measuring Fairness in Computer Vision","authors":["N Lui, B Chia, W Berrios, C Ross, D Kiela - arXiv preprint arXiv:2311.15108, 2023"],"snippet":"Computer vision models have been known to encode harmful biases, leading to the potentially unfair treatment of historically marginalized groups, such as people of color. However, there remains a lack of datasets balanced along demographic traits …","url":["https://arxiv.org/pdf/2311.15108"]}
-{"year":"2023","title":"Leveraging Domain Adaptation and Data Augmentation to Improve Qur'anic IR in English and Arabic","authors":["V Pavlova - arXiv preprint arXiv:2312.02803, 2023"],"snippet":"In this work, we approach the problem of Qur'anic information retrieval (IR) in Arabic and English. Using the latest state-of-the-art methods in neural IR, we research what helps to tackle this task more efficiently. Training retrieval models requires a lot of …","url":["https://arxiv.org/pdf/2312.02803"]}
-{"year":"2023","title":"Leveraging Feature Selection to Improve the Accuracy for Malware Detection","authors":["D Smith, S Khorsandroo, K Roy - 2023"],"snippet":"Malware is becoming increasingly sophisticated and difficult to detect with traditional monitoring tools and antivirus software. As a result, machine learning has become a popular approach for classifying and detecting malware-related data. In this study …","url":["https://www.researchsquare.com/article/rs-3045391/latest.pdf"]}
-{"year":"2023","title":"Leveraging Function Space Aggregation for Federated Learning at Scale","authors":["N Dhawan, N Mitchell, Z Charles, Z Garrett… - arXiv preprint arXiv …, 2023"],"snippet":"… C4 and CC-News are hosted by commoncrawl.org and we access both through HuggingFace datasets. … C4 The Colossal Clean Crawled Corpus (C4) dataset is a cleaned version of Common Crawl’s web crawl corpus (Raffel et al., 2020). We use …","url":["https://arxiv.org/pdf/2311.10291"]}
-{"year":"2023","title":"Leveraging Image-Text Similarity and Caption Modification for the DataComp Challenge: Filtering Track and BYOD Track","authors":["S Yokoo, P Zhu, Y Ishikawa, M Tanaka, M Kondo… - arXiv preprint arXiv …, 2023"],"snippet":"… DataComp provides a new candidate pool of 12.8B image-text pairs collected from Common Crawl. This challenge contains four distinct compute and data scales. In this work, we mainly focus on the small scale (12.8M samples). …","url":["https://arxiv.org/pdf/2310.14581"]}
-{"year":"2023","title":"Leveraging Prior Knowledge and Structure for Data-Efficient Machine Learning","authors":["B Gunel - 2022"],"snippet":"Building high-performing end-to-end machine learning systems primarily consists of developing the machine learning model and gathering high-quality training data for the application of interest, assuming one has access to the right hardware. Although …","url":["https://search.proquest.com/openview/02abeb62b4586808841b511d8c6b8891/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Leveraging supplementary text data to kick-start automatic speech recognition system development with limited transcriptions","authors":["N San, M Bartelds, B Billings, E de Falco, H Feriza… - arXiv preprint arXiv …, 2023"],"snippet":"Recent research using pre-trained transformer models suggests that just 10 minutes of transcribed speech may be enough to fine-tune such a model for automatic speech recognition (ASR) -- at least if we can also leverage vast amounts of text …","url":["https://arxiv.org/pdf/2302.04975"]}
-{"year":"2023","title":"LFWE: L inguistic F eature Based W ord E mbedding for Hindi Fake News Detection","authors":["R Sharma, A Arya - ACM Transactions on Asian and Low-Resource …, 2023"],"snippet":"It is essential for the research communities to investigate ways for authenticating news. The use of linguistic feature-based analysis to automatically detect false news is gaining popularity among the scientific community. However, such techniques are …","url":["https://dl.acm.org/doi/pdf/10.1145/3589764"]}
-{"year":"2023","title":"LibriSpeech-PC: Benchmark for Evaluation of Punctuation and Capitalization Capabilities of end-to-end ASR Models","authors":["A Meister, M Novikov, N Karpov, E Bakhturina… - arXiv preprint arXiv …, 2023"],"snippet":"… To enrich our LM model with more diverse examples of punctuation and capitalization, we download a random subset from the Common Crawl dataset [20]. The Common Crawl subset is 100 times bigger than LibriSpeech-PC and is normalized …","url":["https://arxiv.org/pdf/2310.02943"]}
-{"year":"2023","title":"Life-long phishing attack detection using continual learning","authors":["A Ejaz, AN Mian, S Manzoor - Scientific Reports, 2023"],"snippet":"… Also, FastText is trained on a common crawl dataset consisting of web pages related to our problem. Word2Vec and Glove are small and used for non-complex tasks, while ELMo and BERT are very complex models used for complex tasks. …","url":["https://www.nature.com/articles/s41598-023-37552-9"]}
-{"year":"2023","title":"Lightweb: Private web browsing without all the baggage","authors":["E Dauterman, H Corrigan-Gibbs - 2023"],"snippet":"This paper proposes lightweb, a new system for private browsing. A lightweb client can browse a web of textbased pages without revealing to anyone—not the network, not the servers hosting the pages—which pages it is reading. Unlike Tor and other …","url":["https://people.csail.mit.edu/henrycg/files/academic/papers/lightweb.pdf"]}
-{"year":"2023","title":"Limitations of democratic rights during the Covid-19 pandemic—exploring the citizens' perception and discussions on dangers to democracy in Germany","authors":["A Katsanidou, M Kneuer, F Bensmann, D Dimitrov… - Zeitschrift für Vergleichende …, 2023"],"snippet":"The governments’ mitigation measures to fight the COVID-19 pandemic are unprecedented in our post-war history. For overcoming this crisis, citizens were expected to act in compliance with these measures in order to control the spread of …","url":["https://link.springer.com/article/10.1007/s12286-023-00556-w"]}
-{"year":"2023","title":"Linear Mappings: Semantic Transfer from Transformer Models for Cognate Detection and Coreference Resolution","authors":["A Nath - 2022"],"snippet":"Embeddings or vector representations of language and their properties are useful for under-standing how Natural Language Processing technology works. The usefulness of embeddings, however, depends on how contextualized or information-rich …","url":["https://mountainscholar.org/bitstream/handle/10217/235958/Nath_colostate_0053N_17510.pdf?sequence=1"]}
-{"year":"2023","title":"Lingualyzer: A computational linguistic tool for multilingual and multidimensional text analysis","authors":["GM Linders, MM Louwerse - Behavior Research Methods, 2023"],"snippet":"… resources utilize large amounts of publicly available data in many languages, such as data coming from Wikipedia and Common Crawl. … We used the 300 dimensional fastText word vectors, which were created from Wikipedia and Common …","url":["https://link.springer.com/article/10.3758/s13428-023-02284-1"]}
-{"year":"2023","title":"Linking Representations with Multimodal Contrastive Learning","authors":["A Arora, X Yang, SY Jheng, M Dell - arXiv preprint arXiv:2304.03464, 2023"],"snippet":"… [52] find that GPT-3 performs substantially better on samples from ReCoRD that have near duplicates in RealNews, a subset of Common Crawl included in the GPT-3 training data, compared to those that did not. While most deduplication of noisy text …","url":["https://arxiv.org/pdf/2304.03464"]}
-{"year":"2023","title":"Literature Review: Challenges In Creating A Generic Model For Text Classification In Multiple Languages","authors":["R Sinha, R Srivastava - resmilitaris, 2023"],"snippet":"… Authors [60] used a dataset that included Wikipedia and Common Crawl to train the Skip-gram and CBOW word vector models. They also developed a quick language identifier that recognizes 176 different languages. While researchers [61]evaluated …","url":["https://resmilitaris.net/menu-script/index.php/resmilitaris/article/download/2911/2364"]}
-{"year":"2023","title":"LLaMA 2: The New Open Source Language Model","authors":["N Jayaseelan"],"snippet":"Language models have revolutionized the field of artificial intelligence, by enabling machines to understand and generate human-like text. Among the plethora of language models, LLaMA (Large Language Models AI) stands out as the latest …","url":["https://www.e2enetworks.com/blog/llama-2-the-new-open-source-language-model"]}
-{"year":"2023","title":"LLaMA: Open and Efficient Foundation Language Models","authors":["H Touvron, T Lavril, G Izacard, X Martinet, MA Lachaux… - arXiv preprint arXiv …, 2023"],"snippet":"… We preprocess five CommonCrawl dumps, ranging from 2017 to 2020, with the CCNet pipeline (… We expect these biases to come from CommonCrawl despite multiple filtering steps. … This allowed to train a 5-gram model on 975 billions tokens …","url":["https://arxiv.org/pdf/2302.13971"]}
-{"year":"2023","title":"LLEMMA: AN OPEN LANGUAGE MODEL FOR MATHEMATICS","authors":["Z Azerbayev, H Schoelkopf, K Paster, M Dos Santos… - Minerva"],"snippet":"We present LLEMMA, a large language model for mathematics. We continue pretraining Code Llama on Proof-Pile-2, a mixture of scientific papers, web data containing mathematics, and mathematical code, yielding LLEMMA. On the MATH …","url":["https://arxiv.org/pdf/2310.10631"]}
-{"year":"2023","title":"LLM Self Defense: By Self Examination, LLMs Know They Are Being Tricked","authors":["A Helbling, M Phute, M Hull, DH Chau - arXiv preprint arXiv:2308.07308, 2023"],"snippet":"Large language models (LLMs) have skyrocketed in popularity in recent years due to their ability to generate high-quality text in response to human prompting. However, these models have been shown to have the potential to generate harmful content in …","url":["https://arxiv.org/pdf/2308.07308"]}
-{"year":"2023","title":"LLM's for Spanish Song Text Analysis and Classification Using Language Variants","authors":["O García-Vázquez, T Alcántara, H Calvo, G Sidorov - … International Conference on …, 2023"],"snippet":"… The results show that tweets are the best for song lyrics analysis, while Google News and Common Crawl are the best for movie analysis, since the vocabulary that used in these portals is very similar in both cases. Models trained with GLoVe …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47640-2_10"]}
-{"year":"2023","title":"LLM-augmented Preference Learning from Natural Language","authors":["I Kang, S Ruan, T Ho, JC Lin, F Mohsin, O Seneviratne… - arXiv preprint arXiv …, 2023"],"snippet":"… The authors query for sentences that contain mentions of both alternatives from the Common Crawl dataset and present a final dataset of 7,199 sentences with 217 unique pairs of alternatives and 3 classes – 𝐴 ≻ 𝐵, 𝐴 ≺ 𝐵, N/A. Because of the …","url":["https://arxiv.org/pdf/2310.08523"]}
-{"year":"2023","title":"LLM-QAT: Data-Free Quantization Aware Training for Large Language Models","authors":["Z Liu, B Oguz, C Zhao, E Chang, P Stock, Y Mehdad… - arXiv preprint arXiv …, 2023"],"snippet":"Several post-training quantization methods have been applied to large language models (LLMs), and have been shown to perform well down to 8-bits. We find that these methods break down at lower bit precision, and investigate quantization …","url":["https://arxiv.org/pdf/2305.17888"]}
-{"year":"2023","title":"LLM-RM at SemEval-2023 Task 2: Multilingual Complex NER using XLM-RoBERTa","authors":["R Mehta, V Varma - arXiv preprint arXiv:2305.03300, 2023"],"snippet":"Named Entity Recognition(NER) is a task of recognizing entities at a token level in a sentence. This paper focuses on solving NER tasks in a multilingual setting for complex named entities. Our team, LLM-RM participated in the recently organized …","url":["https://arxiv.org/pdf/2305.03300"]}
-{"year":"2023","title":"LLM360: Towards Fully Transparent Open-Source LLMs","authors":["Z Liu, A Qiao, W Neiswanger, H Wang, B Tan, T Tao… - arXiv preprint arXiv …, 2023"],"snippet":"The recent surge in open-source Large Language Models (LLMs), such as LLaMA, Falcon, and Mistral, provides diverse options for AI practitioners and researchers. However, most LLMs have only released partial artifacts, such as the final model …","url":["https://arxiv.org/pdf/2312.06550"]}
-{"year":"2023","title":"LLMs: A Promising New Tool for Improving Healthcare in Low-Resource Nations","authors":["A Gangavarapu - 2023 IEEE Global Humanitarian Technology …, 2023"],"snippet":"This paper explores the potential of large language models (LLMs) in addressing healthcare inequalities, particularly in underserved nations with provider shortages, limited resources, and funding constraints. The UN’s Sustainable Development Goal …","url":["https://ieeexplore.ieee.org/abstract/document/10354650/"]}
-{"year":"2023","title":"LMU at HaSpeeDe3: Multi-Dataset Training for Cross-Domain Hate Speech Detection","authors":["V Hangya, A Fraser - 2023"],"snippet":"We describe LMU Munich’s hate speech detection system for participating in the cross-domain track of the HaSpeeDe3 shared task at EVALITA 2023. The task focuses on the politics and religion domains, having no in-domain training data for …","url":["https://ceur-ws.org/Vol-3473/paper24.pdf"]}
-{"year":"2023","title":"Logical definition-based identification of potential missing concepts in SNOMED CT","authors":["X Hao, R Abeysinghe, K Roberts, L Cui - BMC Medical Informatics and Decision …, 2023"],"snippet":"Biomedical ontologies are representations of biomedical knowledge that provide terms with precisely defined meanings. They play a vital role in facilitating biomedical research in a cross-disciplinary manner. Quality issues of biomedical …","url":["https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-023-02183-7"]}
-{"year":"2023","title":"Long Form Question Answering Dataset Creation for Business Use Cases using Noise-Added Siamese-BERT","authors":["T Cekiç, Y Manav, B Helvacıoglu, EB Dündar, O Deniz… - 2022"],"snippet":"… To generate related documents, they use a TFIDF retriever on the CommonCrawl web dump, to retrieve related documents and combine all documents related parts to generate one supporting document.In the KILT (Petroni et al., 2021) benchmark …","url":["https://www.scitepress.org/Papers/2022/115509/115509.pdf"]}
-{"year":"2023","title":"LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery","authors":["T Chen, T Ding, B Yadav, I Zharkov, L Liang"],"snippet":"Large Language Models (LLMs) have transformed the landscape of artificial intelligence, while their enormous size presents significant challenges in terms of computational costs. We introduce LoRAShear, a novel efficient approach to …","url":["https://www.researchgate.net/profile/Tianyi-Chen-36/publication/374945275_LoRAShear_Efficient_Large_Language_Model_Structured_Pruning_and_Knowledge_Recovery/links/65382b2873a2865c7ad0f1a4/LoRAShear-Efficient-Large-Language-Model-Structured-Pruning-and-Knowledge-Recovery.pdf"]}
-{"year":"2023","title":"Lost in Translation: Large Language Models in Non-English Content Analysis","authors":["G Nicholas, A Bhatia - arXiv preprint arXiv:2306.07377, 2023"],"snippet":"In recent years, large language models (eg, Open AI's GPT-4, Meta's LLaMa, Google's PaLM) have become the dominant approach for building AI systems to analyze and generate language online. However, the automated systems that …","url":["https://arxiv.org/pdf/2306.07377"]}
-{"year":"2023","title":"Low Resource Summarization using Pre-trained Language Models","authors":["M Munaf, H Afzal, N Iltaf, K Mahmood - arXiv preprint arXiv:2310.02790, 2023"],"snippet":"With the advent of Deep Learning based Artificial Neural Networks models, Natural Language Processing (NLP) has witnessed significant improvements in textual data processing in terms of its efficiency and accuracy. However, the research is mostly …","url":["https://arxiv.org/pdf/2310.02790"]}
-{"year":"2023","title":"Low-Resource Cross-Lingual Adaptive Training for Nigerian Pidgin","authors":["PJ Lin, M Saeed, E Chang, M Scholman - arXiv preprint arXiv:2307.00382, 2023"],"snippet":"Developing effective spoken language processing systems for low-resource languages poses several challenges due to the lack of parallel data and limited resources for fine-tuning models. In this work, we target on improving upon both text …","url":["https://arxiv.org/pdf/2307.00382"]}
-{"year":"2023","title":"Low-resource image captioning","authors":["M Du Plessis - 2022"],"snippet":"… The language model is pretrained on the colossal clean crawled corpus (C4), which is a cleaned version of the common crawl dataset [70] and consists of 700 GB of unlabelled text. The cleaning applications include removing non-English text …","url":["https://scholar.sun.ac.za/bitstream/handle/10019.1/126059/duplessis_low_2022.pdf?sequence=1"]}
-{"year":"2023","title":"LSTM-Based Encoder–Decoder Attention Model for Text Translation and Simplification on the Constitution of India","authors":["M Navlakha, R Lobo, R Bhargava, RB Karani - … in Computing: ICRIC 2022, Volume 2, 2023"],"snippet":"Natural language processing techniques can be used on judicial and legislative documents like the Constitution for making it more accessible to the general audience. Various approaches such as Natural Machine Translation (NMT), text …","url":["https://link.springer.com/chapter/10.1007/978-981-99-0601-7_64"]}
-{"year":"2023","title":"LT at SemEval-2023 Task 1: Effective Zero-Shot Visual Word Sense Disambiguation Approaches using External Knowledge Sources","authors":["F Schneider, C Biemann"],"snippet":"… Further, we assessed the suitability of three external knowledge sources: Wikipedia, a large-scale English Common Crawl corpus, and the multi-modal knowledge graph VisualSem. Our best-performing approach involved the Common …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2023-schneider-et-al-semeval-task-1-vwsd.pdf"]}
-{"year":"2023","title":"M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models","authors":["W Zhang, SM Aljunied, C Gao, YK Chia, L Bing - arXiv preprint arXiv:2306.05179, 2023"],"snippet":"… We rank languages by their ratio in the CommonCrawl corpus, which is a widely-used data source for training LLMs. It can be observed that our selected languages span a wide range, from high-resource languages like English and Chinese, to extremely …","url":["https://arxiv.org/pdf/2306.05179"]}
-{"year":"2023","title":"MA-INF 4328","authors":["DRE DEMIDOVA"],"snippet":"… • GeoVectors adopts the 300-dimensional English word vectors trained on the Common Crawl, and Wikipedia …","url":["https://www.lostinthe.cloud/Spatial/STDA12-Geographic%20Entity%20Linking.pdf"]}
-{"year":"2023","title":"MACEDONIZER-The Macedonian Transformer Language Model","authors":["J Dobreva, T Pavlov, K Mishev, M Simjanoska… - International Conference on …, 2022"],"snippet":"Contextualized language models are becoming omnipresent in the field of Natural Language Processing (NLP). Their learning representation capabilities show dominant results in almost all downstream NLP tasks. The main challenge that low-resource …","url":["https://link.springer.com/chapter/10.1007/978-3-031-22792-9_5"]}
-{"year":"2023","title":"Machine learning and Bayesian inference in nuclear fusion research: an overview","authors":["A Pavone, A Merlo, S Kwak, J Svensson - Plasma Physics and Controlled Fusion, 2023"],"snippet":"This article reviews applications of Bayesian inference and machine learning in nuclear fusion research. Current and next-generation nuclear fusion experiments require analysis and modelling efforts that integrate different models consistently …","url":["https://iopscience.iop.org/article/10.1088/1361-6587/acc60f/pdf"]}
-{"year":"2023","title":"Machine Learning and Collective Unintelligence","authors":["E Fournier-Tombs - Gender Reboot: Reprogramming Gender Rights in the …, 2023"],"snippet":"… The Common Crawl data, which is a sizable collection of articles pulled from the Internet (as its name suggests), is well known for having significant gender bias. WebText is a very comparable data source that was also created by OpenAI by web …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41390-2_9"]}
-{"year":"2023","title":"Machine Learning and Knowledge Discovery in Databases: Research Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023 …","authors":["D Koutra, C Plant, MG Rodriguez, E Baralis, F Bonchi - 2023"],"snippet":"The multi-volume set LNAI 14169 until 14175 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, in September 2023 …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=RYDXEAAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=OkkriZylPk&sig=cgEvn9s2ibUQ-Y4Bnh_3e_AbxWU"]}
-{"year":"2023","title":"Machine Learning for Malicious URL Classification: A Temporal Analysis","authors":["EN Wehr - 2024"],"snippet":"When Machine Learning (ML) is applied to labelled datasets, it is standard practice that 70% of the dataset is used for training models, with 30% used for testing. That approach assumes the dataset does not change over time. This praxis makes the …","url":["https://search.proquest.com/openview/046bd0f2e3b912dcc732f0f7e3e4772f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"MACHINE LEARNING IN CYBERSECURITY: COMPREHENSIVE ANALYSIS AND DETECTION OF URL PHISHING ATTACKS","authors":["B Patel - Journal of Research Administration, 2023"],"snippet":"In the face of escalating cyber threats, particularly phishing attacks, this research provides a comprehensive analysis of machine learning techniques for effective phishing URL detection. Leveraging a meticulously curated dataset comprising …","url":["https://journalra.org/index.php/jra/article/download/417/226"]}
-{"year":"2023","title":"Machine Learning Insights into Multifaceted Social Impacts on Global Urban Slum Population","authors":["S Shan - 2023"],"snippet":"The growth of the urban slum population proportion highlights the extent of urban inequality. This article uses machine learning to surpass the limitations of traditional static linear regression models. By handling large data volumes and uncovering …","url":["https://www.researchsquare.com/article/rs-3137402/latest.pdf"]}
-{"year":"2023","title":"Machine Learning Model for Paraphrases Detection Based on Text Content Pair Binary Classification","authors":["N Kholodna, V Vysotska, O Markiv, S Chyrun"],"snippet":"This article dwells process of ML-model development for detecting paraphrasing by binary classification of texts pair. For this study, the following semantic similarity metrics or indicators have been selected as features: Jacquard coefficient for shared …","url":["https://ceur-ws.org/Vol-3312/paper23.pdf"]}
-{"year":"2023","title":"Machine Learning on Knowledge Graphs for Health applications.","authors":["D Scala"],"snippet":"In the past decade, many impressive results have been reported for machine learning (ML) tools that are developed to assist in clinical decision making. However, translating these largely theoretical achievements to realistic settings remains a …","url":["https://picuslab.dieti.unina.it/images/pdfs/_TESI__DOROTEA_SCALA.pdf"]}
-{"year":"2023","title":"Machine Learning-Based Phishing Detection Using URL Features: A Comprehensive Review","authors":["AUZ Asif, H Shirazi, I Ray - International Symposium on Stabilizing, Safety, and …, 2023"],"snippet":"… Common Crawl is a large-scale web crawl that is made up of petabytes of data that have been collected since 2008. It includes raw web page data, extracted metadata, and text extractions. This repository’s material is maintained in Web …","url":["https://link.springer.com/chapter/10.1007/978-3-031-44274-2_36"]}
-{"year":"2023","title":"Machine translation and its evaluation: a study","authors":["SK Mondal, H Zhang, HMD Kabir, K Ni, HN Dai - Artificial Intelligence Review, 2023"],"snippet":"Abstract Machine translation (namely MT) has been one of the most popular fields in computational linguistics and Artificial Intelligence (AI). As one of the most promising approaches, MT can potentially break the language barrier of people from all over …","url":["https://link.springer.com/article/10.1007/s10462-023-10423-5"]}
-{"year":"2023","title":"Machine visions: Mapping depictions of machine vision through critical image synthesis","authors":["R Carter, RA Carter - Open Library of Humanities, 2023"],"snippet":"This paper conducts a speculative examination of how AI image synthesisers, which generate novel imagery in response to inputted textual prompts – such as DALL-E, Midjourney, and Stable Diffusion – can be employed reflexively to investigate …","url":["https://olh.openlibhums.org/articles/10.16995/olh.10077/"]}
-{"year":"2023","title":"Machine-Assisted Social Psychology Hypothesis Generation","authors":["S Banker, P Chatterjee, H Mishra, A Mishra - 2023"],"snippet":"… GPT-3 was developed by OpenAI and has been trained on several large text corpora such as Common Crawl, Wikipedia, digitized books, WebText2 (which is based on Reddit posts), etc., amounting to about 45 terabytes of training data. GPT-3 …","url":["https://psyarxiv.com/kv6f7/download?format=pdf"]}
-{"year":"2023","title":"MADLAD-400: A Multilingual And Document-Level Large Audited Dataset","authors":["S Kudugunta, I Caswell, B Zhang, X Garcia… - arXiv preprint arXiv …, 2023"],"snippet":"… We introduce MADLAD-400, a manually audited, general domain 3T token monolingual dataset based on CommonCrawl, spanning 419 languages. We discuss the limitations revealed by self-auditing MADLAD-400, and the role data auditing had in …","url":["https://arxiv.org/pdf/2309.04662"]}
-{"year":"2023","title":"MahaEmoSen: Towards Emotion-aware Multimodal Marathi Sentiment Analysis","authors":["P Chaudhari, P Nandeshwar, S Bansal, N Kumar - ACM Transactions on Asian and …, 2023"],"snippet":"… It is a BERT-based model trained on PMINDIA [13], commoncrawl [14], Wikipedia3, Dakshina corpus [15] for 17 diferent Indic languages like Hindi, Marathi, Tamil etc. It is also trained on … Total of 100 languages from CommonCrawl data were used as …","url":["https://dl.acm.org/doi/pdf/10.1145/3618057"]}
-{"year":"2023","title":"Make PDF safe again","authors":["K DORNER"],"snippet":"Malware is an ever-present problem, and while most people are aware that executable files can be dangerous, other file formats are deemed as trustworthy and safe. One of these file formats is PDF. Billions of PDF files are created each day and …","url":["https://phaidra.fhstp.ac.at/detail/o:5121.pdf"]}
-{"year":"2023","title":"Making Changes in Webpages Discoverable: A Change-Text Search Interface for Web Archives","authors":["L Frew, ML Nelson, MC Weigle - arXiv preprint arXiv:2305.00546, 2023"],"snippet":"Webpages change over time, and web archives hold copies of historical versions of webpages. Users of web archives, such as journalists, want to find and view changes on webpages over time. However, the current search interfaces for web …","url":["https://arxiv.org/pdf/2305.00546"]}
-{"year":"2023","title":"Man vs the machine: The Struggle for Effective Text Anonymisation in the Age of Large Language Models","authors":["C Patsakis, N Lykousas - arXiv preprint arXiv:2303.12429, 2023"],"snippet":"… According to OpenAI, the training data for GPT-3 includes various sources such as books, articles, and websites, with a primary source being the Common Crawl2, a repository of web pages and documents that is regularly updated and maintained …","url":["https://arxiv.org/pdf/2303.12429"]}
-{"year":"2023","title":"Man vs. Machine: An applied study comparing a man-made lexicon, a machine learned lexicon, and OpenAI's GPT for sentiment analysis.","authors":["MA Alexandersen, J Rutlin - 2023"],"snippet":"Sentiment analysis, at scale, has become an essential tool in the methodological toolbox of finance. In this thesis, we construct a sentiment lexicon using a supervised machine learning model by Taddy (2013) and compare it to the traditional finance …","url":["https://openaccess.nhh.no/nhh-xmlui/bitstream/handle/11250/3088766/masterthesis.pdf?sequence=1"]}
-{"year":"2023","title":"Mapping Language Literacy At Scale: A Case Study on Facebook","authors":["YR Lin, S Wu, W Mason - arXiv preprint arXiv:2303.12179, 2023"],"snippet":"Literacy is one of the most fundamental skills for people to access and navigate today's digital environment. This work systematically studies the language literacy skills of online populations for more than 160 countries and regions across the world …","url":["https://arxiv.org/pdf/2303.12179"]}
-{"year":"2023","title":"MARGEN: Marathi Question Answering Generative Conversation Model","authors":["SV Bhalshankar, RR Deshmukh - … Conference on Applications of Machine Intelligence …, 2023"],"snippet":"The conversational system aka chatbot market capture was worth USD 526 million in 2021 around the world. The innovations created such as Machine learning, Deep learning, Natural Language Processing (NLP), and Big data analytics have given a …","url":["https://www.atlantis-press.com/article/125986308.pdf"]}
-{"year":"2023","title":"Massively Multi-Lingual Event Understanding: Extraction, Visualization, and Search","authors":["C Jenkins, S Agarwal, J Barry, S Fincke, E Boschee - arXiv preprint arXiv:2305.10561, 2023"],"snippet":"In this paper, we present ISI-Clear, a state-of-the-art, cross-lingual, zero-shot event extraction system and accompanying user interface for event visualization & search. Using only English training data, ISI-Clear makes global events available on-demand …","url":["https://arxiv.org/pdf/2305.10561"]}
-{"year":"2023","title":"MatSciRE: Leveraging pointer networks to automate entity and relation extraction for material science knowledge-base construction","authors":["A Mullick, A Ghosh, GS Chaitanya, S Ghui, T Nayak… - Computational Materials …, 2024"],"snippet":"Material science literature is a rich source of factual information about various categories of entities (like materials and compositions) and various relations between these entities, such as conductivity, voltage, etc. Automatically extracting …","url":["https://www.sciencedirect.com/science/article/pii/S0927025623006535"]}
-{"year":"2023","title":"Mazen ALSAREM","authors":["SS via Query-Biased"],"snippet":"In our knowledge-driven society, the acquisition and the transfer of knowledge play a principal role. Web search engines are somehow tools for knowledge acquisition and transfer from the web to the user. The search engine results page (SERP) …","url":["https://hal.science/tel-01327769v1/preview/Thesis.pdf"]}
-{"year":"2023","title":"MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods","authors":["M Finkelstein, M Freitag - arXiv preprint arXiv:2309.10966, 2023"],"snippet":"… For that, we take a random sample of 200,000 English sentences from Common Crawl1. … Phase 2 MBR and QE finetuning from the base checkpoint on the larger Common Crawl … on either self-QE-Common-Crawl or self-MBRCommon-Crawl …","url":["https://arxiv.org/pdf/2309.10966"]}
-{"year":"2023","title":"MCPG: A Flexible Multi-Level Controllable Framework for Unsupervised Paraphrase Generation","authors":["Y Chen, H Jiang, L Liu, R Wang, S Shi, R Xu - Findings of the Association for …, 2022"],"snippet":"We present MCPG: a simple and effectiveapproach for controllable unsupervised paraphrase generation, which is also flexible toadapt to specific domains without extra training. MCPG is controllable in different levels: local lexicons, global …","url":["https://aclanthology.org/2022.findings-emnlp.439.pdf"]}
-{"year":"2023","title":"MCTS: A Multi-Reference Chinese Text Simplification Dataset","authors":["R Chong, L Lu, L Yang, J Nie, S Zhou, Y Li, E Yang - arXiv preprint arXiv:2306.02796, 2023"],"snippet":"Text simplification aims to make the text easier to understand by applying rewriting transformations. There has been very little research on Chinese text simplification for a long time. The lack of generic evaluation data is an essential reason for this …","url":["https://arxiv.org/pdf/2306.02796"]}
-{"year":"2023","title":"Measuring and Evading Turkmenistan's Internet Censorship","authors":["SNVTX Jiang, K Bock, N Feamster, NP Hoang, D Levin - 2023"],"snippet":"… As shown in Figure 2, the payload of our probes contains domains curated from the Citizen Lab lists [5], the full Tranco list [42], and Common Crawl Project [8]. Due to limited resources of our VPS, we opt to probe the frst 10M FQDNs ranked by the …","url":["https://www.cs.umd.edu/users/dml/papers/tm_www23.pdf"]}
-{"year":"2023","title":"Measuring and Evading Turkmenistan's Internet Censorship: A Case Study in Large-Scale Measurements of a Low-Penetration Country","authors":["S Nourin, V Tran, X Jiang, K Bock, N Feamster… - arXiv preprint arXiv …, 2023"],"snippet":"… [5], the full Tranco list [42] of most popular websites, and Common Crawl Project [8]. Due to limited resources of our VPS, we opt to probe the first 10M FQDNs ranked by the Common Crawl Project instead of the full list of almost 400M FQDNs. The …","url":["https://arxiv.org/pdf/2304.04835"]}
-{"year":"2023","title":"Measuring Gender Bias in West Slavic Language Models","authors":["S Martinková, KSI Augenstein - arXiv preprint arXiv:2304.05783, 2023"],"snippet":"Pre-trained language models have been known to perpetuate biases from the underlying datasets to downstream tasks. However, these findings are predominantly based on monolingual language models for English, whereas there …","url":["https://arxiv.org/pdf/2304.05783"]}
-{"year":"2023","title":"Measuring Normative and Descriptive Biases in Language Models Using Census Data","authors":["S Touileb, L Øvrelid, E Velldal - arXiv preprint arXiv:2304.05764, 2023"],"snippet":"We investigate in this paper how distributions of occupations with respect to gender is reflected in pre-trained language models. Such distributions are not always aligned to normative ideals, nor do they necessarily reflect a descriptive assessment …","url":["https://arxiv.org/pdf/2304.05764"]}
-{"year":"2023","title":"Medical knowledge-enhanced prompt learning for diagnosis classification from clinical text","authors":["Y Lu, X Zhao, J Wang - Proceedings of the 5th Clinical Natural Language …, 2023"],"snippet":"Artificial intelligence based diagnosis systems have emerged as powerful tools to reform traditional medical care. Each clinician now wants to have his own intelligent diagnostic partner to expand the range of services he can provide. When reading a …","url":["https://aclanthology.org/2023.clinicalnlp-1.33.pdf"]}
-{"year":"2023","title":"MedMine: Examining Pre-trained Language Models on Medication Mining","authors":["H Alrdahi, L Han, H Šuvalov, G Nenadic - arXiv preprint arXiv:2308.03629, 2023"],"snippet":"Automatic medication mining from clinical and biomedical text has become a popular topic due to its real impact on healthcare applications and the recent development of powerful language models (LMs). However, fully-automatic …","url":["https://arxiv.org/pdf/2308.03629"]}
-{"year":"2023","title":"MEE4 and XLsim: IIIT HYD's Submissions' for WMT23 Metrics Shared Task","authors":["A Mukherjee, M Shrivastava - Proceedings of the Eighth Conference on Machine …, 2023"],"snippet":"This paper presents our contributions to the WMT2023 shared metrics task, consisting of two distinct evaluation approaches: a) Unsupervised Metric (MEE4) and b) Supervised Metric (XLSim). MEE4 represents an unsupervised, reference-based …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.66.pdf"]}
-{"year":"2023","title":"Meet in the Middle: A New Pre-training Paradigm","authors":["A Nguyen, N Karampatziakis, W Chen - arXiv preprint arXiv:2303.07295, 2023"],"snippet":"… • CC-Stories contains a subset of CommonCrawl data filtered to match the story-like style of Winograd schemas (31GB). • CC-100 is a dataset extracted from CommonCrawl snapshots between January 2018 and December 2018, filtered to …","url":["https://arxiv.org/pdf/2303.07295"]}
-{"year":"2023","title":"MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers","authors":["L Yu, D Simig, C Flaherty, A Aghajanyan, L Zettlemoyer… - arXiv preprint arXiv …, 2023"],"snippet":"Autoregressive transformers are spectacular models for short sequences but scale poorly to long sequences such as high-resolution images, podcasts, code, or books. We proposed Megabyte, a multi-scale decoder architecture that enables end-to-end …","url":["https://arxiv.org/pdf/2305.07185"]}
-{"year":"2023","title":"MELA: Multilingual Evaluation of Linguistic Acceptability","authors":["Z Zhang, Y Liu, W Huang, J Mao, R Wang, H Hu - arXiv preprint arXiv:2311.09033, 2023"],"snippet":"Recent benchmarks for Large Language Models (LLMs) have mostly focused on application-driven tasks such as complex reasoning and code generation, and this has led to a scarcity in purely linguistic evaluation of LLMs. Against this background …","url":["https://arxiv.org/pdf/2311.09033"]}
-{"year":"2023","title":"Memorization of Named Entities in Fine-Tuned BERT Models","authors":["A Diera, N Lell, A Garifullina, A Scherp - International Cross-Domain Conference for …, 2023"],"snippet":"… During prompt creation, we sampled a string with a character length of 100 either from the Common Crawl dataset (naive prompting) or from the test set (informed prompting). We set the sequence length to 256 tokens. We removed the tokens of …","url":["https://link.springer.com/chapter/10.1007/978-3-031-40837-3_16"]}
-{"year":"2023","title":"Method for Sentiment Analysis of Ukrainian-Language Reviews in E-Commerce Using RoBERTa Neural Network","authors":["O Zalutska, M Molchanova, O Sobko, O Mazurets… - 2023"],"snippet":"… This layer is based on the pre-trained model \"xlm_roberta_multi_cased_L-12_H-768_A-12\" [41], which is the result of unsupervised crosslanguage representative training at scale (XLM-RoBERTa) [41] and is pre-trained on 2.5 TB of filtered CommonCrawl …","url":["https://ceur-ws.org/Vol-3387/paper26.pdf"]}
-{"year":"2023","title":"Methods for Leveraging Auxiliary Signals for Low-Resource NLP","authors":["X Dong - 2023"],"snippet":"… The standard pre-trained word vectors used for English are the GloVe [69] ones trained on 840 billion tokens of Common Crawl data1, while for other languages, we rely on the Facebook fastText Wikipedia embeddings [76] as input representations …","url":["https://search.proquest.com/openview/6606bd82987b987846b711ddeee598e8/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Methods for Text Generation in NLP","authors":["S Matwin, A Milios, P Prałat, A Soares, F Théberge - Generative Methods for Social …, 2023"],"snippet":"… RoBERTa incorporates far more training data than the original BERT, using the Book Corpus and English Wikipedia datasets from the original paper, but adds several additional datasets for further training (CommonCrawl News, CommonCrawl Stories 6…","url":["https://link.springer.com/chapter/10.1007/978-3-031-33617-1_3"]}
-{"year":"2023","title":"Mini But Mighty: Efficient Multilingual Pretraining with Linguistically-Informed Data Selection","authors":["T Ogunremi, D Jurafsky, CD Manning - Findings of the Association for Computational …, 2023"],"snippet":"With the prominence of large pretrained language models, low-resource languages are rarely modelled monolingually and become victims of the “curse of multilinguality” in massively multilingual models. Recently, AfriBERTa showed that training …","url":["https://aclanthology.org/2023.findings-eacl.93.pdf"]}
-{"year":"2023","title":"Mining Electronic Health Records: Turning Unstructured Text into Research Data Using Natural Language Processing","authors":["MS Laursen - 2023"],"snippet":"The electronic health record (EHR) contains a detailed account of the patients’ medical history and is an important source of clinical research data. It is estimated that 80% of the information in the EHR is unstructured and this complicates locating …","url":["https://portal.findresearcher.sdu.dk/files/243587681/PhD_dissertation_Martin_Laursen_Redacted.pdf"]}
-{"year":"2023","title":"Mining Parallel Sentences from Internet with Multi-view Knowledge Distillation for Low-resource Language Pairs","authors":["S Zhu, S Li, S Gu, L Xu - 2023"],"snippet":"… For the future, we will increase the number of mining data by crawling common crawl platform and focus on more low-resource language pairs. The large amount of parallel data also attracts interesting attention how to use it best. Therefore, we will …","url":["https://www.researchsquare.com/article/rs-2817043/latest.pdf"]}
-{"year":"2023","title":"Misinformation Detection in the Wild: News Source Classification as a Proxy for Non-article Texts","authors":["M Bohacek - Proceedings of the Second Workshop on NLP for …, 2022"],"snippet":"… To first obtain URLs of sites with individual articles from those domains, we used the Commoncrawl API 2. We specified for the API to include only articles discovered between January 2019 and September 2021. Once these were obtained, we …","url":["https://aclanthology.org/2022.nlp4pi-1.10.pdf"]}
-{"year":"2023","title":"ML and DL-based Phishing Website Detection: The Effects of Varied Size Datasets and Informative Feature Selection Techniques","authors":["K Adane, B Beyene, M Abebe - Journal of Artificial Intelligence and Technology, 2023"],"snippet":"One must interact with a specific webpage or website in order to use the Internet for communication, teamwork, and other productive activities. However, because phishing websites look benign and not all website visitors have the same knowledge …","url":["https://ojs.istp-press.com/jait/article/download/269/274"]}
-{"year":"2023","title":"Modeling Brain Representations of Words' Concreteness in Context Using GPT‐2 and Human Ratings","authors":["A Bruera, Y Tao, A Anderson, D Çokal, J Haber… - Cognitive Science, 2023"],"snippet":"The meaning of most words in language depends on their context. Understanding how the human brain extracts contextualized meaning, and identifying where in the brain this takes place, remain important scientific challenges. But technological and …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1111/cogs.13388"]}
-{"year":"2023","title":"Modeling Sequential Sentence Relation to Improve Cross-lingual Dense Retrieval","authors":["S Zhang, Y Liang, M Gong, D Jiang, N Duan - arXiv preprint arXiv:2302.01626, 2023"],"snippet":"… (2019), we collect a clean version of Common Crawl (CC) including a 2,500GB multi-lingual corpus covering 108 languages, which adopt the same pre-processing method as XLMR (Conneau et al., 2019). Note that we only train on CC without any …","url":["https://arxiv.org/pdf/2302.01626"]}
-{"year":"2023","title":"Modelling an Efficient URL Phishing Detection Approach Based on a Dense Network Model.","authors":["AA Tenis, R Santhosh - Computer Systems Science & Engineering, 2023"],"snippet":"… The PhishTank provides the URLs for phishing to be gathered, and the Common Crawl provides the legal URLs. The LSTM technique … The repositories of Common Crawl and PhishTank provide the dataset to be gathered. A deep belief network (DBN) …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=02676192&AN=169779920&h=WGjAKpK7ACB1ZcUfp8Ikhm9IcDPjsbjptgyhA5ityW47Z2oYK4JmZTEMhj6t1UhLOFgbraBWyMgS1NID6mz%2BcA%3D%3D&crl=c"]}
-{"year":"2023","title":"Modern Applications With a Focus on Training ChatGPT and GPT Models: Exploring Generative AI and NLP","authors":["I Kondurkar, A Raj, D Lakshmi - Advanced Applications of Generative AI and Natural …, 2024"],"snippet":"Generative AI (GAI) and natural language processing (NLP) have emerged as the most exciting and rapidly growing fields in artificial intelligence (AI). This book chapter provides a comprehensive exploration of the advanced applications of GAI …","url":["https://www.igi-global.com/chapter/modern-applications-with-a-focus-on-training-chatgpt-and-gpt-models/335839"]}
-{"year":"2023","title":"Modular DiffPruning for Bias Mitigation","authors":["J KEPLER"],"snippet":"… They can leverage unlabelled text data which is available in large amounts on the internet and is collected by projects such as common crawl.Unsurprisingly raw text data crawled from the internet often contains bias towards different groups [3, 4] …","url":["https://epub.jku.at/obvulihs/download/pdf/8342002?originalFilename=true"]}
-{"year":"2023","title":"ModuleFormer: Learning Modular Large Language Models From Uncurated Data","authors":["Y Shen, Z Zhang, T Cao, S Tan, Z Chen, C Gan - arXiv preprint arXiv:2306.04640, 2023"],"snippet":"Large Language Models (LLMs) have achieved remarkable results. But existing models are expensive to train and deploy, and it is also difficult to expand their knowledge beyond pre-training data without forgetting previous knowledge. This …","url":["https://arxiv.org/pdf/2306.04640"]}
-{"year":"2023","title":"MONITORING FILE FORMAT OBSOLESCENCE IN REPOSITORIES: An applied method","authors":["S Alloing - iPRES 2023, 2023"],"snippet":"… Common Crawl and data from different institutional repositories (Netherlands Institute for Sound and Vision and Data Archiving and Networked Services (DANS)). The Common Crawl … and this prevents the need to process all the Common Crawl …","url":["https://www.ideals.illinois.edu/items/128320/bitstreams/429005/object"]}
-{"year":"2023","title":"Mono-and Multilingual GPT-3 Models for Hungarian","authors":["ZG Yang, LJ Laki, T Váradi, G Prószéky - … Conference on Text, Speech, and Dialogue, 2023"],"snippet":"… Common Crawl (CC): Most of our Hungarian text was collected from the Common Crawl database. Since the Webcorpus 2.0 contains text only until April of 2019, we collected the data that was created afterwards. For downloading and boilerplate-cleaning …","url":["https://link.springer.com/chapter/10.1007/978-3-031-40498-6_9"]}
-{"year":"2023","title":"Monolingual and Cross-Lingual Survey Response Annotation","authors":["Y Zhao - 2023"],"snippet":"… This model is pre-trained on the CommonCrawl data of 100 languages using multilingual MLM, with a vocabulary size 250k. It outperforms state-of-the-art cross-lingual benchmark models, including mBERT, in cross-language classification, sequence …","url":["https://www.diva-portal.org/smash/get/diva2:1814552/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Monolingual, multilingual and cross-lingual code comment classification","authors":["M Kostić, V Batanović, B Nikolić - Engineering Applications of Artificial Intelligence, 2023"],"snippet":"Code comments are one of the most useful forms of documentation and metadata for understanding software implementation. Previous research on code comment classification has focused only on comments in English, typically extracted from a …","url":["https://www.sciencedirect.com/science/article/pii/S0952197623006693"]}
-{"year":"2023","title":"MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining","authors":["J Portes, AR Trott, S Havens, D King, A Venigalla… - Thirty-seventh Conference …, 2023"],"snippet":"Although BERT-style encoder models are heavily used in NLP research, many researchers do not pretrain their own BERTs from scratch due to the high cost of training. In the past half-decade since BERT first rose to prominence, many …","url":["https://openreview.net/pdf?id=5zipcfLC2Z"]}
-{"year":"2023","title":"MosaicBERT: How to Train BERT with a Lunch Money Budget","authors":["J Portes, AR Trott, S Havens, D King, A Venigalla… - Workshop on Efficient …, 2023"],"snippet":"Although BERT-style encoder models are heavily used in NLP research, many researchers do not pretrain their own BERTs from scratch due to the high cost of training. In the past half-decade since BERT first rose to prominence, many …","url":["https://openreview.net/pdf?id=WH1S0gonzR"]}
-{"year":"2023","title":"mPLM-Sim: Unveiling Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language Models","authors":["P Lin, C Hu, Z Zhang, AFT Martins, H Schütze - arXiv preprint arXiv:2305.13684, 2023"],"snippet":"Recent multilingual pretrained language models (mPLMs) have been shown to encode strong language-specific signals, which are not explicitly provided during pretraining. It remains an open question whether it is feasible to employ mPLMs to …","url":["https://arxiv.org/pdf/2305.13684"]}
-{"year":"2023","title":"mPLUG-2: A Modularized Multi-modal Foundation Model Across Text, Image and Video","authors":["H Xu, Q Ye, M Yan, Y Shi, J Ye, Y Xu, C Li, B Bi, Q Qian… - arXiv preprint arXiv …, 2023"],"snippet":"Recent years have witnessed a big convergence of language, vision, and multi-modal pretraining. In this work, we present mPLUG-2, a new unified paradigm with modularized design for multi-modal pretraining, which can benefit from modality …","url":["https://arxiv.org/pdf/2302.00402"]}
-{"year":"2023","title":"muGen: Generative AI as Machinic Exploration of Cultural Archives","authors":["Y Yu - 2023"],"snippet":"In recent years, generative AI has quickly become a new creative and artistic tool that could challenge our understanding of the creative process and the role of the machine. Despite having exhibited visually promising results, images generated by …","url":["https://www.diva-portal.org/smash/get/diva2:1813415/FULLTEXT01.pdf"]}
-{"year":"2023","title":"Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams","authors":["M Tavakoli, R Chandra, F Tian, C Bravo - arXiv preprint arXiv:2304.10740, 2023"],"snippet":"Knowing which factors are significant in credit rating assignment leads to better decision-making. However, the focus of the literature thus far has been mostly on structured data, and fewer studies have addressed unstructured or multi-modal …","url":["https://arxiv.org/pdf/2304.10740"]}
-{"year":"2023","title":"MultiFin: A Dataset for Multilingual Financial NLP","authors":["R Jørgensen, O Brandt, M Hartmann, X Dai, C Igel… - Findings of the Association …, 2023"],"snippet":"… Embedding alignment We map monolingual fasttext embeddings trained on Wikipedia and Commoncrawl into a shared space using RCSLS, by computing pairwise mappings between source languages and English as a target language. As …","url":["https://aclanthology.org/2023.findings-eacl.66.pdf"]}
-{"year":"2023","title":"Multilanguage Word Embeddings for Social Scientists: Estimation, Inference and Validation Resources for 157 Languages","authors":["PL Rodriguez, A Spirling, BM Stewart, EM Wirsching"],"snippet":"… from Common Crawl and Wikipedia. A strength of the fastText model is that it uses subword … Common Crawl includes a large number of typos and very rare terms (plus many English loan … Beyond this potential for noise, note also that Common Crawl …","url":["https://alcembeddings.org/assets/img/RSSW_paper_June_2023.pdf"]}
-{"year":"2023","title":"MultiLegalPile: A 689GB Multilingual Legal Corpus","authors":["J Niklaus, V Matoshi, M Stürmer, I Chalkidis, DE Ho - arXiv preprint arXiv:2306.02069, 2023"],"snippet":"… The Common Crawl corpus is a publicly available multilingual dataset of scraped web pages, … As a result, utilizing the Common Crawl dataset necessitates additional post-filtering and … 2020a) performed several cleaning steps on the April …","url":["https://arxiv.org/pdf/2306.02069"]}
-{"year":"2023","title":"Multilingual and Multi-domain Opinion Mining","authors":["L JACQMIN - 2023"],"snippet":"Everyday, multinational companies receive large amounts of customer feedback. Valuable insights can be extracted from it to address customers’ needs. This textual feedback can span various languages and domains. Due to this variability, generic …","url":["https://jacqle.github.io/assets/pdf/Masters_Thesis_Leo_Jacqmin.pdf"]}
-{"year":"2023","title":"Multilingual Coarse Political Stance Classification of Media. The Editorial Line of a ChatGPT and Bard Newspaper","authors":["C España-Bonet - arXiv preprint arXiv:2310.16269, 2023"],"snippet":"Neutrality is difficult to achieve and, in politics, subjective. Traditional media typically adopt an editorial line that can be used by their potential readers as an indicator of the media bias. Several platforms currently rate news outlets according to their …","url":["https://arxiv.org/pdf/2310.16269"]}
-{"year":"2023","title":"Multilingual Jailbreak Challenges in Large Language Models","authors":["Y Deng, W Zhang, SJ Pan, L Bing - arXiv preprint arXiv:2310.06474, 2023"],"snippet":"… (2023), we determine the resource levels for each language by utilizing the data ratio from the CommonCrawl corpus1, which serves as the primary dataset for most LLMs’ pre-training. Specifically, a language is categorized as high-resource if its …","url":["https://arxiv.org/pdf/2310.06474"]}
-{"year":"2023","title":"Multilingual Language Models are not Multicultural: A Case Study in Emotion","authors":["S Havaldar, S Rai, B Singhal, LLSC Guntuku, L Ungar - arXiv preprint arXiv …, 2023"],"snippet":"Emotions are experienced and expressed differently across the world. In order to use Large Language Models (LMs) for multilingual tasks that require emotional sensitivity, LMs must reflect this cultural variation in emotion. In this study, we …","url":["https://arxiv.org/pdf/2307.01370"]}
-{"year":"2023","title":"Multilingual Natural Language Processing Model for Radiology Reports The Summary is all you need!","authors":["M Lindo, AS Santos, A Ferreira, J Li, G Luijten… - arXiv preprint arXiv …, 2023"],"snippet":"… guages gathered from the publicly available Common Crawl Web Scrape. The mT5 model offers five model sizes, one of which is the base size with 580M parameters, and was used in this project. One difference between T5 and mT5 is that mT5 was …","url":["https://www.researchgate.net/profile/Mariana-Lindo/publication/374414168_Multilingual_Natural_Language_Processing_Model_for_Radiology_Reports_-_The_Summary_is_all_you_need/links/651c3ce13ab6cb4ec6b76a5e/Multilingual-Natural-Language-Processing-Model-for-Radiology-Reports-The-Summary-is-all-you-need.pdf"]}
-{"year":"2023","title":"Multilingual semantic distance: Automatic verbal creativity assessment in many languages.","authors":["JD Patterson, HM Merseal, DR Johnson, S Agnoli… - Psychology of Aesthetics …, 2023"],"snippet":"… MBERT is trained on the 104 languages with the largest Wikipedia databases, while XLMR is trained on cleaned CommonCrawl data that covers 100 languages. CommonCrawl is an archive of steadily increasing size that is produced by an …","url":["https://psycnet.apa.org/record/2024-07870-002"]}
-{"year":"2023","title":"Multilingual Simplification of Medical Texts","authors":["S Joseph, K Kazanas, K Reina, VJ Ramanathan, W Xu… - arXiv preprint arXiv …, 2023"],"snippet":"… 2022) used Common Crawl to mine millions of sequence pairs in English, Spanish, and French. The significant difference between MUSS and our dataset is MUSS’s lack of cross-lingual alignment, ie, alignment of sequence pairs from one language …","url":["https://arxiv.org/pdf/2305.12532"]}
-{"year":"2023","title":"Multilingual Summarization with Factual Consistency Evaluation","authors":["R Aharoni, S Narayan, J Maynez, J Herzig, E Clark… - Findings of the Association …, 2023"],"snippet":"Abstractive summarization has enjoyed renewed interest in recent years, thanks to pre-trained language models and the availability of large-scale datasets. Despite promising results, current models still suffer from generating factually inconsistent …","url":["https://aclanthology.org/2023.findings-acl.220.pdf"]}
-{"year":"2023","title":"Multilingual text categorization and sentiment analysis: a comparative analysis of the utilization of multilingual approaches for classifying twitter data","authors":["G Manias, A Mavrogiorgou, A Kiourtis, C Symvoulidis… - Neural Computing and …, 2023"],"snippet":"… XLM-RoBERTa (XLM-R) XLM-RoBERTa (XLM-R) is a multilingual masked language model introduced by authors in [21] that trained on 2.5 TB of newly created clean CommonCrawl data in 100 languages. It is an update to the original XLM-100 …","url":["https://link.springer.com/article/10.1007/s00521-023-08629-3"]}
-{"year":"2023","title":"Multilingual Text Representation","authors":["F Faisal - arXiv preprint arXiv:2309.00949, 2023"],"snippet":"Modern NLP breakthrough includes large multilingual models capable of performing tasks across more than 100 languages. State-of-the-art language models came a long way, starting from the simple one-hot representation of words capable of …","url":["https://arxiv.org/pdf/2309.00949"]}
-{"year":"2023","title":"Multilingual, monolingual and mono-dialectal transfer learning for Moroccan Arabic sentiment classification","authors":["N Boudad, R Faizi, R Oulad Haj Thami - Social Network Analysis and Mining, 2024"],"snippet":"Transfer learning has recently proven to be very powerful in diverse natural language processing (NLP) tasks such as Machine translation, Sentiment Analysis, and Question/Answering. In this work, we investigate the use of transfer learning (TL) …","url":["https://link.springer.com/article/10.1007/s13278-023-01159-9"]}
-{"year":"2023","title":"Multilinguality in Language Models","authors":["I Partalas - 2023"],"snippet":"• Increasing batch size and training time enhances model performance• Tokenization tools used by mBERT and XLM-100 make these models more difficult to use on raw text• No performance loss for models trained with SPM, compared to …","url":["https://cis.lmu.de/~yehao/teaching/gpts/multilinguality.pdf"]}
-{"year":"2023","title":"Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved With Text","authors":["W Zhu, J Hessel, A Awadalla, SY Gadre, J Dodge… - arXiv preprint arXiv …, 2023"],"snippet":"… We first retrieve the original webpages for each document in the c4-en dataset from the Common Crawl version 2019-18, which is the default version for c4. Next, we extract the URLs for downloadable images from the raw WAT files. We restrict the …","url":["https://arxiv.org/pdf/2304.06939"]}
-{"year":"2023","title":"Multimodal Coreference Resolution","authors":["AS Varela, K Knill"],"snippet":"In a situated dialog system, multimodal coreference resolution is the task of identifying which entity the user is referring to within a certain context defined by both natural language and visual modalities. This is a crucial task to tackle in order …","url":["https://www.mlmi.eng.cam.ac.uk/files/2021-2022_dissertations/multimodal_coreference_resolution_reduced.pdf"]}
-{"year":"2023","title":"Multimodal text summarization with evaluation approaches","authors":["AFUR Khilji, U Sinha, P Singh, A Ali, SR Laskar… - Sādhanā, 2023"],"snippet":"Multimodal text summarization is a complex and challenging task in the field of natural language processing. Its objective is to use a combination of features from various modalities to create a concise yet informative summary from a given set of …","url":["https://link.springer.com/article/10.1007/s12046-023-02284-z"]}
-{"year":"2023","title":"MULTITuDE: Large-Scale Multilingual Machine-Generated Text Detection Benchmark","authors":["D Macko, R Moro, A Uchendu, JS Lucas, M Yamashita… - arXiv preprint arXiv …, 2023"],"snippet":"… We have used on-request author-provided processed data as well as CommonCrawl based links published in the GitHub repository. Both sources result in per-language … XLM-RoBERTa16 is a pre-trained on 2.5TB of filtered …","url":["https://arxiv.org/pdf/2310.13606"]}
-{"year":"2023","title":"MultiVENT: Multilingual Videos of Events with Aligned Natural Text","authors":["K Sanders, D Etter, R Kriz, B Van Durme - arXiv preprint arXiv:2307.03153, 2023"],"snippet":"… To incorporate multilinguality into the model’s frame-level features, we use a ViT architecture trained with a contrastive objective over multilingual image-caption pairs from the LAION-5B dataset [42], which is constructed from the Common Crawl …","url":["https://arxiv.org/pdf/2307.03153"]}
-{"year":"2023","title":"Murreviikko-A Dialectologically Annotated and Normalized Dataset of Finnish Tweets","authors":["O Kuparinen - Tenth Workshop on NLP for Similar Languages …, 2023"],"snippet":"This paper presents Murreviikko, a dataset of dialectal Finnish tweets which have been dialectologically annotated and manually normalized to a standard form. The dataset can be used as a test set for dialect identification and dialect-to-standard …","url":["https://aclanthology.org/2023.vardial-1.3.pdf"]}
-{"year":"2023","title":"Mutation-Based Adversarial Attacks on Neural Text Detectors","authors":["G Liang, J Guerrero, I Alsmadi - arXiv preprint arXiv:2302.05794, 2023"],"snippet":"Neural text detectors aim to decide the characteristics that distinguish neural (machine-generated) from human texts. To challenge such detectors, adversarial attacks can alter the statistical characteristics of the generated text, making the detection task more and …","url":["https://arxiv.org/pdf/2302.05794"]}
-{"year":"2023","title":"NAIL: Lexical Retrieval Indices with Efficient Non-Autoregressive Decoders","authors":["LB Soares, D Gillick, JR Cole, T Kwiatkowski - arXiv preprint arXiv:2305.14499, 2023"],"snippet":"Neural document rerankers are extremely effective in terms of accuracy. However, the best models require dedicated hardware for serving, which is costly and often not feasible. To avoid this serving-time requirement, we present a method of …","url":["https://arxiv.org/pdf/2305.14499"]}
-{"year":"2023","title":"Named Entity Recognition for De-identifying Real-World Health Records in Spanish","authors":["G López-García, FJ Moreno-Barea, H Mesa, JM Jerez… - International Conference on …, 2023"],"snippet":"… XLM-R: this multilingual version of the RoBERTa architecture [18] was pretrained on a massive 2.4TB CommonCrawl Corpus in 100 languages [2], using a large multilingual vocabulary of \\(\\sim \\)250K subwords. We experimented with both the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-36024-4_17"]}
-{"year":"2023","title":"Named entity recognition in resumes","authors":["E Kesim, A Deliahmetoglu - arXiv preprint arXiv:2306.13062, 2023"],"snippet":"Named entity recognition (NER) is used to extract information from various documents and texts such as names and dates. It is important to extract education and work experience information from resumes in order to filter them. Considering …","url":["https://arxiv.org/pdf/2306.13062"]}
-{"year":"2023","title":"Named Entity-Oriented Sentiment Analysis with text2text Generation Approach","authors":["I Moloshnikov, M Skorokhodov, A Naumov, R Rybka… - Proceedings of the …, 2023"],"snippet":"… The CommonCrawl data contains text in 100 languages, of which the Russian language is one of the most representative. … Wikipedia, books, news, and CommonCrawl texts were used to train them. The model dictionary size is 32101 …","url":["https://www.dialog-21.ru/media/5916/moloshnikoviplusetal113.pdf"]}
-{"year":"2023","title":"Natural Language Inference for Arabic using Recurrent Neural Network and Word Embedding","authors":["M Bensghaier, W Bakari, M Neji - 2022 IEEE/ACS 19th International Conference on …, 2022"],"snippet":"The Natural Language Inference (NLI) task is a field of Natural Language Processing (NLP) in which researchers try to find ways to decide about the inference relation between two sentences. In this paper, we present an early version of an …","url":["https://ieeexplore.ieee.org/abstract/document/10017722/"]}
-{"year":"2023","title":"Natural language processing deep learning models for the differential between high-grade gliomas and metastasis: what if the key is how we report them?","authors":["T Martín-Noguerol, P López-Úbeda, A Pons-Escoda… - European Radiology, 2023"],"snippet":"Objectives The differential between high-grade glioma (HGG) and metastasis remains challenging in common radiological practice. We compare different natural language processing (NLP)–based deep learning models to assist radiologists …","url":["https://link.springer.com/article/10.1007/s00330-023-10202-4"]}
-{"year":"2023","title":"Natural Language Processing For Automatic text summarization [Datasets]-Survey","authors":["AA AL-Banna, AK AL-Mashhadany - Wasit Journal of Computer and Mathematics …, 2022"],"snippet":"… These stories are based on sources mentioned by WCEP editors and automatically collected from Common Crawl News and supplemented with items acquired automatically from t (WCEP) [14]. The best result in the dataset shown in [15] …","url":["https://wjcm.uowasit.edu.iq/index.php/wjcm/article/download/72/68"]}
-{"year":"2023","title":"Natural Language Processing with Generative AI Models: A Methodological Approach for Their Application","authors":["S Strippoli - 2023"],"snippet":"… OpenAI trained eight different models of varying sizes, ranging from 125 million to 175 billion parameters, using a dataset refined from the CommonCrawl, which contained nearly a trillion words of … For GPT-3, the size refers to the filtered …","url":["https://webthesis.biblio.polito.it/secure/28973/1/tesi.pdf"]}
-{"year":"2023","title":"Natural Language Processing: Practical Approach","authors":["SM Basha, AS Fathima - 2023"],"snippet":"… Using External Data: There are several online resources that provide large text corpora such as Project Gutenberg, Common Crawl and Wikipedia. These resources can be accessed using the appropriate API and downloaded locally for further analysis. …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=ciOwEAAAQBAJ&oi=fnd&pg=PA1&dq=commoncrawl&ots=s-uWXu426A&sig=EnVdKElz2TIaNnf_YbXj0JBhNZE"]}
-{"year":"2023","title":"Natural Language-Assisted Sign Language Recognition","authors":["R Zuo, F Wei, B Mak - arXiv preprint arXiv:2303.12080, 2023"],"snippet":"… Concretely, given a sign vocabulary containing N glosses, we leverage fastText [38] pretrained on Common Crawl to extract a 300-d feature for each gloss. We use E ∈ RN×300 to denote the N gloss features. Language-Aware Label Smoothing and …","url":["https://arxiv.org/pdf/2303.12080"]}
-{"year":"2023","title":"Navigating Alignment for Non-identical Client Class Sets: A Label Name-Anchored Federated Learning Framework","authors":["J Zhang, X Zhang, X Zhang, D Hong, RK Gupta… - 2023"],"snippet":"Traditional federated classification methods, even those designed for non-IID clients, assume that each client annotates its local data with respect to the same universal class set. In this paper, we focus on a more general yet practical setting, non-identical …","url":["http://mesl.ucsd.edu/pubs/Jiayun_KDD2023_FEDALIGN.pdf"]}
-{"year":"2023","title":"Navigating the Ethical Landmines of ChatGPT: Implications of Intelligent Chatbots in Plastic Surgery Clinical Practice","authors":["NC Oleck, HI Naga, DS Nichols, MX Morris, B Dhingra… - Plastic and Reconstructive …, 2023"],"snippet":"… The large dataset used to train ChatGPT is derived from “internet dumps” obtained via web scraping from open source datasets such as Common Crawl and OpenWebText. These datasets are composed of data sourced from over 20 million …","url":["https://journals.lww.com/prsgo/fulltext/2023/09000/navigating_the_ethical_landmines_of_chatgpt_.42.aspx?context=latestarticles"]}
-{"year":"2023","title":"Navigating the generative AI era: Introducing the AI assessment scale for ethical GenAI assessment","authors":["M Perkins, L Furze, J Roe, J MacVaugh - arXiv preprint arXiv:2312.07086, 2023"],"snippet":"Recent developments in Generative Artificial Intelligence (GenAI) have created a paradigm shift in multiple areas of society, and the use of these technologies is likely to become a defining feature of education in coming decades. GenAI offers …","url":["https://arxiv.org/pdf/2312.07086"]}
-{"year":"2023","title":"Negation and speculation processing: A study on cue-scope labelling and assertion classification in Spanish clinical text","authors":["N Perez, M Cuadros, G Rigau - Artificial Intelligence in Medicine, 2023"],"snippet":"Natural Language Processing (NLP) based on new deep learning technology is contributing to the emergence of powerful solutions that help healthcare providers and researchers discover valuable patterns within insurmountable volumes of health …","url":["https://www.sciencedirect.com/science/article/pii/S0933365723001963"]}
-{"year":"2023","title":"Negativity spreads faster: A large-scale multilingual twitter analysis on the role of sentiment in political communication","authors":["D Antypas, A Preece, J Camacho-Collados - Online Social Networks and Media, 2023"],"snippet":"Social media has become extremely influential when it comes to policy making in modern societies, especially in the western world, where platforms such as Twitter allow users to follow politicians, thus making citizens more involved in political …","url":["https://www.sciencedirect.com/science/article/pii/S2468696423000010"]}
-{"year":"2023","title":"Nested Named-Entity Recognition in Multilingual Code-Switched NLP Check for updates","authors":["A Patil, U Kolhe - Big Data, Machine Learning, and Applications …, 2024"],"snippet":"… OSCAR Open Super-large Crawled Aggregated coRpus (OSCAR) is a huge multilingual corpus obtained by language classification and filtering of Common Crawl corpus. The dataset contains 166 languages in total. We are using this dataset for adaptive …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=IrrmEAAAQBAJ&oi=fnd&pg=PA368&dq=commoncrawl&ots=mzlcvjaWFp&sig=UAZ6zHL60TQpG3gRkxgshDExQjw"]}
-{"year":"2023","title":"Netizens, Academicians, and Information Professionals' Opinions About AI With Special Reference To ChatGPT","authors":["A Subaveerapandiyan, A Vinoth, N Tiwary - Library Philosophy and Practice (e …, 2023","N Tiwary - arXiv preprint arXiv:2302.07136, 2023"],"snippet":"This study aims to understand the perceptions and opinions of academicians towards ChatGPT-3 by collecting and analyzing social media comments, and a survey was conducted with library and information science professionals. The …","url":["https://arxiv.org/pdf/2302.07136","https://hcommons.org/deposits/view/hc:52298/CONTENT/netizens-academicians-and-information-professionals-opinions-about-ai-with-special-reference-to-chatgpt.pdf/"]}
-{"year":"2023","title":"Neural correlates of object-extracted relative clause processing across English and Chinese","authors":["D Dunagan, M Stanojević, M Coavoux, S Zhang… - Neurobiology of Language"],"snippet":"Are the brain bases of language comprehension the same across all human languages, or do these bases vary in a way that corresponds to differences in linguistic typology? English and Mandarin Chinese attest such a typological …","url":["https://direct.mit.edu/nol/article-pdf/doi/10.1162/nol_a_00110/2112616/nol_a_00110.pdf"]}
-{"year":"2023","title":"Neural Data Search for Table Augmentation","authors":["A Brinkmann - 2023"],"snippet":"… WDC table corpus2 consists of 4.2 million relational tables generated by extracting schema.org3 annotations from the Common Crawl and grouping the annotations by class and host. All tables in this corpus share a common schema. By …","url":["https://ceur-ws.org/Vol-3379/PhDWorkshop_2023_brinkmann-paper.pdf"]}
-{"year":"2023","title":"Neural Embeddings for Web Testing","authors":["A Stocco, A Willi, LLL Starace, M Biagiola, P Tonella - arXiv preprint arXiv …, 2023"],"snippet":"Web test automation techniques employ web crawlers to automatically produce a web app model that is used for test generation. Existing crawlers rely on app-specific, threshold-based, algorithms to assess state equivalence. Such algorithms are hard …","url":["https://arxiv.org/pdf/2306.07400"]}
-{"year":"2023","title":"Neural Language Generation for Content Adaptation: Explainable, Efficient Low-Resource Text Simplification and Evaluation","authors":["GC Garbacea - 2023"],"snippet":"There are rich opportunities to reduce the language complexity of professional content (either human-written or computer-generated) and make it accessible to a broad audience. As a sub-task of natural language generation (NLG), text …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/178028/garbacea_1.pdf?sequence=1"]}
-{"year":"2023","title":"Neural machine translation for in‐text citation classification","authors":["I Safder, M Ali, NR Aljohani, R Nawaz, SU Hassan - Journal of the Association for …"],"snippet":"The quality of scientific publications can be measured by quantitative indices such as the h‐index, Source Normalized Impact per Paper, or g‐index. However, these measures lack to explain the function or reasons for citations and the context of …","url":["https://asistdl.onlinelibrary.wiley.com/doi/abs/10.1002/asi.24817"]}
-{"year":"2023","title":"Neural Machine Translation For Low Resource Languages","authors":["C Utsa, G Vakul, K Parvathy, RG Kannan","V Goyle, K Goyle, P Krishnaswamy, KG Ravikumar… - arXiv preprint arXiv …, 2023"],"snippet":"… It is trained on the monolingual common crawl corpus for 25 languages (CC25). The text corpus is further tokenized using the sentence-piece model (SPM) [6] which provides both subword tokenization and unigram language modelling additionally …","url":["https://arxiv.org/pdf/2304.07869","https://www.academia.edu/download/102811574/TeamT_Project_Report_1.pdf"]}
-{"year":"2023","title":"Neural machine translation to local languages","authors":["V Shah, S Valiullah, MY Makwana"],"snippet":"Neural Machine Translation (NMT) has demonstrated significant potential in facilitating communication across language barriers. However, adapting NMT systems to low-resource local languages poses significant challenges due to the …","url":["https://www.researchgate.net/profile/Vaibhav-Shah-36/publication/369857893_Neural_machine_translation_to_local_languages/links/642fe1044e83cd0e2f979230/Neural-machine-translation-to-local-languages.pdf"]}
-{"year":"2023","title":"Neural Machine Translation, Large Language Models and Literary Translation: The Story So Far","authors":["D Kenny, D Hansen - ITIA CPD, 2023"],"snippet":"We understand ‘literary machine translation’as an emerging interdisciplinary field that embraces a range of phenomena related to the application of MT to the translation of literary texts. It touches upon or intersects with, among other areas: ● …","url":["https://orbi.uliege.be/bitstream/2268/302554/1/presentation_ITIA_kenny_hansen.pdf"]}
-{"year":"2023","title":"Neural semantic tagging for natural language-based search in building information models: Implications for practice","authors":["M Shahinmoghadam, SE Kahou, A Motamedi - Computers in Industry, 2024"],"snippet":"While the adoption of open Building Information Modeling (open BIM) standards continues to grow, the inherent complexity and multifaceted nature of the built asset lifecycle data present a critical bottleneck for effective information retrieval. To …","url":["https://www.sciencedirect.com/science/article/pii/S0166361523002130"]}
-{"year":"2023","title":"NeuralMind-UNICAMP at 2022 TREC NeuCLIR: Large Boring Rerankers for Cross-lingual Retrieval","authors":["V Jeronymo, R Lotufo, R Nogueira - arXiv preprint arXiv:2303.16145, 2023"],"snippet":"This paper reports on a study of cross-lingual information retrieval (CLIR) using the mT5-XXL reranker on the NeuCLIR track of TREC 2022. Perhaps the biggest contribution of this study is the finding that despite the mT5 model being fine-tuned …","url":["https://arxiv.org/pdf/2303.16145"]}
-{"year":"2023","title":"Neuroinformatics, Neural Networks and Neurocomputers for Computational Intelligence","authors":["NK Kasabov - Neuroinformatics, 2023"],"snippet":"1. Learning from (big) data-> neural networks and deep NN 2. Explainability (extracting rules, associations)(explainable AI)→ fuzzy logic/neuro-fuzzy systems 3. Evolvability→ evolving connectionist systems (ECOS) and brain-inspired SNN (NeuCube). 4 …","url":["http://conf.uni-obuda.hu/saci2023/SACI2023PlenaryPaper_NKasabov_presentation.pdf"]}
-{"year":"2023","title":"New Challenges in Official Statistics: Big Data Analytics and Multi-level Product Classification of Web Scraped Data","authors":["JFU Machado - 2023"],"snippet":"The surge in internet usage has significantly amplified data generation, paving the way for researchers and policymakers to gain in-depth and granular insights about society. This shift has transformed data collection methodologies, fostering the …","url":["https://repositorio-aberto.up.pt/bitstream/10216/151290/2/635323.pdf"]}
-{"year":"2023","title":"New Evaluation Metrics Capture Quality Degradation due to LLM Watermarking","authors":["K Singh, J Zou - arXiv preprint arXiv:2312.02382, 2023"],"snippet":"With the increasing use of large-language models (LLMs) like ChatGPT, watermarking has emerged as a promising approach for tracing machine-generated content. However, research on LLM watermarking often relies on simple perplexity …","url":["https://arxiv.org/pdf/2312.02382"]}
-{"year":"2023","title":"New models developed for detection of misconceptions in physics with artificial intelligence","authors":["MU Demirezen, O Yilmaz, E Ince - Neural Computing and Applications, 2023"],"snippet":"Students’ misconceptions of various topics in physics have been investigated by many researchers. The detection of misconceptions is very difficult and takes a long time as a human being. Our aim in the study carried out is to determine the …","url":["https://link.springer.com/article/10.1007/s00521-023-08414-2"]}
-{"year":"2023","title":"nl2spec: Interactively Translating Unstructured Natural Language to Temporal Logics with Large Language Models","authors":["M Cosler, C Hahn, D Mendoza, F Schmitt, C Trippel - arXiv preprint arXiv:2303.04864, 2023"],"snippet":"A rigorous formalization of desired system requirements is indispensable when performing any verification task. This often limits the application of verification techniques, as writing formal specifications is an error-prone and time-consuming …","url":["https://arxiv.org/pdf/2303.04864"]}
-{"year":"2023","title":"NLP Meets Agronomy: Document Classification for Plant Health Surveillance","authors":["LAV Reina, R Bossy - 2023"],"snippet":"In the field of Plant Health Epidemiological Surveillance, accurately analyzing written reports of events affecting agriculture is crucial. This master’s thesis in Natural Language Processing leverages the power of Automatic Text Classification …","url":["https://hal.science/hal-04223051/document"]}
-{"year":"2023","title":"NLP-Based Automated Conspiracy Detection for Massive Twitter Datasets","authors":["R Akbari - 2023"],"snippet":"The COVID-19 pandemic, which affected societies worldwide, and many were compelled to shut down, also affected social media platforms like Twitter. The COVID-19-related misinformation on Twitter covered various topics and contained many competing …","url":["https://www.duo.uio.no/bitstream/handle/10852/103705/17/MasterThesis_RohullahAkbari.pdf"]}
-{"year":"2023","title":"NosWalker: A Decoupled Architecture for Out-of-Core Random Walk Processing","authors":["S Wang, M Zhang, K Yang, K Chen, S Ma, J Jiang… - Proceedings of the 28th …, 2023"],"snippet":"Out-of-core random walk system has recently attracted a lot of attention as an economical way to run billions of walkers over large graphs. However, existing out-of-core random walk systems are all built upon general out-of-core graph processing …","url":["https://dl.acm.org/doi/abs/10.1145/3582016.3582025"]}
-{"year":"2023","title":"Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting","authors":["H Huang, T Tang, D Zhang, WX Zhao, T Song, Y Xia… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs) demonstrate impressive multilingual capability, but their performance varies substantially across different languages. In this work, we introduce a simple yet effective method, called cross-lingual-thought prompting (XLT) …","url":["https://arxiv.org/pdf/2305.07004"]}
-{"year":"2023","title":"Nougat: Neural Optical Understanding for Academic Documents","authors":["L Blecher, G Cucurull, T Scialom, R Stojnic - arXiv preprint arXiv:2308.13418, 2023"],"snippet":"Scientific knowledge is predominantly stored in books and scientific journals, often in the form of PDFs. However, the PDF format leads to a loss of semantic information, particularly for mathematical expressions. We propose Nougat (Neural Optical …","url":["https://arxiv.org/pdf/2308.13418"]}
-{"year":"2023","title":"NovaCOMET: Open Commonsense Foundation Models with Symbolic Knowledge Distillation","authors":["P West, RL Bras, T Sorensen, BY Lin, L Jiang, X Lu… - arXiv preprint arXiv …, 2023"],"snippet":"We present NovaCOMET, an open commonsense knowledge model, that combines the best aspects of knowledge and general task models. Compared to previous knowledge models, NovaCOMET allows open-format relations enabling direct …","url":["https://arxiv.org/pdf/2312.05979"]}
-{"year":"2023","title":"Novel embeddings improve the prediction of risk perception","authors":["Z Hussain, DU Wulff, R Mata - 2023"],"snippet":"… fastText was trained on the Common Crawl, a corpus of web pages that is more diverse and with 600B tokens considerably larger than the … GloVe was trained on a slightly larger version of the Common Crawl than fastText comprising 804B. We …","url":["https://psyarxiv.com/yrjfb/download?format=pdf"]}
-{"year":"2023","title":"Ntcir-17 mednlp-sc social media adverse drug event detection: Subtask overview","authors":["S Wakamiya, LK Pereira, L Raithel, HS Yeh, P Han… - Proceedings of the 17th …, 2023"],"snippet":"… It is pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. XLM-R has been shown to perform particularly well in low-resource languages, such as Swahili and Urdu. We use the XLM-R base model released by the authors. …","url":["http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings17/pdf/ntcir/01-NTCIR17-OV-MEDNLP-WakamiyaS.pdf"]}
-{"year":"2023","title":"Oasis: Data Curation and Assessment System for Pretraining of Large Language Models","authors":["T Zhou, Y Chen, P Cao, K Liu, J Zhao, S Liu - arXiv preprint arXiv:2311.12537, 2023"],"snippet":"… Aside from introducing Oasis, we demonstrate a complete case that utilizes this platform to build a high-quality and high-diversity Common Crawl corpus. Meanwhile, we holistic assess the corpus in the different development stages. The assessments …","url":["https://arxiv.org/pdf/2311.12537"]}
-{"year":"2023","title":"OBELISC: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents","authors":["H Laurençon, L Saulnier, L Tronchon, S Bekman… - arXiv preprint arXiv …, 2023"],"snippet":"… We introduce the OBELISC dataset, an open web-scale filtered dataset of interleaved image-text documents comprising 141 million web pages extracted from Common Crawl, 353 million associated images, and 115 billion text tokens. We …","url":["https://arxiv.org/abs/2306.16527"]}
-{"year":"2023","title":"Objaverse-XL: A Universe of 10M+ 3D Objects","authors":["M Deitke, R Liu, M Wallingford, H Ngo, O Michel… - arXiv preprint arXiv …, 2023"],"snippet":"… In language understanding, datasets like Common Crawl [1] have culminated in unprecedented capabilities of large language models such as GPT-4 [43], which in turn power mainstream applications like ChatGPT. The impact of large datasets is …","url":["https://arxiv.org/pdf/2307.05663"]}
-{"year":"2023","title":"OHYEAH AT VLSP2022-EVJVQA CHALLENGE: A JOINTLY LANGUAGE-IMAGE MODEL FOR MULTILINGUAL VISUAL QUESTION ANSWERING","authors":["LN Dinh, H Le Ngoc, LQ Phan - Journal of Computer Science and Cybernetics, 2023"],"snippet":"… mT5 [5] is a massively multilingual pre-trained text-to-text transformer, which leverages T5 [11] to train on a new Common Crawl-based dataset with up to 101 languages. It has been proven to outperform many multilingual models in a variety of …","url":["https://vjs.ac.vn/index.php/jcc/article/download/18122/2543255286"]}
-{"year":"2023","title":"Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback","authors":["VD Lai, C Van Nguyen, NT Ngo, T Nguyen… - arXiv preprint arXiv …, 2023"],"snippet":"… Table 1: List of 26 non-English languages in our Okapi framework along with language codes, numbers of first and second speakers (the “Pop.” column), data ratios in the CommonCrawl corpus, and language categories. The languages are …","url":["https://arxiv.org/pdf/2307.16039"]}
-{"year":"2023","title":"On Bilingual Lexicon Induction with Large Language Models","authors":["Y Li, A Korhonen, I Vulić - arXiv preprint arXiv:2310.13995, 2023"],"snippet":"Bilingual Lexicon Induction (BLI) is a core task in multilingual NLP that still, to a large extent, relies on calculating cross-lingual word representations. Inspired by the global paradigm shift in NLP towards Large Language Models (LLMs), we examine …","url":["https://arxiv.org/pdf/2310.13995"]}
-{"year":"2023","title":"On Corpora and Writing","authors":["M Chitez, A Dinca - Digital Writing Technologies in Higher Education …, 2023"],"snippet":"… For example, the filtered version of the Common Crawl Footnote 1 used for the pre-training dataset for GPT-3 (ie Generative Pre-trained Transformer 3 Footnote 2 ) consists of 410 billion tokens. This large quantity of data enables powerful quantitative analyses …","url":["https://link.springer.com/chapter/10.1007/978-3-031-36033-6_24"]}
-{"year":"2023","title":"On generalization of the sense retrofitting model","authors":["YY Lee, TY Yen, HH Huang, YT Shiue, HH Chen - Natural Language Engineering, 2023"],"snippet":"With the aid of recently proposed word embedding algorithms, the study of semantic relatedness has progressed rapidly. However, word-level representations are still lacking for many natural language processing tasks. Various sense-level …","url":["https://www.cambridge.org/core/journals/natural-language-engineering/article/on-generalization-of-the-sense-retrofitting-model/34C8E293327067D21168C01AFBA5E57B"]}
-{"year":"2023","title":"On Hate Scaling Laws For Data-Swamps","authors":["A Birhane, V Prabhu, S Han, VN Boddeti - arXiv preprint arXiv:2306.13141, 2023"],"snippet":"… Given that both LAION-400M and LAION-2B-en are extracted from the CommonCrawl dataset, we hypothesize that during the race to expand the dataset to 2 billion samples, the dataset scraping module might have sampled from the low-quality …","url":["https://arxiv.org/pdf/2306.13141"]}
-{"year":"2023","title":"On Methods of Data Standardization of German Social Media Comments","authors":["L Melnyk, L Feld - Journal of Computer-Assisted Linguistic Research, 2023"],"snippet":"This article is part of a larger project aiming at identifying discursive strategies in social media discourses revolving around the topic of gender diversity, for which roughly 350,000 comments were scraped from the comments sections below …","url":["https://polipapers.upv.es/index.php/jclr/article/download/19907/16253"]}
-{"year":"2023","title":"On reading and interpreting black box deep neural networks","authors":["JE Dobson - International Journal of Digital Humanities, 2023"],"snippet":"The deep neural networks used in computer vision and in recent large language models are widely recognized as black boxes, a term that describes their complicated architectures and opaque decision-making mechanisms. This essay …","url":["https://link.springer.com/article/10.1007/s42803-023-00075-w"]}
-{"year":"2023","title":"On the Benefits of Learning to Route in Mixture-of-Experts Models","authors":["N Dikkala, N Ghosh, R Meka, R Panigrahy, N Vyas… - Proceedings of the 2023 …, 2023"],"snippet":"… We study language modeling objective on the Common Crawl (mC4) dataset with T5 transformers. A first approach one could consider would be to compare neural networks where the router is learned versus networks where the router is frozen …","url":["https://aclanthology.org/2023.emnlp-main.583.pdf"]}
-{"year":"2023","title":"On the Effectiveness of Log Representation for Log-based Anomaly Detection","authors":["X Wu, H Li, F Khomh"],"snippet":"Logs are an essential source of information for people to understand the running status of a software system. Due to the evolving modern software architecture and maintenance methods, more research efforts have been devoted to automated log …","url":["https://www.hengli.org/pdf/Wu2023LogRepresentation.pdf"]}
-{"year":"2023","title":"On the Evolution of Knowledge Graphs: A Survey and Perspective","authors":["X Jiang, C Xu, Y Shen, X Sun, L Tang, S Wang, Z Chen… - arXiv preprint arXiv …, 2023"],"snippet":"Knowledge graphs (KGs) are structured representations of diversified knowledge. They are widely used in various intelligent applications. In this article, we provide a comprehensive survey on the evolution of various types of knowledge graphs (ie …","url":["https://arxiv.org/pdf/2310.04835"]}
-{"year":"2023","title":"On the fractal patterns of language structures","authors":["LC Ribeiro, AT Bernardes, H Mello - Plos one, 2023"],"snippet":"… -profit CommonCrawl Foundation [39–41]. The data is publicly available in the Amazon cloud and were collected from many independent crawls from 2008 to 2017. As a reference of the magnitude of the raw data used by December 2017, the …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0285630"]}
-{"year":"2023","title":"On the Generalization Ability of Retrieval-Enhanced Transformers","authors":["T Norlund, E Doostmohammadi, R Johansson… - arXiv preprint arXiv …, 2023"],"snippet":"Recent work on the Retrieval-Enhanced Transformer (RETRO) model has shown that off-loading memory from trainable weights to a retrieval database can significantly improve language modeling and match the performance of non-retrieval …","url":["https://arxiv.org/pdf/2302.12128"]}
-{"year":"2023","title":"On the Importance of Data Representation for the Success of Text Classification","authors":["CY Cuello, V Jofre Caradonna, MJ Garciarena Ucelay… - … (CACIC)(La Rioja, 3 al 6 de …, 2023"],"snippet":"… We also used the GloVe embeddings trained with Common Crawl data which have 300 components. For both methods, the document … metrics were reached with vectors of 300 dimensions and, in the case of GloVe, using the pre-trained …","url":["http://sedici.unlp.edu.ar/bitstream/handle/10915/149536/Documento_completo.pdf?sequence=1"]}
-{"year":"2023","title":"On the Ordering of Pooled Web Pages, Gold Assessments, and Bronze Assessments","authors":["T Sakai, S Tao, N Chen, Y Li, M Maistro, Z Chu, N Ferro - ACM Transactions on …, 2023"],"snippet":"The present study leverages a recent opportunity we had to create a new English web search test collection for the NTCIR-16 We Want Web (WWW-4) task, which concluded in June 2022. More specifically, through the test collection construction …","url":["https://dl.acm.org/doi/pdf/10.1145/3600227"]}
-{"year":"2023","title":"On the Question of Authorship in Large Language Models (LLMs)","authors":["C Soos, L Haroutunian - NASKO, 2023"],"snippet":"… GPT-3’s gigantic scale came along with, of course, a gigantic training set, which includes English Wikipedia and BookCorpus along with the CommonCrawl dataset, which is a web crawl dataset consisting of the text from billions of web pages. Like …","url":["https://journals.lib.washington.edu/index.php/nasko/article/view/16299/13969"]}
-{"year":"2023","title":"On the Reliability of Watermarks for Large Language Models","authors":["J Kirchenbauer, J Geiping, Y Wen, M Shu, K Saifullah… - arXiv preprint arXiv …, 2023"],"snippet":"… [2023], we use the Colossal Common Crawl Cleaned corpus (C4) dataset as a source of prompts for open-ended generation. For the human study, we adopt the “Long-Form Question Answering” (LFQA) dataset curated by Krishna et al. [2023] based on a …","url":["https://arxiv.org/pdf/2306.04634"]}
-{"year":"2023","title":"On the Role of Morphological Information for Contextual Lemmatization","authors":["O Toporkov, R Agerri - arXiv preprint arXiv:2302.00407, 2023"],"snippet":"Lemmatization is a Natural Language Processing (NLP) task which consists of producing, from a given inflected word, its canonical form or lemma. Lemmatization is one of the basic tasks that facilitate downstream NLP applications, and is of …","url":["https://arxiv.org/pdf/2302.00407"]}
-{"year":"2023","title":"On the State of German (Abstractive) Text Summarization","authors":["D Aumiller, J Fan, M Gertz - arXiv preprint arXiv:2301.07095, 2023"],"snippet":"With recent advancements in the area of Natural Language Processing, the focus is slowly shifting from a purely English-centric view towards more language-specific solutions, including German. Especially practical for businesses to analyze their …","url":["https://arxiv.org/pdf/2301.07095"]}
-{"year":"2023","title":"On the use of sentiment analysis for linguistics research. Observations on sentiment polarity and the use of the progressive in Italian","authors":["L Violaa"],"snippet":"Today computational methods are used more and more in domains outside of their original conception. For example, sentiment analysis (SA)–a technique originally designed to infer general opinions from product reviews–is applied to make stock …","url":["https://2023.dhbenelux.org/wp-content/uploads/2023/05/DHB2023_paper_9150.pdf"]}
-{"year":"2023","title":"On Web-based Visual Corpus Construction for Visual Document Understanding","authors":["D Kim, T Hong, M Yim, Y Kim, G Kim - International Conference on Document Analysis …, 2023"],"snippet":"… 5.1 Scale-up Using CommonCrawl Our initial goal was to handle tons of HTML data, such as CommonCrawl dataset Footnote 13 which consists of petabytes of data. … https://commoncrawl.github.io/cc-crawl-statistics/plots/crawlsize. …","url":["https://link.springer.com/chapter/10.1007/978-3-031-41682-8_19"]}
-{"year":"2023","title":"On\" Scientific Debt\" in NLP: A Case for More Rigour in Language Model Pre-Training Research","authors":["MN Nityasya, HA Wibowo, AF Aji, GI Winata… - arXiv preprint arXiv …, 2023"],"snippet":"This evidence-based position paper critiques current research practices within the language model pre-training literature. Despite rapid recent progress afforded by increasingly better pre-trained language models (PLMs), current PLM research …","url":["https://arxiv.org/pdf/2306.02870"]}
-{"year":"2023","title":"One Textbook Is All You Need","authors":["A Sawyer, I Moradi, L Welch, J Zhao, S Huang… - 2023"],"snippet":"Large Language Models don’t have a strong understanding of under-represented languages due to the lack of requisite training data [12]. Previous efforts increased model performance on low-resource languages by using news [15], synthetic data [2] …","url":["https://lucaswelch.me/images/Modulus%20Magnus%20Linguae.pdf"]}
-{"year":"2023","title":"One True Pairing: Evaluating Effective Language Pairings for Fake News Detection Employing Zero-Shot Cross-Lingual Transfer","authors":["S Kasim - Soft Computing and Its Engineering Applications: 4th …, 2023"],"snippet":"… [5] conducted unsupervised training of cross-lingual embeddings at very large scale using the CommonCrawl Corpus. To develop XLM-R, which is a transformer-based multilingual masked language model, they applied a SentencePiece model directly …","url":["https://link.springer.com/chapter/10.1007/978-3-031-27609-5_2"]}
-{"year":"2023","title":"Open Government Data Corpus for Table Search","authors":["M Glass, S Bagchi, O Hassanzadeh, G Rossiello… - arXiv preprint arXiv …, 2023"],"snippet":"… Web Table Retrieval [1] uses HTML tables from Common Crawl and uses crowd sourcing and query logs to gather 60 queries. These queries are then attempted over several baseline methods and the resulting tables are pooled for relevance …","url":["https://arxiv.org/pdf/2308.13560"]}
-{"year":"2023","title":"Open Problems in Applied Deep Learning","authors":["M Raissi - arXiv preprint arXiv:2301.11316, 2023"],"snippet":"This work formulates the machine learning mechanism as a bi-level optimization problem. The inner level optimization loop entails minimizing a properly chosen loss function evaluated on the training data. This is nothing but the well-studied training …","url":["https://arxiv.org/pdf/2301.11316"]}
-{"year":"2023","title":"OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch","authors":["J Li, Z Tang, Y Ding, P Wang, P Guo, W You, D Qiao… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs) with billions of parameters have demonstrated outstanding performance on various natural language processing tasks. This report presents OpenBA, an open-sourced 15B bilingual asymmetric seq2seq model, to …","url":["https://arxiv.org/pdf/2309.10706"]}
-{"year":"2023","title":"OpenFact at CheckThat! 2023: Head-to-Head GPT vs. BERT-A Comparative Study of Transformers Language Models for the Detection of Check-worthy","authors":["M Sawiński, K Węcel, E Księżniak, M Stróżyna… - 2023"],"snippet":"This paper presents the research findings resulting from experiments conducted as part of the Check-That! Lab Task 1B-English submission at CLEF 2023. The aim of the research was to evaluate the check-worthiness of short texts in English. Various …","url":["https://www.dei.unipd.it/~faggioli/temp/CLEF2023-proceedings/paper-040.pdf"]}
-{"year":"2023","title":"OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text","authors":["K Paster, MD Santos, Z Azerbayev, J Ba - arXiv preprint arXiv:2310.06786, 2023"],"snippet":"… Due to the high variance in the quality of documents from Common Crawl, we additionally use several methods for filtering and boilerplate reduction. Throughout the creation of OpenWebMath, we iteratively refined these methods to ensure that …","url":["https://arxiv.org/pdf/2310.06786"]}
-{"year":"2023","title":"Opportunities for Large Language Models and Discourse in Engineering Design","authors":["J Göpfert, JM Weinand, P Kuckertz, D Stolten - arXiv preprint arXiv:2306.09169, 2023"],"snippet":"In recent years, large language models have achieved breakthroughs on a wide range of benchmarks in natural language processing and continue to increase in performance. Recently, the advances of large language models have raised interest …","url":["https://arxiv.org/pdf/2306.09169"]}
-{"year":"2023","title":"OPTIMIZATION METHODS FOR MODELING DIVERSITY IN LANGUAGE TECHNOLOGIES","authors":["S Kumar - 2023"],"snippet":"Abstract Language use varies across individuals, communities, and populations giving rise to different variations with diverging vocabularies, syntax, semantics, and pragmatics. Despite rapid improvements in natural language processing systems on …","url":["https://www.lti.cs.cmu.edu/sites/default/files/kumar%2C%20sachin%20-%20THESIS.pdf"]}
-{"year":"2023","title":"Optimized Tokenization for Transcribed Error Correction","authors":["T Wullach, SE Chazan - arXiv preprint arXiv:2310.10704, 2023"],"snippet":"… 2020) data set, a variant of the Common Crawl dataset that consists of 101 languages. For each language, we randomly select a set of 20M sentences that ranges from 3 to 15 words long. We use lowercase synthetic texts, remove …","url":["https://arxiv.org/pdf/2310.10704"]}
-{"year":"2023","title":"Optimizing Machine Translation for Virtual Assistants: Multi-Variant Generation with VerbNet and Conditional Beam Search","authors":["M Sowanski, A Janicki - 2023"],"snippet":"In this paper, we introduce a domain-adapted machine translation (MT) model for intelligent virtual assistants (IVA) designed to translate natural language understanding (NLU) training data sets. This work uses a constrained beam search …","url":["https://annals-csis.org/proceedings/2023/pliks/8601.pdf"]}
-{"year":"2023","title":"Optimizing Match-LSTM for SQuAD v2. 0","authors":["P Nsaka, J Dong, A Lee"],"snippet":"… The word vectors utilized in our model are trained on the 840B word corpora from Common Crawl data. The dimensionality of the embedding at 300 is significantly higher that the other choices of 50, 100 and 200 it provides more contextual …","url":["https://www.researchgate.net/profile/Peter-Nsaka/publication/368662438_Optimizing_Match-LSTM_for_SQuAD_v20_Stanford_CS224N_Default_Project/links/63f3adbbb1704f343f6b1376/Optimizing-Match-LSTM-for-SQuAD-v20-Stanford-CS224N-Default-Project.pdf"]}
-{"year":"2023","title":"Options Speak Louder Than Words: Strategic Negativity in Earnings Calls Prior to Option Grants","authors":["N Palacio, M Toivonen - 2023"],"snippet":"We investigate whether executive compensation affects disclosure during earnings conference calls. In particular, we hypothesize that executives who have an upcoming option grant will use overly negative language in earnings calls, intending …","url":["https://openaccess.nhh.no/nhh-xmlui/bitstream/handle/11250/3096032/masterthesis.pdf?sequence=1"]}
-{"year":"2023","title":"ORGANIZATIONS AS ALGORITHMS: A NEW METAPHOR FOR ADVANCING MANAGEMENT THEORY","authors":["VL Glaser, J Sloan, J Gehman"],"snippet":"According to the ‘Point’essay, management research’s reliance on corporate data threatens to replace objective theory with profit-biased ‘corporate empiricism,’undermining the scientific and ethical integrity of the field. In this ‘Counterpoint’essay, we offer a …","url":["https://www.researchgate.net/profile/Vern-Glaser-2/publication/375863735_Organizations_as_Algorithms_A_New_Metaphor_for_Advancing_Management_Theory/links/655fb1893fa26f66f421ef08/Organizations-as-Algorithms-A-New-Metaphor-for-Advancing-Management-Theory.pdf"]}
-{"year":"2023","title":"Other Applications of Comparable Corpora","authors":["S Sharoff, R Rapp, P Zweigenbaum - Building and Using Comparable Corpora for …, 2023"],"snippet":"This section concerns applications of comparable corpora beyond pure machine translation. It has been argued [ 1 , 2 ] that downstream applications such as cross-lingual document classification, information retrieval or natural language inference, apart …","url":["https://link.springer.com/chapter/10.1007/978-3-031-31384-4_7"]}
-{"year":"2023","title":"Overview of the CLEF-2023 CheckThat! lab task 2 on subjectivity in news articles","authors":["A Galassi, F Ruggeri, A Barrón-Cedeño, F Alam… - M. Aliannejadi, G. Faggioli …, 2023"],"snippet":"We describe the outcome of the 2023 edition of the CheckThat! Lab at CLEF. We focus on subjectivity (Task 2), which has been proposed for the first time. It aims at fostering the technology for the identification of subjective text fragments in news …","url":["https://www.dei.unipd.it/~faggioli/temp/CLEF2023-proceedings/paper-020.pdf"]}
-{"year":"2023","title":"Overview of the NTCIR-17 FairWeb-1 Task","authors":["S Tao, N Chen, T Sakai, Z Chu, H Arai, I Soboroff… - Proceedings of the 17th …, 2023"],"snippet":"This paper provides an overview of the NTCIR-17 FairWeb-1 Task. FairWeb-1 is an English web search task which seeks more than an ad-hoc web search task. Our task considers not only document relevance but also group fairness. We designed …","url":["http://research.nii.ac.jp/ntcir/workshop/OnlineProceedings17/pdf/ntcir/01-NTCIR17-OV-FAIRWEB-TaoS.pdf"]}
-{"year":"2023","title":"Overview of the TREC 2022 NeuCLIR Track","authors":["D Lawrie, S MacAvaney, J Mayfield, P McNamee…"],"snippet":"… , and Russian, drawn from the Common Crawl news collection.The documents were obtained by the Common Crawl service between August 1, … , an alternative source of the document collection can be obtained directly from Common Crawl …","url":["https://trec.nist.gov/pubs/trec31/papers/Overview_neuclir.pdf"]}
-{"year":"2023","title":"Overview of Touché 2023: Argument and Causal Retrieval","authors":["A Bondarenko, M Fröbe, J Kiesel, F Schlatt, V Barriere…"],"snippet":"The goal of Touché is to foster and support the development of technologies for argument and causal retrieval and analysis. For the fourth time, we organize the Touché lab featuring four shared tasks:(a) argument retrieval for controversial topics …","url":["https://webis.de/downloads/publications/papers/bondarenko_2023a.pdf"]}
-{"year":"2023","title":"OWLER: PRELIMINARY RESULTS FOR BUILDING A COLLABORATIVE OPEN WEB CRAWLER","authors":["M Dinzinger, S Zerhoudi, M Al-Maamari, M Istaiti…"],"snippet":"… The used seed URLs are a random sample from a recent CommonCrawl (CC) dump. Note that a CC dump gives no guarantee on a fair or even distribution of URLs, so the set of seed URLs could possibly be biased in any direction. …","url":["https://ca-roll.github.io/downloads/owler.pdf"]}
-{"year":"2023","title":"PaLM 2 Technical Report","authors":["R Anil, AM Dai, O Firat, M Johnson, D Lepikhin… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is a Transformer-based model trained using a mixture of …","url":["https://arxiv.org/pdf/2305.10403"]}
-{"year":"2023","title":"Palmyra-Med: Instruction-Based Fine-Tuning of LLMs Enhancing Medical Domain Performance","authors":["K Kamble, W AlShikh"],"snippet":"The development of Large Language Models (LLMs) has greatly impacted natural language processing tasks by demonstrating exceptional performance across various applications. However, a significant challenge faced by these models is their …","url":["https://www.researchgate.net/profile/Waseem-Alshikh/publication/372157453_Palmyra-Med_Instruction-Based_Fine-Tuning_of_LLMs_Enhancing_Medical_Domain_Performance/links/64a6e10c8de7ed28ba7e1598/Palmyra-Med-Instruction-Based-Fine-Tuning-of-LLMs-Enhancing-Medical-Domain-Performance.pdf"]}
-{"year":"2023","title":"Paloma: A Benchmark for Evaluating Language Model Fit","authors":["I Magnusson, A Bhagia, V Hofmann, L Soldaini, AH Jha… - arXiv preprint arXiv …, 2023"],"snippet":"… pretraining without data beyond Common Crawl leads to inconsistent fit to many domains. … are trained only on data derived from Common Crawl (C4, FALCON REFINEDWEB, and MC4… majority of our domains are not sourced from Common …","url":["https://arxiv.org/pdf/2312.10523"]}
-{"year":"2023","title":"PALS: Personalized Active Learning for Subjective Tasks in NLP","authors":["K Kanclerz, K Karanowski, J Bielaniewicz, M Gruza… - Proceedings of the 2023 …, 2023"],"snippet":"For subjective NLP problems, such as classification of hate speech, aggression, or emotions, personalized solutions can be exploited. Then, the learned models infer about the perception of the content independently for each reader. To acquire …","url":["https://aclanthology.org/2023.emnlp-main.823.pdf"]}
-{"year":"2023","title":"Panda LLM: Training Data and Evaluation for Open-Sourced Chinese Instruction-Following Large Language Models","authors":["F Jiao, B Ding, T Luo, Z Mo - arXiv preprint arXiv:2305.03025, 2023"],"snippet":"This project focuses on enhancing open-source large language models through instruction-tuning and providing comprehensive evaluations of their performance. We explore how various training data factors, such as quantity, quality, and linguistic …","url":["https://arxiv.org/pdf/2305.03025"]}
-{"year":"2023","title":"PandeMedia: an annotated corpus of digital media for issue salience","authors":["DC Almeida - 2022"],"snippet":"… Though available at the start of this project, these large datasets from Common Crawl would not significantly reduce the amount of work necessary to build the pipeline, because metadata curation and data parsing are still necessary to locate …","url":["https://repositorio.ul.pt/bitstream/10451/55576/1/TM_David_Almeida.pdf"]}
-{"year":"2023","title":"PanGu-{\\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous Computing","authors":["X Ren, P Zhou, X Meng, X Huang, Y Wang, W Wang… - arXiv preprint arXiv …, 2023"],"snippet":"The scaling of large language models has greatly improved natural language understanding, generation, and reasoning. In this work, we develop a system that trained a trillion-parameter language model on a cluster of Ascend 910 AI …","url":["https://arxiv.org/pdf/2303.10845"]}
-{"year":"2023","title":"PaniniQA: Enhancing Patient Education Through Interactive Question Answering","authors":["P Cai, Z Yao, F Liu, D Wang, M Reilly, H Zhou, L Li… - arXiv preprint arXiv …, 2023"],"snippet":"Patient portal allows discharged patients to access their personalized discharge instructions in electronic health records (EHRs). However, many patients have difficulty understanding or memorizing their discharge instructions. In this paper, we …","url":["https://arxiv.org/pdf/2308.03253"]}
-{"year":"2023","title":"PAPERS IN ENGLISH","authors":["F Adilova, R Davronov, R Safarov - … редактор: Ахметов Сайранбек Махсутович, д-р …, 2023"],"snippet":"… Distributed word representations for 157 distinct languages were created using the Wikipedia and Common Crawl databases [8]. The author's Uzbek Wikipedia model has 110K words, but the Common Crawl model only has 830K words. They …","url":["https://api.scienceweb.uz/storage/publication_files/4164/13954/653b94725edea___10(115_6)_compressed.pdf#page=28"]}
-{"year":"2023","title":"Parameter-Efficient Fine-Tuning without Introducing New Latency","authors":["B Liao, Y Meng, C Monz - arXiv preprint arXiv:2305.16742, 2023"],"snippet":"Parameter-efficient fine-tuning (PEFT) of pre-trained language models has recently demonstrated remarkable achievements, effectively matching the performance of full fine-tuning while utilizing significantly fewer trainable parameters, and consequently …","url":["https://arxiv.org/pdf/2305.16742"]}
-{"year":"2023","title":"Pashto offensive language detection: a benchmark dataset and monolingual Pashto BERT","authors":["I Haq, W Qiu, J Guo, P Tang - PeerJ Computer Science, 2023"],"snippet":"… XLM-R is trained on 2.5TB of CommonCrawl data in 100 languages simultaneously. This model outperforms other multilingual models on many NLP tasks, demonstrating its effectiveness at learning cross-lingual representations. We …","url":["https://peerj.com/articles/cs-1617/"]}
-{"year":"2023","title":"Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script","authors":["X Cao, D Dawa, N Qun, T Nyima"],"snippet":"The textual adversarial attack refers to an attack method in which the attacker adds imperceptible perturbations to the original texts by elaborate design so that the NLP (natural language processing) model produces false judgments. This method is also used to …","url":["https://trustnlpworkshop.github.io/papers/6.pdf"]}
-{"year":"2023","title":"PDF investigation with parser differentials and ontology","authors":["D Lam, L Li, C Anderson - 2023"],"snippet":"This paper describes the Verifiable Automatic Language Analysis and Recognition for Inputs (VALARIN) system to process, evaluate, and flag unsafe PDFs. The system extracts error features from a collection of PDF parsers, and organizes the different …","url":["https://www.techrxiv.org/articles/preprint/PDF_investigation_with_parser_differentials_and_ontology/23290277/1/files/41098616.pdf"]}
-{"year":"2023","title":"PDFTriage: Question Answering over Long, Structured Documents","authors":["J Saad-Falcon, J Barrow, A Siu, A Nenkova, RA Rossi… - arXiv preprint arXiv …, 2023"],"snippet":"… For our documents, we sampled 1000 documents from the common crawl to get visually-rich, professional documents from various domains, then subsampled 100 documents based on their reading level (Flesch… 3https://mturk.com 4https://commoncrawl.org/ …","url":["https://arxiv.org/pdf/2309.08872"]}
-{"year":"2023","title":"PDHF: Effective Phishing Detection Model Combining Optimal Artificial and Automatic Deep Features","authors":["E Zhu, K Cheng, Z Zhang, H Wang - Computers & Security, 2023"],"snippet":"Currently, the increasing number of high-volume phishing attacks is among the largest threats to networking environments on a daily basis. During such a severe attack, researchers prefer to extract numerous features to improve the accuracy of …","url":["https://www.sciencedirect.com/science/article/pii/S0167404823004716"]}
-{"year":"2023","title":"Pearls and pitfalls of ChatGPT in medical oncology","authors":["J Blum, AK Menta, X Zhao, VB Yang, MA Gouda… - Trends in Cancer, 2023"],"snippet":"… Common Crawl is an open repository of web data from billions of web pages, consisting of petabytes of information on web pages, images… medical literature, it is diluted by unverified information contained in the Common Crawl, WebText2, and …","url":["https://www.sciencedirect.com/science/article/pii/S2405803323001097"]}
-{"year":"2023","title":"Performance of Generative Large Language Models on Ophthalmology Board Style Questions","authors":["LZ Cai, A Shaheen, A Jin, R Fukui, SY Jonathan… - American Journal of …, 2023"],"snippet":"… The specialized medical information used to train these LLMs is limited, as they are currently trained on publicly available datasets designed for natural language processing such as Common Crawl, WebText, Wikipedia, and available Web Books …","url":["https://www.sciencedirect.com/science/article/pii/S0002939423002301"]}
-{"year":"2023","title":"PERFORMANCE STUDY OF THE TEXT ANALYSIS MODULE IN THE PROPOSED MODEL OF AUTOMATIC SPEAKER'S SPEECH ANNOTATION","authors":["О БАРКОВСЬКА - Computer systems and information technologies, 2022"],"snippet":"… This solution was trained in 101 languages on a corpus of Common Crawl web pages, and supplemented with the XL-SUM dataset (covering 45 languages, highly abstract, concise and high-end as evidenced by human and internal evaluation) …","url":["https://csitjournal.khmnu.edu.ua/index.php/csit/article/download/182/112"]}
-{"year":"2023","title":"Perplexity-Driven Case Encoding Needs Augmentation for CAPITALIZATION Robustness","authors":["RJHKR Grundkiewicz, M Junczys-Dowmunt"],"snippet":"Subword segmentation methods are the predominant solution to vocab sparsity in NMT. However, they cannot currently handle capitalization well. We re-encode case to allow the perplexity-driven SPM unigram language model algorithm to learn how …","url":["http://www.afnlp.org/conferences/ijcnlp2023/proceedings/main-short/cdrom/pdf/2023.ijcnlp-short.17.pdf"]}
-{"year":"2023","title":"Persian Text Sentiment Analysis Based on BERT and Neural Networks","authors":["SR Zardak, AH Rasekh, MS Bashkari - Iranian Journal of Science and Technology …, 2023"],"snippet":"Sentiment analysis and opinion mining are studies that analyze people’s opinions, feelings, experiences, and emotions through written language. This is one of the most active research fields in natural language processing and data mining, web …","url":["https://link.springer.com/article/10.1007/s40998-023-00626-5"]}
-{"year":"2023","title":"Personality Traits in Large Language Models","authors":["M Safdari, G Serapio-García, C Crepy, S Fitz… - arXiv preprint arXiv …, 2023"],"snippet":"The advent of large language models (LLMs) has revolutionized natural language processing, enabling the generation of coherent and contextually relevant text. As LLMs increasingly power conversational agents, the synthesized personality …","url":["https://arxiv.org/pdf/2307.00184"]}
-{"year":"2023","title":"Perspective: Large Language Models in Applied Mechanics","authors":["N Brodnik, S Carton, C Muir, S Ghosh, D Downey… - Journal of Applied …, 2023"],"snippet":"Large language models (LLMs), such as ChatGPT and PaLM, are able to perform sophisticated text comprehension and generation tasks with little or no training. Alongside their broader societal impacts, these capabilities carry great promise for …","url":["https://asmedigitalcollection.asme.org/appliedmechanics/article/doi/10.1115/1.4062773/1164084"]}
-{"year":"2023","title":"Phish-armour: phishing detection using deep recurrent neural networks","authors":["P Dhanavanthini, SS Chakkravarthy - Soft Computing, 2023"],"snippet":"Phishing is an illegal cybercrime, wherein a target gets victimized for sacrificing their personal and corporate information. It is one of the most straightforward forms of cyber-attack for hackers, as well as one of the simplest for victims to fall for. It can …","url":["https://link.springer.com/article/10.1007/s00500-023-07962-y"]}
-{"year":"2023","title":"PHISHING WEBSITE DETECTION TECHNIQUES: A LITERATURE SURVEY","authors":["K Subashini, V Narmatha - Journal of Data Acquisition and Processing, 2023"],"snippet":"… The names of legal sites that are likely to be used for phishing are included in Alexa and Common Crawl [26][27]. End-users submit suspicious URLs to Phish-tank and Open-Fish to assess if these websites are phishing scams [28][29]. The dataset …","url":["https://sjcjycl.cn/article/view-2023/pdf/02_3329.pdf"]}
-{"year":"2023","title":"Phishing website detection using genetic algorithm-based feature selection and parameter hypertuning","authors":["ASP Silva - 2023"],"snippet":"False webpages are created by cyber attackers who seek to mislead users into revealing sensitive and personal information, from credit card details to passwords. Phishing is a class of cyber attacks that mislead users into clicking on false websites …","url":["https://run.unl.pt/bitstream/10362/152538/1/TCDMAA1276.pdf"]}
-{"year":"2023","title":"Phonetically-Grounded Language Generation: The Case of Tongue Twisters","authors":["T Loakman, C Tang, C Lin - arXiv preprint arXiv:2306.03457, 2023"],"snippet":"Previous work in phonetically-grounded language generation has mainly focused on domains such as lyrics and poetry. In this paper, we present work on the generation of tongue twisters - a form of language that is required to be phonetically …","url":["https://arxiv.org/pdf/2306.03457"]}
-{"year":"2023","title":"Physics language and language use in physics--What do we know and how AI might enhance language-related research and instruction","authors":["P Wulff - European Journal of Physics, 2023"],"snippet":"Abstract Language is an important resource for physicists and learners of physics to construe physical phenomena and processes, and communicate ideas. Moreover, any physics-related instructional setting is inherently language-bound, and physics …","url":["https://iopscience.iop.org/article/10.1088/1361-6404/ad0f9c/pdf"]}
-{"year":"2023","title":"PLACES: Prompting Language Models for Social Conversation Synthesis","authors":["M Chen, A Papangelis, C Tao, S Kim, A Rosenbaum… - arXiv preprint arXiv …, 2023"],"snippet":"… 2020) or Common Crawl. This allows language models to have exposure to a large amount of linguistic diversity, but this also results in exposure to a lot of hateful, … a preliminary analysis of undesirable content in the common crawl corpus. arXiv …","url":["https://arxiv.org/pdf/2302.03269"]}
-{"year":"2023","title":"Poisoning Web-Scale Training Datasets is Practical","authors":["N Carlini, M Jagielski, CA Choquette-Choo, D Paleka… - arXiv preprint arXiv …, 2023"],"snippet":"… For example, both Wikipedia and Common Crawl regularly produce snapshots of their entire database. This simplifies access for people … We will investigate this attack on Wikipedia-derived datasets, but also discuss how similar vulnerabilities …","url":["https://arxiv.org/pdf/2302.10149"]}
-{"year":"2023","title":"Polyglot or Not? Measuring Multilingual Encyclopedic Knowledge in Foundation Models","authors":["T Schott, D Furman, S Bhat - Proceedings of the 2023 Conference on Empirical …, 2023"],"snippet":"In this work, we assess the ability of foundation models to recall encyclopedic knowledge across a wide range of linguistic contexts. To support this, we: 1) produce a 20-language dataset that contains 303k factual associations paired with …","url":["https://aclanthology.org/2023.emnlp-main.691.pdf"]}
-{"year":"2023","title":"PolyLM: An Open Source Polyglot Large Language Model","authors":["X Wei, H Wei, H Lin, T Li, P Zhang, X Ren, M Li, Y Wan… - arXiv preprint arXiv …, 2023"],"snippet":"… For instance, Thai and Indonesian have over 300 million (M) speakers, yet the size of these two languages in common crawl-based dataset … and CommonCrawl web documents as the negative samples. To sum up, about 28.3% data are filtered …","url":["https://arxiv.org/pdf/2307.06018"]}
-{"year":"2023","title":"PooRaa‐Agri KG: An agricultural knowledge graph‐based simplified multilingual query system","authors":["N Sivakumar, P Srinivasan, M Kannan, VP - Expert Systems"],"snippet":"The current work proposes PooRaa‐Agri KG, an agricultural knowledge graph‐based simplified multilingual query system that works in real time to provide concise answers for agriculture‐based queries. The proposed approach accommodates real‐time …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.13434"]}
-{"year":"2023","title":"Popular LLMs","authors":["T Amaratunga - … Large Language Models: Learning Their Underlying …, 2023"],"snippet":"… For the training of GPT-2, the CommonCrawl corpus was initially considered because of its large size. CommonCrawl is a large text corpus created … Unlike CommonCrawl, WebText was generated by scraping only pages linked to Reddit …","url":["https://link.springer.com/chapter/10.1007/979-8-8688-0017-7_5"]}
-{"year":"2023","title":"Posthuman Bodies: Why They (Still) Matter","authors":["NK Hayles - Mapping the Posthuman"],"snippet":"Emphasizing the common capacity for cognition, this chapter presents an integrated framework that includes humans, nonhuman biological lifeforms, and computational media. It clearly distinguishes between the agential powers of material processes …","url":["https://www.taylorfrancis.com/chapters/edit/10.4324/9781003322603-3/posthuman-bodies-katherine-hayles"]}
-{"year":"2023","title":"Practical Named Entity Recognition: The Role of Entity and Its Context","authors":["O Agarwal - 2023"],"snippet":"Neural supervised models for named entity recognition perform well within the same domain but fail to recognize entities not seen in the (pre-) training data with high accuracy. For better generalization, it is essential that models are able to recognize …","url":["https://search.proquest.com/openview/287c19e142ec4083a741bcf00f23209b/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Pre-processing and Resource Modelling for English-Assamese NMT System","authors":["MA Ahmed, K Kashyap, SK Sarma - 2023 4th International Conference on Computing …, 2023"],"snippet":"Neural Machine Translation (NMT) modelling for low-resourced languages is usually under-explored lacking proper analysis in the pre-processing stages which could potentially influence the performance of the model. Assamese, an indigenous …","url":["https://ieeexplore.ieee.org/abstract/document/10127567/"]}
-{"year":"2023","title":"Pre-Training for Manipulation: The Case for Shape Biased Vision Transformers","authors":["K Burns, T Yu, C Finn, K Hausman"],"snippet":"Inspired by the success of transfer learning in computer vision, roboticists have investigated visual pre-training as a means to learn visuallyrobust policies from pixels. To that end, past work has favored large object interaction data, such as first …","url":["https://kayburns.github.io/media/robust_manipulation_with_spatial_features.pdf"]}
-{"year":"2023","title":"PrecogIIITH@ WASSA2023: Emotion Detection for Urdu-English Code-mixed Text","authors":["BH Vedula, P Kodali, M Shrivastava, P Kumaraguru"],"snippet":"Code-mixing refers to the phenomenon of using two or more languages interchangeably within a speech or discourse context. This practice is particularly prevalent on social media platforms, and determining the embedded affects in a …","url":["https://precog.iiit.ac.in/pubs/WASSA_ACL23_sharedtask_emotion_cameraready.pdf"]}
-{"year":"2023","title":"Predicting COVID-19 Related Tweets Using Ensemble of Transformers Models","authors":["Q Ismail, M Massadeh, QB Baker - 2022 IEEE/ACS 19th International Conference on …, 2022"],"snippet":"… We also utilized RoBERTa in addition to BERT; RoBERTa is a powerful pre-trained linguistic model used for English; because RoBERTa was developed using 160GB of text from CommonCrawl, Wikipedia, news sources, novels, and other online …","url":["https://ieeexplore.ieee.org/abstract/document/10017516/"]}
-{"year":"2023","title":"PreSTU: Pre-Training for Scene-Text Understanding (Supplementary Material)","authors":["J Kil, S Changpinyo, X Chen, H Hu, S Goodman…"],"snippet":"… Our language module is initialized from mT5-Base [33], a multilingual variant of T5 [23], pre-trained on a new Common Crawlbased dataset with 101 different languages. During training, all parameters in vision and language blocks are …","url":["https://openaccess.thecvf.com/content/ICCV2023/supplemental/Kil_PreSTU_Pre-Training_for_ICCV_2023_supplemental.pdf"]}
-{"year":"2023","title":"Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of Privacy","authors":["D Ippolito, F Tramèr, M Nasr, C Zhang, M Jagielski…"],"snippet":"Studying data memorization in neural language models helps us understand the risks (eg, to privacy or copyright) associated with models regurgitating training data and aids in the development of countermeasures. Many prior works—and some …","url":["https://sigdialinlg2023.github.io/static/papers/inlg/12_Paper.pdf"]}
-{"year":"2023","title":"Prevention or Promotion? Predicting Author's Regulatory Focus","authors":["A Velutharambath, K Sassenberg, R Klinger - Northern European Journal of …, 2023"],"snippet":"People differ fundamentally in what motivates them to pursue a goal and how they approach it. For instance, some people seek growth and show eagerness, whereas others prefer security and are vigilant. The concept of regulatory focus is employed …","url":["https://nejlt.ep.liu.se/article/download/4561/3982"]}
-{"year":"2023","title":"Priorities for Generative AI Regulation in the UK: CREATe response to the Digital Regulation Cooperation Forum (DRCF)","authors":["M Eben, K Erickson, M Kretschmer, G Cifrodelli, Z Li… - 2023"],"snippet":"In July 2023 the UK Digital Regulation Cooperation Forum (DRCF) issued a request for comment on the status of generative AI and priority regulatory concerns. The DRCF is comprised of four of the UK’s major regulators: the Competition and …","url":["https://eprints.gla.ac.uk/306163/1/306163.pdf"]}
-{"year":"2023","title":"Privacy Implications of Retrieval-Based Language Models","authors":["Y Huang, S Gupta, Z Zhong, K Li, D Chen - arXiv preprint arXiv:2305.14888, 2023"],"snippet":"Retrieval-based language models (LMs) have demonstrated improved interpretability, factuality, and adaptability compared to their parametric counterparts, by incorporating retrieved text from external datastores. While it is well known that …","url":["https://arxiv.org/pdf/2305.14888"]}
-{"year":"2023","title":"Privacy-Preserving Recommender Systems with Synthetic Query Generation using Differentially Private Large Language Models","authors":["AG Carranza, R Farahani, N Ponomareva, A Kurakin… - arXiv preprint arXiv …, 2023"],"snippet":"We propose a novel approach for developing privacy-preserving large-scale recommender systems using differentially private (DP) large language models (LLMs) which overcomes certain challenges and limitations in DP training these complex …","url":["https://arxiv.org/pdf/2305.05973"]}
-{"year":"2023","title":"PrivacyGLUE: A Benchmark Dataset for General Language Understanding in Privacy Policies","authors":["A Shankar, A Waldis, C Bless, MA Rodriguez… - 2023"],"snippet":"Benchmarks for general language understanding have been rapidly developing in recent years of NLP research, particularly because of their utility in choosing strong-performing models for practical downstream applications. While benchmarks have been …","url":["https://www.preprints.org/manuscript/202303.0046/download/final_file"]}
-{"year":"2023","title":"Private Federated Learning in Gboard","authors":["Y Zhang, D Ramage, Z Xu, Y Zhang, S Zhai, P Kairouz - arXiv preprint arXiv …, 2023"],"snippet":"… We have employed model pre-training on public C4 corpus based on Common Crawl dataset [15] combined with training configuration tuning, and achieved almost neutral utility change measured by prediction picked ratio: the ratio of picked …","url":["https://arxiv.org/pdf/2306.14793"]}
-{"year":"2023","title":"Private Web Search with Tiptoe","authors":["A Henzinger, E Dauterman, H Corrigan-Gibbs… - Cryptology ePrint Archive, 2023"],"snippet":"… For text search, we search over the C4 data set, a cleaned version of the Common Crawl’s English web crawl corpus with 364M web pages [109, 110]. The Common Crawl data set is not as comprehensive as the crawls used by commercial …","url":["https://eprint.iacr.org/2023/1438.pdf"]}
-{"year":"2023","title":"Probing Pre-trained Large Language Models for Narrative Coherence","authors":["R David - 2023"],"snippet":"The extend to which PTLLMs capture narrative coherence, given (coherent) sequences of text and a set of possible ending sequences, in a zero-shot, multilingual setting has not been explored yet. This research presents an extensive …","url":["https://fse.studenttheses.ub.rug.nl/31225/1/mCCS_2023_DavidRA.pdf"]}
-{"year":"2023","title":"Probing Reasoning of Language Models with Inductive In-Context Learning","authors":["I Fostiropoulos, L Itti - International Joint Conference on Artificial Intelligence …, 2023"],"snippet":"… We attempt to use expressions directly to large corpus on 367 dataset like Common Crawl1 and Github repositories. Based 368 on sub-sample of our results it is computationally expensive 369 to perform exhaustive search and did not lead to …","url":["https://openreview.net/pdf?id=skvqz58ys1U"]}
-{"year":"2023","title":"Probing Taxonomic and Thematic Embeddings for Taxonomic Information","authors":["F Klubička, JD Kelleher - arXiv preprint arXiv:2301.10656, 2023"],"snippet":"Modelling taxonomic and thematic relatedness is important for building AI with comprehensive natural language understanding. The goal of this paper is to learn more about how taxonomic information is structurally encoded in embeddings. To do …","url":["https://arxiv.org/pdf/2301.10656"]}
-{"year":"2023","title":"Profiting from Data Commons: Theory, Evidence, and Strategy Implications","authors":["J Potts, A Torrance, D Harhoff, E von Hippel - Strategy Science, 2023"],"snippet":"We define data commons as repositories of freely-accessible, “open source” innovation-related data, information and knowledge. Data commons are and can be a significant resource for both innovating and innovation-adopting firms and …","url":["https://pubsonline.informs.org/doi/pdf/10.1287/stsc.2021.0080"]}
-{"year":"2023","title":"PROMPTING TECHNIQUES FOR NATURAL LANGUAGE GENERATION IN THE MEDICAL DOMAIN","authors":["M Rossini, P Torroni, E Cabrio, S Villata"],"snippet":"… The model is pre-trained on a modified version of the data scraped by Common Crawl1, an open repository of data crawled from the web … Unfortunately, while the Common Crawl corpus has been used for various NLP applications throughout the …","url":["https://amslaurea.unibo.it/28396/1/master_thesis_rossini.pdf"]}
-{"year":"2023","title":"Prosody Analysis of Audiobooks","authors":["C Pethe, Y Yin, S Skiena - arXiv preprint arXiv:2310.06930, 2023"],"snippet":"Recent advances in text-to-speech have made it possible to generate natural-sounding audio from text. However, audiobook narrations involve dramatic vocalizations and intonations by the reader, with greater reliance on emotions, dialogues, and …","url":["https://arxiv.org/pdf/2310.06930"]}
-{"year":"2023","title":"Protectbot: A Chatbot to Protect Children on Gaming Platforms","authors":["A Faraz - 2022"],"snippet":"Online gaming no longer has limited access, as it has become available to a high percentage of children in recent years. Consequently, children are exposed to multifaceted threats, such as cyberbullying, grooming, and sexting. The online …","url":["https://scholarworks.rit.edu/cgi/viewcontent.cgi?article=12518&context=theses"]}
-{"year":"2023","title":"ProteinChat: Towards Achieving ChatGPT-Like Functionalities on Protein 3D Structures","authors":["H Guo, M Huo, R Zhang, P Xie - 2023"],"snippet":"The study of proteins is critical in various scientific disciplines, but understanding their complex structure-function relationships remains challenging. Recent advancements in large language models (LLMs) have demonstrated their ability to …","url":["https://www.techrxiv.org/articles/preprint/ProteinChat_Towards_Achieving_ChatGPT-Like_Functionalities_on_Protein_3D_Structures/23120606/1/files/40841009.pdf"]}
-{"year":"2023","title":"Provably Convergent Subgraph-wise Sampling for Fast GNN Training","authors":["J Wang, Z Shi, X Liang, S Ji, B Li, F Wu - arXiv preprint arXiv:2303.11081, 2023"],"snippet":"Subgraph-wise sampling -- a promising class of mini-batch training techniques for graph neural networks (GNNs -- is critical for real-world applications. During the message passing (MP) in GNNs, subgraph-wise sampling methods discard …","url":["https://arxiv.org/pdf/2303.11081"]}
-{"year":"2023","title":"QASA: Advanced Question Answering on Scientific Articles","authors":["Y Lee, K Lee, S Park, D Hwang, J Kim, H Lee, M Lee - 2023"],"snippet":"Reasoning is the crux of intellectual thinking. While question answering (QA) tasks are prolific with various computational models and benchmark datasets, they mostly tackle factoid or shallow QA without asking deeper understanding. Dual process …","url":["https://openreview.net/pdf?id=5ud0h8OXwD"]}
-{"year":"2023","title":"Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model","authors":["Q Ye, J Liu, D Chong, P Zhou, Y Hua, A Liu - arXiv preprint arXiv:2310.09089, 2023"],"snippet":"Integrating large language models (LLMs) into healthcare presents potential but faces challenges. Directly pre-training LLMs for domains like medicine is resource-heavy and sometimes unfeasible. Sole reliance on Supervised Fine-tuning (SFT) can result …","url":["https://arxiv.org/pdf/2310.09089"]}
-{"year":"2023","title":"QLoRA: Efficient Finetuning of Quantized LLMs","authors":["T Dettmers, A Pagnoni, A Holtzman, L Zettlemoyer - arXiv preprint arXiv:2305.14314, 2023"],"snippet":"We present QLoRA, an efficient finetuning approach that reduces memory usage enough to finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit finetuning task performance. QLoRA backpropagates gradients through a …","url":["https://arxiv.org/pdf/2305.14314"]}
-{"year":"2023","title":"QRDP: A System that Facilitates the Selection of English Materials for Translator Education","authors":["T Abekawa, R Miyata, K Kageura - International Conference on Asian Digital Libraries, 2023"],"snippet":"We are currently developing a system that facilitates teachers of translation to evaluate and select suitable document segments as materials for translator training. The system needs to satisfy several requirements. Firstly, because translation is an …","url":["https://link.springer.com/chapter/10.1007/978-981-99-8085-7_19"]}
-{"year":"2023","title":"QUADRo: Dataset and Models for QUestion-Answer Database Retrieval","authors":["S Campese, I Lauriola, A Moschitti - arXiv preprint arXiv:2304.01003, 2023"],"snippet":"… (2021): given an input question, we queried a 2020 CommonCrawl snapshot1 using BM25 and we selected the 200 most relevant documents. Then, documents are split into sentences and a state-of-the-art sentence selector (Lauriola … 1https://commoncrawl.org/2020/?utm_sou …","url":["https://arxiv.org/pdf/2304.01003"]}
-{"year":"2023","title":"Qualitative Research Methods for Large Language Models: Conducting Semi-Structured Interviews with ChatGPT and BARD on Computer Science Education","authors":["A Dengel, R Gehrlein, D Fernes, S Görlich, J Maurer… - Informatics, 2023"],"snippet":"… In 2020, they published GPT 3 [9], which was trained on around 570 GB of text from a filtered version of Common Crawl, a openly available crawl of the internet. For newer models such as GPT 3.5 and GPT 4 [1], which were released in early 2023 …","url":["https://www.mdpi.com/2227-9709/10/4/78"]}
-{"year":"2023","title":"Quality Evaluation of Summarization Models for Patent Documents","authors":["J Ding, H Chen, S Kolapudi, L Pobbathi, H Nguyen - 2023 IEEE 23rd International …, 2023"],"snippet":"Several recently developed neural network models have shown their potential for automated text summarization. However, the evaluation results of these models on summarization of long text are fairly close in almost every major evaluation …","url":["https://ieeexplore.ieee.org/abstract/document/10366709/"]}
-{"year":"2023","title":"Quality Optimization Methods in Neural Machine Translation Systems","authors":["A Nowakowski"],"snippet":"Chapter 1 introduces the research problem, motivation, structure and scope of the thesis. It provides an overview of the included papers, together with details on authors, venues, presentation type, and the contribution of the thesis author. The …","url":["https://bip.amu.edu.pl/__data/assets/pdf_file/0032/463667/Nowakowski-Artur_rozprawa-doktorska.pdf"]}
-{"year":"2023","title":"Quality> Quantity: Synthetic Corpora from Foundation Models for Closed-Domain Extractive Question Answering","authors":["S Sengupta, C Heaton, S Ghosh, P Nakov, P Mitra - arXiv preprint arXiv:2310.16995, 2023"],"snippet":"Domain adaptation, the process of training a model in one domain and applying it to another, has been extensively explored in machine learning. While training a domain-specific foundation model (FM) from scratch is an option, recent methods have focused on …","url":["https://arxiv.org/pdf/2310.16995"]}
-{"year":"2023","title":"Quantum Natural Language Processing: A New and Promising Way to Solve NLP Problems","authors":["Y Bouakba, H Belhadef - Artificial Intelligence: Theories and Applications: First …, 2023"],"snippet":"… It is well known that more dataset and more parameters are essential for training deep transformers from scratch such as, GPT-3 which has used 175 billion parameters, 96 attention layers, and a Common Crawl data-set that is 45 TB in size [7] …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28540-0_17"]}
-{"year":"2023","title":"Querying Large Language Models with SQL","authors":["M Saeed, N De Cao, P Papotti - arXiv preprint arXiv:2304.00472, 2023"],"snippet":"… stored effectively in the parameters of the model: the CommonCrawl+ text corpus takes 45TB, while GPT-3 only 350GB. However, LLMs have their shortcomings, as we discuss next, including poor data manipulation skills, eg, they fail with numerical …","url":["https://arxiv.org/pdf/2304.00472"]}
-{"year":"2023","title":"Question and Answer Generation from Text Using Transformers","authors":["C Srihari, S Sunagar, RK Kamat, KS Raghavendra… - International Symposium on …, 2023"],"snippet":"Natural language generation is one of the major tasks that comes under Natural Language Processing and, Question Generation (QG) and Question Answering (QA) are two NLP-based tasks that have found widespread application. The QA and QG …","url":["https://link.springer.com/chapter/10.1007/978-981-19-8094-7_15"]}
-{"year":"2023","title":"Question Answer Generation in Bengali: Mitigating the scarcity of QA datasets in a low-resource language","authors":["MSSA Al Fayad, CMA Ehsan, AR Kamal"],"snippet":"… For fastText word embeddings, we use the pretrained word vector model for Bengali, trained on Common Crawl7 and Wikipedia. For back-translation, we use the \"csebuetnlp/banglat5_nmt_bn_en\" model checkpoint. To train our answer span …","url":["http://www.afnlp.org/conferences/ijcnlp2023/proceedings/main-long/cdrom/pdf/2023.ijcnlp-long.29.pdf"]}
-{"year":"2023","title":"Question Answering Chatbots for Biomedical Research using Transformers","authors":["E Xygi, AD Andriopoulos, DA Koutsomitropoulos"],"snippet":"Professionals as well as the general public need effective help to access, understand and consume complex biomedical concepts. The existence of an interaction environment capable of automatically processing such information-thus …","url":["https://www.ceid.upatras.gr/webpages/koutsomi/pdf/icaiic2023.pdf"]}
-{"year":"2023","title":"Question Answering System for Tamil Using Deep Learning","authors":["B Antony, NRR Paul - Speech and Language Technologies for Low …, 2023"],"snippet":"Tamil, a Dravidian language family member, is widely spoken in numerous Indian states. But languages like Tamil, are underrepresented on the web. Many NLP models perform worse with these languages when compared to English, the effects …","url":["https://link.springer.com/chapter/10.1007/978-3-031-33231-9_17"]}
-{"year":"2023","title":"QUESTION GENERATION AGENT","authors":["A Azzi, V Cavalli-Sforza - 2023"],"snippet":"According to recent studies that highlight the impact of technology on modern students’ learning, it came to light that modern tools increase learners’ interactivity. However, there is still an absence of modern technological tools that can be helpful …","url":["http://www.aui.ma/sse-capstone-repository/pdf/spring2023/QUESTION%20GENERATION%20AGENT.pdf"]}
-{"year":"2023","title":"Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities","authors":["J Bai, S Bai, S Yang, S Wang, S Tan, P Wang, J Lin… - arXiv preprint arXiv …, 2023"],"snippet":"… In order to improve the text-oriented tasks, we collect pdf and HTML format data from Common Crawl3 and generate synthetic OCR data in English and Chinese language with natural scenery background, following Kim et al. (2022). Finally, we …","url":["https://arxiv.org/pdf/2308.12966"]}
-{"year":"2023","title":"Rapidgzip: Parallel Decompression and Seeking in Gzip Files Using Cache Prefetching","authors":["M Knespel, H Brunst - Proceedings of the 32nd International Symposium on …, 2023"],"snippet":"… 吀栀e multiple petabytes large Common Crawl [8] dataset is also distributed as a set of gzip-compressed 昀椀les. A pipeline for decompressing and preprocessing such data, eg, for use in machine learning context, would bene昀椀t from being …","url":["https://dl.acm.org/doi/abs/10.1145/3588195.3592992"]}
-{"year":"2023","title":"RAVEN: Stateless Rapid IP Address Variation for Enterprise Networks.","authors":["L Wang, H Kim, P Mittal, J Rexford - Proc. Priv. Enhancing Technol., 2023"],"snippet":"Enterprise networks face increasing threats against the privacy of their clients. Existing enterprise services like Network Address Translation (NAT) offer limited privacy protection, at the cost of requiring per-flow state. In this paper, we introduce …","url":["https://petsymposium.org/2023/files/papers/issue3/popets-2023-0077.pdf"]}
-{"year":"2023","title":"Re-examining cross-cultural similarity judgments using language statistics","authors":["KN Le, S Gao, MC Frank, A Carstensen - Proceedings of the Annual Meeting of the …, 2023"],"snippet":"… These models were trained on Common Crawl and Wikipedia using fastText and use character n-grams of length 5, and 10 negative examples. The training used a Continuous Bag of Words with position-weights and a window of size 5. From these …","url":["https://escholarship.org/content/qt2gf8p2pn/qt2gf8p2pn.pdf"]}
-{"year":"2023","title":"Realistic but Non-Identifiable Synthetic User Data Generation","authors":["I Noble, I Vendrov, X Xu, D Ramachandran - 2023"],"snippet":"… Recent revolutions in Computer Vision and Natural Language Processing are often credited to the use of massive datasets such as ImageNet [1] and Common Crawl [2], which dramatically improved performance across a multitude of tasks, and …","url":["https://reclist.io/kdd2023-cup/papers/EVALRS2023_paper_1.pdf"]}
-{"year":"2023","title":"Reclaiming Data Agency in the Age of Ubiquitous Machine Learning","authors":["EJ Wenger - 2023"],"snippet":"… For example, text generation models like ChatGPT are trained on datasets like Common Crawl [5], which is an open repository containing … Or at least this is the operating assumption of ML developers who create large-scale internet datasets like …","url":["https://search.proquest.com/openview/7542a8303694795501071b1917e60a98/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Reclaiming the Digital Commons: A Public Data Trust for Training Data","authors":["A Chan, H Bradley, N Rajkumar - arXiv preprint arXiv:2303.09001, 2023"],"snippet":"… The data trust could also start from existing efforts, such as the Common Crawl We emphasize that the process of scraping data should be a continual, iterative process given the continual growth in the amount of internet data [100]. The data …","url":["https://arxiv.org/pdf/2303.09001"]}
-{"year":"2023","title":"Recommending Answers to Math Questions Using KL-Divergence and the Approximate XML Tree Matching Approach","authors":["S Gao - 2023"],"snippet":"… The dataset used by ChatGPT to train the language model is Common Crawl dataset that includes nearly a trillion of words. ChatGPT, which uses a large unsupervised corpus of tokens to train the language model, applies alternating …","url":["https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=10975&context=etd"]}
-{"year":"2023","title":"Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models","authors":["T Ahmed, S Ghosh, C Bansal, T Zimmermann, X Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"Incident management for cloud services is a complex process involving several steps and has a huge impact on both service health and developer productivity. On-call engineers require significant amount of domain knowledge and manual effort for …","url":["https://arxiv.org/pdf/2301.03797"]}
-{"year":"2023","title":"Red AI? Inconsistent Responses from GPT3. 5 Models on Political Issues in the US and China","authors":["D Zhou, Y Zhang - arXiv preprint arXiv:2312.09917, 2023"],"snippet":"The rising popularity of ChatGPT and other AI-powered large language models (LLMs) has led to increasing studies highlighting their susceptibility to mistakes and biases. However, most of these studies focus on models trained on English texts. Taking an …","url":["https://arxiv.org/pdf/2312.09917"]}
-{"year":"2023","title":"ReDASPersuasion at SemEval-2023 Task 3: Persuasion Detection using Multilingual Transformers and Language Agnostic Features","authors":["FZ Qachfar, R Verma - Proceedings of the The 17th International Workshop on …, 2023"],"snippet":"This paper describes a multilingual persuasion detection system that incorporates persuasion technique attributes for a multi-label classification task. The proposed method has two advantages. First, it combines persuasion features with a sequence …","url":["https://aclanthology.org/2023.semeval-1.293.pdf"]}
-{"year":"2023","title":"Regret and Hope on Transformers: An Analysis of Transformers on Regret and Hope Speech Detection Datasets","authors":["G Sidorov, F Balouchzahi, S Butt, A Gelbukh - Applied Sciences, 2023"],"snippet":"… than BERT, including additional data from CommonCrawl and the WebText dataset. The training … XLNet was trained on a large corpus of text from Wikipedia and the CommonCrawl dataset. … The model was trained on a large corpus of text …","url":["https://www.mdpi.com/2076-3417/13/6/3983"]}
-{"year":"2023","title":"Regulating ChatGPT and other Large Generative AI Models","authors":["P Hacker, A Engel, M Mauer - arXiv preprint arXiv:2302.02337, 2023"],"snippet":"Large generative AI models (LGAIMs), such as ChatGPT or Stable Diffusion, are rapidly transforming the way we communicate, illustrate, and create. However, AI regulation, in the EU and beyond, has primarily focused on conventional AI models …","url":["https://arxiv.org/pdf/2302.02337"]}
-{"year":"2023","title":"Reinforced UI Instruction Grounding: Towards a Generic UI Task Automation API","authors":["Z Zhang, W Xie, X Zhang, Y Lu - arXiv preprint arXiv:2310.04716, 2023"],"snippet":"… As for the experiments with desktop data, we collect about 37K UI images from Common Crawl2, an open repository of web crawl data. We follow the practices in the open repository3 of (Burns et al., 2022) to generate 0.5M image-instruction pairs …","url":["https://arxiv.org/pdf/2310.04716"]}
-{"year":"2023","title":"RelBERT: Embedding Relations with Language Models","authors":["A Ushio, J Camacho-Collados, S Schockaert - arXiv preprint arXiv:2310.00299, 2023"],"snippet":"Many applications need access to background knowledge about how different concepts and entities are related. Although Knowledge Graphs (KG) and Large Language Models (LLM) can address this need to some extent, KGs are inevitably …","url":["https://arxiv.org/pdf/2310.00299"]}
-{"year":"2023","title":"ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models","authors":["I Mirzadeh, K Alizadeh, S Mehta, CC Del Mundo… - arXiv preprint arXiv …, 2023"],"snippet":"… We chose RefinedWeb because it is a high-quality subset of Common Crawl, which is often used in the pretraining phase of LLMs, including Llama, Falcon, and OPT. We also use the validation split of WikiText [54] for measuring the sparsity and …","url":["https://arxiv.org/pdf/2310.04564"]}
-{"year":"2023","title":"Remodelling internet infrastructure: A first look at platform governance in the era of ChatGPT","authors":["F McKelvey, R Hunt - 2023"],"snippet":"… nature and scope of OpenAI’s filtering of the Common Crawl set, rather mysterious. Common Crawl is a nonprofit organization that relies on a broad … Ostensibly, Common Crawl operates on a commons-based production model. At its launch in …","url":["https://osf.io/preprints/mediarxiv/9zqje/download"]}
-{"year":"2023","title":"RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model","authors":["F Bie, Y Yang, Z Zhou, A Ghanem, M Zhang, Z Yao… - arXiv preprint arXiv …, 2023"],"snippet":"… The image-text pairs are retrieved from random web pages with Common Crawl [224] and are filtered by CLIP score to ensure image-text alignment. Beyond the textual descriptions, LAION400M also equips users with CLIP embeddings and KNN …","url":["https://arxiv.org/pdf/2309.00810"]}
-{"year":"2023","title":"Report of the 1st Workshop on Generative AI and Law","authors":["AF Cooper, K Lee, J Grimmelmann, D Ippolito… - arXiv preprint arXiv …, 2023"],"snippet":"This report presents the takeaways of the inaugural Workshop on Generative AI and Law (GenLaw), held in July 2023. A cross-disciplinary group of practitioners and scholars from computer science and law convened to discuss the technical, doctrinal …","url":["https://arxiv.org/pdf/2311.06477"]}
-{"year":"2023","title":"Report on the 16th Round of NII Testbeds and Community for Information Access Research (NTCIR-16)","authors":["T Yamamoto, Z Dou, N Kando, CLA Clarke, MP Kato… - ACM SIGIR Forum, 2023"],"snippet":"… Firstly, Chuweb21, a subset of the Common Crawl dataset, is introduced for this task. Chuweb21 contains 3,402,457 domains and 858,616,203 English web pages. Secondly, two types of relevance assessment are introduced: the Gold version given …","url":["https://dl.acm.org/doi/abs/10.1145/3582900.3582911"]}
-{"year":"2023","title":"Requirements Classification for Smart Allocation: A Case Study in the Railway Industry","authors":["S Bashir, M Abbas, A Ferrari, M Saadatmand…"],"snippet":"Allocation of requirements to different teams is a typical preliminary task in large-scale system development projects. This critical activity is often performed manually and can benefit from automated requirements classification techniques. To date, limited …","url":["http://www.es.mdh.se/pdf_publications/6697.pdf"]}
-{"year":"2023","title":"Research on The Evaluation of Token Imbalance Degree in NMT Corpus","authors":["H WANG, L YU, H WANG - ACTA ELECTONICA SINICA, 2023"],"snippet":"… 1 实验数据与参数设置 本文选择国际机器翻译大赛 WMT15 的 NewsCommentary-v10 和 Common Crawl corpus 以及 WMT21 … 其中,News-Commentary-v10 和 NewsCommentary-v16 语料库的词表规模设置为 30K,Com⁃ mon Crawl corpus语料库的词表规模设置为200K …","url":["https://www.ejournal.org.cn/EN/article/downloadArticleFile.do?attachType=PDF&id=13181"]}
-{"year":"2023","title":"Research proposal content extraction using natural language processing and semi-supervised clustering: A demonstration and comparative analysis","authors":["BM Knisely, HH Pavliscsak - Scientometrics, 2023"],"snippet":"Funding institutions often solicit text-based research proposals to evaluate potential recipients. Leveraging the information contained in these documents could help institutions understand the supply of research within their domain. In this work, an …","url":["https://link.springer.com/article/10.1007/s11192-023-04689-3"]}
-{"year":"2023","title":"Resolving Elliptical Compounds in German Medical Text","authors":["N Kammer, F Borchert, S Winkler, G De Melo… - The 22nd Workshop on …, 2023"],"snippet":"… mT5 closely follows the original T5 architecture, but was trained on a multilingual Common Crawl-based dataset called mC4 with 101 languages, including German. We performed some preliminary experiments with other models. These included a …","url":["https://aclanthology.org/2023.bionlp-1.26.pdf"]}
-{"year":"2023","title":"Responsible Task Automation: Empowering Large Language Models as Responsible Task Automators","authors":["Z Zhang, X Zhang, W Xie, Y Lu - arXiv preprint arXiv:2306.01242, 2023"],"snippet":"The recent success of Large Language Models (LLMs) signifies an impressive stride towards artificial general intelligence. They have shown a promising prospect in automatically completing tasks upon user instructions, functioning as brain-like …","url":["https://arxiv.org/pdf/2306.01242"]}
-{"year":"2023","title":"Rethinking Homework in the Age of Artificial Intelligence","authors":["H Ibrahim, R Asim, F Zaffar, T Rahwan, Y Zaki - IEEE Intelligent Systems, 2023"],"snippet":"… ChatGPT, for instance, is trained on a curated version of the common crawl dataset, built upon text available on the Internet. However, if this content is not properly cited, it could be considered a violation of copyright laws. Indeed, this has …","url":["https://ieeexplore.ieee.org/iel7/9670/10111508/10111520.pdf"]}
-{"year":"2023","title":"Retrieving Webpages Using Online Discussions","authors":["K Ros, M Jin, J Levine, CX Zhai - Proceedings of the 2023 ACM SIGIR International …, 2023"],"snippet":"… query search over all training, validation, and testing splits, it could be expanded by collecting more webpages (eg, from the Common Crawl corpus [6]). … http://web.archive.org/web/ 20221002030422/https://campuswire.com/chatrooms [6] Common Crawl. 2022 …","url":["https://dl.acm.org/doi/abs/10.1145/3578337.3605139"]}
-{"year":"2023","title":"RetVec: Resilient and Efficient Text Vectorizer","authors":["E Bursztein, M Zhang, O Vallis, X Jia, A Kurakin - arXiv preprint arXiv:2302.09207, 2023"],"snippet":"This paper describes RetVec, a resilient multilingual embedding scheme designed for neural-based text processing, including small-text classification and large-language models. RetVec combines a novel character encoding with an optional small model …","url":["https://arxiv.org/pdf/2302.09207"]}
-{"year":"2023","title":"Reveal the Unknown: Out-of-Knowledge-Base Mention Discovery with Entity Linking","authors":["H Dong, J Chen, Y He, Y Liu, I Horrocks - arXiv preprint arXiv:2302.07189, 2023"],"snippet":"Discovering entity mentions that are out of a Knowledge Base (KB) from texts plays a critical role in KB maintenance, but has not yet been fully explored. The current methods are mostly limited to the simple threshold-based approach and feature-based …","url":["https://arxiv.org/pdf/2302.07189"]}
-{"year":"2023","title":"Revealing Media Bias in News Articles: NLP Techniques for Automated Frame Analysis","authors":["F Hamborg - 2023"],"snippet":"This open access book presents an interdisciplinary approach to reveal biases in English news articles reporting on a given political event. The approach named person-oriented framing analysis identifies the coverage’s different perspectives on …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=zi-wEAAAQBAJ&oi=fnd&pg=PR7&dq=commoncrawl&ots=gws7ZxYf_L&sig=o7ezwsVJPQVwe91PdSNmqiYoDJg"]}
-{"year":"2023","title":"Review on Query focused Multi-Document Summarization (QMDS) with Comparative Analysis","authors":["P Roy, S Kundu - ACM Computing Surveys, 2023"],"snippet":"… AQUAMUSE is one of the recent question-answering datasets generated using the Google Natural Questions (NQ) dataset [98] and Common Crawl corpus [160]. The inputs are matched documents from the Common Crawl corpus, whereas the …","url":["https://dl.acm.org/doi/pdf/10.1145/3597299"]}
-{"year":"2023","title":"REVIEWTAG: TAGGING AMAZON NEGATIVE PRODUCT REVIEW WITH DEEP LEARNING","authors":["P Kumari - 2023"],"snippet":"… It is trained on a massive dataset of text, Common Crawl, consisting of over 600 billion tokens from various sources, including web pages, news articles, and social media posts [31]. The model outputs 2 million word vectors, each with a …","url":["https://uhcl-ir.tdl.org/bitstream/handle/10657.1/3009/KUMARI-MASTERSTHESIS-2023.pdf?sequence=1&isAllowed=y"]}
-{"year":"2023","title":"Revisiting and Improving Retrieval-Augmented Deep Assertion Generation","authors":["W Sun, H Li, M Yan, Y Lei, H Zhang - arXiv preprint arXiv:2309.10264, 2023"],"snippet":"Unit testing validates the correctness of the unit under test and has become an essential activity in software development process. A unit test consists of a test prefix that drives the unit under test into a particular state, and a test oracle (eg, assertion) …","url":["https://arxiv.org/pdf/2309.10264"]}
-{"year":"2023","title":"Revisiting Entropy Rate Constancy in Text","authors":["V Verma, N Tomlin, D Klein - arXiv preprint arXiv:2305.12084, 2023"],"snippet":"… 3.2 Common Crawl News We include a subset of the Common Crawl News Dataset due to its chronological diversity. In particular, we run the majority of our experiments on GPT-2; because articles in the NYT … To address this concern, we …","url":["https://arxiv.org/pdf/2305.12084"]}
-{"year":"2023","title":"Revisiting non-English Text Simplification: A Unified Multilingual Benchmark","authors":["MJ Ryan, T Naous, W Xu - arXiv preprint arXiv:2305.15678, 2023"],"snippet":"Recent advancements in high-quality, large-scale English resources have pushed the frontier of English Automatic Text Simplification (ATS) research. However, less work has been done on multilingual text simplification due to the lack of a diverse …","url":["https://arxiv.org/pdf/2305.15678"]}
-{"year":"2023","title":"Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Processing","authors":["A Ghaddar, Y Wu, S Bagga, A Rashid, K Bibi… - Proceedings of the 2022 …, 2022"],"snippet":"There is a growing body of work in recent years to develop pre-trained language models (PLMs) for the Arabic language. This work addresses two major problems in existing Arabic PLMs that limit the progress of the Arabic NLU and NLG fields. First …","url":["https://aclanthology.org/2022.emnlp-main.205.pdf"]}
-{"year":"2023","title":"Revolutionizing subjective assessments: A three-pronged comprehensive approach with NLP and deep learning","authors":["R Agrawal, H Mishra, I Kandasamy, SR Terni… - Expert Systems with …, 2024"],"snippet":"… The model also uses the CCNet dataset, extracted from a common crawl with a different filtering process than for OSCAR. The model’s performance measure was impossible for NER due to the limited availability of annotated corpora. The model’s …","url":["https://www.sciencedirect.com/science/article/pii/S095741742302972X"]}
-{"year":"2023","title":"RIATIG: Reliable and Imperceptible Adversarial Text-to-Image Generation With Natural Prompts","authors":["H Liu, Y Wu, S Zhai, B Yuan, N Zhang - Proceedings of the IEEE/CVF Conference on …, 2023"],"snippet":"The field of text-to-image generation has made remarkable strides in creating high-fidelity and photorealistic images. As this technology gains popularity, there is a growing concern about its potential security risks. However, there has been limited …","url":["https://openaccess.thecvf.com/content/CVPR2023/papers/Liu_RIATIG_Reliable_and_Imperceptible_Adversarial_Text-to-Image_Generation_With_Natural_Prompts_CVPR_2023_paper.pdf"]}
-{"year":"2023","title":"Right to be Forgotten in the Era of Large Language Models: Implications, Challenges, and Solutions","authors":["D Zhang, P Finckenberg-Broman, T Hoang, S Pan… - arXiv preprint arXiv …, 2023"],"snippet":"… For example, Common Crawl data is 60% of the training data used in GPT-3 [3]; 50% of PaLM’s training dataset is social media conversations [4]; and OpenAI and Google have extensively used Reddit user posts in their large language models [5, 6 …","url":["https://arxiv.org/pdf/2307.03941"]}
-{"year":"2023","title":"ROBBIE: Robust Bias Evaluation of Large Generative Language Models","authors":["D Esiobu, X Tan, S Hosseini, M Ung, Y Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"As generative large language models (LLMs) grow more performant and prevalent, we must develop comprehensive enough tools to measure and improve their fairness. Different prompt-based datasets can be used to measure social bias across …","url":["https://arxiv.org/pdf/2311.18140"]}
-{"year":"2023","title":"RoBERTa-CoA: RoBERTa-Based Effective Finetuning Method Using Co-Attention","authors":["JH Kim, SW Park, JY Kim, J Park, SH Jung, CB Sim - IEEE Access, 2023"],"snippet":"… has improved upon BERT by adding Common CrawlNews (CC-News), open web text, and story data, applying dynamic masking with multiple masked words generated per sentence, removing NSP, and increasing the batch size from 256 to …","url":["https://ieeexplore.ieee.org/iel7/6287639/10005208/10299620.pdf"]}
-{"year":"2023","title":"Robust Information Extraction From Unstructured Documents","authors":["M Namysł - 2023"],"snippet":"In computer science, robustness can be thought of as the ability of a system to handle erroneous or nonstandard input during execution. This thesis studies the robustness of the methods that extract structured information from unstructured …","url":["https://bonndoc.ulb.uni-bonn.de/xmlui/bitstream/handle/20.500.11811/10560/6921.pdf?sequence=2"]}
-{"year":"2023","title":"ROZAM at SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis","authors":["M Rostamkhani, G Zamaninejad, S Eetemadi - … of the The 17th International Workshop …, 2023"],"snippet":"We build a model using large multilingual pretrained language model XLM-T for regression task and fine-tune it on the MINT (Multilingual INTmacy) analysis dataset which covers 6 languages for training and 4 languages for testing zero-shot …","url":["https://aclanthology.org/2023.semeval-1.278.pdf"]}
-{"year":"2023","title":"RTQ: Rethinking Video-language Understanding Based on Image-text Model","authors":["X Wang, Y Li, T Gan, Z Zhang, J Lv, L Nie - Proceedings of the 31st ACM International …, 2023"],"snippet":"… Besides, Flamingo uses 2 billion image-text pairs and 27 million video-text pairs, while mPLUG-B uses 2 million videotext pairs and a large natural language corpus (WikiCorpus and common crawl) as the pre-training data. It is noteworthy that HiTeA [50] …","url":["https://dl.acm.org/doi/abs/10.1145/3581783.3612152"]}
-{"year":"2023","title":"RuSentNE-2023: Evaluating Entity-Oriented Sentiment Analysis on Russian News Texts","authors":["A Golubev, N Rusnachenko, N Loukachevitch - arXiv preprint arXiv:2305.17679, 2023"],"snippet":"… The authors selected articles of 14 US newspapers from the Common Crawl news crawl (CC-NEWS). Mentions of named entities such as PERSON or ORG were automatically identified, and corresponding sentences were extracted. The …","url":["https://arxiv.org/pdf/2305.17679"]}
-{"year":"2023","title":"s-elBat: a Semantic Interpretation Approach for Messy taBle-s","authors":["M Cremaschi, R Avogadro, D Chieregato - Semantic Web Challenge on Tabular Data …, 2022"],"snippet":"This paper describes s-elBat, a Semantic Table Interpretation approach. The approach inherits and improves the part of the techniques belonging to the MantisTable, an approach used and tested in previous editions of the SemTab …","url":["https://ceur-ws.org/Vol-3320/paper7.pdf"]}
-{"year":"2023","title":"Sailing the Data Sea to Advance Research on the Sustainable Development Goals","authors":["A Spezzatti, E Kheradmand, K Gupta, M Peras… - The Ethics of Artificial …, 2023"],"snippet":"The Sustainable Development Goals (SDGs) are the framework adopted by the global community to encourage taking actions on the multiple challenges facing the world today to ensure environmental protection, health and well-being, and …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21147-8_24"]}
-{"year":"2023","title":"Saisiyat Is Where It Is At! Insights Into Backdoors And Debiasing Of Cross Lingual Transformers For Named Entity Recognition","authors":["RA Calix, J Ben-Joseph, N Lopatina, R Ashley… - 2022 IEEE International …, 2022"],"snippet":"… This RoBERTa XLM model was pre-trained on text from 100 languages which came from a Common crawl and had a size of around 2.5 terabytes. Not all languages in this corpus are equally represented in terms of amount of text and …","url":["https://ieeexplore.ieee.org/abstract/document/10020403/"]}
-{"year":"2023","title":"Salogni at GeoLingIt: Geolocalization by Fine-tuning BERT","authors":["I Salogni - Proceedings of the Eighth Evaluation Campaign of …, 2023"],"snippet":"… In this work, the models pre-trained on a miscellaneous corpus (umberto-commoncrawl-… work the best performing ones are the 32k umberto-commoncrawl-cased-v1 and the 31k bert-base-… However it is necessary to remember that only umberto-commoncrawl-cased-v1 …","url":["https://ceur-ws.org/Vol-3473/paper17.pdf"]}
-{"year":"2023","title":"SAND: Semantic Annotation of Numeric Data in Web Tables","authors":["Y Su, D Rafiei, BK Nazari - Proceedings of the 32nd ACM International …, 2023"],"snippet":"A large portion of quantitative information about entities is expressed as Web tables, and these tables often lack proper schema and annotation, which introduces challenges for the purpose of querying and analysis. In this paper, we introduce …","url":["https://dl.acm.org/doi/abs/10.1145/3583780.3615046"]}
-{"year":"2023","title":"Sarcasm Detection in English and Arabic Tweets Using Transformer Models","authors":["R Lad - 2023"],"snippet":"… XLM-RoBERTa is pre-trained on 2.5TB of filtered CommonCrawl data containing text from 100 languages [6]. RoBERTa, on the other hand… , in gigabytes, between CommonCrawl and Wikipedia data across a plethora of languages. CommonCrawl …","url":["https://digitalcommons.dartmouth.edu/cgi/viewcontent.cgi?article=1019&context=cs_senior_theses"]}
-{"year":"2023","title":"SC-Block: Supervised Contrastive Blocking within Entity Resolution Pipelines","authors":["A Brinkmann, R Shraga, C Bizer - arXiv preprint arXiv:2303.03132, 2023","C Bizer"],"snippet":"… In total, 502 million records describing products and 55 million records describing local businesses were extracted from the Common Crawl. Due to the shallow coverage of the Common Crawl, the extracted data only represents a fraction of the …","url":["https://2024.eswc-conferences.org/wp-content/uploads/2024/04/146640116.pdf","https://arxiv.org/pdf/2303.03132"]}
-{"year":"2023","title":"Scalable 3D Captioning with Pretrained Models","authors":["T Luo, C Rockwell, H Lee, J Johnson - arXiv preprint arXiv:2306.07279, 2023"],"snippet":"We introduce Cap3D, an automatic approach for generating descriptive text for 3D objects. This approach utilizes pretrained models from image captioning, image-text alignment, and LLM to consolidate captions from multiple views of a 3D asset …","url":["https://arxiv.org/pdf/2306.07279"]}
-{"year":"2023","title":"Scalable and Accurate Self-Supervised Multimodal Representation Learning Without Aligned Video and Text Data","authors":["V Lialin, S Rawls, D Chan, S Ghosh, A Rumshisky… - Proceedings of the IEEE …, 2023"],"snippet":"… Using Wikipedia, Common Crawl, and other text sources for dataset mining was essential in the recent NLP progress [17, 6]. CLIP [52] and ALIGN [27] demonstrated the importance of the scale of weakly-supervised data for images. …","url":["https://openaccess.thecvf.com/content/WACV2023W/Pretrain/papers/Lialin_Scalable_and_Accurate_Self-Supervised_Multimodal_Representation_Learning_Without_Aligned_Video_WACVW_2023_paper.pdf"]}
-{"year":"2023","title":"Scalable Extraction of Training Data from (Production) Language Models","authors":["M Nasr, N Carlini, J Hayase, M Jagielski, AF Cooper… - arXiv preprint arXiv …, 2023"],"snippet":"This paper studies extractable memorization: training data that an adversary can efficiently extract by querying a machine learning model without prior knowledge of the training dataset. We show an adversary can extract gigabytes of training data …","url":["https://arxiv.org/pdf/2311.17035"]}
-{"year":"2023","title":"SCALE: Scaling up the Complexity for Advanced Language Model Evaluation","authors":["V Rasiah, R Stern, V Matoshi, M Stürmer, I Chalkidis… - arXiv preprint arXiv …, 2023"],"snippet":"Recent strides in Large Language Models (LLMs) have saturated many NLP benchmarks (even professional domain-specific ones), emphasizing the need for novel, more challenging novel ones to properly assess LLM capabilities. In this …","url":["https://arxiv.org/pdf/2306.09237"]}
-{"year":"2023","title":"Scaling Expert Language Models with Unsupervised Domain Discovery","authors":["S Gururangan, M Li, M Lewis, W Shi, T Althoff… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models are typically trained densely: all parameters are updated with respect to all inputs. This requires synchronization of billions of parameters across thousands of GPUs. We introduce a simple but effective method to …","url":["https://arxiv.org/pdf/2303.14177"]}
-{"year":"2023","title":"Scaling Laws for Generative Mixed-Modal Language Models","authors":["A Aghajanyan, L Yu, A Conneau, WN Hsu… - arXiv preprint arXiv …, 2023"],"snippet":"… CommonCrawl). This also applies to auditory or visual modalities, which are captured with different sensors. Yet the decisions are not … (2022), and a custom image-text dataset scraped from Common Crawl. We remove all NSFW images and …","url":["https://arxiv.org/pdf/2301.03728"]}
-{"year":"2023","title":"Scaling Speech Technology to 1,000+ Languages","authors":["V Pratap, A Tjandra, B Shi, P Tomasello, A Babu… - arXiv preprint arXiv …, 2023"],"snippet":"… MMS-lab compared to Common Crawl, then we add it to the subset of words we include in our study. This enables us to evaluate on 51 languages of the FLEURS corpus since not all languages are covered by MMS-lab and we also need to find …","url":["https://arxiv.org/pdf/2305.13516"]}
-{"year":"2023","title":"Schema. org: How is it used?","authors":["MH Dang, A Gaignard, H Skaf-Molli, P Molli - International Semantic Web Conference …, 2023"],"snippet":"Schema.org defines a shared vocabulary for semantically annotating web pages. Due to the vast and diverse nature of the contributed annotations, it is not easy to understand the widespread use of Schema.org. In this poster, we rely on the …","url":["https://hal.science/hal-04250523/document"]}
-{"year":"2023","title":"Science Fact vs Science Fiction: A ChatGPT Immunological Review Experiment Gone Awry","authors":["J Wittmann - Immunology Letters, 2023"],"snippet":"Artificial intelligence (AI) has made great progress in recent years. The latest chatbot to make a splash is ChatGPT. To see if this type of AI could also be helpful in creating an immunological review article, I put a planned review on different classes …","url":["https://www.sciencedirect.com/science/article/pii/S0165247823000536"]}
-{"year":"2023","title":"SciFoodNER: Food Named Entity Recognition for Scientific Text","authors":["G Cenikj, G Petelin, BK Seljak, T Eftimov - 2022 IEEE International Conference on Big …, 2022"],"snippet":"… Apart from the data used for the pre-training of BERT model, RoBERTa is trained on data from 3 additional sources: the CommonCrawl News dataset [24], the OpenWebText corpus [25] and the Common Crawl Stories dataset [26]. BioBERT is …","url":["https://ieeexplore.ieee.org/abstract/document/10020459/"]}
-{"year":"2023","title":"SciOL and MuLMS-Img: Introducing a Large-Scale Multimodal Scientific Dataset and Models for Image-Text Tasks in the Scientific Domain","authors":["T Tarsi, H Adel, JH Metzen, D Zhang, M Finco… - Proceedings of the IEEE …, 2024"],"snippet":"In scientific publications, a substantial part of the information is expressed via figures containing images and diagrams. Hence, the retrieval of relevant figures given a natural language query is an important real-world task. However, due to the lack of …","url":["https://openaccess.thecvf.com/content/WACV2024/papers/Tarsi_SciOL_and_MuLMS-Img_Introducing_a_Large-Scale_Multimodal_Scientific_Dataset_and_WACV_2024_paper.pdf"]}
-{"year":"2023","title":"Scraping Data from Web Pages Using SPARQL Queries","authors":["R Burget - International Conference on Web Engineering, 2023"],"snippet":"… According to Web Data Commons statistics, structured data was available in 42% of the 33.8 million domains included in the Common Crawl corpus [3]. However, the use of structured data is growing slowly and is limited to certain domains. A large …","url":["https://link.springer.com/chapter/10.1007/978-3-031-34444-2_21"]}
-{"year":"2023","title":"Scrapism: A Manifesto","authors":["S Lavigne - Critical AI, 2023"],"snippet":"Web scraping is a technique for automatically downloading and processing web content or converting online text and other media into structured data. This article describes the role that web scraping plays for web businesses and machine …","url":["https://read.dukeupress.edu/critical-ai/article/382464/Scrapism-A-Manifesto"]}
-{"year":"2023","title":"SeaLLMs--Large Language Models for Southeast Asia","authors":["XP Nguyen, W Zhang, X Li, M Aljunied, Q Tan, L Cheng… - arXiv preprint arXiv …, 2023"],"snippet":"… data, we include web-based corpora such as Common Crawl2, journalistic content such as CC-News, text corpora with expertly-curated knowledge such as Wikipedia [9], and some scholarly publications. After collecting the data, we employ …","url":["https://arxiv.org/pdf/2312.00738"]}
-{"year":"2023","title":"Seals_Lab at SemEval-2023 Task 12: Sentiment Analysis for Low-resource African Languages, Hausa and Igbo","authors":["N Raychawdhary, A Das, G Dozier, CD Seals - … of the The 17th International Workshop …, 2023"],"snippet":"… The pretraining data includes 2.5 TB of filtered CommonCrawl data with 100 languages. … and also This particular model was trained on Common Crawl Corpus and the BBC news website. After our initial experiments, our task of sentiment …","url":["https://aclanthology.org/2023.semeval-1.208.pdf"]}
-{"year":"2023","title":"Search This Blog","authors":["H Josephson"],"snippet":"The California Effect occurs when California’s large market, its capacity to successfully regulate, its preference for stringent standards, the inability of the regulatory target to simply move beyond California’s jurisdiction, and non-divisibility …","url":["https://www.henryjos.com/p/a-california-effect-for-artificial.html"]}
-{"year":"2023","title":"Searching for Needles in a Haystack: On the Role of Incidental Bilingualism in PaLM's Translation Capability","authors":["E Briakou, C Cherry, G Foster - arXiv preprint arXiv:2305.10266, 2023"],"snippet":"Large, multilingual language models exhibit surprisingly good zero- or few-shot machine translation capabilities, despite having never seen the intentionally-included translation examples provided to typical neural translation systems. We investigate …","url":["https://arxiv.org/pdf/2305.10266"]}
-{"year":"2023","title":"SecureBERT and LLAMA 2 Empowered Control Area Network Intrusion Detection and Classification","authors":["X Li, H Fu - arXiv preprint arXiv:2311.12074, 2023"],"snippet":"… These models were trained on an extensive dataset comprising 2 trillion tokens sourced from various outlets such as web pages (CommonCrawl), open-source repository code (GitHub), Wikipedia content (in 20 different languages), public …","url":["https://arxiv.org/pdf/2311.12074"]}
-{"year":"2023","title":"Segmentation-Free Streaming Machine Translation","authors":["J Iranzo-Sánchez, J Iranzo-Sánchez, A Giménez… - arXiv preprint arXiv …, 2023"],"snippet":"Streaming Machine Translation (MT) is the task of translating an unbounded input text stream in real-time. The traditional cascade approach, which combines an Automatic Speech Recognition (ASR) and an MT system, relies on an intermediate …","url":["https://arxiv.org/pdf/2309.14823"]}
-{"year":"2023","title":"Selecting Shots for Demographic Fairness in Few-Shot Learning with Large Language Models","authors":["C Aguirre, K Sasse, I Cachola, M Dredze - arXiv preprint arXiv:2311.08472, 2023"],"snippet":"Recently, work in NLP has shifted to few-shot (in-context) learning, with large language models (LLMs) performing well across a range of tasks. However, while fairness evaluations have become a standard for supervised methods, little is known …","url":["https://arxiv.org/pdf/2311.08472"]}
-{"year":"2023","title":"Self-Attention-Based Bi-LSTM Model for Sentiment Analysis on Tweets about Distance Learning in Higher Education.","authors":["I Lasri, A Riadsolh, M Elbelkacemi - … Journal of Emerging Technologies in Learning, 2023"],"snippet":"For limiting the COVID-19 spread, countries around the world have implemented prevention measures such as lockdowns, social distancing, and the closers of educational institutions. Therefore, most academic activities are shifted to distance …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=18630383&AN=164443579&h=bStCT4%2BxfhAJRiq6NGagbm98POmb0gC%2Bd5I7CB55%2BSW7FEV7Tt4WhFTl4ZAtVC0Ydiqxw1onkLZNHmC7sVrrLg%3D%3D&crl=c"]}
-{"year":"2023","title":"Self-Deception: Reverse Penetrating the Semantic Firewall of Large Language Models","authors":["Z Wang, W Xie, K Chen, B Wang, Z Gui, E Wang - arXiv preprint arXiv:2308.11521, 2023"],"snippet":"Large language models (LLMs), such as ChatGPT, have emerged with astonishing capabilities approaching artificial general intelligence. While providing convenience for various societal needs, LLMs have also lowered the cost of generating harmful …","url":["https://arxiv.org/pdf/2308.11521"]}
-{"year":"2023","title":"Self-Influence Guided Data Reweighting for Language Model Pre-training","authors":["M Thakkar, T Bolukbasi, S Ganapathy, S Vashishth… - arXiv preprint arXiv …, 2023"],"snippet":"Language Models (LMs) pre-trained with self-supervision on large text corpora have become the default starting point for developing models for various NLP tasks. Once the pre-training corpus has been assembled, all data samples in the corpus are …","url":["https://arxiv.org/pdf/2311.00913"]}
-{"year":"2023","title":"Self-Supervised and Weakly-Supervised Domain-Adaptive Continual Pre-Training in Low-Resource Settings","authors":["A Alexandrov - 2023"],"snippet":"… Using this we process 3 Common Crawl dumps and extract all the available Bulgarian text from the .doc and .docx files they contain. Dump 2023-14 contains 52k documents and 75M words, dump 2022-49 contains 24k documents and 35M …","url":["https://www.research-collection.ethz.ch/bitstream/handle/20.500.11850/634894/1/Alexandrov_Anton.pdf"]}
-{"year":"2023","title":"Self-supervised learning in natural language processing","authors":["D Ruiter - 2023"],"snippet":"Most natural language processing (NLP) learning algorithms require labeled data. While this is given for a select number of (mostly English) tasks, the availability of labeled data is sparse or non-existent for the vast majority of use-cases. To alleviate …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/36090/1/Dissertation_final_mitDefense.pdf"]}
-{"year":"2023","title":"Self-supervised learning of multi-omics embeddings in the low-label, high-data regime","authors":["CJ Hurry, E Slade - arXiv preprint arXiv:2311.09962, 2023"],"snippet":"Contrastive, self-supervised learning (SSL) is used to train a model that predicts cancer type from miRNA, mRNA or RPPA expression data. This model, a pretrained FT-Transformer, is shown to outperform XGBoost and CatBoost, standard …","url":["https://arxiv.org/pdf/2311.09962"]}
-{"year":"2023","title":"Self-training Reduces Flicker in Retranslation-based Simultaneous Translation","authors":["S Sen, R Sennrich, B Zhang, B Haddow - Proceedings of the 17th Conference of the …, 2023"],"snippet":"In simultaneous translation, the retranslation approach has the advantage of requiring no modifications to the inference engine. However, in order to reduce the undesirable flicker in the output, previous work has resorted to increasing the …","url":["https://aclanthology.org/2023.eacl-main.270.pdf"]}
-{"year":"2023","title":"Semantic Information Extraction From Natural Language Using a Learning and Rule-Based Approach","authors":["V Singh - 2023"],"snippet":"Open Information Extraction (OIE) is a subset of Natural Language Processing (NLP) that constitutes the processing of natural language into structured and machinereadable data. This thesis uses data in Resource Description Framework (RDF) …","url":["https://keep.lib.asu.edu/system/files/c7/Singh_asu_0010N_23427.pdf"]}
-{"year":"2023","title":"SEMANTIC TEXT ANALYSIS USING ARTIFICIAL NEURAL NETWORKS BASED ON NEURAL-LIKE ELEMENTS WITH TEMPORAL SIGNAL SUMMATION","authors":["K Alexander, S Eugeny, K Dmitry, P Dmitry - Проблемы искусственного интеллекта, 2023"],"snippet":"… • and, of course, Internet web-pages collected, for example, in the CommonCrawl database [9] containing about a petabyte of data, although of low quality. Filtered versions of this base can already be used for training language models, such as the …","url":["https://cyberleninka.ru/article/n/semantic-text-analysis-using-artificial-neural-networks-based-on-neural-like-elements-with-temporal-signal-summation"]}
-{"year":"2023","title":"SemDeDup: Data-efficient learning at web-scale through semantic deduplication","authors":["A Abbas, K Tirumala, D Simig, S Ganguli, AS Morcos - arXiv preprint arXiv …, 2023"],"snippet":"Progress in machine learning has been driven in large part by massive increases in data. However, large web-scale datasets such as LAION are largely uncurated beyond searches for exact duplicates, potentially leaving much redundancy. Here …","url":["https://arxiv.org/pdf/2303.09540"]}
-{"year":"2023","title":"Semi-Supervised Dimensional Media Sentiment Analysis via Exploring Sample Relationships","authors":["P Liu, W Qian, H Li, J Cao - IEEE Transactions on Computational Social Systems, 2023"],"snippet":"Dimensional sentiment analysis (DSA) aims to recognize continuous real-valued annotations in multidimensional spaces such as valence-arousal space. It can serve as a sentiment analysis that is more fine-grained than traditional polarity …","url":["https://ieeexplore.ieee.org/abstract/document/10238426/"]}
-{"year":"2023","title":"Semi-supervised learning and bidirectional decoding for effective grammar correction in low-resource scenarios","authors":["Z Mahmoud, C Li, M Zappatore, A Solyman, A Alfatemi… - PeerJ Computer Science, 2023"],"snippet":"The correction of grammatical errors in natural language processing is a crucial task as it aims to enhance the accuracy and intelligibility of written language. However, developing a grammatical error correction (GEC) framework for low-resource …","url":["https://peerj.com/articles/cs-1639/"]}
-{"year":"2023","title":"SentAlign: Accurate and Scalable Sentence Alignment","authors":["S Steingrímsson, H Loftsson, A Way - arXiv preprint arXiv:2311.08982, 2023"],"snippet":"We present SentAlign, an accurate sentence alignment tool designed to handle very large parallel document pairs. Given user-defined parameters, the alignment algorithm evaluates all possible alignment paths in fairly large documents of …","url":["https://arxiv.org/pdf/2311.08982"]}
-{"year":"2023","title":"Sentence-Level Multimodal and Language-Agnostic Representations","authors":["PA Duquenne, H Schwenk, B Sagot - arXiv preprint arXiv:2308.11466, 2023"],"snippet":"We introduce SONAR, a new multilingual and multimodal fixed-size sentence embedding space. Our single text encoder, covering 200 languages, substantially outperforms existing sentence embeddings such as LASER3 and LabSE on the …","url":["https://arxiv.org/pdf/2308.11466"]}
-{"year":"2023","title":"SENTENCES SIMILARITY DETECTION IN INDONESIAN POETRY COMPARISON USING SIAMESE MALSTM","authors":["E Anggriawan, F Farid, RF Sari"],"snippet":"… It contains 2 million common crawl words with 300 dimensions, providing 600 billion word-vectors. FastText is different from Google word embedding because it does the analysis in the sub word context by providing the n-gram character level …","url":["http://www.icicel.org/ell/contents/2023/4/el-17-04-02.pdf"]}
-{"year":"2023","title":"Sentiment analysis in Portuguese tweets: an evaluation of diverse word representation models","authors":["D Vianna, F Carneiro, J Carvalho, A Plastino, A Paes - Language Resources and …, 2023"],"snippet":"During the past years, we have seen a steady increase in the number of social networks worldwide. Among them, Twitter has consolidated its position as one of the most influential social platforms, with Brazilian Portuguese speakers holding the fifth …","url":["https://link.springer.com/article/10.1007/s10579-023-09661-4"]}
-{"year":"2023","title":"Sentiment analysis in Tourism: Fine-tuning BERT or sentence embeddings concatenation?","authors":["I Bouabdallaoui, F Guerouate, S Bouhaddour, C Saadi… - arXiv preprint arXiv …, 2023"],"snippet":"Undoubtedly that the Bidirectional Encoder representations from Transformers is the most powerful technique in making Natural Language Processing tasks such as Named Entity Recognition, Question & Answers or Sentiment Analysis, however, the …","url":["https://arxiv.org/pdf/2312.07797"]}
-{"year":"2023","title":"Sentiment Analysis of Forest Fires on Social Media Networks Twitter Using the Long Short Term Memory (LSTM) Method","authors":["AA Aziz, W Maharani - KLIK: Kajian Ilmiah Informatika dan Komputer, 2023"],"snippet":"… This research will also build two corpus, namely the tweet corpus for the GloVe extension feature and the common crawl corpus for the FastText extension feature, to increase the model's accuracy. Classification of reviews through this process will …","url":["https://djournals.com/klik/article/download/866/563"]}
-{"year":"2023","title":"Sentiment analysis on Hindi tweets during COVID‐19 pandemic","authors":["A Saroj, A Thakur, S Pal - Computational Intelligence"],"snippet":"… The CBOW model learns by predicting the current word based on its context, and it was trained on Common Crawl and Wikipedia. Fasttext has given remarkable results in the English language. Still, in a regional language like Hindi, it is found …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/coin.12622"]}
-{"year":"2023","title":"Sentiment Analysis with Neural Models for Hungarian","authors":["LJ Laki, ZG Yang - Acta Polytechnica Hungarica, 2023"],"snippet":"Sentiment analysis is a powerful tool to gain insight into the emotional polarity of opinionated texts. Computerized applications can contribute to the establishment of nextgeneration models that can provide us with data of unprecedented quantity and …","url":["http://acta.uni-obuda.hu/Laki_Yang_134.pdf"]}
-{"year":"2023","title":"Separating the Wheat from the Chaff with BREAD: An open-source benchmark and metrics to detect redundancy in text","authors":["I Caswell, L Wang, I Papadimitriou - arXiv preprint arXiv:2311.06440, 2023"],"snippet":"Data quality is a problem that perpetually resurfaces throughout the field of NLP, regardless of task, domain, or architecture, and remains especially severe for lower-resource languages. A typical and insidious issue, affecting both training data and model …","url":["https://arxiv.org/pdf/2311.06440"]}
-{"year":"2023","title":"Sequence to Sequence Pre-Trained Model for Natural Language Processing","authors":["G Dhasmana, PK HR, G Prasad - … International Conference on Computer Science and …, 2023"],"snippet":"… Text available in wikipedia is of good quality but it is small for pre –trianed model On the other side common crawl web scrapes are massive but relatively low quality. Colossal clean crawled corpus which is called as C4 it can serve the purpose of pre …","url":["https://ieeexplore.ieee.org/abstract/document/10346822/"]}
-{"year":"2023","title":"Sequence‐to‐sequence transfer transformer network for automatic flight plan generation","authors":["Y Yang, S Qian, M Zhang, K Cai - IET Intelligent Transport Systems, 2023"],"snippet":"In this work, a machine translation framework is proposed to tackle the flight plan generation in the air transport field. Diverging from the traditional human expert‐based way, a novel sequence‐to‐sequence transfer transformer network to automatic flight …","url":["https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/itr2.12478"]}
-{"year":"2023","title":"Sequential Modeling Enables Scalable Learning for Large Vision Models","authors":["Y Bai, X Geng, K Mangalam, A Bar, A Yuille, T Darrell… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce a novel sequential modeling approach which enables learning a Large Vision Model (LVM) without making use of any linguistic data. To do this, we define a common format, \"visual sentences\", in which we can represent raw images …","url":["https://arxiv.org/pdf/2312.00785"]}
-{"year":"2023","title":"Sequential Text-based Knowledge Update with Self-Supervised Learning for Generative Language Models","authors":["HR Sung, YJ Tang, YC Cheng, PL Chen, TY Li… - Proceedings of the 32nd …, 2023"],"snippet":"… articles from Common Crawl3 that contain the information of ⟨𝑒1,𝑒2, ..., 𝑒𝑇 ⟩. The details are described as follows. Inspired by the concept in Gholipour Ghalandari et al. [11], we first collect the news events that are listed in Wiki Current …","url":["https://dl.acm.org/doi/abs/10.1145/3583780.3615188"]}
-{"year":"2023","title":"Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study","authors":["B Wang, W Ping, P Xu, L McAfee, Z Liu, M Shoeybi… - arXiv preprint arXiv …, 2023"],"snippet":"Large decoder-only language models (LMs) can be largely improved in terms of perplexity by retrieval (eg, RETRO), but its impact on text generation quality and downstream task accuracy is unclear. Thus, it is still an open question: shall we …","url":["https://arxiv.org/pdf/2304.06762"]}
-{"year":"2023","title":"Shared Language: Linguistic Similarity in an Algebra Discussion Forum","authors":["MP Banawan, J Shin, T Arner, R Balyan, WL Leite… - Computers, 2023"],"snippet":"Academic discourse communities and learning circles are characterized by collaboration, sharing commonalities in terms of social interactions and language. The discourse of these communities is composed of jargon, common terminologies …","url":["https://www.mdpi.com/2163962"]}
-{"year":"2023","title":"Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning","authors":["M Xia, T Gao, Z Zeng, D Chen - arXiv preprint arXiv:2310.06694, 2023"],"snippet":"The popularity of LLaMA (Touvron et al., 2023a;b) and other recently emerged moderate-sized large language models (LLMs) highlights the potential of building smaller yet powerful LLMs. Regardless, the cost of training such models from scratch …","url":["https://arxiv.org/pdf/2310.06694"]}
-{"year":"2023","title":"Short-Answer Grading for German: Addressing the Challenges","authors":["U Padó, Y Eryilmaz, L Kirschner - International Journal of Artificial Intelligence in …, 2023"],"snippet":"Short-Answer Grading (SAG) is a time-consuming task for teachers that automated SAG models have long promised to make easier. However, there are three challenges for their broad-scale adoption: A technical challenge regarding the need …","url":["https://link.springer.com/article/10.1007/s40593-023-00383-w"]}
-{"year":"2023","title":"Should ChatGPT and Bard Share Revenue with Their Data Providers? A New Business Model for the AI Era Advances in Artificial Intelligence and Machine Learning …","authors":["D Zhang - 2023"],"snippet":"… of data sources, including the CommonCrawl data, WebText, two internet-based books corpora, as well as English-language Wikipedia. The CommonCrawl data contains 410 billion tokens originally from billions of web pages collected by the …","url":["https://www.oajaiml.com/uploads/archivepdf/28781163.pdf"]}
-{"year":"2023","title":"Should ChatGPT and Bard Share Revenue with Their Data Providers? A New Business Model for the AI Era","authors":["D Zhang - arXiv preprint arXiv:2305.02555, 2023"],"snippet":"… sources, including the CommonCrawl data, WebText, two internetbased books corpora, as well as English-language Wikipedia. The CommonCrawl data contains 410 billion tokens originally from billions of web pages collected by the …","url":["https://arxiv.org/pdf/2305.02555"]}
-{"year":"2023","title":"Should ChatGPT be Biased? Challenges and Risks of Bias in Large Language Models","authors":["E Ferrara - arXiv preprint arXiv:2304.03738, 2023"],"snippet":"As the capabilities of generative language models continue to advance, the implications of biases ingrained within these models have garnered increasing attention from researchers, practitioners, and the broader public. This article …","url":["https://arxiv.org/pdf/2304.03738"]}
-{"year":"2023","title":"Sidlr: Slot and intent detection models for low-resource language varieties","authors":["SY Kwon, G Bhatia, EMB Nagoudi, AA Inciarte… - Tenth Workshop on NLP for …, 2023"],"snippet":"Intent detection and slot filling are two critical tasks in spoken and natural language understandingfor task-oriented dialog systems. In this work, we describe our participation in slot and intent detection for low-resource language varieties (SID4LR)(Aepli …","url":["https://aclanthology.org/2023.vardial-1.24.pdf"]}
-{"year":"2023","title":"SIEVE: MULTIMODAL DATASET PRUNING USING IMAGE CAPTIONING MODELS","authors":["A Mahmoud, M Elhoushi, A Abbas, Y Yang, N Ardalani… - arXiv preprint arXiv …, 2023"],"snippet":"… To pretrain CLIP, billions of image-text pairs are collected using common crawl The raw data is highly diverse but contains many noisy image-text pairs, including low quality images, low quality alternative text (alt-text), and misaligned image-text …","url":["https://arxiv.org/pdf/2310.02110"]}
-{"year":"2023","title":"SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore","authors":["S Min, S Gururangan, E Wallace, H Hajishirzi… - arXiv preprint arXiv …, 2023"],"snippet":"The legality of training language models (LMs) on copyrighted or otherwise restricted data is under intense debate. However, as we show, model performance significantly degrades if trained only on low-risk text (eg, out-of-copyright books or …","url":["https://arxiv.org/pdf/2308.04430"]}
-{"year":"2023","title":"Simple LLM Prompting is State-of-the-Art for Robust and Multilingual Dialogue Evaluation","authors":["J Mendonça, P Pereira, JP Carvalho, A Lavie… - arXiv preprint arXiv …, 2023"],"snippet":"… This model is the multilingual version of RoBERTa, pretrained on CommonCrawl data containing 100 languages. We used a single Quadro RTX 6000 24GB GPU for the encoder experiments, and accessed ChatGPT (gpt-3.5-turbo) in late March using …","url":["https://arxiv.org/pdf/2308.16797"]}
-{"year":"2023","title":"Simple Yet Effective Neural Ranking and Reranking Baselines for Cross-Lingual Information Retrieval","authors":["J Lin, D Alfonso-Hermelo, V Jeronymo, E Kamalloo… - arXiv preprint arXiv …, 2023"],"snippet":"The advent of multilingual language models has generated a resurgence of interest in cross-lingual information retrieval (CLIR), which is the task of searching documents in one language with queries from another. However, the rapid pace of …","url":["https://arxiv.org/pdf/2304.01019"]}
-{"year":"2023","title":"Simulating Users in Interactive Web Table Retrieval","authors":["B Engelmann, T Breuer, P Schaer - arXiv preprint arXiv:2310.11931, 2023"],"snippet":"… Here, tables, with their context, are added from the Common Crawl dataset. Tables are thus present in different modalities, such as page titles, entities, text before/after, and the table itself. Modality relevance assessments were created by crowdsourcing. …","url":["https://arxiv.org/pdf/2310.11931"]}
-{"year":"2023","title":"Sinhala Part of Speech Tagger using Deep Learning Techniques","authors":["M Sathsarani, T Thalawaththa, NK Galappaththi… - 2022 6th International …, 2022"],"snippet":"Natural Language Processing (NLP) is a sub-field of Artificial Intelligence (AI) that consists of a collection of computational methods motivated by theory for the automated classification and reflection of human languages. The foundation for …","url":["https://ieeexplore.ieee.org/abstract/document/10026395/"]}
-{"year":"2023","title":"Sinhala-English Word Embedding Alignment: Introducing Datasets and Benchmark for a Low Resource Language","authors":["K Wickramasinghe, N de Silva - arXiv preprint arXiv:2311.10436, 2023"],"snippet":"Since their inception, embeddings have become a primary ingredient in many flavours of Natural Language Processing (NLP) tasks supplanting earlier types of representation. Even though multilingual embeddings have been used for the …","url":["https://arxiv.org/pdf/2311.10436"]}
-{"year":"2023","title":"Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models","authors":["MF Chen, N Roberts, K Bhatia, J Wang, C Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"The quality of training data impacts the performance of pre-trained large language models (LMs). Given a fixed budget of tokens, we study how to best select data that leads to good downstream model performance across tasks. We develop a new …","url":["https://arxiv.org/pdf/2307.14430"]}
-{"year":"2023","title":"Skill-Mix: a Flexible and Expandable Family of Evaluations for AI models","authors":["D Yu, S Kaur, A Gupta, J Brown-Cohen, A Goyal… - arXiv preprint arXiv …, 2023"],"snippet":"… We identified 17 skills that appeared with rather high frequency in the common crawl corpus. Omitting them from the evaluation appeared to make it much harder for most models (see Section 5.2). This second version is recommended. …","url":["https://arxiv.org/pdf/2310.17567"]}
-{"year":"2023","title":"SKIM at WMT 2023 general translation task","authors":["K Kudo, T Ito, M Morishita, J Suzuki - Proceedings of the Eighth Conference on …, 2023"],"snippet":"… Monolingual Corpus We also used the following provided monolingual data: News Crawl, News Commentary, and Common Crawl. We backtranslated the monolingual sentences using a targetto-source model (ie, an initial translation model) …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.9.pdf"]}
-{"year":"2023","title":"SLDT: Sequential Latent Document Transformer for Multilingual Document-based Dialogue","authors":["Z Ma, Z Liu, J Ye"],"snippet":"… XLM-R is trained with a cross-lingual masked language modeling objective on data in 100 languages from Common Crawl. To improve the pre-training data quality, pages from Common Crawl were filtered by an n-gram language model trained on …","url":["https://openreview.net/pdf?id=CZRH2wjjAt"]}
-{"year":"2023","title":"Slice-and-Forge: Making Better Use of Caches for Graph Convolutional Network Accelerators","authors":["M Yoo, J Song, H Lee, J Lee, N Kim, Y Kim, J Lee - arXiv preprint arXiv:2301.09813, 2023"],"snippet":"Graph convolutional networks (GCNs) are becoming increasingly popular as they can process a wide variety of data formats that prior deep neural networks cannot easily support. One key challenge in designing hardware accelerators for GCNs is …","url":["https://arxiv.org/pdf/2301.09813"]}
-{"year":"2023","title":"SlimPajama-DC: Understanding Data Combinations for LLM Training","authors":["Z Shen, T Tao, L Ma, W Neiswanger, J Hestness… - arXiv preprint arXiv …, 2023"],"snippet":"… We tested different sampling strategies for different domains of our training data: (1) each token is trained only once during training, such as Commoncrawl, and (2) we perform more than one epoch for training on particular sources, such as the …","url":["https://arxiv.org/pdf/2309.10818"]}
-{"year":"2023","title":"Smaller Language Models are Better Black-box Machine-Generated Text Detectors","authors":["F Mireshghallah, J Mattern, S Gao, R Shokri… - arXiv preprint arXiv …, 2023"],"snippet":"… The GPT-2 family is reportedly trained on the WebText dataset, GPT-3 is trained on a combination of the Common Crawl 1, WebText2, books and Wikipedia, and there is not any information released about the training data of ChatGPT. … 1https://commoncrawl.org …","url":["https://arxiv.org/pdf/2305.09859"]}
-{"year":"2023","title":"Smart Home Notifications in Croatian Language: A Transformer-Based Approach","authors":["M Simunec, R Soic - 2023 17th International Conference on …, 2023"],"snippet":"Natural language generation is one of the essential components in achieving spoken interaction between a human user and a computer system. In this paper, we describe the process of generating notifications in Croatian language by employing …","url":["https://ieeexplore.ieee.org/abstract/document/10198978/"]}
-{"year":"2023","title":"Smart Knowledge Submission System Based on Natural Language Processing (NLP) Leveraging on Language Modelling Approach","authors":["MA Idris, H Alsultan - Gas & Oil Technology Showcase and Conference, 2023"],"snippet":"… This led to the development of pre-trained systems such as BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer), which were trained with large language datasets, such as the …","url":["https://onepetro.org/SPEGOTS/proceedings-abstract/23GOTS/3-23GOTS/517915"]}
-{"year":"2023","title":"Smart Subs Subtitling App for Watching Live Virtual Dome Performances","authors":["D Christopoulos, E Chatzi, G Sofianopoulos… - 2023 18th International …, 2023"],"snippet":"… from the Greek Wikipedia, (b) the europarl database which contains textual data from the European Parliament, including eleven different languages, including Greek which we used, (c) the oscar database created by language classification and …","url":["https://ieeexplore.ieee.org/abstract/document/10255166/"]}
-{"year":"2023","title":"Smart Video Retrieval and Question Answering System","authors":["M Dubey, M Dashora, VK Shree, R Jayashree - 2023 International Conference for …, 2023"],"snippet":"More and more video content is being produced on daily basis and utilizing it to its fullest has never been easier. In this paper we propose a new solution for this problem as a smart video retrieval system, leveraging the progress made in …","url":["https://ieeexplore.ieee.org/abstract/document/10080460/"]}
-{"year":"2023","title":"SMS Spam Classification–Simple Deep Learning Models With Higher Accuracy Using BUNOW And GloVe Word Embedding","authors":["S Giri, S Das, SB Das, S Banerjee - Journal of Applied Science and Engineering, 2023"],"snippet":"… tokens; 2014 Wikipedia dump with 1.6 billion tokens; Gigaword5 which has 4.3 billion tokens; the combination Gigaword5 and Wikipedia2014, which has 6 billion tokens; and 42 billion tokens of web data, from Common Crawl. Each corpus was …","url":["http://jase.tku.edu.tw/articles/jase-202310-26-10-0015.pdf"]}
-{"year":"2023","title":"So2al-wa-Gwab: A new Arabic Question-Answering Dataset Trained on Answer Extraction Models","authors":["H Al-Omari, R Duwairi - ACM Transactions on Asian and Low-Resource …"],"snippet":"Question answering (QA) is the task of responding to questions posed by users automatically. A question-answering system is divided into three main components: question analysis, information retrieval, and answer extraction; where this paper has …","url":["https://dl.acm.org/doi/pdf/10.1145/3605550"]}
-{"year":"2023","title":"Socially Aware Natural Language Processing with Commonsense Reasoning and Fairness in Intelligent Systems","authors":["S Saeedi - 2023"],"snippet":"Although Artificial Intelligence (AI) promises to deliver ever more user-friendly consumer applications, recent mishaps involving fake information and biased treatment serve as vivid reminders of the pitfalls of AI. AI can harbor latent biases …","url":["https://search.proquest.com/openview/60a820c6375a2dfacc20921b3e8cead3/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Soft Language Clustering for Multilingual Model Pre-training","authors":["J Zeng, Y Jiang, Y Yin, Y Jing, F Meng, B Lin, Y Cao… - arXiv preprint arXiv …, 2023"],"snippet":"Multilingual pre-trained language models have demonstrated impressive (zero-shot) cross-lingual transfer abilities, however, their performance is hindered when the target language has distant typology from source languages or when pre-training …","url":["https://arxiv.org/pdf/2306.07610"]}
-{"year":"2023","title":"SOTAB: The WDC Schema. org Table Annotation Benchmark","authors":["K Korini, R Peeters, C Bizer - Semantic Web Challenge on Tabular Data to …, 2022"],"snippet":"Understanding the semantics of table elements is a prerequisite for many data integration and data discovery tasks. Table annotation is the task of labeling table elements with terms from a given vocabulary. This paper presents the WDC Schema …","url":["https://ceur-ws.org/Vol-3320/paper1.pdf"]}
-{"year":"2023","title":"SoUnD Framework: Analyzing (So) cial Representation in (Un) structured (D) ata","authors":["M Díaz, S Dev, E Reif, R Denton, V Prabhakaran - arXiv preprint arXiv:2311.17259, 2023"],"snippet":"… We apply the framework in two toy examples using the Common Crawl web text corpus (C4) and LAION-400M. We also propose a set of … LAION-400M is a multimodal text and image dataset that features over 400 million image-text pairs …","url":["https://arxiv.org/pdf/2311.17259"]}
-{"year":"2023","title":"Source Prompt: Coordinated Pre-training of Language Models on Diverse Corpora from Multiple Sources","authors":["Y Xu, D Lu, J Liang, X Wang, Y Geng, Y Xin, H Wu… - arXiv preprint arXiv …, 2023"],"snippet":"… For common crawl based corpora such as C4, their source information is largely unusable because their data is crawled from millions of web pages. Therefore, our current method is limited to the scenario where a certain number of small corpora …","url":["https://arxiv.org/pdf/2311.09732"]}
-{"year":"2023","title":"Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models","authors":["Y Huang, Z Meng, F Liu, Y Su, N Collier, Y Lu - arXiv preprint arXiv:2308.16463, 2023"],"snippet":"Large language models exhibit enhanced zero-shot performance on various tasks when fine-tuned with instruction-following data. Multimodal instruction-following models extend these capabilities by integrating both text and images. However …","url":["https://arxiv.org/pdf/2308.16463"]}
-{"year":"2023","title":"SPARSITY IN LARGE LANGUAGE MODELS","authors":["RS BACK"],"snippet":"… We chose RefinedWeb because it is a high-quality subset of Common Crawl, which is often used in the pretraining phase of LLMs, including Llama, Falcon, and OPT. We also use the validation split of WikiText (Merity et al., 2017) for measuring …","url":["https://openreview.net/pdf?id=osoWxY8q2E"]}
-{"year":"2023","title":"Spatiotemportal and multilingual Semantic Machine Learning Analysis of Social Media Data for the recent protests in Europe–based on Twitter data–","authors":["K Tamás - 2023"],"snippet":"The perception of inherent tensions between justice and injustice (or the disproportion of good and bad) often press a group of people (or even the whole society) to seek change concerning politics and power, for example in the form of …","url":["https://pea.lib.pte.hu/bitstream/handle/pea/34845/KOVACS_disszertacio_final.pdf?sequence=1"]}
-{"year":"2023","title":"Speak While You Think: Streaming Speech Synthesis During Text Generation","authors":["A Dekel, S Shechtman, R Fernandez, D Haws, Z Kons… - arXiv preprint arXiv …, 2023"],"snippet":"… We construct our training dataset based on the C4 (Common Crawl Cleaned Corpus) dataset [20], which was also used to train T5. As C4 contains 365M samples, we consider only a random fraction of the dataset containing 3M training and 130K …","url":["https://arxiv.org/pdf/2309.11210"]}
-{"year":"2023","title":"Specious Sites: Tracking the Spread and Sway of Spurious News Stories at Scale","authors":["HWA Hanley, D Kumar, Z Durumeric - arXiv preprint arXiv:2308.02068, 2023"],"snippet":"… To ensure full coverage of each site’s published articles, we additionally gather the HTML pages indexed by Common Crawl [48] for each site during this same period. We emphasize that under 1% of articles were only found in the Common …","url":["https://arxiv.org/pdf/2308.02068"]}
-{"year":"2023","title":"Spelling convention sensitivity in neural language models","authors":["E Nielsen, C Kirov, B Roark - arXiv preprint arXiv:2303.03457, 2023"],"snippet":"We examine whether large neural language models, trained on very large collections of varied English text, learn the potentially long-distance dependency of British versus American spelling conventions, ie, whether spelling is consistently …","url":["https://arxiv.org/pdf/2303.03457"]}
-{"year":"2023","title":"Spot: A Natural Language Interface for Geospatial Searches in OSM","authors":["L Khellaf, IB Schlicht, J Bayer, R Bouwmeester, T Miraß… - arXiv preprint arXiv …, 2023"],"snippet":"Investigative journalists and fact-checkers have found OpenStreetMap (OSM) to be an invaluable resource for their work due to its extensive coverage and intricate details of various locations, which play a crucial role in investigating news scenes …","url":["https://arxiv.org/pdf/2311.08093"]}
-{"year":"2023","title":"Sprinter: Speeding Up High-Fidelity Crawling of the Modern Web","authors":["A Goel, J Zhu, R Netravali, HV Madhyastha"],"snippet":"Crawling the web at scale forms the basis of many important systems: web search engines, smart assistants, generative AI, web archives, and so on. Yet, the research community has paid little attention to this workload in the last decade. In this paper …","url":["https://goelayu.github.io/files/sprinter-2024.pdf"]}
-{"year":"2023","title":"SRBerta-BERT transformer language model for Serbian legal texts","authors":["M Bogdanovic, J Tošic"],"snippet":"… OSCAR is a large set of open data created using linguistic classification over data from the Common Crawl corpus [3]. The dataset we used consisted of 645,747 texts. The evaluation of the SRBert network was performed using 10of which consists of …","url":["https://imi.pmf.kg.ac.rs/aaa2023/pdf/accepted-finished/d93c7914a7bfff76e6c64d160e9f1281_10_05162023_084339/MilosBogdanovic-Abstract.pdf"]}
-{"year":"2023","title":"SSL-GAN-RoBERTa: A robust semi-supervised model for detecting Anti-Asian COVID-19 hate speech on social media","authors":["X Su, Y Li, P Branco, D Inkpen - Natural Language Engineering, 2023"],"snippet":"Anti-Asian speech during the COVID-19 pandemic has been a serious problem with severe consequences. A hate speech wave swept social media platforms. The timely detection of Anti-Asian COVID-19-related hate speech is of utmost importance …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/D24DDC58F7DEE72216EB04196A4BB440/S1351324923000396a.pdf/div-class-title-ssl-gan-roberta-a-robust-semi-supervised-model-for-detecting-anti-asian-covid-19-hate-speech-on-social-media-div.pdf"]}
-{"year":"2023","title":"Stable Bias: Analyzing Societal Representations in Diffusion Models","authors":["AS Luccioni, C Akiki, M Mitchell, Y Jernite - arXiv preprint arXiv:2303.11408, 2023"],"snippet":"As machine learning-enabled Text-to-Image (TTI) systems are becoming increasingly prevalent and seeing growing adoption as commercial services, characterizing the social biases they exhibit is a necessary first step to lowering their …","url":["https://arxiv.org/pdf/2303.11408"]}
-{"year":"2023","title":"StarCoder: may the source be with you!","authors":["R Li, LB Allal, Y Zi, N Muennighoff, D Kocetkov, C Mou… - arXiv preprint arXiv …, 2023"],"snippet":"The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context …","url":["https://arxiv.org/pdf/2305.06161"]}
-{"year":"2023","title":"stopes-Modular Machine Translation Pipelines","authors":["P Andrews, G Wenzek, K Heffernan, O Çelebi, A Sun… - Proceedings of the The …, 2022"],"snippet":"Neural machine translation, as other natural language deep learning applications, is hungry for data. As research evolves, the data pipelines supporting that research evolve too, oftentimes re-implementing the same core components. Despite the …","url":["https://aclanthology.org/2022.emnlp-demos.26.pdf"]}
-{"year":"2023","title":"Strengthening Small and Medium-Sized Businesses' Cybersecurity: A Machine Learning-based Phishing Classification Model","authors":["SC Song - 2023"],"snippet":"… The study used 5,000 URLs from the PhishTank, OpenPhish, Alexa, and Common Crawl archives. The best model used a Random Forest algorithm and had an … The phishing URLs were extracted from phishtank.org while the legitimate …","url":["https://search.proquest.com/openview/3205e8ac8b6f3c1e6a2a02a6c2110253/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"STRESS TEST FOR BERT AND DEEP MODELS: PREDICTING WORDS FROM ITALIAN POETRY","authors":["R Delmonte, N Busetto"],"snippet":"In this paper we present a set of experiments carried out with BERT on a number of Italian sentences taken from poetry domain. The experiments are organized on the hypothesis of a very high level of difficulty in predictability at the three levels of …","url":["https://www.researchgate.net/profile/Rodolfo-Delmonte/publication/366733361_STRESS_TEST_FOR_BERT_AND_DEEP_MODELS_PREDICTING_WORDS_FROM_ITALIAN_POETRY/links/63b07957c3c99660ebbaf13a/STRESS-TEST-FOR-BERT-AND-DEEP-MODELS-PREDICTING-WORDS-FROM-ITALIAN-POETRY.pdf"]}
-{"year":"2023","title":"string2string: A Modern Python Library for String-to-String Algorithms","authors":["M Suzgun, SM Shieber, D Jurafsky - arXiv preprint arXiv:2304.14395, 2023"],"snippet":"We introduce string2string, an open-source library that offers a comprehensive suite of efficient algorithms for a broad range of string-to-string problems. It includes traditional algorithmic solutions as well as recent advanced neural approaches to …","url":["https://arxiv.org/pdf/2304.14395"]}
-{"year":"2023","title":"Strong Prediction: Language model surprisal explains multiple N400 effects","authors":["JA Michaelov, MD Bardolph, CK Van Petten…"],"snippet":"Theoretical accounts of the N400 are divided as to whether the amplitude of the N400 response to a stimulus reflects the extent to which the stimulus was predicted, the extent to which the stimulus is semantically similar to its preceding context, or …","url":["https://pages.ucsd.edu/~bkbergen/papers/michaelov_et_al_NoL.pdf"]}
-{"year":"2023","title":"Structural Self-Supervised Objectives for Transformers","authors":["L Di Liello - arXiv preprint arXiv:2309.08272, 2023"],"snippet":"This thesis focuses on improving the pre-training of natural language models using unsupervised raw data to make them more efficient and aligned with downstream applications. In the first part, we introduce three alternative pre-training objectives to …","url":["https://arxiv.org/pdf/2309.08272"]}
-{"year":"2023","title":"Students' perceptions of using ChatGPT in a physics class as a virtual tutor","authors":["L Ding, T Li, S Jiang, A Gapud - International Journal of Educational Technology in …, 2023"],"snippet":"The latest development of Generative Artificial Intelligence (GenAI), particularly ChatGPT, has drawn the attention of educational researchers and practitioners. We have witnessed many innovative uses of ChatGPT in STEM classrooms. However …","url":["https://link.springer.com/article/10.1186/s41239-023-00434-1"]}
-{"year":"2023","title":"Study of ChatGPT and its Comparison with Other Mainstream Large Language Models","authors":["C Yuyang"],"snippet":"… T5 was pre-trained on 34B tokens, which filtered the publicly crawled web dataset Common Crawl to remove some duplicates, low-quality, code-looking texts, etc., and finally kept only English texts to obtain dataset C4: the Colossal Clean Crawled …","url":["http://www.ijklp.org/archives/vol13no2/Study%20of%20ChatGPT%20and%20its%20Comparison%20with%20Other%20Mainstream%20Large%20Language%20Models.pdf"]}
-{"year":"2023","title":"Sub-Standards and Mal-Practices: Misinformation's Role in Insular, Polarized, and Toxic Interactions","authors":["HWA HANLEY, Z DURUMERIC"],"snippet":"… pages that were indexed by Common Crawl before August 2021. For each HTML page indexed by Common Crawl, we parse the HTML … Altogether we gather the available Common Crawl pages and scrape the HTML for 541 misinformation and …","url":["https://www.hanshanley.com/files/Sub_Standards_and_Mal_Practices.pdf"]}
-{"year":"2023","title":"Subject-verb Agreement with Seq2Seq Transformers: Bigger Is Better, but Still Not Best","authors":["MA Wilson, Z Zhou, R Frank - Proceedings of the Society for Computation in …, 2023"],"snippet":"Past work (Linzen et al., 2016; Goldberg, 2019, ao) has used the performance of neural network language models on subject-verb agreement to argue that such models possess structure-sensitive grammatical knowledge. We investigate what …","url":["https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1303&context=scil"]}
-{"year":"2023","title":"Submission of USTC's system for the IWSLT 2023-Offline Speech Translation Track","authors":["X Zhou, J Cui, Z Ye, Y Wang, L Xu, H Zhang, W Zhang… - Proceedings of the 20th …, 2023"],"snippet":"This paper describes the submissions of the research group USTC-NELSLIP to the 2023 IWSLT Offline Speech Translation competition, which involves translating spoken English into written Chinese. We utilize both cascaded models and end-to-end …","url":["https://aclanthology.org/2023.iwslt-1.15.pdf"]}
-{"year":"2023","title":"Subversion of the Human Aura: A Crisis in Representation","authors":["NK Hayles - American Literature, 2023"],"snippet":"The human aura is now being subverted by a variety of simulacra. OpenAI’s language-generation program GPT-3 illustrates the challenges of interpreting algorithmic-generated texts. This article advocates interpretive strategies that …","url":["https://read.dukeupress.edu/american-literature/article-abstract/doi/10.1215/00029831-10575063/344236"]}
-{"year":"2023","title":"Subword-Based Neural Machine Translation for Low-Resource Fusion Languages","authors":["A Nürnberger, EW De Luca, M Gasser","AM Gezmu - 2023"],"snippet":"Neural approaches, which are currently state-of-the-art in many areas, have contributed significantly to the exciting advancements in machine translation. However, Neural Machine Translation (NMT) requires a substantial quantity and …","url":["https://opendata.uni-halle.de/bitstream/1981185920/105783/1/Gezmu_Andargachew_Mekonnen_Dissertation_2023.pdf","https://repo.bibliothek.uni-halle.de/bitstream/1981185920/105783/1/Gezmu_Andargachew_Mekonnen_Dissertation_2023.pdf"]}
-{"year":"2023","title":"Suicidal Text Detection in Social Media","authors":["MP Karthikeyan, I Ajay, R Magesh, G Saran - 2023"],"snippet":"This system is developed with the aim of providing and insight information of people who are personally disturbed by the factors of either their personal life or family background or bully at school or work pressure. With the help of people’s online …","url":["https://www.ijrar.org/papers/IJRAR23B1004.pdf"]}
-{"year":"2023","title":"Suicide risk assessment using word-level model with dictionary-based risky posts selection","authors":["YS Tsai, ALP Chen - Multimedia Tools and Applications, 2023"],"snippet":"Suicide is a serious issue around the world and is a leading cause of death in US. In the past 20 years, the suicide rate has seen a significant increase of 35%. With the rapid development of information technology, more and more people begin to use …","url":["https://link.springer.com/article/10.1007/s11042-023-16361-2"]}
-{"year":"2023","title":"SuperDialseg: A Large-scale Dataset for Supervised Dialogue Segmentation","authors":["J Jiang, C Dong, A Aizawa, S Kurohashi - arXiv preprint arXiv:2305.08371, 2023"],"snippet":"… For TextTiling+Glove, we used the version pretrained with 42 billion tokens of web data from Common Crawl.For GreedySeg and CSM, we corrected some inconsistencies in their open-sourced codes with respect to their original published …","url":["https://arxiv.org/pdf/2305.08371"]}
-{"year":"2023","title":"Superlim: A Swedish Language Understanding Evaluation Benchmark","authors":["A Berdičevskis, G Bouma, R Kurtz, F Morger, J Öhman… - Proceedings of the 2023 …, 2023"],"snippet":"We present Superlim, a multi-task NLP benchmark and analysis platform for evaluating Swedish language models, a counterpart to the English-language (Super) GLUE suite. We describe the dataset, the tasks, the leaderboard and report the …","url":["https://aclanthology.org/2023.emnlp-main.506.pdf"]}
-{"year":"2023","title":"Supervised Feature Selection to Improve the Accuracy for Malware Detection","authors":["D Smith, S Khorsandroo, K Roy - 2023"],"snippet":"Malware is becoming increasingly sophisticated and difficult to detect with traditional monitoring tools and antivirus software. As a result, machine learning has become a popular approach for classifying and detecting malware-related data. In this study …","url":["https://www.researchsquare.com/article/rs-2898970/latest.pdf"]}
-{"year":"2023","title":"Supervised Feature-based Classification Approach to Bilingual Lexicon Induction from Specialised Comparable Corpora","authors":["AR Terryn"],"snippet":"This study, submitted to the BUCC2023 shared task on bilingual term alignment in comparable specialised corpora, introduces a supervised, feature-based classification approach. The approach employs both static cross-lingual …","url":["https://www.researchgate.net/profile/Ayla_Rigouts_Terryn2/publication/373823779_Supervised_Feature-based_Classification_Approach_to_Bilingual_Lexicon_Induction_from_Specialised_Comparable_Corpora/links/64febb3c68ca5847e3cdcbd2/Supervised-Feature-based-Classification-Approach-to-Bilingual-Lexicon-Induction-from-Specialised-Comparable-Corpora.pdf"]}
-{"year":"2023","title":"Supervised Knowledge Makes Large Language Models Better In-context Learners","authors":["L Yang, S Zhang, Z Yu, G Bao, Y Wang, J Wang, R Xu… - arXiv preprint arXiv …, 2023"],"snippet":"Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the …","url":["https://arxiv.org/pdf/2312.15918"]}
-{"year":"2023","title":"Supervised Machine Generated Text Detection Using LLM Encoders In Various Data Resource Scenarios","authors":["M Capobianco"],"snippet":"With the recent innovation in Large Language Models, the world has been taken by storm by the vast implications and applications of including these effective new creations into our everyday lives. However, as with most things, these new …","url":["https://digital.wpi.edu/downloads/hh63t0231"]}
-{"year":"2023","title":"Support of Sparse Tensor Computing for MLIR HLS","authors":["GM Liang, CL Lee, R Lai, JK Lee - Proceedings of the 52nd International Conference …, 2023"],"snippet":"Nowadays, sparse tensor computations are widely used in machine learning. Without the multiplications in zero values, sparse tensor computation can significantly reduce the latency and power consumption. Famous frameworks like …","url":["https://dl.acm.org/doi/abs/10.1145/3605731.3605908"]}
-{"year":"2023","title":"Supporting Account-Based Queries for Archived Instagram Posts","authors":["HR Jayanetti - 2023"],"snippet":"Social media has become one of the primary modes of communication in recent times, with popular platforms such as Facebook, Twitter, and Instagram leading the way. Despite its popularity, Instagram has not received as much attention in …","url":["https://search.proquest.com/openview/69156b126b64d5b62da188c26e82268f/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Surface-Based Retrieval Reduces Perplexity of Retrieval-Augmented Language Models","authors":["E Doostmohammadi, T Norlund, M Kuhlmann… - arXiv preprint arXiv …, 2023"],"snippet":"Augmenting language models with a retrieval mechanism has been shown to significantly improve their performance while keeping the number of parameters low. Retrieval-augmented models commonly rely on a semantic retrieval mechanism …","url":["https://arxiv.org/pdf/2305.16243"]}
-{"year":"2023","title":"Surgicberta: a pre-trained language model for procedural surgical language","authors":["M Bombieri, M Rospocher, SP Ponzetto, P Fiorini - International Journal of Data …, 2023"],"snippet":"… of the CommonCrawl News, from OpenWebText, and some stories from CommonCrawl data. RoBERTa has been trained via MLM with dynamic masking: ie, each time a sequence is input to the model, a new masking pattern is created …","url":["https://link.springer.com/article/10.1007/s41060-023-00433-5"]}
-{"year":"2023","title":"SurreyAI 2023 Submission for the Quality Estimation Shared Task","authors":["A Sindhujan, D Kanojia, C Orasan, T Ranasinghe - Proceedings of the Eigth …, 2023"],"snippet":"Quality Estimation (QE) systems are important in situations where it is necessary to assess the quality of translations, but there is no reference available. This paper describes the approach adopted by the SurreyAI team for addressing the Sentence-Level …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.74.pdf"]}
-{"year":"2023","title":"Survey On Machine Learning Paradigms For Phishing Website Detection","authors":["M Baduwal, P Madai, T Alam, Q Yuan"],"snippet":"Phishing attacks continue to be a major security threat for individuals and organizations alike. It causes billions of dollars in losses annually. Machine learning (ML) has shown great promise in detecting such attacks by identifying patterns and …","url":["https://www.researchgate.net/profile/Madan-Baduwal-2/publication/370658818_Survey_On_Machine_Learning_Paradigms_For_Phishing_Website_Detection/links/645c91fcf43b8a29ba42daba/Survey-On-Machine-Learning-Paradigms-For-Phishing-Website-Detection.pdf"]}
-{"year":"2023","title":"Survey Paper: Automatic Title Generation for Text with RNN and Pre-trained Transformer Language Model","authors":["V Lodhwal, G Choudhary"],"snippet":"Nowadays huge amounts of text data are available due to the evolution of the Internet. Although search engines are used to select text data, it is unfeasible to go through the entire search results of text that are related to search intent. Therefore …","url":["https://www.researchgate.net/profile/Vishal-Lodhwal-2/publication/369741619_Survey_Paper_Automatic_Title_Generation_for_Text_with_RNN_and_Pre-trained_Transformer_Language_Model/links/642fd66e20f25554da158ea3/Survey-Paper-Automatic-Title-Generation-for-Text-with-RNN-and-Pre-trained-Transformer-Language-Model.pdf"]}
-{"year":"2023","title":"Syntactic-Semantic Similarity Based on Dependency Tree Kernel","authors":["M Alian, A Awajan - Arabian Journal for Science and Engineering, 2023"],"snippet":"The representation of words in the vector space generated using the Word2Vec model does not capture the syntactic similarity between sentences, but only the semantic similarity by considering the context of words. To address this problem, we …","url":["https://link.springer.com/article/10.1007/s13369-023-07694-z"]}
-{"year":"2023","title":"Synthetic Cross-language Information Retrieval Training Data","authors":["J Mayfield, E Yang, D Lawrie, S Barham, O Weller… - arXiv preprint arXiv …, 2023"],"snippet":"… Documents in NeuCLIR 1 are news articles extracted from Common Crawl News. The HC3 dataset consists of Chinese and Persian Tweet reply … criterion used for the NeuCLIR 1 was dropped since Twitter conversations are less coherent than …","url":["https://arxiv.org/pdf/2305.00331"]}
-{"year":"2023","title":"System for Enhancing Accuracy of Noisy Text using Deep Network Language Models","authors":["R Rohit, SA Gandheesh, KS Suriya, PB Pati - 2023 IEEE 8th International Conference …, 2023"],"snippet":"… C4 dataset is a collection of English language text sourced from an open-source Common Crawl web scrape. Each record consists of an input erroneous test along with its target text. While the dataset contains many millions of sentences, for this …","url":["https://ieeexplore.ieee.org/abstract/document/10126194/"]}
-{"year":"2023","title":"Systematic Rectification of Language Models via Dead-end Analysis","authors":["M Cao, M Fatemi, JCK Cheung, S Shabanian - arXiv preprint arXiv:2302.14003, 2023"],"snippet":"With adversarial or otherwise normal prompts, existing large language models (LLM) can be pushed to generate toxic discourses. One way to reduce the risk of LLMs generating undesired discourses is to alter the training of the LLM. This can be very …","url":["https://arxiv.org/pdf/2302.14003"]}
-{"year":"2023","title":"Systems and Algorithms for Dynamic Graph Processing","authors":["K Ammar - 2023"],"snippet":"Data generated from human and systems interactions could be naturally represented as graph data. Several emerging applications rely on graph data, such as the semantic web, social networks, bioinformatics, finance, and trading among …","url":["https://uwspace.uwaterloo.ca/bitstream/handle/10012/19195/Ammar_Khaled.pdf?sequence=3&isAllowed=y"]}
-{"year":"2023","title":"Systems and Resources for Telugu: Question Answering and Summarization","authors":["P Ravva - 2023"],"snippet":"Natural language processing (NLP) is a bridge between the computer and human interactions in their natural language. NLP has wide variety of applications such as machine translation, text summarization, question-answering, sentiment analysis, etc …","url":["https://web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.b93b1f715416394f.46696e616c5468657369735375626d697373696f6e5f50726979616e6b61202831292e706466.pdf"]}
-{"year":"2023","title":"T-MARS: Improving Visual Representations by Circumventing Text Feature Learning","authors":["P Maini, S Goyal, ZC Lipton, JZ Kolter, A Raghunathan - arXiv preprint arXiv …, 2023"],"snippet":"… 46] datasets, there has been a growing interest in exploring improved strategies for selecting subsets of the common crawl that help learn better … Most recently, DataComp [14] was introduced as a benchmark challenge for subset selection from …","url":["https://arxiv.org/pdf/2307.03132"]}
-{"year":"2023","title":"T3L: Translate-and-Test Transfer Learning for Cross-Lingual Text Classification","authors":["IJ Unanue, G Haffari, M Piccardi - arXiv preprint arXiv:2306.04996, 2023"],"snippet":"… 2021), all typically using hundreds of gigabytes or terabytes of pretraining data (eg, 2.5 TB of Common Crawl data for XLM-R). However, such large, pretrained multilingual models still suffer from significant performance limitations, particularly in …","url":["https://arxiv.org/pdf/2306.04996"]}
-{"year":"2023","title":"T5G2P: Multilingual Grapheme-to-Phoneme Conversion with Text-to-Text Transfer Transformer","authors":["M Řezáčková, A Frémund, J Švec, J Matoušek - Asian Conference on Pattern …, 2023"],"snippet":"… The original Google’s T5-base English model Footnote 4 (labeled as t5-EN in our paper) was trained from Common Crawl data Footnote 5 . We replicated the same pre-processing procedure to obtain the data for other languages tested in the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-47665-5_27"]}
-{"year":"2023","title":"TabLib: A Dataset of 627M Tables with Context","authors":["G Eggert, K Huo, M Biven, J Waugh - arXiv preprint arXiv:2310.07875, 2023"],"snippet":"… An important caveat is that there may be a selection bias affecting this analysis, due to factors such as our exclusion of tables larger than 1 GB, Common Crawl’s truncation of large responses, parsing bugs and limitations, etc. We leave a more …","url":["https://arxiv.org/pdf/2310.07875"]}
-{"year":"2023","title":"Tackling Fake News in Bengali: Unraveling the Impact of Summarization vs. Augmentation on Pre-trained Language Models","authors":["AS Chowdhury, GM Shahariar, AT Aziz, SM Alam… - arXiv preprint arXiv …, 2023"],"snippet":"With the rise of social media and online news sources, fake news has become a significant issue globally. However, the detection of fake news in low resource languages like Bengali has received limited attention in research. In this paper, we …","url":["https://arxiv.org/pdf/2307.06979"]}
-{"year":"2023","title":"Tackling Hallucinations in Chart Summarization","authors":["S Obaid ul Islam - 2023"],"snippet":"… Pre-training models on large corpora like Common Crawl results in models learning language in its parameters. This is called parametric knowledge which helps improve the performance when the model is finetuned on a downstream task …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/179356/120437011.pdf?sequence=1"]}
-{"year":"2023","title":"Tackling the multilingual and heterogeneous documents with the pre-trained language identifiers","authors":["MR Kanfoud, A Bouramoul - International Journal of Computers and Applications, 2023"],"snippet":"… The authors collected data from a non-profit foundation, Common Crawl, which explores the Web and provides data freely to the public. The collected datasets are heterogeneous and multilingual. The authors proposed a multithreaded pipelined …","url":["https://www.tandfonline.com/doi/abs/10.1080/1206212X.2023.2218236"]}
-{"year":"2023","title":"TaCo: Enhancing Cross-Lingual Transfer for Low-Resource Languages in LLMs through Translation-Assisted Chain-of-Thought Processes","authors":["B Upadhayay, V Behzadan - arXiv preprint arXiv:2311.10797, 2023"],"snippet":"… Authors trained XLM-R model by increasing the training examples and training the cross-lingual presentations from more than 2 terabytes of Common Crawl data. Chi et al. [28] further improved these models using two discriminative pretraining …","url":["https://arxiv.org/pdf/2311.10797"]}
-{"year":"2023","title":"TaCo: Targeted Concept Removal in Output Embeddings for NLP via Information Theory and Explainability","authors":["F Jourdan, L Béthune, A Picard, L Risser, N Asher - arXiv preprint arXiv:2312.06499, 2023"],"snippet":"… 2018) a dataset containing a subset of CommonCrawl data filtered to match the story-like style of Winograd schemas. Pre-training was performed on these data by randomly masking 15% of the words in each of the input sentences and then trying …","url":["https://arxiv.org/pdf/2312.06499"]}
-{"year":"2023","title":"Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model","authors":["YT Lin, YN Chen - arXiv preprint arXiv:2311.17487, 2023"],"snippet":"… When we added approximately 9 billion tokens of CommonCrawl data, specifically filtered for Traditional Chinese content (zh-tw), the performance of TAIWAN-LLM unexpectedly declined. For the 13 billion parameter model, the Exact …","url":["https://arxiv.org/pdf/2311.17487"]}
-{"year":"2023","title":"Take a Closer Look at Multilinguality! Improve Multilingual Pre-Training Using Monolingual Corpora Only","authors":["J Lu, Y Lu, J Zhang - Findings of the Association for Computational …, 2023"],"snippet":"… Pre-training Data We collect monolingual corpora from Common Crawl Corpus, which contains about 890GB data for 50 languages. Different from previous studies, we do not use any bilingual corpus. Following (Conneau and Lample…","url":["https://aclanthology.org/2023.findings-emnlp.190.pdf"]}
-{"year":"2023","title":"Taken out of context: On measuring situational awareness in LLMs","authors":["L Berglund, AC Stickland, M Balesni, M Kaufmann… - arXiv preprint arXiv …, 2023"],"snippet":"We aim to better understand the emergence of `situational awareness' in large language models (LLMs). A model is situationally aware if it's aware that it's a model and can recognize whether it's currently in testing or deployment. Today's LLMs are …","url":["https://arxiv.org/pdf/2309.00667"]}
-{"year":"2023","title":"Targeted and Troublesome: Tracking and Advertising on Children's Websites","authors":["Z Moti, A Senol, H Bostani, FZ Borgesius, V Moonsamy… - arXiv preprint arXiv …, 2023"],"snippet":"… Applying this classifier to over two million pages from the Common Crawl dataset, we compile a list of two thousand child-directed websites. Crawling these sites from five vantage points, we measure the prevalence of trackers, fingerprinting scripts …","url":["https://arxiv.org/pdf/2308.04887"]}
-{"year":"2023","title":"Targeted Data Augmentation Improves Context-aware Neural Machine Translation","authors":["H Gete, T Etchegoyhen, G Labaka - Proceedings of Machine Translation Summit XIX …, 2023"],"snippet":"Progress in document-level Machine Translation is hindered by the lack of parallel training data that include context information. In this work, we evaluate the potential of data augmentation techniques to circumvent these limitations, showing that …","url":["https://aclanthology.org/2023.mtsummit-research.25.pdf"]}
-{"year":"2023","title":"TASTA: Text‐Assisted Spatial and Temporal Attention Network for Video Question Answering","authors":["T Wang, B Hou, J Li, P Shi, B Zhang, H Snoussi - Advanced Intelligent Systems, 2022"],"snippet":"… GLoVe[34] is pretrained on the Common Crawl dataset and it maps each word (eg, the ith word) into a 300D feature vector (eg, ti ∈ ℝ300). Considering that the length of the video and the image size are not fixed, the video is preprocessed to a uniform …","url":["https://onlinelibrary.wiley.com/doi/pdf/10.1002/aisy.202200131"]}
-{"year":"2023","title":"Taxi1500: A Multilingual Dataset for Text Classification in 1500 Languages","authors":["C Ma, A ImaniGooghari, H Ye, E Asgari, H Schütze - arXiv preprint arXiv:2305.08487, 2023"],"snippet":"… massive data from Common Crawl in 104 languages, significantly boosting the performance and outperforming mBERT. Compared with XLM, XLM-R has a larger vocabulary size of 250K. Besides, the training data scales from Wikipedia to a larger …","url":["https://arxiv.org/pdf/2305.08487"]}
-{"year":"2023","title":"Teach LLMs to Personalize--An Approach inspired by Writing Education","authors":["C Li, M Zhang, Q Mei, Y Wang, SA Hombaiah, Y Liang… - arXiv preprint arXiv …, 2023"],"snippet":"Personalized text generation is an emerging research area that has attracted much attention in recent years. Most studies in this direction focus on a particular domain by designing bespoke features or models. In this work, we propose a general …","url":["https://arxiv.org/pdf/2308.07968"]}
-{"year":"2023","title":"TeamAmpa at SemEval-2023 Task 3: Exploring Multilabel and Multilingual RoBERTa Models for Persuasion and Framing Detection","authors":["A Pauli, R Sarabia, L Derczynski, I Assent - Proceedings of the The 17th International …, 2023"],"snippet":"This paper describes our submission to theSemEval 2023 Task 3 on two subtasks: detectingpersuasion techniques and framing. Bothsubtasks are multi-label classification problems. We present a set of experiments, exploring howto get robust …","url":["https://aclanthology.org/2023.semeval-1.117.pdf"]}
-{"year":"2023","title":"Tech tapas-one byte at a time more about AI, machine learning and ChatGPT","authors":["F MacDowall - Australian Law Librarian, 2023"],"snippet":"… The Common Crawl corpus13 contains petabytes of data collected over 12 years of web … While it can be argued that the Common Crawl corpus is an accurate portrayal of the discourse of … Notably, the Common Crawl overrepresents those …","url":["https://search.informit.org/doi/pdf/10.3316/agispt.20230621090484"]}
-{"year":"2023","title":"Tensor Programs VI: Feature Learning in Infinite-Depth Neural Networks","authors":["G Yang, D Yu, C Zhu, S Hayou"],"snippet":"… , which we illustrate both theoretically and empirically on simple networks as well as Megatron transformer trained on Common Crawl. … We demonstrate this pedagogically on resnet with MLP blocks but also on Megatron transformer trained …","url":["https://arxiv.org/pdf/2310.02244"]}
-{"year":"2023","title":"Testing the Depth of ChatGPT's Comprehension via Cross-Modal Tasks Based on ASCII-Art: GPT3. 5's Abilities in Regard to Recognizing and Generating ASCII-Art …","authors":["D Bayani - arXiv preprint arXiv:2307.16806, 2023"],"snippet":"… Thus, this is a form of ASCII-art for which GPT3.5 may have a substantial amount of varied training data as compiled in the common-crawl dataset11 and potentially other locations. Additionally, owing to its use in technical areas often as an aid to …","url":["https://arxiv.org/pdf/2307.16806"]}
-{"year":"2023","title":"Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks","authors":["S Sarkar, L Lausen - arXiv preprint arXiv:2310.00789, 2023"],"snippet":"… . 2015) is a collection of about 125 million data tables extracted from the Common Crawl. 3. TAPEX: w use the dataset used in training the … The tables were extracted from the Common Crawl although the timeline of the pages of the common crawl …","url":["https://arxiv.org/pdf/2310.00789"]}
-{"year":"2023","title":"TEXILA INTERNATIONAL JOURNAL OF ACADEMIC RESEARCH","authors":["NM Ndongala"],"snippet":"RAT-SQL is among the popular framework used in the Text-To-SQL challenges for jointly encoding the database relations and questions in a way to improve the semantic parser. In this work, we propose a light version of the RAT-SQL where we …","url":["https://www.texilajournal.com/academic-research/edition/161-volume10-issue2"]}
-{"year":"2023","title":"Text Analytics Solutions for the Control of Fake News: Materials and Methods","authors":["E Ogbuju, T Abiodun, F Oladipo - International Journal of Open Information …, 2023"],"snippet":"The increase in the rate of internet and social media use has given rise to a lot of fake news and misinformation available online. The internet and social media have made information and communications flow to be faster and easier. On the other …","url":["http://injoit.org/index.php/j1/article/viewFile/1475/1408"]}
-{"year":"2023","title":"Text augmentation for semantic frame induction and parsing","authors":["S Anwar, A Shelmanov, N Arefyev, A Panchenko… - Language Resources and …, 2023"],"snippet":"Semantic frames are formal structures describing situations, actions or events, eg, Commerce buy, Kidnapping, or Exchange. Each frame provides a set of frame elements or semantic roles corresponding to participants of the situation and lexical …","url":["https://link.springer.com/article/10.1007/s10579-023-09679-8"]}
-{"year":"2023","title":"Text Content Moderation Model to Detect Sexually Explicit Content","authors":["SAN Murthy"],"snippet":"Our objective is to build a Transformer based classification model for the recognition of Sexually Explicit Speech and do a comparative analysis with other (fine-tuned) models in the Sexually Explicit domain. Our approach was to take an open-source …","url":["http://cs230.stanford.edu/projects_spring_2022/reports/127569181.pdf"]}
-{"year":"2023","title":"Text Intimacy Analysis using Ensembles of Multilingual Transformers","authors":["T Chavan, V Patwardhan - arXiv preprint arXiv:2312.02590, 2023"],"snippet":"Intimacy estimation of a given text has recently gained importance due to the increase in direct interaction of NLP systems with humans. Intimacy is an important aspect of natural language and has a substantial impact on our everyday …","url":["https://arxiv.org/pdf/2312.02590"]}
-{"year":"2023","title":"Text mining of scientific literature and the need for open access","authors":["M Vishwanath - 2023"],"snippet":"… We need a scientific analogue to Common-Crawl, an open repository of scientific articles for use in exploratory data analysis. Ironically, this argument is not new, and indeed, was anticipated as part of the original definition of open access given at the …","url":["https://osf.io/mf4pt/download"]}
-{"year":"2023","title":"Text Summarization for Resource-Poor Languages: Datasets and Models for Multiple Indian Languages","authors":["VL Sireesha - 2023"],"snippet":"… model pre-trained on Common Crawl [7] data in 100 languages. XLM-R is created by training a Transformer-based masked language model on a hundred languages. • mT5: mT5 [77] is a multilingual variant of T5 model pre-trained on …","url":["https://cdn.iiit.ac.in/cdn/web2py.iiit.ac.in/research_centres/publications/download/mastersthesis.pdf.957680cd46d4bccb.73697265657368612d7468657369732d7072657072696e74202831292e706466.pdf"]}
-{"year":"2023","title":"Text Summarization of Medical Documents using Abstractive Techniques","authors":["E Lalitha, K Ramani, D Shahida, EVS Deepak… - 2023 2nd International …, 2023"],"snippet":"Medical researchers are exposed to enormous amounts of medical information in the form of medical news, clinical trial reports, research articles, etc. Researchers would need the documents' summaries that help them decide to do an in-depth study …","url":["https://ieeexplore.ieee.org/abstract/document/10140885/"]}
-{"year":"2023","title":"Text, Speech, and Dialogue: 26th International Conference, TSD 2023, Pilsen, Czech Republic, September 4–6, 2023, Proceedings","authors":["K Ekštein"],"snippet":"The annual International Conference on Text, Speech and Dialogue (TSD), which emerged in 1998, constitutes a recognized platform for presenting and discussing stateof-the-art technology and recent achievements in the computer processing of …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=enjSEAAAQBAJ&oi=fnd&pg=PP7&dq=commoncrawl&ots=eW1UKfh2RN&sig=PrJzRFJpibqDn4L9UvBekfOn5Qg"]}
-{"year":"2023","title":"Text-based Patent-Quality Prediction Using Multi-Section Attention","authors":["X Krant - 2023"],"snippet":"The number of patents has increased tremendously in recent years and statistics derived from patents have become the standard measurement for innovation. Patents statistics are widely available and correlate well with patent valuation and …","url":["https://fse.studenttheses.ub.rug.nl/29717/1/Scriptie_X_Krant_s2955156_final.pdf"]}
-{"year":"2023","title":"Text-Blueprint: An Interactive Platform for Plan-based Conditional Generation","authors":["F Huot, J Maynez, S Narayan, RK Amplayo, K Ganchev… - Proceedings of the 17th …, 2023"],"snippet":"… -sourced answer spans from Wikipedia, and matched with passages from web documents from Common Crawl. AQuaMuse uses the answer passages as summaries with the passages extracted from Common Crawl as the input documents …","url":["https://aclanthology.org/2023.eacl-demo.13.pdf"]}
-{"year":"2023","title":"Text-CRS: A Generalized Certified Robustness Framework against Textual Adversarial Attacks","authors":["X Zhang, H Hong, Y Hong, P Huang, B Wang, Z Ba… - arXiv preprint arXiv …, 2023"],"snippet":"The language models, especially the basic text classification models, have been shown to be susceptible to textual adversarial attacks such as synonym substitution and word insertion attacks. To defend against such attacks, a growing body of …","url":["https://arxiv.org/pdf/2307.16630"]}
-{"year":"2023","title":"Text-Guided Image Generation for Railway Intrusion Anomaly Detection","authors":["J Chen, C Zhang, X Feng, Y Liu - 2023 IEEE International Conference on Unmanned …, 2023"],"snippet":"Railway intrusion are characterized by strong suddenness, high unpredictability and many disturbing factors, which are key factors affecting railway safety. Currently, the deep neural network-based intrusion object detection algorithm relies on the …","url":["https://ieeexplore.ieee.org/abstract/document/10318477/"]}
-{"year":"2023","title":"Text-guided Image-and-Shape Editing and Generation: A Short Survey","authors":["CKT Chao, Y Gingold - arXiv preprint arXiv:2304.09244, 2023"],"snippet":"… CLIP is trained on 400 million text-image pairs from common-crawl dataset with contrastive objectives to learn image representations from text. The overall framework can be seen in Figure 1. To be more specific, the image encoder is …","url":["https://arxiv.org/pdf/2304.09244"]}
-{"year":"2023","title":"That was the last straw, we need more: Are Translation Systems Sensitive to Disambiguating Context?","authors":["J Lee, A Liu, O Ahia, H Gonen, NA Smith - arXiv preprint arXiv:2310.14610, 2023"],"snippet":"… Moreover, we observe that the differences between LMs and MT-specific models become less pronounced for more under-resourced languages (the languages are ordered left to right based on count of pages in Common Crawl9). 9https://commoncrawl.github.io …","url":["https://arxiv.org/pdf/2310.14610"]}
-{"year":"2023","title":"The (Undesired) Attenuation of Human Biases by Multilinguality","authors":["C España-Bonet, A Barrón-Cedeño - Proceedings of the 2022 Conference on …, 2022"],"snippet":"… CCWP: Models trained on Common Crawl and Wikipedia using CBOW with position weights and subword information (Grave et al.… We also build 5 static in-house word embeddings on Common Crawl using a subset of the CC-100 corpus (Conneau et al.…","url":["https://aclanthology.org/2022.emnlp-main.133.pdf"]}
-{"year":"2023","title":"The Algorithmic Internet: Culture, capture, corruption","authors":["C Lu"],"snippet":"The internet is haunted by ailing social media platforms with declining engagement and perpetual feeds of quick dopamine hits; large machine learning models are contaminated with an insurmountable sea of toxicity and cul-de-sacs of gibberish …","url":["https://www.paradigmtrilogy.com/assets/documents/issue-02/christina-lu--the-algorithmic-internet.pdf"]}
-{"year":"2023","title":"The Axiom of Choice and Its Influence on LLM Hallucinations: An Exploration","authors":["R Kaushik - 2023"],"snippet":"The Axiom of Choice (AoC), a foundational proposition in set theory, allows for the selection of elements from a collection of non-empty sets without specifying the selection method. Surprisingly, this mathematical principle offers insights into the …","url":["https://www.researchgate.net/profile/Rahul-Kaushik-15/publication/375074101_The_Axiom_of_Choice_and_Its_Influence_on_LLM_Hallucinations_An_Exploration/links/653f7d38ff8d8f507cd86e37/The-Axiom-of-Choice-and-Its-Influence-on-LLM-Hallucinations-An-Exploration.pdf"]}
-{"year":"2023","title":"The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants","authors":["L Bandarkar, D Liang, B Muller, M Artetxe, SN Shukla… - arXiv preprint arXiv …, 2023"],"snippet":"We present Belebele, a multiple-choice machine reading comprehension (MRC) dataset spanning 122 language variants. Significantly expanding the language coverage of natural language understanding (NLU) benchmarks, this dataset …","url":["https://arxiv.org/pdf/2308.16884"]}
-{"year":"2023","title":"The BETTER Cross-Language Datasets","authors":["I Soboroff - Proceedings of the 46th International ACM SIGIR …, 2023"],"snippet":"… The document collections are taken from CommonCrawl.The phase 1 documents were collected by MITRE, and for phases 2 and 3 by ARLIS. Care was taken to identify subsets of the CommonCrawl collection that were likely to contain topical …","url":["https://dl.acm.org/doi/abs/10.1145/3539618.3591910"]}
-{"year":"2023","title":"The BETTER Cross-Language Information Retrieval Datasets","authors":["I Soboroff - 2023"],"snippet":"… The document collections are taken from CommonCrawl.The phase 1 documents were collected by MITRE, and for phases 2 and 3 by ARLIS. Care was taken to identify subsets of the CommonCrawl collection that were likely to contain topical …","url":["https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=936449"]}
-{"year":"2023","title":"The Claire French Dialogue Dataset","authors":["J Hunter, J Louradour, V Rennard, I Harrando… - arXiv preprint arXiv …, 2023"],"snippet":"We present the Claire French Dialogue Dataset (CFDD), a resource created by members of LINAGORA Labs in the context of the OpenLLM France initiative. CFDD is a corpus containing roughly 160 million words from transcripts and stage plays in …","url":["https://arxiv.org/pdf/2311.16840"]}
-{"year":"2023","title":"The Cultivated Practices of Text-to-Image Generation","authors":["J Oppenlaender - arXiv preprint arXiv:2306.11393, 2023"],"snippet":"Humankind is entering a novel creative era in which anybody can synthesize digital information using generative artificial intelligence (AI). Text-to-image generation, in particular, has become vastly popular and millions of practitioners produce AI-generated …","url":["https://arxiv.org/pdf/2306.11393"]}
-{"year":"2023","title":"The Cultural Devaluation of Feminized Work: The Evolution of Occupational Prestige and Gender Typing in the United States, 1900-2019","authors":["W Jiang - 2023"],"snippet":"… to head and visual modality from the Common Crawl embedding are positively associated with an occupation’s survey-based prestige. … Index (ISEI) and prestige measures from the embeddings of the Common Crawl (CC) corpus. Table 1 …","url":["https://osf.io/preprints/socarxiv/8q3ca/download"]}
-{"year":"2023","title":"The Diagnostic and Triage Accuracy of the GPT-3 Artificial Intelligence Model","authors":["DM Levine, R Tuwani, B Kompa, A Varma… - medRxiv, 2023"],"snippet":"Importance: Artificial intelligence (AI) applications in health care have been effective in many areas of medicine, but they are often trained for a single task using labeled data, making deployment and generalizability challenging. Whether a general-purpose …","url":["https://www.medrxiv.org/content/10.1101/2023.01.30.23285067.full.pdf"]}
-{"year":"2023","title":"The Dimensions of Data Labor: A Road Map for Researchers, Activists, and Policymakers to Empower Data Producers","authors":["H Li, N Vincent, S Chancellor, B Hecht - arXiv preprint arXiv:2305.13238, 2023"],"snippet":"Many recent technological advances (eg ChatGPT and search engines) are possible only because of massive amounts of user-generated data produced through user interactions with computing systems or scraped from the web (eg …","url":["https://arxiv.org/pdf/2305.13238"]}
-{"year":"2023","title":"The Effect of Scaling, Retrieval Augmentation and Form on the Factual Consistency of Language Models","authors":["L Hagström, D Saynova, T Norlund, M Johansson… - arXiv preprint arXiv …, 2023"],"snippet":"Large Language Models (LLMs) make natural interfaces to factual knowledge, but their usefulness is limited by their tendency to deliver inconsistent answers to semantically equivalent questions. For example, a model might predict both \"Anne …","url":["https://arxiv.org/pdf/2311.01307"]}
-{"year":"2023","title":"The Effects of Corpus Choice and Morphosyntax on Multilingual Space Induction","authors":["V Ravishankar, J Nivre - Findings of the Association for Computational …, 2022"],"snippet":"… There is also a clear difference between Wikipedia and Common Crawl; in general, we find that correlations tend to be either weaker or less significant with Common Crawl than with Wikipedia. We hypothesise that this is due to Wikipedia …","url":["https://aclanthology.org/2022.findings-emnlp.304.pdf"]}
-{"year":"2023","title":"The emergence of autolography: the 'magical'invocation of images from text through AI","authors":["C Chesher, C Albarrán-Torres - Media International Australia, 2023"],"snippet":"In mid-2022, AI systems automatically translating text into evocative original images became an internet sensation. People compared it to magic: invoking an uncannily competent artist–magician. We call it ‘autolography’ from the Greek ‘automatos + …","url":["https://journals.sagepub.com/doi/pdf/10.1177/1329878X231193252"]}
-{"year":"2023","title":"The Falcon Series of Open Language Models","authors":["E Almazrouei, H Alobeidli, A Alshamsi, A Cappelli… - arXiv preprint arXiv …, 2023"],"snippet":"… CommonCrawl), and evaluate on English tasks. Each data split uses a dedicated tokenizer. … Latin alphabet, and sufficient presence in CommonCrawl to collect at least 10 billion tokens. … Since training of the models was started before we had …","url":["https://arxiv.org/pdf/2311.16867"]}
-{"year":"2023","title":"The Future of AI-Assisted Writing","authors":["CA Pereira, T Komarlu, W Mobeirek - arXiv preprint arXiv:2306.16641, 2023"],"snippet":"The development of Natural Language Generation models has led to the creation of powerful Artificial Intelligence-assisted writing tools. These tools are capable of predicting users' needs and actively providing suggestions as they write. In this work …","url":["https://arxiv.org/pdf/2306.16641"]}
-{"year":"2023","title":"The Future of the Human–Machine Interface (HMI) in Society 5.0","authors":["D Mourtzis, J Angelopoulos, N Panopoulos - Future Internet, 2023"],"snippet":"The blending of human and mechanical capabilities has become a reality in the realm of Industry 4.0. Enterprises are encouraged to design frameworks capable of harnessing the power of human and technological resources to enhance the era of …","url":["https://www.mdpi.com/1999-5903/15/5/162"]}
-{"year":"2023","title":"The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages","authors":["B Muller, B Alastruey, P Hansanti, E Kalbassi… - arXiv preprint arXiv …, 2023"],"snippet":"… level for Common Crawl. We segment each sample at the word level using Stanza tokenizer available in the given language (Qi et al.… In addition, we run the pipeline on a sample of Common CrawlCommon Crawl is a snapshot of crawlable …","url":["https://arxiv.org/pdf/2308.16871"]}
-{"year":"2023","title":"The generative art community bridging between UNESCO Heritage and AI-generated works: an interview with Celestino Soddu and Enrica Colabella","authors":["S Park - Proceedings of GA2023, XXVI Generative Art …, 2023"],"snippet":"… Around 60% of ChatGPT-3’s dataset was based on af iltered version of the web-crawled data of Common Crawl [1], a non -profit organisation that scraps publicly available textual data on the internet such as books, web pages and ar ticles. Most of the tasks …","url":["https://wrap.warwick.ac.uk/181879/1/WRAP-Generative-art-community-bridging-UNESCO-heritage-AI-interview-23.pdf"]}
-{"year":"2023","title":"The Ghost in the Machine: Generating Beliefs with Large Language Models","authors":["JL Bybee"],"snippet":"I introduce a methodology to generate economic expectations by applying large language models to historical news. Leveraging this methodology, I make three key contributions.(1) I show generated expectations closely match existing survey …","url":["https://lelandbybee.com/files/LLM.pdf"]}
-{"year":"2023","title":"The Governance Challenge Posed by Large Learning Models","authors":["SA Aaronson - 2023"],"snippet":"On August 24, 2023, the Office of the Australian Information Commissioner (OAIC) and 11 of its international data protection and privacy counterparts released a joint statement on web scraping (data collected by a bot from a wide range of websites) …","url":["https://www2.gwu.edu/~iiep/assets/docs/papers/2023WP/AaronsonIIEP2023-07.pdf"]}
-{"year":"2023","title":"The Great Awokening as a Global Phenomenon","authors":["D Rozado - arXiv preprint arXiv:2304.01596, 2023"],"snippet":"… The text content of the analyzed articles is available on the web domains of the respective media outlets and often also in Internet cache repositories such as Common Crawl, Google cache or the Internet Archive. Our content analysis is limited …","url":["https://arxiv.org/pdf/2304.01596"]}
-{"year":"2023","title":"The History and Future of Human–Robot Communication","authors":["F Shkurti - The SAGE Handbook of Human–Machine …, 2023"]}
-{"year":"2023","title":"The House that Looked Like It Should Collapse. Natural Language Processing for Architectural Design","authors":["N Gaudillière-Jami - … Conference on Computer-Aided Architectural Design …, 2023"],"snippet":"… It has been trained on billions of online texts, coming from databases such as Common Crawl, Books2 or Wikipedia. The texts it generates are therefore based on a very large range of information, including about architecture. While only being word-based …","url":["https://link.springer.com/chapter/10.1007/978-3-031-37189-9_7"]}
-{"year":"2023","title":"The Impact of Arabic Diacritization on Word Embeddings","authors":["M Abbache, A Abbache, J Xu, F Meziane, X Wen - ACM Transactions on Asian and …, 2023"],"snippet":"Word embedding is used to represent words for text analysis. It plays an essential role in many Natural Language Processing (NLP) studies and has hugely contributed to the extraordinary developments in the field in the last few years. In …","url":["https://dl.acm.org/doi/pdf/10.1145/3592603"]}
-{"year":"2023","title":"The Impact of Depth and Width on Transformer Language Model Generalization","authors":["J Petty, S van Steenkiste, I Dasgupta, F Sha, D Garrette… - arXiv preprint arXiv …, 2023"],"snippet":"To process novel sentences, language models (LMs) must generalize compositionally -- combine familiar elements in new ways. What aspects of a model's structure promote compositional generalization? Focusing on transformers …","url":["https://arxiv.org/pdf/2310.19956"]}
-{"year":"2023","title":"The Impact of GloVe and Word2Vec Word-Embedding Technologies on Bug Localization with Convolutional Neural Network","authors":["AS Al-Aidaroos"],"snippet":"In the field of software engineering, software quality assurance faces many challenges, including overcoming the problem of identifying errors in the source code. Finding the location of the error in the source code is a very important process …","url":["https://www.researchgate.net/profile/Ahmed-Al-Aidaroos/publication/367179325_The_Impact_of_GloVe_and_Word2Vec_Word-Embedding_Technologies_on_Bug_Localization_with_Convolutional_Neural_Network/links/63e12e5bc97bd76a827660ea/The-Impact-of-GloVe-and-Word2Vec-Word-Embedding-Technologies-on-Bug-Localization-with-Convolutional-Neural-Network.pdf"]}
-{"year":"2023","title":"The Importance of Context in the Evaluation of Word Embeddings: The Effects of Antonymy and Polysemy","authors":["J Fodor, S De Deyne, S Suzuki"],"snippet":"Word embeddings are widely used for diverse applications in natural language processing. Despite extensive research, it is unclear when they succeed or fail to capture human judgements of semantic relatedness and similarity. In this study, we …","url":["https://iwcs.pimoid.fr/11.pdf"]}
-{"year":"2023","title":"The Less the Merrier? Investigating Language Representation in Multilingual Models","authors":["HH Nigatu, AL Tonja, J Kalita - arXiv preprint arXiv:2310.13228, 2023"],"snippet":"… 2019) is a multilingual Transformer-based MLM trained on the Common Crawl data for 100 languages. To balance data between English and other languages, the XLM-R uses one dump for English and 12 dumps for all other languages. … Filtered …","url":["https://arxiv.org/pdf/2310.13228"]}
-{"year":"2023","title":"The Library & Generative AI","authors":["N Gustafson-Sundell, M McCullough - 2023"],"snippet":"A demonstration of several AI tools, including ChatGPT, ChatPDF, Consensus, and more. The focus of the session is on potential student uses of the tools and related library initiatives, so we address the limits of ChatGPT as an information source …","url":["https://cornerstone.lib.mnsu.edu/cgi/viewcontent.cgi?article=1205&context=lib_services_fac_pubs"]}
-{"year":"2023","title":"The Mental Representation of Structured Auditory Sequences in Memory","authors":["O Raccah - 2023"],"snippet":"The capacity to remember and retrieve sequences of items or everyday experiences is fundamental to human intelligence. The goal of this research is to understand how the episodic memory system supports the integration, representation, and retrieval of …","url":["https://search.proquest.com/openview/1ad1d94e88a7df947828924bc4fafb4b/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"The more","authors":["KS Yong, JSY Liew - Journal of Intelligent Information Systems, 2023"],"snippet":"… The main difference between the two InferSent model is one uses GloVe word embeddings trained on Common Crawl 840B (InferSent-GloVe) and the other uses fastText word embeddings trained on Common Crawl 600B (InferSent-fastText). …","url":["https://link.springer.com/article/10.1007/s10844-023-00791-3"]}
-{"year":"2023","title":"The Nordic Pile: A 1.2 TB Nordic Dataset for Language Modeling","authors":["J Öhman, S Verlinden, A Ekgren, AC Gyllensten… - arXiv preprint arXiv …, 2023"],"snippet":"… We decided that our Nordic-language datasets were more prone to include many duplicate documents since we included several data sources from Common Crawl that may overlap for these languages. So, our English data was deduplicated intra-shard …","url":["https://arxiv.org/pdf/2303.17183"]}
-{"year":"2023","title":"The Ouroboros Threat","authors":["JM Vukov, TL Joseph, G Lebkuecher, M Ramirez… - The American Journal of …, 2023"],"snippet":"Jorge Luis Borges introduces the mythical ouroboros as follows:“A third-century Greek amulet, to be found today in the British Museum, gives us an image that can better illustrate that infinitude: the serpent that bites its own tail”(Borges 2005). In this …","url":["https://www.tandfonline.com/doi/full/10.1080/15265161.2023.2250284"]}
-{"year":"2023","title":"The Perils & Promises of Fact-checking with Large Language Models","authors":["D Quelle, A Bovet - arXiv preprint arXiv:2310.13549, 2023"],"snippet":"… The GPT models are trained on vast amounts of unstructured textual data like the common crawl data-set, which is the largest data-set to be included in the training. Common Crawl is a web archive that consists of terabytes of data collected since …","url":["https://arxiv.org/pdf/2310.13549"]}
-{"year":"2023","title":"The perpetual motion machine of AI-generated data and the distraction of ChatGPT-as-scientist","authors":["J Listgarten - arXiv preprint arXiv:2312.00818, 2023"],"snippet":"Since ChatGPT works so well, are we on the cusp of solving science with AI? Is not AlphaFold2 suggestive that the potential of LLMs in biology and the sciences more broadly is limitless? Can we use AI itself to bridge the lack of data in the sciences in …","url":["https://arxiv.org/pdf/2312.00818"]}
-{"year":"2023","title":"The Photographic Pipeline of Machine Vision; or, Machine Vision's Latent Photographic Theory","authors":["N Malevé, K Sluis - Critical AI, 2023"],"snippet":"Despite computer vision's extensive mobilization of cameras, photographers, and viewing subjects, photography's place in machine vision remains undertheorized. This article illuminates an operative theory of photography that exists in a latent form …","url":["https://read.dukeupress.edu/critical-ai/article-abstract/doi/10.1215/2834703X-10734066/382465"]}
-{"year":"2023","title":"The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data Only","authors":["G Penedo, Q Malartic, D Hesslow, R Cojocaru… - Thirty-seventh Conference …, 2023"],"snippet":"… Although this is only a 135 narrow subset of the kind of pages making up CommonCrawl, we found this finding to hold more 136 broadly. We use trafilatura for text extraction, and apply extra formatting via regular expressions: 137 we limit new …","url":["https://openreview.net/pdf?id=kM5eGcdCzq"]}
-{"year":"2023","title":"The RefinedWeb Dataset for Falcon LLM: Outperforming Curated Corpora with Web Data, and Web Data Only","authors":["G Penedo, Q Malartic, D Hesslow, R Cojocaru…"],"snippet":"… Although this is only a narrow subset of the kind of pages making up CommonCrawl, we found this finding to hold more broadly. We use trafilatura … in the processed CommonCrawl data were identified as English. We find the …","url":["https://falconllm.tii.ae/Falcon_LLM_RefinedWeb.pdf"]}
-{"year":"2023","title":"The Role of Codeword-to-Class Assignments in Error-Correcting Codes: An Empirical Study","authors":["I Evron, O Onn, TW Orzech, H Azeroual, D Soudry - arXiv preprint arXiv:2302.05334, 2023"],"snippet":"Error-correcting codes (ECC) are used to reduce multiclass classification tasks to multiple binary classification subproblems. In ECC, classes are represented by the rows of a binary matrix, corresponding to codewords in a codebook. Codebooks are …","url":["https://arxiv.org/pdf/2302.05334"]}
-{"year":"2023","title":"The Role of Pre-training Data in Transfer Learning","authors":["R Entezari, M Wortsman, O Saukh, MM Shariatnia… - arXiv preprint arXiv …, 2023"],"snippet":"… Common crawl. https://commoncraw .org/. Accessed: 2022-09-20. … 2021): The images and corresponding alt-texts come from web pages collected by Common Crawl (Com) between 2014 and 2021. We randomly select a subset of 2.7M and …","url":["https://arxiv.org/pdf/2302.13602"]}
-{"year":"2023","title":"The Skipped Beat: A Study of Sociopragmatic Understanding in LLMs for 64 Languages","authors":["C Zhang, KD Doan, Q Liao, M Abdul-Mageed - arXiv preprint arXiv:2310.14557, 2023"],"snippet":"Instruction tuned large language models (LLMs), such as ChatGPT, demonstrate remarkable performance in a wide range of tasks. Despite numerous recent studies that examine the performance of instruction-tuned LLMs on various NLP benchmarks …","url":["https://arxiv.org/pdf/2310.14557"]}
-{"year":"2023","title":"The social construction of datasets: On the practices, processes and challenges of dataset creation for machine learning","authors":["W Orr, K Crawford - 2023"],"snippet":"Despite the critical role that datasets play in how systems make predictions and interpret the world, the dynamics of their construction are not well understood. Drawing on a corpus of interviews with dataset creators, we uncover the messy and …","url":["https://osf.io/preprints/socarxiv/8c9uh/download"]}
-{"year":"2023","title":"The Three Terms Task-an open benchmark to compare human and artificial semantic representations","authors":["V Borghesani, J Armoza, MN Hebart, P Bellec… - Scientific Data, 2023"],"snippet":"… A fasttext 32 model trained on Common Crawl with subword information. Finally, three additional fasttext 32,39,40 models trained on … First, fasttext models outperform glove ones, except for the fasttext model trained on Common Crawl. As a …","url":["https://www.nature.com/articles/s41597-023-02015-3"]}
-{"year":"2023","title":"The Use of a Large Language Model for Cyberbullying Detection. Analytics 2023, 2, 694–707","authors":["B Ogunleye, B Dharmaraj - 2023"],"snippet":"… It was trained on 100 languages from 2.5 TB of filtered common crawl data. The “RoBERTa” part in XLM-RoBERTa originates from the fact that it uses the identical training procedures as the monolingual RoBERTa model, with the Masked Language Model …","url":["https://www.academia.edu/download/106522086/analytics_02_00038_6_.pdf"]}
-{"year":"2023","title":"The Utility of Large Language Models and Generative AI for Education Research","authors":["A Katz, U Shakir, B Chambers - arXiv preprint arXiv:2305.18125, 2023"],"snippet":"… Typically pre-trained on extensive text corpora (eg, a common crawl of the web consisting of billions of tokens of text) and fine-tuned for tasks such as question-answering or text classification [1], LLMs are distinguished by their capacity to seemingly …","url":["https://arxiv.org/pdf/2305.18125"]}
-{"year":"2023","title":"The Value of Web Data Scraping: An Application to TripAdvisor","authors":["G Barbera, L Araujo, S Fernandes - Big Data and Cognitive Computing, 2023"],"snippet":"Social Media Analytics (SMA) is more and more relevant in today’s market dynamics. However, it is necessary to use it wisely, either in promoting any kind of product/brand, or interacting with customers. This requires its effective understanding and …","url":["https://www.mdpi.com/2504-2289/7/3/121"]}
-{"year":"2023","title":"The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation","authors":["DN Manh, NL Hai, ATV Dau, AM Nguyen, K Nghiem… - arXiv preprint arXiv …, 2023"],"snippet":"We present The Vault, an open-source, large-scale code-text dataset designed to enhance the training of code-focused large language models (LLMs). Existing open-source datasets for training code-based LLMs often face challenges in terms of size, quality (due …","url":["https://arxiv.org/pdf/2305.06156"]}
-{"year":"2023","title":"The Web Can Be Your Oyster for Improving Language Models","authors":["J Li, T Tang, WX Zhao, J Wang, JY Nie, JR Wen - Findings of the Association for …, 2023"],"snippet":"… Common Crawl snapshot which covers a wide range of 134M web documents and finally yields 906M passages of 100 tokens. CCNet processes Common Crawl … an analysis of undesirable content in the common crawl corpus. In Proceedings of …","url":["https://aclanthology.org/2023.findings-acl.46.pdf"]}
-{"year":"2023","title":"The Web Can Be Your Oyster for Improving Large Language Models","authors":["J Li, T Tang, WX Zhao, J Wang, JY Nie, JR Wen - arXiv preprint arXiv:2305.10998, 2023"],"snippet":"… Common Crawl snapshot which covers a wide range of 134M web documents and finally yields 906M passages of 100 tokens. CCNet processes Common Crawl … an analysis of undesirable content in the common crawl corpus. In Proceedings of …","url":["https://arxiv.org/pdf/2305.10998"]}
-{"year":"2023","title":"The Web Data Commons Schema. org Data Set Series","authors":["A Brinkmann, A Primpeli, C Bizer - Companion Proceedings of the ACM Web …, 2023"],"snippet":"… The Web Data Commons project has been extracting schema.org data from the Common Crawl every year since 2013 and offers the extracted data for public download in the form of the schema.org data set series. The latest release in the …","url":["https://dl.acm.org/doi/abs/10.1145/3543873.3587331"]}
-{"year":"2023","title":"Theoretical Considerations on AI-based Business Models for Lexicography","authors":["H Køhler Simonsen - Lexicographica, 2023"],"snippet":"AI-generated text production is on the rise Zandan (2020), and AI writers seem to be playing an increasingly important role in marketing, L2 text production, lexicography and language teaching, cf. Simonsen (2020b; 2021a; 2022a; 2022b; Sharples/Pérez …","url":["https://www.degruyter.com/document/doi/10.1515/lex-2023-0013/html"]}
-{"year":"2023","title":"There's no Data Like Better Data: Using QE Metrics for MT Data Filtering","authors":["JT Peter, D Vilar, D Deutsch, M Finkelstein, J Juraska… - arXiv preprint arXiv …, 2023"],"snippet":"Quality Estimation (QE), the evaluation of machine translation output without the need of explicit references, has seen big improvements in the last years with the use of neural metrics. In this paper we analyze the viability of using QE metrics for …","url":["https://arxiv.org/pdf/2311.05350"]}
-{"year":"2023","title":"This Is a Local Domain: On Amassing Country-Code Top-Level Domains from Public Data","authors":["R Sommese, R van Rijswijk-Deij, M Jonker - arXiv preprint arXiv:2309.01441, 2023"],"snippet":"… For Common Crawl we consider data for crawl snapshots dated between June 2017 and June 2023 (inclusive). There are 58 such snapshots, collectively accounting for 127 million registered domain names. The combined total number of …","url":["https://arxiv.org/pdf/2309.01441"]}
-{"year":"2023","title":"Thou Shalt Not Reject: Analyzing Accept-Or-Pay Cookie Banners on the Web","authors":["A Rasaii, D Gosain, O Gasser - 2023"],"snippet":"Privacy regulations have led to many websites showing cookie banners to their users. Usually, cookie banners present the user with the option to “accept” or “reject” cookies. Recently, a new form of paywall-like cookie banner has taken hold on the …","url":["https://www.devashishgosain.com/assets/files/paper-cameraready.pdf"]}
-{"year":"2023","title":"TiBERT: A Non-autoregressive Pre-trained Model for Text Editing","authors":["B Wang, Z Wang, W Che, D Wu, R Zhang, B Wang… - … International Conference on …, 2023"],"snippet":"Text editing refers to the task of creating new sentences by altering existing text through methods such as replacing, inserting, or deleting. Two commonly used techniques for text editing are Seq2Seq and sequence labeling. The Seq2Seq …","url":["https://link.springer.com/chapter/10.1007/978-3-031-44699-3_2"]}
-{"year":"2023","title":"TiC-CLIP: Continual Training of CLIP Models","authors":["S Garg, M Farajtabar, H Pouransari, R Vemulapalli… - arXiv preprint arXiv …, 2023"],"snippet":"… OpenCLIP models (eg, models trained on Datacomp and LAION-5B) have been trained on data curated from Common Crawl. Since the retrieval tasks we constructed are built on top of data curated from Common Crawl, one may argue …","url":["https://arxiv.org/pdf/2310.16226"]}
-{"year":"2023","title":"TIL TA'LIMIDA RAQAMLI TEXNOLOGIY VA SUN'IY INTELLEKT VOSITALARIDAN FOYDALANISH","authors":["M Shahista - Innovations in Technology and Science Education, 2023"],"snippet":"… Algoritmni o’qitish uchun ingliz tilidagi 570 Gb hajmdagi matndan foydalanigan – matnlar Vikipediyadan, Common Crawl loyihasidan, ikkita kitoblar datasetidan va WebText2 datasetdagi web-sahifalardan olingan. Lekin bunda rus tilidagi matnlar …","url":["https://humoscience.com/index.php/itse/article/download/711/1277"]}
-{"year":"2023","title":"TIL TA'LIMIDA RAQAMLI TEXNOLOGIYALARDAN FOYDALANISH USUL VA VOSITALARI","authors":["R Ayupov, S Maksimkulava, G Baltabaeva - Евразийский журнал академических …, 2023"],"snippet":"… Algoritmni o’qitish uchun ingliz tilidagi 570 Gb hajmdagi matndan foydalanigan – matnlar Vikipediyadan, Common Crawl loyihasidan, ikkita kitoblar datasetidan va WebText2 datasetdagi web-sahifalardan olingan. Lekin bunda rus tilidagi matnlar …","url":["https://in-academy.uz/index.php/ejar/article/download/14466/10065"]}
-{"year":"2023","title":"TinyStories: How Small Can Language Models Be and Still Speak Coherent English?","authors":["R Eldan, Y Li - arXiv preprint arXiv:2305.07759, 2023"],"snippet":"Language models (LMs) are powerful tools for natural language processing, but they often struggle to produce coherent and fluent text when they are small. Models with around 125M parameters such as GPT-Neo (small) or GPT-2 (small) can rarely …","url":["https://arxiv.org/pdf/2305.07759"]}
-{"year":"2023","title":"TKG: Telecom Knowledge Governance Framework for LLM Application","authors":["H Cai, S Wu - 2023"],"snippet":"… 15], such as Common Crawl and Wikipedia, which offer limited exposure to domain-specific resources. In telecommunications, there exist numerous manuals, delivery documents, and fault diagnosis cases related to communication equipment …","url":["https://www.researchsquare.com/article/rs-3252192/latest.pdf"]}
-{"year":"2023","title":"TMD-BERT: A Transformer-Based Model for Transportation Mode Detection","authors":["I Drosouli, A Voulodimos, P Mastorocostas, G Miaoulis… - Electronics, 2023"],"snippet":"… This feature led to the development of pre-trained systems such as BERT (Bidirectional Encoder Representations from Transformers) [23] which was trained with large language datasets, such as the Wikipedia Corpus and Common Crawl. Thus …","url":["https://www.mdpi.com/2090966"]}
-{"year":"2023","title":"TMD-NER: Turkish multi-domain named entity recognition for informal texts","authors":["SF Yilmaz, FB Mutlu, I Balaban, SS Kozat - Signal, Image and Video Processing, 2023"],"snippet":"We examine named entity recognition (NER), an essential and commonly used first step in many natural language processing tasks, including chatbots and language translation. We focus on the application of NER to texts that have a lot of noise, such …","url":["https://link.springer.com/article/10.1007/s11760-023-02898-0"]}
-{"year":"2023","title":"tmn at SemEval-2023 Task 9: Multilingual Tweet Intimacy Detection using XLM-T, Google Translate, and Ensemble Learning","authors":["A Glazkova - arXiv preprint arXiv:2304.04054, 2023"],"snippet":"The paper describes a transformer-based system designed for SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis. The purpose of the task was to predict the intimacy of tweets in a range from 1 (not intimate at all) to 5 (very intimate). The …","url":["https://arxiv.org/pdf/2304.04054"]}
-{"year":"2023","title":"To token or not to token: A Comparative Study of Text Representations for Cross-Lingual Transfer","authors":["MM Rahman, FA Sakib, F Faisal, A Anastasopoulos - arXiv preprint arXiv:2310.08078, 2023"],"snippet":"Choosing an appropriate tokenization scheme is often a bottleneck in low-resource cross-lingual transfer. To understand the downstream implications of text representation choices, we perform a comparative analysis on language models …","url":["https://arxiv.org/pdf/2310.08078"]}
-{"year":"2023","title":"Token-level Identification of Multiword Expressions using Pre-trained Multilingual Language Models","authors":["R Swaminathan, P Cook - Proceedings of the 19th Workshop on Multiword …, 2023"],"snippet":"In this paper, we consider novel cross-lingual settings for multiword expression (MWE) identification (Ramisch et al., 2020) and idiomaticity prediction (Tayyar Madabushi et al., 2022) in which systems are tested on languages that are unseen during training …","url":["https://aclanthology.org/2023.mwe-1.1.pdf"]}
-{"year":"2023","title":"Tokenization and the Noiseless Channel","authors":["V Zouhar, C Meister, JL Gastaldi, L Du, M Sachan… - arXiv preprint arXiv …, 2023"],"snippet":"… of 0.78 with BLEU on German → English MT (1M parallel sentences from CommonCrawl). This stands in contrast to Shannon entropy or expected … We use the English→German CommonCrawl dataset in all experiments. The specifics of the …","url":["https://arxiv.org/pdf/2306.16842"]}
-{"year":"2023","title":"Tokenizer Choice For LLM Training: Negligible or Crucial?","authors":["M Ali, M Fromm, K Thellmann, R Rutmann…"],"snippet":"The recent success of Large Language Models (LLMs) has been predominantly driven by curating the training dataset composition, scaling of model architectures and dataset sizes and advancements in pretraining objectives, leaving tokenizer …","url":["https://arxiv.org/pdf/2310.08754"]}
-{"year":"2023","title":"Too Legal; Didn't Read (TLDR): Summarization of Court Opinions","authors":["A Ghimire, R Shrestha, J Edwards - 2023 Intermountain Engineering, Technology and …, 2023"],"snippet":"… The majority of data in the PEGASUS project come from web common crawl, social media, and news. It however also includes the BillSum dataset [17]. BillSum (Kornilova & Eidelman, 2019) contains 23k US Congressional bills and human-written …","url":["https://ieeexplore.ieee.org/abstract/document/10152119/"]}
-{"year":"2023","title":"Topical Clustering of Unlabeled Transformer-Encoded Researcher Activity","authors":["Z Bettouche, A Fischer - Bavarian Journal of Applied Sciences, 2023"],"snippet":"Transformer models have the ability to understand the meaning of text efficiently through the use of self-attention mechanisms. We investigate the bundled meanings in clusters of transformer-generated embeddings by evaluating the topical clustering …","url":["https://jas.bayern/index.php/bjas/article/download/135/55"]}
-{"year":"2023","title":"Topological Interpretations of GPT-3","authors":["T Sun, B Nelson - arXiv preprint arXiv:2308.03565, 2023"],"snippet":"This is an experiential study of investigating a consistent method for deriving the correlation between sentence vector and semantic meaning of a sentence. We first used three state-of-the-art word/sentence embedding methods including GPT-3 …","url":["https://arxiv.org/pdf/2308.03565"]}
-{"year":"2023","title":"TorchicTab: Semantic Table Annotation with Wikidata and Language Models","authors":["I Dasoulas, D Yang, X Duan, A Dimou - CEUR Workshop Proceedings, 2023"],"snippet":"… (3) The SOTAB Tables refer to the WDC Schema.org Table Annotation Benchmark3, generated by extracting Schema.org data from the Common Crawl. The data is grouped into separate tables for each class/host combination with the label spaces …","url":["https://lirias.kuleuven.be/retrieve/733695"]}
-{"year":"2023","title":"TourismNLG: A Multi-lingual Generative Benchmark for the Tourism Domain","authors":["SM Bhatt, S Agarwal, O Gurjar, M Gupta, M Shrivastava - Advances in Information …, 2023"],"snippet":"… We use the mC4-pretrained mT5-base and CommonCrawl-pretrained mBART-large models, and perform domain adaptive pretraining to adapt them to the tourism domain. These are then further finetuned using task-specific labeled data. We …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28244-7_10"]}
-{"year":"2023","title":"Toward automatic generation of control structures for process flow diagrams with large language models","authors":["E Hirtreiter, L Schulze Balhorn, AM Schweidtmann - AIChE Journal, 2023"],"snippet":"Developing Piping and Instrumentation Diagrams (P&IDs) is a crucial step during process development. We propose a data‐driven method for the prediction of control structures. Our methodology is inspired by end‐to‐end transformer‐based human …","url":["https://aiche.onlinelibrary.wiley.com/doi/pdf/10.1002/aic.18259"]}
-{"year":"2023","title":"Toward Detection of Arabic Cyberbullying on Online Social Networks using Arabic BERT Models","authors":["ME AlFarah, I Kamel, Z Al Aghbari - 2023 International Symposium on Networks …, 2023"],"snippet":"Cyberbullying is one of the serious threats on social networks particularly toward children and teenagers. Cyberbullying can cause many harmful consequences towards victims such as anxiety, depression and even suicide. This research studies …","url":["https://ieeexplore.ieee.org/abstract/document/10323808/"]}
-{"year":"2023","title":"Toward Semi-supervised Transcription of NAKO+ ILSE: Influence of Auto-matic Speech Recognition Performance on Manual Transcription Effort","authors":["E Brauße, K Scheck, T Schultz"],"snippet":"… The best performance was achieved using flat start HMMGaussian Mixture Model initialization in acoustic modeling and an RNN-LM trained on the ILSE training text data with additional, semantically similar Common Crawl text data. The mismatch …","url":["https://csl.uni-bremen.de/cms/images/documents/publications/BrausseScheckSchultz_ITG23.pdf"]}
-{"year":"2023","title":"Towards a Common Understanding of Contributing Factors for Cross-Lingual Transfer in Multilingual Language Models: A Review","authors":["F Philippy, S Guo, S Haddadan - arXiv preprint arXiv:2305.16768, 2023"],"snippet":"In recent years, pre-trained Multilingual Language Models (MLLMs) have shown a strong ability to transfer knowledge across different languages. However, given that the aspiration for such an ability has not been explicitly incorporated in the design of …","url":["https://arxiv.org/pdf/2305.16768"]}
-{"year":"2023","title":"Towards Auditing Large Language Models: Improving Text-based Stereotype Detection","authors":["W Zekun, S Bulathwela, AS Koshiyama - arXiv preprint arXiv:2311.14126, 2023"],"snippet":"… However, they show fairness concerns due to their training on extensive, unfiltered datasets such as book [8] and Wikipedia corpora [9], and large internet corpora like Common Crawl [10]. This training data often exhibits systemic biases …","url":["https://arxiv.org/pdf/2311.14126"]}
-{"year":"2023","title":"Towards Automatic Evaluation of NLG Tasks Using Conversational Large Language Models","authors":["M Riyadh, MO Shafiq - Artificial Intelligence Applications and Innovations: 19th …, 2023"],"snippet":"Evaluating the quality of machine generated open-ended texts is a long-standing challenge in Natural Language Processing (NLP). Even though there have been dramatic advancements in the machine learning technologies that propelled the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-34107-6_34"]}
-{"year":"2023","title":"Towards Automatic Identification of Violation Symptoms of Architecture Erosion","authors":["R Li, P Liang, P Avgeriou - arXiv preprint arXiv:2306.08616, 2023"],"snippet":"… Based on the fastText model, Meta published pre-trained word vectors with 300 dimensions for 157 languages constructed on Common Crawl and Wikipedia5. In this study, we employed the pre-trained fastText model, which can be transformed …","url":["https://arxiv.org/pdf/2306.08616"]}
-{"year":"2023","title":"Towards Better Evaluation of Instruction-Following: A Case-Study in Summarization","authors":["O Skopek, R Aralikatte, S Gooding, V Carbune - arXiv preprint arXiv:2310.08394, 2023"],"snippet":"Despite recent advances, evaluating how well large language models (LLMs) follow user instructions remains an open problem. While evaluation methods of language models have seen a rise in prompt-based approaches, limited work on the …","url":["https://arxiv.org/pdf/2310.08394"]}
-{"year":"2023","title":"Towards Comparable Active Learning","authors":["T Werner, J Burchert, L Schmidt-Thieme - arXiv preprint arXiv:2311.18356, 2023"],"snippet":"Active Learning has received significant attention in the field of machine learning for its potential in selecting the most informative samples for labeling, thereby reducing data annotation costs. However, we show that the reported lifts in recent literature …","url":["https://arxiv.org/pdf/2311.18356"]}
-{"year":"2023","title":"Towards End-User Development for IoT: A Case Study on Semantic Parsing of Cooking Recipes for Programming Kitchen Devices","authors":["F Ventirozos, S Clinch, R Batista-Navarro - arXiv preprint arXiv:2309.14165, 2023"],"snippet":"Semantic parsing of user-generated instructional text, in the way of enabling end-users to program the Internet of Things (IoT), is an underexplored area. In this study, we provide a unique annotated corpus which aims to support the transformation of …","url":["https://arxiv.org/pdf/2309.14165"]}
-{"year":"2023","title":"Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning","authors":["Z Charles, N Mitchell, K Pillutla, M Reneer, Z Garrett - arXiv preprint arXiv:2307.09619, 2023"],"snippet":"We introduce a library, Dataset Grouper, to create large-scale group-structured (eg, federated) datasets, enabling federated learning simulation at the scale of foundation models. This library allows the creation of group-structured versions of …","url":["https://arxiv.org/pdf/2307.09619"]}
-{"year":"2023","title":"Towards General Text Embeddings with Multi-stage Contrastive Learning","authors":["Z Li, X Zhang, Y Zhang, D Long, P Xie, M Zhang - arXiv preprint arXiv:2308.03281, 2023"],"snippet":"We present GTE, a general-purpose text embedding model trained with multi-stage contrastive learning. In line with recent advancements in unifying various NLP tasks into a single format, we train a unified text embedding model by employing …","url":["https://arxiv.org/pdf/2308.03281"]}
-{"year":"2023","title":"Towards Informed Pre-Training for Critical Error Detection in English-German","authors":["L Pucknat, M Pielka, R Sifa - 2022"],"snippet":"This paper presents two data augmentation methods for pre-training, to find critical errors in machine translations. This includes an alignment approach used in traditional machine translation and an imitation method, mimicking the structure of …","url":["https://ceur-ws.org/Vol-3341/KDML-LWDA_2022_CRC_9736.pdf"]}
-{"year":"2023","title":"Towards Massively Multi-domain Multilingual Readability Assessment","authors":["T Naous, MJ Ryan, M Chandra, W Xu - arXiv preprint arXiv:2305.14463, 2023"],"snippet":"We present ReadMe++, a massively multi-domain multilingual dataset for automatic readability assessment. Prior work on readability assessment has been mostly restricted to the English language and one or two text domains. Additionally, the …","url":["https://arxiv.org/pdf/2305.14463"]}
-{"year":"2023","title":"Towards Multilingual Automatic Dialogue Evaluation","authors":["J Mendonça, A Lavie, I Trancoso - arXiv preprint arXiv:2308.16795, 2023"],"snippet":"The main limiting factor in the development of robust multilingual dialogue evaluation metrics is the lack of multilingual data and the limited availability of open sourced multilingual dialogue systems. In this work, we propose a workaround for …","url":["https://arxiv.org/pdf/2308.16795"]}
-{"year":"2023","title":"Towards multilingual automatic open-domain dialogue evaluation","authors":["J Mendonça, A Lavie, I Trancoso - Proceedings of the 24th Meeting of the Special …, 2023"],"snippet":"The main limiting factor in the development of robust multilingual open-domain dialogue evaluation metrics is the lack of multilingual data and the limited availability of open-sourced multilingual dialogue systems. In this work, we propose a …","url":["https://aclanthology.org/2023.sigdial-1.11.pdf"]}
-{"year":"2023","title":"Towards Scalable Structured Data from Clinical Text","authors":["M Agrawal - 2023"],"snippet":"The adoption of electronic health records (EHRs) presents an incredible opportunity to improve medicine both at the point-of-care and through retrospective research. Unfortunately, many pertinent variables are trapped in unstructured clinical note text …","url":["https://dspace.mit.edu/bitstream/handle/1721.1/150049/Agrawal-magrawal-PhD-EECS-2023-thesis.pdf?sequence=1&isAllowed=y"]}
-{"year":"2023","title":"Towards Sentence-level Text Readability Assessment for French","authors":["D Van Ngo, Y Parmentier - Second Workshop on Text Simplification, Accessibility …, 2023"],"snippet":"In this paper, we report on some experiments aimed at exploring the relation between document-level and sentence-level readability assessment for French. These were run on an open-source tailored corpus, which was automatically created …","url":["https://hal.science/hal-04192063/document"]}
-{"year":"2023","title":"Towards Understanding the Generalization of Medical Text-to-SQL Models and Datasets","authors":["R Tarbell, KKR Choo, G Dietrich, A Rios - arXiv preprint arXiv:2303.12898, 2023"],"snippet":"… To train T5, Google used a diverse corpus of text data from sources such as Wikipedia, Common Crawl, and the web pages crawled by Google. We apply the T5 model to the medical text-to-SQL task. The input to the model includes the database …","url":["https://arxiv.org/pdf/2303.12898"]}
-{"year":"2023","title":"Toxic Content Recognition in Conversational Systems","authors":["A Černý - 2023"],"snippet":"Guidelines: The goal of the thesis is to devise a method of recognition of toxic content in conversational systems. 1) Review the current methods used for recognizing toxic content, with focus on methods based on embedding clustering …","url":["https://dspace.cvut.cz/bitstream/handle/10467/109402/F3-BP-2023-Cerny-Adam-toxic_content_recognition_in_conversational_systems.pdf"]}
-{"year":"2023","title":"Traces of Human Attitudes in Contemporary and Historical Word Embeddings (1800-2000)","authors":["K Morehouse, V Rouduri, W Cunningham… - 2023"],"snippet":"… When inspecting the 36 separate models (each measuring the relationship between implicit attitudes and an evaluative language representation eg, Glove:Common Crawl WEAT-long), results showed that > 95% of the posterior fell outside the ROPE …","url":["https://www.researchsquare.com/article/rs-2922677/latest"]}
-{"year":"2023","title":"Tracking the Newsworthiness of Public Documents","authors":["A Spangher, E Ferrara, B Welsh, N Peng, S Tumgoren… - arXiv preprint arXiv …, 2023"],"snippet":"… 2013–2023 and via the Common Crawl4. We parse article text5 and deduplicate based on text, and ultimately are left with a set of 202,644 SFChron articles6. We also scrape the public meeting calendar on the SFBOS website7 to collect all …","url":["https://arxiv.org/pdf/2311.09734"]}
-{"year":"2023","title":"Tracking User Web Browsing Behavior: Privacy Harms and Security Benefits","authors":["K Crichton - 2023"],"snippet":"The presence of web tracking technology has grown to a near-ubiquitous state as web pages contain a growing number of trackers, representing progressively more and more third parties, that employ an increasingly diverse set of tracking techniques …","url":["https://search.proquest.com/openview/6b098df0b4bbe2dc898f1ba71c4d5c4c/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"TrackSign-labeled web tracking dataset","authors":["I Castell-Uroz, P Barlet-Ros - Computer Networks, 2023"],"snippet":"Recent studies [8] show that more than 95% of the websites available on the Internet contain at least one of the so-called web tracking systems. These systems are specialized in identifying their users by means of a plethora of different methods …","url":["https://www.sciencedirect.com/science/article/pii/S1389128623001329"]}
-{"year":"2023","title":"Training CLIP models on Data from Scientific Papers","authors":["C Metzger - arXiv preprint arXiv:2311.04711, 2023"],"snippet":"Contrastive Language-Image Pretraining (CLIP) models are able to capture the semantic relationship of images and texts and have enabled a wide range of applications, from image retrieval to classification. These models are trained with …","url":["https://arxiv.org/pdf/2311.04711"]}
-{"year":"2023","title":"Transfer Learning across Several Centuries: Machine and Historian Integrated Method to Decipher Royal Secretary's Diary","authors":["SL Kim, T Jang, J Ahn, H Lee, J Lee - arXiv preprint arXiv:2306.14592, 2023"],"snippet":"A named entity recognition and classification plays the first and foremost important role in capturing semantics in data and anchoring in translation as well as downstream study for history. However, NER in historical text has faced challenges …","url":["https://arxiv.org/pdf/2306.14592"]}
-{"year":"2023","title":"Transfer Learning for Code-Mixed Data: Do Pretraining Languages Matter?","authors":["K Tatariya, H Lent, M De Lhoneux - Proceedings of the 13th Workshop on …, 2023"],"snippet":"… 2020) is the multilingual version of RoBERTa, pretrained on 100 languages from the CommonCrawl corpus. The Hindi included in the pretraining is … , with data sourced from the BBC news and the Common Crawl Corpus. It is trained with the …","url":["https://aclanthology.org/2023.wassa-1.32.pdf"]}
-{"year":"2023","title":"Transfer Learning of Transformer-based Speech Recognition Models from Czech to Slovak","authors":["J Lehečka, JV Psutka, J Psutka - arXiv preprint arXiv:2306.04399, 2023"],"snippet":"… As training data, we used web pages from the Common Crawl project3. We downloaded and processed 34 crawls from August 2018 to October 2021 following the same cleaning and deduplicating rules as in the English C4 dataset [14] …","url":["https://arxiv.org/pdf/2306.04399"]}
-{"year":"2023","title":"Transformer based Answer-Aware Bengali Question Generation","authors":["JF Ruma, TT Mayeesha, RM Rahman - International Journal of Cognitive Computing …, 2023"],"snippet":"… or T5 (Raffel et al., 2020) trained on a Common-Crawl based dataset called mC4 covering 101 languages. T5 model was introduced during … MC4 dataset contains 101 language variants drawn from the Common Crawl web scrape. MT5 did not …","url":["https://www.sciencedirect.com/science/article/pii/S2666307423000311"]}
-{"year":"2023","title":"Transformer Based Image-Text Consistency Analysis for Infographic Articles","authors":["Y Chen, MC Chang - 2023 IEEE 6th International Conference on Multimedia …, 2023"],"snippet":"… We start with a T5 model that is pre-trained on both the common crawl-based dataset of Colossal Clean Crawled Corpus (C4) [8] and the Multi-NLI [13] datasets. Thereafter, we fine-tuned the Transformer further by using the Stanford Natural …","url":["https://ieeexplore.ieee.org/abstract/document/10254411/"]}
-{"year":"2023","title":"Transformer Based Implementation for Automatic Book Summarization","authors":["S Porwal, L Bewoor, V Deshpande - International Journal of Intelligent Systems and …, 2022"],"snippet":"Document Summarization is the procedure of generating a meaningful and concise summary of a given document with the inclusion of relevant and topic-important points. There are two approaches-one is picking up the most relevant statements …","url":["https://ijisae.org/index.php/IJISAE/article/download/2421/1003"]}
-{"year":"2023","title":"Transformer Models for Machine Translation and Streaming Automatic Speech Recognition","authors":["P Baquero Arnal - 2023"],"snippet":"[EN] Natural language processing (NLP) is a set of fundamental computing problems with immense applicability, as language is the natural communication vehicle for people. NLP, along with many other computer technologies, has been …","url":["https://riunet.upv.es/bitstream/handle/10251/193680/Baquero%20-%20Transformer%20models%20for%20Machine%20Translation%20and%20Streaming%20Automatic%20Speech%20Recognition.pdf?sequence=4"]}
-{"year":"2023","title":"Transformer models for mining intents and predicting activities from emails in knowledge-intensive processes","authors":["F Khandaker, A Senderovich, J Zhao, E Cohen, E Yu… - Engineering Applications of …, 2024"],"snippet":"Process mining is an interdisciplinary field that combines Artificial Intelligence and Business Process Management to extract insights from historical event data. Knowledge-intensive processes, which predominantly involve knowledge work, are …","url":["https://www.sciencedirect.com/science/article/pii/S0952197623016342"]}
-{"year":"2023","title":"Transformer models: an introduction and catalog","authors":["X Amatriain - arXiv preprint arXiv:2302.07730, 2023"],"snippet":"In the past few years we have seen the meteoric appearance of dozens of models of the Transformer family, all of which have funny, but not self-explanatory, names. The goal of this paper is to offer a somewhat comprehensive but simple catalog and …","url":["https://arxiv.org/pdf/2302.07730"]}
-{"year":"2023","title":"Transformers in Healthcare: A Survey","authors":["S Nerella, S Bandyopadhyay, J Zhang, M Contreras… - arXiv preprint arXiv …, 2023"],"snippet":"With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications. Transformer is a type of deep learning …","url":["https://arxiv.org/pdf/2307.00067"]}
-{"year":"2023","title":"Translating Ancient Chinese to Modern Chinese at Scale: A Large Language Model-based Approach","authors":["J Cao, D Peng, Y Shi, Z Jiang, L Jin - These articles are licensed under a Creative …, 2023"],"snippet":"Recently, the emergence of large language models (LLMs) has provided powerful foundation models for a wide range of natural language processing (NLP) tasks. However, the vast majority of the pre-training corpus for most existing LLMs is in …","url":["https://files.sciconf.cn/upload/file/20230830/20230830181020_39986.pdf#page=71"]}
-{"year":"2023","title":"Trigger Warning Assignment as a Multi-Label Document Classification Problem","authors":["M Wiegmann, M Wolska, C Schröder, O Borchardt…"],"snippet":"A trigger warning is used to warn people about potentially disturbing content. We introduce trigger warning assignment as a multi-label classification task, create the Webis Trigger Warning Corpus 2022, and with it the first dataset of 1 million …","url":["https://webis.de/downloads/publications/papers/wiegmann_2023a.pdf"]}
-{"year":"2023","title":"Triple-Entry Accounting as a Means of Auditing Large Language Models","authors":["K Sgantzos, MA Hemairy, P Tzavaras, S Stelios - Journal of Risk and Financial …, 2023"],"snippet":"The usage of Large Language Models (LMMs) and their exponential progress has created a Cambrian Explosion in the development of new tools for almost every field of science and technology, but also presented significant concerns regarding the AI …","url":["https://www.mdpi.com/1911-8074/16/9/383/pdf"]}
-{"year":"2023","title":"Trustworthy Digital Repository Certification: A Longitudinal Study","authors":["DR Donaldson, SV Russell - Information for a Better World: Normality, Virtuality …, 2023"],"snippet":"Increasingly, government policies are directing federal agencies to make the results of federally funded scientific research publicly available in data repositories. Additionally, academic journal policies are progressively recommending that …","url":["https://link.springer.com/chapter/10.1007/978-3-031-28032-0_42"]}
-{"year":"2023","title":"Tryage: Real-time, intelligent Routing of User Prompts to Large Language Model","authors":["SN Hari, M Thomson - arXiv preprint arXiv:2308.11601, 2023"],"snippet":"… Language models are trained on data sampled from both generalized data sources like CommonCrawl as well as domain specific data (Pile sub-sets, financial data, clinical data), and also trained and fined tuned using different paradigms (Masked …","url":["https://arxiv.org/pdf/2308.11601"]}
-{"year":"2023","title":"Tsetlin Machine for Fake News Detection: Enhancing Accuracy and Reliability","authors":["BV Ledaal - 2023"],"snippet":"This thesis aims to improve the accuracy of fake news detection by using Tsetlin Machines (TM). TMs are well suited for noisy and complex relations within the provided data, which on initial analysis, overlaps nicely with characteristics found in …","url":["https://uia.brage.unit.no/uia-xmlui/bitstream/handle/11250/3080494/no.uia:inspera:145679742:6941642.pdf?sequence=1"]}
-{"year":"2023","title":"Tsinghua Issue-Generative AI, Learning And New Literacies","authors":["SY Chen - Journal of Educational Technology Development and …, 2023"],"snippet":"Launched in November 2022, OpenAI's ChatGPT garnered over 100 million users within two months, sparking a surge in research and concern over potential risks of extensive AI experiments. The article, originating from a conference presentation by …","url":["https://aquila.usm.edu/cgi/viewcontent.cgi?article=1205&context=jetde"]}
-{"year":"2023","title":"TTIC's Submission to WMT-SLT 23","authors":["M Sandoval-Castañeda, Y Li, B Shi, D Brentari… - Proceedings of the Eighth …, 2023"],"snippet":"… on the German Colossal Cleaned Common Crawl (GC4) corpus, which is a cleaned and pre-processed Germanonly corpus based on Common Crawl. We take pre-… This is a subset of Common Crawl where the primary language is German …","url":["http://www2.statmt.org/wmt23/pdf/2023.wmt-1.35.pdf"]}
-{"year":"2023","title":"TUDublin at CheckThat! 2023: ChatGPT for Data Augmentation","authors":["E Shushkevich, J Cardiff - 2023"],"snippet":"This work describes the approach of the TUDublin team at the CheckThat! 2023 Task 2: Subjectivity in News Articles. This task is aimed to discern whether a sentence in a news article conveys the subjective perspective of its author or …","url":["https://www.dei.unipd.it/~faggioli/temp/CLEF2023-proceedings/paper-041.pdf"]}
-{"year":"2023","title":"TunBERT: Pretraining BERT for Tunisian Dialect Understanding","authors":["H Haddad, AC Rouhou, A Messaoudi, A Korched… - SN Computer Science, 2023"],"snippet":"… We describe the process of creating a training dataset from collecting a Common-Crawl-based dataset, filtering and pre-processing the … Our models results indicate that a proportionately small sized Common-Crawl-based dataset (500K sentences, 67.2MB) …","url":["https://link.springer.com/article/10.1007/s42979-022-01541-y"]}
-{"year":"2023","title":"TurkishBERTweet: Fast and Reliable Large Language Model for Social Media Analysis","authors":["A Najafi, O Varol - arXiv preprint arXiv:2311.18063, 2023"],"snippet":"Turkish is one of the most popular languages in the world. Wide us of this language on social media platforms such as Twitter, Instagram, or Tiktok and strategic position of the country in the world politics makes it appealing for the social network …","url":["https://arxiv.org/pdf/2311.18063"]}
-{"year":"2023","title":"TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations at Twitter","authors":["X Zhang, Y Malkov, O Florez, S Park, B McWilliams… - Proceedings of the 29th …, 2023"],"snippet":"… It is trained on over two terabytes of CommonCrawl data. … pre-training objectives, the vast majority of the work has focused on text-only training objectives applied to general domain corpora, eg, Wikipedia and CommonCrawl. In this paper, we …","url":["https://dl.acm.org/doi/abs/10.1145/3580305.3599921"]}
-{"year":"2023","title":"TWIGMA: A dataset of AI-Generated Images with Metadata From Twitter","authors":["Y Chen, J Zou - arXiv preprint arXiv:2306.08310, 2023"],"snippet":"… ArtBench features 60,000 high-quality, genre-annotated images of artwork spanning ten different art genres from the 14th century to the 21st century; and LAION encompasses CLIP-similarity-filtered image-text pairs sourced from the Common Crawl. …","url":["https://arxiv.org/pdf/2306.08310"]}
-{"year":"2023","title":"Twitter Accounts Suggestion: Pipeline Technique SpaCy Entity Recognition","authors":["S Algamdi, A Albanyan, SK Shah, Z Tariq - … International Conference on Big Data (Big …, 2022"],"snippet":"Twitter Accounts Suggestion is concerned with recommending accounts for the users according to their tweet contents. Twitter contains a massive amount of data that can be useful for knowing each user’s preferences. This paper uses Named …","url":["https://ieeexplore.ieee.org/abstract/document/10020570/"]}
-{"year":"2023","title":"Two Neural Models for Multilingual Grammatical Error Detection","authors":["P Le-Hong, TMH Nguyen - Swedish Language Technology Conference and …, 2023"],"snippet":"This paper presents two neural models for multilingual grammatical error detection and their results in the MultiGED-2023 shared task. The first model uses a simple, purely supervised character-based approach. The second model uses a large …","url":["https://ecp.ep.liu.se/index.php/sltc/article/download/681/587"]}
-{"year":"2023","title":"Typhoon: Thai Large Language Models","authors":["K Pipatanakul, P Jirabovonvisut, P Manakul… - arXiv preprint arXiv …, 2023"],"snippet":"… of the Common Crawl data [13], making Thai the 26th rank in terms of size in Common Crawl. … the Oscar dataset extracted a single package of the Common Crawl (CC) data and MC4 only … (1) Scaling the Data: we initiate the process by …","url":["https://arxiv.org/pdf/2312.13951"]}
-{"year":"2023","title":"UBERT22: Unsupervised Pre-training of BERT for Low Resource Urdu Language","authors":["B Tahir, MA Mehmood - 2022 16th International Conference on Open Source …, 2022"],"snippet":"Natural Language Understanding (NLU) tools have enabled the development of sophisticated and powerful Natural Language Processing (NLP) models. However, this progress is limited to English and European languages and low resource …","url":["https://ieeexplore.ieee.org/abstract/document/10016821/"]}
-{"year":"2023","title":"UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis","authors":["D Hu, L Wei, Y Liu, W Zhou, S Hu - arXiv preprint arXiv:2306.01093, 2023"],"snippet":"… It is pre-trained on filtered CommonCrawl data containing 100 languages. We use xlm-roberta-base3 to initialize XLM-R. … It is trained on an aggregation of datasets from the BBC news website and Common Crawl. We use castorini/afriberta_large3 …","url":["https://arxiv.org/pdf/2306.01093"]}
-{"year":"2023","title":"UD-MULTIGENRE–a UD-Based Dataset Enriched with Instance-Level Genre Annotations","authors":["V Danilova, S Stymne - Proceedings of the 3rd Workshop on Multi-lingual …, 2023"],"snippet":"Prior research on the impact of genre on crosslingual dependency parsing has suggested that genre is an important signal. However, these studies suffer from a scarcity of reliable data for multiple genres and languages. While Universal …","url":["https://aclanthology.org/2023.mrl-1.19.pdf"]}
-{"year":"2023","title":"UHGEval: Benchmarking the Hallucination of Chinese Large Language Models via Unconstrained Generation","authors":["X Liang, S Song, S Niu, Z Li, F Xiong, B Tang, Z Wy… - arXiv preprint arXiv …, 2023"],"snippet":"… For example, the Chinese data incorporated in GPT’s training from the Common Crawl corpus comprises less than 5%4. Evaluations by Type. Given the categorization of news into four types, we can … 4https://commoncrawl.github.io/cc-crawl-statistics/plots/languages.html …","url":["https://arxiv.org/pdf/2311.15296"]}
-{"year":"2023","title":"UM6P at SemEval-2023 Task 3: News genre classification based on transformers, graph convolution networks and number of sentences","authors":["H Alami, A Benlahbib, A El Mahdaouy, I Berrada - Proceedings of the The 17th …, 2023"],"snippet":"This paper presents our proposed method for english documents genre classification in the context of SemEval 2023 task 3, subtask 1. Our method use ensemble technique to combine four distinct models predictions: Longformer …","url":["https://aclanthology.org/2023.semeval-1.118.pdf"]}
-{"year":"2023","title":"UMUTeam at SemEval-2023 Task 12: Ensemble Learning of LLMs applied to Sentiment Analysis for Low-resource African Languages","authors":["JA García-Díaz, C Caparros-Laiz, Á Almela… - Proceedings of the The 17th …, 2023"],"snippet":"These working notes summarize the participation of the UMUTeam in the SemEval 2023 shared task: AfriSenti, focused on Sentiment Analysis in several African languages. Two subtasks are proposed, one in which each language is considered …","url":["https://aclanthology.org/2023.semeval-1.38.pdf"]}
-{"year":"2023","title":"Uncovering and Categorizing Social Biases in Text-to-SQL","authors":["Y Liu, Y Gao, Z Su, X Chen, E Ash, JG Lou - arXiv preprint arXiv:2305.16253, 2023"],"snippet":"Content Warning: This work contains examples that potentially implicate stereotypes, associations, and other harms that could be offensive to individuals in certain social groups.} Large pre-trained language models are acknowledged to carry social …","url":["https://arxiv.org/pdf/2305.16253"]}
-{"year":"2023","title":"UNDERSTANDING AND MITIGATING THE LABEL NOISE IN PRE-TRAINING ON DOWNSTREAM TASKS","authors":["H Chen, J Wang, A Shah, R Tao, H Wei, X Xie… - arXiv preprint arXiv …, 2023"],"snippet":"Pre-training on large-scale datasets and then fine-tuning on downstream tasks have become a standard practice in deep learning. However, pre-training data often contain label noise that may adversely affect the generalization of the model. This …","url":["https://arxiv.org/pdf/2309.17002"]}
-{"year":"2023","title":"Understanding Catastrophic Forgetting in Language Models via Implicit Inference","authors":["S Kotha, JM Springer, A Raghunathan - arXiv preprint arXiv:2309.10105, 2023"],"snippet":"Fine-tuning (via methods such as instruction-tuning or reinforcement learning from human feedback) is a crucial step in training language models to robustly carry out tasks of interest. However, we lack a systematic understanding of the effects of fine-tuning …","url":["https://arxiv.org/pdf/2309.10105"]}
-{"year":"2023","title":"Understanding Finetuning for Factual Knowledge Extraction from Language Models","authors":["M Kazemi, S Mittal, D Ramachandran - arXiv preprint arXiv:2301.11293, 2023"],"snippet":"… Recently, Language Models (LMs) pre-trained on large corpora of web documents such as CommonCrawl1 have achieved impressive results on multiple NLP tasks. In their pioneering work, Petroni et al. (2019) showed that LMs also …","url":["https://arxiv.org/pdf/2301.11293"]}
-{"year":"2023","title":"Understanding Multilingual Language Models: Training, Representation and Architecture","authors":["V Ravishankar - 2023"],"snippet":"The field of natural language processing has seen numerous advancements since its inception during the Cold War, when attempts were made to automate translating Russian text to English. The 2010s have been a particularly fertile decade, going by …","url":["https://www.duo.uio.no/bitstream/handle/10852/102833/PhD-Ravishankar-2023.pdf?sequence=1"]}
-{"year":"2023","title":"Understanding the Effectiveness of Very Large Language Models on Dialog Evaluation","authors":["J Huynh, C Jiao, P Gupta, S Mehri, P Bajaj… - arXiv preprint arXiv …, 2023"],"snippet":"… TNLGv2 has not seen datasets explicitly categorized as having dialog, but elements of casual language may be included in the Common Crawl snapshots and other internet-based corpora. Symbols: means that the category is included and × …","url":["https://arxiv.org/pdf/2301.12004"]}
-{"year":"2023","title":"Understanding the Role of Human Intuition on Reliance in Human-AI Decision-Making with Explanations","authors":["V Chen, QV Liao, JW Vaughan, G Bansal - arXiv preprint arXiv:2301.07255, 2023"],"snippet":"… The AI system used in this task was trained on the BIOS dataset [23], which contains hundreds of thousands of online biographies from the CommonCrawl corpus. While the original dataset consisted individuals with 29 professions, we …","url":["https://arxiv.org/pdf/2301.07255"]}
-{"year":"2023","title":"Understanding Website Privacy Policies—A Longitudinal Analysis Using Natural Language Processing","authors":["V Belcheva, T Ermakova, B Fabian - Information, 2023"],"snippet":"Privacy policies are the main method for informing Internet users of how their data are collected and shared. This study aims to analyze the deficiencies of privacy policies in terms of readability, vague statements, and the use of pacifying phrases …","url":["https://www.mdpi.com/2078-2489/14/11/622"]}
-{"year":"2023","title":"UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning","authors":["A Masry, P Kavehzadeh, XL Do, E Hoque, S Joty - arXiv preprint arXiv:2305.14761, 2023"],"snippet":"Charts are very popular for analyzing data, visualizing key insights and answering complex reasoning questions about data. To facilitate chart-based data analysis using natural language, several downstream tasks have been introduced recently …","url":["https://arxiv.org/pdf/2305.14761"]}
-{"year":"2023","title":"UniDoc: A Universal Large Multimodal Model for Simultaneous Text Detection, Recognition, Spotting and Understanding","authors":["H Feng, Z Wang, J Tang, J Lu, W Zhou, H Li, C Huang - arXiv preprint arXiv …, 2023"],"snippet":"… The data were collected from the “Common Crawl” dataset, a vast web corpus containing publicly available web page. We opt for PowerPoint files based on two primary considerations. On one hand, PowerPoint presentations are characterized …","url":["https://arxiv.org/pdf/2308.11592"]}
-{"year":"2023","title":"Unifying Corroborative and Contributive Attributions in Large Language Models","authors":["T Worledge, JH Shen, N Meister, C Winston, C Guestrin - arXiv preprint arXiv …, 2023"],"snippet":"As businesses, products, and services spring up around large language models, the trustworthiness of these models hinges on the verifiability of their outputs. However, methods for explaining language model outputs largely fall across two distinct fields …","url":["https://arxiv.org/pdf/2311.12233"]}
-{"year":"2023","title":"UniManc at NADI 2023 Shared Task: A Comparison of Various T5-based Models for Translating Arabic Dialectical Text to Modern Standard Arabic","authors":["A Khered, I Abdelhalim, N Abdelhalim, A Soliman… - Proceedings of ArabicNLP …, 2023"],"snippet":"This paper presents the methods we developed for the Nuanced Arabic Dialect Identification (NADI) 2023 shared task, specifically targeting the two subtasks focussed on sentence-level machine translation (MT) of text written in any of four …","url":["https://aclanthology.org/2023.arabicnlp-1.71.pdf"]}
-{"year":"2023","title":"Universal Multimodal Representation for Language Understanding","authors":["Z Zhang, K Chen, R Wang, M Utiyama, E Sumita, Z Li… - IEEE Transactions on …, 2023"],"snippet":"Abstract Representation learning is the foundation of natural language processing (NLP). This work presents new methods to employ visual information as assistant signals to general NLP tasks. For each sentence, we first retrieve a flexible number of images …","url":["https://www.computer.org/csdl/journal/tp/5555/01/10005816/1JF3SmbCxbi"]}
-{"year":"2023","title":"University of Pennsylvania Working Paper s in Linguistic s","authors":["N Markl"],"snippet":"As speech datasets used in sociolinguistic research increase in size, laborious and time-intensive manual orthographic transcription is a challenge, limiting the amount of (transcribed) data which can be analysed. In this paper, I discuss the use of (commercial) …","url":["https://www.pure.ed.ac.uk/ws/files/345647217/Commercial_Automatic_MARKL_DOA05082022_VOR.pdf"]}
-{"year":"2023","title":"Unleashing the Power of Edge-Cloud Generative AI in Mobile Networks: A Survey of AIGC Services","authors":["M Xu, H Du, D Niyato, J Kang, Z Xiong, S Mao, Z Han… - arXiv preprint arXiv …, 2023"],"snippet":"Artificial Intelligence-Generated Content (AIGC) is an automated method for generating, manipulating, and modifying valuable and diverse data using AI algorithms creatively. This survey paper focuses on the deployment of AIGC …","url":["https://arxiv.org/pdf/2303.16129"]}
-{"year":"2023","title":"Unlocking Model Insights: A Dataset for Automated Model Card Generation","authors":["S Singh, H Lodwal, H Malwat, R Thakur, M Singh - arXiv preprint arXiv:2309.12616, 2023"],"snippet":"… LLaMa is trained on trillions of tokens, using publicly available datasets such as C4, CommonCrawl, Github, Wikipedia, Gutenberg and … , Wikipedia, StackExchange, scientific knowledge bases, scientific and academic Common Crawl …","url":["https://arxiv.org/pdf/2309.12616"]}
-{"year":"2023","title":"Unlocking the Potential of Electronic Health Records With Danish Clinical Language Models for Text Mining","authors":["JS Pedersen - 2023"],"snippet":"This PhD dissertation focuses on the development of language technology that can be used to extract clinical information from Danish electronic health records (EHRs). EHRs contain important health-related information that can be used to guide the …","url":["https://portal.findresearcher.sdu.dk/files/243589320/Reduced_Unlocking_the_Potential_of_Electronic_Health_Records_With_Danish_Clinical_Language_Models_for_Text_Mining.pdf"]}
-{"year":"2023","title":"Unmaking AI Imagemaking: A Methodological Toolkit for Critical Investigation","authors":["L Munn, L Magee, V Arora - arXiv preprint arXiv:2307.09753, 2023"],"snippet":"… To create the dataset, developers drew on Common Crawl, an immense repository of web pages scraped from the internet over twelve years which is now petabytes in size. Developers identified all the image tags in each webpage along …","url":["https://arxiv.org/pdf/2307.09753"]}
-{"year":"2023","title":"Unsupervised Anomaly Detection in Multi-Topic Short-Text Corpora","authors":["M Ait-Saada, M Nadif - Proceedings of the 17th Conference of the European …, 2023"],"snippet":"Unsupervised anomaly detection seeks to identify deviant data samples in a dataset without using labels and constitutes a challenging task, particularly when the majority class is heterogeneous. This paper addresses this topic for textual data and …","url":["https://aclanthology.org/2023.eacl-main.101.pdf"]}
-{"year":"2023","title":"Unsupervised ASR via Cross-Lingual Pseudo-Labeling","authors":["T Likhomanenko, L Lugosch, R Collobert - arXiv preprint arXiv:2305.13330, 2023","VIACL PSEUDO-LABELING"],"snippet":"… For African languages, we use Kinyarwanda only as a source language (as text data are not available in the Common Crawl dataset), and Swahili and Hausa only as target languages (as they are low resource). Finally, to compare with wav2vec-U …","url":["https://arxiv.org/pdf/2305.13330","https://openreview.net/pdf?id=4lOWCkhr4g"]}
-{"year":"2023","title":"Unsupervised Deep Representation Learning for Low-Resourced Languages and Applications","authors":["K Goswami"],"snippet":"Artificial intelligence and Natural Language Processing (NLP) are becoming integral parts of modern technologies and amenities starting from the adaptation of Amazon Alexa to automatic chatbots in different industries. Though earlier NLP algorithms …","url":["https://aran.library.nuigalway.ie/bitstream/handle/10379/17767/PhD_Writing_camera_ready.pdf?sequence=1"]}
-{"year":"2023","title":"Unsupervised Story Discovery from Continuous News Streams via Scalable Thematic Embedding","authors":["S Yoon, D Lee, Y Zhang, J Han - arXiv preprint arXiv:2304.04099, 2023"],"snippet":"… WCEP [11] is a benchmark news data set collected from Wikipedia Current Event Portal and the Common Crawl archive. We used articles in the stories of at least 50 articles and published in 2018 and 2019 (ie, WCEP18 and WCEP19). For a …","url":["https://arxiv.org/pdf/2304.04099"]}
-{"year":"2023","title":"Unsupervised Ultra-Fine Entity Typing with Distributionally Induced Word Senses","authors":["C Biemann"],"snippet":"The lack of annotated data is one of the challenging issues in an ultra-fine entity typing, which is the task to assign semantic types for a given entity mention. Hence, automatic type generation is receiving increased interest, typically to be used as …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2023-sevgilietal-ufet-aist.pdf"]}
-{"year":"2023","title":"Unveiling Multilinguality in Transformer Models: Exploring Language Specificity in Feed-Forward Networks","authors":["S Bhattacharya, O Bojar - arXiv preprint arXiv:2310.15552, 2023"],"snippet":"… The model description of the XGLM model states that the model was trained on CommonCrawl data of various languages. CzEng heavily relies on various freely accessible web sources and a part of the data included in CzEng is also drawn from …","url":["https://arxiv.org/pdf/2310.15552"]}
-{"year":"2023","title":"Unveiling the Black Box: Investigating the Interplay between AI Technologies, Explainability, and Legal Implications","authors":["C Erdoğanyılmaz, B Mengünoğul, M Balci - 2023 8th International Conference on …, 2023"],"snippet":"Discovering patterns is the process of understanding, while explainability refers to the ability to represent the discovered patterns in a way that the target audience can comprehend. If we adapt the relevant proposition to explainability in law, jurists …","url":["https://ieeexplore.ieee.org/abstract/document/10286653/"]}
-{"year":"2023","title":"Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment","authors":["F Xu, J Zhang, C Gao, J Feng, Y Li - arXiv preprint arXiv:2312.11813, 2023"],"snippet":"… As claimed in open source models [159, 139, 8], most of the training corpus are from the public web text like common crawl project and only limited common data processing methods are applied due to the high-cost of handling the large volume …","url":["https://arxiv.org/pdf/2312.11813"]}
-{"year":"2023","title":"Urdu paraphrase detection: A novel DNN-based implementation using a semi-automatically generated corpus","authors":["HR Iqbal, R Maqsood, AA Raza, SU Hassan - Natural Language Engineering, 2023"],"snippet":"Automatic paraphrase detection is the task of measuring the semantic overlap between two given texts. A major hurdle in the development and evaluation of paraphrase detection approaches, particularly for South Asian languages like Urdu …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/62AF020B1B9BD7DAAE4F7B6262E81CA6/S1351324923000189a.pdf/urdu_paraphrase_detection_a_novel_dnnbased_implementation_using_a_semiautomatically_generated_corpus.pdf"]}
-{"year":"2023","title":"Use of Large Language Model for Cyberbullying Detection","authors":["B Ogunleye, B Dharmaraj - 2023"],"snippet":"… It was trained on 100 languages from 2.5TB of filtered common crawl data. The \"RoBERTa\" part in XLM-RoBERTa originates from the fact that it uses the identical training procedures as the monolingual RoBERTa model, with the Masked Language Model …","url":["https://www.preprints.org/manuscript/202306.1075/download/final_file"]}
-{"year":"2023","title":"USE OF SCHEMA. ORG MICRO-MARKUP IN E-COMMERCE PROJECTS","authors":["O Belz - Three Seas Economic Journal, 2022"],"snippet":"… were removed (Common Crawl, 2022). Both scientists and practitioners are working with the obtained data sets of the Common Crawl project. … SOTAB is based on data from schema.org and Common Crawl. SOTAB has two annotation …","url":["http://baltijapublishing.lv/index.php/threeseas/article/download/1964/1973"]}
-{"year":"2023","title":"User-defined Content Detection Framework","authors":["K Kim, S Cho, Y Lee"],"snippet":"This paper presents UCDF, a simple interactive framework for training a classifier that can detect user-defined content. User-defined content signifies texts that a user wants to detect. UCDF receives examples of user-defined content as queries to …","url":["https://internlp.github.io/documents/2022/papers/8.pdf"]}
-{"year":"2023","title":"Using AI-based detectors to control AI-assisted plagiarism in ESL writing:“The Terminator Versus the Machines”","authors":["K Ibrahim - Language Testing in Asia, 2023"],"snippet":"The release of ChatGPT marked the beginning of a new era of AI-assisted plagiarism that disrupts traditional assessment practices in ESL composition. In the face of this challenge, educators are left with little guidance in controlling AI-assisted …","url":["https://languagetestingasia.springeropen.com/articles/10.1186/s40468-023-00260-2"]}
-{"year":"2023","title":"Using AI-generated suggestions from ChatGPT to optimize clinical decision support","authors":["S Liu, AP Wright, BL Patterson, JP Wanderer, RW Turer… - Journal of the American …, 2023"],"snippet":"Objective To determine if ChatGPT can generate useful suggestions for improving clinical decision support (CDS) logic and to assess noninferiority compared to human-generated suggestions. Methods We supplied summaries of CDS logic to …","url":["https://academic.oup.com/jamia/advance-article/doi/10.1093/jamia/ocad072/7136722"]}
-{"year":"2023","title":"Using artificial intelligence in day-to-day practice","authors":["M FRADKIN","M Fradkin - 2023"],"snippet":"… Most of the data used for ChatGPT’s dataset come from the Common Crawl, a collection of over 12 years of raw webpage data, metadata, and text extracts from websites starting in 2008. It does not have access to medical journal articles or raw …","url":["https://search.proquest.com/openview/800783b95fd58bb2f24f7bdfa01f9cb3/1?pq-origsite=gscholar&cbl=34319","https://www.contemporarypediatrics.com/view/using-artificial-intelligence-in-day-to-day-practice"]}
-{"year":"2023","title":"Using Automated Procedures to Score Written Essays in Persian: An Application of the Multilingual BERT System","authors":["T Firoozi - 2023"],"snippet":"The automated scoring of student essays is now recognized as a significant development in both the research and practice of educational testing. The majority of the published studies on automated essay scoring (AES) focus on outcomes in …","url":["https://era.library.ualberta.ca/items/4d29bb1c-7d95-49c7-885e-bc69d25cd951/download/46d81deb-d867-4828-88dd-d5a16eac2ef5"]}
-{"year":"2023","title":"USING CHATGPT TO INVESTIGATE TRENDS IN DIGITAL STORYTELLING AND KNOWLEDGE SHARING IN HIGHER EDUCATION","authors":["D Cranfield, I Venter, A Daniels - EDULEARN23 Proceedings, 2023"],"snippet":"Literature reviews are traditionally used by researchers to consider large bodies of knowledge within their field of research and to synthesize new knowledge. The principal objective of this research was to do a state-of-the-art review using ChatGPT …","url":["https://library.iated.org/view/CRANFIELD2023USI"]}
-{"year":"2023","title":"Using Domain-Specific Word Embeddings to Examine the Demand for Skills","authors":["S Chaturvedi, K Mahajan, Z Siddique - 2023"],"snippet":"… We examine and compare domain-specific word embeddings with word embeddings trained on Common Crawl on … Common Crawl on the web and Wikipedia demonstrates the benefits of using the former.As opposed to pre-trained …","url":["https://docs.iza.org/dp16593.pdf"]}
-{"year":"2023","title":"Using Language Models to Detect Alarming Student Responses","authors":["CM Ormerod, M Patel, H Wang - arXiv preprint arXiv:2305.07709, 2023"],"snippet":"This article details the advances made to a system that uses artificial intelligence to identify alarming student responses. This system is built into our assessment platform to assess whether a student's response indicates they are a threat to …","url":["https://arxiv.org/pdf/2305.07709"]}
-{"year":"2023","title":"Using Large Pre-Trained Language Model to Assist FDA in Premarket Medical Device Classification","authors":["Z Xu - SoutheastCon 2023, 2023"],"snippet":"… This paper selects the FastText embeddings with subword information pre-trained on Common Crawl which has a dimension of 300. When constructing the embeddings for the device descriptions, pre-trained embeddings are found for each …","url":["https://ieeexplore.ieee.org/abstract/document/10115070/"]}
-{"year":"2023","title":"Using machine learning to extract information and predict outcomes from reports of randomised trials of smoking cessation interventions in the Human Behaviour …","authors":["R West, F Bonin, J Thomas, AJ Wright… - 2023"],"snippet":"… The vectors are generated based on the cooccurrence statistics of words in a large corpus of text, such as Wikipedia or Common Crawl. The algorithm is trained to learn a weighted average of the co-occurrence probabilities between words …","url":["https://psyarxiv.com/wzn2b/download"]}
-{"year":"2023","title":"Using the web to explain claims","authors":["N Bremen - 2023"],"snippet":"An important part of human interaction is argumentation. Arguments can be found anywhere and have been studied in various disciplines, going all the way back to ancient times. With the rise of the world wide web, and more specifically the social …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/43676/2023-02-13%20Thesis%20Nick%20van%20Bremen.pdf?sequence=1"]}
-{"year":"2023","title":"Using Transformers to Extract Date Expressions From Receipts","authors":["A Leander"],"snippet":"The extraction of date expressions in documents is a time-consuming task if done manually. For computers, automating this process can be achieved through various methods. In this thesis, I compare a regular expression system that extracts date …","url":["https://lup.lub.lu.se/student-papers/record/9138650/file/9138651.pdf"]}
-{"year":"2023","title":"Using Vector Embeddings and Feature Vectors to Humor Identification","authors":["MC Aguirre-Delgado, AE Cadena-Bautista - 2023"],"snippet":"Expressing prejudice is the most common strategy to harm minority groups. Prejudice is defined as\" the formation of a negative concept or judgment in advance about members of a race, religion, or any other significant social group, despite facts …","url":["https://ceur-ws.org/Vol-3496/huhu-paper7.pdf"]}
-{"year":"2023","title":"Using word embeddings to investigate human psychology: Methods and applications","authors":["HWS BAO, ZX WANG, X CHENG, Z SU, Y YANG… - Advances in Psychological …"],"snippet":"… 词向量通常是根据大 规模文本语料训练的(比如 Common Crawl 语料库 覆盖了多种 来源,万亿级规模的网页链接), 分析 结果更能代表人群总体.而传统方法中, 样本量 一般 比较有限, 且以学生样本居多, 只有经过严 格,系统的抽样才能保证样本代表性. 第三 …","url":["https://journal.psych.ac.cn/xlkxjz/EN/article/downloadArticleFile.do?attachType=PDF&id=6610"]}
-{"year":"2023","title":"UT5: Pretraining Non autoregressive T5 with unrolled denoising","authors":["MG Salem, J Ye, CC Lin, F Liu - arXiv preprint arXiv:2311.08552, 2023"],"snippet":"… For our pretraining experiments, we use the C4 dataset, which is a large-scale web document corpus created by scraping the Common Crawl data. The C4 dataset contains over 750GB of text data and includes a diverse range of topics, such as …","url":["https://arxiv.org/pdf/2311.08552"]}
-{"year":"2023","title":"Vacaspati: A Diverse Corpus of Bangla Literature","authors":["P Bhattacharyya, J Mondal, S Maji, A Bhattacharya - arXiv preprint arXiv:2307.05083, 2023"],"snippet":"Bangla (or Bengali) is the fifth most spoken language globally; yet, the state-of-the-art NLP in Bangla is lagging for even simple tasks such as lemmatization, POS tagging, etc. This is partly due to lack of a varied quality corpus. To alleviate this need, we …","url":["https://arxiv.org/pdf/2307.05083"]}
-{"year":"2023","title":"Valence without meaning: investigating form and semantic components in pseudowords valence","authors":["D Gatti, L Raveling, A Petrenco, F Günther - 2023"],"snippet":"Valence is a dominant semantic dimension, and it is fundamentally linked to basic approach-avoidance behavior within a broad range of contexts. Previous studies have shown that it is possible to approximate the valence of existing words based on …","url":["https://psyarxiv.com/sfzgr/download?format=pdf"]}
-{"year":"2023","title":"Variational Imbalanced Regression: Fair Uncertainty Quantification via Probabilistic Smoothing","authors":["Z Wang, H Wang"],"snippet":"Existing regression models tend to fall short in both accuracy and uncertainty estimation when the label distribution is imbalanced. In this paper, we propose a probabilistic deep learning model, dubbed variational imbalanced regression (VIR) …","url":["http://www.wanghao.in/paper/NIPS23_VIR.pdf"]}
-{"year":"2023","title":"Vashantor: A Large-scale Multilingual Benchmark Dataset for Automated Translation of Bangla Regional Dialects to Bangla Language","authors":["FTJ Faria, MB Moin, AA Wase, M Ahmmed, MR Sani… - arXiv preprint arXiv …, 2023"],"snippet":"The Bangla linguistic variety is a fascinating mix of regional dialects that adds to the cultural diversity of the Bangla-speaking community. Despite extensive study into translating Bangla to English, English to Bangla, and Banglish to Bangla in the past …","url":["https://arxiv.org/pdf/2311.11142"]}
-{"year":"2023","title":"Vax-Culture: A Dataset for Studying Vaccine Discourse on Twitter","authors":["MR Zarei, M Christensen, S Everts, M Komeili - arXiv preprint arXiv:2304.06858, 2023"],"snippet":"Vaccine hesitancy continues to be a main challenge for public health officials during the COVID-19 pandemic. As this hesitancy undermines vaccine campaigns, many researchers have sought to identify its root causes, finding that the increasing …","url":["https://arxiv.org/pdf/2304.06858"]}
-{"year":"2023","title":"VECO 2.0: Cross-lingual Language Model Pre-training with Multi-granularity Contrastive Learning","authors":["ZR Zhang, C Tan, S Huang, F Huang - arXiv preprint arXiv:2304.08205, 2023"],"snippet":"Recent studies have demonstrated the potential of cross-lingual transferability by training a unified Transformer encoder for multiple languages. In addition to involving the masked language model objective, existing cross-lingual pre-training …","url":["https://arxiv.org/pdf/2304.08205"]}
-{"year":"2023","title":"Vega-mt: The jd explore academy machine translation system for wmt22","authors":["C Zan, K Peng, L Ding, B Qiu, B Liu, S He, Q Lu… - Proceedings of the Seventh …, 2022"],"snippet":"We describe the JD Explore Academy’s submission of the WMT 2022 shared general translation task. We participated in all high-resource tracks and one medium-resource track, including Chinese-English, German-English, Czech-English, Russian-English …","url":["https://aclanthology.org/2022.wmt-1.37.pdf"]}
-{"year":"2023","title":"Verbalising Query Results to Text","authors":["MS Xydas - 2023"],"snippet":"… C4 is a colossal, cleaned version of Common Crawl’s web crawl corpus. It was based on Common Crawl dataset which consists of all the websites on the internet. In our case, C4 has a regulatory effect on our pretraining process and we use a …","url":["https://pergamos.lib.uoa.gr/uoa/dl/object/3336431/file.pdf"]}
-{"year":"2023","title":"ViCGCN: Graph Convolutional Network with Contextualized Language Models for Social Media Mining in Vietnamese","authors":["CT Phan, QN Nguyen, CT Dang, TH Do, K Van Nguyen - arXiv preprint arXiv …, 2023"],"snippet":"… XLM-R particularly impressive is the extensive and careful curation of over 2.5TB of data from CommonCrawl. Among its notable contributions are the improvements made for low-resource languages through specialized training and vocabulary …","url":["https://arxiv.org/pdf/2309.02902"]}
-{"year":"2023","title":"Video question answering supported by a multi-task learning objective","authors":["A Falcon, G Serra, O Lanz - Multimedia Tools and Applications, 2023"],"snippet":"… By using GloVe, pretrained on the Common Crawl dataset , a vector of size E = 300 is computed for each word in both question and answer. Since GloVe is not contextual, question and answer can be given in input to it either jointly or separately …","url":["https://link.springer.com/article/10.1007/s11042-023-14333-0"]}
-{"year":"2023","title":"VideoCon: Robust Video-Language Alignment via Contrast Captions","authors":["H Bansal, Y Bitton, I Szpektor, KW Chang, A Grover - arXiv preprint arXiv:2311.10111, 2023"],"snippet":"Despite being (pre)trained on a massive amount of data, state-of-the-art video-language alignment models are not robust to semantically-plausible contrastive changes in the video captions. Our work addresses this by identifying a broad spectrum of …","url":["https://arxiv.org/pdf/2311.10111"]}
-{"year":"2023","title":"Vision-Aware Language Reasoning for Referring Image Segmentation","authors":["F Xu, B Luo, C Zhang, L Xu, M Pu, B Li - Neural Processing Letters, 2023"],"snippet":"… Like [20, 28], we use the Glove word embedding [48] pretrained on Common Crawl 840B tokens as the language initial encoding. We default the length of expressions to 20 on all datasets and perform language feature extraction …","url":["https://link.springer.com/article/10.1007/s11063-023-11377-z"]}
-{"year":"2023","title":"Vision-Language Models for Vision Tasks: A Survey","authors":["J Zhang, J Huang, S Jin, S Lu - arXiv preprint arXiv:2304.00685, 2023"],"snippet":"Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, leading to a laborious and time-consuming visual recognition …","url":["https://arxiv.org/pdf/2304.00685"]}
-{"year":"2023","title":"ViSoBERT: A Pre-Trained Language Model for Vietnamese Social Media Text Processing","authors":["QN Nguyen, TC Phan, DV Nguyen, K Van Nguyen - arXiv preprint arXiv:2310.11166, 2023"],"snippet":"English and Chinese, known as resource-rich languages, have witnessed the strong development of transformer-based language models for natural language processing tasks. Although Vietnam has approximately 100M people speaking …","url":["https://arxiv.org/pdf/2310.11166"]}
-{"year":"2023","title":"Visual experience modulates the sensitivity to the distributional history of words in natural language","authors":["G Anceresi, D Gatti, M Marelli, T Vecchi, L Rinaldi - 2023"],"snippet":"Different experiential traces (ie, linguistic, motor and perceptual) are likely contributing to the organization of human semantic knowledge. Here, we aimed to address this issue by investigating whether visual experience may affect the …","url":["https://psyarxiv.com/jqa9k/download?format=pdf"]}
-{"year":"2023","title":"Visual Question Answering: A Survey on Techniques and Common Trends in Recent Literature","authors":["ACAM de Faria, FC Bastos, JVNA da Silva, VL Fabris… - arXiv preprint arXiv …, 2023","CFG dos Sants, F de Castro Bastos, ACAM de Faria… - 2023"],"snippet":"… More technically, this new architecture has a language model based on Text-toText transformer and uses the base of T5 [78] because of its extensive pre-training data using Common Crawl, that is 750GB of cleaned English text data. To complement, a …","url":["https://arxiv.org/pdf/2305.11033","https://www.researchsquare.com/article/rs-3015858/latest.pdf"]}
-{"year":"2023","title":"Visual-Semantic Learning","authors":["C Yin - 2023"],"snippet":"… of 15 words, while the questions with length smaller than 15 were padded with zeros to the length of 15 (10 for the MSVD-QA dataset), and each word in the questions was represented as a 300D vectors using the GloVe word embedding [214] …","url":["https://search.proquest.com/openview/f5cf7cabc3e1cbcb0a2fece160ce1319/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2023","title":"Visualisation and Classification of Phishing URL using Ensemble Learning Algorithms and Hyper-Parameter Tuning","authors":["G Agarwal, C Goel, K Jindal, T Subbulakshmi - 2023 Third International Conference …, 2023"],"snippet":"… Alexa and Common Crawl were used to gather legitimate URLs. Lexical features, host-based features, and correlated feature groups are the three categories used to classify the features. Lexical features are textual aspects of the URL rather than the …","url":["https://ieeexplore.ieee.org/abstract/document/10176642/"]}
-{"year":"2023","title":"Vocabulary-free Image Classification","authors":["A Conti, E Fini, M Mancini, P Rota, Y Wang, E Ricci - arXiv preprint arXiv:2306.00917, 2023"],"snippet":"Recent advances in large vision-language models have revolutionized the image classification paradigm. Despite showing impressive zero-shot capabilities, a pre-defined set of categories, aka the vocabulary, is assumed at test time for composing the …","url":["https://arxiv.org/pdf/2306.00917"]}
-{"year":"2023","title":"WADER at SemEval-2023 Task 9: A Weak-labelling framework for Data augmentation in tExt Regression Tasks","authors":["M Suri, A Garg, D Chaudhary, I Gorton, B Kumar - arXiv preprint arXiv:2303.02758, 2023"],"snippet":"… This model is pre-trained on a massive dataset of 2.5 terabytes of CommonCrawl data filtered for 100 different languages. By training on such a large and diverse dataset, XLM-RoBERTa is able to capture the linguistic nuances and patterns that …","url":["https://arxiv.org/pdf/2303.02758"]}
-{"year":"2023","title":"WanJuan: A Comprehensive Multimodal Dataset for Advancing English and Chinese Large Models","authors":["C He, Z Jin, C Xu, J Qiu, B Wang, W Li, H Yan… - arXiv preprint arXiv …, 2023"],"snippet":"The rise in popularity of ChatGPT and GPT-4 has significantly accelerated the development of large models, leading to the creation of numerous impressive large language models(LLMs) and multimodal large language models (MLLMs). These …","url":["https://arxiv.org/pdf/2308.10755"]}
-{"year":"2023","title":"WDC Products: A Multi-Dimensional Entity Matching Benchmark","authors":["R Peeters, RC Der, C Bizer - arXiv preprint arXiv:2301.09521, 2023"],"snippet":"… The first step of the pipeline is the extraction of large amounts of product offers from the Common Crawl4 using schema.org annotations. Some product offers contain product identifiers like MPNs and GTINs which allow us to group offers into …","url":["https://arxiv.org/pdf/2301.09521"]}
-{"year":"2023","title":"Weak supervision and label noise handling for Natural language processing in low-resource scenarios","authors":["MA Hedderich - 2022"],"snippet":"The lack of large amounts of labeled data is a significant factor blocking many low-resource languages and domains from catching up with recent advancements in natural language processing. To reduce this dependency on labeled instances, weak …","url":["https://publikationen.sulb.uni-saarland.de/bitstream/20.500.11880/35026/1/MHedderich_Thesis_23-01-11.pdf"]}
-{"year":"2023","title":"Web content classification analysis","authors":["TX Nissopoulou - 2023"],"snippet":"This dissertation was written as a part of the MSc in Data Science at the International Hellenic University. Web analytics is a way for companies to learn more about the people who visit their websites. This information may include things like how people …","url":["https://repository.ihu.edu.gr/xmlui/bitstream/handle/11544/30145/thesis.pdf?sequence=1"]}
-{"year":"2023","title":"Web Page Prediction Model using Machine Learning Approaches: A Review","authors":["PA Omosebi, AP Adewole, O Sennaike - … on Science, Engineering and Business for …, 2023"],"snippet":"Webpage classification and prefetching are essential techniques to reduce internet access latency. However, insufficient server resources and network bandwidth can lead to inefficient usage when the majority of the prefetched web pages are not …","url":["https://ieeexplore.ieee.org/abstract/document/10124586/"]}
-{"year":"2023","title":"Web Readability Challenges","authors":["E Elahi, AMI Maqueda, JLM Lara - Proceedings of the Computational Methods in …, 2023"],"snippet":"… The datasets called Common Crawl comprised more than sixty million domain names, seven million Word documents, and more than ninety million PDF documents. Around sixty percent of the information is created from the organization, commercial …","url":["https://link.springer.com/chapter/10.1007/978-3-031-21438-7_35"]}
-{"year":"2023","title":"Web Structure Mining and Social Network Analysis","authors":["C Bizer"],"snippet":"… Covers 3.5 billion web pages and 128 billion hyperlinks, extracted from Common Crawl 2012 …","url":["https://www.uni-mannheim.de/media/Einrichtungen/dws/Files_Teaching/Web_Mining/FSS2023/WM02-WebStructureMining-Part1-FSS2023.pdf"]}
-{"year":"2023","title":"WebCPM: Interactive Web Search for Chinese Long-form Question Answering","authors":["Y Qin, Z Cai, D Jin, L Yan, S Liang, K Zhu, Y Lin, X Han… - arXiv preprint arXiv …, 2023"],"snippet":"… 2021) covers 101 languages collected from the public Common Crawl web scrape. mT5 achieves superior performance in various … Mengzi-T5 was trained on Chinese Wikipedia, Chinese News, and Common Crawl and the total size of the pre-training …","url":["https://arxiv.org/pdf/2305.06849"]}
-{"year":"2023","title":"WEBIE: Faithful and Robust Information Extraction on the Web","authors":["C Whitehouse, C Vania, AF Aji, C Christodoulopoulos…"],"snippet":"… We present WEBIE, the first large-scale, entity-linked closed IE dataset consisting of 1.6M sentences automatically collected from the English Common Crawl corpus. WEBIE also includes negative examples, ie sentences without fact triples, to better …","url":["https://christos-c.com/papers/whitehouse_23_webie.pdf"]}
-{"year":"2023","title":"wGMU: A Novel Fusion Strategy to Identify the Important Parts of Sentence for Relation Classification","authors":["D Escobar-Grisales, SA Moreno-Acevedo… - Workshop on Engineering …, 2023"],"snippet":"… This model was pre-trained with 2.5 TB of text data from the Common Crawl corpus [17], which includes text in 100 different languages. This extensive pre-training has allowed RoBERTa to compute text representations in multiple languages …","url":["https://link.springer.com/chapter/10.1007/978-3-031-46739-4_16"]}
-{"year":"2023","title":"What can we learn from Data Leakage and Unlearning for Law?","authors":["J Borkar - arXiv preprint arXiv:2307.10476, 2023"],"snippet":"… the model with the start-of-the-sequence token (2) Prompting the model with random ten tokens from the Common Crawl3 for each … 5since we use tokens from common crawl for prompts we assume that the attacker has access to a dataset with …","url":["https://arxiv.org/pdf/2307.10476"]}
-{"year":"2023","title":"What ChatGPT Tells Us about Gender: A Cautionary Tale about Performativity and Gender Biases in AI","authors":["N Gross - Social Sciences, 2023"],"snippet":"Large language models and generative AI, such as ChatGPT, have gained influence over people’s personal lives and work since their launch, and are expected to scale even further. While the promises of generative artificial intelligence are compelling …","url":["https://www.mdpi.com/2076-0760/12/8/435"]}
-{"year":"2023","title":"What comes next?: Investigating the neural correlates of predictability during conversation with fMRI","authors":["J Sundström - 2023"],"snippet":"The notion that prediction plays a role in language processing is getting less controversial, however research and discussion is ongoing as to the nature and extent of its involvement. Previous studies have mainly focused on prediction during …","url":["https://www.diva-portal.org/smash/get/diva2:1768530/FULLTEXT01.pdf"]}
-{"year":"2023","title":"What do text-to-image models know about the languages of the world?","authors":["V Firsanova - Записки научных семинаров ПОМИ, 2023"],"snippet":"… Another way is to use statistics of a large multilingual dataset such as Common Crawl [6]. We could try using statistics of the most spoken languages in the world [13]. But it would not be representative for our purposes because widespread spoken …","url":["https://www.mathnet.ru/rus/znsl7425"]}
-{"year":"2023","title":"What is (and was) a person? Evidence on historical mind perceptions from natural language","authors":["E Ash, D Stammbach, K Tobia - Cognition, 2023"],"snippet":"… Embeddings trained on a broader, less-well-curated corpus (Common Crawl) get worse performance in the human validation. Performance with our newly trained embeddings using recent decades of the Corpus of Historical American English (Davies …","url":["https://www.sciencedirect.com/science/article/pii/S001002772300135X"]}
-{"year":"2023","title":"What is a Fair Diffusion Model? Designing Generative Text-To-Image Models to Incorporate Various Worldviews","authors":["Z De Simone, A Boggust, A Satyanarayan, A Wilson - arXiv preprint arXiv:2309.09944, 2023"],"snippet":"… For example, Stable Diffusion [37] is trained on the image-text pairs from LAION-5B [41], a dataset synthesized from a repository of webcrawled data (Common Crawl [17]) and filtered using a CLIP [35] image classification model. This data represents a …","url":["https://arxiv.org/pdf/2309.09944"]}
-{"year":"2023","title":"What Makes ImageNet Look Unlike LAION","authors":["A Shirali, M Hardt - arXiv preprint arXiv:2306.15769, 2023"],"snippet":"ImageNet was famously created from Flickr image search results. What if we recreated ImageNet instead by searching the massive LAION dataset based on image captions alone? In this work, we carry out this counterfactual investigation …","url":["https://arxiv.org/pdf/2306.15769"]}
-{"year":"2023","title":"What Makes LLMs Large?","authors":["T Amaratunga - … Large Language Models: Learning Their Underlying …, 2023"],"snippet":"By now you should have a high-level understanding of the concepts of natural language processing and how the transformer architecture and attention mechanisms revolutionized the NLP field and how it changed the way we look at …","url":["https://link.springer.com/chapter/10.1007/979-8-8688-0017-7_4"]}
-{"year":"2023","title":"WHAT MAKES PRE-TRAINED VISUAL REPRESENTATIONS SUCCESSFUL FOR ROBUST MANIPULATION?","authors":["K Burns, Z Witzel, JI Hamid, T Yu, C Finn, K Hausman"],"snippet":"Inspired by the success of transfer learning in computer vision, roboticists have investigated visual pre-training as a means to improve the learning efficiency and generalization ability of policies learned from pixels. To that end, past work has …","url":["https://kayburns.github.io/segmentingfeatures/static/segmentingfeatures_paper.pdf"]}
-{"year":"2023","title":"What Works When in Context-aware Neural Machine Translation?","authors":["H Gete, T Etchegoyhen, G Labaka - Proceedings of the 24th Annual Conference of …, 2023"],"snippet":"Document-level Machine Translation has emerged as a promising means to enhance automated translation quality, but it is currently unclear how effectively context-aware models use the available context during translation. This paper aims …","url":["https://aclanthology.org/2023.eamt-1.15.pdf"]}
-{"year":"2023","title":"What's in a Name? Evaluating Assembly-Part Semantic Knowledge in Language Models through User-Provided Names in CAD Files","authors":["P Meltzer, JG Lambourne, D Grandi - arXiv preprint arXiv:2304.14275, 2023"],"snippet":"Semantic knowledge of part-part and part-whole relationships in assemblies is useful for a variety of tasks from searching design repositories to the construction of engineering knowledge bases. In this work we propose that the natural language …","url":["https://arxiv.org/pdf/2304.14275"]}
-{"year":"2023","title":"What's in a Name? Evaluating Assembly-Part Semantic Knowledge in Language Models Through User-Provided Names in Computer Aided Design Files","authors":["P Meltzer, JG Lambourne, D Grandi - Journal of Computing and Information Science …, 2024"],"snippet":"Semantic knowledge of part-part and part-whole relationships in assemblies is useful for a variety of tasks from searching design repositories to the construction of engineering knowledge bases. In this work, we propose that the natural language …","url":["https://asmedigitalcollection.asme.org/computingengineering/article/24/1/011002/1163204"]}
-{"year":"2023","title":"What's In My Big Data?","authors":["Y Elazar, A Bhagia, I Magnusson, A Ravichander… - arXiv preprint arXiv …, 2023"],"snippet":"… The dataset: The Colossal Clean Crawled Corpus (C4 in short) is based on Common Crawl as a source of text that was scraped from the … We use the latest version (v.3.1.0) which was used to train umT5, containing documents collected from …","url":["https://arxiv.org/pdf/2310.20707"]}
-{"year":"2023","title":"What's in the News? Towards Identification of Bias by Commission, Omission, and Source Selection (COSS)","authors":["A Zhukova, TL Ruas, F Hamborg, K Donnay, B Gipp - 2023"],"snippet":"In a world overwhelmed with news, determining which information comes from reliable sources or how neutral is the reported information in the news articles poses a challenge to news readers. In this paper, we propose a methodology for …","url":["https://www.gipp.com/wp-content/papercite-data/pdf/zhukova2023.pdf"]}
-{"year":"2023","title":"When AI Moves Downstream","authors":["F Grodzinsky, K Miller, M Wolf - International Conference on Computer Ethics, 2023"],"snippet":"… The training set for GPT-3 filtered a version of Common Crawl used to develop GPT-2. These were deliberate developer choices. In … Developers should be aware of the harm that uncurated and unanalyzed large data sets gathered from web …","url":["http://journals.library.iit.edu/index.php/CEPE2023/article/download/245/250"]}
-{"year":"2023","title":"When Automated Assessment Meets Automated Content Generation: Examining Text Quality in the Era of GPTs","authors":["M Bevilacqua, K Oketch, R Qin, W Stamey, X Zhang… - arXiv preprint arXiv …, 2023"],"snippet":"… RoBERTa also uses BookCorpus and Wikipedia, but in addition to common crawl news (CC-News), open web text, and stories, resulting in over 30 million tokens used for pre-training [50]. Both BERT and RoBERTa have performed well on text …","url":["https://arxiv.org/pdf/2309.14488"]}
-{"year":"2023","title":"When Giant Language Brains Just Aren't Enough! Domain Pizzazz with Knowledge Sparkle Dust","authors":["MT Nguyen, DH Nguyen, S Sabahi, H Le, J Yang… - arXiv preprint arXiv …, 2023"],"snippet":"Large language models (LLMs) have significantly advanced the field of natural language processing, with GPT models at the forefront. While their remarkable performance spans a range of tasks, adapting LLMs for real-world business …","url":["https://arxiv.org/pdf/2305.07230"]}
-{"year":"2023","title":"When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities","authors":["J Chen, Z Liu, X Huang, C Wu, Q Liu, G Jiang, Y Pu… - arXiv preprint arXiv …, 2023"],"snippet":"… For another thing, the pre-training is conducted based on much more unsupervised corpora, with hundreds of billions or trillions of tokens carefully filtered from sources like Common Crawl, GitHub, Wikipedia, Books, ArXiv, etc. The impact …","url":["https://arxiv.org/pdf/2307.16376"]}
-{"year":"2023","title":"When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale","authors":["M Marion, A Üstün, L Pozzobon, A Wang, M Fadaee… - arXiv preprint arXiv …, 2023"],"snippet":"… test set from the same CommonCrawl snapshot with identical … CommonCrawl A reference model trained on Wikipedia (an example of a clean noise-free corpus) achieves consistently lower validation perplexity compared to a reference model …","url":["https://arxiv.org/pdf/2309.04564"]}
-{"year":"2023","title":"When to Show a Suggestion? Integrating Human Feedback in AI-Assisted Programming","authors":["H Mozannar, G Bansal, A Fourney, E Horvitz - arXiv preprint arXiv:2306.04930, 2023"],"snippet":"AI powered code-recommendation systems, such as Copilot and CodeWhisperer, provide code suggestions inside a programmer's environment (eg, an IDE) with the aim to improve their productivity. Since, in these scenarios, programmers accept and …","url":["https://arxiv.org/pdf/2306.04930"]}
-{"year":"2023","title":"Where Did the News Come From? Detection of News Agency Releases in Historical Newspapers","authors":["L Marxen - 2023"],"snippet":"Since their beginnings in the 1830s and 1840s, news agencies have played an important role in the national and international news market, aiming to deliver news as fast and as reliable as possible. While we know that newspapers have been …","url":["https://infoscience.epfl.ch/record/305129/files/Marxen_Master_Thesis_2023_08_18.pdf"]}
-{"year":"2023","title":"Where's the Liability in Harmful AI Speech?","authors":["P Henderson, T Hashimoto, M Lemley - arXiv preprint arXiv:2308.04635, 2023"],"snippet":"… The underlying datasets can range from crawls of the web (eg, CommonCrawl) to court opinions from CourtListener and even to books downloaded from BitTorrent trackers.This input data may be lightly filtered for hate speech and private information …","url":["https://arxiv.org/pdf/2308.04635"]}
-{"year":"2023","title":"Who can verify this? Finding authorities for rumor verification in Twitter","authors":["F Haouari, T Elsayed, W Mansour - Information Processing & Management, 2023"],"snippet":"A large body of research work has proposed verification techniques for rumors spreading in social media that mainly relied on subjective evidence, eg, propagation networks or user interactions. Alternatively, in this work, we introduce the task of …","url":["https://www.sciencedirect.com/science/article/pii/S0306457323001036"]}
-{"year":"2023","title":"Who Killed the Winograd Schema Challenge?","authors":["H Neri, FG Cozman - Brazilian Conference on Intelligent Systems, 2023"],"snippet":"In which we investigate the technical issues surrounding the defeat, or perhaps the sudden assassination, of the Winograd Schema Challenge. We argue that, while the obvious suspect is the WinoGrande-based solution, the real cause of death was the …","url":["https://link.springer.com/chapter/10.1007/978-3-031-45392-2_14"]}
-{"year":"2023","title":"Why do Words with Negative Connotations Still Exist? A Corpus-Based Analysis of the Words 'Handicapped','Diffable', and 'Disability'","authors":["Y Yolanda, B Setyono - 2023"],"snippet":"This corpus-based study examines the persistence of negatively connoted words in the Indonesian, particularly focusing on cacat (handicapped). Cacat is compared to its synonyms, namely difabel (difable) and disabilitas (disability). The study employs …","url":["https://rupkatha.com/V15/n4/v15n415.pdf"]}
-{"year":"2023","title":"Why You Should Give Your Students Automatic Process Feedback on Their Collaboration: Evidence from a Randomized Experiment","authors":["L Menzel, S Gombert, J Weidlich, A Fink, A Frey… - European Conference on …, 2023"],"snippet":"In Computer-Supported Collaborative Learning (CSCL), students learn in small groups to achieve learning benefits outside what would be possible for individual students. As in other forms of learning, students need feedback on the quality of their …","url":["https://link.springer.com/chapter/10.1007/978-3-031-42682-7_14"]}
-{"year":"2023","title":"WiCE: Real-World Entailment for Claims in Wikipedia","authors":["R Kamoi, T Goyal, JD Rodriguez, G Durrett - arXiv preprint arXiv:2303.01432, 2023"],"snippet":"… For each claim c, we re-retrieve the cited web articles from Common Crawl.We automatically parse the cited articles’ (note that there might be more than one cited article) HTML to extract the article text. This process is often quite noisy and may …","url":["https://arxiv.org/pdf/2303.01432"]}
-{"year":"2023","title":"Witscript 3: A Hybrid AI System for Improvising Jokes in a Conversation","authors":["J Toplyn - arXiv preprint arXiv:2301.02695, 2023"],"snippet":"Previous papers presented Witscript and Witscript 2, AI systems for improvising jokes in a conversation. Witscript generates jokes that rely on wordplay, whereas the jokes generated by Witscript 2 rely on common sense. This paper extends that …","url":["https://arxiv.org/pdf/2301.02695"]}
-{"year":"2023","title":"WizardLM: Empowering Large Language Models to Follow Complex Instructions","authors":["C Xu, Q Sun, K Zheng, X Geng, P Zhao, J Feng, C Tao… - arXiv preprint arXiv …, 2023"],"snippet":"Training large language models (LLM) with open-domain instruction following data brings colossal success. However, manually creating such instruction data is very time-consuming and labor-intensive. Moreover, humans may struggle to produce …","url":["https://arxiv.org/pdf/2304.12244"]}
-{"year":"2023","title":"Word Embedding for Bengali Language using Domain-related Corpus","authors":["A Bandyopadhyay, J Nair - 2023 International Conference on Inventive …, 2023"],"snippet":"… Of late, word embeddings from general corpus such as Wikipedia dump, and common crawl corpus are very famous to make word vectors. In the case of Indian languages also such type of corpus is used to make word vectors. But it suffers in …","url":["https://ieeexplore.ieee.org/abstract/document/10134311/"]}
-{"year":"2023","title":"Word length and frequency effects on text reading are highly similar in 12 alphabetic languages","authors":["V Kuperman, S Schroeder, D Gnetov - 2023"],"snippet":"One of the most robust findings in research on eye-movement control in reading is that shorter and more frequent words are recognized faster and skipped more often than longer and less frequent words. These benchmark effects of word length and …","url":["https://files.osf.io/v1/resources/cbvjr/providers/osfstorage/63e3ee839b908d02d12aee42?action=download&direct&version=1"]}
-{"year":"2023","title":"WordScape: a Pipeline to extract multilingual, visually rich Documents with Layout Annotations from Web Crawl Data","authors":["M Weber, C Siebenschuh, RM Butler, A Alexandrov… - Thirty-seventh Conference …, 2023"],"snippet":"… Similar to large-scale NLP dataset creation pipelines like CCNet [33], we use the Common Crawl web corpus 2 as our primary source of documents. We parse Common Crawl to collect urls pointing to MS Word documents embedded in …","url":["https://openreview.net/pdf?id=xewwYquInO"]}
-{"year":"2023","title":"Working with Corpora in Translation Technology Teaching: Enhancing Aspects of Course Design","authors":["M Shuttleworth - Corpora and Translation Education: Advances and …, 2023"],"snippet":"This chapter offers a discussion of two linked areas that are relevant to the translation technology curriculum. Firstly, in the absence of a suitable cost-effective industry-standard terminology extraction utility—as well as the relative under-representation …","url":["https://link.springer.com/chapter/10.1007/978-981-99-6589-2_6"]}
-{"year":"2023","title":"X-ABI: Toward Parameter-Efficient Multilingual Adapter-Based Inference for Cross-Lingual Transfer","authors":["AS Menon, K Anand - … Management, Analytics and Innovation: Proceedings of …, 2023"],"snippet":"… XLM-RoBERTa is a multilingual self-supervised transformers model that is pre-trained on 2.5 TB of filtered CommonCrawl data containing 100 … Table 6 is a comparison between XNLI accuracy and number of tokens present in the 2.5 TB of filtered …","url":["https://link.springer.com/chapter/10.1007/978-981-99-1414-2_23"]}
-{"year":"2023","title":"xDial-Eval: A Multilingual Open-Domain Dialogue Evaluation Benchmark","authors":["C Zhang, LF D'Haro, C Tang, K Shi, G Tang, H Li"],"snippet":"Recent advancements in reference-free learned metrics for open-domain dialogue evaluation have been driven by the progress in pre-trained language models and the availability of dialogue data with high-quality human annotations. However …","url":["https://arxiv.org/pdf/2310.08958"]}
-{"year":"2023","title":"XFEVER: Exploring Fact Verification across Languages","authors":["YC Chang, C Kruengkrai, J Yamagishi - arXiv preprint arXiv:2310.16278, 2023"],"snippet":"This paper introduces the Cross-lingual Fact Extraction and VERification (XFEVER) dataset designed for benchmarking the fact verification models across different languages. We constructed it by translating the claim and evidence texts of the Fact …","url":["https://arxiv.org/pdf/2310.16278"]}
-{"year":"2023","title":"XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models","authors":["D Liang, H Gonen, Y Mao, R Hou, N Goyal… - arXiv preprint arXiv …, 2023"],"snippet":"Large multilingual language models typically rely on a single vocabulary shared across 100+ languages. As these models have increased in parameter count and depth, vocabulary size has remained largely unchanged. This vocabulary bottleneck …","url":["https://arxiv.org/pdf/2301.10472"]}
-{"year":"2023","title":"XNLI 2.0: Improving XNLI dataset and performance on Cross Lingual Understanding (XLU)","authors":["AK Upadhyay, HK Upadhya - arXiv preprint arXiv:2301.06527, 2023"],"snippet":"Natural Language Processing systems are heavily dependent on the availability of annotated data to train practical models. Primarily, models are trained on English datasets. In recent times, significant advances have been made in multilingual …","url":["https://arxiv.org/pdf/2301.06527"]}
-{"year":"2023","title":"xSIM++: An Improved Proxy to Bitext Mining Performance for Low-Resource Languages","authors":["M Chen, K Heffernan, O Çelebi, A Mourachko… - arXiv preprint arXiv …, 2023"],"snippet":"We introduce a new proxy score for evaluating bitext mining based on similarity in a multilingual embedding space: xSIM++. In comparison to xSIM, this improved proxy leverages rule-based approaches to extend English sentences in any evaluation set …","url":["https://arxiv.org/pdf/2306.12907"]}
-{"year":"2023","title":"XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource Languages","authors":["D Taunk, S Sagare, A Patil, S Subramanian, M Gupta… - arXiv preprint arXiv …, 2023"],"snippet":"… 2020) was pretrained on CommonCrawl corpus using the BART objective where the input texts are noised by masking phrases and permuting sentences, and a single Transformer model is learned to recover the texts. Specifically, our mT5-base …","url":["https://arxiv.org/pdf/2303.12308"]}
-{"year":"2023","title":"Yes but.. Can ChatGPT Identify Entities in Historical Documents?","authors":["CE González-Gallardo, E Boros, N Girdhar, A Hamdi… - arXiv preprint arXiv …, 2023","E Boros, N Girdhar, A Hamdi, JG Moreno, A Doucet"],"snippet":"Large language models (LLMs) have been leveraged for several years now, obtaining state-of-the-art performance in recognizing entities from modern documents. For the last few months, the conversational agent ChatGPT has \"prompted\" …","url":["https://arxiv.org/pdf/2303.17322","https://www.academia.edu/download/101050375/chatGPT.pdf"]}
-{"year":"2023","title":"You Call This Archaeology? Evaluating Web Archives for Reproducible Web Security Measurements","authors":["F Hantke, S Calzavara, M Wilhelm, A Rabitti, B Stock - 2023","S Calzavara, F Hantke, M Wilhelm, A Rabitti, B Stock - 2023"],"snippet":"… Besides Memento-based archives, we also consider Common Crawl as a possible alternative source of archival data. Common Crawl … Besides Common Crawl, we consider a public list4 of web archives supporting the Memento protocol …","url":["https://swag.cispa.saarland/papers/calzavara2023archaeology.pdf","https://swag.cispa.saarland/papers/hantke2023archaeology.pdf"]}
-{"year":"2023","title":"YUAN 2.0: A Large Language Model with Localized Filtering-based Attention","authors":["S Wu, X Zhao, S Wang, J Luo, L Li, X Chen, B Zhao… - arXiv preprint arXiv …, 2023"],"snippet":"In this work, the Localized Filtering-based Attention (LFA) is introduced to incorporate prior knowledge of local dependencies of natural language into Attention. Based on LFA, we develop and release Yuan 2.0, a large language model with …","url":["https://arxiv.org/pdf/2311.15786"]}
-{"year":"2023","title":"Zero-shot cross-lingual transfer language selection using linguistic similarity","authors":["J Eronen, M Ptaszynski, F Masui - Information Processing & Management, 2023"],"snippet":"We study the selection of transfer languages for different Natural Language Processing tasks, specifically sentiment analysis, named entity recognition and dependency parsing. In order to select an optimal transfer language, we propose to …","url":["https://www.sciencedirect.com/science/article/pii/S030645732200351X"]}
-{"year":"2023","title":"Zero-shot Cross-lingual Transfer With Learned Projections Using Unlabeled Target-Language Data","authors":["U Deb, R Parab, P Jyothi - The 61st Annual Meeting Of The Association For …, 2023"],"snippet":"Adapters have emerged as a parameter-efficient Transformer-based framework for cross-lingual transfer by inserting lightweight languagespecific modules (language adapters) and taskspecific modules (task adapters) within pretrained multilingual …","url":["https://www.cse.iitb.ac.in/~pjyothi/files/ACL2023a.pdf"]}
-{"year":"2023","title":"Zero-shot Cross-lingual Transfer without Parallel Corpus","authors":["Y Zhang, X Han, B Wang - arXiv preprint arXiv:2310.04726, 2023"],"snippet":"Recently, although pre-trained language models have achieved great success on multilingual NLP (Natural Language Processing) tasks, the lack of training data on many tasks in low-resource languages still limits their performance. One effective …","url":["https://arxiv.org/pdf/2310.04726"]}
-{"year":"2023","title":"Zero-Shot ECG Diagnosis with Large Language Models and Retrieval-Augmented Generation","authors":["H Yu, P Guo, A Sano - Machine Learning for Health (ML4H), 2023"],"snippet":"Recently, Large Language Models (LLMs) have become essential players in the deep learning domain. While their capabilities are evident across various textual tasks, this study aims to bridge the gap and explore the potential of leveraging LLMs …","url":["https://proceedings.mlr.press/v225/yu23b/yu23b.pdf"]}
-{"year":"2023","title":"Zero-Shot Learning on Low-Resource Languages by Cross-Lingual Retrieval","authors":["E Nie"],"snippet":"Research on zero-shot learning on low-resource languages in NLP is motivated by inherent data scarcity of low-resource languages. On the contrary, languages with a large amount of both labeled and unlabeled resources are not fully utilized …","url":["https://www.cip.ifi.lmu.de/~nie/Files/Master_Thesis_Nie.pdf"]}
-{"year":"2023","title":"Zero-Shot Slot and Intent Detection in Low-Resource Languages","authors":["SY Kwon, G Bhatia, EMB Nagoudi, AA Inciarte… - arXiv preprint arXiv …, 2023"],"snippet":"Intent detection and slot filling are critical tasks in spoken and natural language understanding for task-oriented dialog systems. In this work we describe our participation in the slot and intent detection for low-resource language varieties (SID4LR; …","url":["https://arxiv.org/pdf/2304.13292"]}
-{"year":"2023","title":"Zero-Shot Speech Emotion Recognition Using Generative Learning with Reconstructed Prototypes","authors":["X Xu, J Deng, Z Zhang, Z Yang, BW Schuller - ICASSP 2023-2023 IEEE International …, 2023"],"snippet":"… For the prototype-reconstruction step, we employ the 300-dimensional fastText model considering 2 million word vectors (600 billion tokens) trained on Common Crawl [31]. Then, a three-fold emotion-independent Cross-Validation (CV) is …","url":["https://ieeexplore.ieee.org/abstract/document/10094888/"]}
-{"year":"2023","title":"Zero-Shot Transfer Learning using Affix and Correlated Cross-Lingual Embeddings.","authors":["A Modupe, T Sindane, V Marivate - 2023"],"snippet":"Learning morphologically supplemented embedding spaces using cross-lingual models has become an active area of research and facilitated many research breakthroughs in various applications such as machine translation, named entity …","url":["https://www.authorea.com/doi/pdf/10.22541/au.167878643.36371140"]}
-{"year":"2023","title":"Zhanglin Wu, Zhengzhe Yu, Zongyao Li, Daimeng Wei, Yuhao Xie, Xiaoyu Chen, Hengchao Shang, Jiaxin Guo, Zhiqiang Rao, Shaojun Li, Song peng, Lizhi Lei, Hao …","authors":["X Chen - Machine Translation: 19th China Conference, CCMT …, 2023"],"snippet":"This paper presents Huawei Translation Service Center (HW-TSC)'s submission to the machine translation tasks of the 19th China Conference on Machine Translation (CCMT 2023). We participate in all machine translation tasks, including five bilingual …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=OYHgEAAAQBAJ&oi=fnd&pg=PA13&dq=commoncrawl&ots=UiY3rNSUOc&sig=KqCm2llH57sdbm9NHbTvEsbAR2A"]}
-{"year":"2023","title":"Ziya2: Data-centric Learning is All LLMs Need","authors":["R Gan, Z Wu, R Sun, J Lu, X Wu, D Zhang, K Pan… - arXiv preprint arXiv …, 2023"],"snippet":"… First, we find that Common Crawl and other open-source datasets contain substantial duplication of web pages and thus use Bloomfilter5 to de-duplicate URLs, which significantly reduces the computational load required for subsequent content …","url":["https://arxiv.org/pdf/2311.03301"]}
-{"year":"2023","title":"Zoology: Measuring and Improving Recall in Efficient Language Models","authors":["S Arora, S Eyuboglu, A Timalsina, I Johnson, M Poli… - arXiv preprint arXiv …, 2023"],"snippet":"Attention-free language models that combine gating and convolutions are growing in popularity due to their efficiency and increasingly competitive performance. To better understand these architectures, we pretrain a suite of 17 attention and \"gated-convolution\" …","url":["https://arxiv.org/pdf/2312.04927"]}
-{"year":"2023","title":"Zootopi at HOPE2023IberLEF: Is Zero-Shot Chat-GPT the Future of Hope Speech Detection","authors":["A Ngo, HTH Tran - Proceedings of the Iberian Languages Evaluation …, 2023"],"snippet":"Hope Speech Detection is a Natural Language Processing (NLP) task where we aim to detect any message or text that can relax a hostile environment and inspire people in a time of suffering illness, stress, loneliness or depression with optimism …","url":["https://ceur-ws.org/Vol-3496/hope-paper6.pdf"]}
-{"year":"2024","title":"1-Diffractor: Efficient and Utility-Preserving Text Obfuscation Leveraging Word-Level Metric Differential Privacy","authors":["S Meisenbacher, M Chevli, F Matthes - arXiv preprint arXiv:2405.01678, 2024"],"snippet":"The study of privacy-preserving Natural Language Processing (NLP) has gained rising attention in recent years. One promising avenue studies the integration of Differential Privacy in NLP, which has brought about innovative methods in a variety …","url":["https://arxiv.org/pdf/2405.01678"]}
-{"year":"2024","title":"101 Billion Arabic Tokens Dataset","authors":["M Aloui, H Chouikhi, G Chaabane, H Kchaou…"],"snippet":"… , we heavily depend on Common Crawl (1) as our primary source of web-scraped content. Common Crawl provides an accessible web archive … a Dataset Pipeline expressed in the following figure (1) aimed at cleaning up the web-extracted text …","url":["https://www.researchgate.net/profile/Hasna-Chouikhi/publication/380396476_101_Billion_Arabic_Words_Dataset/links/663a610306ea3d0b742f3141/101-Billion-Arabic-Words-Dataset.pdf"]}
-{"year":"2024","title":"101 Billion Arabic Words Dataset","authors":["M Aloui, H Chouikhi, G Chaabane, H Kchaou… - arXiv preprint arXiv …, 2024"],"snippet":"… We undertook a large-scale data mining project, extracting a substantial volume of text from the Common Crawl WET files, specifically targeting Arabic content. The extracted data underwent a rigorous cleaning and deduplication process, using …","url":["https://arxiv.org/pdf/2405.01590"]}
-{"year":"2024","title":"2 Text Preprocessing Method","authors":["J Peng, S Huo"],"snippet":"This paper uses easy data augmentation (EDA) and back translation for text enhancement. After text enhancement, the number of samples in the dataset can be significantly increased, which is helpful for model parameters through training and …","url":["https://journals.riverpublishers.com/index.php/JWE/article/download/25003/19983?inline=1"]}
-{"year":"2024","title":"4 CHATGPT IN ACADEMIA: AN IN-DEPTH EXPLORATION OF STUDENT VIEWS–PROS AND CONS","authors":["D Rajkumar, P Murugeswari, M Karthigaieswari - TRANSDISCIPLINARY THREADS"],"snippet":"… GPT-3’s training data came from five existing datasets: • Common Crawl: A collection of text pulled from billions of web pages containing trillions of words. OpenAI filtered it for high-quality reference material only. • WebText2: OpenAI …","url":["https://www.researchgate.net/profile/Namrata-Shrivastava/publication/378011746_TRANSDISCIPLINARY_THREADS_CRAFTING_THE_FUTURE_THROUGH_MULTIDISCIPLINARY_RESEARCH_VOLUME_-2_httpswwwamazonindp9392917295ref_cm_sw_r_apan_dp_DF7WRSTHCX72MEDVWPB2languageen-IN/links/65c33ae71e1ec12eff78f577/TRANSDISCIPLINARY-THREADS-CRAFTING-THE-FUTURE-THROUGH-MULTIDISCIPLINARY-RESEARCH-VOLUME-2-https-wwwamazonin-dp-9392917295ref-cm-sw-r-apan-dp-DF7WRSTHCX72MEDVWPB2-languageen-IN.pdf#page=34"]}
-{"year":"2024","title":"6 Performance Analysis","authors":["A Safi, S Singh, G Kaur, T Kaur - Intelligent Security Solutions for Cyber-Physical …, 2024"],"snippet":"… The dataset used in this research was gathered from Alexa and the Common Crawl archive. … from a variety of sources, including Common Crawl, Alexa, and PhishTank for the phishing … They used three datasets, including real URLs …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=1VUIEQAAQBAJ&oi=fnd&pg=PA89&dq=commoncrawl&ots=EsWoOABs6N&sig=ot4zCN0ozxE0H1-OW-AyC-mvYJA"]}
-{"year":"2024","title":"\" Previously on...\" From Recaps to Story Summarization","authors":["AK Singh, D Srivastava, M Tapaswi - arXiv preprint arXiv:2405.11487, 2024"],"snippet":"We introduce multimodal story summarization by leveraging TV episode recaps - short video sequences interweaving key story moments from previous episodes to bring viewers up to speed. We propose PlotSnap, a dataset featuring two crime …","url":["https://arxiv.org/pdf/2405.11487"]}
-{"year":"2024","title":"“More than Words”: A Legal Approach to the Risks of Commercial Chatbots Powered by Generative Artificial Intelligence","authors":["S Migliorini - European Journal of Risk Regulation, 2024"],"snippet":"… In the training of ChatGPT, this “clean”19 version of the Common Crawl has been complemented and filtered with the addition of a few … also that the training gave more prominence to the “clean” Common Crawl.Although this explanation may be …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/4EB4DD9997211B81283EF7B34299E254/S1867299X24000047a.pdf/div-class-title-more-than-words-a-legal-approach-to-the-risks-of-commercial-chatbots-powered-by-generative-artificial-intelligence-div.pdf"]}
-{"year":"2024","title":"A Balancing Act: Data Protection Compliance of Artificial Intelligence","authors":["M Bartels - GRUR International, 2024"],"snippet":"Neural network based generative artificial intelligence (GenAI) systems, in particular large language models (LLMs), hold huge potential for economic, scientific, and artistic progress. However, they are also the subject of ongoing fierce data protection …","url":["https://academic.oup.com/grurint/advance-article/doi/10.1093/grurint/ikae060/7671464"]}
-{"year":"2024","title":"A bilingual benchmark for evaluating large language models","authors":["M Alkaoud - PeerJ Computer Science, 2024"],"snippet":"This work introduces a new benchmark for the bilingual evaluation of large language models (LLMs) in English and Arabic. While LLMs have transformed various fields, their evaluation in Arabic remains limited. This work addresses this …","url":["https://peerj.com/articles/cs-1893/"]}
-{"year":"2024","title":"A Canary in the AI Coal Mine: American Jews May Be Disproportionately Harmed by Intellectual Property Dispossession in Large Language Model Training","authors":["H Precel, A McDonald, B Hecht, N Vincent - arXiv preprint arXiv:2403.13073, 2024"],"snippet":"Systemic property dispossession from minority groups has often been carried out in the name of technological progress. In this paper, we identify evidence that the current paradigm of large language models (LLMs) likely continues this long history …","url":["https://arxiv.org/pdf/2403.13073"]}
-{"year":"2024","title":"A Comparative Analysis of Text Embedding Models for Bug Report Semantic Similarity","authors":["A Patil, K Han, A Jadon - 2024 11th International Conference on Signal …, 2024"],"snippet":"… For Fasttext, the ”crawl-300d-2M-subword” model was employed, which consisted of 2 million word vectors trained with subword information on the Common Crawl dataset, encompassing 600 billion tokens. In the case of Doc2Vec, the ”GoogleNews-vectors-negative300” …","url":["https://ieeexplore.ieee.org/abstract/document/10512000/"]}
-{"year":"2024","title":"A Comparative Analysis of Word Embeddings Techniques for Italian News Categorization","authors":["F Rollo, G Bonisoli, L Po - IEEE Access, 2024"],"snippet":"Text categorization remains a formidable challenge in information retrieval, requiring effective strategies, especially when applied to low-resource languages such as Italian. This paper delves into the intricacies of categorizing Italian news articles …","url":["https://ieeexplore.ieee.org/iel7/6287639/10380310/10439164.pdf"]}
-{"year":"2024","title":"A Comparative Study of ChatGPT and Seq2Seq Chatbot for Effective Students Advising","authors":["SK Assayed, M Alkhatib, K Shaalan - ChatGPT and Global Higher Education: Using …, 2024"],"snippet":"Artificial Intelligence (AI) chatbots are increasingly becoming a part of students’ lives, from school learning to university admissions and orientations. AI chatbots are finding ways to facilitate and improve learning experiences. Moreover, AI chatbots …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Xy4KEQAAQBAJ&oi=fnd&pg=PA148&dq=commoncrawl&ots=xiIl7ODrch&sig=SjnxTdqq-f8-Iy1AhxxUa2Nt0lA"]}
-{"year":"2024","title":"A comparative study of cross-lingual sentiment analysis","authors":["P Přibáň, J Šmíd, J Steinberger, A Mištera - Expert Systems with Applications, 2024"],"snippet":"This paper presents a detailed comparative study of the zero-shot cross-lingual sentiment analysis. Namely, we use modern multilingual Transformer-based models and linear transformations combined with CNN and LSTM neural networks. We …","url":["https://www.sciencedirect.com/science/article/pii/S095741742400112X"]}
-{"year":"2024","title":"A Comparison of Pretrained Models for Classifying Issue Reports","authors":["J Heo, G Kwon, C Kwak, S Lee - IEEE Access, 2024"],"snippet":"Issues are evolving requirements which are the main factor that increase the cost of software evolution. To help developers manage issues, GitHub provides issue labeling mechanisms in issue management systems. However, manually labeling …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10546475.pdf"]}
-{"year":"2024","title":"A Comprehensive Review on Large Language Models","authors":["A Yadav - … Software Engineering Through AI, Federated Learning …, 2024"],"snippet":"In the realm of computer science and language, large language models (LLMs) stand out as remarkable tools of artificial intelligence (AI). Proficient in deciphering intricate language nuances, LLMs offer sensible responses and find applications in …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=sd0FEQAAQBAJ&oi=fnd&pg=PA17&dq=commoncrawl&ots=Mfcu5iTaq4&sig=eYkY6zLRcF4QgfOXXfp_HUxZO_4"]}
-{"year":"2024","title":"A contemporary review on chatbots, AI-powered virtual conversational agents, ChatGPT: Applications, open challenges and future research directions","authors":["A Casheekar, A Lahiri, K Rath, KS Prabhakar… - Computer Science Review, 2024"],"snippet":"This review paper offers an in-depth analysis of AI-powered virtual conversational agents, specifically focusing on OpenAI’s ChatGPT. The main contributions of this paper are threefold: (i) an exhaustive review of prior literature on chatbots, (ii) a …","url":["https://www.sciencedirect.com/science/article/pii/S1574013724000169"]}
-{"year":"2024","title":"A Copious Void: Rhetoric as Artificial Intelligence 1.0","authors":["A Hallsby - Rhetoric Society Quarterly, 2024"],"snippet":"Rhetoric is a trace retained in and by artificial intelligence (AI) technologies. This concept illuminates how rhetoric and AI have faced issues related to information abundance, entrenched social inequalities, discriminatory biases, and the …","url":["https://www.tandfonline.com/doi/pdf/10.1080/02773945.2024.2343265"]}
-{"year":"2024","title":"A Critical Analysis of the Largest Source for Generative AI Training Data: Common Crawl","authors":["S Baack - The 2024 ACM Conference on Fairness, Accountability …, 2024"],"snippet":"… among LLM builders about the implications of using Common Crawl’s data. This paper discusses what Common Crawl’s popularity for LLM development means … Our qualitative analysis is based on indepth interviews with Common Crawl staffers …","url":["https://dl.acm.org/doi/abs/10.1145/3630106.3659033"]}
-{"year":"2024","title":"A critical examination of document-level machine translation systems","authors":["P Nayak - 2024"],"snippet":"The need for accurate and effective translation cannot be overstated in an increasingly globalised world where communication is paramount. Bridging language barriers is important for promoting understanding and cooperation among …","url":["https://doras.dcu.ie/29345/1/19213962_final_thesis_upload.pdf"]}
-{"year":"2024","title":"A CURATEd CATalog: Rethinking the Extraction of Pretraining Corpora for Mid-Resourced Languages","authors":["J Palomar-Giner, JJ Saiz, F Espuña, M Mina, S Da Dalt… - Proceedings of the 2024 …, 2024"],"snippet":"We present and describe two language resources in this paper: CATalog 1.0, the largest text corpus in Catalan to date, and CURATE (Corpus Utility for RAting TExt), a modular, parallelizable pipeline used for processing and scoring documents …","url":["https://aclanthology.org/2024.lrec-main.31.pdf"]}
-{"year":"2024","title":"A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages","authors":["L Raithel, HS Yeh, S Yada, C Grouin, T Lavergne… - arXiv preprint arXiv …, 2024"],"snippet":"User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world. However, the existing clinical corpora predominantly revolve around scientific …","url":["https://arxiv.org/pdf/2403.18336"]}
-{"year":"2024","title":"A Dataset for the Detection of Dehumanizing Language","authors":["P Engelmann, PB Trolle, C Hardmeier - arXiv preprint arXiv:2402.08764, 2024"],"snippet":"… The Common Crawl is an open repository of web crawled data, which features crawls from all … As the Common Crawl includes several petabytes of data in total, we have selectively ex… As we limit ourselves to English, the Common Crawl data …","url":["https://arxiv.org/pdf/2402.08764"]}
-{"year":"2024","title":"A Decade's Battle on Dataset Bias: Are We There Yet?","authors":["Z Liu, K He - arXiv preprint arXiv:2403.08632, 2024"],"snippet":"We revisit the \"dataset classification\" experiment suggested by Torralba and Efros a decade ago, in the new era with large-scale, diverse, and hopefully less biased datasets as well as more capable neural network architectures. Surprisingly, we …","url":["https://arxiv.org/pdf/2403.08632"]}
-{"year":"2024","title":"A field guide to using LLMs for online conflict analysis","authors":["E Borra, P Bollini, L Caroleo, B Cerigo, R Dubèl, F Gaw…"],"snippet":"… Two ways in which we studied LLMs was by looking at some of their open-source datasets, which one can sift through in WebText2, CommonCrawl and Wikipedia. Another is by studying autocompletions as perpetuations of standardized knowledge …","url":["https://www.digitalmethods.net/Dmi/FieldGuideToUsingLLMs"]}
-{"year":"2024","title":"A Framework for Embedding Entities in a Textual Narrative: a Case Study on Les Misérables","authors":["G Guex - 2023"],"snippet":"In this article, we propose a general and flexible framework in order to study narrative entities found in a literary work. This framework is exposed starting from a broad perspective, consisting in how to segment the work into textual units and …","url":["https://ceur-ws.org/Vol-3602/paper4.pdf"]}
-{"year":"2024","title":"A Framework for Preparing a Balanced and Comprehensive Phishing Dataset","authors":["I Skula, M Kvet - IEEE Access, 2024"],"snippet":"… • Choon Lin Tan (2018) [19] - dataset contains 5000 legitimate records sourced from Alexa and Common Crawl and 5000 phishing records from PhishTank and … Common Crawl (commoncrawl.org)- is a humongous web archive collected by …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10497090.pdf"]}
-{"year":"2024","title":"A Framework to Construct Financial Causality Knowledge Graph from Text","authors":["Z Xu, H Takamura, R Ichise - 2024 IEEE 18th International Conference on Semantic …, 2024"],"snippet":"Causality analysis holds a prominent role in finance, and the presentation of causality could offer valuable insights for risk mitigation, investment decisions, and portfolio optimization. Recent research has extensively investigated the identification …","url":["https://www.computer.org/csdl/proceedings-article/icsc/2024/853500a057/1Vwkcfe9osw"]}
-{"year":"2024","title":"A Galician Corpus for Misogyny Detection Online","authors":["LM Álvarez-Crespo, LM Castro - Proceedings of the 16th International Conference on …, 2024"],"snippet":"Social networks are virtual spaces where millions of people share ideas, opinions, and experiences. However, this broad social interaction also exposes negative and harmful behaviors, such as harassment and misogyny. Misogyny, particularly, is a …","url":["https://aclanthology.org/2024.propor-1.3.pdf"]}
-{"year":"2024","title":"A Generalize Hardware Debugging Approach for Large Language Models Semi-Syntectic Datasets","authors":["W Fu, S Li, Y Zhao, K Yang, X Zhang, Y Jin, X Guo"],"snippet":"… C4 specifically employs the Common Crawl [44] dataset, focusing on deduplication, removing non-English content, and filtering out offensive language. Redpajama combines sources from Wikipedia and StackExchange, similar to C4 …","url":["https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.171527592.25632661"]}
-{"year":"2024","title":"A Holistic Review on Detection of Malicious Browser Extensions and Links using Deep Learning","authors":["T Zonta, M Sathiyanarayanan - 2024 IEEE 3rd International Conference on AI in …, 2024"],"snippet":"… Common Crawl [36] is a website which crawls over the web and suggest many datasets of legitimate website and their metadata namely … Available: https://commoncrawl.or g/2021/10/september-2021-crawlarchive-now-available/ [37] AC Bahnsen, EC …","url":["https://ieeexplore.ieee.org/abstract/document/10433842/"]}
-{"year":"2024","title":"A Hybrid Deep BiLSTM-CNN for Hate Speech Detection in Multi-social media","authors":["A Kumar, S Kumar, K Passi, A Mahanti - ACM Transactions on Asian and Low …, 2024"],"snippet":"Nowadays, ways of communication among people have changed due to advancements in information technology and the rise of online multi-social media. Many people express their feelings, ideas, and emotions on social media sites such …","url":["https://dl.acm.org/doi/pdf/10.1145/3657635"]}
-{"year":"2024","title":"A Japanese-Chinese Parallel Corpus Using Crowdsourcing for Web Mining","authors":["M Nagata, M Morishita, K Chousa, N Yasuda - arXiv preprint arXiv:2405.09017, 2024"],"snippet":"… In ParaCrawl, they determine which websites to crawl by analyzing the Common Crawl … In this study, we analyzed 12 sets of Common Crawl archives (104TB in total) published from … and bilingual website URLs obtained from Common Crawl …","url":["https://arxiv.org/pdf/2405.09017"]}
-{"year":"2024","title":"A Language Model Trained on Uruguayan Spanish News Text","authors":["JP Filevich, G Marco, S Castro, L Chiruzzo, A Rosá - LREC-COLING 2024, 2024"],"snippet":"This paper presents a language model trained from scratch exclusively on a brand new corpus consisting of about 6 GiB of Uruguayan newspaper text. We trained the model for 30 days on a single Nvidia P100 using the RoBERTa-base architecture …","url":["https://www.iris.unina.it/retrieve/684d559a-e9e4-4eb1-8a80-4a3d654fc7f2/book.v3%20LATEST.pdf#page=63"]}
-{"year":"2024","title":"A Large-Scale Exploration of $\\mu $-Transfer","authors":["L Lingle - arXiv preprint arXiv:2404.05728, 2024"],"snippet":"Large neural network models have become a mainstay of natural language processing and computer vision, yet their initialization and learning rates are set in a largely heuristic fashion, potentially varying from paper to paper and one model size …","url":["https://arxiv.org/html/2404.05728v1"]}
-{"year":"2024","title":"A Legal Framework for Natural Language Model Training in Portugal","authors":["R Almeida, E Amorim - Proceedings of the Workshop on Legal and Ethical …, 2024"],"snippet":"Recent advances in deep learning have promoted the advent of many computational systems capable of performing intelligent actions that, until then, were restricted to the human intellect. In the particular case of human languages, these …","url":["https://aclanthology.org/2024.legal-1.2.pdf"]}
-{"year":"2024","title":"A Legal Framework for Natural Language Processing Model Training in Portugal","authors":["R Almeida, E Amorim - arXiv preprint arXiv:2405.00536, 2024"],"snippet":"Recent advances in deep learning have promoted the advent of many computational systems capable of performing intelligent actions that, until then, were restricted to the human intellect. In the particular case of human languages, these …","url":["https://arxiv.org/pdf/2405.00536"]}
-{"year":"2024","title":"A Little Leak Will Sink a Great Ship: Survey of Transparency for Large Language Models from Start to Finish","authors":["M Kaneko, T Baldwin - arXiv preprint arXiv:2403.16139, 2024"],"snippet":"… The most common sources included in all LLMs are web page sources such as C4, CommonCrawl, and the Pile. Because they are collected from various web pages, there is a risk that they may contain personal information, copyrighted texts …","url":["https://arxiv.org/pdf/2403.16139"]}
-{"year":"2024","title":"A Longitudinal Study of Content Control Mechanisms","authors":["M Dinzinger, M Granitzer - Companion Proceedings of the ACM on Web …, 2024"],"snippet":"… Both resources, robots.txt and regular pages, were collected from the Common Crawl web archive 7 and processed through a customized … As Common Crawl is furhtermore not focused on particular web domains, but randomly samples the …","url":["https://dl.acm.org/doi/abs/10.1145/3589335.3651893"]}
-{"year":"2024","title":"A methodology for using players' chat content for dynamic difficulty adjustment in metaverse multiplayer games","authors":["MM Rezapour, A Fatemi, MA Nematbakhsh - Applied Soft Computing, 2024"],"snippet":"… RoBERTa, on the other hand, was trained on a much larger corpus of text that includes not only Wikipedia and BookCorpus but also Common Crawl, a dataset that contains billions of web pages. This larger and more diverse corpus of text allows …","url":["https://www.sciencedirect.com/science/article/pii/S1568494624002710"]}
-{"year":"2024","title":"A Multilingual Dataset for Investigating Stereotypes and Negative Attitudes Towards Migrant Groups in Large Language Models","authors":["D Sorato, CC Ventura, D Zavala-Rojas - … of the 16th International Conference on …, 2024"],"snippet":"… 2020), which is a cleaned version of the CommonCrawl corpus. … where stereotypes are presented in more subtle and/or strategic ways (when compared to social media/CommonCrawl texts) and the explicit discrimination of migrant groups …","url":["https://aclanthology.org/2024.propor-1.1.pdf"]}
-{"year":"2024","title":"A Multilingual Perspective on Probing Gender Bias","authors":["K Stańczak - arXiv preprint arXiv:2403.10699, 2024"],"snippet":"Gender bias represents a form of systematic negative treatment that targets individuals based on their gender. This discrimination can range from subtle sexist remarks and gendered stereotypes to outright hate speech. Prior research has …","url":["https://arxiv.org/pdf/2403.10699"]}
-{"year":"2024","title":"A New Massive Multilingual Dataset for High-Performance Language Technologies","authors":["O de Gibert, G Nail, N Arefyev, M Bañón… - arXiv preprint arXiv …, 2024"],"snippet":"We present the HPLT (High Performance Language Technologies) language resources, a new massive multilingual dataset including both monolingual and bilingual corpora extracted from CommonCrawl and previously unused web crawls …","url":["https://arxiv.org/pdf/2403.14009"]}
-{"year":"2024","title":"A Permutaion Importance Based feature selection method and Deep Learning Model to Detect Phishing Websites","authors":["R Zaimi, M Hafidi, L Mahnane - 2024"],"snippet":"Phishing attacks pose a significant and escalating threat to cybersecurity in recent times. This deceptive scam aims to trick naive users, luring them into visiting harmful websites and sharing sensitive information, including credentials, credit card …","url":["https://www.researchsquare.com/article/rs-3943049/latest.pdf"]}
-{"year":"2024","title":"A phenomenology and epistemology of large language models: Transparency, trust, and trustworthiness","authors":["R Heersmink, B de Rooij, MJC Vázquez, M Colombo"],"snippet":"… We know that its dataset includes the Common Crawl, which is a publicly available corpus of Webpages, including billions of Webpages … whether sources in the Common Crawl or Wikipedia are prioritised. This is again a serious issue to do …","url":["https://philpapers.org/archive/HEEAPA.pdf"]}
-{"year":"2024","title":"A Review of Current Trends, Techniques, and Challenges in Large Language Models (LLMs)","authors":["R Patil, V Gudivada - 2024"],"snippet":"… For low-resource languages, XLM models trained on CommonCrawl-100 did better than the ones trained using Wikipedia. Another example is mT5 [32], which uses multilingual corpus mC4 to pretrain the model. When dealing with multilingual …","url":["https://www.preprints.org/manuscript/202402.0357/download/final_file"]}
-{"year":"2024","title":"A Review of Multi-Modal Large Language and Vision Models","authors":["K Carolan, L Fennelly, AF Smeaton - arXiv preprint arXiv:2404.01322, 2024"],"snippet":"… The Falcon LLM team created the RefinedWed dataset, which is a massive web dataset based on CommonCrawl. TII focused on scaling and improving the quality of web data by employing large-scale de-duplication and strict filtering, resulting in …","url":["https://arxiv.org/pdf/2404.01322"]}
-{"year":"2024","title":"A Robust Approach to E-Banking Phishing Detection using Ensemble Methods and LSTM","authors":["NVS Reddy, ARR Saai, TV Ramanujan, NRK Reddy… - … International Conference on …, 2024"],"snippet":"… range of datasets from reputable community platforms like VirusTotal, Common Crawl, and PhishTank. This extensive dataset, spanning … Integration of Common Crawl further enriched the dataset, ensuring a diverse set of websites for effective …","url":["https://ieeexplore.ieee.org/abstract/document/10533883/"]}
-{"year":"2024","title":"A Shocking Amount of the Web is Machine Translated: Insights from Multi-Way Parallelism","authors":["B Thompson, MP Dhaliwal, P Frisch, T Domhan… - arXiv preprint arXiv …, 2024"],"snippet":"… 2021), which is in turn based on Common CrawlCommon Crawl is a long running web-scraping project which maintains a free, open source repository of web-scraped data. ccMatrix is created by embedding Common Crawl sentences into a …","url":["https://arxiv.org/pdf/2401.05749"]}
-{"year":"2024","title":"A Short Commentary on Trinh & Le (2018)","authors":["WS SABA"],"snippet":"… corpus (trained on the language model LM-1-Billion, CommonCrawl, and SQuAD), the probabilities of s1 and s2 appearing in a large corpus. The substitution that turns out to be more probable, is considered to be the more probable referent of “it”. There …","url":["https://www.academia.edu/download/108648524/1810.00521.pdf"]}
-{"year":"2024","title":"A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization","authors":["T Kumarage, G Agrawal, P Sheth, R Moraffah… - arXiv preprint arXiv …, 2024"],"snippet":"We have witnessed lately a rapid proliferation of advanced Large Language Models (LLMs) capable of generating high-quality text. While these LLMs have revolutionized text generation across various domains, they also pose significant …","url":["https://arxiv.org/pdf/2403.01152"]}
-{"year":"2024","title":"A Survey of Multimodal Large Language Model from A Data-centric Perspective","authors":["T Bai, H Liang, B Wan, L Yang, B Li, Y Wang, B Cui… - arXiv preprint arXiv …, 2024"],"snippet":"… CommonCrawl project serves as the most commonly … , CommonCrawl’s vast archive of web pages, which includes numerous image-text pairs, has also become a vital resource for constructing multimodal pre-training datasets such as LAION-5B [236] …","url":["https://arxiv.org/pdf/2405.16640"]}
-{"year":"2024","title":"A Survey of Neural Machine Translation based on Knowledge Distillation","authors":["MA Chang, T Yonghong, Z Xiaoli, SUN Kangkang - Journal of Frontiers of Computer Science …"],"snippet":"Abstract: Machine Translation (MT) is the process of using a computer to convert a language into another language with the same semantics. With the introduction of neural network, neural machine translation (NMT), as a powerful machine …","url":["http://fcst.ceaj.org/EN/article/downloadArticleFile.do?attachType=PDF&id=3451"]}
-{"year":"2024","title":"A Survey of Resource-efficient LLM and Multimodal Foundation Models","authors":["M Xu, W Yin, D Cai, R Yi, D Xu, Q Wang, B Wu, Y Zhao… - arXiv preprint arXiv …, 2024"],"snippet":"Large foundation models, including large language models (LLMs), vision transformers (ViTs), diffusion, and LLM-based multimodal models, are revolutionizing the entire machine learning lifecycle, from training to deployment …","url":["https://arxiv.org/pdf/2401.08092"]}
-{"year":"2024","title":"A Survey of Web Content Control for Generative AI","authors":["M Dinzinger, F Heß, M Granitzer - arXiv preprint arXiv:2404.02309, 2024"],"snippet":"… The documents were sourced from the web archive of Common Crawl,16 offering a broad and randomly selected cross-section of the internet. These files were all collected in November and December 2023. Further details on the experimental …","url":["https://arxiv.org/pdf/2404.02309"]}
-{"year":"2024","title":"A Survey on Data Selection for Language Models","authors":["A Albalak, Y Elazar, SM Xie, S Longpre, N Lambert… - arXiv preprint arXiv …, 2024"],"snippet":"… They train a classifier using the “high-quality” reference corpora as the positive class and unfiltered Common Crawl documents as the negative class. This classifier then defines the utility metric for selecting data that follows the desired distribution …","url":["https://arxiv.org/pdf/2402.16827"]}
-{"year":"2024","title":"A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers","authors":["K Huang, F Mo, H Li, Y Li, Y Zhang, W Yi, Y Mao, J Liu… - arXiv preprint arXiv …, 2024"],"snippet":"The rapid development of Large Language Models (LLMs) demonstrates remarkable multilingual capabilities in natural language processing, attracting global attention in both academia and industry. To mitigate potential discrimination …","url":["https://arxiv.org/pdf/2405.10936"]}
-{"year":"2024","title":"A Survey on Multilingual Large Language Models: Corpora, Alignment, and Bias","authors":["Y Xu, L Hu, J Zhao, Z Qiu, Y Ye, H Gu - arXiv preprint arXiv:2404.00929, 2024"],"snippet":"… A significant portion of these training data originates from multilingual repositories like Common Crawl, WikiPedia and Web documents, encompassing a broad range of languages. These multilingual repositories are crucial for enhancing the cross-lingual …","url":["https://arxiv.org/pdf/2404.00929"]}
-{"year":"2024","title":"A survey on recent advances in named entity recognition","authors":["I Keraghel, S Morbieu, M Nadif - arXiv preprint arXiv:2401.10825, 2024"],"snippet":"Named Entity Recognition seeks to extract substrings within a text that name real-world objects and to determine their type (for example, whether they refer to persons or organizations). In this survey, we first present an overview of recent popular …","url":["https://arxiv.org/pdf/2401.10825"]}
-{"year":"2024","title":"A systematic review of multidimensional relevance estimation in information retrieval","authors":["G Peikos, G Pasi - Wiley Interdisciplinary Reviews: Data Mining and …"],"snippet":"In information retrieval, relevance is perceived as a multidimensional and dynamic concept influenced by user, task, and domain factors. Relying on this perspective, researchers have introduced multidimensional relevance models addressing …","url":["https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/widm.1541"]}
-{"year":"2024","title":"A Systematic Study of the Role of Data Quality and Alignment for Fine-tuning LLMs for Enhanced Autoformalization","authors":["K Chawla, A Sahai, M DePavia, B Miranda - The Second Tiny Papers Track at ICLR 2024"],"snippet":"This study explores the role of data quality, particularly alignment, in fine-tuning Large Language Models (LLMs) for the task of autoformalization. Contrary to the conventional emphasis on dataset size, our research highlights the importance of …","url":["https://openreview.net/pdf?id=9LkPbnRwXu"]}
-{"year":"2024","title":"A Trustworthy Automated Short-Answer Scoring System Using a New Dataset and Hybrid Transfer Learning Method","authors":["M Maslim, HC Wang, CD Putra, YD Prabowo - 2024"],"snippet":"To measure the quality of student learning, teachers must conduct evaluations. One of the most efficient modes of evaluation is the short answer question. However, there can be inconsistencies in teacher-performed manual evaluations due to an …","url":["https://reunir.unir.net/bitstream/handle/123456789/16203/A%20Trustworthy%20Automated%20Short-Answer%20Scoring%20System%20Using%20a%20New%20Dataset%20and%20Hybrid%20Transfer%20Learning%20Method.pdf?sequence=1"]}
-{"year":"2024","title":"AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters","authors":["L Lucy, S Gururangan, L Soldaini, E Strubell… - arXiv preprint arXiv …, 2024"],"snippet":"… From this Common Crawl data, we identify website hostnames that include an ABOUT page, which we define as URL paths containing about, aboutme, about-us, or bio (Appendix A). We then pair each ABOUT page with a random page on the …","url":["https://arxiv.org/pdf/2401.06408"]}
-{"year":"2024","title":"Abusive Language Detection in Khasi Social Media Comments","authors":["A Baruah, L Wahlang, F Jyrwa, F Shadap, F Barbhuiya… - ACM Transactions on Asian …, 2024"],"snippet":"This paper describes the work performed for automated abusive language detection in the Khasi language, a low-resource language spoken primarily in the state of Meghalaya, India. A dataset named Khasi Abusive Language Dataset (KALD) was …","url":["https://dl.acm.org/doi/pdf/10.1145/3664285"]}
-{"year":"2024","title":"Accelerating Spiking Neural Networks with Parallelizable Leaky Integrate-and-Fire Neurons","authors":["SYA Yarga, SUN Wood - 2024"],"snippet":"… To achieve this, these models undergo training on massive datasets, such as the Common Crawl corpus1, which contains petabytes of textual data. Training on such extensive datasets necessitates the use of fast machine learning models like the …","url":["https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.170905886.62702188"]}
-{"year":"2024","title":"ACCEPTANCE OF GENERATIVE AI IN KNOWLEDGE WORK","authors":["K Koponen - 2023"],"snippet":"… The GPT-3 was trained with Corpus, a large and structured collection of texts or language data, called Common Crawl including nearly a trillion words. (Brown et al., 2020) In addition, the training set was also expanded with known high-quality …","url":["https://trepo.tuni.fi/bitstream/handle/10024/154287/KoponenKati.pdf?sequence=2"]}
-{"year":"2024","title":"ACCSAMS: Automatic Conversion of Exam Documents to Accessible Learning Material for Blind and Visually Impaired","authors":["D Wilkening, O Moured, T Schwarz, K Muller… - arXiv preprint arXiv …, 2024"],"snippet":"… We collected exam materials from the Common Crawl project4, a public archive of web data. We analyzed eight datasets, released between mid 2022 and the end of 2023, extracting PDFs, which include “exam” or “klausur” as a keyword in the URL …","url":["https://arxiv.org/pdf/2405.19124"]}
-{"year":"2024","title":"Accuracy of ChatGPT in Neurolocalization","authors":["WF Dabbas, YM Odeibat, M Alhazaimeh, MY Hiasat… - Cureus, 2024"],"snippet":"… The datasets used for pre-training included Common Crawl dataset, an expanded version of the WebText dataset, two internet-based books corpora (Books1 and Books2), and English-language Wikipedia [13]. …","url":["https://www.cureus.com/articles/249830-accuracy-of-chatgpt-in-neurolocalization.pdf"]}
-{"year":"2024","title":"Adapting LLMs to Downstream Applications","authors":["A Kucharavy - Large, 2024"],"snippet":"… The model was fed with text that generally precedes private information in a dataset used to train GPT-2—specifically the “Common Crawl” dataset to achieve a better recall. 2 With this approach, authors were not only able to extract extensive …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-54827-7.pdf#page=36"]}
-{"year":"2024","title":"Adaptive Ensembles of Fine-Tuned Transformers for LLM-Generated Text Detection","authors":["Z Lai, X Zhang, S Chen - arXiv preprint arXiv:2403.13335, 2024"],"snippet":"… 5) XLMRoberta: XLMRoberta is a large-scale multilingual transformer-based LM pretrained on a diverse set of one hundred languages using extensive CommonCrawl data [68]. We use the “xlm roberta base multi” as pretrained backbone weight. …","url":["https://arxiv.org/pdf/2403.13335"]}
-{"year":"2024","title":"Addressing Both Statistical and Causal Gender Fairness in NLP Models","authors":["H Chen, Y Ji, D Evans - arXiv preprint arXiv:2404.00463, 2024"],"snippet":"… 2019) comprising nearly 400,000 online biographies of 28 unique occupations scraped from the CommonCrawl. The task is to predict the occupation given in the biography with the occupation title removed. Each biography includes the name and …","url":["https://arxiv.org/pdf/2404.00463"]}
-{"year":"2024","title":"Addressing the Challenge of Online Health Misinformation: Detection, Retrieval, and Explainability","authors":["R Upadhyay - 2024"],"snippet":"Nell’odierna epoca digitale, le piattaforme online costituiscono uno dei mezzi principali utilizzati dalle persone per cercare informazioni relative alla propria salute. Nonostante il web sia un vasto repository di conoscenze in tale ambito, è affetto dal …","url":["https://boa.unimib.it/bitstream/10281/465160/2/phd_unimib_865291.pdf"]}
-{"year":"2024","title":"Adjusting Interpretable Dimensions in Embedding Space with Human Judgments","authors":["K Erk, M Apidianaki - arXiv preprint arXiv:2404.02619, 2024"],"snippet":"… The GLoVe embeddings used were trained on Common Crawl (42B tokens, 1.9M vocab, uncased, 300d vectors), downloaded from https: //nlp.stanford.edu/projects/glove/. In order to generate embeddings for contextualized instances of words in our …","url":["https://arxiv.org/html/2404.02619v1"]}
-{"year":"2024","title":"Adult Content Detection on Indonesian Tweets by Fine-tuning Transformer-based Models","authors":["AF Hidayatullah, RA Apong, DTC Lai, A Qazi - 2023 6th International Conference on …, 2023"],"snippet":"The prevalence of adult content on social media has harmful effects on the moral values of young individuals. Therefore, effectively filtering inappropriate content on social media like Twitter is essential. Researchers have utilized machine learning …","url":["https://ieeexplore.ieee.org/abstract/document/10367283/"]}
-{"year":"2024","title":"Advancing Fake News Detection: Hybrid Deep Learning with FastText and Explainable AI","authors":["E Hashmi, SY Yayilgan, MM Yamin, S Ali, M Abomhara - IEEE Access, 2024"],"snippet":"… FastText, a word representation tool developed by Facebook’s research division, provides both unsupervised and supervised modes, featuring an extensive lexicon of 2 million words sourced from Common Crawl. Each word is represented in a 300-dimensional …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10477989.pdf"]}
-{"year":"2024","title":"Advancing Internet Viewpoint Diversity: A Novel Algorithm and a Corpus Creation Tool","authors":["J Harwell - 2023"],"snippet":"… To achieve this, we first develop a big data processing architecture for creating indexed corpora from the Common Crawl web archives. The … Utilizing this tool, we processed approximately 1.2 billion web pages from the Common Crawl dataset …","url":["https://scholarship.claremont.edu/cgi/viewcontent.cgi?article=1768&context=cgu_etd"]}
-{"year":"2024","title":"Advancing language models through domain knowledge integration: a comprehensive approach to training, evaluation, and optimization of social scientific neural …","authors":["F Stöhr - Journal of Computational Social Science, 2024"],"snippet":"This article proposes a comprehensive strategy for training, evaluating, and optimizing domain-specific word2vec-based word embeddings, using social science literature as an example. Our primary objectives are:(1) to train the embeddings …","url":["https://link.springer.com/article/10.1007/s42001-024-00286-3"]}
-{"year":"2024","title":"Advancing Large Multi-modal Models with Explicit Chain-of-Reasoning and Visual Question Generation","authors":["K Uehara, N Goswami, H Wang, T Baba, K Tanaka… - arXiv preprint arXiv …, 2024"],"snippet":"The increasing demand for intelligent systems capable of interpreting and reasoning about visual content requires the development of Large Multi-Modal Models (LMMs) that are not only accurate but also have explicit reasoning capabilities. This paper …","url":["https://arxiv.org/pdf/2401.10005"]}
-{"year":"2024","title":"Advancing medical imaging with language models: featuring a spotlight on ChatGPT","authors":["M Hu, JY Qian, S Pan, Y Li, RLJ Qiu, X Yang - Physics in Medicine and Biology, 2024"],"snippet":"This review paper aims to serve as a comprehensive guide and instructional resource for researchers seeking to effectively implement language models in medical imaging research. First, we presented the fundamental principles and …","url":["https://iopscience.iop.org/article/10.1088/1361-6560/ad387d/pdf"]}
-{"year":"2024","title":"Advancing Real-time Pandemic Forecasting Using Large Language Models: A COVID-19 Case Study","authors":["H Du, J Zhao, Y Zhao, S Xu, X Lin, Y Chen, LM Gardner - arXiv preprint arXiv …, 2024","HF Yang, H Du, J Zhao, Y Zhao, S Xu, X Lin, Y Chen… - 2024"],"snippet":"Forecasting the short-term spread of an ongoing disease outbreak is a formidable challenge due to the complexity of contributing factors, some of which can be characterized through interlinked, multi-modality variables such as epidemiological …","url":["https://arxiv.org/pdf/2404.06962","https://www.researchsquare.com/article/rs-4244182/latest.pdf"]}
-{"year":"2024","title":"Afrikaans Literary Genre Recognition using Embeddings and Pre-Trained Multilingual Language Models","authors":["E Kotzé, BA Senekal - 2024 International Conference on Artificial Intelligence …, 2024"],"snippet":"… XLM-R (or XLM-RoBERTa) is a multilingual version of RoBERTa with 279M parameters and was trained on a 2.5TB of CommonCrawl data containing 100 languages. Afrikaans is included in all three of these multilingual models. …","url":["https://ieeexplore.ieee.org/abstract/document/10467838/"]}
-{"year":"2024","title":"Aggression and Misogyny in Hindi and Bangla: A Study of YouTube Comments","authors":["R Kumar, B Lahiri - Studies in Pragmatics, 2024"],"snippet":"… The pre-trained models are typically trained on web-scale data, ie text collected from all over the web such as the whole of Wikipedia and a common crawl of the websites currently on the internet amounting to billions (or trillions) of tokens and …","url":["https://brill.com/downloadpdf/display/title/69958.pdf#page=130"]}
-{"year":"2024","title":"AI unveiled personalities: Profiling optimistic and pessimistic attitudes in Hindi dataset using transformer‐based models","authors":["D Jain, A Kumar - Expert Systems"],"snippet":"Both optimism and pessimism are intricately intertwined with an individual's inherent personality traits and people of all personality types can exhibit a wide range of attitudes and behaviours, including levels of optimism and pessimism. This paper …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.13572"]}
-{"year":"2024","title":"AI's Secret Weapon in Education. ChatGPT–The Future of Personalized Learning","authors":["A Popescu - Bulletin of the Transilvania University of Brasov. Series …, 2023"],"snippet":"This article delves into the fascinating intersection of AI and education, with a focus on ChatGPT, a conversational AI developed by OpenAI. Noted for its human-like responses, ChatGPT is positioned as a game-changer in personalized learning. The …","url":["https://webbut.unitbv.ro/index.php/Series_V/article/download/6816/5216"]}
-{"year":"2024","title":"AI-Powered Code Review Assistant for Streamlining Pull Request Merging","authors":["C Adapa, SS Avulamanda, ARK Anjana, A Victor - 2024 IEEE International …, 2024"],"snippet":"… The model's reliance on Refined Web, primarily sourced from Common Crawl, underscores its commitment to exceptional quality through advanced data augmentation techniques, notably largescale deduplication and rigorous filtering. Unlike conventional …","url":["https://ieeexplore.ieee.org/abstract/document/10503540/"]}
-{"year":"2024","title":"AI-Proof Your Assignments","authors":["S Vital - 2024"],"snippet":"ChatGPT and other AI tools are powerful, free, and seemingly everywhere. Faculty love it, fear it, and everything in between. Students also love it, fear it, and everything in between; All the while, they are using it. In this session, we’ll cover a bit about how …","url":["https://digitalcommons.stmarys-ca.edu/cgi/viewcontent.cgi?article=1159&context=staff-works"]}
-{"year":"2024","title":"AI-Replicas as Ethical Practice: Introducing an Alternative to Traditional Anonymization Techniques in Image-Based Research","authors":["T Kamelski, F Olivos - 2024"],"snippet":"This paper introduces the use of AI-replicas as an alternative to traditional anonymization methods in image-based qualitative research. It emphasizes the ethical and practical dilemmas posed by current anonymization methods, such as …","url":["https://osf.io/8frst/download"]}
-{"year":"2024","title":"Algorithmic amplification of biases on Google Search","authors":["H Habib, R Stoldt, A High, B Ekdale, A Peterson… - arXiv preprint arXiv …, 2024"],"snippet":"The evolution of information-seeking processes, driven by search engines like Google, has transformed the access to information people have. This paper investigates how individuals' preexisting attitudes influence the modern information-seeking …","url":["https://arxiv.org/pdf/2401.09044"]}
-{"year":"2024","title":"Alpaca against Vicuna: Using LLMs to Uncover Memorization of LLMs","authors":["AM Kassem, O Mahmoud, N Mireshghallah, H Kim… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we introduce a black-box prompt optimization method that uses an attacker LLM agent to uncover higher levels of memorization in a victim agent, compared to what is revealed by prompting the target model with the training data …","url":["https://arxiv.org/pdf/2403.04801"]}
-{"year":"2024","title":"Amharic LLaMA and LLaVA: Multimodal LLMs for Low Resource Languages","authors":["M Andersland - arXiv preprint arXiv:2403.06354, 2024"],"snippet":"… Less than 0.1% of CommonCrawl2 is Amharic, and even when combining open source datasets without deduplication, we find that less than 500 million tokens of Amharic are available. In addition, the content of this data tends to be biased …","url":["https://arxiv.org/pdf/2403.06354"]}
-{"year":"2024","title":"An Ambiguous Technique for Nonvisual Text Entry","authors":["DC Gaines - 2023"],"snippet":"Text entry is a common daily task for many people, but it can be a challenge for people with visual impairments when using virtual touchscreen keyboards that lack physical key boundaries. In this thesis, we investigate using a small number of …","url":["https://digitalcommons.mtu.edu/cgi/viewcontent.cgi?article=2800&context=etdr"]}
-{"year":"2024","title":"An Analysis of Langauge Frequency and Error Correction for Esperanto","authors":["J Liang - arXiv preprint arXiv:2402.09696, 2024"],"snippet":"… Goyal builds Commoncrawl Corpus in 100 languages and then uses a language identification model to select Esperanto contexts[8], which … OSCAR [11] provides a collection of unannotated raw data and devises a method to improve the quality of …","url":["https://arxiv.org/pdf/2402.09696"]}
-{"year":"2024","title":"An Assessment on Comprehending Mental Health through Large Language Models","authors":["M Arcan, PD Niland, F Delahunty - arXiv preprint arXiv:2401.04592, 2024"],"snippet":"… The training data for GPT-3 is primarily sourced from a filtered version of Common Crawl, contributing to 60% of the weighted pre-training dataset, comprising 410 billion bytepair-encoded tokens. Other data sources include 19 billion tokens from …","url":["https://arxiv.org/pdf/2401.04592"]}
-{"year":"2024","title":"An Extensive Survey on Investigation Methodologies for Text Summarization","authors":["A Saklecha, P Uplavdiya, MPS Chawla - Indian Journal of Signal Processing (IJSP), 2023"],"snippet":"Natural language processing (NLP) is a fastexpanding field, and text summarization has recently gained a lot of research interest. The necessity for automatic summarizing approaches to effectively digest massive amounts of textual data has …","url":["https://www.ijsp.latticescipub.com/wp-content/uploads/papers/v3i4/D1016113423.pdf"]}
-{"year":"2024","title":"An Integrated Data Processing Framework for Pretraining Foundation Models","authors":["Y Sun, F Wang, Y Zhu, WX Zhao, J Mao - arXiv preprint arXiv:2402.16358, 2024"],"snippet":"… In the end-to-end evaluation, we train two GPT-2 models using CommonCrawl before and after processing, respectively. The model trained on the refined data demonstrates remarkable performance enhancement across downstream tasks of …","url":["https://arxiv.org/pdf/2402.16358"]}
-{"year":"2024","title":"An Introduction to Vision-Language Modeling","authors":["F Bordes, RY Pang, A Ajay, AC Li, A Bardes, S Petryk… - arXiv preprint arXiv …, 2024"],"snippet":"… Multiple curation steps are used to curate this dataset where English data is collected from common crawl and deduplicated followed by pre-processing HTML document where useful DOM nodes are identified and retained, then for each DOM …","url":["https://arxiv.org/pdf/2405.17247"]}
-{"year":"2024","title":"Analysing Slow Thinking Capabilities in Large Language Model Agent-Agent Dialogue","authors":["J Cornelje - 2024"],"snippet":"… LLMs can be given data from books, CommonCrawl, Reddit links and Wikipedia, where CommonCrawl consists of petabytes of web archives [113]. Having large datasets makes it more difficult to curate the data. Documentation of the data can …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/46440/Master%20Thesis%20-%20Joel%20Cornelje.pdf?sequence=1"]}
-{"year":"2024","title":"Analysing The Impact of Sequence Composition on Language Model Pre-Training","authors":["Y Zhao, Y Qu, K Staniszewski, S Tworkowski, W Liu… - arXiv preprint arXiv …, 2024"],"snippet":"Most language model pre-training frameworks concatenate multiple documents into fixed-length sequences and use causal masking to compute the likelihood of each token given its context; this strategy is widely adopted due to its simplicity and …","url":["https://arxiv.org/pdf/2402.13991"]}
-{"year":"2024","title":"Analysing the landscape of Deep Fake Detection: A Survey","authors":["K Vyas, P Pareek, R Jayaswal, S Patil - … of Intelligent Systems and Applications in …, 2024"],"snippet":"… Grover utilizes a test set created by the free and open-source web crawler and archive Common Crawl [35]. As an example, a team of academics from Harvard and the MIT-IBM Watson laboratory developed the Giant language model test room, a …","url":["https://www.ijisae.org/index.php/IJISAE/article/download/4418/3078"]}
-{"year":"2024","title":"AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets","authors":["P Lesci, A Vlachos - arXiv preprint arXiv:2404.05623, 2024"],"snippet":"Active learning for imbalanced classification tasks is challenging as the minority classes naturally occur rarely. Gathering a large pool of unlabelled data is thus essential to capture minority instances. Standard pool-based active learning is …","url":["https://arxiv.org/html/2404.05623v1"]}
-{"year":"2024","title":"and S. Abirami","authors":["RS Gulecha, SKNR Subramanian - Speech and Language Technologies for Low …"],"snippet":"In recent years, the Internet and social media have sparked a revolution in the way information is exchanged. The growth of social media and micro-blogging sites not only provides platforms for empowering freedom of expression and individual voices …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Rs0DEQAAQBAJ&oi=fnd&pg=PA225&dq=commoncrawl&ots=l6SKt6PjDk&sig=xgAK9FCRDZ55-F9mtury-zU49yk"]}
-{"year":"2024","title":"Answer Agnostic Question Generation in Bangla Language","authors":["AR Fahad, N Al Nahian, MA Islam, RM Rahman - International Journal of Networked …, 2024"],"snippet":"… mT5 is a massively multilingual model pre-trained using fresh Common Crawl-based data that includes 101 languages [14]. Another model, BanglaT5, a Transformer model for the Bangla language, was trained using a 27.5 GB clean corpus of Bangla …","url":["https://link.springer.com/article/10.1007/s44227-023-00018-5"]}
-{"year":"2024","title":"AntiPhishStack: LSTM-based Stacked Generalization Model for Optimized Phishing URLs Detection","authors":["S Aslam, H Aslam, A Manzoor, C Hui, A Rasool - 2024"],"snippet":"The escalating reliance on revolutionary online web services has introduced heightened security risks, with persistent challenges posed by phishing despite extensive security measures. Traditional phishing systems, reliant on machine …","url":["https://www.preprints.org/manuscript/202401.1142/download/final_file"]}
-{"year":"2024","title":"AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling","authors":["J Zhan, J Dai, J Ye, Y Zhou, D Zhang, Z Liu, X Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce AnyGPT, an any-to-any multimodal language model that utilizes discrete representations for the unified processing of various modalities, including speech, text, images, and music. AnyGPT can be trained stably without any …","url":["https://arxiv.org/pdf/2402.12226"]}
-{"year":"2024","title":"Application of an Improved Convolutional Neural Network Algorithm in Text Classification","authors":["J Peng, S Huo - Journal of Web Engineering, 2024"],"snippet":"This paper proposes a text classification model based on a combination of a convolutional neural network (CNN) and a support vector machine (SVM) using Amazon review polarity, TREC, and Kaggle as experimental data. By adding an …","url":["https://journals.riverpublishers.com/index.php/JWE/article/download/25003/19981"]}
-{"year":"2024","title":"Application of Open-source Large Language Model (LLM) for Simulation of a Vulnerable IoT System and Cybersecurity Best Practices Assistance","authors":["V Yosifova - 2024"],"snippet":"This paper explores the role of open-source large language models in IoT cybersecurity world. The threats of malicious activity on the Internet and the loss of private information are very real and lead to serious consequences. The purpose of …","url":["https://www.preprints.org/manuscript/202405.1169/download/final_file"]}
-{"year":"2024","title":"Applications of AI in Computer Vision and NLP","authors":["SB Rajasekaran - Journal of Artificial Intelligence & Cloud Computing …, 2023"],"snippet":"… In language AI, there are several commonly used datasets such as Common Crawl, Wikipedia, and OpenWebText. However, creating and maintaining these datasets can also be a challenging task, as it needs a big amount of work and it can ���","url":["https://www.onlinescientificresearch.com/articles/applications-of-ai-in-computer-vision-and-nlp.pdf"]}
-{"year":"2024","title":"Applying German word vectors to assess flexibility performance in the associative fluency task.","authors":["M Camenzind, M Single, SM Gerber, T Nef, CL Bassetti… - Psychology of Aesthetics …, 2024"],"snippet":"… One model was trained on common crawl, a nonprofit organization crawling the web and making resulting data publicly available, and the other was trained on Wikipedia. The vectors were trained using the CBOW algorithm with a special focus …","url":["https://psycnet.apa.org/record/2024-67165-001"]}
-{"year":"2024","title":"Applying Named Entity Recognition and Graph Networks to Extract Common Interests from Thematic Subfora on Reddit","authors":["J Sawicki, M Ganzha, M Paprzycki, Y Watanobe - Applied Sciences, 2024"],"snippet":"… , accessed on 13 February 2024) (pre-trained BERT large models fine-tuned on the CoNLL-2003 dataset) and flair/ner-english-large (https://huggingface.co/flair/ner-english-large, accessed on 13 February 2024) (an XLM-RoBERTa [89] pre-trained on a cleaned …","url":["https://www.mdpi.com/2076-3417/14/5/1696"]}
-{"year":"2024","title":"Applying Transfer Learning to German Metaphor Prediction","authors":["M Berger, SM Reimann, NM Kiwitt - Proceedings of the 2024 Joint International …, 2024"],"snippet":"… -scores using CommonCrawl embeddings (F1 60%) and News Commentary embeddings (F1 58%) while CommonCrawl contains over 2 m… 4), we can see that the bilingual embeddings approach, especially using Europarl and CommonCrawl …","url":["https://aclanthology.org/2024.lrec-main.123.pdf"]}
-{"year":"2024","title":"Arabic sarcasm detection: An enhanced fine-tuned language model approach","authors":["MA Galal, AH Yousef, HH Zayed, W Medhat - Ain Shams Engineering Journal, 2024"],"snippet":"Sarcasm is a complex linguistic phenomenon involving humor, criticism, or phrases that convey the opposite meaning, mask true feelings, and play pivotal roles in various aspects of communication. Therefore, identifying sarcasm is essential for …","url":["https://www.sciencedirect.com/science/article/pii/S2090447924001114"]}
-{"year":"2024","title":"Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding Models","authors":["L Merrick, D Xu, G Nuti, D Campos - arXiv preprint arXiv:2405.05374, 2024"],"snippet":"This report describes the training dataset creation and recipe behind the family of \\texttt{arctic-embed} text embedding models (a set of five models ranging from 22 to 334 million parameters with weights open-sourced under an Apache-2 license). At the time of …","url":["https://arxiv.org/pdf/2405.05374"]}
-{"year":"2024","title":"Are Human Conversations Special? A Large Language Model Perspective","authors":["T Jawale, C Animesh, S Vallath, K Talamadupula… - arXiv preprint arXiv …, 2024"],"snippet":"… We analyze the web data from CommonCrawl[21] dumps for human conversation data and the types of conversations in Table 1. We randomly sample a subset of the dump and deduplicate it so that it can be used to approximate the data distribution …","url":["https://arxiv.org/html/2403.05045v1"]}
-{"year":"2024","title":"Are LLMs Robust for Spoken Dialogues?","authors":["SM Mousavi, G Roccabruna, S Alghisi, M Rizzoli… - arXiv preprint arXiv …, 2024"],"snippet":"… The LLM finetuned for this task is T5 Small [21], (12 layers, 60M parameters), a transformer-based encoder-decoder model, pre-trained on the Common Crawl dataset with 750GB of web page text. The fine-tuning was performed following the …","url":["https://arxiv.org/pdf/2401.02297"]}
-{"year":"2024","title":"Artificial Intelligence for Anesthesiology Board-style Examination Questions: Role of Large Language Models","authors":["AA Khan, R Yunus, M Sohail, TA Rehman, S Saeed… - Journal of Cardiothoracic …, 2024"],"snippet":"Background : New artificial intelligence tools have been developed that have implications for medical usage. Large language models such as the widely used ChatGPT, developed by OpenAI, have not been explored in the context of …","url":["https://www.sciencedirect.com/science/article/pii/S1053077024000909"]}
-{"year":"2024","title":"Artificial Intelligence in the Media Economy: A Systematic Review of Use Cases, Application Potentials, and Challenges of Generative Language Models","authors":["T Prien, K Goldhammer - 2024"],"snippet":"Springer MRW: [AU:, IDX:] Page 1 Artificial Intelligence in the Media Economy: A Systematic Review of Use Cases, Application Potentials, and Challenges of Generative Language Models Tim Prien and Klaus Goldhammer Contents 1 …","url":["https://link.springer.com/content/pdf/10.1007/978-3-658-34048-3_89-1.pdf"]}
-{"year":"2024","title":"Artificial intelligence in the news: how AI retools, rationalizes, and reshapes journalism and the public arena","authors":["F Simon - 2024"],"snippet":"Despite growing interest, the effects of AI on the news industry and our information environment — the public arena — remain poorly understood. Insufficient attention has also been paid to the implications of the news industry’s dependence on …","url":["https://ora.ox.ac.uk/objects/uuid:aeb25013-1d17-40b2-b471-5bdca309db87/files/s4t64gp800"]}
-{"year":"2024","title":"Artificial Intelligence Supporting Independent Student Learning: An Evaluative Case Study of ChatGPT and Learning to Code","authors":["K Hartley, M Hayak, UH Ko - Education Sciences, 2024"],"snippet":"Artificial intelligence (AI) tools like ChatGPT demonstrate the potential to support personalized and adaptive learning experiences. This study explores how ChatGPT can facilitate self-regulated learning processes and learning computer programming …","url":["https://www.mdpi.com/2227-7102/14/2/120"]}
-{"year":"2024","title":"Artificial Intelligence, Large Language Models, and Design Thinking in TPC Classrooms","authors":["C Masters-Wheeler, J Bay, P Sullivan - Programmatic Perspectives, 2023"],"snippet":"… Common Crawl, for instance, is an open repository of web data that is accessible to anyone and can be used to train AI models. Large language models (LLMs) use the textual data from sources like Common Crawl and other freely accessible data …","url":["https://programmaticperspectives.cptsc.org/index.php/jpp/article/download/58/73"]}
-{"year":"2024","title":"Asking GPT for the Ordinary Meaning of Statutory Terms","authors":["C Engel, RH McAdams - MPI Collective Goods Discussion Paper, 2024"],"snippet":"We report on our test of the Large Language Model (LLM) ChatGPT (GPT) as a tool for generating evidence of the ordinary meaning of statutory terms. We explain why the most useful evidence for interpretation involves a distribution of replies rather …","url":["https://pure.mpg.de/rest/items/item_3566108/component/file_3566109/content"]}
-{"year":"2024","title":"Asking Questions Framework for Oral History Archives","authors":["J Švec, M Bulín, A Frémund, F Polák - European Conference on Information Retrieval, 2024"],"snippet":"… The resulting Wav2Vec 2.0 end-to-end model was combined with a lower-case four-gram language model estimated from CommonCrawl data. To decrease the model’s … The model was pre-trained on a self-supervised text-restoration task …","url":["https://link.springer.com/chapter/10.1007/978-3-031-56063-7_11"]}
-{"year":"2024","title":"Assessing and Optimizing Large Language Models on Spondyloarthritis Multi-Choice Question Answering: Protocol for Enhancement and Assessment","authors":["A Wang, Y Wu, X Ji, X Wang, J Hu, F Zhang, Z Zhang… - JMIR Research Protocols, 2024"],"snippet":"Background Spondyloarthritis (SpA), a chronic inflammatory disorder, predominantly impacts the sacroiliac joints and spine, significantly escalating the risk of disability. SpA’s complexity, as evidenced by its diverse clinical presentations and symptoms …","url":["https://www.researchprotocols.org/2024/1/e57001"]}
-{"year":"2024","title":"Assessing the research landscape and clinical utility of large language models: a scoping","authors":["YJ Park, A Pillai, J Deng, E Guo, M Gupta, M Paget… - 2024"],"snippet":"… Introduced in November 2022, ChatGPT was trained using a large corpora of unlabelled text, including CommonCrawl, WebText, and Wikipedia, as well as internet-based book corpora spanning multiple languages [3]. GPT, along with other …","url":["https://bmcmedinformdecismak.biomedcentral.com/counter/pdf/10.1186/s12911-024-02459-6.pdf"]}
-{"year":"2024","title":"Asymmetric Polysemous Reasoning for Image-Text Matching","authors":["H Zhang, M Yang - 2023 IEEE International Conference on Data Mining …, 2023"],"snippet":"Image-text matching has received growing interest since it bridges vision and language. The key challenge lies in how to learn correspondence between image and text. Upon observation, we find existing works suffer from two limitations. Firstly …","url":["https://ieeexplore.ieee.org/abstract/document/10411666/"]}
-{"year":"2024","title":"Asynchronous Local-SGD Training for Language Modeling","authors":["B Liu, R Chhaparia, A Douillard, S Kale, AA Rusu… - arXiv preprint arXiv …, 2024"],"snippet":"Local stochastic gradient descent (Local-SGD), also referred to as federated averaging, is an approach to distributed optimization where each device performs more than one SGD update per communication. This work presents an empirical …","url":["https://arxiv.org/pdf/2401.09135"]}
-{"year":"2024","title":"Atmospheric Limitations for High-frequency Ground-based Very Long Baseline Interferometry","authors":["DW Pesce, L Blackburn, R Chaves, SS Doeleman… - The Astrophysical Journal, 2024"],"snippet":"Very long baseline interferometry (VLBI) provides the highest-resolution images in astronomy. The sharpest resolution is nominally achieved at the highest frequencies, but as the observing frequency increases, so too does the atmospheric contribution …","url":["https://iopscience.iop.org/article/10.3847/1538-4357/ad3961"]}
-{"year":"2024","title":"AtomGPT: Atomistic Generative Pre-trained Transformer for Forward and Inverse Materials Design","authors":["K Choudhary - arXiv preprint arXiv:2405.03680, 2024"],"snippet":"Large language models (LLMs) such as generative pretrained transformers (GPTs) have shown potential for various commercial applications, but their applicability for materials design remains underexplored. In this article, we introduce AtomGPT, a …","url":["https://arxiv.org/pdf/2405.03680"]}
-{"year":"2024","title":"Auditing Large Language Models for Enhanced Text-Based Stereotype Detection and Probing-Based Bias Evaluation","authors":["Z Wu, S Bulathwela, M Perez-Ortiz, AS Koshiyama - arXiv preprint arXiv:2404.01768, 2024"],"snippet":"Recent advancements in Large Language Models (LLMs) have significantly increased their presence in human-facing Artificial Intelligence (AI) applications. However, LLMs could reproduce and even exacerbate stereotypical outputs from …","url":["https://arxiv.org/pdf/2404.01768"]}
-{"year":"2024","title":"Augmenting a Spanish clinical dataset for transformer-based linking of negations and their out-of-scope references","authors":["AJ Tamayo-Herrera, DA Burgos, A Gelbukh - Natural Language Processing"],"snippet":"A negated statement consists of three main components: the negation cue, the negation scope, and the negation reference. The negation cue is the indicator of negation, while the negation scope defines the extent of the negation. The negation …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/AD9F18ADEE45FA58A4041E059E111C52/S2977042424000104a.pdf/augmenting_a_spanish_clinical_dataset_for_transformerbased_linking_of_negations_and_their_outofscope_references.pdf"]}
-{"year":"2024","title":"Augmenting Knowledge-Based Conversational Search Systems With Large Language Models","authors":["M Klettner"],"snippet":"Conversational interfaces are increasingly used by websites and apps, including office software as well as creativity tools. This trend reflects a shift towards natural language in human-computer interaction, which is also facilitated by utilizing Large …","url":["https://wwwmatthes.in.tum.de/file/kuo9al9qqe3h/Sebis-Public-Website/Student-Theses-Guided-Research/Current-Theses-Guided-Researches/Master-s-Thesis-Manuel-Klettner/Klettner_Manuel_MastersThesis.pdf"]}
-{"year":"2024","title":"AutoMathText: Autonomous Data Selection with Language Models for Mathematical Texts","authors":["Y Zhang, Y Luo, Y Yuan, ACC Yao - arXiv preprint arXiv:2402.07625, 2024"],"snippet":"To improve language models' proficiency in mathematical reasoning via continual pretraining, we introduce a novel strategy that leverages base language models for autonomous data selection. Departing from conventional supervised fine-tuning or …","url":["https://arxiv.org/pdf/2402.07625"]}
-{"year":"2024","title":"Automatic Coding of Contingency in Child-Caregiver Conversations","authors":["A Agrawal, M Nikolaus, B Favre, A Fourtassi - 2024"],"snippet":"One of the most important communicative skills children have to learn is to engage in meaningful conversations with people around them. At the heart of this learning lies the mastery of contingency, ie, the ability to contribute to an ongoing exchange …","url":["https://files.osf.io/v1/resources/hwnms/providers/osfstorage/65fc3931d09d170113eee760?action=download&direct&version=1"]}
-{"year":"2024","title":"Automatic Data Curation for Self-Supervised Learning: A Clustering-Based Approach","authors":["HV Vo, V Khalidov, T Darcet, T Moutakanni… - arXiv preprint arXiv …, 2024"],"snippet":"… By filtering Common Crawl data, the authors managed to obtain large datasets to train reliable … To this end, we apply our curation pipeline to two text pools based on Common Crawl. The first … Doing so keeps the original data distribution closer to …","url":["https://arxiv.org/pdf/2405.15613"]}
-{"year":"2024","title":"Automatic detection of hate speech in code-mixed Indian languages in twitter social media interaction using DConvBLSTM-MuRIL ensemble method","authors":["P Kakati, D Dandotiya - Social Network Analysis and Mining, 2024"],"snippet":"… During the pre-training process, 2.5 terabytes of Common Crawl data in 100 languages are used. This model gives a much better performance than multilingual BERT when code-switching, especially for languages with little resources, because …","url":["https://link.springer.com/article/10.1007/s13278-024-01264-3"]}
-{"year":"2024","title":"Automatic Extraction of User-Centric Aspects for Tourist Spot Recommender Systems Using Reviews in Japanese","authors":["F Uwano, R Kobayashi, M Ohta - International Conference on Human-Computer …, 2024"],"snippet":"In tourist reviews, various pieces of information are described to confirm the characteristics of tourist spots. This paper proposes a method to extract tourist spot aspects using Japanese tourist reviews automatically. The aspects of tourist spots …","url":["https://link.springer.com/chapter/10.1007/978-3-031-60125-5_17"]}
-{"year":"2024","title":"Automating Code Adaptation for MLOps--A Benchmarking Study on LLMs","authors":["H Patel, BA Ramanan, MA Khan, T Williams… - arXiv preprint arXiv …, 2024"],"snippet":"This paper explores the possibilities of the current generation of Large Language Models for incorporating Machine Learning Operations (MLOps) functionalities into ML training code bases. We evaluate the performance of OpenAI (gpt-3.5-turbo) and …","url":["https://arxiv.org/pdf/2405.06835"]}
-{"year":"2024","title":"Automating String Encoding in AutoML","authors":["CH Lam"],"snippet":"Automated Machine Learning (AutoML) systems often struggle with data sets with string data. Due to their unstructured nature and dependence on domain knowledge, string data are a frequent cause of errors and coming up with generalized ways of …","url":["https://pure.tue.nl/ws/portalfiles/portal/319777301/Lam_C.pdf"]}
-{"year":"2024","title":"Autonomous Data Selection with Language Models for Mathematical Texts","authors":["Y Zhang, Y Luo, Y Yuan, AC Yao - ICLR 2024 Workshop on Navigating and …, 2024"],"snippet":"To improve language models’ proficiency in mathematical reasoning via continual pretraining, we introduce a novel strategy that leverages base language models for autonomous data selection. Departing from conventional supervised fine-tuning or …","url":["https://openreview.net/pdf?id=bBF077z8LF"]}
-{"year":"2024","title":"BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models","authors":["J Xue, M Zheng, Y Hu, F Liu, X Chen, Q Lou - arXiv preprint arXiv:2406.00083, 2024"],"snippet":"Large Language Models (LLMs) are constrained by outdated information and a tendency to generate incorrect data, commonly referred to as \"hallucinations.\" Retrieval-Augmented Generation (RAG) addresses these limitations by combining …","url":["https://arxiv.org/pdf/2406.00083"]}
-{"year":"2024","title":"Bailong: Bilingual Transfer Learning based on QLoRA and Zip-tie Embedding","authors":["LC Chen, ZR Li - arXiv preprint arXiv:2404.00862, 2024"],"snippet":"… Owing to computational constraints, we further conducted additional sampling of the OSCAR dataset and the Common Crawl dataset to mitigate the issue related to dataset size. In the long run, there are around 13 billion tokens left in the corpus. The …","url":["https://arxiv.org/html/2404.00862v1"]}
-{"year":"2024","title":"Balanced Data Sampling for Language Model Training with Clustering","authors":["Y Shao, L Li, Z Fei, H Yan, D Lin, X Qiu - arXiv preprint arXiv:2402.14526, 2024"],"snippet":"Data plays a fundamental role in the training of Large Language Models (LLMs). While attention has been paid to the collection and composition of datasets, determining the data sampling strategy in training remains an open question. Most …","url":["https://arxiv.org/pdf/2402.14526"]}
-{"year":"2024","title":"Balancing Multilingual Model Training Data Using Exponential Smoothing","authors":["D Kundu - 2023"],"snippet":"… The XLM-R [9] model is pre-trained over a larger common crawl corpus similarly to MBERT, using language sampling according to exponentially-smoothed language probabilities. Again, performance on low-resources tasks seems to benefit …","url":["https://ijsret.com/wp-content/uploads/2023/11/IJSRET_V9_issue6_417.pdf"]}
-{"year":"2024","title":"Bangla Emergency Post Classification on Social Media using Transformer Based BERT Models","authors":["AA Nabil, D Das, MS Salim, S Arifeen, HMA Fattah - 2023 6th International …, 2023"],"snippet":"… It is a large multi-lingual language model trained on 2.5TB of filtered Common Crawl data. XLMRoBERTa is a multilingual model trained in 100 different languages. Unlike some XLM multilingual models, it does not require lang tensors to understand …","url":["https://ieeexplore.ieee.org/abstract/document/10427900/"]}
-{"year":"2024","title":"Benchmarking PathCLIP for Pathology Image Analysis","authors":["S Zheng, X Cui, Y Sun, J Li, H Li, Y Zhang, P Chen… - arXiv preprint arXiv …, 2024"],"snippet":"… All these versions are trained using masked language modeling and next-word prediction techniques with training data sourced from publicly available repositories like Wikipedia, Common Crawl. The results of LLaMA demonstrate that cuttingedge …","url":["https://arxiv.org/pdf/2401.02651"]}
-{"year":"2024","title":"Benchmarking zero-shot stance detection with FlanT5-XXL: Insights from training data, prompting, and decoding strategies into its near-SoTA performance","authors":["R Aiyappa, S Senthilmani, J An, H Kwak, YY Ahn - arXiv preprint arXiv:2403.00236, 2024"],"snippet":"We investigate the performance of LLM-based zero-shot stance detection on tweets. Using FlanT5-XXL, an instruction-tuned open-source LLM, with the SemEval 2016 Tasks 6A, 6B, and P-Stance datasets, we study the performance and its variations …","url":["https://arxiv.org/pdf/2403.00236"]}
-{"year":"2024","title":"BengaliLCP: A Dataset for Lexical Complexity Prediction in the Bengali Texts","authors":["N Ayman, MA Hossain, A Aziz, RU Faruqui, AN Chy - Proceedings of the 2024 Joint …, 2024"],"snippet":"Encountering intricate or ambiguous terms within a sentence produces distress for the reader during comprehension. Lexical Complexity Prediction (LCP) deals with predicting the complexity score of a word or a phrase considering its context. This …","url":["https://aclanthology.org/2024.lrec-main.200.pdf"]}
-{"year":"2024","title":"BERT, RoBERTa or DeBERTa? Comparing Performance Across Transformer Models in Political Science Text","authors":["J Carreras Timoneda, S Vallejo Vera"],"snippet":"Transformer models such as BERT, RoBERTa, and DeBERTa have revolutionized the field of Natural Language Processing in recent years with substantial improvements in the contextual understanding of text. While political scientists have …","url":["https://www.journals.uchicago.edu/doi/pdf/10.1086/730737"]}
-{"year":"2024","title":"BERT, RoBERTa or DeBERTa? Comparing Performance Across Transformers Models in Political Science Text","authors":["JC Timoneda, SV Vera"],"snippet":"Transformer models such as BERT, RoBERTa, and DeBERTa have revolutionized the field of Natural Language Processing in recent years with substantial improvements in the contextual understanding of text. While political scientists have …","url":["https://svallejovera.github.io/files/bert_roberta_jop.pdf"]}
-{"year":"2024","title":"BERTicelli at HaSpeeDe 3: Fine-tuning and Cross-validating Large Language Models for Hate Speech Detection Leonardo Grotti¹², Patrick Quick¹ ¹Universiteit …","authors":["L Grotti¹ - EVALITA Proceedings of the Eighth Evaluation …, 2024"],"snippet":"The present paper describes the results from the experiments carried out for the HaSpeeDe 3 shared task, an Italian-language Hate Speech (HS) detection task, at EVALITA 2023. Two BERT-based language models were selected: UmBERTO (cased) …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=ZLfuEAAAQBAJ&oi=fnd&pg=PA188&dq=commoncrawl&ots=BBnDdqOBAj&sig=H6DFO9BmsqkOJQHbUMkZxiadwmA"]}
-{"year":"2024","title":"BERTs are Generative In-Context Learners","authors":["D Samuel - arXiv preprint arXiv:2406.04823, 2024"],"snippet":"This paper explores the in-context learning capabilities of masked language models, challenging the common view that this ability does not 'emerge' in them. We present an embarrassingly simple inference technique that enables DeBERTa to operate as …","url":["https://arxiv.org/pdf/2406.04823"]}
-{"year":"2024","title":"Beyond Lexical Boundaries: LLM-Generated Text Detection for Romanian Digital Libraries","authors":["M Nitu, M Dascalu - Future Internet, 2024"],"snippet":"Machine-generated content reshapes the landscape of digital information; hence, ensuring the authenticity of texts within digital libraries has become a paramount concern. This work introduces a corpus of approximately 60 k Romanian documents …","url":["https://www.mdpi.com/1999-5903/16/2/41"]}
-{"year":"2024","title":"Beyond Metrics: Evaluating LLMs' Effectiveness in Culturally Nuanced, Low-Resource Real-World Scenarios","authors":["M Ochieng, V Gumma, S Sitaram, J Wang, K Ronen… - arXiv preprint arXiv …, 2024"],"snippet":"The deployment of Large Language Models (LLMs) in real-world applications presents both opportunities and challenges, particularly in multilingual and code-mixed communication settings. This research evaluates the performance of seven leading …","url":["https://arxiv.org/pdf/2406.00343"]}
-{"year":"2024","title":"Beyond Scale: The Diversity Coefficient as a Data Quality Metric for Variability in Natural Language Data","authors":["A Lee, B Miranda, S Sundar, A Casasola, S Koyeyo"],"snippet":"… Since many datasets are publicly available (eg Common Crawl, Wikipedia), data used to train new models may be curated from such … We evaluate on Pile-CC (Pile Common Crawl) and OpenWebText2 since those datasets align with intuitively …","url":["https://openreview.net/pdf?id=tgkWxsOapD"]}
-{"year":"2024","title":"BharatBhasaNet-A unified framework to identify Indian code mix Languages","authors":["S Dey, S Thakur, A Kandwal, R Kumar, S Dasgupta… - IEEE Access, 2024"],"snippet":"In the rapidly globalizing digital communication sphere, the imperative for advanced multilingual text recognition and identification is increasingly evident. Contrasting the previous works, which were predominantly constrained to 2-3 languages, this …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10517602.pdf"]}
-{"year":"2024","title":"Bi-directional GRU-Based Approach for Multi-Class Text Error Identification System","authors":["S Reeha, BV Nikith, GMP Reddy, PB Pati - 2024 IEEE 9th International Conference …, 2024"],"snippet":"… The C4 dataset, utilized in this study, is an extensively cleaned and curated version of Common Crawl's web crawl corpus. Common Crawl is a publicly available dataset accessible at commoncrawl.org. and boasting over 700 million …","url":["https://ieeexplore.ieee.org/abstract/document/10543361/"]}
-{"year":"2024","title":"Big City Bias: Evaluating the Impact of Metropolitan Size on Computational Job Market Abilities of Language Models","authors":["C Campanella, R van der Goot - arXiv preprint arXiv:2403.08046, 2024"],"snippet":"Large language models (LLMs) have emerged as a useful technology for job matching, for both candidates and employers. Job matching is often based on a particular geographic location, such as a city or region. However, LLMs have known …","url":["https://arxiv.org/pdf/2403.08046"]}
-{"year":"2024","title":"Bioeconomy firms and where to find them","authors":["L Kriesch, S Losacker - REGION, 2024"],"snippet":"… This dataset uses the open-source web repository CommonCrawl to identify German company websites and has proven to be a valuable database for spatial research. From this data, we identify bioeconomy firms using a combination of …","url":["https://openjournals.wu-wien.ac.at/ojs/index.php/region/article/view/523/456"]}
-{"year":"2024","title":"BioMedLM: A 2.7 B Parameter Language Model Trained On Biomedical Text","authors":["E Bolton, A Venigalla, M Yasunaga, D Hall, B Xiong… - arXiv preprint arXiv …, 2024"],"snippet":"… The Pile contains multiple sub-corpora, including general content from Common Crawl and specialized content like PubMed, Github, and FreeLaw. This model serves as an important baseline for comparison with our domain-specific models; …","url":["https://arxiv.org/pdf/2403.18421"]}
-{"year":"2024","title":"BIS Papers","authors":["I Aldasoro, S Doerr, L Gambacorta, S Notra, T Oliviero… - 2024"],"snippet":"Generative artificial intelligence (gen AI) introduces novel opportunities to strengthen central banks’ cyber security but also presents new risks. We use data from a unique survey among cyber security experts at major central banks to shed …","url":["https://www.bis.org/publ/bppdf/bispap145.pdf"]}
-{"year":"2024","title":"Botlitica: A generative AI-based tool to assist journalists in navigating political propaganda campaigns","authors":["E Musi, EEG Aguilar, L Federico - Studies in Communication Sciences, 2024"],"snippet":"The hype on generative AI has raised concerns about the spread of disinformation but also opened up new opportunities for hybrid journalism. The proliferation of political propaganda campaigns spread across digital media during election periods …","url":["https://www.hope.uzh.ch/scoms/article/download/4270/4464"]}
-{"year":"2024","title":"Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM","authors":["S Sukhbaatar, O Golovneva, V Sharma, H Xu, XV Lin… - arXiv preprint arXiv …, 2024"],"snippet":"We investigate efficient methods for training Large Language Models (LLMs) to possess capabilities in multiple specialized domains, such as coding, math reasoning and world knowledge. Our method, named Branch-Train-MiX (BTX), starts …","url":["https://arxiv.org/pdf/2403.07816"]}
-{"year":"2024","title":"Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models","authors":["T Blevins, T Limisiewicz, S Gururangan, M Li, H Gonen… - arXiv preprint arXiv …, 2024"],"snippet":"Despite their popularity in non-English NLP, multilingual language models often underperform monolingual ones due to inter-language competition for model parameters. We propose Cross-lingual Expert Language Models (X-ELM), which …","url":["https://arxiv.org/pdf/2401.10440"]}
-{"year":"2024","title":"Bridging large language model disparities: Skill tagging of multilingual educational content","authors":["Y Kwak, ZA Pardos - British Journal of Educational Technology, 2024"],"snippet":"The adoption of large language models (LLMs) in education holds much promise. However, like many technological innovations before them, adoption and access can often be inequitable from the outset, creating more divides than they bridge. In …","url":["https://bera-journals.onlinelibrary.wiley.com/doi/pdf/10.1111/bjet.13465"]}
-{"year":"2024","title":"Bridging the Bosphorus: Advancing Turkish Large Language Models through Strategies for Low-Resource Language Adaptation and Benchmarking","authors":["EC Acikgoz, M Erdogan, D Yuret - arXiv preprint arXiv:2405.04685, 2024"],"snippet":"… This dataset was generated by extracting content from 71 monthly snapshots of the internet via Common Crawl (CC). CulturaX contains version … However, the diversity of these datasets should be sufficient, including common crawl, book …","url":["https://arxiv.org/pdf/2405.04685"]}
-{"year":"2024","title":"Building a Large Japanese Web Corpus for Large Language Models","authors":["N Okazaki, K Hattori, H Shota, H Iida, M Ohi, K Fujii… - arXiv preprint arXiv …, 2024"],"snippet":"… The corpus developed in this study is made from 21 snapshots of Common Crawl (from CC-MAIN-2020-40 to CC-MAIN-2023-23), and the size of the corpus after cleaning is 173,350,375 pages and 312,093,428,689 characters. To confirm the …","url":["https://arxiv.org/pdf/2404.17733"]}
-{"year":"2024","title":"Building Question-Answer Data Using Web Register Identification","authors":["A Eskelinen, A Myntti, E Henriksson, S Pyysalo… - Proceedings of the 2024 …, 2024"],"snippet":"… (2015), is a corpus of Finnish collected between 2015 and 2016 from Common Crawl and by crawling .fi domains. As all of these resources are Common Crawl based, in the post-processing stage we make sure that duplicate QA pairs are …","url":["https://aclanthology.org/2024.lrec-main.234.pdf"]}
-{"year":"2024","title":"By Senior Judge Stephanie Domitrovich and Judge Herbert B. Dixon Jr.","authors":["CJJ Federal Judiciary - Judges Journal, 2024"],"snippet":"… For example, the datasets used to train ChatGPT 3 included text from the following sources: (1) Common Crawl, containing petabytes of data collected from the internet since 2008; (2) WebText2, text from webpages with highly ranked Reddit …","url":["https://heinonline.org/hol-cgi-bin/get_pdf.cgi?handle=hein.journals/judgej63&section=3"]}
-{"year":"2024","title":"Bye-bye Bias: What to Consider When Training Generative AI Models on Subjective Marketing Metrics","authors":["C Schamp - 2024"],"snippet":"… However, these models are trained on vast data sets scraped from the Internet, such as Common Crawl or LAION, that contain little information on the types of perceptual measures marketing is often interested in, such as perceived brand …","url":["https://sciendo.com/pdf/10.2478/nimmir-2024-0007"]}
-{"year":"2024","title":"Cache Me If You Can: The Case For Retrieval Augmentation in Federated Learning","authors":["A Muhamed, P Thaker, MT Diab, V Smith - Privacy Regulation and Protection in Machine …"],"snippet":"We propose retrieval augmentation (RA) as an enhancement to federated learning (FL) that can improve privacy protection and ensure regulatory compliance. FL, primarily designed for data privacy preservation, faces challenges with conventional …","url":["https://openreview.net/pdf?id=MKd1SkDbbz"]}
-{"year":"2024","title":"CAM 2.0: End-to-End Open Domain Comparative Question Answering System","authors":["A Shallouf, H Herasimchyk, M Salnikov, RG Veliz…"],"snippet":"… After extracting objects and aspects, we look for their matches in the Common Crawl text. It is also important to mention, that for the final … (lemmatized) corpus containing 14.3 billion English sentences from the Common Crawl. To retrieve …","url":["https://www.inf.uni-hamburg.de/en/inst/ab/lt/publications/2024-nikishina-cam2.pdf"]}
-{"year":"2024","title":"Can ChatGPT learn Chinese or Swahili? Considering how large language models might act differently if trained in different languages.","authors":["N Savage"],"snippet":"… Thien Nguyen, a professor of computer science at the University of Oregon, looked at the CommonCrawl corpus, a selection of text scraped … Then, because only a small percentage of the CommonCrawl corpus is in Korean, the company …","url":["https://dl.acm.org/doi/full/10.1145/3640351"]}
-{"year":"2024","title":"Can ChatGPT Plan Your Retirement?: Generative AI andFinancial Advice","authors":["AW Lo, J Ross"],"snippet":"We identify some of the most pressing issues facing the adoption of large language models (LLMs) in practical settings, and propose a research agenda to reach the next technological inflection point in generative AI. We focus on three challenges …","url":["https://assets.pubpub.org/z7x033cz/Lo%20&%20Ross%20(2024)_Just%20Accepted-01717176710726.pdf"]}
-{"year":"2024","title":"Can cross-domain term extraction benefit from cross-lingual transfer and nested term labeling?","authors":["HTH Tran, M Martinc, A Repar, N Ljubešić, A Doucet… - Machine Learning, 2024"],"snippet":"Automatic term extraction (ATE) is a natural language processing task that eases the effort of manually identifying terms from domain-specific corpora by providing a list of candidate terms. In this paper, we treat ATE as a sequence-labeling task and …","url":["https://link.springer.com/article/10.1007/s10994-023-06506-7"]}
-{"year":"2024","title":"Cascaded transformer-based networks for wikipedia large-scale image-caption matching","authors":["N Messina, DA Coccomini, A Esuli, F Falchi - Multimedia Tools and Applications, 2024"],"snippet":"… It uses an XLM-RoBERTa masked language model pre-trained on the CommonCrawl dataset and fine-tuned on the image URL-caption match classification task. The CLS token in output from XLM-RoBERTa is attached to a feed-forward …","url":["https://link.springer.com/article/10.1007/s11042-023-17977-0"]}
-{"year":"2024","title":"Causality-driven multivariate stock movement forecasting","authors":["A Díaz Berenguer, Y Da, MN Bossa, MC Oveneke… - PloS one, 2024"],"snippet":"Our study aims to investigate the interdependence between international stock markets and sentiments from financial news in stock forecasting. We adopt the Temporal Fusion Transformers (TFT) to incorporate intra and inter-market …","url":["https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0302197"]}
-{"year":"2024","title":"CC-GPX: Extracting High-Quality Annotated Geospatial Data from Common Crawl","authors":["I Ilyankou, J Haworth, S Cavazzi - arXiv preprint arXiv:2405.11039, 2024"],"snippet":"The Common Crawl (CC) corpus is the largest open web crawl dataset containing 9.5+ petabytes of data captured since 2008. The dataset is instrumental in training large language models, and as such it has been studied for (un)desirable content ���","url":["https://arxiv.org/pdf/2405.11039"]}
-{"year":"2024","title":"CCSUM: A large-scale and high-quality dataset for abstractive news summarization","authors":["X Jiang, M Dreyer - 2024"],"snippet":"… Accordingly, among 35 million CommonCrawl News articles, we identify pairs of articles about the same news story and use one article’s first sentence as the summary for the other article. To ensure high quality, we apply strict filters whose …","url":["https://www.amazon.science/publications/ccsum-a-large-scale-and-high-quality-dataset-for-abstractive-news-summarization"]}
-{"year":"2024","title":"CERM: Context-aware Literature-based Discovery via Sentiment Analysis","authors":["JC Young, U Akujuobi - arXiv preprint arXiv:2402.01724, 2024"],"snippet":"Driven by the abundance of biomedical publications, we introduce a sentiment analysis task to understand food-health relationship. Prior attempts to incorporate health into recipe recommendation and analysis systems have primarily focused on …","url":["https://arxiv.org/pdf/2402.01724"]}
-{"year":"2024","title":"Challenge design roadmap","authors":["HJE Balderas, I Guyon, A Howard, W Reade, S Treguer - AI Competitions and …, 2023"],"snippet":"Challenges can be seen as a type of game that motivates participants to solve serious tasks. As a result, competition organizers must develop effective game rules. However, these rules have multiple objectives beyond making the game enjoyable …","url":["https://hal.science/hal-04333280/document"]}
-{"year":"2024","title":"Chatbots in Airport Customer Service—Exploring Use Cases and Technology Acceptance","authors":["I Auer, S Schlögl, G Glowka - Future Internet, 2024"],"snippet":"… Those pre-trained transformer systems like BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformer) have been trained on vast language corpora such as Wikipedia and Common Crawl …","url":["https://www.mdpi.com/1999-5903/16/5/175/pdf"]}
-{"year":"2024","title":"ChatGPT Alternative Solutions: Large Language Models Survey","authors":["H Alipour, N Pendar, K Roy - arXiv preprint arXiv:2403.14469, 2024"],"snippet":"In recent times, the grandeur of Large Language Models (LLMs) has not only shone in the realm of natural language processing but has also cast its brilliance across a vast array of applications. This remarkable display of LLM capabilities has ignited a …","url":["https://arxiv.org/pdf/2403.14469"]}
-{"year":"2024","title":"ChatGPT and GPT-4: utilities in the legal sector","authors":["FJ Dosal Gómez, J Nieto Galende - 2024"],"snippet":"Artificial intelligence systems such as ChatGPT, the OpenAI chatbot, based on the language model family GPT (generative pre-trained transformers), as well as other solutions built on this technology and fine-tuned for specific tasks, have generated …","url":["https://www.tecnologia-ciencia-educacion.com/index.php/TCE/article/download/19081/21543/46195"]}
-{"year":"2024","title":"ChatGPT and Language Translation: A Small Case Study Evaluating English–Mandarin Translation","authors":["C Woodrum - International Conference on Human-Computer …, 2024"],"snippet":"… has been informed speculation that it relies heavily on common crawl [13], a compendium of publicly available … common crawl. The \\(15^{th}\\) most common language, Indonesian, makes up less than 1% of the data set [14, 15]. It is important …","url":["https://link.springer.com/chapter/10.1007/978-3-031-60615-1_10"]}
-{"year":"2024","title":"ChatGPT as the Marketplace of Ideas: Should Truth-Seeking Be the Goal of AI Content Governance?","authors":["J Zhang - arXiv preprint arXiv:2405.18636, 2024"],"snippet":"As one of the most enduring metaphors within legal discourse, the marketplace of ideas has wielded considerable influence over the jurisprudential landscape for decades. A century after the inception of this theory, ChatGPT emerged as a …","url":["https://arxiv.org/pdf/2405.18636"]}
-{"year":"2024","title":"ChatGPT in Cyber Onslaught and Fortification: Past, Present, and Future","authors":["M Gunda, V Manda, P Naradasu, S Mekala… - 2024 IEEE 9th International …, 2024"],"snippet":"… GPT-1 was unveiled in 2018 and trained on a pair of data sets: over 11,000 books from Book Corpus and the enormous Common Crawl … With 1.5 billion features and a much more extensive and diversified training dataset comprising Common Crawl …","url":["https://ieeexplore.ieee.org/abstract/document/10543384/"]}
-{"year":"2024","title":"ChatGPT versus NASS clinical guidelines for degenerative spondylolisthesis: a comparative analysis","authors":["W Ahmed, M Saturno, R Rajjoub, AH Duey, B Zaidat… - European Spine Journal, 2024"],"snippet":"… Furthermore, the largest dataset used to train both ChatGPT 3.5 and 4.0 is CommonCrawl, a platform that does not include PubMed and consists predominantly of open access articles, some of which may be of less rigorous if not …","url":["https://link.springer.com/article/10.1007/s00586-024-08198-6"]}
-{"year":"2024","title":"ChatGPT vs Gemini vs LLaMA on Multilingual Sentiment Analysis","authors":["A Buscemi, D Proverbio - arXiv preprint arXiv:2402.01715, 2024"],"snippet":"… It relied on a dataset referred to as the Common Crawl [30], a publicly accessible repository that comprises billions of web pages, making it one of the most extensive text databases available. It is important to note that the choice of dataset significantly …","url":["https://arxiv.org/pdf/2402.01715"]}
-{"year":"2024","title":"ChatGPT's applications in marketing: a topic modeling approach","authors":["W Tafesse, A Wien - Marketing Intelligence & Planning, 2024"],"snippet":"Purpose ChatGPT is a versatile technology with practical use cases spanning many professional disciplines including marketing. Being a recent innovation, however, there is a lack of academic insight into its tangible applications in the marketing …","url":["https://www.emerald.com/insight/content/doi/10.1108/MIP-10-2023-0526/full/html"]}
-{"year":"2024","title":"ChatGPT-3.5 can create and justify short Afrikaans poems: Implications for practice","authors":["CJ van Staden - Suid-Afrikaanse Tydskrif vir Natuurwetenskap en …, 2024"],"snippet":"ChatGPT-3.5 can create poems but the implications thereof has not yet been sufficiently investigated. The purpose of this explorative case study was to determine to which extent ChatGPT-3.5 can create and justify Afrikaans poems. Because …","url":["https://journals.co.za/doi/abs/10.36303/SATNT.2024.43.1.973"]}
-{"year":"2024","title":"ChatQA: Building GPT-4 Level Conversational QA Models","authors":["Z Liu, W Ping, R Roy, P Xu, M Shoeybi, B Catanzaro - arXiv preprint arXiv …, 2024"],"snippet":"… We collect 7k documents (average ∼1k words per document) from common crawl, which cover a wide range of domains. Each document is used for generation of a single conversational QA sample, which leads to a total of 7k multi-turn QA dialogues …","url":["https://arxiv.org/pdf/2401.10225"]}
-{"year":"2024","title":"Cheap Learning: Maximising Performance of Language Models for Social Data Science Using Minimal Data","authors":["L Castro-Gonzalez, YL Chung, HR Kirk, J Francis… - arXiv preprint arXiv …, 2024"],"snippet":"The field of machine learning has recently made significant progress in reducing the requirements for labelled training data when building new models. These `cheaper' learning techniques hold significant potential for the social sciences, where …","url":["https://arxiv.org/pdf/2401.12295"]}
-{"year":"2024","title":"Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model","authors":["X Du, Z Yu, S Gao, D Pan, Y Cheng, Z Ma, R Yuan… - arXiv preprint arXiv …, 2024"],"snippet":"In this study, we introduce CT-LLM, a 2B large language model (LLM) that illustrates a pivotal shift towards prioritizing the Chinese language in developing LLMs. Uniquely initiated from scratch, CT-LLM diverges from the conventional …","url":["https://arxiv.org/pdf/2404.04167"]}
-{"year":"2024","title":"CLAPNQ: Cohesive Long-form Answers from Passages in Natural Questions for RAG systems","authors":["S Rosenthal, A Sil, R Florian, S Roukos - arXiv preprint arXiv:2404.02103, 2024"],"snippet":"… However, they use sentencelevel matching (by encoding sentences for semantic similarity comparisons) to retrieve up to top 7 documents from Common Crawl while avoiding exact matches as the abstractive dataset. In the extractive version, the …","url":["https://arxiv.org/pdf/2404.02103"]}
-{"year":"2024","title":"CLASSLA-web: Comparable Web Corpora of South Slavic Languages Enriched with Linguistic and Genre Annotation","authors":["N Ljubešić, T Kuzman - arXiv preprint arXiv:2403.12721, 2024"],"snippet":"This paper presents a collection of highly comparable web corpora of Slovenian, Croatian, Bosnian, Montenegrin, Serbian, Macedonian, and Bulgarian, covering thereby the whole spectrum of official languages in the South Slavic language space …","url":["https://arxiv.org/pdf/2403.12721"]}
-{"year":"2024","title":"Cleaner Pretraining Corpus Curation with Neural Web Scraping","authors":["Z Xu, Z Liu, Y Yan, Z Liu, C Xiong, G Yu - arXiv preprint arXiv:2402.14652, 2024"],"snippet":"… The web-crawled datasets, such as Common Crawl, have been widely used for pretraining, facilitating the development of language … htmlparser serves as the text pre-extraction tool for CommonCrawl6 WET file (containing pre-extracted text), while …","url":["https://arxiv.org/html/2402.14652v1"]}
-{"year":"2024","title":"CLEARNESS: Coreference Resolution for Generating and Ranking Arguments Extracted from Debate Portals for Queries","authors":["J Weidmann, L Dumani, R Schenkel - 2023"],"snippet":"… Refining Arg-CTRL with data from Common Crawl leads to a higher quality of generated arguments compared to using user discussions from Reddit comments. In the mentioned studies, new arguments are generated through the use of knowledge …","url":["https://ceur-ws.org/Vol-3630/LWDA2023-paper15.pdf"]}
-{"year":"2024","title":"CLIP and the City: Addressing the Artificial Encoding of Cities in Multimodal Foundation Deep Learning Models","authors":["DN del Castillo, I Neri"],"snippet":"In this project, we propose and explore a computational pipeline to examine urban cultural landscapes through the lens of artificial intelligence, and for questioning modes of embedding culture in machine learning models. By employing machine …","url":["https://www.strand.rs/publishing/2023/OA2023_proceedings_p100.pdf"]}
-{"year":"2024","title":"Co-constructing AI Authoring Using Ethical Theories","authors":["B Jones - 88th Annual International Conference"],"snippet":"We must show ethical humility, historically contextualizing ethical standards, as we implement AI tools in courses. The pace of change requires agile approaches to defining standards for the ethical use of AI. We invited students to co-construct a …","url":["https://researchmap.jp/hiroyuki-london/published_papers/45908700/attachment_file.pdf#page=218"]}
-{"year":"2024","title":"CoastTerm: a Corpus for Multidisciplinary Term Extraction in Coastal Scientific Literature","authors":["J Delaunay, HTH Tran, CE González-Gallardo… - arXiv preprint arXiv …, 2024"],"snippet":"… – Multilingual pre-trained model: We opt for XLMR [9], a transformer-based model pre-trained on 2.5TB of filtered CommonCrawl data containing 100 languages. This multilingual version of RoBERTa, achieves benchmark performance in ATE for rich-resourced …","url":["https://arxiv.org/pdf/2406.09128"]}
-{"year":"2024","title":"Comparative Study on Synthetic and Natural Error Analysis with BART & MarianMT","authors":["R Rohit, SA Gandheesh, GS Sannala, PB Pati - 2024 IEEE 9th International …, 2024"],"snippet":"Text is essential for communication, information sharing, knowledge acquisition, and analysis. It shapes public opinion, supports education, and drives online content, making it crucial in various domains. While there are various language models …","url":["https://ieeexplore.ieee.org/abstract/document/10543923/"]}
-{"year":"2024","title":"Comparing Bad Apples to Good Oranges: Aligning Large Language Models via Joint Preference Optimization","authors":["H Bansal, A Suvarna, G Bhatt, N Peng, KW Chang… - arXiv preprint arXiv …, 2024"],"snippet":"A common technique for aligning large language models (LLMs) relies on acquiring human preferences by comparing multiple generations conditioned on a fixed context. This only leverages the pairwise comparisons when the generations are …","url":["https://arxiv.org/html/2404.00530v1"]}
-{"year":"2024","title":"Comparing Explanation Faithfulness between Multilingual and Monolingual Fine-tuned Language Models","authors":["Z Zhao, N Aletras - arXiv preprint arXiv:2403.12809, 2024"],"snippet":"In many real natural language processing application scenarios, practitioners not only aim to maximize predictive performance but also seek faithful explanations for the model predictions. Rationales and importance distribution given by feature …","url":["https://arxiv.org/pdf/2403.12809"]}
-{"year":"2024","title":"Comparing Foundations: Insights into the Construction of Financial Causal Knowledge Graphs with and without Ontology","authors":["Z Xu, R Ichise - 人工知能学会全国大会論文集 第 38 回 (2024), 2024"],"snippet":"Simplicity in information navigation, interpretation, and reasoning has positioned mono-relation knowledge graphs (KGs) as a focus of attention, particularly in targeted scenarios. However, their deficiency in hierarchical interactions between …","url":["https://www.jstage.jst.go.jp/article/pjsai/JSAI2024/0/JSAI2024_2Q5IS102/_pdf"]}
-{"year":"2024","title":"Comparing generative and retrieval-based chatbots in answering patient questions regarding age-related macular degeneration and diabetic retinopathy","authors":["KX Cheong, C Zhang, TE Tan, BJ Fenner, WM Wong… - British Journal of …, 2024"],"snippet":"… ChatGPT was trained on multiple extremely large datasets, of which Common Crawl (open repository of web crawl data) constituted the bulk of the datasets.30 31 Google Bard was trained on Infiniset (data comprising public forum dialogue …","url":["https://bjo.bmj.com/content/early/2024/05/15/bjo-2023-324533.abstract"]}
-{"year":"2024","title":"Compass: Large Multilingual Language Model for South-east Asia","authors":["S Maria - arXiv preprint arXiv:2404.09220, 2024"],"snippet":"… We categorized these sources into seven types: CommonCrawl, C4, Wikipedia, WebText, Academic, Books, and Code. We upsampled and … We expect that the introduction of biases may originate from CommonCrawl, as this substantial dataset …","url":["https://arxiv.org/pdf/2404.09220"]}
-{"year":"2024","title":"Compilation of a Synthetic Judeo-French Corpus","authors":["I Nikolova-Stoupak, G Lejeune, E Schaeffer-Lacroix - Proceedings of the 8th Joint …, 2024"],"snippet":"This is a short paper describing the process of derivation of synthetic Judeo-French text. Judeo-French is one of a number of rare languages used in speaking and writing by Jewish communities as confined to a particular temporal and …","url":["https://aclanthology.org/2024.latechclfl-1.5.pdf"]}
-{"year":"2024","title":"Compositional Text-to-Image Generation with Dense Blob Representations","authors":["W Nie, S Liu, M Mardani, C Liu, B Eckart, A Vahdat - arXiv preprint arXiv:2405.08246, 2024"],"snippet":"Existing text-to-image models struggle to follow complex text prompts, raising the need for extra grounding inputs for better controllability. In this work, we propose to decompose a scene into visual primitives - denoted as dense blob representations …","url":["https://arxiv.org/pdf/2405.08246"]}
-{"year":"2024","title":"Comprehensive analysis of natural language processing","authors":["RK Yadav, A Madaan - Global Journal of Engineering and Technology …, 2024"],"snippet":"… Huge datasets like the Penn Treebank and the Common Crawl drove the development of more sophisticated NLP models. Transfer learning techniques like BERT enabled finetuning of pre-trained models for specific tasks. TensorFlow and …","url":["http://gjeta.com/sites/default/files/GJETA-2024-0058.pdf"]}
-{"year":"2024","title":"COMPREHENSIVE STUDY OF CLINICAL ENTITY EXTRACTION AND CLASSIFICATION USING LARGE LANGUAGE MODELS","authors":["M Faedi, P Torroni, DA Galassi, DG Grundler…"],"snippet":"This project aims to evaluate various techniques for extraction and categorization of clinical terms in unstructured documents. The purpose of this study is to assist automated systems operating in the biomedical domain by highlighting relevant …","url":["https://amslaurea.unibo.it/30623/1/Tesi_MicheleFaedi.pdf"]}
-{"year":"2024","title":"Compressing Lengthy Context With UltraGist","authors":["P Zhang, Z Liu, S Xiao, N Shao, Q Ye, Z Dou - arXiv preprint arXiv:2405.16635, 2024"],"snippet":"Compressing lengthy context is a critical but technically challenging problem. In this paper, we propose a new method called UltraGist, which is distinguished for its high-quality compression of lengthy context due to the innovative design of the compression and …","url":["https://arxiv.org/pdf/2405.16635"]}
-{"year":"2024","title":"Compression Represents Intelligence Linearly","authors":["Y Huang, J Zhang, Z Shan, J He - arXiv preprint arXiv:2404.09937, 2024"],"snippet":"… Concretely, for assessing knowledge and commonsense, we have compiled texts from the latest Common Crawl dataset. To evaluate coding ability, we have sourced data from GitHub repositories mainly on the Python language since the downstream …","url":["https://arxiv.org/pdf/2404.09937"]}
-{"year":"2024","title":"Computational criminology: at-scale quantitative analysis of the evolution of cybercrime forums","authors":["J Hughes - 2024"],"snippet":"Cybercrime forums and marketplaces are used by members to share hacking techniques, general community-building discussions, and trade hacking tools. While there is a large corpus of literature studying these platforms, from a cross-forum …","url":["https://www.repository.cam.ac.uk/bitstreams/0b5dcda3-56e5-4f29-8d3e-e9aecb2b95dc/download"]}
-{"year":"2024","title":"Computerized diagnostic decision support systems–a comparative performance study of Isabel Pro vs. ChatGPT4","authors":["JM Bridges - Diagnosis, 2024"],"snippet":"… ChatGPT4 is trained on Common Crawl, a publicly available dataset and one of the most extensive text datasets. While not trained explicitly for medical diagnosis, ChatGPT4 accesses medical textbooks, medical websites, medical papers, and …","url":["https://www.degruyter.com/document/doi/10.1515/dx-2024-0033/html"]}
-{"year":"2024","title":"Comquest: an Adaptive Crawler for User Comments on the Web","authors":["Z Chen - 2024"],"snippet":"This thesis introduces Comquest, an adaptive framework designed for the large-scale collection and integration of user comments from the Web. User comments are featured on many websites and there is growing interest in mining and studying user …","url":["https://scholarshare.temple.edu/bitstream/handle/20.500.12613/10236/Chen_temple_0225E_15673.pdf?sequence=1&isAllowed=y"]}
-{"year":"2024","title":"Comquest: Large Scale User Comment Crawling and Integration","authors":["Z Chen, L He, A Mukherjee, E Dragut - 2024"],"snippet":"… To train the model, we collect an extensive dataset from the Common Crawl Project. We filter the webpages that show apparent code signals (eg, loading the commenting system libraries) of the supported commenting systems. …","url":["https://www.researchgate.net/profile/Zhijia-Chen-3/publication/379953271_Comquest_Large_Scale_User_Comment_Crawling_and_Integration/links/6622cba3f7d3fc28746df7e6/Comquest-Large-Scale-User-Comment-Crawling-and-Integration.pdf"]}
-{"year":"2024","title":"Considering the Role of Fairness in Copyright Fair Use","authors":["B Rosenblatt - Houston Law Review, 2023"],"snippet":"Moral intuitions regarding when it is \"fair\" to engage in unauthorized copying or derivation from a copyrighted work may often take into account factors that the fair use statute, 17 USC § 107, does not enumerate among fair use considerations. This …","url":["https://houstonlawreview.org/article/92123-considering-the-role-of-fairness-in-copyright-fair-use"]}
-{"year":"2024","title":"Construction of Text Summarization Corpus in Economics Domain and Baseline Models","authors":["S Jumpathong, A Takhom, P Boonkwan… - 2024"],"snippet":"… It was pre-trained with a data collection of 101 languages from Common Crawl Due to time and resource constraints, we chose mT5-small… It was pre-trained with a data collection of 101 languages from Common Crawl. Due to time and resource …","url":["https://www.jicce.org/journal/view.html?uid=1254&vmd=Full"]}
-{"year":"2024","title":"Context-aware Transliteration of Romanized South Asian Languages","authors":["C Kirov, C Johny, A Katanova, A Gutkin, B Roark - Computational Linguistics, 2024"],"snippet":"While most transliteration research is focused on single tokens such as named entities – eg, transliteration of “અમદાવાદ” from the Gujarati script to the Latin script “Ahmedabad” – the informal romanization prevalent in South Asia and elsewhere …","url":["https://direct.mit.edu/coli/article-pdf/doi/10.1162/coli_a_00510/2213805/coli_a_00510.pdf"]}
-{"year":"2024","title":"Contextual Chart Generation for Cyber Deception","authors":["DD Nguyen, D Liebowitz, S Nepal, SS Kanhere… - arXiv preprint arXiv …, 2024"],"snippet":"… (1) HPN-T5 is based on Text-to-Text Transfer Transformer (T5) [42], a highly scalable sequence-to-sequence Transformer pre-trained on a large corpus harvested from Common Crawl. T5 introduced a novel pre-training objective that …","url":["https://arxiv.org/pdf/2404.04854"]}
-{"year":"2024","title":"Contextual Word Embedding for Biomedical Knowledge Extraction: a Rapid Review and Case Study","authors":["D Vithanage, P Yu, L Wang, C Deng - Journal of Healthcare Informatics Research, 2024"],"snippet":"Recent advancements in natural language processing (NLP), particularly contextual word embedding models, have improved knowledge extraction from biomedical and healthcare texts. However, limited comprehensive research compares these models …","url":["https://link.springer.com/article/10.1007/s41666-023-00157-y"]}
-{"year":"2024","title":"Contextually Enriched Meta-Learning Ensemble Model for Urdu Sentiment Analysis Symmetry 2023, 15, 645","authors":["K Ahmed, MI Nadeem, D Li, Z Zheng, N Al-Kahtani… - 2023"],"snippet":"… On the other hand, this model makes use of pre-trained word vectors that were trained on “common crawl” and “Wikipedia” through the use of the fastText model [82]. The CBOW algorithm with position-weighting is used to train this word vector. After …","url":["https://www.academia.edu/download/101809833/symmetry-15-00645-v2.pdf"]}
-{"year":"2024","title":"Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities","authors":["K Fujii, T Nakamura, M Loem, H Iida, M Ohi, K Hattori… - arXiv preprint arXiv …, 2024"],"snippet":"Cross-lingual continual pre-training of large language models (LLMs) initially trained on English corpus allows us to leverage the vast amount of English language resources and reduce the pre-training cost. In this study, we constructed Swallow, an …","url":["https://arxiv.org/pdf/2404.17790"]}
-{"year":"2024","title":"Controllable Sentence Simplification in Dutch","authors":["T Seidl, V Vandeghinste - Computational Linguistics in the Netherlands Journal, 2024"],"snippet":"Text simplification aims to reduce complexity in vocabulary and syntax, enhancing the readability and comprehension of text. This paper presents a supervised sentence simplification approach for Dutch using a pre-trained large language …","url":["https://clinjournal.org/clinj/article/download/171/184"]}
-{"year":"2024","title":"Controllable Sentence Simplification in Swedish Using Control Prefixes and Mined Paraphrases","authors":["J Monsen, A Jönsson - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"… 2020), an opensource repository with tools to download and clean Common Crawl snapshots. Each file in the CC-100 corpus contains … The Common Crawl snapshots contain a large portion of low-quality data, including offensive and …","url":["https://aclanthology.org/2024.lrec-main.349.pdf"]}
-{"year":"2024","title":"Copilot for Microsoft 365: A Comprehensive End-user Training Plan for Organizations","authors":["M Kytö - 2024"],"snippet":"This thesis presents a comprehensive end user training plan for Copilot for Microsoft 365, a generative AI tool that integrates with Microsoft’s productivity suite of applications. The research is conducted within the context of Sulava Ltd., a Finnish …","url":["https://www.theseus.fi/bitstream/handle/10024/852578/Kyto_Miska.pdf?sequence=2"]}
-{"year":"2024","title":"Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implications","authors":["X Guo, Y Li, Y Peng, X Wei - arXiv preprint arXiv:2402.12216, 2024"],"snippet":"As AIGC has impacted our society profoundly in the past years, ethical issues have received tremendous attention. The most urgent one is the AIGC copyright dilemma, which can immensely stifle the development of AIGC and greatly cost the entire …","url":["https://arxiv.org/pdf/2402.12216"]}
-{"year":"2024","title":"CoRePooL—Corpus for Resource‐Poor Languages: Badaga Speech Corpus","authors":["HB Barathi Ganesh, G Jyothish Lal, R Jairam… - … Speech Recognition and …, 2024"],"snippet":"This chapter presents a corpus named CoRePooL that stands for Corpus for Resource‐Poor Languages. As voice‐specific human‐machine interaction applications are accelerated by deep learning algorithms, the lack of resources …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394214624.ch10"]}
-{"year":"2024","title":"Corpus Considerations for Annotator Modeling and Scaling","authors":["OO Sarumi, B Neuendorf, J Plepi, L Flek, J Schlötterer… - arXiv preprint arXiv …, 2024"],"snippet":"Recent trends in natural language processing research and annotation tasks affirm a paradigm shift from the traditional reliance on a single ground truth to a focus on individual perspectives, particularly in subjective tasks. In scenarios where …","url":["https://arxiv.org/html/2404.02340v1"]}
-{"year":"2024","title":"CorpusNÓS: A massive Galician corpus for training large language models","authors":["I de-Dios-Flores, SP Suárez, CC Pérez, DB Outeiriño… - Proceedings of the 16th …, 2024"],"snippet":"CorpusNÓS is a massive Galician corpus made up of 2.1 B words primarily devised for training large language models. The corpus sources are varied and represent a relatively wide range of genres. CorpusNÓS is, to the best of our knowledge, the …","url":["https://aclanthology.org/2024.propor-1.66.pdf"]}
-{"year":"2024","title":"Counter (media) Intelligence and Visioning: An Interview with Adam Harvey","authors":["A Harvey, PB Smith"],"snippet":"… Among the largest and most popular datasets used in AI research projects are Common Crawl (for NLP), and ImageNet and COCO (for computer vision), which are all derived from user-generated content. In my research project Exposing.ai, I’ve …","url":["https://salford-repository.worktribe.com/preview/2389095/Counter%28media%29%20Visioning%20and%20AI%20Harvey%20and%20Smith.pdf"]}
-{"year":"2024","title":"Creating Ad Campaigns Using Generative AI Check for updates","authors":["A Bulut, B Arslan - Applications of Generative AI"],"snippet":"Search campaigns consist of ad groups. An ad group contains a related set of keywords and ads. During an online campaign, search advertisers experiment with different marketing messages such as subtle vs. strong being used in ad copies, with …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=61_8EAAAQBAJ&oi=fnd&pg=PA23&dq=commoncrawl&ots=nk-w5Z-zal&sig=6KV6RzRkuWAeVreoPJlrVlxbFNU"]}
-{"year":"2024","title":"Creating Ad Campaigns Using Generative AI","authors":["A Bulut, B Arslan - Applications of Generative AI, 2024"],"snippet":"… In particular, T5 and PEGASUS models were trained on 750 GB of English-language text from the public Common Crawl web scrape while the BART model was trained on the CNN/Daily Mail dataset, which contains roughly 300K unique news articles …","url":["https://link.springer.com/chapter/10.1007/978-3-031-46238-2_2"]}
-{"year":"2024","title":"Creating Parallel Corpora for Ukrainian: a German-Ukrainian Parallel Corpus (ParaRook|| DE-UK)","authors":["M Shvedova, A Lukashevskyi - Proceedings of the Third Ukrainian Natural Language …, 2024"],"snippet":"Parallel corpora are currently a popular and vibrantly developing category of linguistic resources, used both in literature and translation studies, as well as in the field of NLP. For Ukrainian, though, there are still not enough significant parallel …","url":["https://aclanthology.org/2024.unlp-1.3.pdf"]}
-{"year":"2024","title":"CroissantLLM: A Truly Bilingual French-English Language Model","authors":["M Faysse, P Fernandes, N Guerreiro, A Loison, D Alves… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce CroissantLLM, a 1.3B language model pretrained on a set of 3T English and French tokens, to bring to the research and industrial community a high-performance, fully open-sourced bilingual model that runs swiftly on consumer-grade local …","url":["https://arxiv.org/pdf/2402.00786"]}
-{"year":"2024","title":"Cross-cultural Inspiration Detection and Analysis in Real and LLM-generated Social Media Data","authors":["O Ignat, GG Lakshmy, R Mihalcea - arXiv preprint arXiv:2404.12933, 2024"],"snippet":"Inspiration is linked to various positive outcomes, such as increased creativity, productivity, and happiness. Although inspiration has great potential, there has been limited effort toward identifying content that is inspiring, as opposed to just engaging …","url":["https://arxiv.org/pdf/2404.12933"]}
-{"year":"2024","title":"Cross-Language Harmonization of Linguistic Resources","authors":["D Zeman"],"snippet":"The presented work consists of two parts. In the first part I summarize the main directions of my research since the defense of my PhD thesis in 2005. I start with cross-language transfer of parsing models to languages that have little or no …","url":["https://chres.is.cuni.cz/media/documents/2024/02/25/thesis-without-papers.pdf"]}
-{"year":"2024","title":"Cross-Lingual Cross-Modal Retrieval with Noise-Robust Fine-Tuning","authors":["R Cai, J Dong, T Liang, Y Liang, Y Wang, X Yang… - IEEE Transactions on …, 2024"],"snippet":"… from snapshots of the CommonCrawl public dataset2. Experiments in this paper concern parallel data between English and other four languages, namely Chinese (ZH), French (FR), German (DE) and Czech (CZ). Evaluation metrics. … https://commoncrawl.org/ …","url":["https://www.computer.org/csdl/journal/tk/5555/01/10530137/1WUyX1bSatO"]}
-{"year":"2024","title":"Cross-lingual Editing in Multilingual Language Models","authors":["H Beniwal, M Singh - arXiv preprint arXiv:2401.10521, 2024"],"snippet":"The training of large language models (LLMs) necessitates substantial data and computational resources, and updating outdated LLMs entails significant efforts and resources. While numerous model editing techniques (METs) have emerged to …","url":["https://arxiv.org/pdf/2401.10521"]}
-{"year":"2024","title":"Cyber Risks of Machine Translation Critical Errors: Arabic Mental Health Tweets as a Case Study","authors":["H Saadany, A Tantawy, C Orasan - arXiv preprint arXiv:2405.11668, 2024"],"snippet":"With the advent of Neural Machine Translation (NMT) systems, the MT output has reached unprecedented accuracy levels which resulted in the ubiquity of MT tools on almost all online platforms with multilingual content. However, NMT systems, like …","url":["https://arxiv.org/pdf/2405.11668"]}
-{"year":"2024","title":"Data Augmentation and Large Language Model for Legal Case Retrieval and Entailment","authors":["MQ Bui, DT Do, NK Le, DH Nguyen, KVH Nguyen… - The Review of Socionetwork …, 2024"],"snippet":"The Competition on Legal Information Extraction and Entailment (COLIEE) is a well-known international competition organized each year with the goal of applying machine learning algorithms and techniques in the analysis and understanding of legal …","url":["https://link.springer.com/article/10.1007/s12626-024-00158-2"]}
-{"year":"2024","title":"Data augmentation for language generation inspired by machine translation","authors":["P Chen - 2024"],"snippet":"The field of natural language processing has witnessed a surge in the adoption of deep learning, which faces notable hurdles when the training data is scarce. This thesis aims to study automatic data augmentation for language generation tasks …","url":["https://era.ed.ac.uk/bitstream/handle/1842/41873/Chen2024.pdf?sequence=1&isAllowed=y"]}
-{"year":"2024","title":"Data Augmentation with Semantic Enrichment for Deep Learning Invoice Text Classification","authors":["WW Chi, TY Tang, NM Salleh, M Mukred, H AlSalman… - IEEE Access, 2024"],"snippet":"Natural language processing (NLP) is a research field that provides huge potential to automate accounting tasks dealing with text data. This research studies the application of NLP in automatically categorizing invoices based on the invoice text …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10496671.pdf"]}
-{"year":"2024","title":"Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?","authors":["S Longpre, R Mahari, N Obeng-Marnu, W Brannon… - arXiv preprint arXiv …, 2024"],"snippet":"… Common Crawl is accurate with wide coverage, but not detailed. Hugging Face can be inaccurate with varying levels of detail, but it has extensive coverage. The Data Provenance Initiative is highly accurate and detailed but is currently limited in scope. …","url":["https://arxiv.org/pdf/2404.12691"]}
-{"year":"2024","title":"Data Collection Pipeline for Low-Resource Languages: A Case Study on Constructing a Tetun Text Corpus","authors":["G de Jesus, SS Nunes - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"This paper proposes Labadain Crawler, a data collection pipeline tailored to automate and optimize the process of constructing textual corpora from the web, with a specific target to low-resource languages. The system is built on top of Nutch, an …","url":["https://aclanthology.org/2024.lrec-main.390.pdf"]}
-{"year":"2024","title":"Data Engineering for Scaling Language Models to 128K Context","authors":["Y Fu, R Panda, X Niu, X Yue, H Hajishirzi, Y Kim… - arXiv preprint arXiv …, 2024"],"snippet":"We study the continual pretraining recipe for scaling language models' context lengths to 128K, with a focus on data engineering. We hypothesize that long context modeling, in particular \\textit{the ability to utilize information at arbitrary input …","url":["https://arxiv.org/pdf/2402.10171"]}
-{"year":"2024","title":"Data Mixing Made Efficient: A Bivariate Scaling Law for Language Model Pretraining","authors":["C Ge, Z Ma, D Chen, Y Li, B Ding - arXiv preprint arXiv:2405.14908, 2024"],"snippet":"Large language models exhibit exceptional generalization capabilities, primarily attributed to the utilization of diversely sourced data. However, conventional practices in integrating this diverse data heavily rely on heuristic schemes, lacking …","url":["https://arxiv.org/pdf/2405.14908"]}
-{"year":"2024","title":"Data-Centric Methods for Decentralizing Large Language Models","authors":["S Gururangan - 2024"],"snippet":"… from large web crawl services like Common Crawl. Web crawl is perceived to be wholly representative of activity on the Internet [Brügger… Indeed, web dumps like Common Crawl offer the promise of more diverse text than what is available in …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/51332/Gururangan_washington_0250E_26513.pdf?sequence=1&isAllowed=y"]}
-{"year":"2024","title":"DataComp Challenge","authors":["D Brunner - 2023"],"snippet":"… billion sample image-text dataset filtered from a comparable pool of samples to Common Crawl. For the creation of the LAION-2B dataset, first language filtering is applied to the original Common Crawl pool so that only samples with English texts …","url":["https://pub.tik.ee.ethz.ch/students/2023-HS/GA-2023-09.pdf"]}
-{"year":"2024","title":"Dataset Decomposition: Faster LLM Training with Variable Sequence Length Curriculum","authors":["H Pouransari, CL Li, JHR Chang, PKA Vasu, C Koc… - arXiv preprint arXiv …, 2024"],"snippet":"… Although the benefits of ICLM with large-scale Common Crawl data (used in our experiments) are marginal in regular evaluation, it significantly boosts long-context evaluation metrics from 27.5 to 28.7 by constructing long data sequences through …","url":["https://arxiv.org/pdf/2405.13226"]}
-{"year":"2024","title":"Dataset Growth","authors":["Z Qin, Z Xu, Y Zhou, Z Zheng, Z Cheng, H Tang… - arXiv preprint arXiv …, 2024"],"snippet":"Deep learning benefits from the growing abundance of available data. Meanwhile, efficiently dealing with the growing data scale has become a challenge. Data publicly available are from different sources with various qualities, and it is …","url":["https://arxiv.org/pdf/2405.18347"]}
-{"year":"2024","title":"Datasets for Large Language Models: A Comprehensive Survey","authors":["Y Liu, J Cao, C Liu, K Ding, L Jin - arXiv preprint arXiv:2402.18041, 2024"],"snippet":"… The first method involves building upon Common Crawl1. Common Crawl is a massive, unstructured, multilingual web corpus that provides public access to web archives by regularly crawling and storing webpage data from the Internet. However …","url":["https://arxiv.org/pdf/2402.18041"]}
-{"year":"2024","title":"Dataverse: Open-Source ETL (Extract, Transform, Load) Pipeline for Large Language Models","authors":["H Park, S Lee, G Gim, Y Kim, D Kim, C Park - arXiv preprint arXiv:2403.19340, 2024"],"snippet":"To address the challenges associated with data processing at scale, we propose Dataverse, a unified open-source Extract-Transform-Load (ETL) pipeline for large language models (LLMs) with a user-friendly design at its core. Easy addition of …","url":["https://arxiv.org/pdf/2403.19340"]}
-{"year":"2024","title":"Dated Data: Tracing Knowledge Cutoffs in Large Language Models","authors":["J Cheng, M Marone, O Weller, D Lawrie, D Khashabi… - arXiv preprint arXiv …, 2024"],"snippet":"… Our analysis reveals two reasons for these inconsistencies: (1) temporal biases of CommonCrawl data due to non-trivial amounts of old data in new dumps and (2) complications in LLM deduplication schemes involving semantic duplicates and …","url":["https://arxiv.org/pdf/2403.12958"]}
-{"year":"2024","title":"DE-COP: Detecting Copyrighted Content in Language Models Training Data","authors":["AV Duarte, X Zhao, AL Oliveira, L Li - arXiv preprint arXiv:2402.09910, 2024"],"snippet":"How can we detect if copyrighted content was used in the training process of a language model, considering that the training data is typically undisclosed? We are motivated by the premise that a language model is likely to identify verbatim …","url":["https://arxiv.org/pdf/2402.09910"]}
-{"year":"2024","title":"Dear GPT-3: Collaborative Writing with Neural Networks","authors":["J Becker - Artificial Intelligence-Intelligent Art?: Human-Machine …, 2024"],"snippet":"GPT-3 and I engaged in this dialogue about four months ago. I wanted to develop a collaborative writing project, not only to collectively realise a novel, but also to negotiate poetological questions which might arise during the process. These …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=gDoGEQAAQBAJ&oi=fnd&pg=PA189&dq=commoncrawl&ots=SRY3txNCwF&sig=VbXixnNRFp15ZSTcqSY4fdZnrCA"]}
-{"year":"2024","title":"DeBERTa-BiLSTM: A multi-label classification model of arabic medical questions using pre-trained models and deep learning","authors":["BS Al-Smadi - Computers in Biology and Medicine, 2024"],"snippet":"… Using data from CommonCrawl in 100 different languages, the authors in [38] introduce XLM-RoBERTa, an advanced masked multilingual language model. XLM-RoBERTa outperformed previous multilingual models such as XLM and mBERT. [39] …","url":["https://www.sciencedirect.com/science/article/pii/S0010482524000052"]}
-{"year":"2024","title":"Deconstructing In-Context Learning: Understanding Prompts via Corruption","authors":["N Shivagunde, V Lialin, S Muckatira, A Rumshisky - arXiv preprint arXiv:2404.02054, 2024"],"snippet":"The ability of large language models (LLMs) to \"learn in context\" based on the provided prompt has led to an explosive growth in their use, culminating in the proliferation of AI assistants such as ChatGPT, Claude, and Bard. These AI …","url":["https://arxiv.org/pdf/2404.02054"]}
-{"year":"2024","title":"Deep learning aided clinical decision support","authors":["R Schneider - 2023"],"snippet":"Medical professionals create vast amounts of clinical texts during patient care. Often, these documents describe medical cases from anamnesis to the final clinical outcome. Automated understanding and selection of relevant medical records pose …","url":["https://elib.uni-stuttgart.de/bitstream/11682/13875/1/20231204%20Thesis%20Deep%20Learning%20aided%20Clinical%20Decision%20Support.pdf"]}
-{"year":"2024","title":"Deep Learning Based Multi-document Summarization","authors":["C Ma - 2024"],"snippet":"In this era of rapidly advancing technology, the exponential increase of data availability makes analyzing and understanding text files a tedious, labor-intensive, and time-consuming task. Multi-document summarization (MDS) is an effective tool …","url":["https://digital.library.adelaide.edu.au/dspace/bitstream/2440/140499/1/Ma2024_PhD.pdf"]}
-{"year":"2024","title":"Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook","authors":["X Zou, Y Yan, X Hao, Y Hu, H Wen, E Liu, J Zhang, Y Li… - arXiv preprint arXiv …, 2024"],"snippet":"As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for sustainable development by harnessing the power of cross-domain data fusion from diverse sources (eg, geographical, traffic, social media, and environmental data) …","url":["https://arxiv.org/pdf/2402.19348"]}
-{"year":"2024","title":"Deep Learning Model for Tamil Part-of-Speech Tagging","authors":["H Visuwalingam, R Sakuntharaj, J Alawatugoda… - The Computer Journal, 2024"],"snippet":"… These pre-trained word embeddings are trained on Common Crawl and Wikipedia. This model was trained using CBOW with position-weights, in dimension 300, with character n-grams of length 5, a window of size 5 and 10 negatives. …","url":["https://academic.oup.com/comjnl/advance-article/doi/10.1093/comjnl/bxae033/7641754"]}
-{"year":"2024","title":"DeepSeek LLM: Scaling Open-Source Language Models with Longtermism","authors":["X Bi, D Chen, G Chen, S Chen, D Dai, C Deng, H Ding… - arXiv preprint arXiv …, 2024"],"snippet":"… Our analysis revealed that deduplicating the entire Common Crawl corpus results in higher removal of duplicate instances compared to deduplicating within a single dump. Table 1 illustrates that deduplicating across 91 dumps eliminates four times …","url":["https://arxiv.org/pdf/2401.02954"]}
-{"year":"2024","title":"DeepSeek-VL: Towards Real-World Vision-Language Understanding","authors":["H Lu, W Liu, B Zhang, B Wang, K Dong, B Liu, J Sun… - arXiv preprint arXiv …, 2024"],"snippet":"We present DeepSeek-VL, an open-source Vision-Language (VL) Model designed for real-world vision and language understanding applications. Our approach is structured around three key dimensions: We strive to ensure our data is diverse …","url":["https://arxiv.org/pdf/2403.05525"]}
-{"year":"2024","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","authors":["Z Shao, P Wang, Q Zhu, R Xu, J Song, M Zhang, YK Li… - arXiv preprint arXiv …, 2024"],"snippet":"… the DeepSeekMath Corpus from Common Crawl. As depicted in Figure 2, … Common Crawl, we employ URL-based deduplication and near-deduplication techniques, resulting in 40B HTML web pages. We then recall mathematical web …","url":["https://arxiv.org/pdf/2402.03300"]}
-{"year":"2024","title":"Deliverable 3.1: WP3 1st Interim technical report","authors":["A May-Wachowius–UC, A Lintulampi–UC…"],"snippet":"1.1. Background This document is the first Interim Technical Report (deliverable 3.1) prepared within the WP3 New usecases for the ESSnet Trusted Smart Statistics–Web Intelligence Network project (ESSnet TSS-WIN). The report covers the period from …","url":["https://cros.ec.europa.eu/system/files/2023-12/wp3_deliverable_3_1_wp3_1st_interim_technical_report_20220330.pdf"]}
-{"year":"2024","title":"Design of Artificial Intelligence Companion Chatbot","authors":["X Chen, J Kang, C Hu"],"snippet":"With the development of cities and the prevalence of networks, interpersonal relationships have become increasingly distant. When people crave communication, they hope to find someone to confide in. With the rapid advancement of deep …","url":["https://cdn.techscience.cn/files/jnm/2024/TSP_JNM-6/TSP_JNM_45833/TSP_JNM_45833.pdf"]}
-{"year":"2024","title":"Design, Implementation and Evaluation of a Chatbot for Accounting Firm: A Fine-Tuning Approach With Two Novel Dataset","authors":["M Basilico - 2024"],"snippet":"Artificial intelligence, particularly in the field of Chatbots, is fundamentally reshaping learning, communication, and work paradigms. This phenomenon has sparked growing interest among businesses, viewing Chatbots as a means to streamline …","url":["https://webthesis.biblio.polito.it/secure/31058/1/tesi.pdf"]}
-{"year":"2024","title":"Designing a course for pre-service science teachers using ChatGPT: what ChatGPT brings to the table","authors":["HZ Okulu, N Muslu - Interactive Learning Environments, 2024"],"snippet":"ChatGPT holds significant potential for enhancing learning through integration into education as an advanced chatbot. With the goal of harnessing this potential, our research focused on exploring the utilization of ChatGPT in designing a course plan …","url":["https://www.tandfonline.com/doi/abs/10.1080/10494820.2024.2322462"]}
-{"year":"2024","title":"Designing an Intelligent System to Map Global Connections","authors":["E Bellamy, K Farrell, A Hopping, J Pinter, M Saju… - 2024"],"snippet":"… Extended Abstract: This study develops a knowledge graph from the Common Crawl News Dataset to provide situational awareness and … We developed a data pipeline to extract semantic content from the Common Crawl News feed and filter it …","url":["https://www.ieworldconference.org/content/WP2024/Papers/GDRKMCC24_2.pdf"]}
-{"year":"2024","title":"Designing and developing a dedicated Natural Language Processing Framework for Healthcare Information Technology Management and Assessment","authors":["A Luschi - 2024"],"snippet":"The escalating complexity of the hospital environment, propelled by technological advancements, necessitates a comprehensive exploration of the integration and management of diverse tools and technologies in healthcare settings. In this context …","url":["https://flore.unifi.it/bitstream/2158/1353284/1/Luschi_PhD_Thesis.pdf"]}
-{"year":"2024","title":"Designing Heterogeneous LLM Agents for Financial Sentiment Analysis","authors":["F Xing - arXiv preprint arXiv:2401.05799, 2024"],"snippet":"… GPT-3.5 was trained mainly on the Common Crawl corpus [2], which archives the web. BLOOMZ was trained on an even larger Open-science Open-collaboration Text Sources corpus [19], which is mainly crowd-sourced scientific datasets. The five …","url":["https://arxiv.org/pdf/2401.05799"]}
-{"year":"2024","title":"Detecting Dementia from Transcribed Speech in Slovak using Pre-trained BERT Models","authors":["J Staš, D Hládek, A Kopnický - 2024 34th International Conference Radioelektronika …, 2024"],"snippet":"… TB of texts written in 100 languages from the Common Crawl dataset [14]; • RemBERT model6: a Rebalanced multilingual BERT model pre-trained on a large unlabeled text created by the combination of mC4 Common Crawl and Wikipedia …","url":["https://ieeexplore.ieee.org/abstract/document/10524067/"]}
-{"year":"2024","title":"Detecting Hidden Meaning in Stock Images","authors":["P Sülzle"],"snippet":"OBJECTIVE − Automated extraction of hidden meaning in stock images− Is it possible to distinguish what is shown from what is meant?− Examine the divergence of text and image− Analyze the usage of stock images and textual descriptions on the web …","url":["https://downloads.webis.de/theses/slides/suelzle_2023.pdf"]}
-{"year":"2024","title":"Detection of Hate Speech and Offensive Language CodeMix Text in Dravidian Languages using Cost-Sensitive Learning Approach","authors":["K Sreelakshmi, B Premjith, BR Chakravarthi… - IEEE Access, 2024"],"snippet":"… It was trained using more than two terabytes of filtered CommonCrawl data. It has significantly improved performance on various cross-lingual transfer tasks and outperformed the mBERT model. XLM-R has 24 layers and 16 attention heads …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10419328.pdf"]}
-{"year":"2024","title":"Detection of phishing addresses and pages with a data set balancing approach by generative adversarial network (GAN) and convolutional neural network (CNN) …","authors":["S Jafari, N Aghaee‐Maybodi - Concurrency and Computation: Practice and …"],"snippet":"Phishing attacks have a remarkable ability to steal user information by using simple techniques. Phishing attacks steal valuable information, such as user names and passwords. The loss caused by phishing attacks is significant, and every year …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.8033"]}
-{"year":"2024","title":"Detection of Sarcasm in Urdu Tweets using Deep Learning and Transformer based Hybrid Approaches","authors":["ME Hassan, M Hussain, I Maab, U Habib, MA Khan… - IEEE Access, 2024"],"snippet":"Sarcasm has a significant role in human communication especially on social media platforms where users express their sentiments through humor, satire, and criticism. The identification of sarcasm is crucial in comprehending the sentiment and the …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10508575.pdf"]}
-{"year":"2024","title":"Detection of Twitter Spam Using GLoVe Vocabulary Features, Bidirectional LSTM and Convolution Neural Network","authors":["P Manasa, A Malik, I Batra - SN Computer Science, 2024"],"snippet":"… The training of the GloVe model involves a substantial text corpus, like Wikipedia or Common Crawl, which facilitates the learning of connections between words and phrases. For every word in the corpus, the model creates a vector, wherein each …","url":["https://link.springer.com/article/10.1007/s42979-023-02518-1"]}
-{"year":"2024","title":"Developing ChatGPT for Biology and Medicine: A Complete Review of Biomedical Question Answering","authors":["Q Li, L Li, Y Li - arXiv preprint arXiv:2401.07510, 2024"],"snippet":"ChatGPT explores a strategic blueprint of question answering (QA) in delivering medical diagnosis, treatment recommendations, and other healthcare support. This is achieved through the increasing incorporation of medical domain data via natural …","url":["https://arxiv.org/pdf/2401.07510"]}
-{"year":"2024","title":"Development and Evaluation of a German Language Model for the Financial Domain","authors":["N Kozaeva, S Hamotskyi, C Hänig - Proceedings of the Joint Workshop of the 7th …, 2024"],"snippet":"… The German colossal, cleaned Common Crawl corpus15 was employed, comprising texts of varying lengths. Further the results of LM performance for mixed datasets (financial corpus mixed with common language sentences and financial …","url":["https://aclanthology.org/2024.finnlp-1.5.pdf"]}
-{"year":"2024","title":"Development and Evaluation of Pre-trained Language Models for Historical Danish and Norwegian Literary Texts","authors":["A Al-Laith, A Conroy, J Bjerring-Hansen… - Proceedings of the 2024 …, 2024"],"snippet":"We develop and evaluate the first pre-trained language models specifically tailored for historical Danish and Norwegian texts. Three models are trained on a corpus of 19th-century Danish and Norwegian literature: two directly on the corpus with no …","url":["https://aclanthology.org/2024.lrec-main.431.pdf"]}
-{"year":"2024","title":"Diagonalization & Forcing FLEX: From Cantor to Cohen and Beyond","authors":["E Moritz - 2024"],"snippet":"Background: Maybe very high energy cosmic radiation started a synaptic butterfly cascade 2... who knows? For one reason or another, I decided to embark on a journey of exploring and discussing the possible role of Artificial Intelligence (AI) on …","url":["https://www.researchgate.net/profile/Elan-Moritz/publication/379960940_Diagonalization_Forcing_FLEX_From_Cantor_to_Cohen_and_Beyond_Alt_Title_Learning_from_Leibniz_Cantor_Turing_Godel_and_Cohen_crawling_towards_AGI/links/662498f743f8df018d1e5573/Diagonalization-Forcing-FLEX-From-Cantor-to-Cohen-and-Beyond-Alt-Title-Learning-from-Leibniz-Cantor-Turing-Goedel-and-Cohen-crawling-towards-AGI.pdf"]}
-{"year":"2024","title":"Differentially Private Low-Rank Adaptation of Large Language Model Using Federated Learning","authors":["XY Liu, R Zhu, D Zha, J Gao, S Zhong, M Qiu - arXiv preprint arXiv:2312.17493, 2023"],"snippet":"The surge in interest and application of large language models (LLMs) has sparked a drive to fine-tune these models to suit specific applications, such as finance and medical science. However, concerns regarding data privacy have emerged …","url":["https://arxiv.org/pdf/2312.17493"]}
-{"year":"2024","title":"Digital Threats","authors":["S Samtani, E Raff, H Anderson, E Domschot… - 2024"],"snippet":"… First, we used the common crawl GloVe embedding, created by Stanford [28]. This embedding was trained over 42 billion tokens, with a 300-dimensional vector space, and was used as the embedding layer of the BiLSTM model. Results are …","url":["https://dl.acm.org/doi/pdf/10.1145/3613525"]}
-{"year":"2024","title":"DiPaCo: Distributed Path Composition","authors":["A Douillard, Q Feng, AA Rusu, A Kuncoro, Y Donchev… - arXiv preprint arXiv …, 2024"],"snippet":"Progress in machine learning (ML) has been fueled by scaling neural network models. This scaling has been enabled by ever more heroic feats of engineering, necessary for accommodating ML approaches that require high bandwidth …","url":["https://arxiv.org/html/2403.10616v1"]}
-{"year":"2024","title":"Disambiguating Homographs and Homophones Simultaneously: A Regrouping Method for Japanese","authors":["Y Sato - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"We present a method that re-groups surface forms into clusters representing synonyms, and help disambiguate homographs as well as homophone. The method is applied post-hoc to trained contextual word embeddings. It is beneficial to …","url":["https://aclanthology.org/2024.lrec-main.442.pdf"]}
-{"year":"2024","title":"Disambiguating natural language via aligning meaningful descriptions","authors":["Y Xin - 2023"],"snippet":"Artificial Intelligence (AI) technologies are increasingly pervading aspects of our lives. Because people use natural language to communicate with each other, computers should also use natural language to communicate with us. One of the principal …","url":["https://open.bu.edu/bitstream/handle/2144/48024/Xin_bu_0017E_17540.pdf?sequence=6"]}
-{"year":"2024","title":"Display options","authors":["Z Zhai, C Druckenbrodt, C Thorne"],"snippet":"Chemical patents are a commonly used channel for disclosing novel compounds and reactions, and hence represent important resources for chemical and pharmaceutical research. Key chemical data in patents is often presented in tables …","url":["https://www.uiindex.org/search/articledetails/32298116"]}
-{"year":"2024","title":"Dissecting Whiteness: consistencies and differences in the stereotypes of lower-and upper-class White US Americans","authors":["T Morgenroth, CT Begeny, TA Kirby, B Paaßen, Y Zeng - Self and Identity, 2024"],"snippet":"Economic inequality is increasing in the United States, making categorization and stereotyping based on social class more likely. Yet, social class stereotypes have received relatively little attention. Focusing on spontaneously generated stereotypes …","url":["https://www.tandfonline.com/doi/abs/10.1080/15298868.2024.2322179"]}
-{"year":"2024","title":"Distance Comparison Operators for Approximate Nearest Neighbor Search: Exploration and Benchmark","authors":["Z Wang, H Xiong, Z He, P Wang - arXiv preprint arXiv:2403.13491, 2024"],"snippet":"Approximate nearest neighbor search (ANNS) on high-dimensional vectors has become a fundamental and essential component in various machine learning tasks. Prior research has shown that the distance comparison operation is the bottleneck of …","url":["https://arxiv.org/html/2403.13491v1"]}
-{"year":"2024","title":"Do Language Models Care About Text Quality? Evaluating Web-Crawled Corpora Across 11 Languages","authors":["R van Noord, T Kuzman, P Rupnik, N Ljubešić… - arXiv preprint arXiv …, 2024"],"snippet":"… rest of corpora compared in this paper, MaCoCu corpora are not obtained by processing Common Crawl data. Instead, a strategy consisting of crawling relevant internet top-level domains directly for the targeted languages is followed (eg, .al for …","url":["https://arxiv.org/pdf/2403.08693"]}
-{"year":"2024","title":"Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks","authors":["TY Chang, J Thomason, R Jia"],"snippet":"The concept of localization in LLMs is often mentioned in prior work; however, methods for localization have never been systematically and directly evaluated. We propose two complementary benchmarks that evaluate the ability of localization …","url":["https://terarachang.github.io/assests/loc.pdf"]}
-{"year":"2024","title":"Do not shut up and do dribble: social media and TV consumption","authors":["M Pazzona, N Spagnolo - Journal of Population Economics, 2024"],"snippet":"… Footnote 11 The NLP model utilized in this study, XLM-RoBERTa, undergoes pre-training on 2.5TB of filtered CommonCrawl data encompassing 100 languages. For tweet classification, we employed the general-purpose Python library TweetNLP (Camacho-Collados …","url":["https://link.springer.com/article/10.1007/s00148-024-01034-7"]}
-{"year":"2024","title":"Does Lack of Knowledge and Hardship of Information Access Signify Powerful AI? A Large Language Model Perspective","authors":["IA Zahid, SS Joudar - Applied Data Science and Analysis, 2023"],"snippet":"Large Language Models (LLMs) are evolving and expanding enormously. With the consistent improvement of LLMs, more complex and sophisticated tasks will be tackled. Handling various tasks and fulfilling different queries will be more precise …","url":["https://journals.mesopotamian.press/index.php/ADSA/article/download/235/211"]}
-{"year":"2024","title":"Does the Language Matter? Curriculum Learning over Neo-Latin Languages","authors":["G Pucci, L Ranaldi - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"Curriculum Learning (CL) is emerging as a relevant technique to reduce the cost of pre-training Large Language Models. The idea, tested for the English language, is to train LLMs by organizing training examples from the simplest to the most complex …","url":["https://aclanthology.org/2024.lrec-main.464.pdf"]}
-{"year":"2024","title":"Does your data spark joy? Performance gains from domain upsampling at the end of training","authors":["C Blakeney, M Paul, BW Larsen, S Owen, J Frankle - arXiv e-prints, 2024"],"snippet":"Pretraining datasets for large language models (LLMs) have grown to trillions of tokens composed of large amounts of CommonCrawl (CC) web scrape along with smaller, domain-specific datasets. It is expensive to understand the impact of these …","url":["https://ui.adsabs.harvard.edu/abs/2024arXiv240603476B/abstract"]}
-{"year":"2024","title":"Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research","authors":["L Soldaini, R Kinney, A Bhagia, D Schwenk, D Atkinson… - arXiv preprint arXiv …, 2024"],"snippet":"… In total, we find 0.02% of documents in the 25 Common Crawl snapshots match this filter. … Head, Middle, and Tail parts of our Common Crawl data. The correlation is computed for 24M, … The correlation among the documents flagged for removal …","url":["https://arxiv.org/pdf/2402.00159"]}
-{"year":"2024","title":"DPHANet: Discriminative Parallel and Hierarchical Attention Network for Natural Language Video Localization","authors":["R Chen, J Tan, Z Yang, X Yang, Q Dai, Y Cheng, L Lin - IEEE Transactions on …, 2024"],"snippet":"Natural Language Video Localization (NLVL) has recently attracted much attention because of its practical significance. However, the existing methods still face the following challenges: 1) When the models learn intra-modal semantic association …","url":["https://ieeexplore.ieee.org/abstract/document/10517423/"]}
-{"year":"2024","title":"Dr. Nahid Ebrahimi Majd","authors":["R Ferdaws - 2024"],"snippet":"The issue of web phishing attacks has been more prevalent in recent years, and phishing is one of the riskiest online crimes that can have disastrous consequences. The aim of phishing is to collect confidential information by tricking a target and …","url":["https://scholarworks.calstate.edu/downloads/s1784t388"]}
-{"year":"2024","title":"DrawL: Understanding the Effects of Non-Mainstream Dialects in Prompted Image Generation","authors":["JN Williams, M FitzMorris, O Aka, S Laszlo - arXiv preprint arXiv:2405.05382, 2024"],"snippet":"… Stable Diffusion is trained in part using the LAION-5B dataset [50], which consists of text-image pairs from Common CrawlCommon Crawl includes archived data from a large variety of sources, including sites such as Reddit and a variety of blogs …","url":["https://arxiv.org/pdf/2405.05382"]}
-{"year":"2024","title":"DrBenchmark: A Large Language Understanding Evaluation Benchmark for French Biomedical Domain","authors":["Y Labrak, A Bazoge, OE Khettari, M Rouvier, N Grabar… - arXiv preprint arXiv …, 2024"],"snippet":"The biomedical domain has sparked a significant interest in the field of Natural Language Processing (NLP), which has seen substantial advancements with pre-trained language models (PLMs). However, comparing these models has proven …","url":["https://arxiv.org/pdf/2402.13432"]}
-{"year":"2024","title":"DsDm: Model-Aware Dataset Selection with Datamodels","authors":["L Engstrom, A Feldmann, A Madry - arXiv preprint arXiv:2401.12926, 2024"],"snippet":"When selecting data for training large-scale models, standard practice is to filter for examples that match human notions of data quality. Such filtering yields qualitatively clean datapoints that intuitively should improve model behavior. However, in …","url":["https://arxiv.org/pdf/2401.12926"]}
-{"year":"2024","title":"Dual Modalities of Text: Visual and Textual Generative Pre-training","authors":["Y Chai, Q Liu, J Xiao, S Wang, Y Sun, H Wu - arXiv preprint arXiv:2404.10710, 2024"],"snippet":"… Meanwhile, The C4 dataset represents a substantial refinement of the Common Crawl corpus. This dataset, derived from the extensive Common Crawl web scrape, undergoes rigorous cleaning and preprocessing to ensure the quality and relevance …","url":["https://arxiv.org/pdf/2404.10710"]}
-{"year":"2024","title":"Dynamic Few-shot Learning for Computational Social Science","authors":["R Malla, TG Coan, V Srinivasan, C Boussalis"],"snippet":"Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP) and have recently demonstrated remarkable potential in social science research through their capacity to efficiently perform a wide range of text-as-data tasks …","url":["https://files.osf.io/v1/resources/nfhe8/providers/osfstorage/65c1f35335be200988a501a7?action=download&direct&version=1"]}
-{"year":"2024","title":"Easy Problems That LLMs Get Wrong","authors":["S Williams, J Huckle - arXiv preprint arXiv:2405.19616, 2024"],"snippet":"We introduce a comprehensive Linguistic Benchmark designed to evaluate the limitations of Large Language Models (LLMs) in domains such as logical reasoning, spatial intelligence, and linguistic understanding, among others. Through a series of …","url":["https://arxiv.org/pdf/2405.19616"]}
-{"year":"2024","title":"Echoes of culture: Relationships of implicit and explicit attitudes with contemporary English, historical English, and 53 non-English languages","authors":["TES Charlesworth, K Morehouse, V Rouduri… - Social Psychological and …, 2024"],"snippet":"Attitudes are intertwined with culture and language. But to what extent? Emerging perspectives in attitude research suggest that cultural representations in language are more related to implicitly measured (vs. explicitly measured) attitudes, and that …","url":["https://journals.sagepub.com/doi/abs/10.1177/19485506241256400"]}
-{"year":"2024","title":"Efficiency Comparison of Dataset Generated by LLMs using Machine Learning Algorithms","authors":["P Pawade, M Kulkarni, S Naik, A Raut, KS Wagh - 2024 International Conference on …, 2024"],"snippet":"… • Bing Chat was trained on web text data, including Common Crawl, Wikipedia, news articles, social media posts, and other publicly available text, via a technique called denoising autoencoder (DAE). In DAE, the model is given a noisy version of a …","url":["https://ieeexplore.ieee.org/abstract/document/10497340/"]}
-{"year":"2024","title":"Efficient learning in spiking neural networks","authors":["A Rast, MA Aoun, EG Elia, N Crook - Neurocomputing, 2024"],"snippet":"… Training data required is similarly massive: the CommonCrawl dataset is 242 TB in size, and hyperparameter tuning remains an expensive, search-based process that can require ∼ 1000 − 10 , 000 + sweeps. After evaluating a number of possible …","url":["https://www.sciencedirect.com/science/article/pii/S0925231224007331"]}
-{"year":"2024","title":"Efficient Model-Relational Data Management: Challenges and Opportunities","authors":["V Sanca, A Ailamaki - IEEE Transactions on Knowledge and Data …, 2024"],"snippet":"As modern data pipelines continue to collect, produce, and store various data formats, extracting and combining value from traditional and context-rich sources becomes unsuitable for RDBMS. To tap into the dark data, domain experts analyze …","url":["https://ieeexplore.ieee.org/abstract/document/10488724/"]}
-{"year":"2024","title":"Efficient Training and Inference: Techniques for Large Language Models Using Llama","authors":["SR Cunningham, D Archambault, A Kung"],"snippet":"… The training dataset consisted of a mixture of the Common Crawl, Wikipedia, and BooksCorpus datasets, encompassing a diverse range of linguistic structures and vocabularies. For evaluation, the GLUE benchmark suite was utilized, providing a …","url":["https://www.techrxiv.org/doi/pdf/10.36227/techrxiv.171651876.65094225"]}
-{"year":"2024","title":"Eliciting Big Five Personality Traits in Large Language Models: A Textual Analysis with Classifier-Driven Approach","authors":["A Hilliard, C Munoz, Z Wu, AS Koshiyama - arXiv preprint arXiv:2402.08341, 2024"],"snippet":"… GPT-3 followed, with 175 billion parameters and training on datasets like Common Crawl [15]. GPT-3.5 Turbo was introduced to enhance real-time performance, and the latest, GPT-4, boasts 1.76 trillion parameters and capabilities …","url":["https://arxiv.org/pdf/2402.08341"]}
-{"year":"2024","title":"EMBA: Entity Matching using Multi-Task Learning of BERT with Attention-over-Attention","authors":["J Zhang, H Sun, JC Ho - 2024"],"snippet":"… The WDC Product Data Corpus for Large-scale Product Matching [34], was built by extracting product offers from Common Crawl. The WDC datasets serve as a popular benchmark and have been used for evaluation in DITTO, JointBERT, and …","url":["https://openproceedings.org/2024/conf/edbt/paper-76.pdf"]}
-{"year":"2024","title":"Embedding-based Query Spelling Correction","authors":["I Zelch, G Lahmann, M Hagen - 2024"],"snippet":"For many retrieval systems, correcting spelling errors in the queries that searchers submit is an essential step of query understanding. Inspired by a blog post on spelling correction from 2018, we implement and analyze a simple embedding-based …","url":["https://downloads.webis.de/publications/papers/zelch_2024b.pdf"]}
-{"year":"2024","title":"Emergent Abilities in Reduced-Scale Generative Language Models","authors":["S Muckatira, V Deshpande, V Lialin, A Rumshisky - arXiv preprint arXiv:2404.02204, 2024"],"snippet":"Large language models can solve new tasks without task-specific fine-tuning. This ability, also known as in-context learning (ICL), is considered an emergent ability and is primarily seen in large language models with billions of parameters. This …","url":["https://arxiv.org/html/2404.02204v1"]}
-{"year":"2024","title":"Emerging AI Tools for Education and Research: Perspective and Policies for IISc","authors":["GJ OC, AK CSA, V Kumar, YN CSA…"],"snippet":"The Director, IISc, constituted a committee on August 21, 2023 with the following mandate:(a) Explore the challenges and benefits of emerging AI tools in the context of academic teaching and learning,(b) provide guidance and recommendations to …","url":["https://iisc.ac.in/wp-content/uploads/2024/03/Report-of-Committee-on-AI-Tools-for-Education-and-Research.pdf"]}
-{"year":"2024","title":"Emotional significance in Cross-Cultural Semantic Crossmodal Correspondences","authors":["J Alvarado - Proceedings of the Annual Meeting of the Cognitive …, 2024"],"snippet":"Crossmodal correspondences are associations between perceptual features from different senses that aid in crossmodal binding. The semantic coding of these correspondences is expected to capture and mediate the emergence of perceptual …","url":["https://escholarship.org/content/qt2sc9n8q9/qt2sc9n8q9.pdf"]}
-{"year":"2024","title":"Employing Siamese MaLSTM Model and ELMO Word Embedding for Quora Duplicate Questions Detection","authors":["A Altamimi, M Umer, D Hanif, S Alsubai, TH Kim… - IEEE Access, 2024"],"snippet":"… 3) FastText Subword FastText Subword comprises a collection of 2 million word vectors trained on the Common Crawl dataset, which consists of a massive 600 billion tokens. In contrast to traditional word embeddings, sub-word embeddings …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10440276.pdf"]}
-{"year":"2024","title":"Empowering hate speech detection: leveraging linguistic richness and deep learning","authors":["IGBJ Abasan, EB Setiawan - Bulletin of Electrical Engineering and Informatics, 2024"],"snippet":"… What they don’t realize is the use of pre-trained models, namely CommonCrawl and Wiki, in extraction using FastText or GloVe. The pre-trained model used is not specific for hate speech detection and, of course, consists of many languages, and …","url":["https://www.beei.org/index.php/EEI/article/download/6938/3660"]}
-{"year":"2024","title":"Enabling action crossmodality for a pretrained large language model","authors":["A Caesar, O Özdemir, C Weber, S Wermter - Natural Language Processing Journal, 2024"],"snippet":"Natural language processing and vision tasks have seen large improvements recently through the rise of Transformer architectures. The high performing large language models (LLMs) benefit from large textual datasets that are numerously …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000207"]}
-{"year":"2024","title":"Enabling High-Sparsity Foundational Llama Models with Efficient Pretraining and Deployment","authors":["A Agarwalla, A Gupta, A Marques, S Pandit, M Goin… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have revolutionized Natural Language Processing (NLP), but their size creates computational bottlenecks. We introduce a novel approach to create accurate, sparse foundational versions of performant LLMs that achieve full …","url":["https://arxiv.org/pdf/2405.03594"]}
-{"year":"2024","title":"Enabling self-identification in intelligent agent: insights from computational psychoanalysis","authors":["L Li, C Li - arXiv preprint arXiv:2403.07664, 2024"],"snippet":"Building upon prior framework of computational Lacanian psychoanalysis with the theory of active inference, this paper aims to further explore the concept of self-identification and its potential applications. Beginning with two classic paradigms in psychology …","url":["https://arxiv.org/pdf/2403.07664"]}
-{"year":"2024","title":"End to End Urdu Abstractive Text Summarization with Dataset and Improvement in Evaluation Metric","authors":["H Raza, W Shahzad - IEEE Access, 2024"],"snippet":"Urdu, being a common language in South Asia, has not received significant attention in terms of language processing compared to more advanced languages. In the field of Natural Language Processing (NLP), the task of text summarization …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10472483.pdf"]}
-{"year":"2024","title":"EnhancedBERT: A Feature-rich Ensemble Model for Arabic Word Sense Disambiguation with Statistical Analysis and Optimized Data Collection","authors":["S Kaddoura, R Nassar - Journal of King Saud University-Computer and …, 2024"],"snippet":"Accurate assignment of meaning to a word based on its context, known as Word Sense Disambiguation (WSD), remains challenging across languages. Extensive research aims to develop automated methods for determining word senses in …","url":["https://www.sciencedirect.com/science/article/pii/S1319157823004652"]}
-{"year":"2024","title":"Enhancing 3D Asset Retrieval with Semantic Search","authors":["SA FatemiJahromi - 2024"],"snippet":"Semantic search goes beyond exact keyword matching and instead focuses on the comprehension of search queries' purpose and the surrounding context to deliver relevant search results. In this work, we focus on integrating hybrid search, which …","url":["https://aaltodoc.aalto.fi/bitstreams/76d339fd-de51-4bb0-8a8c-e43d799b7023/download"]}
-{"year":"2024","title":"ENHANCING AUTOMATIC INVOICE CODING PERFORMANCE WITH UNSTRUCTURED DATA","authors":["T Eerola - 2024"],"snippet":"… The published word vectors are 300 dimensional and trained on the internet data from Common Crawl3. The pretrained word vectors can be further fine-tuned using the provided code and datasets more similar to the final usage scenario to increase …","url":["https://trepo.tuni.fi/bitstream/handle/10024/155981/EerolaTeemu.pdf?sequence=2"]}
-{"year":"2024","title":"Enhancing Cybersecurity: A Review and Comparative Analysis of Convolutional Neural Network Approaches for Detecting URL-Based Phishing Attacks","authors":["M Nanda, M Saraswat, PK Sharma - e-Prime-Advances in Electrical Engineering …, 2024"],"snippet":"Phishing attempts to mimic the official websites of businesses, including banks, e-commerce, government offices, and financial institutions. Phishing websites aim to collect and retrieve sensitive data from users, including passwords, credit card numbers, email …","url":["https://www.sciencedirect.com/science/article/pii/S2772671124001153"]}
-{"year":"2024","title":"Enhancing Ecological Knowledge Discovery Using Large Language Models","authors":["V Domazetoski"],"snippet":"Earth is home to an astonishing diversity of life forms. Among these, vascular plants stand as one of the most vital and ubiquitous groups, accounting for approximately 80% of global biomass [3]. The census of vascular plants, which presently exceeds …","url":["https://gipplab.org/wp-content/papercite-data/pdf/domazetoski2024.pdf"]}
-{"year":"2024","title":"Enhancing English Translation Quality Assessment through Knowledge Transfer in Artificial Intelligence Context","authors":["X Zhao - 2024"],"snippet":"Abstract Machine translation technology, which employs computers to autonomously convert text between source and target languages, represents a pivotal realm within artificial intelligence and natural language processing research. This paper …","url":["https://www.researchsquare.com/article/rs-4483708/latest.pdf"]}
-{"year":"2024","title":"Enhancing knowledge graphs with microdata and LLMs: the case of Schema. org and Wikidata in touristic information","authors":["L Gonzalez-Garcia, G González-Carreño… - The Electronic Library, 2024"],"snippet":"… We have used the Common Crawl (CC) corpus of crawled Web pages to extract metadata published in the wild, and then used a mapping of Schema.org annotations to Wikidata to get estimates of the added value (in terms of additional …","url":["https://www.emerald.com/insight/content/doi/10.1108/EL-06-2023-0160/full/html"]}
-{"year":"2024","title":"Enhancing Parameter Efficiency in Model Inference Using an Ultralight Inter-Transformer Linear Structure","authors":["H Shi, T Sakai - IEEE Access, 2024"],"snippet":"… It was constructed from the Chuweb21 generated based on the April 2021 block of the Common Crawl dataset. The WWW-4 dataset comprises 50 queries. Robust04 dataset is also an English web corpus generated from TREC disks 4 and 5, and …","url":["https://ieeexplore.ieee.org/iel7/6287639/10380310/10474022.pdf"]}
-{"year":"2024","title":"Enhancing Phishing Detection, Leveraging Deep Learning Techniques","authors":["A Ullah, RA Shah, SA Nawaz, N Ahmad, MH Malik - Journal of Computing & …, 2024"],"snippet":"… To achieve this, we utilized the Common Crawl Corpus, which aggregates extensive data collected over seven years. This corpus comprises raw web page data, metadata, and textual content. Legitimate domains with substantial backlink …","url":["https://jcbi.org/index.php/Main/article/download/340/252"]}
-{"year":"2024","title":"Enhancing Product Design through AI-Driven Sentiment Analysis of Amazon Reviews Using BERT","authors":["MK Shaik Vadla, MA Suresh, VK Viswanathan - Algorithms, 2024"],"snippet":"Understanding customer emotions and preferences is paramount for success in the dynamic product design landscape. This paper presents a study to develop a prediction pipeline to detect the aspect and perform sentiment analysis on review …","url":["https://www.mdpi.com/1999-4893/17/2/59"]}
-{"year":"2024","title":"Enhancing Sentiment Analysis Accuracy in Borobudur Temple Visitor Reviews through Semi-Supervised Learning and SMOTE Upsampling","authors":["C Agustina, P Purwanto, F Farikhin - Journal of Advances in Information Technology, 2024"],"snippet":"The level of visitor satisfaction with tourist destinations can be known from reviews on social media. One method used is to carry out sentiment analysis on comments given by visitors on social media or related websites. This study was envisioned as a …","url":["https://www.jait.us/uploadfile/2024/JAIT-V15N4-492.pdf"]}
-{"year":"2024","title":"Enhancing Sentiment Analysis on Social Media Data with Advanced Deep Learning Techniques.","authors":["HH Nguyen - International Journal of Advanced Computer Science & …, 2024"],"snippet":"This paper introduces a comprehensive methodology for conducting sentiment analysis on social media using advanced deep learning techniques to address the unique challenges of this domain. As digital platforms play an increasingly pivotal …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=2158107X&AN=177684405&h=gXTVgMzshbdYbIB8QB5iY2khYefExufWIzwbWX54fXIt%2Bfzrlh8r7t0tSXHbiXxI0typ97LA8y%2FqCMzmDhr%2FjA%3D%3D&crl=c"]}
-{"year":"2024","title":"Enhancing Vision-Language Pre-training with Rich Supervisions","authors":["Y Gao, K Shi, P Zhu, E Belval, O Nuriel, S Appalaraju… - arXiv preprint arXiv …, 2024"],"snippet":"… This is expected as our data collected from Common Crawl has different distribution against the original Pix2struct data due to the data size (2M vs. 80M) and potentially different website filtering strategies. Specifically, we filter out website …","url":["https://arxiv.org/pdf/2403.03346"]}
-{"year":"2024","title":"Enriching Interactive Explanations with Fuzzy Temporal Constraint Networks","authors":["M Canabal-Juanatey, JM Alonso-Moral, A Catala… - International Journal of …, 2024"],"snippet":"… such as BERT [2] (Bidirectional Encoder Representations from Transformers), GPT [26] (Generative Pre-trained Transformer) and their successors (ALBERT [4], RoBERTa [3], BART [7], GPT-3 [5] or GPT-4 [27]), which were trained with huge …","url":["https://www.sciencedirect.com/science/article/pii/S0888613X2400015X"]}
-{"year":"2024","title":"EpilepsyLLM: Domain-Specific Large Language Model Fine-tuned with Epilepsy Medical Knowledge","authors":["X Zhao, Q Zhao, T Tanaka - arXiv preprint arXiv:2401.05908, 2024"],"snippet":"With large training datasets and massive amounts of computing sources, large language models (LLMs) achieve remarkable performance in comprehensive and generative ability. Based on those powerful LLMs, the model fine-tuned with domain-specific …","url":["https://arxiv.org/pdf/2401.05908"]}
-{"year":"2024","title":"Ethics of AI in the Teaching of English","authors":["A Piotrowski"],"snippet":"New technologies have always impacted literacy, and artificial intelligence (AI) is no exception (Tyner, 1998). English teachers find themselves having to consider how AI may impact how they teach. NCTE’s Beliefs for Integrating Technology Into the …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=HtIDEQAAQBAJ&oi=fnd&pg=PA221&dq=commoncrawl&ots=Wd6CuXLoH8&sig=-k9bfBVB4zHhmTOBXH6OEGq0Xws"]}
-{"year":"2024","title":"EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluation","authors":["AL Tonja, IA Azime, TD Belay, MG Yigezu… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have gained popularity recently due to their outstanding performance in various downstream Natural Language Processing (NLP) tasks. However, low-resource languages are still lagging behind current state-of-the-art …","url":["https://arxiv.org/pdf/2403.13737"]}
-{"year":"2024","title":"EvalQuiz: self-assessment generated through language transformer models","authors":["J Kieslinger - 2023"],"snippet":"This thesis explores the constraints of self-assessment creation in higher education, focusing on the lack of tools, standardization, and time. We conduct didactic field expert interviews to investigate how teaching evolves towards learning management …","url":["http://elib.uni-stuttgart.de/bitstream/11682/13953/1/Julian_Kieslinger_Bachelorarbeit_Abgabe_offiziell.pdf"]}
-{"year":"2024","title":"Evaluating and improving lexical language understanding in neural machine translation","authors":["D Emelin - 2024"],"snippet":"Lexical understanding is an inalienable component of the translation process. In order to correctly map the meaning of a linguistic unit to the appropriate target language expression, the meaning of its constituent words has first to be identified …","url":["https://era.ed.ac.uk/bitstream/handle/1842/41561/EmelinD_2024.pdf?sequence=1"]}
-{"year":"2024","title":"Evaluating and Mitigating Limitations of Large Language Models in Clinical Decision Making","authors":["P Hager, F Jungmann, K Bhagat, I Hubrecht, M Knauer… - medRxiv, 2024"],"snippet":"Clinical decision making is one of the most impactful parts of a physician's responsibilities and stands to benefit greatly from AI solutions and large language models (LLMs) in particular. However, while LLMs have achieved excellent …","url":["https://www.medrxiv.org/content/medrxiv/early/2024/01/26/2024.01.26.24301810.full.pdf"]}
-{"year":"2024","title":"Evaluating Differential Privacy Approaches for Query Obfuscation in Information Retrieval","authors":["G Faggioli, N Ferro - 2023"],"snippet":"Protecting the privacy of a user while they interact with an Information Retrieval (IR) system is crucial. This becomes more challenging when the IR system is not cooperative in satisfying the user’s privacy needs. Recent advancements in Natural …","url":["https://ceur-ws.org/Vol-3643/paper5.pdf"]}
-{"year":"2024","title":"Evaluating embedded semantics for accessibility description of web crawl data","authors":["R Navarrete, D Martinez-Mosquera, L Recalde… - AHFE (2023) International …, 2023"],"snippet":"… The dataset for analysis is provided by Web Data Commons (WDC), an organization that releases extracted data from Common Crawl (CC), the largest web corpus available to the public. The dataset was released in October 2021 …","url":["https://www.researchgate.net/profile/Diana-Martinez-Mosquera/publication/372284128_Evaluating_embedded_semantics_for_accessibility_description_of_web_crawl_data/links/658ee9706f6e450f19b4b6a5/Evaluating-embedded-semantics-for-accessibility-description-of-web-crawl-data.pdf"]}
-{"year":"2024","title":"Evaluating English-language morphological awareness assessments","authors":["CL Hudson Kam, E Sadlier-Brown, S Clark, C Jang… - First Language, 2024"],"snippet":"… These corpora were selected because they contain language that children are exposed to, and so, provide a more realistic picture of children’s potential knowledge than an adult-language based corpus would (eg the Enron email dataset …","url":["https://journals.sagepub.com/doi/pdf/10.1177/01427237241245500"]}
-{"year":"2024","title":"Evaluating Large Language Model Performance on Haskell","authors":["A Chen - 2024"],"snippet":"I introduce HaskellEval, a Haskell evaluation benchmark for Large Language Models. HaskellEval’s curation leverages a novel synthetic generation framework, streamlining the process of dataset curation by minimizing manual intervention. The …","url":["https://scholarworks.wm.edu/cgi/viewcontent.cgi?article=3209&context=honorstheses"]}
-{"year":"2024","title":"Evaluating Large Language Models for Generalization and Robustness via Data Compression","authors":["Y Li, Y Guo, F Guerin, C Lin - arXiv preprint arXiv:2402.00861, 2024"],"snippet":"Existing methods for evaluating large language models face challenges such as data contamination, sensitivity to prompts, and the high cost of benchmark creation. To address this, we propose a lossless data compression based evaluation …","url":["https://arxiv.org/pdf/2402.00861"]}
-{"year":"2024","title":"Evaluating Large Language Models on Academic Literature Understanding and Review: An Empirical Study among Early-stage Scholars","authors":["J Wang, H Hu, Z Wang, Y Song, Y Sheng, D He - 2024"],"snippet":"The rapid advancement of large language models (LLMs) such as ChatGPT makes LLM-based academic tools possible. However, little research has empirically evaluated how scholars perform different types of academic tasks with LLMs …","url":["https://personal.hkust-gz.edu.cn/hedengbo/assets/publicationPDFs/Wang_CHI_2024a.pdf"]}
-{"year":"2024","title":"Evaluating Multilingual Abstractive Dialogue Summarization in Indian Languages using mT5-small & IndicBART","authors":["M Sharma, G Goyal, A Gupta, R Rani, A Sharma, A Dev - 2024 IEEE 9th International …, 2024"],"snippet":"… The mC4 dataset consists of natural text in 101 languages including Indian languages like Hindi, Mararti, Punjabi and others, that was collected from the public Common Crawl web scrape. Introduced as a multilingual, sequence-to-sequence pre-trained …","url":["https://ieeexplore.ieee.org/abstract/document/10543588/"]}
-{"year":"2024","title":"Evaluating Shortest Edit Script Methods for Contextual Lemmatization","authors":["O Toporkov, R Agerri - arXiv preprint arXiv:2403.16968, 2024"],"snippet":"Modern contextual lemmatizers often rely on automatically induced Shortest Edit Scripts (SES), namely, the number of edit operations to transform a word form into its lemma. In fact, different methods of computing SES have been proposed as an …","url":["https://arxiv.org/pdf/2403.16968"]}
-{"year":"2024","title":"Evaluating the Experience of LGBTQ+ People Using Large Language Model Based Chatbots for Mental Health Support","authors":["Z Ma, Y Mei, Y Long, Z Su, KZ Gajos - arXiv preprint arXiv:2402.09260, 2024"],"snippet":"LGBTQ+ individuals are increasingly turning to chatbots powered by large language models (LLMs) to meet their mental health needs. However, little research has explored whether these chatbots can adequately and safely provide tailored support …","url":["https://arxiv.org/pdf/2402.09260"]}
-{"year":"2024","title":"Evaluating the Factuality of Zero-shot Summarizers Across Varied Domains","authors":["S Ramprasad, K Krishna, ZC Lipton, BC Wallace - arXiv preprint arXiv:2402.03509, 2024"],"snippet":"Recent work has shown that large language models (LLMs) are capable of generating summaries zero-shot (ie, without explicit supervision) that, under human assessment, are often comparable or even preferred to manually composed …","url":["https://arxiv.org/pdf/2402.03509"]}
-{"year":"2024","title":"Evaluating the impact of design decisions on passive DNS-based domain rankings","authors":["V Le Pochat, S Fernandez, T Van Goethem…"],"snippet":"… They recommend that researchers select a random sample of websites among Common Crawl hosts. Ruth et al. [6] compared top lists to Cloudflare traffic data, concluding that the Chrome User Experience Report [11] most accurately represents …","url":["https://lepoch.at/files/domain-ranking-design-decisions-tma24.pdf"]}
-{"year":"2024","title":"Evaluating the Quality of AI-Generated Items for a Certification Exam","authors":["AD Mead, C Zhou - Journal of Applied Testing Technology, 2024"],"snippet":"OpenAI’s GPT-3 model can write multiple-choice exam items. This paper reviewed the literature on automatic item generation and then described the recent history of OpenAI GPT models and their operation, and then described a methodology for …","url":["http://jattjournal.net/index.php/atp/article/download/173204/117130"]}
-{"year":"2024","title":"Evaluating Transformers and Linguistic Features integration for Author Profiling tasks in Spanish","authors":["JA García-Díaz, G Beydoun, R Valencia-García - Data & Knowledge Engineering, 2024"],"snippet":"… This model is a training from scratch of RoBERTa, trained on the Spanish texts from mC4, compiled from the public Common Crawl web … This is a multilingual version of RoBERTa, pre-trained with about 2.5 TB of data from the 100 different …","url":["https://www.sciencedirect.com/science/article/pii/S0169023X24000314"]}
-{"year":"2024","title":"Evaluation and Adaptation of Neural Language Models for Under-Resourced Languages","authors":["W de Vries - 2024"],"snippet":"Abstract Language models are now commonly used by researchers, industry, and anyone interested. However, language models of all sizes and types are primarily developed for the English language while efforts on other languages lag behind …","url":["https://research.rug.nl/files/993731020/Complete_thesis.pdf"]}
-{"year":"2024","title":"Evaluation of AI-generated Responses by Different Artificial Intelligence Chatbots to the Clinical Decision-Making Case-Based Questions in Oral and Maxillofacial …","authors":["A Azadi, F Gorjinejad, H Mohammad-Rahimi, R Tabrizi… - Oral Surgery, Oral Medicine …, 2024"],"snippet":"Objectives This study aims to evaluate the correctness of the generated answers by Google Bard, GPT-3.5, GPT-4, Claude-Instant, and Bing chatbots to decision-making clinical questions in the oral and maxillofacial surgery (OMFS) area. Study Design A …","url":["https://www.sciencedirect.com/science/article/pii/S2212440324000956"]}
-{"year":"2024","title":"Evaluation of Geographical Distortions in Language Models: A Crucial Step Towards Equitable Representations","authors":["R Decoupes, R Interdonato, M Roche, M Teisseire… - arXiv preprint arXiv …, 2024"],"snippet":"Language models now constitute essential tools for improving efficiency for many professional tasks such as writing, coding, or learning. For this reason, it is imperative to identify inherent biases. In the field of Natural Language Processing …","url":["https://arxiv.org/pdf/2404.17401"]}
-{"year":"2024","title":"Evaluation of word embedding models used for diachronic semantic change analysis","authors":["Y Maslennikova, V Bochkarev - Journal of Physics: Conference Series, 2024"],"snippet":"… As a reference word2vec model, we used pre-trained word vectors that were trained on English versions of Common Crawl dataset using fastText library [14]. fastText is a library for efficient learning of word representations and sentence …","url":["https://iopscience.iop.org/article/10.1088/1742-6596/2701/1/012082/pdf"]}
-{"year":"2024","title":"Evidence for a digital divide? Measuring DNS dependencies in the context of the indigenous population of Australia","authors":["R Holz, N Nazemi, O Tavallaie, AY Zomaya"],"snippet":"We recently presented a work-in-progress paper at the Workshop on Transparency, Accountability and User Control for a Responsible Internet (TAURIN 2023). Our paper investigates the relationship between the digital divide, Internet transparency …","url":["https://www.ietf.org/slides/slides-biasws-evidence-for-a-digital-divide-measuring-dns-dependencies-in-the-context-of-the-indigenous-population-of-australia-00.pdf"]}
-{"year":"2024","title":"EXAMINING ACCURACY HETEROGENEITIES IN CLASSIFICATION OF MULTILINGUAL AI-GENERATED TEXT","authors":["R Subramaniam"],"snippet":"Tools for detection of AI-generated texts are used globally, however, the nature of the apparent accuracy disparities between languages must be further observed. This paper aims to examine the nature of these differences through testing OpenAI’s …","url":["https://csitcp.org/paper/13/1312csit21.pdf"]}
-{"year":"2024","title":"Experimental Evaluation of Possible Feature Combinations for the Detection of Fraudulent Online Shops","authors":["A Janavičiūtė, A Liutkevičius, G Dabužinskas… - Applied Sciences, 2024"],"snippet":"Online shopping has become a common and popular form of shopping, so online attackers try to extract money from customers by creating online shops whose purpose is to compel the buyer to disclose credit card details or to pay money for …","url":["https://www.mdpi.com/2076-3417/14/2/919"]}
-{"year":"2024","title":"Explainable Generative AI (GenXAI): A Survey, Conceptualization, and Research Agenda","authors":["J Schneider - arXiv preprint arXiv:2404.09554, 2024"],"snippet":"Generative AI (GenAI) marked a shift from AI being able to recognize to AI being able to generate solutions for a wide variety of tasks. As the generated solutions and applications become increasingly more complex and multi-faceted, novel needs …","url":["https://arxiv.org/pdf/2404.09554"]}
-{"year":"2024","title":"Exploring LLMs' Capabilities for Error Detection in Dutch L1 and L2 Writing Products","authors":["J Kruijsbergen, S Van Geertruyen, V Hoste… - Computational Linguistics in …, 2024"],"snippet":"This research examines the capabilities of Large Language Models for writing error detection, which can be seen as a first step towards automated writing support. Our work focuses on Dutch writing error detection, targeting two envisaged end-users …","url":["https://www.clinjournal.org/clinj/article/download/179/195"]}
-{"year":"2024","title":"Exploring Machine Learning for Malware Detection With Feature Selection, Explainable AI, and Generative Adversarial Networks","authors":["DQ Smith Jr - 2023"],"snippet":"This research focuses on the detection of malware in sample datasets using machine learning algorithms. As malware becomes more advanced against detection in the cybersecurity sector, researchers have looked for other methods to …","url":["https://search.proquest.com/openview/3851d57453e23cecb2a424ea1df4e607/1?pq-origsite=gscholar&cbl=18750&diss=y"]}
-{"year":"2024","title":"Exploring the competence of ChatGPT for customer and patient service management","authors":["A Haleem, M Javaid, RP Singh - Intelligent Pharmacy, 2024"],"snippet":"The modern language generation model ChatGPT, created by Open Artificial Intelligence (AI), is recognised for its capacity to comprehend context and produce pertinent content. This model is built on the transformer architecture, which enables …","url":["https://www.sciencedirect.com/science/article/pii/S2949866X24000480"]}
-{"year":"2024","title":"Exploring the Reasoning Abilities of Multimodal Large Language Models (MLLMs): A Comprehensive Survey on Emerging Trends in Multimodal Reasoning","authors":["Y Wang, W Chen, X Han, X Lin, H Zhao, Y Liu, B Zhai… - arXiv preprint arXiv …, 2024"],"snippet":"Strong Artificial Intelligence (Strong AI) or Artificial General Intelligence (AGI) with abstract reasoning ability is the goal of next-generation AI. Recent advancements in Large Language Models (LLMs), along with the emerging field of Multimodal Large …","url":["https://arxiv.org/pdf/2401.06805"]}
-{"year":"2024","title":"Exploring the Robustness of Task-oriented Dialogue Systems for Colloquial German Varieties","authors":["E Artemova, V Blaschke, B Plank - arXiv preprint arXiv:2402.02078, 2024"],"snippet":"Mainstream cross-lingual task-oriented dialogue (ToD) systems leverage the transfer learning paradigm by training a joint model for intent recognition and slot-filling in English and applying it, zero-shot, to other languages. We address a gap in prior …","url":["https://arxiv.org/pdf/2402.02078"]}
-{"year":"2024","title":"Exploring the Role of ChatGPT in Cardiology: A Systematic Review of the Current Literature","authors":["A Sharma, T Medapalli, M Alexandrou, E Brilakis… - Cureus, 2024"],"snippet":"Chat Generative Pre-Trained Transformer (ChatGPT) is a chatbot based on a large language model that has gained public interest since its release in November 2022. This systematic review examines the current literature on the potential applications …","url":["https://www.cureus.com/articles/244400-exploring-the-role-of-chatgpt-in-cardiology-a-systematic-review-of-the-current-literature.pdf"]}
-{"year":"2024","title":"Exploring the role of ChatGPT in higher education: opportunities, challenges and ethical considerations","authors":["A Zeb, R Ullah, R Karim - The International Journal of Information and Learning …, 2024"],"snippet":"Purpose This paper aims to examine the opportunities and challenges of using ChatGPT in higher education. Furthermore, it is also discuss the potential risks and plunders of these tools. Design/methodology/approach The paper discuss the use of …","url":["https://www.emerald.com/insight/content/doi/10.1108/IJILT-04-2023-0046/full/html"]}
-{"year":"2024","title":"EXPRESS: Malay Lexicon Project 3: The Impact of Orthographic-Semantic Consistency on Lexical Decision Latencies","authors":["M Maziyah Mohamed, D Jared - Quarterly Journal of Experimental Psychology, 2024"],"snippet":"Theories of word processing propose that readers are sensitive to statistical co-occurrences between spelling and meaning. Orthographic-Semantic Consistency (OSC) measures provide a continuous estimate of the statistical regularities between …","url":["https://journals.sagepub.com/doi/abs/10.1177/17470218241234668"]}
-{"year":"2024","title":"Extending the Comparative Argumentative Machine: Multilingualism and Stance Detection","authors":["I Nikishina, A Bondarenko, S Zaczek, OL Haag…"],"snippet":"The comparative argumentative machine CAM can retrieve arguments that answer comparative questions—questions that ask which of several to-be-compared options should be favored in some scenario. In this paper, we describe how we equipped …","url":["https://downloads.webis.de/publications/papers/nikishina_2024.pdf"]}
-{"year":"2024","title":"Extending Translate-Train for ColBERT-X to African Language CLIR","authors":["E Yang, DJ Lawrie, P McNamee, J Mayfield - arXiv preprint arXiv:2404.08134, 2024"],"snippet":"… We used Common Crawl documents in Afriberta Corpus [6] for the four African languages and collected additional English Common Crawl documents to match the genre. We fine-tune the model for 200,000 update steps using a learning rate of 1×10-5 …","url":["https://arxiv.org/pdf/2404.08134"]}
-{"year":"2024","title":"Extracting intersectional stereotypes from embeddings: Developing and validating the Flexible Intersectional Stereotype Extraction procedure","authors":["TES Charlesworth, K Ghate, A Caliskan, MR Banaji - PNAS Nexus, 2024"],"snippet":"… text corpora, ranging from static GloVe embeddings trained on 840 billion words from the Common Crawl to contextualized BERT embeddings trained on a combination of Wikipedia and Common Crawl text. Additionally, in supplemental …","url":["https://academic.oup.com/pnasnexus/article/3/3/pgae089/7626925"]}
-{"year":"2024","title":"Factuality of Large Language Models in the Year 2024","authors":["Y Wang, M Wang, MA Manzoor, G Georgiev, RJ Das… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs), especially when instruction-tuned for chat, have become part of our daily lives, freeing people from the process of searching, extracting, and integrating information from multiple sources by offering a …","url":["https://arxiv.org/pdf/2402.02420"]}
-{"year":"2024","title":"FairDeDup: Detecting and Mitigating Vision-Language Fairness Disparities in Semantic Dataset Deduplication","authors":["E Slyman, S Lee, S Cohen, K Kafle - arXiv preprint arXiv:2404.16123, 2024"],"snippet":"Recent dataset deduplication techniques have demonstrated that content-aware dataset pruning can dramatically reduce the cost of training Vision-Language Pretrained (VLP) models without significant performance losses compared to …","url":["https://arxiv.org/pdf/2404.16123"]}
-{"year":"2024","title":"Fake news detection in low-resource languages: A novel hybrid summarization approach","authors":["J Alghamdi, Y Lin, S Luo - Knowledge-Based Systems, 2024"],"snippet":"… Pre-training encompasses a vast dataset exceeding 2TB of CommonCrawl data. The overarching concept involves mapping any given language to a language-agnostic vector space, ensuring that inputs in various languages converge to corresponding …","url":["https://www.sciencedirect.com/science/article/pii/S0950705124005185"]}
-{"year":"2024","title":"Feature-augmented model for multilingual discourse relation classification","authors":["E Metheniti, C Braud, P Muller - Proceedings of the 5th Workshop on Computational …, 2024"],"snippet":"Discourse relation classification within a multilingual, cross-framework setting is a challenging task, and the best-performing systems so far have relied on monolingual and mono-framework approaches. In this paper, we introduce transformer-based …","url":["https://aclanthology.org/2024.codi-1.9.pdf"]}
-{"year":"2024","title":"Federated learning for privacy-preserving depression detection with multilingual language models in social media posts","authors":["SS Khalil, NS Tawfik, M Spruit - Patterns, 2024"],"snippet":"The incidences of mental health illnesses, such as suicidal ideation and depression, are increasing, which highlights the urgent need for early detection methods. There is a growing interest in using natural language processing (NLP) models to analyze …","url":["https://www.cell.com/patterns/fulltext/S2666-3899(24)00105-3"]}
-{"year":"2024","title":"Few shot clinical entity recognition in three languages: Masked language models outperform LLM prompting","authors":["M Naguib, X Tannier, A Névéol - arXiv preprint arXiv:2402.12801, 2024"],"snippet":"Large Language Models are becoming the go-to solution for many natural language processing tasks, including in specialized domains where their few-shot capacities are expected to yield high performance in low-resource settings. Herein, we aim to …","url":["https://arxiv.org/pdf/2402.12801"]}
-{"year":"2024","title":"Final Thoughts: Digital Humanities Looking at Generative AI","authors":["M Aguiar, S Araújo - Digital Humanities Looking at the World: Exploring …, 2024"],"snippet":"In this chapter, we examine generative artificial intelligence in the context of Digital Humanities. We commence by providing a concise overview of this technology and its prevalent models. Following that, we provide a brief survey of the existing …","url":["https://link.springer.com/chapter/10.1007/978-3-031-48941-9_28"]}
-{"year":"2024","title":"Final Words","authors":["M McTear, M Ashurkina - Transforming Conversational AI: Exploring the Power …, 2024"],"snippet":"Conversational AI is a dynamic and fast moving field, and a lot has happened in the six months or so since we began writing this book. We have tried to ensure that what we have covered in the preceding chapters provides a sufficiently general and …","url":["https://link.springer.com/chapter/10.1007/979-8-8688-0110-5_10"]}
-{"year":"2024","title":"Fine grain emotion analysis in Spanish using linguistic features and transformers","authors":["A Salmerón-Ríos, JA García-Díaz, R Pan… - PeerJ Computer Science, 2024"],"snippet":"Mental health issues are a global concern, with a particular focus on the rise of depression. Depression affects millions of people worldwide and is a leading cause of suicide, particularly among young people. Recent surveys indicate an increase in …","url":["https://peerj.com/articles/cs-1992/"]}
-{"year":"2024","title":"Fine Tuning LLM for Enterprise: Practical Guidelines and Recommendations","authors":["K VM, H Warrier, Y Gupta - arXiv preprint arXiv:2404.10779, 2024"],"snippet":"… The datasets are massive text corpus like Common crawl, The Pile and code repositories from Github. Further the model can be fine tuned for specific tasks using specialised datasets. One such series of datasets are called Instruction datasets like …","url":["https://arxiv.org/pdf/2404.10779"]}
-{"year":"2024","title":"Fine-Tuned Large Language Models for Symptom Recognition from Spanish Clinical Text","authors":["MA Shaaban, A Akkasi, A Khan, M Komeili, M Yaqub - arXiv preprint arXiv …, 2024"],"snippet":"… XLM-RL (561M parameters) and XLM-RB (279M parameters) are multilingual masked language models, trained on a filtered CommonCrawl dataset of over two terabytes. We leverage BBS and BBES both pretrained on Spanish clinical data …","url":["https://arxiv.org/pdf/2401.15780"]}
-{"year":"2024","title":"Fine-tuning BERT-based Models for Negative Content Identification on Indonesian Tweets","authors":["AF Hidayatullah, K Kalinaki, MM Aslam, RY Zakari…"],"snippet":"Social media platforms like Twitter have become substantial sources of user-generated content, enabling people to easily express their emotions and opinions. However, this freedom has increased the spread of harmful content, such as abusive language …","url":["https://www.researchgate.net/profile/Wasswa-Shafik-2/publication/378272650_Fine-Tuning_BERT-Based_Models_for_Negative_Content_Identification_on_Indonesian_Tweets/links/65d17d8928b7720cecda923e/Fine-Tuning-BERT-Based-Models-for-Negative-Content-Identification-on-Indonesian-Tweets.pdf"]}
-{"year":"2024","title":"Fine-tuning Large Language Models for Multigenerator, Multidomain, and Multilingual Machine-Generated Text Detection","authors":["F Xiong, T Markchom, Z Zheng, S Jung, V Ojha… - arXiv preprint arXiv …, 2024"],"snippet":"SemEval-2024 Task 8 introduces the challenge of identifying machine-generated texts from diverse Large Language Models (LLMs) in various languages and domains. The task comprises three subtasks: binary classification in monolingual …","url":["https://arxiv.org/pdf/2401.12326"]}
-{"year":"2024","title":"FINETUNING COMMERCIAL LARGE LANGUAGE MODELS WITH LORA FOR ENHANCED ITALIAN LANGUAGE UNDERSTANDING","authors":["J Hartsuiker, P Torroni, AE Ziri, DF Alise, F Ruggeri"],"snippet":"The world of Artificial intelligence is booming, especially the fields of natural language processing (NLP) and Computer Vision (CV). Recently the chatGPT models from OpenAI have caused another shock-wave. This was a clear sign to the …","url":["https://amslaurea.unibo.it/30534/1/Hartsuiker,%20J.M.%20Master%20Thesis%20-%20Finetuning%20commercial%20Large%20Language%20Models%20with%20LoRA%20for%20enhanced%20Italian%20language%20understanding.pdf"]}
-{"year":"2024","title":"Finite State Automata on Multi-Word Units for Efficient Text-Mining","authors":["A Postiglione - Mathematics, 2024"],"snippet":"Text mining is crucial for analyzing unstructured and semi-structured textual documents. This paper introduces a fast and precise text mining method based on a finite automaton to extract knowledge domains. Unlike simple words, multi-word …","url":["https://www.mdpi.com/2227-7390/12/4/506/pdf"]}
-{"year":"2024","title":"FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models","authors":["G Bhatia, EMB Nagoudi, H Cavusoglu… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce FinTral, a suite of state-of-the-art multimodal large language models (LLMs) built upon the Mistral-7b model and tailored for financial analysis. FinTral integrates textual, numerical, tabular, and image data. We enhance FinTral with domain-specific …","url":["https://arxiv.org/pdf/2402.10986"]}
-{"year":"2024","title":"Foregrounding Artist Opinions: A Survey Study on Transparency, Ownership, and Fairness in AI Generative Art","authors":["J Lovato, J Zimmerman, I Smith, P Dodds, J Karson - arXiv preprint arXiv:2401.15497, 2024"],"snippet":"Generative Artificial Intelligence (AI) tools are used to create art-like outputs and aid in the creative process. While these tools have potential benefits for artists, they also have the potential to harm the art workforce and infringe upon artistic and intellectual …","url":["https://arxiv.org/pdf/2401.15497"]}
-{"year":"2024","title":"Fostering the Ecosystem of Open Neural Encoders for Portuguese with Albertina PT* Family","authors":["R Santos, J Rodrigues, L Gomes, J Silva, A Branco… - arXiv preprint arXiv …, 2024"],"snippet":"… The OSCAR subset for Portuguese we use is based on November/December 2022 version of Common Crawl, which is an automatic crawl from the web. Despite being a crawl, the final dataset is of relatively good quality due the filtering performed …","url":["https://arxiv.org/pdf/2403.01897"]}
-{"year":"2024","title":"Frequently asked questions on erectile dysfunction: evaluating artificial intelligence answers with expert mentorship","authors":["M Baturu, M Solakhan, TG Kazaz, O Bayrak - International Journal of Impotence …, 2024"],"snippet":"The present study assessed the accuracy of artificiaI intelligence-generated responses to frequently asked questions on erectile dysfunction. A cross-sectional analysis involved 56 erectile dysfunction-related questions searched on Google …","url":["https://www.nature.com/articles/s41443-024-00898-3"]}
-{"year":"2024","title":"From Bytes to Biases: Investigating the Cultural Self-Perception of Large Language Models","authors":["W Messner, T Greene, J Matalone - arXiv preprint arXiv:2312.17256, 2023"],"snippet":"Large language models (LLMs) are able to engage in natural-sounding conversations with humans, showcasing unprecedented capabilities for information retrieval and automated decision support. They have disrupted human-technology …","url":["https://arxiv.org/pdf/2312.17256"]}
-{"year":"2024","title":"From Cosine Similarity to Likelihood Ratio: Coupling Representations From Machine Learning (and Other Sources) With Cognitive Models","authors":["GE Cox"],"snippet":"Modern machine learning models yield vector representations that capture similarity relations between complex items like text and images. These representations can help explain and predict how individuals respond to those items in particular tasks …","url":["https://osf.io/v7xuz/download"]}
-{"year":"2024","title":"From Data Creator to Data Reuser: Distance Matters","authors":["CL Borgman, PT Groth - arXiv preprint arXiv:2402.07926, 2024"],"snippet":"… Common Crawl, launched in 2007, now spends roughly $200,000 per year to maintain petabytes of openly available web crawl data (Common Crawl, 2023; Roberts, 2023). The use of these data to train large language models has …","url":["https://arxiv.org/pdf/2402.07926"]}
-{"year":"2024","title":"From Data Quality to Model Performance: Navigating the Landscape of Deep Learning Model Evaluation","authors":["M Akram, WH Moosa - Deep Learning for Multimedia Processing Applications, 2024"],"snippet":"Deep learning (DL) technologies have revolutionized the analysis of multimedia data, with natural language processing, visual data analytics, and audio recognition being just a few examples of multimedia applications that have effectively utilized DL. This …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781032646268-13/data-quality-model-performance-muhammad-akram-wajid-hassan-moosa-najiba"]}
-{"year":"2024","title":"From Development to Dissemination: Social and Ethical Issues with Text-to-Image AI-Generated Art","authors":["SCY Ho"],"snippet":"… Model developed by the Computer Vision & Learning Group (CompVis) lab at Ludwig Maximilian University of Munich was trained with a subset of the LAION-5B dataset [6], comprising of about 2.3 billion CLIP-filtered image-text pairs by parsing …","url":["https://assets.pubpub.org/sv8awfz7/21682640391665.pdf"]}
-{"year":"2024","title":"From Form (s) to Meaning: Probing the Semantic Depths of Language Models Using Multisense Consistency","authors":["X Ohmer, E Bruni, D Hupkes - arXiv preprint arXiv:2404.12145, 2024"],"snippet":"… We use the current common crawl statistics6 to compute an estimate of how low- or high-resource these languages are in web-based corpora. Of this corpus, English constitutes 46% of the data, German 5.8%, Italian 2.7%, Dutch 2.2%, and Swedish …","url":["https://arxiv.org/pdf/2404.12145"]}
-{"year":"2024","title":"From News to Summaries: Building a Hungarian Corpus for Extractive and Abstractive Summarization","authors":["B Barta, D Lakatos, A Nagy, MK Nyist, J Ács - arXiv preprint arXiv:2404.03555, 2024"],"snippet":"… We use the freely available Common Crawl dataset4 as a basis for constructing the corpus. It contains petabytes of crawled web pages from the past 25 years and it is available on Amazon S3 in WARC format. Retrieval and deduplication of the raw …","url":["https://arxiv.org/pdf/2404.03555"]}
-{"year":"2024","title":"From Text to Transformation: A Comprehensive Review of Large Language Models' Versatility","authors":["P Kaur, GS Kashyap, A Kumar, MT Nafis, S Kumar… - arXiv preprint arXiv …, 2024"],"snippet":"This groundbreaking study explores the expanse of Large Language Models (LLMs), such as Generative Pre-Trained Transformer (GPT) and Bidirectional Encoder Representations from Transformers (BERT) across varied domains ranging from …","url":["https://arxiv.org/pdf/2402.16142"]}
-{"year":"2024","title":"Frozen or Fine-tuned? Analyzing Deep Learning Models and Training Strategies for Optimizing Big Five Personality Traits Prediction from Text","authors":["M Soleimani, HB Kashani - 2024 10th International Conference on Artificial …, 2024"],"snippet":"In today’s digital age, the comprehension and prediction of human personality traits have assumed paramount significance. This study embarks on the task of forecasting the Big Five personality traits through textual data, harnessing the …","url":["https://ieeexplore.ieee.org/abstract/document/10496606/"]}
-{"year":"2024","title":"Fundus: A Simple-to-Use News Scraper Optimized for High Quality Extractions","authors":["M Dallabetta, C Dobberstein, A Breiding, A Akbik - arXiv preprint arXiv:2403.15279, 2024"],"snippet":"… Specifically, we support the CC-NEWS3 dataset provided by the COMMONCRAWL initiative. At the time of writing, this dataset comprises around 40 terabytes of WARC-formatted data, containing millions of news articles dating back …","url":["https://arxiv.org/pdf/2403.15279"]}
-{"year":"2024","title":"Fusing Domain-Specific Content from Large Language Models into Knowledge Graphs for Enhanced Zero Shot Object State Classification","authors":["F Gouidis, K Papantoniou, KPT Patkos, A Argyros… - arXiv preprint arXiv …, 2024"],"snippet":"Domain-specific knowledge can significantly contribute to addressing a wide variety of vision tasks. However, the generation of such knowledge entails considerable human labor and time costs. This study investigates the potential of Large Language …","url":["https://arxiv.org/pdf/2403.12151"]}
-{"year":"2024","title":"Fusion of Deep Learning with Advanced and Traditional Embeddings in Sentiment Analysis","authors":["K Kiran, PD Shenoy - 2024 IEEE 9th International Conference for …, 2024"],"snippet":"In todays changing landscape the abundance of unprocessed data plays a vital role. It is crucial to curate this dataset and conduct a thorough analysis of the sentiments it captures. The aim of this research study is to explore learning techniques such as Bi …","url":["https://ieeexplore.ieee.org/abstract/document/10543279/"]}
-{"year":"2024","title":"GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection","authors":["J Zhao, Z Zhang, B Chen, Z Wang, A Anandkumar… - arXiv preprint arXiv …, 2024"],"snippet":"Training Large Language Models (LLMs) presents significant memory challenges, predominantly due to the growing size of weights and optimizer states. Common memory-reduction approaches, such as low-rank adaptation (LoRA), add a trainable …","url":["https://arxiv.org/html/2403.03507v1"]}
-{"year":"2024","title":"Gauging Novelty in Crowdfunding Projects: A Theory-Driven Text Analysis Approach","authors":["Y Lin, W Boh - 2024"],"snippet":"The explosion of crowdfunding projects has called for new ways to screen for novel projects. Building on the multidimensional nature of novelty, we draw on the literature to propose two measures of project novelty that are theoretically sound and …","url":["https://aisel.aisnet.org/pacis2024/track03_ba/track03_ba/1/"]}
-{"year":"2024","title":"GenDec: A robust generative Question-decomposition method for Multi-hop reasoning","authors":["J Wu, L Yang, Y Ji, W Huang, BF Karlsson, M Okumura - arXiv preprint arXiv …, 2024"],"snippet":"Multi-hop QA (MHQA) involves step-by-step reasoning to answer complex questions and find multiple relevant supporting facts. However, Existing large language models'(LLMs) reasoning ability in multi-hop question answering remains exploration, which is …","url":["https://arxiv.org/pdf/2402.11166"]}
-{"year":"2024","title":"Gender Bias in Natural Gender Language and Grammatical Gender Language within Children's Literature","authors":["KMW Smolinski - 2024"],"snippet":"There has been much research on the connection between language and gender bias but there is little comparing natural gender language, grammatical gender language, and gender bias. This research is important because it can offer an …","url":["https://digitalcommons.liberty.edu/cgi/viewcontent.cgi?article=6353&context=doctoral"]}
-{"year":"2024","title":"Gender Identity and Representation in the Context of Economic Development in India","authors":["B Pandey - 2024"],"snippet":"… It is a large multi-lingual language model, trained on 2.5TB of filtered CommonCrawl data. It represents some of the most sophisticated pre-trained models prevalently being used in natural language processing for text classification …","url":["https://knowledge.uchicago.edu/record/11912/files/Pandey_Thesis_MACSSEcon.pdf"]}
-{"year":"2024","title":"Gendered Grammar or Ingrained Bias? Exploring Gender Bias in Icelandic Language Models","authors":["SR Friðriksdóttir, H Einarsson - Proceedings of the 2024 Joint International …, 2024"],"snippet":"Large language models, trained on vast datasets, exhibit increased output quality in proportion to the amount of data that is used to train them. This data-driven learning process has brought forth a pressing issue where these models may not only reflect …","url":["https://aclanthology.org/2024.lrec-main.671.pdf"]}
-{"year":"2024","title":"Generating Apparel Images by Using Stable Diffusion with Prompt Recommendation","authors":["XZ Liu, HM Hung, LH Chen - 人工知能学会全国大会論文集 第 38 回 (2024), 2024"],"snippet":"Fashion is a profound expression of personal identity, style, and culture in daily life. Making oneself look attractive, which often equates to being fashionable or stylish, is always a priority for many people. In this paper, we proposed a clothing …","url":["https://www.jstage.jst.go.jp/article/pjsai/JSAI2024/0/JSAI2024_2Q4IS502/_pdf"]}
-{"year":"2024","title":"Generating Character Lines in Four-Panel Manga","authors":["M Inaba - Proceedings of the 37th Pacific Asia Conference on …, 2023"],"snippet":"Automatic content generation based on natural language processing is an active research area, especially for story generation. Research on story generation has focused on generating consistent text pertaining to characters’ actions and events; …","url":["https://aclanthology.org/2023.paclic-1.34.pdf"]}
-{"year":"2024","title":"Generating Probabilistic Scenario Programs from Natural Language","authors":["K Elmaaroufi, D Shankar, A Cismaru… - arXiv preprint arXiv …, 2024"],"snippet":"… Most of these model’s are fine-tuned variants of a foundational model that was trained on a wider body of text such as Common Crawl. For instance Codex is ”a GPT language model fine-tuned on publicly available code from GitHub” and it’s ���","url":["https://arxiv.org/pdf/2405.03709"]}
-{"year":"2024","title":"Generation of API Documentation using Large Language Models–Towards Self-explaining APIs","authors":["Y Jorelle - 2024"],"snippet":"Application Programming Interfaces (APIs) play a crucial role in modern software development. They are key in not only in enabling software reuse and adaptation, which greatly increase productivity, but also in facilitating exploration of new …","url":["https://aaltodoc.aalto.fi/bitstreams/b56655a0-32c3-4c19-a816-5bddebf01a6e/download"]}
-{"year":"2024","title":"Generative adversarial network-based phishing URL detection with variational autoencoder and transformer","authors":["JK Sasi, A Balakrishnan - Int J Artif Intell, 2024"],"snippet":"Phishing attacks pose a constant threat to online security, necessitating the development of efficient tools for identifying malicious URLs. In this article, we propose a novel approach to detect phishing URLs employing a generative …","url":["https://www.researchgate.net/profile/Jishnu-K-S/publication/380184574_Generative_adversarial_network-based_phishing_URL_detection_with_variational_autoencoder_and_transformer/links/66308f2b06ea3d0b7419acb6/Generative-adversarial-network-based-phishing-URL-detection-with-variational-autoencoder-and-transformer.pdf"]}
-{"year":"2024","title":"Generative AI and Large Language Models for Cyber Security: All Insights You Need","authors":["MA Ferrag, F Alwahedi, A Battah, B Cherif, A Mechri… - arXiv preprint arXiv …, 2024"],"snippet":"This paper provides a comprehensive review of the future of cybersecurity through Generative AI and Large Language Models (LLMs). We explore LLM applications across various domains, including hardware design security, intrusion detection …","url":["https://arxiv.org/pdf/2405.12750"]}
-{"year":"2024","title":"Generative AI and the Continuing Importance of Information Literacy","authors":["L Svoboda, J Dean - 2024"],"snippet":"GAI models are embedded in a variety of applications. These models are trained using existing information, which is then formatted and delivered within the context of the GAI application. Bias, misand disinformation, and ethical use of information …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/192763/DeanSvoboda-GenAI-InfoLit-Final.pdf?sequence=1"]}
-{"year":"2024","title":"Generative AI for Math: Part I--MathPile: A Billion-Token-Scale Pretraining Corpus for Math","authors":["Z Wang, R Xia, P Liu - arXiv preprint arXiv:2312.17120, 2023"],"snippet":"… expanse of Common Crawl snapshots, a venture we aim to pursue in our future work. … We provide a near-duplicate example found in Common Crawl, as shown in 2 (See Table 8 to … StackExchange that appeared in a document from Common …","url":["https://arxiv.org/pdf/2312.17120"]}
-{"year":"2024","title":"Generative AI for Unmanned Vehicle Swarms: Challenges, Applications and Opportunities","authors":["G Liu, N Van Huynh, H Du, DT Hoang, D Niyato, K Zhu… - arXiv preprint arXiv …, 2024"],"snippet":"With recent advances in artificial intelligence (AI) and robotics, unmanned vehicle swarms have received great attention from both academia and industry due to their potential to provide services that are difficult and dangerous to perform by humans …","url":["https://arxiv.org/pdf/2402.18062"]}
-{"year":"2024","title":"Generative AI from Theory to Practice: A Case Study of Financial Advice","authors":["AW Lo, J Ross - 2024"],"snippet":"We identify some of the most pressing issues facing the adoption of large language models (LLMs) in practical settings and propose a research agenda to reach the next technological inflection point in generative AI. We focus on three challenges …","url":["https://mit-genai.pubpub.org/pub/l89uu140"]}
-{"year":"2024","title":"Generative AI in Education From the Perspective of Students, Educators, and Administrators","authors":["A Ghimire - 2024"],"snippet":"This research explores how advanced artificial intelligence (AI), like the technology that powers tools such as ChatGPT, is changing the way we teach and learn in schools and universities. Imagine AI helping to summarize thick legal documents …","url":["https://digitalcommons.usu.edu/cgi/viewcontent.cgi?article=1119&context=etd2023"]}
-{"year":"2024","title":"Generative AI","authors":["WR Business, T Taulli"],"snippet":"… • CommonCrawl News: This is a dataset of news stories from websites across the globe. …","url":["https://link.springer.com/content/pdf/10.1007/978-1-4842-9367-6.pdf"]}
-{"year":"2024","title":"Generative AI, Plagiarism, and Copyright Infringement in Legal Documents","authors":["AB Cyphert - Minnesota Journal of Law, Science & Technology, 2024"],"snippet":"… OpenAI acknowledged in the GPT-3 research paper that GPT-3 was trained on the Common Crawl dataset, “which includes everything from traditional news sites like the New York Times to sites like Reddit.” Cyphert, supra note 1, at 407, citing Liz …","url":["https://scholarship.law.umn.edu/cgi/viewcontent.cgi?article=1564&context=mjlst"]}
-{"year":"2024","title":"Generative AI-Based Text Generation Methods Using Pre-Trained GPT-2 Model","authors":["R Pandey, H Waghela, S Rakshit, A Rangari, A Singh… - arXiv preprint arXiv …, 2024"],"snippet":"This work delved into the realm of automatic text generation, exploring a variety of techniques ranging from traditional deterministic approaches to more modern stochastic methods. Through analysis of greedy search, beam search, top-k …","url":["https://arxiv.org/pdf/2404.01786"]}
-{"year":"2024","title":"Generative Artificial Intelligence: Models, Benefits, Dangers and Detection of AI-Generated Text on Specialized Domains","authors":["IN Mitrou - 2024"],"snippet":"… However, Radford et al. found that a large amount of document within the hashed pages of Common Crawl was unintelligible. A new approach could be to simply use a curated subset of Common Crawl, but they also created a web scrape from Reddit …","url":["https://pergamos.lib.uoa.gr/uoa/dl/object/3393769/file.pdf"]}
-{"year":"2024","title":"Generative Knowledge Management for Financial Inclusion Through Financial Literacy: A Systematic Review.","authors":["S Vadari, C Malladi - IUP Journal of Knowledge Management, 2024"],"snippet":"… OpenAI utilized an openly available corpus of webpages called Common Crawl, which in turn derives from a bot that crawls the entire Internet. This Common Crawl dataset contains billions of webpages and is one of the colossal textual datasets …","url":["https://search.ebscohost.com/login.aspx?direct=true&profile=ehost&scope=site&authtype=crawler&jrnl=25834592&AN=175575074&h=sCel50fK50xEllhIJpNI7DkOR%2BVRtNQcL6GAPBohcUUqh69TZ2AXa6cLuU8G8cSdXlqrcR2ViJzZZ2Q1%2FABnIQ%3D%3D&crl=c"]}
-{"year":"2024","title":"GeniL: A Multilingual Dataset on Generalizing Language","authors":["AM Davani, S Gubbi, S Dev, S Dave, V Prabhakaran - arXiv preprint arXiv …, 2024"],"snippet":"… For each language, we queried the Multilingual Common Crawl (mC4) language corpus to collect naturally occurring sentences that contain both the terms in the tuples present in SGM. To ensure a diverse representation of different associations …","url":["https://arxiv.org/pdf/2404.05866"]}
-{"year":"2024","title":"German Text Embedding Clustering Benchmark","authors":["S Wehrli, B Arnrich, C Irrgang - arXiv preprint arXiv:2401.02709, 2024"],"snippet":"This work introduces a benchmark assessing the performance of clustering German text embeddings in different domains. This benchmark is driven by the increasing use of clustering neural text embeddings in tasks that require the grouping of texts (such …","url":["https://arxiv.org/pdf/2401.02709"]}
-{"year":"2024","title":"GFWeb: Measuring the Great Firewall's Web Censorship at Scale","authors":["NP Hoang, J Dalek, M Crete-Nishihata, N Christin…"],"snippet":"… Aggregating the ranking information provided by the Tranco list [62] and the Common Crawl dataset [1], we analyze the popularity of the base censored domains discovered by GFWeb for HTTP(S) filters in comparison to the GFWatch (DNS filter) …","url":["https://www3.cs.stonybrook.edu/~mikepo/papers/gfweb.sec24.pdf"]}
-{"year":"2024","title":"Ghost Sentence: A Tool for Everyday Users to Copyright Data from Large Language Models","authors":["S Zhao, L Zhu, R Quan, Y Yang - arXiv preprint arXiv:2403.15740, 2024"],"snippet":"Web user data plays a central role in the ecosystem of pre-trained large language models (LLMs) and their fine-tuned variants. Billions of data are crawled from the web and fed to LLMs. How can \\textit{\\textbf{everyday web users}} confirm if LLMs …","url":["https://arxiv.org/html/2403.15740v1"]}
-{"year":"2024","title":"GPTs: Concerns, Limitations and (Some) Responses","authors":["M Frické"],"snippet":"… The ones of these that are large and containing substantial source material from the Internet (eg from Common Crawl) will have some harms of representation bias. Then, if the training data has bias then so too will LLMs. To address this, there seem …","url":["https://ischool.arizona.edu/sites/ischool.arizona.edu/files/2024-04/Fricke%CC%81%20Information%20on%20Tap.pdf"]}
-{"year":"2024","title":"Grammatical versus Spelling Error Correction: An Investigation into the Responsiveness of Transformer-Based Language Models Using BART and MarianMT","authors":["R Raju, PB Pati, SA Gandheesh, GS Sannala… - Journal of Information & …, 2024"],"snippet":"Text continues to remain a relevant form of representation for information. Text documents are created either in digital native platforms or through the conversion of other media files such as images and speech. While the digital native text is …","url":["https://www.worldscientific.com/doi/abs/10.1142/S0219649224500370"]}
-{"year":"2024","title":"Grammatical vs Spelling Error Correction: An Investigation into the Responsiveness of Transformer-based Language Models using BART and MarianMT","authors":["R Raju, PB Pati, SA Gandheesh, GS Sannala, S KS - arXiv preprint arXiv:2403.16655, 2024"],"snippet":"… C4 Dataset is an Open-Source dataset obtained with Common Crawl web scrape [30]. This dataset contains millions of collected sentences along with their target sentences. The collected statements, referred to as input sentences in this work …","url":["https://arxiv.org/pdf/2403.16655"]}
-{"year":"2024","title":"Granite Code Models: A Family of Open Foundation Models for Code Intelligence","authors":["M Mishra, M Stallone, G Zhang, Y Shen, A Prasad… - arXiv preprint arXiv …, 2024"],"snippet":"Large Language Models (LLMs) trained on code are revolutionizing the software development process. Increasingly, code LLMs are being integrated into software development environments to improve the productivity of human programmers, and …","url":["https://arxiv.org/pdf/2405.04324"]}
-{"year":"2024","title":"Hallucinating (or poorly fed) LLMs? The problem of data accuracy","authors":["E Stringhi - i-lex, 2023"],"snippet":"… This is the case of “Common Crawl”, which consists in a massive collection of web pages and … To give a picture, the Common Crawl dataset constitutes nearly a trillion words. … were publicly available online and memorised in the Common …","url":["https://i-lex.unibo.it/article/download/18877/17434"]}
-{"year":"2024","title":"Harder Tasks Need More Experts: Dynamic Routing in MoE Models","authors":["Q Huang, Z An, N Zhuang, M Tao, C Zhang, Y Jin, K Xu… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we introduce a novel dynamic expert selection framework for Mixture of Experts (MoE) models, aiming to enhance computational efficiency and model performance by adjusting the number of activated experts based on input difficulty …","url":["https://arxiv.org/html/2403.07652v1"]}
-{"year":"2024","title":"Hardware Phi-1.5 B: A Large Language Model Encodes Hardware Domain Specific Knowledge","authors":["W Fu, S Li, Y Zhao, H Ma, R Dutta, X Zhang, K Yang…"],"snippet":"… The first segment includes data from specialized platforms such as Arxiv , Books, Wikipedia, and StackExchange; the second segment is derived from broader internet content via CommonCrawl and C4. Table II provides a comprehensive …","url":["https://ece.k-state.edu/research/hardware-security/papers/ASP_DAC_PreTrainLM_2024_CR.pdf"]}
-{"year":"2024","title":"Harmony in the Australian Domain Space","authors":["X Gong, PX McCarthy, MA Rizoiu, P Boldi - arXiv preprint arXiv:2404.10006, 2024"],"snippet":"… Though not focused on localized networks, the extensive and all-encompassing web graph from Common Crawl utilized in our study enables the extraction of implicit information on a broader scale. … We utilize the datasets mainly from …","url":["https://arxiv.org/pdf/2404.10006"]}
-{"year":"2024","title":"Harnessing Artificial Intelligence in Bariatric Surgery: Comparative Analysis of ChatGPT-4, Bing, and Bard in Generating Clinician-Level Bariatric Surgery …","authors":["Y Lee, T Shin, L Tessier, A Javidan, J Jung, D Hong… - Surgery for Obesity and Related …"],"snippet":"Background The formulation of clinical recommendations pertaining to bariatric surgery is essential in guiding healthcare professionals. However, the extensive and continuously evolving body of literature in bariatric surgery presents considerable …","url":["https://www.soard.org/article/S1550-7289(24)00118-7/fulltext"]}
-{"year":"2024","title":"Harnessing generative AI for overcoming labeled data challenges in social media NLP","authors":["CR Liyanage - 2023"],"snippet":"With the introduction of Transformers and Large Language Models, the field of NLP has significantly evolved. Generative AI, a prominent transformer-based technology for crafting human-like content, has proven powerful skills across numerous NLP …","url":["https://knowledgecommons.lakeheadu.ca/bitstream/handle/2453/5275/LiyanageC2023m-1a.pdf?sequence=1&isAllowed=y"]}
-{"year":"2024","title":"Harnessing the Power of Metadata for Enhanced Question Retrieval in Community Question Answering","authors":["S Ghasemi, A Shakery - IEEE Access, 2024"],"snippet":"… GPT-3 was trained on an open source dataset called ‘CommonCrawl’ and other texts from OpenAI such as Wikipedia entries. GPT-4 is the newest version of OpenAI’s language model systems. In this article, we fine-tune GPT-2 and GPT-3 pretrained …","url":["https://ieeexplore.ieee.org/iel7/6287639/10380310/10525684.pdf"]}
-{"year":"2024","title":"HCI International 2024 Posters: 26th International Conference on Human-Computer Interaction, HCII 2024, Washington, DC, USA, June 29–July 4, 2024, Proceedings …","authors":["C Stephanidis - 2024"],"snippet":"Preliminary scientific results, professional news, or work in progress, described in the form of short research papers (4–11 pages long), constitute a popular submission type among the International Conference on Human-Computer …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=aMULEQAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=hRNpPdcSEp&sig=R0smc7pGlEGxpECYA1HDV-wXEBA"]}
-{"year":"2024","title":"HGT: Leveraging Heterogeneous Graph-enhanced Large Language Models for Few-shot Complex Table Understanding","authors":["R Jin, Y Li, G Qi, N Hu, YF Li, J Chen, J Wang, Y Chen… - arXiv preprint arXiv …, 2024"],"snippet":"Table understanding (TU) has achieved promising advancements, but it faces the challenges of the scarcity of manually labeled tables and the presence of complex table structures.To address these challenges, we propose HGT, a framework with a …","url":["https://arxiv.org/pdf/2403.19723"]}
-{"year":"2024","title":"Hierarchical Multimodal Pre-training for Visually Rich Webpage Understanding","authors":["H Xu, L Chen, Z Zhao, D Ma, R Cao, Z Zhu, K Yu - arXiv preprint arXiv:2402.18262, 2024"],"snippet":"… Common Crawl is a publicly available web crawl dataset that collects webpages from the internet. Instead of using the source code, we collect webpage links from Common Crawl. We traverse all links in a dataset snapshot 4 and categorize and …","url":["https://arxiv.org/pdf/2402.18262"]}
-{"year":"2024","title":"Higher Education's Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania","authors":["J Rudolph, MF Ismail, S Popenici - Journal of University Teaching and Learning …, 2024"],"snippet":"Higher education is currently under a significant transformation due to the emergence of generative artificial intelligence (GenAI) technologies, the hype surrounding GenAI and the increasing influence of educational technology business …","url":["https://www.researchgate.net/profile/Stefan-Popenici/publication/379956424_Higher_Education's_Generative_Artificial_Intelligence_Paradox_The_Meaning_of_Chatbot_Mania/links/66237af9f7d3fc2874703875/Higher-Educations-Generative-Artificial-Intelligence-Paradox-The-Meaning-of-Chatbot-Mania.pdf"]}
-{"year":"2024","title":"Historical Dutch Spelling Normalization with Pretrained Language Models","authors":["A Wolters, A Van Cranenburgh - Computational Linguistics in the Netherlands …, 2024"],"snippet":"… These texts are from the common crawl corpus, which contains petabytes of data scraped from the internet. Further pretraining on in-domain data can make the model more suited for the downstream task it will be finetuned for, and since our task …","url":["https://www.clinjournal.org/clinj/article/download/178/194"]}
-{"year":"2024","title":"History, Development, and Principles of Large Language Models-An Introductory Survey","authors":["Z Chu, S Ni, Z Wang, X Feng, C Li, X Hu, R Xu, M Yang… - arXiv preprint arXiv …, 2024"],"snippet":"Language models serve as a cornerstone in natural language processing (NLP), utilizing mathematical methods to generalize language laws and knowledge for prediction and generation. Over extensive research spanning decades, language …","url":["https://arxiv.org/pdf/2402.06853"]}
-{"year":"2024","title":"Holographic Embeddings for Text and Graphs A Master's Thesis Presented to The Faculty of the Graduate School of Arts and Sciences","authors":["T Obiso - 2024"],"snippet":"… Static word embeddings such as word2vec, Global Vectors for Word Representation (GloVe), and fastText are trained on large amounts of natural language text sources like Common Crawl and Wikipedia dumps. These models …","url":["https://scholarworks.brandeis.edu/view/pdfCoverPage?instCode=01BRAND_INST&filePid=13511842530001921&download=true"]}
-{"year":"2024","title":"Homonym Sense Disambiguation in the Georgian Language","authors":["D Melikidze, A Gamkrelidze - arXiv preprint arXiv:2405.00710, 2024"],"snippet":"This research proposes a novel approach to the Word Sense Disambiguation (WSD) task in the Georgian language, based on supervised fine-tuning of a pre-trained Large Language Model (LLM) on a dataset formed by filtering the Georgian …","url":["https://arxiv.org/pdf/2405.00710"]}
-{"year":"2024","title":"How Do We Learn What We Cannot Say?","authors":["D Yakubov - 2024"],"snippet":"The contributions of this thesis are two-fold. First, this thesis presents UDTube, an easily usable software developed to perform morphological analysis in a multi-task fashion. This work shows the strong performance of UDTube versus the current state-of-the-art …","url":["https://academicworks.cuny.edu/cgi/viewcontent.cgi?article=6726&context=gc_etds"]}
-{"year":"2024","title":"How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites","authors":["Z Chen, W Wang, H Tian, S Ye, Z Gao, E Cui, W Tong… - arXiv preprint arXiv …, 2024"],"snippet":"In this report, we introduce InternVL 1.5, an open-source multimodal large language model (MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding. We introduce three simple …","url":["https://arxiv.org/pdf/2404.16821"]}
-{"year":"2024","title":"How Gender Interacts with Political Values: A Case Study on Czech BERT Models","authors":["AA Ali, J Libovický - arXiv preprint arXiv:2403.13514, 2024"],"snippet":"Neural language models, which reach state-of-the-art results on most natural language processing tasks, are trained on large text corpora that inevitably contain value-burdened content and often capture undesirable biases, which the models …","url":["https://arxiv.org/pdf/2403.13514"]}
-{"year":"2024","title":"How Large Corpora Sizes Influence the Distribution of Low Frequency Text n-grams","authors":["JF Silva, JC Cunha - Pacific-Asia Conference on Knowledge Discovery and …, 2024"],"snippet":"The prediction of the numbers of distinct word n-grams and their frequency distributions in text corpora is important in domains like information processing and language modelling. With big data corpora, there is an increased application …","url":["https://link.springer.com/chapter/10.1007/978-981-97-2259-4_16"]}
-{"year":"2024","title":"How Lexical is Bilingual Lexicon Induction?","authors":["H Kohli, H Feng, N Dronen, C McCarter, S Moeini… - arXiv preprint arXiv …, 2024"],"snippet":"… derived from Common Crawl and Wikipedia. The plot visualizes the Spearman’s Rank correlation of term frequencies between each of the source (by row) and target (by column) language pairs in the 5k vocabularies in the XLING corpus derived from …","url":["https://arxiv.org/pdf/2404.04221"]}
-{"year":"2024","title":"How many news websites block AI crawlers?","authors":["R Fletcher - 2024"],"snippet":"In this factsheet we describe the proportion of news websites in ten countries that block AI (artificial intelligence) crawlers. We find that, (i) by the end 2023, 48% of the most widely used news websites across ten countries were blocking OpenAI’s (ChatGPT) …","url":["https://ora.ox.ac.uk/objects/uuid:6b0653e7-4a3b-4448-b0bd-1bdbd55aa61e/files/s3j333388m"]}
-{"year":"2024","title":"How Much are LLMs Contaminated? A Comprehensive Survey and the LLMSanitize Library","authors":["M Ravaut, B Ding, F Jiao, H Chen, X Li, R Zhao, C Qin… - arXiv preprint arXiv …, 2024"],"snippet":"… This includes policies and protocols for data privacy, consent, and use that help prevent the incorporation of contaminated data from unethical sources and the contamination of widely used pre-training data sources (eg, CommonCrawl) …","url":["https://arxiv.org/pdf/2404.00699"]}
-{"year":"2024","title":"How to Train Data-Efficient LLMs","authors":["N Sachdeva, B Coleman, WC Kang, J Ni, L Hong… - arXiv preprint arXiv …, 2024"],"snippet":"The training of large language models (LLMs) is expensive. In this paper, we study data-efficient approaches for pre-training LLMs, ie, techniques that aim to optimize the Pareto frontier of model quality and training resource/data consumption. We …","url":["https://arxiv.org/pdf/2402.09668"]}
-{"year":"2024","title":"HPLT's First Release of Data and Models","authors":["N Arefyev, M Aulamo, P Chen, O de Gibert, B Haddow… - 2024"],"snippet":"… Datasets For the first release, we processed 1.85 petabytes of the Internet Archive and CommonCrawl to create monolingual and parallel corpora. We release them under the permissive CC0 licence1 through our project website2, OPUS3, and Hugging …","url":["https://pinzhenchen.github.io/paper/2024-hplt-project.pdf"]}
-{"year":"2024","title":"Human-Centered Interaction in Virtual Worlds: A New Era of Generative Artificial Intelligence and Metaverse","authors":["Y Wang, L Wang, KL Siau - International Journal of Human–Computer Interaction, 2024"],"snippet":"The metaverse has emerged as an exciting new paradigm for human-computer interaction (HCI) and virtual collaboration. This paper presents a comprehensive review of the metaverse to address the gap in the existing literature where there is a …","url":["https://www.tandfonline.com/doi/abs/10.1080/10447318.2024.2316376"]}
-{"year":"2024","title":"Human-Centered Natural Language Processing for Countering Misinformation","authors":["A Kazemi - 2024"],"snippet":"As curbing the spread of online misinformation has proven to be challenging, we look to artificial intelligence (AI) and natural language technology for helping individuals and society counter and limit it. Despite current advances, state-of-the-art …","url":["https://deepblue.lib.umich.edu/bitstream/handle/2027.42/193271/ashkank_1.pdf?sequence=1"]}
-{"year":"2024","title":"Hybrid semantic models for building smart and robust home robots","authors":["A Pal - 2023"],"snippet":"The creation of home robots that can aid human beings in daily mundane chores has been a long-standing goal of robotics research. Some common indoor tasks that service robots can help with include retrieving objects from different locations …","url":["https://escholarship.org/content/qt92w4x2f1/qt92w4x2f1.pdf"]}
-{"year":"2024","title":"HYPE: Hyperbolic Entailment Filtering for Underspecified Images and Texts","authors":["W Kim, S Chun, T Kim, D Han, S Yun - arXiv preprint arXiv:2404.17507, 2024"],"snippet":"In an era where the volume of data drives the effectiveness of self-supervised learning, the specificity and clarity of data semantics play a crucial role in model training. Addressing this, we introduce HYPerbolic Entailment filtering (HYPE), a …","url":["https://arxiv.org/pdf/2404.17507"]}
-{"year":"2024","title":"Hypertext Entity Extraction in Webpage","authors":["Y Yang, T Liu, B Shao, H Zhao, L Shou, M Gong… - arXiv preprint arXiv …, 2024"],"snippet":"��� Common Crawl5 is a widely used large-scale dataset for IE. However, they all overlook rich hypertext features and contain too much noise. Moreover, their annotations are often determined by rules or automated tools, lacking accurate manual annotations. …","url":["https://arxiv.org/html/2403.01698v1"]}
-{"year":"2024","title":"I'm In! A Comparative Analysis of Business Pitch Competition","authors":["E Barron, I Bernatovic, LE Ruiz - DIANA INTERNATIONAL RESEARCH …, 2023"],"snippet":"Methods Based on a perceived theoretical gap in research, entrepreneurship scholars have called for increased research to understand how institutions (including governments and academia), influence the construction of intersectional …","url":["https://pure.udem.edu.mx/files/73675582/Conference_Proceedings_Diana_International_Research_Conference_2023_PDF_.pdf"]}
-{"year":"2024","title":"Identification of patients' smoking status using an explainable AI approach: a Danish electronic health records case study","authors":["A Ebrahimi, MBH Henriksen, CL Brasen, O Hilberg… - BMC Medical Research …, 2024"],"snippet":"Smoking is a critical risk factor responsible for over eight million annual deaths worldwide. It is essential to obtain information on smoking habits to advance research and implement preventive measures such as screening of high-risk …","url":["https://bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-024-02231-4"]}
-{"year":"2024","title":"iDRAMA-rumble-2024: A Dataset of Podcasts from Rumble Spanning 2020 to 2022","authors":["U Balci, J Patel, B Balci, J Blackburn - 2024"],"snippet":"Rumble has emerged as a prominent platform hosting controversial figures facing restrictions on YouTube. Despite this, the academic community’s engagement with Rumble has been minimal. To help researchers address this gap, we introduce a …","url":["https://workshop-proceedings.icwsm.org/pdf/2024_07.pdf"]}
-{"year":"2024","title":"IGOT: Information Gain Optimized Tokenizer on Domain Adaptive Pretraining","authors":["D Feng, Y Zhang, Z Xu - arXiv preprint arXiv:2405.09857, 2024"],"snippet":"Pretrained Large Language Models (LLM) such as ChatGPT, Claude, etc. have demonstrated strong capabilities in various fields of natural language generation. However, there are still many problems when using LLM in specialized domain-specific …","url":["https://arxiv.org/pdf/2405.09857"]}
-{"year":"2024","title":"Impact of COVID-19 Pandemic on Social Determinants of Health Issues of Marginalized Black and Asian Communities: A Social Media Analysis Empowered by …","authors":["C Whitfield, Y Liu, M Anwar - Journal of Racial and Ethnic Health Disparities, 2024"],"snippet":"Purpose This study aims to understand the impact of the COVID-19 pandemic on social determinants of health (SDOH) of marginalized racial/ethnic US population groups, specifically African Americans and Asians, by leveraging natural language …","url":["https://link.springer.com/article/10.1007/s40615-024-01996-0"]}
-{"year":"2024","title":"Improved methodology for longitudinal Web analytics using Common Crawl","authors":["HS Thompson - 16th ACM Web Science Conference 2024, 2024"],"snippet":"Common Crawl is a multi-petabyte longitudinal dataset containing over 100 billion web pages which is widely used as a source of language data for sequence model training and in web science research. Each of its constituent archives is on the order …","url":["https://www.research.ed.ac.uk/en/publications/improved-methodology-for-longitudinal-web-analytics-using-common-"]}
-{"year":"2024","title":"Improving Bengali and Hindi Large Language Models","authors":["A Shahriar, D Barbosa - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"Despite being widely spoken worldwide, Bengali and Hindi are low-resource languages. The state-of-the-art in modeling such languages uses BERT and the Wordpiece tokenizer. We observed that the Wordpiece tokenizer often breaks words …","url":["https://aclanthology.org/2024.lrec-main.764.pdf"]}
-{"year":"2024","title":"Improving Cross-lingual Representation for Semantic Retrieval with Code-switching","authors":["M Maimaiti, Y Zheng, J Zhang, F Huang, Y Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"Semantic Retrieval (SR) has become an indispensable part of the FAQ system in the task-oriented question-answering (QA) dialogue scenario. The demands for a cross-lingual smart-customer-service system for an e-commerce platform or some particular …","url":["https://arxiv.org/html/2403.01364v1"]}
-{"year":"2024","title":"INCLURE: a Dataset and Toolkit for Inclusive French Translation","authors":["P Lerner, C Grouin - The 17th Workshop on Building and Using …, 2024"],"snippet":"… Indeed, this corpus mostly contains transcripts of political speeches, whose oral style differs from the text typically found in OSCAR/CommonCrawl. Exceptions are six examples used to illustrate the use of the inclusive neutralization process …","url":["https://hal.science/hal-04531938/document"]}
-{"year":"2024","title":"Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition","authors":["K Buettner, S Malakouti, XL Li, A Kovashka - arXiv preprint arXiv:2401.01482, 2024"],"snippet":"Existing object recognition models have been shown to lack robustness in diverse geographical scenarios due to significant domain shifts in design and context. Class representations need to be adapted to more accurately reflect an object concept …","url":["https://arxiv.org/pdf/2401.01482"]}
-{"year":"2024","title":"IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Context","authors":["NR Sahoo, PP Kulkarni, N Asad, A Ahmad, T Goyal… - arXiv preprint arXiv …, 2024"],"snippet":"The pervasive influence of social biases in language data has sparked the need for benchmark datasets that capture and evaluate these biases in Large Language Models (LLMs). Existing efforts predominantly focus on English language and the …","url":["https://arxiv.org/pdf/2403.20147"]}
-{"year":"2024","title":"IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages","authors":["MSUR Khan, P Mehta, A Sankar, U Kumaravelan… - arXiv preprint arXiv …, 2024"],"snippet":"Despite the considerable advancements in English LLMs, the progress in building comparable models for other languages has been hindered due to the scarcity of tailored resources. Our work aims to bridge this divide by introducing an expansive …","url":["https://arxiv.org/pdf/2403.06350"]}
-{"year":"2024","title":"Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors","authors":["Y Lu, MYR Yang, G Kamath, Y Yu - arXiv preprint arXiv:2402.12626, 2024"],"snippet":"… To collect such large-scale datasets, practitioners usually extract the desired data by crawling on the internet (eg, web pages using Common Crawl1). However, using outsourced data raises an imminent security risk (Kumar et al. 2020; Nelson et al …","url":["https://arxiv.org/html/2402.12626v1"]}
-{"year":"2024","title":"Individual-vs. Multiple-Objective Strategies for Targeted Sentiment Analysis in Finances Using the Spanish MTSA 2023 Corpus","authors":["R Pan, JA García-Díaz, R Valencia-García - Electronics, 2024"],"snippet":"… complexity; (vi) RoBERTuito [22], a pretrained language model for user-generated content in Spanish, trained following RoBERTa guidelines on 500 million tweets; and (vii) XLM-RoBERTa [17], a multilingual version of RoBERTa, trained with data …","url":["https://www.mdpi.com/2079-9292/13/4/717/pdf"]}
-{"year":"2024","title":"IndoBerea: Evolving Semantic Search in Theological Context","authors":["FVP Samosir, S Mendrofa - 2023 Eighth International Conference on Informatics …, 2023"],"snippet":"This paper presents IndoBerea, a semantic search model pre-trained on an Indonesian Bible dataset and based on SentenceTransformers and IndoBERT. It aims to enhance theological research by providing contextually relevant verses in …","url":["https://ieeexplore.ieee.org/abstract/document/10382053/"]}
-{"year":"2024","title":"INDUS: Effective and Efficient Language Models for Scientific Applications","authors":["B Bhattacharjee, A Trivedi, M Muraoka… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs trained using domain-focused corpora perform better …","url":["https://arxiv.org/pdf/2405.10725"]}
-{"year":"2024","title":"Inference-Based No-Learning Approach on Pre-Trained BERT Model Retrieval","authors":["HL Pham, R Mibayashi, T Yamamoto, MP Kato… - 2024 IEEE International …, 2024"],"snippet":"In recent years, the practice of leveraging pre-trained machine learning models for specific tasks has gained traction. Instead of training models from the ground up, it is now common to fine-tune existing pre-trained models. However, users have the …","url":["https://ieeexplore.ieee.org/abstract/document/10488314/"]}
-{"year":"2024","title":"Inferring the Phylogeny of Large Language Models and Predicting their Performances in Benchmarks","authors":["N Yax, PY Oudeyer, S Palminteri - arXiv preprint arXiv:2404.04671, 2024"],"snippet":"This paper introduces PhyloLM, a method applying phylogenetic algorithms to Large Language Models to explore their finetuning relationships, and predict their performance characteristics. By leveraging the phylogenetic distance metric, we …","url":["https://arxiv.org/html/2404.04671v1"]}
-{"year":"2024","title":"Information Retrieval Chatbot on Military Policies and Standards","authors":["C Gunasekara, A Sharafeldin, M Triff, Z Kabir…"],"snippet":"In the Canadian Armed Forces (CAF), navigating through extensive policies and standards can be a challenging task. To address the need for streamlined access to these vital documents, this paper explores the usage of artificial intelligence (AI) and …","url":["https://www.scitepress.org/Papers/2024/123512/123512.pdf"]}
-{"year":"2024","title":"Information Retrieval with Dense and Sparse Representations","authors":["YS Chuang - 2024"],"snippet":"… However, they use 1TB of the training data from Common Crawl dumps while our model only use 115MB of the Wikipedia data for pretraining. We put their scores in Table 2.2 for reference. In SimCSE, the authors propose to use MLM as an auxiliary …","url":["https://dspace.mit.edu/bitstream/handle/1721.1/153774/chuang-yungsung-sm-eecs-2024-thesis.pdf?sequence=1&isAllowed=y"]}
-{"year":"2024","title":"Innovative Use of Self-Attention-Based Ensemble Deep Learning for Suicide Risk Detection in Social Media Posts","authors":["HS Choi, J Yang - Applied Sciences, 2024"],"snippet":"… Specifically, we employed the extensive corpus variant, known as “Common Crawl (840 B tokens, 2.2 M vocab, cased, 300 d vectors)”, which encompasses an impressive 840 billion tokens, a vocabulary of 2.2 million cased terms, and provides …","url":["https://www.mdpi.com/2076-3417/14/2/893"]}
-{"year":"2024","title":"Instruction-tuned Language Models are Better Knowledge Learners","authors":["Z Jiang, Z Sun, W Shi, P Rodriguez, C Zhou, G Neubig… - arXiv preprint arXiv …, 2024"],"snippet":"… However, its scope is limited to Wikipedia, which restricts the trained models’ adaptability to other sources like web pages from Common Crawl or scientific documents from arXiv. We focus on eliciting factual knowledge with instruction-tuning …","url":["https://arxiv.org/pdf/2402.12847"]}
-{"year":"2024","title":"Integrating Generative AI Literacy into the Information Retrieval Course at a university in Canada: towards critical evaluation of online search results","authors":["L Kleinveldt"],"snippet":"… • Trained on information (billions of words) on the open web prior to 2021 • Among other open sources, dataset comes from Common Crawl (crawls the web) and Wikipedia • Length of answers limited - between 500 and 700 words, “leaving …","url":["https://bibliotecas.uchile.cl/congreso/programa/ponencias/dia_3/8_Presentation_Integrating_Generative_AI_Literacy.pdf"]}
-{"year":"2024","title":"Intelligent Pharmacy","authors":["A Haleem, M Javaid, RP Singh"],"snippet":"The modern language generation model ChatGPT, created by Open Artificial Intelligence (AI), is recognised for its capacity to comprehend context and produce pertinent content. This model is built on the transformer architecture, which enables …","url":["https://www.researchgate.net/profile/Mohd-Javaid/publication/379261748_Exploring_the_competence_of_ChatGPT_for_customer_and_patient_service_management/links/660e825af5a5de0a9ffb6418/Exploring-the-competence-of-ChatGPT-for-customer-and-patient-service-management.pdf"]}
-{"year":"2024","title":"Intelligent Phishing Website Detection Model Powered by Deep Learning Techniques","authors":["U Chetachi, O Henry, OA Agbugba - Asian Journal of Research in Computer …, 2024"],"snippet":"… Approximately one million authentic and fraudulent URLs were employed in the dataset gathered from PhishTank and Common Crawl. Over 10,000 images and one million URLs were used in training for the CNN classifier and LSTM to create the …","url":["http://science.sdpublishers.org/id/eprint/2498/1/Chetachi1762023AJRCOS111125.pdf"]}
-{"year":"2024","title":"Intercity relationships between 293 Chinese cities quantified based on toponym co-occurrence","authors":["W Tongjing, Z Yin, Z Bao, E Meijers - Cybergeo: European Journal of Geography, 2024"],"snippet":"… 14The primary dataset of this study was obtained from the Common Crawl, a web archive that has periodically crawled the Internet since … We used the entire Common Crawl text archive from April 2019 for processing and conducting …","url":["https://journals.openedition.org/cybergeo/40721"]}
-{"year":"2024","title":"International Journal of Cognitive Computing in Engineering","authors":["JF Ruma, TT Mayeesha, RM Rahman"],"snippet":"… MC4 dataset contains 101 language variants drawn from the Common Crawl web scrape. MT5 did not deviates much from the original T5 model and attempted to extend the capacities of the T5 to multilingual settings. T5 is a pre-trained language …","url":["https://www.researchgate.net/profile/Tahsin-Mayeesha-2/publication/373997715_Transformer_based_Answer-Aware_Bengali_Question_Generation/links/65b4bfe81bed776ae307bf9f/Transformer-based-Answer-Aware-Bengali-Question-Generation.pdf"]}
-{"year":"2024","title":"Internet-scale Topic Modeling using Large Language Models","authors":["R Kajoluoto - 2024"],"snippet":"… This proportion is estimated from the Common Crawl dataset’s statistics [28]. In short, the model should have an excellent understanding of English, an adequate understanding of languages such as German and Spanish, and be satisfactory at …","url":["https://aaltodoc.aalto.fi/bitstreams/b63ce9d3-a01a-48a1-8ff7-831c872fde9d/download"]}
-{"year":"2024","title":"InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning","authors":["H Ying, S Zhang, L Li, Z Zhou, Y Shao, Z Fei, Y Ma… - arXiv preprint arXiv …, 2024"],"snippet":"The math abilities of large language models can represent their abstract reasoning ability. In this paper, we introduce and open-source our math reasoning LLMs InternLM-Math which is continue pre-trained from InternLM2. We unify chain-of-thought …","url":["https://arxiv.org/pdf/2402.06332"]}
-{"year":"2024","title":"InternLM2 Technical Report","authors":["Z Cai, M Cao, H Chen, K Chen, K Chen, X Chen… - arXiv preprint arXiv …, 2024"],"snippet":"… Our web page data mainly comes from Common Crawl1. Firstly, we need to decompress the original Warc format files and use Trafilatura (… The entire filtering process eliminates a large proportion of Web page data (Common Crawl) and Patent …","url":["https://arxiv.org/pdf/2403.17297"]}
-{"year":"2024","title":"Interpretable Tensor Fusion","authors":["S Varshneya, A Ledent, P Liznerski, A Balinskyy… - arXiv preprint arXiv …, 2024"],"snippet":"Conventional machine learning methods are predominantly designed to predict outcomes based on a single data type. However, practical applications may encompass data of diverse types, such as text, images, and audio. We introduce …","url":["https://arxiv.org/pdf/2405.04671"]}
-{"year":"2024","title":"Interpreting Themes from Educational Stories","authors":["Y Zhang, FA González, T Solorio - arXiv preprint arXiv:2404.05250, 2024"],"snippet":"Reading comprehension continues to be a crucial research focus in the NLP community. Recent advances in Machine Reading Comprehension (MRC) have mostly centered on literal comprehension, referring to the surface-level …","url":["https://arxiv.org/pdf/2404.05250"]}
-{"year":"2024","title":"Intersectional Male-Centric and White-Centric Biases in Collective Concepts","authors":["AH Bailey, A Williams, A Poddar, A Cimpian - 2024"],"snippet":"… Here we used NLP tools (specifically, static word embeddings trained on the Common Crawl corpus) to investigate collective understanding of three fundamental concepts: PERSON, WOMAN, and MAN.These three concepts organize much of …","url":["https://osf.io/72pg5/download"]}
-{"year":"2024","title":"Introducing the Djinni Recruitment Dataset: A Corpus of Anonymized CVs and Job Postings","authors":["N Drushchak, M Romanyshyn - Proceedings of the Third Ukrainian Natural …, 2024"],"snippet":"This paper introduces the Djinni Recruitment Dataset, a large-scale open-source corpus of candidate profiles and job descriptions. With over 150,000 jobs and 230,000 candidates, the dataset includes samples in English and Ukrainian, thereby …","url":["https://aclanthology.org/2024.unlp-1.2.pdf"]}
-{"year":"2024","title":"Investigating Complex Answer Attribution Approaches with Large Language Models","authors":["L Mülln"],"snippet":"This master’s thesis explores the attribution of answers in complex question-answering scenarios utilizing large language models (LLMs). The research aims to assess and enhance the traceability of answers back to their source documents, a critical aspect …","url":["https://wwwmatthes.in.tum.de/file/833ntsa6pimy/Sebis-Public-Website/Student-Theses-Guided-Research/Current-Theses-Guided-Researches/Master-s-Thesis-Luca-Muelln/240315_LMuelln_Thesis_Final_Print_Version.pdf"]}
-{"year":"2024","title":"Investigating Gender Bias in Turkish Language Models","authors":["O Caglidil, M Ostendorff, G Rehm - arXiv preprint arXiv:2404.11726, 2024"],"snippet":"… an analysis of undesirable content in the common crawl corpus. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2 …","url":["https://arxiv.org/pdf/2404.11726"]}
-{"year":"2024","title":"Investigating the pre-training bias in low-resource abstractive summarization","authors":["D Chernyshev, B Dobrov - IEEE Access, 2024"],"snippet":"Recent advances in low-resource abstractive summarization were largely made through the adoption of specialized pre-training, pseudo-summarization, that integrates the content selection knowledge through various centrality-based …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10474365.pdf"]}
-{"year":"2024","title":"IPA Transcription of Bengali Texts","authors":["K Fatema, FD Haider, NF Turpa, T Azmal, S Ahmed… - arXiv preprint arXiv …, 2024"],"snippet":"The International Phonetic Alphabet (IPA) serves to systematize phonemes in language, enabling precise textual representation of pronunciation. In Bengali phonology and phonetics, ongoing scholarly deliberations persist concerning the …","url":["https://arxiv.org/pdf/2403.20084"]}
-{"year":"2024","title":"IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models","authors":["DI Adelani, J Ojo, IA Azime, JY Zhuang, JO Alabi, X He… - arXiv preprint arXiv …, 2024"],"snippet":"Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource languages. Additionally, many low-resource languages (eg African languages) are often …","url":["https://arxiv.org/pdf/2406.03368"]}
-{"year":"2024","title":"Is AI changing learning and assessment as we know it? Evidence from a ChatGPT experiment and a conceptual framework","authors":["O Kolade, A Owoseni, A Egbetokun - Heliyon, 2024"],"snippet":"ChatGPT, a state-of-the-art chatbot built upon Open AI's generative pre-trained transformer, has generated a major public interest and caused quite a stir in the higher education sector, where reactions have ranged from excitement to …","url":["https://www.sciencedirect.com/science/article/pii/S2405844024019844"]}
-{"year":"2024","title":"Is ChatGPT taking over the language classroom? How language ideologies of large language models impact teaching and learning","authors":["M Lau - Working papers in Applied Linguistics and Linguistics …, 2024"],"snippet":"… Thus, using datasets such as the Common Crawl can lead to the over-representation of English and the perspectives of English-speaking content … This means that LLMs that use Common Crawl for training, such as ChatGPT, may perform with …","url":["https://wally.journals.yorku.ca/index.php/default/article/download/36/34"]}
-{"year":"2024","title":"Is Google Getting Worse? A Longitudinal Investigation of SEO Spam in Search Engines","authors":["J Bevendorff, M Wiegmann, M Potthast, B Stein"],"snippet":"Many users of web search engines have been complaining in recent years about the supposedly decreasing quality of search results. This is often attributed to an increasing amount of search-engineoptimized but low-quality content. Evidence for …","url":["https://downloads.webis.de/publications/papers/bevendorff_2024a.pdf"]}
-{"year":"2024","title":"Is Translation All You Need? A Study on Solving Multilingual Tasks with Large Language Models","authors":["C Liu, W Zhang, Y Zhao, AT Luu, L Bing - arXiv preprint arXiv:2403.10258, 2024"],"snippet":"… We categorize languages larger than 1% frequency in Common Crawl2 as high-resource languages (ie, de, ru, fr, zh, es, ja, it and vi), and the rest as low-resource languages. We exclude English since we want to evaluate the efficient prompting strategy for …","url":["https://arxiv.org/pdf/2403.10258"]}
-{"year":"2024","title":"It's About Time: Incorporating Temporality in Retrieval Augmented Language Models","authors":["A Gade, J Jetcheva - arXiv preprint arXiv:2401.13222, 2024"],"snippet":"… Additionally both models are fine-tuned jointly as a Fusion-in-Decoder [3] on common-crawl data using Wikipedia as a document index. The authors showed that Atlas performs well out-of-box and can be adapted to different tasks such as question-answering …","url":["https://arxiv.org/pdf/2401.13222"]}
-{"year":"2024","title":"IUST at ClimateActivism 2024: Towards Optimal Stance Detection: A Systematic Study of Architectural Choices and Data Cleaning Techniques","authors":["G Mahmoudi, S Eetemadi - Proceedings of the 7th Workshop on Challenges and …, 2024"],"snippet":"This work presents a systematic search of various model architecture configurations and data cleaning methods. The study evaluates the impact of data cleaning methods on the obtained results. Additionally, we demonstrate that a combination of …","url":["https://aclanthology.org/2024.case-1.24.pdf"]}
-{"year":"2024","title":"Jack of All Trades, Master of Some, a Multi-Purpose Transformer Agent","authors":["Q Gallouédec, E Beeching, C Romac, E Dellandréa - arXiv preprint arXiv:2402.09844, 2024"],"snippet":"The search for a general model that can operate seamlessly across multiple domains remains a key goal in machine learning research. The prevailing methodology in Reinforcement Learning (RL) typically limits models to a single task …","url":["https://arxiv.org/pdf/2402.09844"]}
-{"year":"2024","title":"Japanese Pointer Network based Entity Linker for Wikidata","authors":["Y Sawamura, T Morita, S Egami, T Ugai, K Fukuda - 2023"],"snippet":"… Pre-trained fastText is a model trained on Common Crawl and Wikipedia and provides pre-computed vectors for a word. The length of the POS Tags was changed from 36 to 18. The other five embeddings, namely Entity Embedding, Text Match …","url":["https://ijckg2023.knowledge-graph.jp/pages/proc/paper_18.pdf"]}
-{"year":"2024","title":"JetMoE: Reaching Llama2 Performance with 0.1 M Dollars","authors":["Y Shen, Z Guo, T Cai, Z Qin - arXiv preprint arXiv:2404.07413, 2024"],"snippet":"Large Language Models (LLMs) have achieved remarkable results, but their increasing resource demand has become a major obstacle to the development of powerful and accessible super-human intelligence. This report introduces JetMoE-8B …","url":["https://arxiv.org/pdf/2404.07413"]}
-{"year":"2024","title":"Jina CLIP: Your CLIP Model Is Also Your Text Retriever","authors":["A Koukounas, G Mastrapas, M Günther, B Wang… - arXiv preprint arXiv …, 2024"],"snippet":"Contrastive Language-Image Pretraining (CLIP) is widely used to train models to align images and texts in a common embedding space by mapping them to fixed-sized vectors. These models are key to multimodal information retrieval and related tasks …","url":["https://arxiv.org/pdf/2405.20204"]}
-{"year":"2024","title":"JiuZhang3. 0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models","authors":["K Zhou, B Zhang, J Wang, Z Chen, WX Zhao, J Sha… - arXiv preprint arXiv …, 2024"],"snippet":"Mathematical reasoning is an important capability of large language models~(LLMs) for real-world applications. To enhance this capability, existing work either collects large-scale math-related texts for pre-training, or relies on stronger LLMs (\\eg GPT-4) …","url":["https://arxiv.org/pdf/2405.14365"]}
-{"year":"2024","title":"JLBert: Japanese Light BERT for Cross-Domain Short Text Classification","authors":["C Kayal, S Chattopadhyay, A Gupta, S Abrol, A Gugol - Proceedings of the 2024 Joint …, 2024"],"snippet":"… Second, there are limited models that have been trained on diverse datasets beyond Wikipedia and Common Crawl, limiting experimentation with other forms of text data. Moreover, with the English language being the focus of research interest …","url":["https://aclanthology.org/2024.lrec-main.833.pdf"]}
-{"year":"2024","title":"Juru: Legal Brazilian Large Language Model from Reputable Sources","authors":["RM Junior, R Pires, R Romero, R Nogueira - arXiv preprint arXiv:2403.18140, 2024"],"snippet":"The high computational cost associated with pretraining large language models limits their research. Two strategies have emerged to address this issue: domain specialization and pretraining with high-quality data. To explore these strategies, we …","url":["https://arxiv.org/pdf/2403.18140"]}
-{"year":"2024","title":"Just Rewrite It Again: A Post-Processing Method for Enhanced Semantic Similarity and Privacy Preservation of Differentially Private Rewritten Text","authors":["S Meisenbacher, F Matthes - arXiv preprint arXiv:2405.19831, 2024"],"snippet":"The study of Differential Privacy (DP) in Natural Language Processing often views the task of text privatization as a $\\textit{rewriting}$ task, in which sensitive input texts are rewritten to hide explicit or implicit private information. In order to evaluate the …","url":["https://arxiv.org/pdf/2405.19831"]}
-{"year":"2024","title":"KazQAD: Kazakh Open-Domain Question Answering Dataset","authors":["R Yeshpanov, P Efimov, L Boytsov, A Shalkarbayuli… - arXiv preprint arXiv …, 2024"],"snippet":"… Kaz-RoBERTa6 is a monolingual model trained on a collection of Kazakh texts from Common Crawl, the Leipzig Corpora Collection, the … XLM-R was pre-trained on a larger multilingual corpus derived from Common Crawl, in which Kazakh is …","url":["https://arxiv.org/pdf/2404.04487"]}
-{"year":"2024","title":"KazSAnDRA: Kazakh Sentiment Analysis Dataset of Reviews and Attitudes","authors":["R Yeshpanov, HA Varol - arXiv preprint arXiv:2403.19335, 2024"],"snippet":"This paper presents KazSAnDRA, a dataset developed for Kazakh sentiment analysis that is the first and largest publicly available dataset of its kind. KazSAnDRA comprises an extensive collection of 180,064 reviews obtained from various sources …","url":["https://arxiv.org/pdf/2403.19335"]}
-{"year":"2024","title":"KEPA-CRF: Knowledge expansion prototypical amortized conditional random field for few-shot event detection","authors":["R Wu, L Yu, S Tian, J Long, T Zhou, B Wang - Journal of Intelligent & Fuzzy Systems"],"snippet":"Event Detection (ED) has long struggled with the ambiguous definition of event categories, making it challenging to accurately classify events. Previous endeavors aimed to tackle this problem by constructing prototypes for specific event categories …","url":["https://content.iospress.com/articles/journal-of-intelligent-and-fuzzy-systems/ifs234368"]}
-{"year":"2024","title":"Key ingredients for effective zero-shot cross-lingual knowledge transfer in generative tasks","authors":["N Chirkova, V Nikoulina - arXiv preprint arXiv:2402.12279, 2024"],"snippet":"… For Intermediate tuning we finetune models for 100k steps on the CommonCrawl data uniformly sampled across all target languages and English, with the batch size of 5k tokens and the LR chosen to optimize fluency of model generations, inspected …","url":["https://arxiv.org/pdf/2402.12279"]}
-{"year":"2024","title":"Knowledge Induced Transformer Network for Causality Prediction","authors":["T Dasgupta, M Sinha, A Naskar - Companion Proceedings of the ACM on Web …, 2024"],"snippet":"… The CausalBank dataset3 contains 314 million pairs of cause-effect statements scraped from the Common Crawl corpus using causal lexical patterns. Baselines: Most of the earlier work on causality detection is based on identifying cause, effect …","url":["https://dl.acm.org/doi/abs/10.1145/3589335.3651531"]}
-{"year":"2024","title":"Knowledge Sources","authors":["M Jiang, BY Lin, S Wang, Y Xu, W Yu, C Zhu - Knowledge-augmented Methods for …, 2024"],"snippet":"… To be more specific, the dataset includes Pile-CommonCrawl (227.12G, web crawling data), PubMed Central (90.27G, biomedical articles), Books (100.96G, a mix of fiction and nonfiction books), OpenWebText (262.77G, content from Reddit) …","url":["https://link.springer.com/chapter/10.1007/978-981-97-0747-8_2"]}
-{"year":"2024","title":"Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models","authors":["R Vemulapalli, H Pouransari, F Faghri, S Mehta… - Forty-first International Conference …"],"snippet":"… 2023) which contains 1.28B images filtered from Common Crawl (web-crawled data). We take 10 randomly augmented crops from each image and create a gallery of 12.8B images. See Appendix B.2 for additional details about this gallery set and …","url":["https://openreview.net/pdf?id=OKYfaYQlML"]}
-{"year":"2024","title":"Knowledge-augmented Methods for Natural Language Processing","authors":["M Jiang"],"snippet":"Ever since language was invented and used, humans have leveraged this powerful tool to pass down experience over generations. These kinds of knowledge summarize precious findings and inspiring ideas, which constitute the human …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=tlsAEQAAQBAJ&oi=fnd&pg=PR5&dq=commoncrawl&ots=XzQIdUcgNg&sig=EzGLwwhZB2mo602CaK_dytKIWaY"]}
-{"year":"2024","title":"Knowledge-Enhanced Neural Networks for Machine Reading Comprehension","authors":["TB Mihaylov - 2024"],"snippet":"Machine Reading Comprehension is a language understanding task where a system is expected to read a given passage of text and typically answer questions about it. When humans assess the task of reading comprehension, in addition to the …","url":["https://archiv.ub.uni-heidelberg.de/volltextserver/34352/1/Thesis_Todor_Mihaylov_Camera_Ready.pdf"]}
-{"year":"2024","title":"KOMPYUTER LINGVISTIKASIDA TA'MINOT MASALASI VA SINONIM BIRLIKLARNING LINGVISTIK TA'MINOTI","authors":["N SOTVOLDIYEVA - News of UzMU journal, 2024"],"snippet":"… Lingvistik ma'lumotlar konsorsiumi (LDC) va Common Crawl[8] loyihasi kabi ochiq hamkorlik tashabbuslari lingvistik resurslarning mavjudligiga sezilarli hissa qo'shdi. Bu hamkorlik resurslar almashinuvini targ‘ib qiladi, ortiqchalikni kamaytiradi va …","url":["https://journalsnuu.uz/index.php/1/article/download/803/266"]}
-{"year":"2024","title":"Krishiq-BERT: A Few-Shot Setting BERT Model to Answer Agricultural-Related Questions in the Kannada Language","authors":["P Ajawan, V Desai, S Kale, S Patil - Journal of The Institution of Engineers (India) …, 2024"],"snippet":"… corpora for 11 languages from two language families obtained primarily by sourcing articles from news crawls [3], and OSCAR (Open Super-large Crawled ALMAnaCH coRpus), a huge multilingual corpus procured by language …","url":["https://link.springer.com/article/10.1007/s40031-023-00952-6"]}
-{"year":"2024","title":"KVP10k: A Comprehensive Dataset for Key-Value Pair Extraction in Business Documents","authors":["O Naparstek, R Pony, I Shapira, FA Dahood, O Azulai… - arXiv preprint arXiv …, 2024"],"snippet":"… : extensive web data from Common Crawl and a collection of images from publicfiles.fcc.gov. From Common Crawl, we employed a systematic … A schematic describing the data acquisition process for the common crawl data is shown in Fig.2 …","url":["https://arxiv.org/pdf/2405.00505"]}
-{"year":"2024","title":"Labadain-30k+: A Monolingual Tetun Document-Level Audited Dataset","authors":["G de Jesus, S Nunes - Proceedings of the 3rd Annual Meeting of the Special …, 2024"],"snippet":"This paper introduces Labadain-30k+, a monolingual dataset comprising 33.6 k documents in Tetun, a low-resource language spoken in Timor-Leste. The dataset was acquired through web crawling and augmented with Wikipedia documents …","url":["https://aclanthology.org/2024.sigul-1.22.pdf"]}
-{"year":"2024","title":"Language Model Frame Filling for Low Resource Languages","authors":["L Zong"],"snippet":"Acceptability judgment tasks are key tools used in the understanding of the grammar of languages by linguists. A typical way to construct these tasks is to use semantic frames. We provide evidence that the fill-mask objective for language models (LMs) …","url":["https://leonzong.com/papers/csc247_final.pdf"]}
-{"year":"2024","title":"Language Models Fine-Tuning for Automatic Format Reconstruction of SEC Financial Filings","authors":["G Lombardo, G Trimigno, M Pellegrino, S Cagnoni - IEEE Access, 2024"],"snippet":"The analysis of financial reports is a crucial task for investors and regulators, especially the mandatory annual reports (10-K) required by the SEC (Securities and Exchange Commission) that provide crucial information about a public company in …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10445214.pdf"]}
-{"year":"2024","title":"Language Models on a Diet: Cost-Efficient Development of Encoders for Closely-Related Languages via Additional Pretraining","authors":["N Ljubešić, V Suchomel, P Rupnik, T Kuzman… - arXiv preprint arXiv …, 2024"],"snippet":"The world of language models is going through turbulent times, better and ever larger models are coming out at an unprecedented speed. However, we argue that, especially for the scientific community, encoder models of up to 1 billion parameters …","url":["https://arxiv.org/pdf/2404.05428"]}
-{"year":"2024","title":"Language models scale reliably with over-training and on downstream tasks","authors":["SY Gadre, G Smyrnis, V Shankar, S Gururangan… - arXiv preprint arXiv …, 2024"],"snippet":"Scaling laws are useful guides for developing language models, but there are still gaps between current scaling studies and how language models are ultimately trained and evaluated. For instance, scaling is usually studied in the compute-optimal …","url":["https://arxiv.org/pdf/2403.08540"]}
-{"year":"2024","title":"Large Language Models (LLMs) on Tabular Data: Predic-tion, Generation, and Understanding-A Survey","authors":["X Fang, W Xu, FA Tan, J Zhang, Z Hu, Y Qi… - arXiv preprint arXiv …, 2024"],"snippet":"Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, tabular data synthesis, question answering, and table …","url":["https://stewarthu.com/papers/LLM-on-tabular-data.pdf"]}
-{"year":"2024","title":"Large Language Models and the Disappearing Private Sphere","authors":["A Cappello, M Dada, V Grigoreva, R Khan, C Stinson… - 2024"],"snippet":"… The higher quality datasets are sampled more often during training, but the Reddit approved contents of CommonCrawl still … of CommonCrawl contains fan fiction, video game chats, conspiracy theories, pornography, junk advertising, and …","url":["https://etlab.cs.queensu.ca/files/2024/04/OPC_Final_Report_2023.pdf"]}
-{"year":"2024","title":"Large Language Models aren't all that you need","authors":["KV Holla, C Kumar, A Singh - arXiv preprint arXiv:2401.00698, 2024"],"snippet":"This paper describes the architecture and systems built towards solving the SemEval 2023 Task 2: MultiCoNER II (Multilingual Complex Named Entity Recognition) [1]. We evaluate two approaches (a) a traditional Conditional Random …","url":["https://arxiv.org/pdf/2401.00698"]}
-{"year":"2024","title":"LARGE LANGUAGE MODELS AS AN AID FOR SOFTWARE DEVELOPMENT USING GRAPHICAL PROGRAMMING LANGUAGE.","authors":["V Tiljander - 2023"],"snippet":"… In pre-training, the model is trained with the Common Crawl dataset, internet books, and Python code, summing up to 400B tokens. After the model is pre-trained, the phase preference model pre-training comes, and after that, the preference model …","url":["https://trepo.tuni.fi/bitstream/handle/10024/153734/TiljanderVille.pdf?sequence=2"]}
-{"year":"2024","title":"Large language models as oracles for instantiating ontologies with domain-specific knowledge","authors":["G Ciatto, A Agiollo, M Magnini, A Omicini - arXiv preprint arXiv:2404.04108, 2024"],"snippet":"… Models following the RoBERTa [30] approach were trained on (i) the same datasets as BERT, plus (ii) a sample of the CommonCrawl4 News dataset (a dump of news … 4https://commoncrawl.org 5https://mistral.ai/news/mixtral-of-experts …","url":["https://arxiv.org/html/2404.04108v1"]}
-{"year":"2024","title":"Large language models for biomedicine: foundations, opportunities, challenges, and best practices","authors":["SS Sahoo, JM Plasek, H Xu, Ö Uzuner, T Cohen… - Journal of the American …, 2024"],"snippet":"… In the pre-training phase, generic training data, such as the Common Crawl dataset or social media posts, are used for unsupervised learning.With further training on prompt-response pairs (such as the Alpaca dataset developed at Stanford23) …","url":["https://academic.oup.com/jamia/advance-article/doi/10.1093/jamia/ocae074/7657768"]}
-{"year":"2024","title":"Large Language Models for Forecasting and Anomaly Detection: A Systematic Literature Review","authors":["J Su, C Jiang, X Jin, Y Qiao, T Xiao, H Ma, R Wei… - arXiv preprint arXiv …, 2024"],"snippet":"… The training data for GPT-3 includes the Common Crawl dataset for lower quality, as well as the WebText2 dataset for higher quality, as well as the Books1, Books2, and Wikipedia datasets for higher quality [148]. GPT-3 assigns different weights to …","url":["https://arxiv.org/pdf/2402.10350"]}
-{"year":"2024","title":"Large Language Models for Human-Machine Collaborative Particle Accelerator Tuning through Natural Language","authors":["J Kaiser, A Eichler, A Lauscher - arXiv preprint arXiv:2405.08888, 2024"],"snippet":"Autonomous tuning of particle accelerators is an active and challenging field of research with the goal of enabling novel accelerator technologies cutting-edge high-impact applications, such as physics discovery, cancer research and material sciences. A …","url":["https://arxiv.org/pdf/2405.08888"]}
-{"year":"2024","title":"Large Language Models for identification of medical data in unstructured records","authors":["P Petkov, E Markov, L Tomov"],"snippet":"… Sources for the training data include web pages extracted by CommonCrawl, opensource GitHub repositories, Wikipedia in twenty languages, Project Gutenberg books in the public domain, LaTeX source code of scientific articles in ArXiv and …","url":["https://www.researchgate.net/profile/Latchezar-Tomov/publication/379754048_Large_Language_Models_for_identification_of_medical_data_in_unstructured_records/links/661927fff7d3fc28744fc7cf/Large-Language-Models-for-identification-of-medical-data-in-unstructured-records.pdf"]}
-{"year":"2024","title":"Large Language Models for Reliable Information Extraction","authors":["L Baliunas"],"snippet":"This project addresses the ongoing challenge of achieving reliable Information Extraction (IE), particularly in domains which require near-perfect precision. ELICIT (Butcher et al., 2023) introduced a novel approach that combines the processing speed of …","url":["https://www.mlmi.eng.cam.ac.uk/files/2022_-_2023_dissertations/large_language_models_for_reliable_information_extraction.pdf"]}
-{"year":"2024","title":"Large Language Models on Tabular Data--A Survey","authors":["X Fang, W Xu, FA Tan, J Zhang, Z Hu, Y Qi… - arXiv preprint arXiv …, 2024"],"snippet":"Recent breakthroughs in large language modeling have facilitated rigorous exploration of their application in diverse tasks related to tabular data modeling, such as prediction, tabular data synthesis, question answering, and table …","url":["https://arxiv.org/pdf/2402.17944"]}
-{"year":"2024","title":"Large Language Models: A Survey","authors":["S Minaee, T Mikolov, N Nikzad, M Chenaghlu… - arXiv preprint arXiv …, 2024"],"snippet":"… Common Crawlbased dataset consisting of texts in 101 languages. … CommonCrawl. They also released an extract of 600 billion tokens from our REFINEDWEB dataset, and 1.3/7.5B parameters language models trained on it. 27 …","url":["https://arxiv.org/pdf/2402.06196"]}
-{"year":"2024","title":"Large Malaysian Language Model Based on Mistral for Enhanced Local Language Understanding","authors":["H Zolkepli, A Razak, K Adha, A Nazhan - arXiv preprint arXiv:2401.13565, 2024"],"snippet":"… An analysis of the widely utilized Common Crawl dataset reveals a mere 0.0742% contribution from the Malay language based on CCMAIN-… We also replicated the same technique for Malaysia Hansard and MS CommonCrawl samples. All synthetic …","url":["https://arxiv.org/pdf/2401.13565"]}
-{"year":"2024","title":"Large-language models facilitate discovery of the molecular signatures regulating sleep and activity","authors":["D Peng, L Zheng, D Liu, C Han, X Wang, Y Yang… - Nature Communications, 2024"],"snippet":"Sleep, locomotor and social activities are essential animal behaviors, but their reciprocal relationships and underlying mechanisms remain poorly understood. Here, we elicit information from a cutting-edge large-language model (LLM), generative pre-trained …","url":["https://www.nature.com/articles/s41467-024-48005-w"]}
-{"year":"2024","title":"Large-Language-Models (LLM)-Based AI Chatbots: Architecture, In-Depth Analysis and Their Performance Evaluation","authors":["V Kumar, P Srivastava, A Dwivedi, I Budhiraja… - International Conference on …, 2023"],"snippet":"… LLaMA models span from 7 billion to 65 billion parameters and were trained on trillions of tokens derived from publicly accessible datasets, including Common Crawl and Wikipedia. The primary objective of LLaMA models is to serve as …","url":["https://link.springer.com/chapter/10.1007/978-3-031-53085-2_20"]}
-{"year":"2024","title":"Latxa: An Open Language Model and Evaluation Suite for Basque","authors":["J Etxaniz, O Sainz, N Perez, I Aldabe, G Rigau, E Agirre… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce Latxa, a family of large language models for Basque ranging from 7 to 70 billion parameters. Latxa is based on Llama 2, which we continue pretraining on a new Basque corpus comprising 4.3M documents and 4.2B tokens. Addressing the …","url":["https://arxiv.org/pdf/2403.20266"]}
-{"year":"2024","title":"Law and the Political Economy of AI Production","authors":["P Terzis"],"snippet":"The governance of Artificial Intelligence (AI) is at a historical juncture. Legislative acts, global treaties, export controls, and technical standards are now dominating the discourse over what used to be a predominantly market-driven space. Amidst all this …","url":["https://osf.io/q593j/download"]}
-{"year":"2024","title":"Law, Technology and Humans","authors":["J De Cooman"],"snippet":"… Around 60% of GPT-3 training data comes from a filtered version of Common Crawl—that is, a non-profit organisation that archives and provides open-access petabytes of data collected since 2011. [30] The remaining 40% comes from diverse …","url":["https://www.austlii.edu.au/au/journals/LawTechHum/2023/3.html"]}
-{"year":"2024","title":"Learning with Noisy Foundation Models","authors":["H Chen, J Wang, Z Wang, R Tao, H Wei, X Xie… - arXiv preprint arXiv …, 2024"],"snippet":"… GPT2 is pre-trained on WebText [29], a scraped web dataset from Common Crawl that contains low-quality raw texts. We also leverage OpenAI’s API service “text-ada-002”. We cannot use larger and more recent language models such as LLaMA [30], since …","url":["https://arxiv.org/pdf/2403.06869"]}
-{"year":"2024","title":"Leveraging AI to Deliver Culturally Responsive Mental Health Care at Scale","authors":["A Cerezo, D Cooper, V Palat, A Jolley, S Peregrine"],"snippet":"… One of the most commonly used datasets to train LLMs is The Common Crawl dataset, a large collection of web pages scraped from the internet since 2014. These pages contain the gamut from high-quality news, science, and literature to the …","url":["https://s3.ca-central-1.amazonaws.com/assets.jmir.org/assets/preprints/preprint-56965-submitted.pdf"]}
-{"year":"2024","title":"Leveraging distant supervision and deep learning for twitter sentiment and emotion classification","authors":["M Kastrati, Z Kastrati, A Shariq Imran, M Biba - Journal of Intelligent Information …, 2024"],"snippet":"Nowadays, various applications across industries, healthcare, and security have begun adopting automatic sentiment analysis and emotion detection in short texts, such as posts from social media. Twitter stands out as one of the most popular …","url":["https://link.springer.com/article/10.1007/s10844-024-00845-0"]}
-{"year":"2024","title":"Leveraging Open Large Language Models for Multilingual Policy Topic Classification: The Babel Machine Approach","authors":["M Sebők, Á Máté, O Ring, V Kovács, R Lehoczki - Social Science Computer Review, 2024"],"snippet":"The article presents an open-source and freely available natural language processing system for comparative policy studies. The CAP Babel Machine allows for the automated classification of input files based on the 21 major policy topics of …","url":["https://journals.sagepub.com/doi/pdf/10.1177/08944393241259434"]}
-{"year":"2024","title":"Leveraging Parameter Efficient Training Methods for Low Resource Text Classification: A case study in Marathi","authors":["P Deshmukh, N Kulkarni, S Kulkarni, K Manghani… - 2024 IEEE 9th International …, 2024"],"snippet":"With the surge in digital content in low-resource languages, there is an escalating demand for advanced Natural Language Processing (NLP) techniques tailored to these languages. BERT (Bidirectional Encoder Representations from Transformers) …","url":["https://ieeexplore.ieee.org/abstract/document/10543946/"]}
-{"year":"2024","title":"Leveraging Zero-Shot Prompting for Efficient Language Model Distillation","authors":["L Vöge, V Gurgul, S Lessmann - arXiv preprint arXiv:2403.15886, 2024"],"snippet":"… Specifically, we use the T5 v1.1 models which were only pretrained on the C4 Common Crawl dataset for general language understanding without additional task-specific finetuning. The use of text-to-text models allows for straightforward processing, as …","url":["https://arxiv.org/pdf/2403.15886"]}
-{"year":"2024","title":"Lib2Life–Digital Library Services Empowered with Advanced Natural Language Processing Techniques","authors":["M Nitu, M Dascalu, MD Dascalu, LM Neagu…"],"snippet":"Educational institutions are struggling to keep up with the accelerated technological advancements; hence, sustainable and supportive tools have become essential to reshape traditional models into intelligent learning systems. This paper introduces …","url":["https://www.researchgate.net/profile/Nitu-Melania-2/publication/380769622_Lib2Life_-_Digital_Library_Services_Empowered_with_Advanced_Natural_Language_Processing_Techniques/links/664efa3022a7f16b4f43a5e1/Lib2Life-Digital-Library-Services-Empowered-with-Advanced-Natural-Language-Processing-Techniques.pdf"]}
-{"year":"2024","title":"LiBERTa: Advancing Ukrainian Language Modeling through Pre-training from Scratch","authors":["M Haltiuk, A Smywiński-Pohl - Proceedings of the Third Ukrainian Natural Language …, 2024"],"snippet":"… CC-100, a multilingual text corpus sourced from Wikipedia and CommonCrawl, was processed following the CCNet1 methodology. The Ukrainian segment of CC-100 encompasses 6.5 billion tokens, equivalent to 84 GiB of data2. This corpus primarily …","url":["https://aclanthology.org/2024.unlp-1.14.pdf"]}
-{"year":"2024","title":"Limitations of Language Models in The Oil & Gas Upstream Operations","authors":["A Alsultan, FA Razak - International Petroleum Technology Conference, 2024"],"snippet":"… Although the process is simple in principle, it is done on very large training corpra which can be as big as dataset provided by the Common Crawl project (428.81 TB as of the date of writing this paper). Thus, training these models using these large …","url":["https://onepetro.org/IPTCONF/proceedings-abstract/24IPTC/All-24IPTC/542606"]}
-{"year":"2024","title":"LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low-Resource and Extinct Languages","authors":["AM Bean, S Hellsten, H Mayne, J Magomere, EA Chi… - arXiv preprint arXiv …, 2024"],"snippet":"… ], while the second and fourth rows are sorted by Common Crawl Share [16]. The upper two … of pages tagged with a given language in the Common Crawl dataset [16]. Figure 12 show the … LLMs are trained on, using the Common Crawl share and …","url":["https://arxiv.org/pdf/2406.06196"]}
-{"year":"2024","title":"Linguistic Profiling of Deepfakes: An Open Database for Next-Generation Deepfake Detection","authors":["Y Wang, Z Huang, Z Ma, X Hong - arXiv preprint arXiv:2401.02335, 2024"],"snippet":"The emergence of text-to-image generative models has revolutionized the field of deepfakes, enabling the creation of realistic and convincing visual content directly from textual descriptions. However, this advancement presents considerably greater …","url":["https://arxiv.org/pdf/2401.02335"]}
-{"year":"2024","title":"Linguistic Structure from a Bottleneck on Sequential Information Processing","authors":["R Futrell, M Hahn - arXiv preprint arXiv:2405.12109, 2024"],"snippet":"… Table 3: English expressions for the given meanings, along with frequencies from the English Common Crawl web corpus [64]. Example … n-gram counts and language models from the common crawl. In Language Resources and Evaluation …","url":["https://arxiv.org/pdf/2405.12109"]}
-{"year":"2024","title":"Llama (LLM)","authors":["C Room - algorithms, 2024"],"snippet":"… Data was mostly from CommonCrawl and C4. Llama-2-70B saw 2T tokens but Llama-3-70B saw 15T tokens. Llama-3-8B and Llama-3-70B took 1.3M and 6.4M GPU hours for pretraining. …","url":["https://devopedia.org/llama-llm"]}
-{"year":"2024","title":"LLaMA Beyond English: An Empirical Study on Language Capability Transfer","authors":["J Zhao, Z Zhang, Q Zhang, T Gui, X Huang - arXiv preprint arXiv:2401.01055, 2024"],"snippet":"In recent times, substantial advancements have been witnessed in large language models (LLMs), exemplified by ChatGPT, showcasing remarkable proficiency across a range of complex tasks. However, many mainstream LLMs (eg LLaMA) are …","url":["https://arxiv.org/pdf/2401.01055"]}
-{"year":"2024","title":"LLM-Datasets: An Open Framework for Pretraining Datasets of Large Language Models","authors":["M Ostendorff, PO Suarez, LF Lage, G Rehm"],"snippet":"… All of the numbers are given by Common Crawl dump. … 2 show the number of documents by both date of the CommonCrawl dump and language, the percentage of documents removed at each filtering step, and the final document and token …","url":["https://ostendorff.org/assets/pdf/ostendorff2024-preprint.pdf"]}
-{"year":"2024","title":"LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement","authors":["N Lee, T Wattanawong, S Kim, K Mangalam, S Shen… - arXiv preprint arXiv …, 2024"],"snippet":"… We assume that we are given an LLM model M (eg, GPT-3.5 or LLaMA2-7B) that is pre-trained on some source dataset (eg, Common Crawl). The goal is to adapt M (hereon called the student model) to a new target domain by using a small seed dataset D …","url":["https://arxiv.org/pdf/2403.15042"]}
-{"year":"2024","title":"LLMs achieve adult human performance on higher-order theory of mind tasks","authors":["W Street, JO Siy, G Keeling, A Baranes, B Barnett… - arXiv preprint arXiv …, 2024"],"snippet":"This paper examines the extent to which large language models (LLMs) have developed higher-order theory of mind (ToM); the human ability to reason about multiple mental and emotional states in a recursive manner (eg I think that you …","url":["https://arxiv.org/pdf/2405.18870"]}
-{"year":"2024","title":"LLMs for Low Resource Languages in Multilingual, Multimodal and Dialectal Settings","authors":["F Alam, SA Chowdhury, S Boughorbel, M Hasanain - … of the 18th Conference of the …, 2024"],"snippet":"The recent breakthroughs in Artificial Intelligence (AI) can be attributed to the remarkable performance of Large Language Models (LLMs) across a spectrum of research areas (eg, machine translation, question-answering, automatic speech …","url":["https://aclanthology.org/2024.eacl-tutorials.5.pdf"]}
-{"year":"2024","title":"LLMs Still Can't Avoid Instanceof: An Investigation Into GPT-3.5, GPT-4 and Bard's Capacity to Handle Object-Oriented Programming Assignments","authors":["BP Cipriano, P Alves - arXiv preprint arXiv:2403.06254, 2024"],"snippet":"… are high-level descriptions of the training datasets (eg a filtered version of Common Crawl 14, English Wikipedia, among others) [3], it was not possible to perform this analysis for those models. 13https:github.com/camilaabrantes/CursoJava …","url":["https://arxiv.org/pdf/2403.06254"]}
-{"year":"2024","title":"LMaaS: Exploring Pricing Strategy of Large Model as a Service for Communication","authors":["P Wu, Q Liu, Y Dong, F Wang - arXiv preprint arXiv:2401.02675, 2024"],"snippet":"The next generation of communication is envisioned to be intelligent communication, that can replace traditional symbolic communication, where highly condensed semantic information considering both source and channel will be extracted and …","url":["https://arxiv.org/pdf/2401.02675"]}
-{"year":"2024","title":"Long-input summarization using Large Language Models","authors":["E Järvinen - 2024"],"snippet":"… the colossal and cleaned version of common crawl CNN … T5 was pre-trained on the C4 (The Colossal and Cleaned version of Common Crawl) dataset. C4 contains text from 350M web pages; the dataset is 750 GB. A maximum sequence length of …","url":["https://aaltodoc.aalto.fi/bitstreams/cd47964e-5b5e-4af0-9af4-731970184358/download"]}
-{"year":"2024","title":"Long-Term Ad Memorability: Understanding & Generating Memorable Ads","authors":["SI Harini, S Singh, Y Kumar, A Bhattacharyya, V Baths…"],"snippet":"Marketers spend billions of dollars on advertisements, but to what end? At purchase time, if customers cannot recognize the brand for which they saw an ad, the money spent on the ad is essentially wasted. Despite its importance in marketing, until now …","url":["https://www.researchgate.net/profile/Yaman-Singla/publication/373642219_Long-Term_Ad_Memorability_Understanding_Generating_Memorable_Ads/links/6645020b0b0d2845743647cc/Long-Term-Ad-Memorability-Understanding-Generating-Memorable-Ads.pdf"]}
-{"year":"2024","title":"LongWanjuan: Towards Systematic Measurement for Long Text Quality","authors":["K Lv, X Liu, Q Guo, H Yan, C He, X Qiu, D Lin - arXiv preprint arXiv:2402.13583, 2024"],"snippet":"… In the English data, the CommonCrawl domain predominates, accounting for over 50% of the data. Apart from a significant amount of aggregated texts in the CommonCrawl domain, the majority of data in other domains consists of holistic texts …","url":["https://arxiv.org/pdf/2402.13583"]}
-{"year":"2024","title":"Look Ahead or Look Around? A Theoretical Comparison Between Autoregressive and Masked Pretraining","authors":["Q Zhang, T Du, H Huang, Y Wang, Y Wang - Forty-first International Conference on Machine …"],"snippet":"In recent years, the rise of generative self-supervised learning (SSL) paradigms has exhibited impressive performance across visual, language, and multi-modal domains. While the varied designs of generative SSL objectives lead to distinct properties in …","url":["https://openreview.net/pdf?id=2rPoTgEmjV"]}
-{"year":"2024","title":"Lory: Fully Differentiable Mixture-of-Experts for Autoregressive Language Model Pre-training","authors":["Z Zhong, M Xia, D Chen, M Lewis - arXiv preprint arXiv:2405.03133, 2024"],"snippet":"… We suspect that segment-level routing may be particularly effective at handling out-of-domain evaluation data (we assume that there is only a very small part of Python code in Commoncrawl). Our analysis in Section 5.4 shows that segment-level routing …","url":["https://arxiv.org/pdf/2405.03133"]}
-{"year":"2024","title":"M2SA: Multimodal and Multilingual Model for Sentiment Analysis of Tweets","authors":["G Thakkar, S Hakimov, M Tadić - arXiv preprint arXiv:2404.01753, 2024"],"snippet":"… 2020b) is a large multilingual language model trained on 2.5 TB of filtered Common Crawl data containing 100 languages. The model was trained with the Masked Language Modelling (MLM) objective, with 15% of the input words masked …","url":["https://arxiv.org/pdf/2404.01753"]}
-{"year":"2024","title":"Machine Learning and the Analysis of Culture","authors":["S Mützel, É Ollion - 2024"],"snippet":"The focus of this chapter is on how machine learning (ML) impacts the analysis of culture in sociology. It shows how ML has greatly advanced the analysis of culture, with new tools enabling a massive and fine-grained extraction of information from …","url":["https://osf.io/nvtp2/download"]}
-{"year":"2024","title":"Machine Translation that Peeks at the Reference","authors":["V Zouhar"],"snippet":"Abstract Machine translation with lexical constraints is a popular research topic, especially for terminology translation. Existing approaches for lexical control in MT are usually complex and not easily applicable to all existing MT toolkits. We propose …","url":["https://vilda.net/papers/mt_peek.pdf"]}
-{"year":"2024","title":"Machines Do See Color: A Guideline to Classify Different Forms of Racist Discourse in Large Corpora","authors":["DD Gordillo, J Timoneda, SV Vera - arXiv preprint arXiv:2401.09333, 2024"],"snippet":"Current methods to identify and classify racist language in text rely on small-n qualitative approaches or large-n approaches focusing exclusively on overt forms of racist discourse. This article provides a step-by-step generalizable guideline to …","url":["https://arxiv.org/pdf/2401.09333"]}
-{"year":"2024","title":"MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions","authors":["K Zhang, Y Luan, H Hu, K Lee, S Qiao, W Chen, Y Su… - arXiv preprint arXiv …, 2024"],"snippet":"… We collect all images with the same URL from Common Crawl2 as a group of images from the same web page for potential pairing. Due to the inevitable noisy images introduced by simple grouping, we remove duplicated, low-resolution, and …","url":["https://arxiv.org/pdf/2403.19651"]}
-{"year":"2024","title":"MAiDE-up: Multilingual Deception Detection of GPT-generated Hotel Reviews","authors":["O Ignat, X Xu, R Mihalcea - arXiv preprint arXiv:2404.12938, 2024"],"snippet":"Deceptive reviews are becoming increasingly common, especially given the increase in performance and the prevalence of LLMs. While work to date has addressed the development of models to differentiate between truthful and …","url":["https://arxiv.org/pdf/2404.12938"]}
-{"year":"2024","title":"MaiNLP at SemEval-2024 Task 1: Analyzing Source Language Selection in Cross-Lingual Textual Relatedness","authors":["S Zhou, H Shan, B Plank, R Litschko - arXiv preprint arXiv:2404.02570, 2024"],"snippet":"This paper presents our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness (STR), on Track C: Cross-lingual. The task aims to detect semantic relatedness of two sentences in a given target language without access to …","url":["https://arxiv.org/pdf/2404.02570"]}
-{"year":"2024","title":"MambaByte: Token-free Selective State Space Model","authors":["J Wang, T Gangavarapu, JN Yan, AM Rush - arXiv preprint arXiv:2401.13660, 2024"],"snippet":"Token-free language models learn directly from raw bytes and remove the bias of subword tokenization. Operating on bytes, however, results in significantly longer sequences, and standard autoregressive Transformers scale poorly in such settings …","url":["https://arxiv.org/pdf/2401.13660"]}
-{"year":"2024","title":"MAmmoTH2: Scaling Instructions from the Web","authors":["X Yue, T Zheng, G Zhang, W Chen - arXiv preprint arXiv:2405.03548, 2024"],"snippet":"… We argue that the pre-training corpus (eg, Common Crawl) already contains a vast amount of high-quality instruction data for LLM reasoning. For example, the web corpus contains a large amount of educational materials in the form of instruction-following …","url":["https://arxiv.org/pdf/2405.03548"]}
-{"year":"2024","title":"MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model Series","authors":["G Zhang, S Qu, J Liu, C Zhang, C Lin, CL Yu, D Pan… - arXiv preprint arXiv …, 2024"],"snippet":"… Inspired by [89], which adopts an iterative pipeline to facilitate the acquisition of large-scale, high-quality data from Common Crawl, we propose to select high-quality data for mathematics, scientific exam synthetic data, and wiki-based content in our Matrix. …","url":["https://arxiv.org/pdf/2405.19327"]}
-{"year":"2024","title":"Massively Multi-Cultural Knowledge Acquisition & LM Benchmarking","authors":["Y Fung, R Zhao, J Doo, C Sun, H Ji - arXiv preprint arXiv:2402.09369, 2024"],"snippet":"Pretrained large language models have revolutionized many applications but still face challenges related to cultural bias and a lack of cultural commonsense knowledge crucial for guiding cross-culture communication and interactions …","url":["https://arxiv.org/pdf/2402.09369"]}
-{"year":"2024","title":"MASTERARBEIT/MASTER'S THESIS","authors":["S Jang - 2023"],"snippet":"Today, a huge amount of unstructured data from various sources is available. Natural language processing (NLP) techniques using such data are applied to several tasks such as named entity recognition (NER). This study is designed to …","url":["https://phaidra.univie.ac.at/detail/o:1637602.pdf"]}
-{"year":"2024","title":"Mastering Transformers: The Journey from BERT to Large Language Models and Stable Diffusion","authors":["S Yıldırım, M Asgari-Chenaghlu - 2024"],"snippet":"Explore transformer-based language models from BERT to GPT, delving into NLP and computer vision tasks, while tackling challenges effectively Key Features Understand the complexity of deep learning architecture and transformers …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=M_wJEQAAQBAJ&oi=fnd&pg=PP1&dq=commoncrawl&ots=avP-WYfjWC&sig=KVeolFlauPbA8bVyuAQyJTiTH4Y"]}
-{"year":"2024","title":"Materials science in the era of large language models: a perspective","authors":["G Lei, R Docherty, SJ Cooper - arXiv preprint arXiv:2403.06949, 2024"],"snippet":"Large Language Models (LLMs) have garnered considerable interest due to their impressive natural language capabilities, which in conjunction with various emergent properties make them versatile tools in workflows ranging from complex …","url":["https://arxiv.org/pdf/2403.06949"]}
-{"year":"2024","title":"Matthew Coscia and","authors":["A Weber"],"snippet":"… URL: https://github.com/commoncrawl/ia-web-commons. [9] Image Details - Container Registry - Google Cloud Platform. 2022. …","url":["https://vtechworks.lib.vt.edu/server/api/core/bitstreams/42cd566c-369f-44c1-afff-4cc3e6a2fb00/content"]}
-{"year":"2024","title":"MDSAA","authors":["IRVG Roque"],"snippet":"In the field of digital marketing, efficient content gap analysis is crucial for developing effective SEO strategies. Traditional approaches to this task are time-consuming, representing a challenge for Organic Performance teams, who must process large …","url":["https://run.unl.pt/bitstream/10362/164588/1/TCDMAA1449.pdf"]}
-{"year":"2024","title":"Measuring and Improving the Energy Efficiency of Large Language Models Inference","authors":["MF Argerich, M Patiño-Martínez - IEEE Access, 2024"],"snippet":"… 4) RedPajama [42]: another family of models based on Pythia with 7B and 3B parameters, fine-tuned on a dataset with the same name as the model, with over 100B text documents coming from 84 CommonCrawl snapshots. Similar to Dolly …","url":["https://ieeexplore.ieee.org/iel8/6287639/6514899/10549890.pdf"]}
-{"year":"2024","title":"Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain","authors":["I García-Ferrero, R Agerri, AA Salazar, E Cabrio… - arXiv preprint arXiv …, 2024"],"snippet":"… mT5 was trained using mC4, a 1 Trillion token Common Crawl-based dataset covering 101 languages. The pre-training is based on a masked language modeling “spancorruption” objective, where consecutive spans of input tokens are replaced …","url":["https://arxiv.org/pdf/2404.07613"]}
-{"year":"2024","title":"Meeting the challenge: A benchmark corpus for automated Urdu meeting summarization","authors":["B Sadia, F Adeeba, S Shams, K Javed - Information Processing & Management, 2024"],"snippet":"Meeting summarization has become crucial as the world is gradually shifting towards remote work. Nowadays, automation of meeting summary generation is really needed in order to minimize the time and effort. The surge in online meetings …","url":["https://www.sciencedirect.com/science/article/pii/S0306457324000943"]}
-{"year":"2024","title":"MELTing point: Mobile Evaluation of Language Transformers","authors":["S Laskaridis, K Kateveas, L Minto, H Haddadi - arXiv preprint arXiv:2403.12844, 2024"],"snippet":"Transformers have revolutionized the machine learning landscape, gradually making their way into everyday tasks and equipping our computers with ``sparks of intelligence''. However, their runtime requirements have prevented them from being …","url":["https://arxiv.org/pdf/2403.12844"]}
-{"year":"2024","title":"Memorization and Privacy Risks in Domain-Specific Large Language Models","authors":["X Yang, Z Wen, W Qu, Z Chen, Z Xiang, B Chen, H Yao - ICLR 2024 Workshop on Reliable …"],"snippet":"… Common Crawl3 is a nonprofit organization that provides a large and open web crawl data repository for public use. It collects web pages from the internet every month and stores them on Amazon Web Services. Common Crawl’s … C4 cleanses …","url":["https://openreview.net/pdf?id=KmW8WkCKRx"]}
-{"year":"2024","title":"Mentions of prejudice in news media–an international comparison","authors":["D Rozado - Journal of Computational Social Science, 2024"],"snippet":"Previous research has identified a post-2010 sharp increase of terms used to denounce prejudice (ie racism, sexism, homophobia, Islamophobia, anti-Semitism, etc.) in US and UK news media content. Here, we extend previous analysis to an …","url":["https://link.springer.com/article/10.1007/s42001-024-00295-2"]}
-{"year":"2024","title":"Methods Futures Report–Sea, Sky, and Land: Engaging in Solidarity in Endangered Ecologies–4S Conference Nov 2023","authors":["R Meckin - 2024"],"snippet":"This is a report of the 4S 2023 conference. The 4S (Society for the Social Studies of Science) conference 2023 was a large, disciplinarily diverse gathering with over 400 sessions spread over four days. Navigating a particular route through the conference …","url":["https://eprints.ncrm.ac.uk/id/eprint/4948/1/NCRM%20method%20futures%204S%20conference%20report.pdf"]}
-{"year":"2024","title":"Milestones in Bengali Sentiment Analysis leveraging Transformer-models: Fundamentals, Challenges and Future Directions","authors":["S Sengupta, S Ghosh, P Mitra, TI Tamiti - arXiv preprint arXiv:2401.07847, 2024"],"snippet":"Sentiment Analysis (SA) refers to the task of associating a view polarity (usually, positive, negative, or neutral; or even fine-grained such as slightly angry, sad, etc.) to a given text, essentially breaking it down to a supervised (since we have the view …","url":["https://arxiv.org/pdf/2401.07847"]}
-{"year":"2024","title":"MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies","authors":["S Hu, Y Tu, X Han, C He, G Cui, X Long, Z Zheng… - arXiv preprint arXiv …, 2024"],"snippet":"The burgeoning interest in developing Large Language Models (LLMs) with up to trillion parameters has been met with concerns regarding resource efficiency and practical expense, particularly given the immense cost of experimentation. This …","url":["https://arxiv.org/pdf/2404.06395"]}
-{"year":"2024","title":"Misinformation Resilient Search Rankings with Webgraph-based Interventions","authors":["P Carragher, EM Williams, KM Carley - arXiv preprint arXiv:2404.08869, 2024"],"snippet":"… To this end, we investigate the distribution of changes in CommonCrawl PageRank as a result of our interventions for all domains in the webgraph, not just news domains. We then take the domains whose PR score changes significantly ( 50%) …","url":["https://arxiv.org/pdf/2404.08869"]}
-{"year":"2024","title":"Mission Critical--Satellite Data is a Distinct Modality in Machine Learning","authors":["E Rolf, K Klemmer, C Robinson, H Kerner - arXiv preprint arXiv:2402.01444, 2024"],"snippet":"Satellite data has the potential to inspire a seismic shift for machine learning -- one in which we rethink existing practices designed for traditional data modalities. As machine learning for satellite data (SatML) gains traction for its real-world impact …","url":["https://arxiv.org/pdf/2402.01444"]}
-{"year":"2024","title":"MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures","authors":["J Ni, F Xue, X Yue, Y Deng, M Shah, K Jain, G Neubig… - arXiv preprint arXiv …, 2024"],"snippet":"… In the detection phase, we train open-source LLMs on self-collected data to detect queries in Common Crawl splits. During filtering, we utilize GPT-4 Turbo to exclude non-query sentences. In classification, we categorize the filtered queries by input …","url":["https://arxiv.org/pdf/2406.06565"]}
-{"year":"2024","title":"MobileVLM: A Fast, Reproducible and Strong Vision Language Assistant for Mobile Devices","authors":["X Chu, L Qiao, X Lin, S Xu, Y Yang, Y Hu, F Wei… - arXiv preprint arXiv …, 2023"],"snippet":"We present MobileVLM, a competent multimodal vision language model (MMVLM) targeted to run on mobile devices. It is an amalgamation of a myriad of architectural designs and techniques that are mobile-oriented, which comprises a set of language …","url":["https://arxiv.org/pdf/2312.16886"]}
-{"year":"2024","title":"Modeling Caption Diversity in Contrastive Vision-Language Pretraining","authors":["S Lavoie, P Kirichenko, M Ibrahim, M Assran… - arXiv preprint arXiv …, 2024"],"snippet":"There are a thousand ways to caption an image. Contrastive Language Pretraining (CLIP) on the other hand, works by mapping an image and its caption to a single vector -- limiting how well CLIP-like models can represent the diverse ways to describe an …","url":["https://arxiv.org/pdf/2405.00740"]}
-{"year":"2024","title":"Modeling the Sacred: Considerations when Using Considerations when Using Religious Texts in Natural Language Processing","authors":["B Hutchinson - arXiv preprint arXiv:2404.14740, 2024"],"snippet":"This position paper concerns the use of religious texts in Natural Language Processing (NLP), which is of special interest to the Ethics of NLP. Religious texts are expressions of culturally important values, and machine learned models have a …","url":["https://arxiv.org/pdf/2404.14740"]}
-{"year":"2024","title":"mOSCAR: A Large-scale Multilingual and Multimodal Document-level Corpus","authors":["M Futeral, A Zebaze, PO Suarez, J Abadji, R Lacroix… - arXiv preprint arXiv …, 2024"],"snippet":"… This motivated us to collect and release the first large-scale multilingual and multimodal document dataset derived from Common Crawl.Our dataset, multimodal OSCAR (mOSCAR), follows the OSCAR initiative [Ortiz Suárez et al., 2019, Abadji et …","url":["https://arxiv.org/pdf/2406.08707"]}
-{"year":"2024","title":"MoVA: Adapting Mixture of Vision Experts to Multimodal Context","authors":["Z Zong, B Ma, D Shen, G Song, H Shao, D Jiang, H Li… - arXiv preprint arXiv …, 2024"],"snippet":"As the key component in multimodal large language models (MLLMs), the ability of the visual encoder greatly affects MLLM's understanding on diverse image content. Although some large-scale pretrained vision encoders such as vision encoders in …","url":["https://arxiv.org/pdf/2404.13046"]}
-{"year":"2024","title":"mPLM-Sim: Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language Models","authors":["P Lin, C Hu, Z Zhang, AFT Martins, H Schütze - Findings of the Association for …, 2024"],"snippet":"Recent multilingual pretrained language models (mPLMs) have been shown to encode strong language-specific signals, which are not explicitly provided during pretraining. It remains an open question whether it is feasible to employ mPLMs to …","url":["https://aclanthology.org/2024.findings-eacl.20.pdf"]}
-{"year":"2024","title":"mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding","authors":["A Hu, H Xu, J Ye, M Yan, L Zhang, B Zhang, C Li… - arXiv preprint arXiv …, 2024"],"snippet":"Structure information is critical for understanding the semantics of text-rich images, such as documents, tables, and charts. Existing Multimodal Large Language Models (MLLMs) for Visual Document Understanding are equipped with text recognition …","url":["https://arxiv.org/pdf/2403.12895"]}
-{"year":"2024","title":"MS MARCO Web Search: a Large-scale Information-rich Web Dataset with Millions of Real Click Labels","authors":["Q Chen, X Geng, C Rosset, C Buractaon, J Lu, T Shen… - Companion Proceedings of …, 2024"],"snippet":"Recent breakthroughs in large models have highlighted the critical significance of data scale, labels and modals. In this paper, we introduce MS MARCO Web Search, the first large-scale information-rich web dataset, featuring millions of real clicked …","url":["https://dl.acm.org/doi/pdf/10.1145/3589335.3648327"]}
-{"year":"2024","title":"Multi Class Depression Detection Through Tweets using Artificial Intelligence","authors":["MO Nusrat, W Shahzad, SA Jamal - arXiv preprint arXiv:2404.13104, 2024"],"snippet":"… Typically, GloVe embeddings were pretrained on extensive corpora like Wikipedia or Common Crawl and fine-tuned for specific tasks. 300 LSTM units were used with a dropout rate of 0.4. For depression classification, the dense layer was …","url":["https://arxiv.org/pdf/2404.13104"]}
-{"year":"2024","title":"Multi-class hate speech detection in the Norwegian language using FAST-RNN and multilingual fine-tuned transformers","authors":["E Hashmi, SY Yayilgan - Complex & Intelligent Systems, 2024"],"snippet":"… FastText, a word representation tool developed by Facebook’s research division, offers both unsupervised and supervised modes and features a comprehensive database of 2 million words from Common Crawl, each represented by 300 …","url":["https://link.springer.com/article/10.1007/s40747-024-01392-5"]}
-{"year":"2024","title":"Multi-Head Mixture-of-Experts","authors":["X Wu, S Huang, W Wang, F Wei - arXiv preprint arXiv:2404.15045, 2024"],"snippet":"Sparse Mixtures of Experts (SMoE) scales model capacity without significant increases in training and inference costs, but exhibits the following two issues: (1) Low expert activation, where only a small subset of experts are activated for …","url":["https://arxiv.org/pdf/2404.15045"]}
-{"year":"2024","title":"Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data Annotation","authors":["J Choi, J Yun, K Jin, YB Kim - arXiv preprint arXiv:2404.09682, 2024"],"snippet":"… an analysis of undesirable content in the common crawl corpus. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2 …","url":["https://arxiv.org/pdf/2404.09682"]}
-{"year":"2024","title":"Multi-Reference Benchmarks for Russian Grammatical Error Correction","authors":["FP Gomez, A Rozovskaya - Proceedings of the 18th Conference of the European …, 2024"],"snippet":"This paper presents multi-reference benchmarks for the Grammatical Error Correction (GEC) of Russian, based on two existing single-reference datasets, for a total of 7,444 learner sentences from a variety of first language backgrounds. Each …","url":["https://aclanthology.org/2024.eacl-long.76.pdf"]}
-{"year":"2024","title":"Multi-Stream Keypoint Attention Network for Sign Language Recognition and Translation","authors":["M Guan, Y Wang, G Ma, J Liu, M Sun - arXiv preprint arXiv:2405.05672, 2024"],"snippet":"Sign language serves as a non-vocal means of communication, transmitting information and significance through gestures, facial expressions, and bodily movements. The majority of current approaches for sign language recognition (SLR) …","url":["https://arxiv.org/pdf/2405.05672"]}
-{"year":"2024","title":"Multi-Task Contrastive Learning for 8192-Token Bilingual Text Embeddings","authors":["I Mohr, M Krimmel, S Sturua, MK Akram, A Koukounas… - arXiv preprint arXiv …, 2024"],"snippet":"… Seeking further diversity and volume, we utilize Common Crawl data to create two types of pairs: one from web page titles and their contents, and another by mining questionanswer pairs from FAQ and support-related pages. Additionally, we pair …","url":["https://arxiv.org/pdf/2402.17016"]}
-{"year":"2024","title":"Multilingual Diversity Improves Vision-Language Representations","authors":["T Nguyen, M Wallingford, S Santy, WC Ma, S Oh… - arXiv preprint arXiv …, 2024"],"snippet":"… Data We experiment with the medium pool of the DataComp benchmark [14], which consists of 128M image-text pairs randomly sampled from Common Crawl dumps between 2014 and 2022, and deduplicated. Unlike other heavily filtered …","url":["https://arxiv.org/pdf/2405.16915"]}
-{"year":"2024","title":"Multilingual E5 Text Embeddings: A Technical Report","authors":["L Wang, N Yang, X Huang, L Yang, R Majumder, F Wei - arXiv preprint arXiv …, 2024"],"snippet":"This technical report presents the training methodology and evaluation results of the open-source multilingual E5 text embedding models, released in mid-2023. Three embedding models of different sizes (small / base / large) are provided, offering a …","url":["https://arxiv.org/pdf/2402.05672"]}
-{"year":"2024","title":"Multilingual Hate Speech Detection: Comparison of Transfer Learning Methods to Classify German, Italian, and Spanish Posts","authors":["J Fillies, MP Hoffmann, A Paschke - 2023 IEEE International Conference on Big Data …, 2023"],"snippet":"… This datasetincludes Wikipedia dumps for all supported languages anda substantial 2.5 terabytes of Common Crawl Data collectedfrom the Internet. The ”RoBERTa” component in the model’sname indicates the adherence to the training procedure …","url":["https://www.computer.org/csdl/proceedings-article/bigdata/2023/10386244/1TUOShUglSU"]}
-{"year":"2024","title":"Multilingual Model Fine-tuning for Sentiment Analysis","authors":["ML Elrefai, MI Khalil, HM Abbas - … on Intelligent Computing and Information Systems …, 2023"],"snippet":"… A sizable multilingual language model was created using 2.5 TB of filtered CommonCrawl data. One of the outstanding XLMRoBERTa in low-resource languages, Low-resource languages are languages with limited available data for …","url":["https://ieeexplore.ieee.org/abstract/document/10391141/"]}
-{"year":"2024","title":"Multilingual Models in Neural Machine Translation","authors":["G Yang"],"snippet":"… XGLM [19] uses the decoder-only model architecture similar to that of GPT-3 [6], and was pre-trained on CC100-XL that covers 68 Common Crawl (CC) snapshots and 134 languages. Experiment results show that XGLM (7.5B) outperforms GPT-3 (6.7B) …","url":["http://mi.eng.cam.ac.uk/~wjb31/MPhil_Thesis_Guangyu_Yang.pdf"]}
-{"year":"2024","title":"MultiLS: A Multi-task Lexical Simplification Framework","authors":["K North, T Ranasinghe, M Shardlow, M Zampieri - arXiv preprint arXiv:2402.14972, 2024"],"snippet":"Lexical Simplification (LS) automatically replaces difficult to read words for easier alternatives while preserving a sentence's original meaning. LS is a precursor to Text Simplification with the aim of improving text accessibility to various target …","url":["https://arxiv.org/pdf/2402.14972"]}
-{"year":"2024","title":"Multimodal Learning for Visual Question Answering using World Knowledge","authors":["MBA Alhaj"],"snippet":"Navigating the frontier of the Visual Turing Test, this research delves into multimodal learning to bridge the gap between visual perception and linguistic interpretation, a foundational challenge in artificial intelligence. It scrutinizes the integration of visual …","url":["https://huggingface.co/spaces/m7mdal7aj/KB-VQA/resolve/main/Files/Dissertation%20Report.pdf"]}
-{"year":"2024","title":"Multiscale cascaded domain-based approach for Arabic fake reviews detection in e-commerce platforms","authors":["N Qandos, G Hamad, M Alharbi, S Alturki, W Alharbi… - Journal of King Saud …, 2024"],"snippet":"Fake reviews in e-commerce can lead to customer deception and financial losses. Despite the importance of fake reviews detection, studies for Arabic language are scarce due to the lack of comprehensive datasets. This study addresses this gap by …","url":["https://www.sciencedirect.com/science/article/pii/S1319157824000156"]}
-{"year":"2024","title":"Multivariate Log-based Anomaly Detection for Distributed Database","authors":["L Zhang, T Jia, M Jia, Y Li, Y Yang, Z Wu - arXiv preprint arXiv:2406.07976, 2024"],"snippet":"… Following this, MultiLog utilizes pre-trained word vectors based on the Common Crawl Corpus with the FastText algorithm[45], which is adept at capturing the inherent relationships among words in natural language. This means each word in a …","url":["https://arxiv.org/pdf/2406.07976"]}
-{"year":"2024","title":"Musical Word Embedding for Music Tagging and Retrieval","authors":["SH Doh, J Lee, D Jeong, J Nam - arXiv preprint arXiv:2404.13569, 2024"],"snippet":"… We used two publicly available embeddings trained on Common Crawl, a large-scale general word corpus, with the GloVe and skipgram … It demonstrates that word embeddings trained with a general word corpus, such as Common Crawl and Wiki …","url":["https://arxiv.org/pdf/2404.13569"]}
-{"year":"2024","title":"Myanmar XNLI: Building a Dataset and Exploring Low-resource Approaches to Natural Language Inference with Myanmar","authors":["AK Htet, M Dras - 2024"],"snippet":"Despite dramatic recent progress in NLP, it is still a major challenge to apply Large Language Models (LLM) to low-resource languages. This is made visible in benchmarks such as Cross-Lingual Natural Language Inference (XNLI), a key task …","url":["https://www.researchsquare.com/article/rs-4329843/latest.pdf"]}
-{"year":"2024","title":"Named Entity Recognition in Italian Lung Cancer Clinical Reports using Transformers","authors":["D Paolo, A Bria, C Greco, M Russano, S Ramella… - 2023 IEEE International …, 2023"],"snippet":"The widespread adoption of electronic health records (EHRs) offers a valuable opportunity to support clinical research by containing crucial patient information, including diagnoses, symptoms, medications, lab tests, and more. Despite the …","url":["https://ieeexplore.ieee.org/abstract/document/10385778/"]}
-{"year":"2024","title":"NATALITY AT RISK? RAISING DOUBTS ON THE EDUCATIONAL IMPORTANCE OF ChatGPT","authors":["P Rojahn - Colloquium, 2024"],"snippet":"Digital tools are part of our daily life. Thus, they also enter educational contexts. With reference to Hannah Arendt’s writings this paper explores if, and to what extent, digital tools can be considered to be helpful and desirable in education. For this …","url":["https://colloquium.elsite.eu/index.php/colloquium/article/download/908/527"]}
-{"year":"2024","title":"Natural Language Processing Advancements: Breaking Barriers in Human-Computer Interaction","authors":["JGC Ramírez - Journal of Artificial Intelligence General science (JAIGS …, 2024"],"snippet":"Natural Language Processing (NLP) advancements have revolutionized human-computer interaction, breaking barriers and opening new frontiers in technology. NLP techniques enable machines to understand, interpret, and generate human …","url":["https://ojs.boulibrary.com/index.php/JAIGS/article/download/63/35"]}
-{"year":"2024","title":"Natural Language Processing for Dialects of a Language: A Survey","authors":["A Joshi, R Dabre, D Kanojia, Z Li, H Zhan, G Haffari… - arXiv preprint arXiv …, 2024"],"snippet":"State-of-the-art natural language processing (NLP) models are trained on massive training corpora, and report a superlative performance on evaluation datasets. This survey delves into an important attribute of these datasets: the dialect of a language …","url":["https://arxiv.org/pdf/2401.05632"]}
-{"year":"2024","title":"Natural Language Processing Journal","authors":["A Caesar, O Özdemir, C Weber, S Wermter"],"snippet":"Natural language processing and vision tasks have recently seen large improvements through the rise of Transformer architectures. The high-performing large language models (LLMs) benefit from large textual datasets that are …","url":["https://www2.informatik.uni-hamburg.de/wtm/publications/2024/COWW24a/1-s2.0-S2949719124000207-main.pdf"]}
-{"year":"2024","title":"Natural Language Processing Methods for Symbolic Music Generation and Information Retrieval: a Survey","authors":["DVT Le, L Bigo, M Keller, D Herremans - arXiv preprint arXiv:2402.17467, 2024"],"snippet":"Several adaptations of Transformers models have been developed in various domains since its breakthrough in Natural Language Processing (NLP). This trend has spread into the field of Music Information Retrieval (MIR), including studies …","url":["https://arxiv.org/pdf/2402.17467"]}
-{"year":"2024","title":"Natural Language Processing Tools for Romanian–Going Beyond a Low-Resource Language","authors":["M Nitu, M Dascalu"],"snippet":"… Oscar (Open Super-large Crawled Aggregated coRpus) [64] is a multilingual dataset obtained via filtering the common crawl corpus. It encompasses 151 languages. The Romanian sub-corpus contains over 4,5 million documents …","url":["https://www.researchgate.net/profile/Nitu-Melania-2/publication/380779085_Natural_Language_Processing_Tools_for_Romanian_-_Going_Beyond_a_Low-Resource_Language/links/664efa81479366623a08548f/Natural-Language-Processing-Tools-for-Romanian-Going-Beyond-a-Low-Resource-Language.pdf"]}
-{"year":"2024","title":"Natural Language Processing","authors":["CH Focke, RM Sylvester - Statistical Methods in Epilepsy, 2024"],"snippet":"In this chapter, we introduce modern natural language processing (NLP) libraries, techniques and their applications. This chapter focuses on deep learning methods and less on computational linguistics that require nuanced knowledge of linguistics …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=x1QIEQAAQBAJ&oi=fnd&pg=PA302&dq=commoncrawl&ots=nunktBqRF2&sig=V-n3c25TaVqCLY-Hs7tRdfKtPBI"]}
-{"year":"2024","title":"Navigating Challenges and Technical Debt in Large Language Models Deployment","authors":["A Menshawy, Z Nawaz, M Fahmy - Proceedings of the 4th Workshop on Machine …, 2024"],"snippet":"… These models, trained on an internet scale data including common crawl, books, and articles, have acquired an extensive understanding of language patterns, nuances, and contexts. This profound comprehension allows LLMs to perform a …","url":["https://dl.acm.org/doi/abs/10.1145/3642970.3655840"]}
-{"year":"2024","title":"Navigating the ethical landscape behind ChatGPT","authors":["L Peng, B Zhao - Big Data & Society, 2024"],"snippet":"… While ChatGPT and similar text-generating AIs claim to be trained on mostly public data such as the Common Crawl archives, rendering … content in public datasets used for AI training, such as the Common Crawl, which is beyond the …","url":["https://journals.sagepub.com/doi/pdf/10.1177/20539517241237488"]}
-{"year":"2024","title":"Navigating the Legal Landscape: Technical Implementation of Copyright Reservations for Text and Data Mining in the Era of AI Language Models","authors":["L Löbling, C Handschigl, K Hofmann, J Schwedhelm - JIPITEC–Journal of Intellectual …, 2023"],"snippet":"… However, limitations arose from the potential omission of specific pages of a website in individual monthly crawls by Common Crawl. Through manual investigation, a section containing the terms of use could be identified for 40 …","url":["https://www.jipitec.eu/jipitec/article/download/16/11"]}
-{"year":"2024","title":"Near to Mid-term Risks and Opportunities of Open Source Generative AI","authors":["F Eiras, A Petrov, B Vidgen, CS de Witt, F Pizzati… - arXiv preprint arXiv …, 2024"],"snippet":"In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about potential …","url":["https://arxiv.org/pdf/2404.17047"]}
-{"year":"2024","title":"Need a Programming Exercise Generated in Your Native Language? ChatGPT's Got Your Back: Automatic Generation of Non-English Programming Exercises Using …","authors":["M Jordan, K Ly, AG Soosai Raj - Proceedings of the 55th ACM Technical Symposium …, 2024"],"snippet":"Large language models (LLMs) like ChatGPT are changing computing education and may create additional barriers to those already faced by non-native English speakers (NNES) learning computing. We investigate an opportunity for a positive …","url":["https://dl.acm.org/doi/pdf/10.1145/3626252.3630897"]}
-{"year":"2024","title":"Nemotron-4 15B Technical Report","authors":["J Parmar, S Prabhumoye, J Jennings, M Patwary… - arXiv preprint arXiv …, 2024"],"snippet":"We introduce Nemotron-4 15B, a 15-billion-parameter large multilingual language model trained on 8 trillion text tokens. Nemotron-4 15B demonstrates strong performance when assessed on English, multilingual, and coding tasks: it …","url":["https://arxiv.org/pdf/2402.16819"]}
-{"year":"2024","title":"Neural Approaches to Decode Semantic Similarities in Spanish Song Lyrics for Enhanced Recommendation Systems","authors":["A Ghajari Espinosa - 2024"],"snippet":"… In this model, it was found that traditional methods of pre-training, which rely on large amounts of data from sources such as Common Crawl… The mC4 dataset is a multilingual variant of C4, containing natural text in 101 languages from the public …","url":["http://e-spacio.uned.es/fez/eserv/bibliuned:master-ETSInformatica-TL-Aghajari/Ghajari_Espinosa_Adrian_TFM.pdf"]}
-{"year":"2024","title":"NEURAL MODELS FOR ONTOLOGY ANNOTATIONS-NEMO","authors":["P Devkota, SD Mohanty"],"snippet":"Words cannot express my gratitude to my advisors Dr. Somya D. Mohanty and Dr. Prashanti Manda for their invaluable supervision and guidance. I am extremely grateful to them for their continuous support, constructive suggestions, and …","url":["https://libres.uncg.edu/ir/uncg/f/Devkota_uncg_0154M_13725.pdf"]}
-{"year":"2024","title":"Neural Network-based Language Modelling for Code-Switching in South African Languages","authors":["JJ van Vüren"],"snippet":"Language models, specifically those based on neural network architectures, have become an attractive alternative to classical statistical language models for natural language processing and speech recognition. Naturally, therefore, the field of neural …","url":["https://scholar.sun.ac.za/bitstreams/481dc105-b6b9-402b-9e68-f600dbc56745/download"]}
-{"year":"2024","title":"Neural Networks with Model Compression","authors":["B Zhang, T Wang, S Xu, D Doermann - 2024"],"snippet":"… Firstly, the availability of large-scale datasets, such as ImageNet for computer vision or the Common Crawl dataset for natural language processing, has enabled the training of deep neural networks with millions or even billions of parameters …","url":["https://link.springer.com/content/pdf/10.1007/978-981-99-5068-3.pdf"]}
-{"year":"2024","title":"No Filter: Cultural and Socioeconomic Diversityin Contrastive Vision-Language Models","authors":["A Pouget, L Beyer, E Bugliarello, X Wang, AP Steiner… - arXiv preprint arXiv …, 2024"],"snippet":"We study cultural and socioeconomic diversity in contrastive vision-language models (VLMs). Using a broad range of benchmark datasets and evaluation metrics, we bring to attention several important findings. First, the common filtering of training …","url":["https://arxiv.org/pdf/2405.13777"]}
-{"year":"2024","title":"Non-governmental Governance of Trust on the Internet: WebPKI as Public Good","authors":["K Grindal, M Mueller, V Srivastava"],"snippet":"… The population of sites we sampled from was indexed by the non-profit foundation Common Crawl. We then employed a script to pull certificate information from our list of URLs. Slightly more than half the sample did not return certificate …","url":["https://weis.utdallas.edu/files/2024/03/Grindal-et-al-WEIS-2024-0836cad1909f1424.pdf"]}
-{"year":"2024","title":"Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models","authors":["ECF German"],"snippet":"This paper identifies a cultural dominance issue within large language models (LLMs) due to the predominant use of English data in model training (eg, ChatGPT). LLMs often provide inappropriate English-culture-related answers that are not relevant to …","url":["https://openreview.net/pdf?id=Og0zmSOFEI0"]}
-{"year":"2024","title":"Notes towards infrastructure governance for large language models","authors":["L Dal Molin - First Monday, 2024"],"snippet":"This paper draws on information infrastructures (IIs) in science and technology studies (STS), as well as on feminist STS scholarship and contemporary critical accounts of digital technologies, to build an initial mapping of the infrastructural …","url":["https://firstmonday.org/ojs/index.php/fm/article/download/13567/11409"]}
-{"year":"2024","title":"NSINA: A News Corpus for Sinhala","authors":["H Hettiarachchi, D Premasiri, L Uyangodage… - arXiv preprint arXiv …, 2024"],"snippet":"The introduction of large language models (LLMs) has advanced natural language processing (NLP), but their effectiveness is largely dependent on pre-training resources. This is especially evident in low-resource languages, such as Sinhala …","url":["https://arxiv.org/pdf/2403.16571"]}
-{"year":"2024","title":"Numerical Claim Detection in Finance: A New Financial Dataset, Weak-Supervision Model, and Market Analysis","authors":["A Shah, A Hiray, P Shah, A Banerjee, A Singh… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we investigate the influence of claims in analyst reports and earnings calls on financial market returns, considering them as significant quarterly events for publicly traded companies. To facilitate a comprehensive analysis, we construct a …","url":["https://arxiv.org/pdf/2402.11728"]}
-{"year":"2024","title":"NusaBERT: Teaching IndoBERT to be Multilingual and Multicultural","authors":["W Wongso, DS Setiawan, S Limcorn, A Joyoadikusumo - arXiv preprint arXiv …, 2024"],"snippet":"… We also note that NusaBERT was pre-trained on Wikipedia and common crawl corpora, which explains its effectiveness on and closeness to NusaX and NusaTranslation source domains, but not so for NusaParagraph. Thus, due to their high linguistic and …","url":["https://arxiv.org/html/2403.01817v1"]}
-{"year":"2024","title":"Nyonic Technical Report","authors":["J Tian, R Wang, C Li, Y Zhou, J Liu, J Wang - arXiv preprint arXiv:2404.15702, 2024"],"snippet":"… Our curated dataset is specifically designed to meet these criteria, incorporating sources such as the Common Crawl, books, Wikipedia, code, and … Our data sources encompass Common Crawl, Wiki, and various coding repositories. The final …","url":["https://arxiv.org/pdf/2404.15702"]}
-{"year":"2024","title":"Ocean Decade Vision 2030 White Papers–Challenge 8: Create a digital representation of the ocean.","authors":["JB Calewaert, PC Sierra-Correa, O McMeel… - 2024"],"snippet":"… The Common crawl and WebImageText are examples, with communities such as Hugging Face and KAGGLE creating new communities of practice16F … 17 https://commoncrawl.org, https://github.com/google-research-datasets/wit, https://huggingface.co, https://www.kaggle.com …","url":["https://aquadocs.org/bitstream/handle/1834/43137/WP8_v.2.0.docx.pdf?sequence=1&isAllowed=y"]}
-{"year":"2024","title":"OLMo: Accelerating the Science of Language Models","authors":["D Groeneveld, I Beltagy, P Walsh, A Bhagia, R Kinney… - arXiv preprint arXiv …, 2024"],"snippet":"… well on evaluations predominated by Common Crawl, such as C4, though different ways of postprocessing Common Crawl are best fit by … The RedPajama evaluation shows a similar pattern, perhaps as only 2 of its 7 domains are from …","url":["https://arxiv.org/pdf/2402.00838"]}
-{"year":"2024","title":"Omniview-Tuning: Boosting Viewpoint Invariance of Vision-Language Pre-training Models","authors":["S Ruan, Y Dong, H Liu, Y Huang, H Su, X Wei - arXiv preprint arXiv:2404.12139, 2024"],"snippet":"Vision-Language Pre-training (VLP) models like CLIP have achieved remarkable success in computer vision and particularly demonstrated superior robustness to distribution shifts of 2D images. However, their robustness under 3D viewpoint …","url":["https://arxiv.org/pdf/2404.12139"]}
-{"year":"2024","title":"On Labs and Fabs: Mapping How Alliances, Acquisitions, and Antitrust are Shaping the Frontier AI Industry","authors":["T Aguirre - arXiv preprint arXiv:2406.01722, 2024"],"snippet":"As frontier AI models progress, policy proposals for safe AI development are gaining increasing attention from researchers and policymakers. This paper evaluates the present landscape of integration within the AI supply chain, emphasizing vertical …","url":["https://arxiv.org/pdf/2406.01722"]}
-{"year":"2024","title":"On Protecting the Data Privacy of Large Language Models (LLMs): A Survey","authors":["B Yan, K Li, M Xu, Y Dong, Y Zhang, Z Ren, X Cheng - arXiv preprint arXiv …, 2024"],"snippet":"… For example, GPT-3, developed by OpenAI, was pre-trained using CommonCrawl, constituting 45TB of compressed plaintext before filtering [37]. Regarding multimodal LLMs, CLIP’s training dataset encompasses 400 million pairs of images and text …","url":["https://arxiv.org/pdf/2403.05156"]}
-{"year":"2024","title":"On the data scarcity problem of neural-based named entity recognition","authors":["R Zhou - 2023"],"snippet":"… The initial release trained on Wikipedia includes word representations for nine languages, namely Arabic, Czech, German, English, Spanish, French, Italian, Romanian and Russian, and has quickly expanded to 157 languages by training on larger …","url":["https://dr.ntu.edu.sg/bitstream/10356/173481/2/Thesis_ZhouRan_final.pdf"]}
-{"year":"2024","title":"On the evaluation and application of neural language models for grammatical error detection","authors":["C Davis - 2024"],"snippet":"Neural language models (NLM) have become a core component in many downstream applications within the field of natural language processing, including the task of data-driven automatic grammatical error detection (GED). This thesis …","url":["https://www.repository.cam.ac.uk/bitstreams/f9ca765c-f10e-4b64-8c10-3d3b7d38810d/download"]}
-{"year":"2024","title":"On the importance of Data Scale in Pretraining Arabic Language Models","authors":["A Ghaddar, P Langlais, M Rezagholizadeh, B Chen - arXiv preprint arXiv:2401.07760, 2024"],"snippet":"Pretraining monolingual language models have been proven to be vital for performance in Arabic Natural Language Processing (NLP) tasks. In this paper, we conduct a comprehensive study on the role of data in Arabic Pretrained Language …","url":["https://arxiv.org/pdf/2401.07760"]}
-{"year":"2024","title":"On the Question of Authorship in Large Language Models","authors":["C Soos, L Haroutunian - KO KNOWLEDGE ORGANIZATION, 2024"],"snippet":"… CommonCrawl exemplifies the problem of documentation debt. The dataset is an effort by The Common Crawl Foundation to “[democratize] access to web information by producing and maintaining an open repository of web crawl data” (Common …","url":["https://www.nomos-elibrary.de/10.5771/0943-7444-2024-2-83.pdf"]}
-{"year":"2024","title":"On the Tip of the Tongue: Analyzing Conceptual Representation in Large Language Models with Reverse-Dictionary Probe","authors":["N Xu, Q Zhang, M Zhang, P Qian, X Huang - arXiv preprint arXiv:2402.14404, 2024"],"snippet":"Probing and enhancing large language models' reasoning capacity remains a crucial open question. Here we re-purpose the reverse dictionary task as a case study to probe LLMs' capacity for conceptual inference. We use in-context learning …","url":["https://arxiv.org/pdf/2402.14404"]}
-{"year":"2024","title":"One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support","authors":["V Rasiah, R Stern, V Matoshi, M Stürmer, I Chalkidis…"],"snippet":"Recent strides in Large Language Models (LLMs) have saturated many NLP benchmarks (even professional domain-specific ones), emphasizing the need for more challenging ones to properly assess LLM capabilities. Domain-specific and …","url":["https://openreview.net/pdf?id=7vkz7cKd1X"]}
-{"year":"2024","title":"Online health search via multi-dimensional information quality assessment based on deep language models","authors":["B Zhang, N Naderi, R Mishra, D Teodoro - 2024"],"snippet":"Background Widespread misinformation in Web resources can lead to serious implications for individuals seeking health advice. Despite that, information retrieval models are often focused only on the query-document relevance dimension to rank …","url":["https://hal.science/hal-04419996/"]}
-{"year":"2024","title":"Online Health Search Via Multidimensional Information Quality Assessment Based on Deep Language Models: Algorithm Development and Validation","authors":["B Zhang, N Naderi, R Mishra, D Teodoro - JMIR AI, 2024"],"snippet":"… In this study, we simulated online health information search scenarios with a topic set of 32 different health-related inquiries and a corpus containing 1 billion web documents from the April 2019 snapshot of Common Crawl. Using state-of-the-art …","url":["https://ai.jmir.org/2024/1/e42630"]}
-{"year":"2024","title":"Ontology Completion with Natural Language Inference and Concept Embeddings: An Analysis","authors":["N Li, T Bailleux, Z Bouraoui, S Schockaert - arXiv preprint arXiv:2403.17216, 2024"],"snippet":"We consider the problem of finding plausible knowledge that is missing from a given ontology, as a generalisation of the well-studied taxonomy expansion task. One line of work treats this task as a Natural Language Inference (NLI) problem, thus relying …","url":["https://arxiv.org/html/2403.17216v1"]}
-{"year":"2024","title":"Open Assistant Toolkit--version 2","authors":["S Fischer, F Rossetto, C Gemmell, A Ramsay, I Mackie… - arXiv preprint arXiv …, 2024"],"snippet":"… To source knowledge and tasks, we release a new offline pipeline to parse and augment task data from CommonCrawl. The offline pipeline supports using LLMs and additional open-source multimodal data sources to enhance tasks and make …","url":["https://arxiv.org/pdf/2403.00586"]}
-{"year":"2024","title":"Open Science at the Generative AI Turn: An Exploratory Analysis of Challenges and Opportunities","authors":["M Hosseini, SPJM Horbach, K Holmes…"],"snippet":"Technology influences Open Science (OS) practices, because conducting science in transparent, accessible, and participatory ways requires tools/platforms for collaborative research and sharing results. Due to this direct relationship …","url":["https://osf.io/zns7g/download"]}
-{"year":"2024","title":"OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models","authors":["F Xue, Z Zheng, Y Fu, J Ni, Z Zheng, W Zhou, Y You - arXiv preprint arXiv:2402.01739, 2024"],"snippet":"To help the open-source community have a better understanding of Mixture-of-Experts (MoE) based large language models (LLMs), we train and release OpenMoE, a series of fully open-sourced and reproducible decoder-only MoE LLMs, ranging from …","url":["https://arxiv.org/pdf/2402.01739"]}
-{"year":"2024","title":"OptiComm-GPT: a GPT-based versatile research assistant for optical fiber communication systems","authors":["X Jiang, M Zhang, Y Song, Y Zhang, Y Wang, C Ju… - Optics Express, 2024"],"snippet":"… Generally, LLMs are pre-trained on publicly available datasets such as BooksCorpus, Common Crawl, and Wikipedia, thereby ensuring comprehensive coverage of knowledge. Meanwhile, with the support of powerful analysis, reasoning …","url":["https://opg.optica.org/oe/fulltext.cfm?uri=oe-32-12-20776"]}
-{"year":"2024","title":"Optimization and Evaluation in Machine Learning Challenges","authors":["J Pokrywka"],"snippet":"To develop new machine learning methods, it is necessary to evaluate them reliably. This doctoral thesis discusses some aspects of preparing machine learning challenges and techniques for developing their solutions. The work consists of …","url":["https://repozytorium.amu.edu.pl/bitstreams/7a38c2a1-c992-4fa5-9ece-1c73f1024154/download"]}
-{"year":"2024","title":"Optimization of news dissemination push mode by intelligent edge computing technology for deep learning","authors":["JL DeGe, S Sang - Scientific Reports, 2024"],"snippet":"… Realnew (https://paperswithcode.com/dataset/realnews) is a large corpus of news articles from CommonCrawl. The data is crawled from CommonCrawl, which is limited to 5000 news fields of Google News Index. The author uses the …","url":["https://www.nature.com/articles/s41598-024-53859-7"]}
-{"year":"2024","title":"Optimization of Unsupervised Neural Machine Translation Based on Syntactic Knowledge Improvement","authors":["A Zhou - Optimization, 2023"],"snippet":"… Common Crawl is a multilingual aligned dataset based on web crawling. Para Crawl is a multilingual parallel corpus for large-scale web crawling. As shown in Table III, the detection accuracies of LSTM in Newstest2020, Newstest2021 …","url":["https://search.proquest.com/openview/b003a8244f2be3b8735b21ff0421e7d0/1?pq-origsite=gscholar&cbl=5444811"]}
-{"year":"2024","title":"Optimizing Data I/O for LLM Datasets on Remote Storage","authors":["T Zhong, J Zhao, X Guo, Q Su, G Fox"],"snippet":"Training large language models (LLMs) demands increasingly larger datasets for optimal performance [13]. In practice, these datasets may include hundreds of terabytes (TB) or even petabytes of data. For example, Common Crawl [3] needs …","url":["https://luosuu.github.io/assets/files/AIOps_24.pdf"]}
-{"year":"2024","title":"Optimizing Language Augmentation for Multilingual Large Language Models: A Case Study on Korean","authors":["CS Choi, Y Jeong, S Park, IH Won, HS Lim, SM Kim… - arXiv preprint arXiv …, 2024"],"snippet":"… Llama2 is a multilingual language model trained using largescale publicly available data (including CommonCrawl, Github, Wikipedia, and ArXiv) for more than 28 languages. Thus, it possesses cross-language understanding capabilities …","url":["https://arxiv.org/pdf/2403.10882"]}
-{"year":"2024","title":"ORCID","authors":["P Gries"],"snippet":"How are Asian and Black men and women stereotyped? Research from the gendered race and stereotype content perspectives has produced mixed empirical findings. Using BERT models pre-trained on English language books, news articles …","url":["https://psychbruce.github.io/paper/Bao_Accepted_BJSP_FMAT_Stereotype_Manuscript.pdf"]}
-{"year":"2024","title":"Organic Data-Driven Approach for Turkish Grammatical Error Correction and LLMs","authors":["A Ersoy, OT Yıldız - arXiv preprint arXiv:2405.15320, 2024"],"snippet":"… 2020) which contains random paragraphs sampled from the CommonCrawl dataset3. Some studies put some effort into filling the gap and … 2020), a multilingual pre-trained encoder-decoder text-to-text transformer trained on a Common Crawl-based …","url":["https://arxiv.org/pdf/2405.15320"]}
-{"year":"2024","title":"Outlier Detection in Serbian CommonCrawl Data","authors":["V Kalušev, D Ćulibrk - 2024 23rd International Symposium INFOTEH …, 2024"],"snippet":"The surge in large language models (LLMs) has greatly advanced natural language processing. However, their development is often hampered by the limited availability and quality of training datasets, particularly for underrepresented languages. Our …","url":["https://ieeexplore.ieee.org/abstract/document/10495987/"]}
-{"year":"2024","title":"Outsmarting Artificial Intelligence in the Classroom—Incorporating Large Language Model-Based Chatbots into Teaching","authors":["J Wutzler - Issues in Accounting Education, 2024"],"snippet":"Since the release of ChatGPT in November 2022, large language model-based chatbots have attracted much attention. Although businesses value their potential for efficiency gains, academics are concerned about their effects on learning and …","url":["https://publications.aaahq.org/iae/article/doi/10.2308/ISSUES-2023-064/12560"]}
-{"year":"2024","title":"Overview of Existing LLM Families","authors":["A Kucharavy - Large, 2024"],"snippet":"… data that are considered as redundant—namely the Common Crawl and Colossal Cleaned Common Crawl (C4). Researchers who created the … to Common Crawl when it came to training LLMs [30] and should be used instead of the whole …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-54827-7.pdf#page=47"]}
-{"year":"2024","title":"Overview of the TREC 2023 NeuCLIR Track (Notebook Paper)","authors":["D Lawrie, S MacAvaney, J Mayfield, P McNamee…"],"snippet":"… For more information about extracting the text for the documents from CommonCrawl News and how the collection can be obtained, see … of the track including HC4 — a CLIR collection built over three years of Common Crawl data in …","url":["https://terpconnect.umd.edu/~oard/pdf/trec23neuclir-notebook.pdf"]}
-{"year":"2024","title":"Pack of LLMs: Model Fusion at Test-Time via Perplexity Optimization","authors":["C Mavromatis, P Karypis, G Karypis - arXiv preprint arXiv:2404.11531, 2024"],"snippet":"… 2019) is sa publicly available distribution of a Common Crawl snapshot. Following cBTM, we use 168B tokens of the no blocklist version (en.noblocklist) that is out of distribution to the OPT model’s pretraining corpus. S2ORC (Lo et al.…","url":["https://arxiv.org/pdf/2404.11531"]}
-{"year":"2024","title":"PAL: Proxy-Guided Black-Box Attack on Large Language Models","authors":["C Sitawarin, N Mu, D Wagner, A Araujo - arXiv preprint arXiv:2402.09674, 2024"],"snippet":"Large Language Models (LLMs) have surged in popularity in recent months, but they have demonstrated concerning capabilities to generate harmful content when manipulated. While techniques like safety fine-tuning aim to minimize harmful use …","url":["https://arxiv.org/pdf/2402.09674"]}
-{"year":"2024","title":"Parameter-Efficient Tuning of Large Convolutional Models","authors":["W Chen, Z Miao, Q Qiu - arXiv preprint arXiv:2403.00269, 2024"],"snippet":"To address the high computational and parameter complexity associated with fine-tuning large pre-trained models, researchers have developed parameter-efficient methods, where only partial parameters are updated for downstream tasks. However, these …","url":["https://arxiv.org/pdf/2403.00269"]}
-{"year":"2024","title":"Paraphrase Generation and Supervised Learning for Improved Automatic Short Answer Grading","authors":["L Ouahrani, D Bennouar - International Journal of Artificial Intelligence in …, 2024"],"snippet":"We consider the reference-based approach for Automatic Short Answer Grading (ASAG) that involves scoring a textual constructed student answer comparing to a teacher-provided reference answer. The reference answer does not cover the variety of student …","url":["https://link.springer.com/article/10.1007/s40593-023-00391-w"]}
-{"year":"2024","title":"Parsability revisited and reassessed","authors":["S Monakhov - Journal of Linguistics, 2023"],"snippet":"This paper provides evidence that the inveterate way of assessing linguistic items’ degrees of analysability by calculating their derivation to base frequency ratios may obfuscate the difference between two meaning processing models: one based on …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/896CFA4F3C89952AF52611DCBCD262B3/S0022226723000385a.pdf/parsability-revisited-and-reassessed.pdf"]}
-{"year":"2024","title":"Part-of-Speech Tagger for Bodo Language using Deep Learning approach","authors":["D Pathak, S Narzary, S Nandi, B Som - arXiv preprint arXiv:2401.03175, 2024"],"snippet":"Language Processing systems such as Part-of-speech tagging, Named entity recognition, Machine translation, Speech recognition, and Language modeling (LM) are well-studied in high-resource languages. Nevertheless, research on these …","url":["https://arxiv.org/pdf/2401.03175"]}
-{"year":"2024","title":"Pathological Liars: Algorithmic Knowing in the Rhetorical Ecosystem of Wallstreetbets","authors":["MH Yang, ZP Majdik - Rhetoric Society Quarterly, 2024"],"snippet":"This essay demonstrates the value of using artificial intelligence (AI) technologies to address specific kinds of research questions in rhetoric. The essay builds on a study of a novel rhetorical object first observed by Yang on the Reddit subreddit r/wallstreetbets …","url":["https://www.tandfonline.com/doi/abs/10.1080/02773945.2024.2343616"]}
-{"year":"2024","title":"Pathological-Llama: an Explainable Medical Visual Question An","authors":["S Nguyen - 2024"],"snippet":"This thesis introduces Pathological-Llama, an explainable medical visual question answering system that integrates computer vision and natural language processing to accurately interpret medical images through a generative task approach. By …","url":["https://www.zhaw.ch/storage/engineering/institute-zentren/cai/studentische_arbeiten/Herbst_2023/MSE__Master_Thesis_23_bogo_PathologicalLlama.pdf"]}
-{"year":"2024","title":"Pedro L. Rodriguez Arthur Spirling Brandon M. Stewart Elisa M. Wirsching","authors":["BM Stewart"],"snippet":"… from Common Crawl and Wikipedia. A strength of the fastText model is that it uses subword … On inspection, we saw that Common Crawl includes many typos and rare terms (plus many … Beyond this potential for noise, Common Crawl is not …","url":["https://alcembeddings.org/assets/img/RSSW_paper_january_2024.pdf"]}
-{"year":"2024","title":"Performance Comparison of Large Language Models, GPT and Gemini on Turkish News Classification Task","authors":["ZA Guven - 2024"],"snippet":"… This was achieved by training a Transformer-based masked language model on 100 languages using more than two terabytes of filtered CommonCrawl data. The balance between high and low-resource languages and the impact of language …","url":["https://www.researchsquare.com/article/rs-4351735/latest.pdf"]}
-{"year":"2024","title":"Performance Evaluation of Word Embedding Algorithms","authors":["S Kulshretha, L Lodha - Performance Evaluation, 2023"],"snippet":"This study intends to explore the field of word embedding and thoroughly examine and contrast various word embedding algorithms. Words retain their semantic relationships and meaning when they are transformed into vectors using word …","url":["https://ijisrt.com/assets/upload/files/IJISRT23DEC1110.pdf"]}
-{"year":"2024","title":"Performance of ChatGPT on American Board of Surgery In-Training Examination Preparation Questions","authors":["CG Tran, J Chang, SK Sherman, JP De Andrade - Journal of Surgical Research, 2024"],"snippet":"… The training dataset of ChatGPT 3.5, where the artificial intelligence (AI) “knowledge” is derived, is comprised of Common Crawl (a monthly updated web archive of data), books, journals, and Wikipedia and totals over 500 billion encoded “tokens.” Many …","url":["https://www.sciencedirect.com/science/article/pii/S0022480424002294"]}
-{"year":"2024","title":"Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models","authors":["Z Ankner, C Blakeney, K Sreenivasan, M Marion… - arXiv preprint arXiv …, 2024"],"snippet":"… Secondly, while previous work only investigates pruning on datasets composed of just one domain (CommonCrawl1), we consider two … dataset, with 81.31% of its data being derived from the CommonCrawl. We find that successful pruning …","url":["https://arxiv.org/pdf/2405.20541"]}
-{"year":"2024","title":"Personal Science Guide to AI","authors":["R Sprague - 2024"],"snippet":"Imagine you have access to a zillion documents, preferably curated in some way reassures you about their quality and consistency. Wikipedia, for example, or maybe Reddit and other posts that have been sufficiently up-voted. Maybe you also have a …","url":["https://ai.personalscience.com/PS-AI/Book/psai.pdf"]}
-{"year":"2024","title":"Personality trait detection via transfer learning","authors":["B Alshouha, J Serrano-Guerrero, F Chiclana… - Comput Mater Continua …, 2024"],"snippet":"Personality recognition plays a pivotal role when developing user-centric solutions such as recommender systems or decision support systems across various domains, including education, e-commerce, or human resources. Traditional machine …","url":["https://cdn.techscience.cn/files/cmc/2024/TSP_CMC-78-2/TSP_CMC_46711/TSP_CMC_46711.pdf"]}
-{"year":"2024","title":"Perspectives of Global and Hong Kong's Media on China's Belt and Road Initiative","authors":["LC Khoo, A Datta - arXiv preprint arXiv:2312.17013, 2023"],"snippet":"This study delves into the media analysis of China's ambitious Belt and Road Initiative (BRI), which, in a polarized world, and furthermore, owing to the very polarizing nature of the initiative itself, has received both strong criticisms and …","url":["https://arxiv.org/pdf/2312.17013"]}
-{"year":"2024","title":"PHISHING DETECTION SYSTEM THROUGH MACHINE LEARNING BASED ON URL","authors":["PU Chandra, TV Teja, VN Reddy, S Agarwalla"],"snippet":"… Legitimate site data is often gathered from Alexa's top-ranking website database or through common-crawl. Additionally, publicly available datasets like those from the UCI machine learning repository, containing over 11,000 records with 31 …","url":["https://www.irjmets.com/uploadedfiles/paper/issue_3_march_2024/49997/final/fin_irjmets1709462277.pdf"]}
-{"year":"2024","title":"Phishing Detection Using Hybrid Algorithm Based on Clustering and Machine Learning","authors":["L Al-Shalabi, Y Hasan Jazyah - International Journal of Computing and Digital …, 2024"],"snippet":"Phishing is a prevalent and evolving cyber threat that continues to exploit human vulnerability to deceive individuals and organizations into revealing sensitive information. Phishing attacks encompass a range of tactics, from deceptive emails …","url":["https://journal.uob.edu.bh/bitstream/handle/123456789/5367/1570989057.pdf?sequence=1"]}
-{"year":"2024","title":"Physics-informed Machine Learning with Uncertainty Quantification","authors":["A Daw - 2024"],"snippet":"Physics Informed Machine Learning (PIML) has emerged as the forefront of research in scientific machine learning with the key motivation of systematically coupling machine learning (ML) methods with prior domain knowledge often available in the …","url":["https://vtechworks.lib.vt.edu/bitstreams/ee8eca5c-29ad-4698-a9ac-f68116d90fe2/download"]}
-{"year":"2024","title":"PIRB: A Comprehensive Benchmark of Polish Dense and Hybrid Text Retrieval Methods","authors":["S Dadas, M Perełkiewicz, R Poświata - arXiv preprint arXiv:2402.13350, 2024"],"snippet":"We present Polish Information Retrieval Benchmark (PIRB), a comprehensive evaluation framework encompassing 41 text information retrieval tasks for Polish. The benchmark incorporates existing datasets as well as 10 new, previously …","url":["https://arxiv.org/pdf/2402.13350"]}
-{"year":"2024","title":"Pitfalls of Conversational LLMs on News Debiasing","authors":["IB Schlicht, D Altiok, M Taouk, L Flek - arXiv preprint arXiv:2404.06488, 2024"],"snippet":"This paper addresses debiasing in news editing and evaluates the effectiveness of conversational Large Language Models in this task. We designed an evaluation checklist tailored to news editors' perspectives, obtained generated texts from three …","url":["https://arxiv.org/pdf/2404.06488"]}
-{"year":"2024","title":"PLAID SHIRTTT for Large-Scale Streaming Dense Retrieval","authors":["D Lawrie, E Kayi, E Yang, J Mayfield, DW Oard - arXiv preprint arXiv:2405.00975, 2024"],"snippet":"… With ten million documents from the news subset of CommonCrawl, NeuCLIR is presently the largest available test collection for MLIR; It is tiny though relative to ClueWeb, and thus has relatively small shards. The NeuCLIR MLIR task is to …","url":["https://arxiv.org/pdf/2405.00975"]}
-{"year":"2024","title":"Please be polite to your peers: a multi-task model for assessing the tone and objectivity of critiques of peer review comments","authors":["PK Bharti, M Agarwal, A Ekbal - Scientometrics, 2024"],"snippet":"The peer-review process plays a pivotal role in maintaining the quality and credibility of scientific publications. However, in recent times, there has been an increase in unhelpful and overly critical reviews, which can be detrimental to the …","url":["https://link.springer.com/article/10.1007/s11192-024-04938-z"]}
-{"year":"2024","title":"Politehnica University of Bucharest, Splaiul Independentei Nr. 313, Cector 6, Bucharest, Romania radu. stefan@ live. de, radu. stefan3@ student. upt. ro","authors":["R Stefan, G Carutasu, M Mocan - The 17th International Conference Interdisciplinarity in …"],"snippet":"This paper aims to investigate the ethical considerations surrounding the implementation and usage of large language models (LLMs). LLMs have shown tremendous advance in natural language processing and have the potential to …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=u9b9EAAAQBAJ&oi=fnd&pg=PA131&dq=commoncrawl&ots=-M9_Zu0oSH&sig=tr2it1m_D-HFpU5IrX5YZn7SwEY"]}
-{"year":"2024","title":"Position: Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?","authors":["S Longpre, R Mahari, N Obeng-Marnu, W Brannon…"],"snippet":"… Common Crawl. For pretraining text data, models routinely rely on the Common Crawl.For instance, sixty percent of GPT-3 training data is … Common Crawl is accurate with wide coverage, but not detailed. Hugging Face can be inaccurate with …","url":["https://openreview.net/pdf?id=3hSTecKy1b"]}
-{"year":"2024","title":"Position: Mission Critical–Satellite Data is a Distinct Modality in Machine Learning","authors":["E Rolf, K Klemmer, C Robinson, H Kerner - Forty-first International Conference on Machine …"],"snippet":"Satellite data has the potential to inspire a seismic shift for machine learning---one in which we rethink existing practices designed for traditional data modalities. As machine learning for satellite data (SatML) gains traction for its real-world impact …","url":["https://openreview.net/pdf?id=PQ0ERKKYJu"]}
-{"year":"2024","title":"Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI","authors":["F Eiras, A Petrov, B Vidgen, CS de Witt, F Pizzati… - Forty-first International Conference …"],"snippet":"In the next few years, applications of Generative AI are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about potential …","url":["https://openreview.net/pdf?id=8q4EPdjTLE"]}
-{"year":"2024","title":"Position: Will we run out of data? Limits of LLM scaling based on human-generated data","authors":["P Villalobos, A Ho, J Sevilla, T Besiroglu, L Heim… - Forty-first International Conference …"],"snippet":"… Assuming that Common Crawl is a representative sample of the indexed web,11 we can use it to estimate the average amount of plain text bytes per web page. This number has increased over time, from around 6100 bytes in 2013 to about 8200 …","url":["https://openreview.net/pdf?id=ViZcgDQjyG"]}
-{"year":"2024","title":"Post-processing Techniques for Word Embedding","authors":["ZM Albujasim - 2024"],"snippet":"Word embedding has been a significant breakthrough in natural language processing (NLP). Although word representation has improved remarkably and resulted in better performance in downstream NLP applications, interpretability of …","url":["https://repository.library.carleton.ca/downloads/g445cf462"]}
-{"year":"2024","title":"Posthumanist AI","authors":["G SARAH"],"snippet":"… In their now canonical paper on “Stochastic Parrots”, Bender, Gebru, McMillan-Major, and Mitchell note that \"it is easy to imagine that very large datasets, such as Common Crawl “…petabytes of data collected over 8 years of web crawling” a …","url":["https://generativeaiandhci.github.io/papers/2024/genaichi2024_32.pdf"]}
-{"year":"2024","title":"Pre-Trained Acoustic-and-Textual Modeling for End-To-End Speech-To-Text Translation","authors":["W Zhang, H Zhang, C Liu, Z Ye, X Zhou, C Lin, L Dai - ICASSP 2024-2024 IEEE …, 2024"],"snippet":"… The monolingual data are mainly from News Commentary, News crawl and Common Crawl. We apply language identification [23] to retain sentences predicted as desired language, remove sentences longer than 250 tokens and with a source/target …","url":["https://ieeexplore.ieee.org/abstract/document/10446635/"]}
-{"year":"2024","title":"Pre-trained language models in medicine: A survey","authors":["X Luo, Z Deng, B Yang, MY Luo - Artificial Intelligence in Medicine, 2024"],"snippet":"With the rapid progress in Natural Language Processing (NLP), Pre-trained Language Models (PLM) such as BERT, BioBERT, and ChatGPT have shown great potential in various medical NLP tasks. This paper surveys the cutting-edge …","url":["https://www.sciencedirect.com/science/article/pii/S0933365724001465"]}
-{"year":"2024","title":"Pre-trained Large Language Models for Financial Sentiment Analysis","authors":["W Luo, D Gong - arXiv preprint arXiv:2401.05215, 2024"],"snippet":"Financial sentiment analysis refers to classifying financial text contents into sentiment categories (eg positive, negative, and neutral). In this paper, we focus on the classification of financial news title, which is a challenging task due to a lack of …","url":["https://arxiv.org/pdf/2401.05215"]}
-{"year":"2024","title":"Pre-training Small Base LMs with Fewer Tokens","authors":["S Sanyal, S Sanghavi, AG Dimakis - arXiv preprint arXiv:2404.08634, 2024"],"snippet":"We study the effectiveness of a simple approach to develop a small base language model (LM) starting from an existing large base LM: first inherit a few transformer blocks from the larger LM, and then train this smaller model on a very small subset (0.1\\%) …","url":["https://arxiv.org/pdf/2404.08634"]}
-{"year":"2024","title":"Predicting fraud in MD&A sections using deep learning","authors":["S Velloor Sivasubramanian, D Skillicorn - Journal of Business Analytics, 2024"],"snippet":"Conventional data analytic techniques have been successfully applied to detecting fraud in the Management’s Discussion and Analysis sections of company filings mandated by the SEC. Here, we investigate whether fraud detection can be …","url":["https://www.tandfonline.com/doi/abs/10.1080/2573234X.2024.2342773"]}
-{"year":"2024","title":"Predicting semantic category of answers for question answering systems using transformers: a transfer learning approach","authors":["S CM, J Prakash, VS Alaparthi - Multimedia Tools and Applications, 2024"],"snippet":"… The model uses a data set of web extracted text that has been created with the help of the Common Crawl and preprocessed to remove short, duplicate, and non-English content, resulting in a corpus called \"Colossal Clean Crawled Corpus\" (C4). An …","url":["https://link.springer.com/article/10.1007/s11042-024-18609-x"]}
-{"year":"2024","title":"Prediction of Author's Profile basing on Fine-Tuning BERT model","authors":["B Bsir, N Khoufi, M Zrigui - Informatica, 2024"],"snippet":"… Indeed, XLMRoBERTa is the multilingual variant of RoBERTa trained with a multilingual MLM on one hundred languages, with more than two terabytes of filtered Common Crawl data.XLM-RoBERTa showed its superiority over BERT by its …","url":["https://informatica.si/index.php/informatica/article/download/4839/2718"]}
-{"year":"2024","title":"Preemptive Answer\" Attacks\" on Chain-of-Thought Reasoning","authors":["R Xu, Z Qi, W Xu - arXiv preprint arXiv:2405.20902, 2024"],"snippet":"Large language models (LLMs) showcase impressive reasoning capabilities when coupled with Chain-of-Thought (CoT) prompting. However, the robustness of this approach warrants further investigation. In this paper, we introduce a novel scenario …","url":["https://arxiv.org/pdf/2405.20902"]}
-{"year":"2024","title":"Pretraining and Updating Language-and Domain-specific Large Language Model: A Case Study in Japanese Business Domain","authors":["K Takahashi, T Omi, K Arima, T Ishigaki - arXiv preprint arXiv:2404.08262, 2024"],"snippet":"… , mC4, and Common Crawl. These datasets contribute to general knowledge, which is essential for diverse natural language processing tasks. … the proportion of clean domain-specific data, we aim to mitigate the impact of noisy data sources such …","url":["https://arxiv.org/pdf/2404.08262"]}
-{"year":"2024","title":"Probability-Aware Word-Confusion-Network-To-Text Alignment Approach for Intent Classification","authors":["E Villatoro-Tello, S Madikeri, B Sharma, D Khalil… - ICASSP 2024-2024 IEEE …, 2024"],"snippet":"… The Language Model (LM) was trained with 34M utterances from publicly available English datasets including People’s Speech, Fisher, Switchboard, AMI, Wikitext103, and subsets of Common Crawl and Reddit datasets. The model was …","url":["https://ieeexplore.ieee.org/abstract/document/10445934/"]}
-{"year":"2024","title":"Probing and enhancing the reliance of Transformer models on poetic information","authors":["A Abdibayev - 2023"],"snippet":"Transformer models have achieved remarkable success in the widest variety of domains, spanning not just a multitude of tasks within natural language processing, but also those in computer vision, speech, and reinforcement learning. The key to …","url":["https://digitalcommons.dartmouth.edu/cgi/viewcontent.cgi?article=1228&context=dissertations"]}
-{"year":"2024","title":"Probing Critical Learning Dynamics of PLMs for Hate Speech Detection","authors":["S Masud, MA Khan, V Goyal, MS Akhtar, T Chakraborty - arXiv preprint arXiv …, 2024"],"snippet":"… Each variant is trained on a training corpus from Wikipedia, and Common-Crawl is curated and updated before the date associated with … that are pretrained on regular and latest Internet snapshots obtained via Common Crawl and Wikipedia …","url":["https://arxiv.org/html/2402.02144v1"]}
-{"year":"2024","title":"Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics","authors":["F Lin, D Altshuler, JB Pierrehumbert - arXiv preprint arXiv:2404.03301, 2024"],"snippet":"… 2018) trained on 600B Common Crawl data as a baseline. For the baseline, we add the representations of strongest and weakest adjectives on s as ⃗s, then also rank cos(⃗a, ⃗s) for each a to calculate MRR. Here, we only report the results for the …","url":["https://arxiv.org/html/2404.03301v1"]}
-{"year":"2024","title":"PRODIS-a speech database and a phoneme-based language model for the study of predictability effects in Polish","authors":["Z Malisz, J Foremski, M Kul - arXiv preprint arXiv:2404.10112, 2024"],"snippet":"We present a speech database and a phoneme-level language model of Polish. The database and model are designed for the analysis of prosodic and discourse factors and their impact on acoustic parameters in interaction with predictability effects. The …","url":["https://arxiv.org/pdf/2404.10112"]}
-{"year":"2024","title":"Prometheus' Digital Fire: The Civic Responsibilities of Artificial Intelligence","authors":["JM Garon - 2024"],"snippet":"[Prometheus], the noble son of Iapetus outwitted [Zeus] and stole the far-seen gleam of unwearying fire in a hollow fennel stalk. And Zeus who thunders on high was stung in spirit, and his dear heart was angered when he saw amongst men the far-seen …","url":["https://kb.osu.edu/bitstreams/b856efe9-db61-4bd8-876c-e1402662d292/download"]}
-{"year":"2024","title":"Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars","authors":["Z Wu, X Lin, Z Dai, W Hu, Y Shu, SK Ng, P Jaillet… - arXiv preprint arXiv …, 2024"],"snippet":"… [2], it is highly likely that GPT-3 has been trained on common benchmark datasets potentially contained in Common Crawl due to data contamination. Hence, further providing high-quality in-context exemplars could hardly improve the performance of …","url":["https://arxiv.org/pdf/2405.16122"]}
-{"year":"2024","title":"Prompting Change: ChatGPT's Impact on Digital Humanities Pedagogy–A Case Study in Art History","authors":["Q Guo - International Journal of Humanities and Arts …, 2024"],"snippet":"This article explores the transformative impact of ChatGPT, a Generative Pre-trained Transformers model, on humanities methodologies and its integration into a digital humanities (DH) course. The advent of ChatGPT enhances the capacity of people …","url":["https://www.euppublishing.com/doi/abs/10.3366/ijhac.2024.0321"]}
-{"year":"2024","title":"PROXYQA: An Alternative Framework for Evaluating Long-Form Text Generation with Large Language Models","authors":["H Tan, Z Guo, Z Shi, L Xu, Z Liu, X Li, Y Wang, L Shang… - arXiv preprint arXiv …, 2024"],"snippet":"… Nevertheless, scaling the context window during the pretraining phase remains a daunting task as the computational demands surge quadratically with the length of the attention span, and a majority of texts within standard corpora, like Common …","url":["https://arxiv.org/pdf/2401.15042"]}
-{"year":"2024","title":"PSILENCE: A Pseudonymization Tool for International Law","authors":["LA Cabrera-Diego, A Gheewala - Proceedings of the Workshop on Computational …, 2024"],"snippet":"Since the announcement of the GDPR, the pseudonymization of legal documents has become a high-priority task in many legal organizations. This means that for making public a document, it is necessary to redact the identity of certain entities …","url":["https://aclanthology.org/2024.caldpseudo-1.4.pdf"]}
-{"year":"2024","title":"PSQE: Personalized Semantic Query Expansion for user-centric query disambiguation","authors":["O Baumann, M Schoenfeld - 2024"],"snippet":"… Furthermore, they enable explainable intelligent systems, in that the results of querying the embedding for similar terms relate directly to the training set, rather than webscale collections such as Common Crawl. To our knowledge, our work is …","url":["https://www.researchsquare.com/article/rs-4178030/latest.pdf"]}
-{"year":"2024","title":"PSQS: Parallel Semantic Querying Service for Self-describing File Formats","authors":["C Niu, W Zhang, S Byna, Y Chen - 2023 IEEE International Conference on Big Data …, 2023"],"snippet":"… Typically, theseword representations are learned from a training dataset suchas the Common Crawl web corpus (840 billion tokens, 2.2million words) or Wikipedia 2014 (6 billion tokens, 400,000words). However, this assumption does not always …","url":["https://www.computer.org/csdl/proceedings-article/bigdata/2023/10386205/1TUOFedcdIQ"]}
-{"year":"2024","title":"Public perception of the Chinese president's visit to Saudi Arabia and the China–Arab Summit: sentiment analysis of Arabic tweets","authors":["AAM Hassan - Social Network Analysis and Mining, 2024"],"snippet":"In recent years, China and Saudi Arabia have had frequent exchanges in the political and economic fields, and public opinion evaluation is an essential aspect of evaluating the two countries’ current relations. This paper analyzes tweets in Arabic …","url":["https://link.springer.com/article/10.1007/s13278-023-01174-w"]}
-{"year":"2024","title":"PUBLIC-PRIVATE PARTNERSHIPS IN HEALTH SECTOR INNOVATION: LESSONS FROM AROUND THE WORLD","authors":["CC Ebulue, OR Ebulue, CS Ekesiobi - International Medical Science Research …, 2024"],"snippet":"Public-Private Partnerships (PPPs) have emerged as a crucial mechanism for fostering innovation in the health sector globally. This review encapsulates the lessons learned from diverse PPP models worldwide, highlighting their significance …","url":["https://www.fepbl.com/index.php/imsrj/article/view/1051/1274"]}
-{"year":"2024","title":"PyLoomer-The Automated Weaving of Python Text","authors":["A Sahani, RB Trivedi, T Singh, SR Goyal - 2024 2nd International Conference on …, 2024"],"snippet":"The introduction of attention mechanisms has evolved NLP methodologies, giving rise to Large Language Models (LLMs) that excel in various sequence-to-sequence tasks like translation, question-answering, summarization, intent, and entity …","url":["https://ieeexplore.ieee.org/abstract/document/10532945/"]}
-{"year":"2024","title":"Quality Does Matter: A Detailed Look at the Quality and Utility of Web-Mined Parallel Corpora","authors":["S Ranathunga, N de Silva, M Velayuthan, A Fernando… - arXiv preprint arXiv …, 2024"],"snippet":"… 2020) is a dataset created using 68 snapshots of CommonCrawl10. Document … of CommonCrawl. It contains around 4.5 billion parallel sentences across 576 language pairs. In building CCMatrix, it was assumed the aligned sentence could …","url":["https://arxiv.org/pdf/2402.07446"]}
-{"year":"2024","title":"Quantifying Gender Bias in Arabic Pre-trained Language Models","authors":["W Alrajhi, H Al-Khalifa, AM Al-Salman - IEEE Access, 2024"],"snippet":"The current renaissance in the development of Arabic Pre-trained Language models (APLMs) has yielded significant advancement across many fields. Nevertheless, no study has explored the dimensions of gender bias in these models. It is argued that …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10537164.pdf"]}
-{"year":"2024","title":"Quantifying Geospatial in the Common Crawl Corpus","authors":["I Ilyankou, M Wang, J Haworth, S Cavazzi - arXiv e-prints, 2024"],"snippet":"… Common Crawl corpus. However, the geospatial content within CC remains largely unexplored, impacting our understanding of LLMs' spatial reasoning. This paper investigates the prevalence of geospatial data in recent Common Crawl …","url":["https://ui.adsabs.harvard.edu/abs/2024arXiv240604952I/abstract"]}
-{"year":"2024","title":"Quantifying task-related gaze","authors":["K Walter, M Freeman, P Bex - Attention, Perception, & Psychophysics, 2024"],"snippet":"… For this study, we used the pretrained word vector Common Crawl (840B tokens, 2.2M vocab, cased, 300d vectors), which can be obtained at https://nlp.stanford.edu/projects/glove/. To utilize GloVe with the LabelMe images, we used it in conjunction with LASS …","url":["https://link.springer.com/article/10.3758/s13414-024-02883-w"]}
-{"year":"2024","title":"Quantifying the Importance of Data Alignment in Downstream Model Performance","authors":["K Chawla, A Sahai, M DePavia, S Sundar, B Miranda - 2024"],"snippet":"Contrary to the conventional emphasis on dataset size, we explore the role of data alignment---an often overlooked aspect of data quality---in training capable Large Language Models (LLMs). To do so, we use the Task2Vec-based alignment …","url":["https://openreview.net/pdf?id=pXTDfeBIPj"]}
-{"year":"2024","title":"Query Obfuscation for Information Retrieval through Differential Privacy","authors":["G Faggioli, N Ferro"],"snippet":"Protecting the privacy of a user querying an Information Retrieval (IR) system is of utmost importance. The problem is exacerbated when the IR system is not cooperative in satisfying the user’s privacy requirements. To address this …","url":["https://www.dei.unipd.it/~ferro/papers/2024/ECIR2024-FF.pdf"]}
-{"year":"2024","title":"Query of CC: Unearthing Large Scale Domain-Specific Knowledge from Public Corpora","authors":["Z Fei, Y Shao, L Li, Z Zeng, H Yan, X Qiu, D Lin - arXiv preprint arXiv:2401.14624, 2024"],"snippet":"… become increasingly rich, including the Pile, RedPajama, and Common Crawl. To ensure the diversity of data sources for retrieval, we constructed our retrieval corpus based on Common CrawlCommon Crawl is an open-source web crawler project …","url":["https://arxiv.org/pdf/2401.14624"]}
-{"year":"2024","title":"Query Performance Prediction using Relevance Judgments Generated by Large Language Models","authors":["C Meng, N Arabzadeh, A Askari, M Aliannejadi… - arXiv preprint arXiv …, 2024"],"snippet":"Query performance prediction (QPP) aims to estimate the retrieval quality of a search system for a query without human relevance judgments. Previous QPP methods typically return a single scalar value and do not require the predicted …","url":["https://arxiv.org/html/2404.01012v1"]}
-{"year":"2024","title":"QuRating: Selecting High-Quality Data for Training Language Models","authors":["A Wettig, A Gupta, S Malik, D Chen - arXiv preprint arXiv:2402.09739, 2024"],"snippet":"… We visualize the distributions for the cluster in CommonCrawl and C4 in Figure 7 in the appendix. They are similarly encouraging, eg, the clusters associated with cells, protein, gene and energy, climate, species are rated highly on required …","url":["https://arxiv.org/pdf/2402.09739"]}
-{"year":"2024","title":"RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors","authors":["L Dugan, A Hwang, F Trhlik, JM Ludan, A Zhu, H Xu… - arXiv preprint arXiv …, 2024"],"snippet":"… The model was allegedly trained with a variety of data including the Common Crawl (fil- … Released on July 18th 2023, LLaMA 2 is the successor to the original LLaMA model which was trained on webpages from CommonCrawl, multilingual …","url":["https://arxiv.org/pdf/2405.07940"]}
-{"year":"2024","title":"Rapidly Developing High-quality Instruction Data and Evaluation Benchmark for Large Language Models with Minimal Human Effort: A Case Study on Japanese","authors":["Y Sun, Z Wan, N Ueda, S Yahata, F Cheng, C Chu… - arXiv preprint arXiv …, 2024"],"snippet":"The creation of instruction data and evaluation benchmarks for serving Large language models often involves enormous human annotation. This issue becomes particularly pronounced when rapidly developing such resources for a non-English …","url":["https://arxiv.org/pdf/2403.03690"]}
-{"year":"2024","title":"Real-time phishing detection using deep learning methods by extensions","authors":["DM Linh, HD Hung, HM Chau, QS Vu, TN Tran - International Journal of Electrical …, 2024"],"snippet":"… [2] used two algorithms, random forest (RF) and long short-term memory (LSTM), to evaluate the PhishTank and Common Crawl datasets, achieving accuracies of 93.5% and 98.7%, respectively. Similarly, Kumar et al. [3] evaluated using the …","url":["https://www.researchgate.net/profile/Dam-Linh-4/publication/379571132_Real-time_phishing_detection_using_deep_learning_methods_by_extensions/links/660f6efc390c214cfd361601/Real-time-phishing-detection-using-deep-learning-methods-by-extensions.pdf"]}
-{"year":"2024","title":"Real-World Robot Applications of Foundation Models: A Review","authors":["K Kawaharazuka, T Matsushima, A Gambardella… - arXiv preprint arXiv …, 2024"],"snippet":"… In terms of the data, the datasets for training LLMs are Internet-scale; for example, the pre-training of GPT-3 [47] uses CommonCrawl covering Internet data from years 2016 to 2019, which amounts to 45TB of compressed plain text and 410 billion …","url":["https://arxiv.org/pdf/2402.05741"]}
-{"year":"2024","title":"Reasoning for fact verification using language models","authors":["M Kanaani - 2024"],"snippet":"In response to the proliferation of misinformation on social media platforms, this thesis introduces the Triple-R framework (Retriever, Ranker, Reasoner) to enhance fact-checking by leveraging the Web for evidence retrieval and generating …","url":["https://unbscholar.lib.unb.ca/bitstreams/4202b462-0a7a-47d2-b52e-927c6384ae44/download"]}
-{"year":"2024","title":"Recent Advances in Large Language Models for Healthcare","authors":["K Nassiri, MA Akhloufi - BioMedInformatics, 2024"],"snippet":"Recent advances in the field of large language models (LLMs) underline their high potential for applications in a variety of sectors. Their use in healthcare, in particular, holds out promising prospects for improving medical practices. As we highlight in …","url":["https://www.mdpi.com/2673-7426/4/2/62"]}
-{"year":"2024","title":"Recent advances in text embedding: A Comprehensive Review of Top-Performing Methods on the MTEB Benchmark","authors":["CAO Hongliu","H Cao - arXiv preprint arXiv:2406.01607, 2024"],"snippet":"… data: (post, comment) pairs from Reddit3, (question, upvoted answer) pairs from Stackexchange4, (entity name + section title, passage) pairs from English Wikipedia, (title, abstract) and citation pairs from Scientific papers [53], and (title, passage) pairs …","url":["https://arxiv.org/pdf/2406.01607","https://www.researchgate.net/profile/Hongliu-Cao/publication/380127334_Recent_advances_in_text_embedding_A_Comprehensive_Review_of_Top-Performing_Methods_on_the_MTEB_Benchmark/links/662becdf06ea3d0b740fe4c9/Recent-advances-in-text-embedding-A-Comprehensive-Review-of-Top-Performing-Methods-on-the-MTEB-Benchmark.pdf"]}
-{"year":"2024","title":"Recognizing Textual Inference in Mongolian Bar Exam Questions","authors":["G Khaltarkhuu, B Batjargal, A Maeda - Applied Sciences, 2024"],"snippet":"This paper examines how to apply deep learning techniques to Mongolian bar exam questions. Several approaches that utilize eight different fine-tuned transformer models were demonstrated for recognizing textual inference in Mongolian bar exam …","url":["https://www.mdpi.com/2076-3417/14/3/1073"]}
-{"year":"2024","title":"Referring expression segmentation: from conventional to generalized","authors":["C Liu - 2024"],"snippet":"In recent years, many remarkable achievements have been made in the field of deep machine learning in various data modalities, such as image processing and natural language comprehension. Based on the good performance of deep neural …","url":["https://dr.ntu.edu.sg/bitstream/10356/175477/2/Thesis_Liu%20Chang_submit_compress.pdf"]}
-{"year":"2024","title":"Reliability Estimation of News Media Sources: Birds of a Feather Flock Together","authors":["S Burdisso, D Sánchez-Cortés, E Villatoro-Tello…"],"snippet":"Evaluating the reliability of news sources is a routine task for journalists and organizations committed to acquiring and disseminating accurate information. Recent research has shown that predicting sources’ reliability represents an …","url":["https://publications.idiap.ch/attachments/papers/2024/Burdisso_NAACL_2024.pdf"]}
-{"year":"2024","title":"Reliability of large language models in managing odontogenic sinusitis clinical scenarios: a preliminary multidisciplinary evaluation","authors":["AM Saibene, F Allevi, C Calvo-Henriquez, A Maniaci… - European Archives of Oto …, 2024"],"snippet":"Purpose This study aimed to evaluate the utility of large language model (LLM) artificial intelligence tools, Chat Generative Pre-Trained Transformer (ChatGPT) versions 3.5 and 4, in managing complex otolaryngological clinical scenarios …","url":["https://link.springer.com/article/10.1007/s00405-023-08372-4"]}
-{"year":"2024","title":"ReLU $^ 2$ Wins: Discovering Efficient Activation Functions for Sparse LLMs","authors":["Z Zhang, Y Song, G Yu, X Han, Y Lin, C Xiao, C Song… - arXiv preprint arXiv …, 2024"],"snippet":"… For the corpus used for calculating the sparsity statistics, we a mixture of texts from Wikipedia, Pile, and Common Crawl. The total number of tokens is about 217. Since we need to store the activation values of all neurons, we only use a part of the …","url":["https://arxiv.org/pdf/2402.03804"]}
-{"year":"2024","title":"Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling","authors":["P Maini, S Seto, H Bai, D Grangier, Y Zhang, N Jaitly - arXiv preprint arXiv …, 2024"],"snippet":"… There are different versions of CommonCrawl data and our selection of C4 for pretraining is driven by driven by its size and quality. … The dataset is also derived from the CommonCrawl, however has a more stringent filtering process. Our …","url":["https://arxiv.org/pdf/2401.16380"]}
-{"year":"2024","title":"Representation Learning for Hierarchical Classification of Entity Titles","authors":["E Chistova - Proceedings of the 6th International Conference on …, 2023"],"snippet":"We present a method for effective title encoding for hierarchical classification in a large taxonomy. The method enables taxonomy-aware encoding in pre-trained text encoders, such as fastText and BERT, which are additionally fine-tuned for the …","url":["https://aclanthology.org/2023.icnlsp-1.4.pdf"]}
-{"year":"2024","title":"Representing Online Handwriting for Recognition in Large Vision-Language Models","authors":["A Fadeeva, P Schlattner, A Maksai, M Collier… - arXiv preprint arXiv …, 2024"],"snippet":"The adoption of tablets with touchscreens and styluses is increasing, and a key feature is converting handwriting to text, enabling search, indexing, and AI assistance. Meanwhile, vision-language models (VLMs) are now the go-to solution …","url":["https://arxiv.org/pdf/2402.15307"]}
-{"year":"2024","title":"Representing relational knowledge with language models","authors":["A Ushio - 2024"],"snippet":"Relational knowledge is the ability to recognize the relationship between instances, and it has an important role in human understanding a concept or commonsense reasoning. We, humans, structure our knowledge by understanding individual …","url":["https://orca.cardiff.ac.uk/id/eprint/168141/1/thesis_clean.pdf"]}
-{"year":"2024","title":"Research and Application of Large Model-Based Intelligent Customer Service System","authors":["Y Xi - International Journal of Emerging Technologies and …, 2024"],"snippet":"With the rapid development of artificial intelligence technology, intelligent customer service systems have been widely used. This paper addresses the limitations of traditional intelligent customer service systems, such as limited language …","url":["https://www.ijetaa.com/article/download/114/15"]}
-{"year":"2024","title":"Research on cross-lingual multi-label patent classification based on pre-trained model","authors":["Y Lu, L Chen, X Tong, Y Peng, H Zhu - Scientometrics, 2024"],"snippet":"Patent classification is an important part of the patent examination and management process. Using efficient and accurate automatic patent classification can significantly improve patent retrieval performance. Current monolingual patent classification …","url":["https://link.springer.com/article/10.1007/s11192-024-05024-0"]}
-{"year":"2024","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","authors":["J Baek, SK Jauhar, S Cucerzan, SJ Hwang - arXiv preprint arXiv:2404.07738, 2024"],"snippet":"Scientific Research, vital for improving human life, is hindered by its inherent complexity, slow pace, and the need for specialized experts. To enhance its productivity, we propose a ResearchAgent, a large language model-powered …","url":["https://arxiv.org/pdf/2404.07738"]}
-{"year":"2024","title":"Retrieval-Based Grammatical Error Correction","authors":["JR Vasselli - 2024"],"snippet":"… a cleaned version of the common crawl to produce nearly 200 million ungrammatical sentences with a realistic distribution of errors. … CWEB consists of randomly selected texts from the first 18 dumps of the Common Crawl, which include …","url":["https://naist.repo.nii.ac.jp/record/2000298/files/R018806.pdf"]}
-{"year":"2024","title":"Revisión de modelos de lenguaje y aplicación a la automatización de tareas de oficina en empresas industriales","authors":["J Zamora Fraguas - 2023"],"snippet":"This project focuses on the evaluation and application of Large Language Models (LLMs) in natural language processing (NLP). The technical properties, advantages, and disadvantages of LLMs are analysed, highlighting their wide use in machine …","url":["https://repositorio.comillas.edu/xmlui/bitstream/handle/11531/78033/TFM_ZamoraFraguas%2CJacobo%20.pdf?sequence=1"]}
-{"year":"2024","title":"Revisiting Adversarial Training at Scale","authors":["Z Wang, X Li, H Zhu, C Xie - arXiv preprint arXiv:2401.04727, 2024"],"snippet":"… DataComp-1B is a more recent dataset with about 1.3B samples filtered from a candidate pool of 12.8B image-text pairs from Common Crawl, which has been recorded to yield superior performance for contrastive training. To summarize, our …","url":["https://arxiv.org/pdf/2401.04727"]}
-{"year":"2024","title":"Revisiting Joke Comprehension with Surprisal and Contextual Similarity: Implication from N400 and P600 Components","authors":["H Xu, M Nakanishi, S Coulson - Proceedings of the Annual Meeting of the Cognitive …, 2024"],"snippet":"… Specifically, we used the version with a 2.2 million word vocabulary and 300-dimensional vectors trained on 840 billion tokens from the Common Crawl corpus. The contextual vector of all the words preceding the final word in each sentence was computed by …","url":["https://escholarship.org/content/qt01n9j76q/qt01n9j76q_noSplash_25244bf314716cf3a964d313018efad3.pdf"]}
-{"year":"2024","title":"Revisiting Pre-training of Embedding Layers in Transformer-based Neural Machine Translation","authors":["M Neishi, N Yoshinaga - Journal of Natural Language Processing, 2024"],"snippet":"Recent trends in the pre-training and fine-tuning paradigm have made significant advances in several natural language processing tasks, including machine translation (MT), particularly for low-resource situations. However, it is reported that …","url":["https://www.jstage.jst.go.jp/article/jnlp/31/2/31_534/_pdf"]}
-{"year":"2024","title":"Rho-1: Not All Tokens Are What You Need","authors":["Z Lin, Z Gou, Y Gong, X Liu, Y Shen, R Xu, C Lin… - arXiv preprint arXiv …, 2024"],"snippet":"Previous language model pre-training methods have uniformly applied a next-token prediction loss to all training tokens. Challenging this norm, we posit that \"Not all tokens in a corpus are equally important for language model training\". Our initial …","url":["https://arxiv.org/pdf/2404.07965"]}
-{"year":"2024","title":"RoBERTaNET: Enhanced RoBERTa Transformer Based Model for Cyberbullying Detection with GloVe Features","authors":["F Alrowais, AA Jamjoom, H Karamti, M Umer, S Alsubai… - IEEE Access, 2024"],"snippet":"… 3) FastText FastText is a word illustration library, that encompasses 300dimensional 2 million common crawl words, resulting in 600 billion word vectors [31]. Particularly, hand-crafted ngrams are used as features alongside solo words. Its straightforward …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10495045.pdf"]}
-{"year":"2024","title":"Robust Neural Machine Translation for Abugidas by Glyph Perturbation","authors":["H Kaing, C Ding, H Tanaka, M Utiyama - Proceedings of the 18th Conference of the …, 2024"],"snippet":"Neural machine translation (NMT) systems are vulnerable when trained on limited data. This is a common scenario in low-resource tasks in the real world. To increase robustness, a solution is to intently add realistic noise in the training phase. Noise …","url":["https://aclanthology.org/2024.eacl-short.27.pdf"]}
-{"year":"2024","title":"RoCode: A Dataset for Measuring Code Intelligence from Problem Definitions in Romanian","authors":["A Cosma, B Iordache, P Rosso - arXiv preprint arXiv:2402.13222, 2024"],"snippet":"… Even if code is present in the dataset (from Common Crawl), it is described in English and comments and documentation are in English. The same argument can be made for mathematics and other scientific disciplines. A large, highly curated and …","url":["https://arxiv.org/pdf/2402.13222"]}
-{"year":"2024","title":"ROME: Memorization Insights from Text, Probability and Hidden State in Large Language Models","authors":["B Li, Q Zhao, L Wen - arXiv preprint arXiv:2403.00510, 2024"],"snippet":"Probing the memorization of large language models holds significant importance. Previous works have established metrics for quantifying memorization, explored various influencing factors, such as data duplication, model size, and prompt length …","url":["https://arxiv.org/pdf/2403.00510"]}
-{"year":"2024","title":"RU22Fact: Optimizing Evidence for Multilingual Explainable Fact-Checking on Russia-Ukraine Conflict","authors":["Y Zeng, X Ding, Y Zhao, X Li, J Zhang, C Yao, T Liu… - arXiv preprint arXiv …, 2024"],"snippet":"Fact-checking is the task of verifying the factuality of a given claim by examining the available evidence. High-quality evidence plays a vital role in enhancing fact-checking systems and facilitating the generation of explanations that are understandable to …","url":["https://arxiv.org/html/2403.16662v1"]}
-{"year":"2024","title":"RuBia: A Russian Language Bias Detection Dataset","authors":["V Grigoreva, A Ivanova, I Alimova, E Artemova - arXiv preprint arXiv:2403.17553, 2024"],"snippet":"Warning: this work contains upsetting or disturbing content. Large language models (LLMs) tend to learn the social and cultural biases present in the raw pre-training data. To test if an LLM's behavior is fair, functional datasets are employed, and due to their …","url":["https://arxiv.org/pdf/2403.17553"]}
-{"year":"2024","title":"Sailor: Open Language Models for South-East Asia","authors":["L Dou, Q Liu, G Zeng, J Guo, J Zhou, W Lu, M Lin - arXiv preprint arXiv:2404.03608, 2024"],"snippet":"We present Sailor, a family of open language models ranging from 0.5B to 7B parameters, tailored for South-East Asian (SEA) languages. These models are continually pre-trained from Qwen1.5, a great language model for multilingual use …","url":["https://arxiv.org/pdf/2404.03608"]}
-{"year":"2024","title":"Sampling-based Pseudo-Likelihood for Membership Inference Attacks","authors":["M Kaneko, Y Ma, Y Wata, N Okazaki - arXiv preprint arXiv:2404.11262, 2024"],"snippet":"… 2023): LLaMA-2 employs English CommonCrawl, C4, Github, Wikipedia, Books, ArXiv, and StackExchange as pre-training datasets. … or filtered to contain predominantly English text, but a small amount of non-English data is still present …","url":["https://arxiv.org/pdf/2404.11262"]}
-{"year":"2024","title":"Scaffold-BPE: Enhancing Byte Pair Encoding with Simple and Effective Scaffold Token Removal","authors":["H Lian, Y Xiong, J Niu, S Mo, Z Su, Z Lin, P Liu, H Chen… - arXiv preprint arXiv …, 2024"],"snippet":"… The Pile is composed of 22 diverse and high-quality datasets, the models trained on which significantly outperform both raw and filtered Common Crawl [10] models. The data distribution for our model training is identical to those described in the …","url":["https://arxiv.org/pdf/2404.17808"]}
-{"year":"2024","title":"Scalable Distributed String Sorting","authors":["F Kurpicz, P Mehnert, P Sanders, M Schimek - arXiv preprint arXiv:2404.16517, 2024"],"snippet":"… While different sampling and group assignment techniques may improve character balance, the CommonCrawl data set contains many duplicated strings (eg, standard legal disclaimers) which are always assigned to a single PE and cannot be …","url":["https://arxiv.org/pdf/2404.16517"]}
-{"year":"2024","title":"Scalable Pre-training of Large Autoregressive Image Models","authors":["A El-Nouby, M Klein, S Zhai, MA Bautista, A Toshev… - arXiv preprint arXiv …, 2024"],"snippet":"This paper introduces AIM, a collection of vision models pre-trained with an autoregressive objective. These models are inspired by their textual counterparts, ie, Large Language Models (LLMs), and exhibit similar scaling properties. Specifically …","url":["https://arxiv.org/pdf/2401.08541"]}
-{"year":"2024","title":"Scalable Range Search over Temporal and Numerical Expressions","authors":["V Ohr, D Gupta - The 10th ACM SIGIR/The 14th International …"],"snippet":"… a subset of Common Crawl amounting to … Common Crawl, published as C4 [30]. This document collection consists of approximately 13.81 million documents. The fourth and final document collection we use is the entire C4-En corpus derived from …","url":["https://openreview.net/pdf?id=84vTskBRPU"]}
-{"year":"2024","title":"Scaling Laws for Data Filtering--Data Curation cannot be Compute Agnostic","authors":["S Goyal, P Maini, ZC Lipton, A Raghunathan, JZ Kolter - arXiv preprint arXiv …, 2024"],"snippet":"… As we train for longer, the accuracy gains using the LAION-filtering subset that filters the common crawl to 10% of its initial size plateau. Surprisingly, even no-filtering of the common crawl is better than the popular LAION-filtering after seeing more …","url":["https://arxiv.org/pdf/2404.07177"]}
-{"year":"2024","title":"Scaling neural machine translation to 200 languages","authors":["Nature, 2024"],"snippet":"… To overcome this problem, we created training datasets through global bitext mining in publicly available web content (drawn from repositories such as CommonCrawl). The underlying idea of our bitext mining approach is first to learn a …","url":["https://www.nature.com/articles/s41586-024-07335-x"]}
-{"year":"2024","title":"sCambiaMenti at ACTI: Ensemble model with majority voting for Automatic Conspiracy Detection","authors":["S Bianco, D Salusso - EVALITA Proceedings of the Eighth Evaluation …, 2024"],"snippet":"In this paper we describe the methodology that we have implemented to solve the subtask A of the Automatic Conspiracy Detection (ACTI) task (EVALITA 2023). We have developed different classifiers and then used a majority voting approach to …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=ZLfuEAAAQBAJ&oi=fnd&pg=PA271&dq=commoncrawl&ots=BBnDdqOBAj&sig=Hn5VYj3sI8L2xkD1qqoIQsmOQOw"]}
-{"year":"2024","title":"SchemaPile: A Large Collection of Relational Database Schemas","authors":["T Döhmen, R Geacu, M Hulsebos, S Schelter - … of the ACM on Management of Data, 2024"],"snippet":"… such as the aforementioned code dataset The Stack [25] or web crawls such as CommonCrawl [12] as alternative data sources. Furthermore, enterprises could adapt our data … Common Crawl – a free, open repository of web crawl data that …","url":["https://dl.acm.org/doi/pdf/10.1145/3654975"]}
-{"year":"2024","title":"Scoping: Towards Streamlined Entity Collections for Multi-Sourced Entity Resolution with Self-Supervised Agents","authors":["L Traeger, A Behrend, G Karabatis"],"snippet":"Linking multiple entities to a real-world object is a time-consuming and error-prone task. Entity Resolution (ER) includes techniques for vectorizing entities (signature), grouping similar entities into partitions (blocking), and matching entity pairs based …","url":["https://www.scitepress.org/Papers/2024/126075/126075.pdf"]}
-{"year":"2024","title":"SD-WEAT: Towards Robustly Measuring Bias in Input Embeddings","authors":["M Gray, L Wu - International Conference on Human-Computer …, 2024"],"snippet":"… 300d” from the Stanford NLP Group [9], which was trained on 840 billion tokens from Common Crawl data and generates 300-dimension vectors. Moreover, other input embedding methods, including those of BERT [10, 11], SciBERT [12, 13], and …","url":["https://link.springer.com/chapter/10.1007/978-3-031-62110-9_5"]}
-{"year":"2024","title":"Second Language (Arabic) Acquisition of LLMs via Progressive Vocabulary Expansion","authors":["J Zhu, H Hunag, Z Lin, J Liang, Z Tang, K Almubarak…"],"snippet":"This paper addresses the critical need for democratizing large language models (LLM) in the Arab world, a region that has seen slower progress in developing models comparable to state-of-the-art offerings like GPT-4 or ChatGPT 3.5, due to a …","url":["https://huggingface.co/FreedomIntelligence/AceGPT-v1.5-13B-Chat/resolve/main/Second_Language_(Arabic)_Acquisition_of_LLMs_via_Progressive_Vocabulary_Expansion.pdf"]}
-{"year":"2024","title":"Secret Collusion Among Generative AI Agents","authors":["SR Motwani, M Baranchuk, M Strohmeier, V Bolina… - arXiv preprint arXiv …, 2024"],"snippet":"Recent capability increases in large language models (LLMs) open up applications in which teams of communicating generative AI agents solve joint tasks. This poses privacy and security challenges concerning the unauthorised sharing of information …","url":["https://arxiv.org/pdf/2402.07510"]}
-{"year":"2024","title":"SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agents","authors":["K Cheng, Q Sun, Y Chu, F Xu, Y Li, J Zhang, Z Wu - arXiv preprint arXiv:2401.10935, 2024"],"snippet":"… We collected approximately 300k web pages from the latest Common Crawl repository 2 to serve as our training data for web UI. For each webpage, we collect two types of elements from the HTML code: (1) elements that display visible text …","url":["https://arxiv.org/pdf/2401.10935"]}
-{"year":"2024","title":"Seeds of Stereotypes: A Large-Scale Textual Analysis of Race and Gender Associations with Diseases in Online Sources","authors":["L Hyldig Hansen, N Andersen, J Gallifant, LG McCoy… - arXiv e-prints, 2024","LH Hansen, N Andersen, J Gallifant, LG McCoy… - arXiv preprint arXiv …, 2024"],"snippet":"… Methods We conducted a large-scale textual analysis using a dataset comprising diverse web sources, including Arxiv, Wikipedia, and Common Crawl. The study analyzed the context in which various diseases are discussed alongside markers of …","url":["https://arxiv.org/pdf/2405.05049","https://ui.adsabs.harvard.edu/abs/2024arXiv240505049H/abstract"]}
-{"year":"2024","title":"Selecting Large Language Model to Fine-tune via Rectified Scaling Law","authors":["H Lin, B Huang, H Ye, Q Chen, Z Wang, S Li, J Ma… - arXiv preprint arXiv …, 2024"],"snippet":"The ever-growing ecosystem of LLMs has posed a challenge in selecting the most appropriate pre-trained model to fine-tune amidst a sea of options. Given constrained resources, fine-tuning all models and making selections afterward is …","url":["https://arxiv.org/pdf/2402.02314"]}
-{"year":"2024","title":"Selective Metric Differential Privacy for Language Models","authors":["A Maratkhan - 2023"],"snippet":"… We used a pre-trained GloVe model trained on Common Crawl data with 840B tokens with a 2.2M vocabulary size for the privatization mechanism. We chose to utilize this model because it has a large vocabulary and is case-sensitive. Since GPT-2 …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/51067/Maratkhan_washington_0250O_26461.pdf?sequence=1"]}
-{"year":"2024","title":"Self-Augmented In-Context Learning for Unsupervised Word Translation","authors":["Y Li, A Korhonen, I Vulić - arXiv preprint arXiv:2402.10024, 2024"],"snippet":"… 2017): the version pretrained on Wikipedia7 is used for XLING and the version pretrained with Wikipedia plus Common Crawl8 is used for PanLex-BLI, as recommended by XLING and PanLex-BLI, respectively. The same WEs are used for …","url":["https://arxiv.org/pdf/2402.10024"]}
-{"year":"2024","title":"Semantic-guided spatio-temporal attention for few-shot action recognition","authors":["J Wang, B Liu - Applied Intelligence, 2024"],"snippet":"… We utilize GloVe [49] to extract text embeddings for action labels, which is pre-trained on Common Crawl dataset of 840B tokens. For labels with multiple words, we average the embeddings of all their words. Finally, one action label is represented …","url":["https://link.springer.com/article/10.1007/s10489-024-05294-4"]}
-{"year":"2024","title":"Semantically Enriched Cross-Lingual Sentence Embeddings for Crisis-related Social Media Texts","authors":["R Lamsal, MR Read, S Karunasekera - arXiv preprint arXiv:2403.16614, 2024"],"snippet":"Tasks such as semantic search and clustering on crisis-related social media texts enhance our comprehension of crisis discourse, aiding decision-making and targeted interventions. Pre-trained language models have advanced performance in …","url":["https://arxiv.org/pdf/2403.16614"]}
-{"year":"2024","title":"SeNSe: embedding alignment via semantic anchors selection","authors":["L Malandri, F Mercorio, M Mezzanzanica, F Pallucchini - International Journal of Data …, 2024"],"snippet":"Word embeddings have proven extremely useful across many NLP applications in recent years. Several key linguistic tasks, such as machine translation and transfer learning, require comparing distributed representations of words belonging to …","url":["https://link.springer.com/article/10.1007/s41060-024-00522-z"]}
-{"year":"2024","title":"SENTA: Sentence Simplification System for Slovene","authors":["A Žagar, M Klemen, M Robnik-Šikonja, I Kosem - Proceedings of the 2024 Joint …, 2024"],"snippet":"… It uses sentence-level paraphrase data obtained by mining paraphrases from Common Crawl in combination with controllable generation mechanisms to adjust the length and lexical complexity of a simplified candidate. …","url":["https://aclanthology.org/2024.lrec-main.1279.pdf"]}
-{"year":"2024","title":"Sentence Embeddings for Massively Multilingual Speech and Text Processing","authors":["PA Duquenne - 2024"],"snippet":"… CommonCrawl raw text data corresponds to partial snapshots of the internet totalling terabytes of text data extracted from web pages in many languages. The authors used the open-source FAISS library (Johnson et al. 2019) in order to …","url":["https://theses.hal.science/tel-04573934/document"]}
-{"year":"2024","title":"Sentence Level Analysis Model for Phishing Detection Using KNN","authors":["L Sawe, J Gikandi, J Kamau, D Njuguna"],"snippet":"Phishing emails have experienced a rapid surge in cyber threats globally, especially following the emergence of the COVID-19 pandemic. This form of attack has led to substantial financial losses for numerous organizations. Although various models …","url":["https://www.researchgate.net/profile/Lindah-Sawe/publication/377242106_Sentence_Level_Analysis_Model_for_Phishing_Detection_Using_KNN/links/659d3bd62468df72d305fd90/Sentence-Level-Analysis-Model-for-Phishing-Detection-Using-KNN.pdf"]}
-{"year":"2024","title":"Sentiment analysis on the issue of COVID-19 vaccination using LSTM and fasttext","authors":["WN Dewani, Y Azhar, N Hayatin - AIP Conference Proceedings, 2024"],"snippet":"… The fasttext model is the result of a word vector previously trained from Common Crawl and Indonesian language Wikipedia data from Facebook. This model is trained using the Continuous Bag of Words (CBOW) method with position weight [13] …","url":["https://pubs.aip.org/aip/acp/article/2927/1/060017/3279268"]}
-{"year":"2024","title":"SETEM: Self-ensemble training with Pre-trained Language Models for Entity Matching","authors":["H Ding, C Dai, Y Wu, W Ma, H Zhou - Knowledge-Based Systems, 2024"],"snippet":"… This benchmark is constructed by extracting schema.org data from the Common Crawl and using the following attributes: brand, title, currency and price. The WDC Products benchmark consists of overall nine training, nine validation and nine test …","url":["https://www.sciencedirect.com/science/article/pii/S0950705124003435"]}
-{"year":"2024","title":"Shapley Values-Powered Framework for Fair Reward Split in Content Produced by GenAI","authors":["A Glinsky, A Sokolsky - arXiv preprint arXiv:2403.09700, 2024"],"snippet":"… DATACOMP introduces a new candidate pool of 12.8 billion image-text pairs sourced from Common Crawl, which is broader than the collection in LAION-5B. This extensive pool offers a more diverse base for dataset creation. Unlike LAION-5B …","url":["https://arxiv.org/pdf/2403.09700"]}
-{"year":"2024","title":"SIGN LANGUAGE RECOGNITION OF WORDS AND SENTENCE PREDICTION USING LSTM AND NLP","authors":["R GAIKWAD, L ADMUTHE - Journal of Theoretical and Applied Information …, 2024"],"snippet":"… The dataset used for the training of the T5 model is the C4 dataset called as Colossal Clean Crawled Corpus which is collected from Common Crawl, a publicly available web archive. It consists of 750 GB clean English text scraped from the …","url":["http://www.jatit.org/volumes/Vol102No4/20Vol102No4.pdf"]}
-{"year":"2024","title":"Silencing the Risk, Not the Whistle: A Semi-automated Text Sanitization Tool for Mitigating the Risk of Whistleblower Re-Identification","authors":["D Staufer, F Pallas, B Berendt - arXiv preprint arXiv:2405.01097, 2024"],"snippet":"Whistleblowing is essential for ensuring transparency and accountability in both public and private sectors. However, (potential) whistleblowers often fear or face retaliation, even when reporting anonymously. The specific content of their …","url":["https://arxiv.org/pdf/2405.01097"]}
-{"year":"2024","title":"SimLESS: A Secure Deduplication System over Similar Data in Cloud Media Sharing","authors":["M Song, Z Hua, Y Zheng, T Xiang, X Jia - IEEE Transactions on Information Forensics …, 2024"],"snippet":"With the growing popularity of cloud computing, sharing media data through the cloud has become a common practice. Due to high information redundancy, media data take up a significant amount of storage space. Moreover, similar media data …","url":["https://ieeexplore.ieee.org/abstract/document/10480626/"]}
-{"year":"2024","title":"Simple and Scalable Strategies to Continually Pre-train Large Language Models","authors":["A Ibrahim, B Thérien, K Gupta, ML Richter, Q Anthony… - arXiv preprint arXiv …, 2024"],"snippet":"… We then generate a fixed token-length response for each of the models trained German Common Crawl. As a baseline, we also evaluate … of German-language outputs from the models trained on German Common Crawl when compared to the …","url":["https://arxiv.org/pdf/2403.08763"]}
-{"year":"2024","title":"Simulating Policy Impacts: Developing a Generative Scenario Writing Method to Evaluate the Perceived Effects of Regulation","authors":["J Barnett, K Kieslich, N Diakopoulos - arXiv preprint arXiv:2405.09679, 2024"],"snippet":"… They utilize proprietary datasets as well as opensource web data such as the continuously growing Common Crawl, which contains more than 250 billion pages of over a decade’s worth of textual content. While these models primarily learn how …","url":["https://arxiv.org/pdf/2405.09679"]}
-{"year":"2024","title":"Slight Corruption in Pre-training Data Makes Better Diffusion Models","authors":["H Chen, Y Han, D Misra, X Li, K Hu, D Zou… - arXiv preprint arXiv …, 2024"],"snippet":"… For example, Stable Diffusion [26] was pre-trained on LAION-2B [17], which contains billion-scale image-text pairs collected from Common Crawl [27]. Despite the heavy filtering mechanisms used in collecting pre-training datasets [17, 28], they …","url":["https://arxiv.org/pdf/2405.20494"]}
-{"year":"2024","title":"Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMs","authors":["J Tan, Z Dou, Y Zhu, P Guo, K Fang, JR Wen - arXiv preprint arXiv:2402.12052, 2024"],"snippet":"The integration of large language models (LLMs) and search engines represents a significant evolution in knowledge acquisition methodologies. However, determining the knowledge that an LLM already possesses and the knowledge that requires the …","url":["https://arxiv.org/pdf/2402.12052"]}
-{"year":"2024","title":"Smaller Language Models are Better Zero-shot Machine-Generated Text Detectors","authors":["N Mireshghallah, J Mattern, S Gao, R Shokri… - Proceedings of the 18th …, 2024"],"snippet":"As large language models are becoming more embedded in different user-facing services, it is important to be able to distinguish between human-written and machine-generated text to verify the authenticity of news articles, product reviews, etc. Thus, in this paper …","url":["https://aclanthology.org/2024.eacl-short.25.pdf"]}
-{"year":"2024","title":"Smart Automation Using LLM","authors":["P Ethape, R Kane, G Gadekar, S Chimane - International Research Journal of …, 2023"],"snippet":"… Such large-scale models can ingest massive amounts of data, often from the internet, but also from sources such as the Common Crawl, which comprises more than 50 billion web pages, and Wikipedia, which has approximately 57 million pages. …","url":["https://search.proquest.com/openview/1c46974bac0d8d641a04a889011c8299/1?pq-origsite=gscholar&cbl=5314840"]}
-{"year":"2024","title":"Smart Bilingual Focused Crawling of Parallel Documents","authors":["C García-Romero, M Esplà-Gomis, F Sánchez-Martínez - arXiv preprint arXiv …, 2024"],"snippet":"Crawling parallel texts $\\unicode{x2014}$texts that are mutual translations$\\unicode{x2014}$ from the Internet is usually done following a brute-force approach: documents are massively downloaded in an unguided process, and only a fraction of them end up …","url":["https://arxiv.org/pdf/2405.14779"]}
-{"year":"2024","title":"Smoky Quartz: A Transparent Bilingual Large Language Model","authors":["Q Huang, C Zhang, M Tao, J Lin, S Huang, Y Feng"],"snippet":"Recent advancements in large-scale models have been remarkable; however, a significant challenge persists in their lack of transparency, particularly concerning the training data utilized. This obscurity raises concerns about potential data leaks …","url":["https://andrewzhe.github.io/figs/A_Transparent_Binlingual_LLM.pdf"]}
-{"year":"2024","title":"SMW Cloud: A Corpus of Domain-Specific Knowledge Graphs from Semantic MediaWikis","authors":["D Dobriy, M Beno, A Polleres"],"snippet":"Semantic wikis have become an increasingly popular means of collaboratively managing Knowledge Graphs. They are powered by platforms such as Semantic MediaWiki and Wikibase, both of which enable MediaWiki to store and publish …","url":["https://2024.eswc-conferences.org/wp-content/uploads/2024/04/146640477.pdf"]}
-{"year":"2024","title":"Social Evolution of Published Text and The Emergence of Artificial Intelligence Through Large Language Models and The Problem of Toxicity and Bias","authors":["A Khan, P Saravanan, SK Venkatesan - arXiv preprint arXiv:2402.07166, 2024"],"snippet":"We provide a birds eye view of the rapid developments in AI and Deep Learning that has led to the path-breaking emergence of AI in Large Language Models. The aim of this study is to place all these developments in a pragmatic broader historical social …","url":["https://arxiv.org/pdf/2402.07166"]}
-{"year":"2024","title":"Sociolinguistically Informed Interpretability: A Case Study on Hinglish Emotion Classification","authors":["K Tatariya, H Lent, J Bjerva, M de Lhoneux - arXiv preprint arXiv:2402.03137, 2024"],"snippet":"Emotion classification is a challenging task in NLP due to the inherent idiosyncratic and subjective nature of linguistic expression, especially with code-mixed data. Pre-trained language models (PLMs) have achieved high performance for many tasks and …","url":["https://arxiv.org/pdf/2402.03137"]}
-{"year":"2024","title":"SoK: SSO-MONITOR—The Current State and Future Research Directions in Single Sign-On Security Measurements","authors":["L Jannett, M Westers, T Wich, C Mainka, A Mayer…"],"snippet":"Single Sign-On (SSO) with OAuth 2.0 and OpenID Connect 1.0 is essential for user authentication and authorization on the Internet. Billions of users rely on SSO services provided by Google, Facebook, and Apple. For large-scale measurements …","url":["https://nerd2.nrw/wp-content/uploads/2024/05/sso-monitor.pdf"]}
-{"year":"2024","title":"Spanning the Spectrum of Hatred Detection: A Persian Multi-Label Hate Speech Dataset with Annotator Rationales","authors":["Z Delbari, NS Moosavi, MT Pilehvar - Proceedings of the AAAI Conference on …, 2024"],"snippet":"With the alarming rise of hate speech in online communities, the demand for effective NLP models to identify instances of offensive language has reached a critical point. However, the development of such models heavily relies on the …","url":["https://ojs.aaai.org/index.php/AAAI/article/view/29743/31279"]}
-{"year":"2024","title":"Speaker independent recognition of low-resourced multilingual Arabic spoken words through hybrid fusion","authors":["S Mehra, V Ranga, R Agarwal, S Susan - Multimedia Tools and Applications, 2024"],"snippet":"This article introduces a supervised strategy designed to enhance spoken word recognition within the constraints of a resource-limited multilingual dataset, specifically focusing on the Arabic language. Notably, existing methodologies often …","url":["https://link.springer.com/article/10.1007/s11042-024-18804-w"]}
-{"year":"2024","title":"Specialising and Analysing Instruction-Tuned and Byte-Level Language Models for Organic Reaction Prediction","authors":["J Pang, I Vulić - arXiv preprint arXiv:2405.10625, 2024"],"snippet":"Transformer-based encoder-decoder models have demonstrated impressive results in chemical reaction prediction tasks. However, these models typically rely on pretraining using tens of millions of unlabelled molecules, which can be time-consuming …","url":["https://arxiv.org/pdf/2405.10625"]}
-{"year":"2024","title":"Specialized Language Models with Cheap Inference from Limited Domain Data","authors":["D Grangier, A Katharopoulos, P Ablin, A Hannun - arXiv preprint arXiv:2402.01093, 2024"],"snippet":"Large language models have emerged as a versatile tool but are challenging to apply to tasks lacking large inference budgets and large in-domain training sets. This work formalizes these constraints and distinguishes four important variables …","url":["https://arxiv.org/pdf/2402.01093"]}
-{"year":"2024","title":"SPHINX-X: Scaling Data and Parameters for a Family of Multi-modal Large Language Models","authors":["D Liu, R Zhang, L Qiu, S Huang, W Lin, S Zhao, S Geng… - Forty-first International Conference …","P Gao, R Zhang, C Liu, L Qiu, S Huang, W Lin, S Zhao… - arXiv preprint arXiv …, 2024"],"snippet":"… Specifically, we first collect large-scale PDF datasets from Common Crawl 1 and arXiv websites. Then, we utilize PyMuPDF 2 to get the rendering results of each page in the PDF file and also save all the text annotations along with their bounding …","url":["https://arxiv.org/pdf/2402.05935","https://openreview.net/pdf?id=tDMlQkJRhZ"]}
-{"year":"2024","title":"Spike No More: Stabilizing the Pre-training of Large Language Models","authors":["S Takase, S Kiyono, S Kobayashi, J Suzuki - arXiv preprint arXiv:2312.16903, 2023"],"snippet":"… 2020) that consists of clean English texts extracted from Common Crawl7 as our LLM pre-training corpus. We also used the separated part of C4 as our validation data. We used GPT-2 vocabulary (Radford et al.… https://commoncrawl.org/ …","url":["https://arxiv.org/pdf/2312.16903"]}
-{"year":"2024","title":"SPML: A DSL for Defending Language Models Against Prompt Attacks","authors":["RK Sharma, V Gupta, D Grossman - arXiv preprint arXiv:2402.11755, 2024"],"snippet":"… The pre-training data included trillions of tokens sourced from publicly available datasets, such as Common Crawl, Wikipedia, and public domain books from Project Gutenberg. We use the versions with 7 billion and 13 billion parameters, available …","url":["https://arxiv.org/pdf/2402.11755"]}
-{"year":"2024","title":"Sports, crisis, and social media: a Twitter-based exploration of the Tokyo Olympics in the COVID-19 era","authors":["V Mehra, P Singh, S Bharany, RS Sawhney - Social Network Analysis and Mining, 2024"],"snippet":"The global landscape underwent a transformative shift due to the unexpected arrival of the COVID-19 pandemic, disrupting various aspects of life, including the staging of sports events. Notably, the Tokyo Olympics, a renowned international sports …","url":["https://link.springer.com/article/10.1007/s13278-024-01218-9"]}
-{"year":"2024","title":"Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text","authors":["A Hans, A Schwarzschild, V Cherepanova, H Kazemi… - arXiv preprint arXiv …, 2024"],"snippet":"… When evaluating Binoculars on samples from languages that are not well represented in Common Crawl data (standard LLM pretraining data), we find that false-positives rates remain low, which is highly desirable from a harm reduction …","url":["https://arxiv.org/pdf/2401.12070"]}
-{"year":"2024","title":"SRBerta—A Transformer Language Model for Serbian Cyrillic Legal Texts","authors":["M Bogdanović, J Kocić, L Stoimenov - Information, 2024"],"snippet":"… CommonCrawl [5] is a collection of texts whose size is measured in petabytes. This collection was … , CommonCrawl contains texts of lower quality, so development teams often resorted to processing texts before training and extracting …","url":["https://www.mdpi.com/2078-2489/15/2/74"]}
-{"year":"2024","title":"Stacking Your Transformers: A Closer Look at Model Growth for Efficient LLM Pre-Training","authors":["W Du, T Luo, Z Qiu, Z Huang, Y Shen, R Cheng, Y Guo… - arXiv preprint arXiv …, 2024"],"snippet":"LLMs are computationally expensive to pre-train due to their large scale. Model growth emerges as a promising approach by leveraging smaller models to accelerate the training of larger ones. However, the viability of these model growth …","url":["https://arxiv.org/pdf/2405.15319"]}
-{"year":"2024","title":"Stage-1 Report: Everything everywhere all at once? Exploring the richness of visual experience beyond words","authors":["L Qianchen, M Yamada, Y Aizawa, N Tsuchiya"],"snippet":"In consciousness research, understanding the nature and mechanism of visual experience has been one of the most debated topics. For humans, vision is arguably the primary sensory modality to understand the environment (Cole & Balcetis, 2021) …","url":["https://osf.io/2z85g/download"]}
-{"year":"2024","title":"StarCoder 2 and The Stack v2: The Next Generation","authors":["A Lozhkov, R Li, LB Allal, F Cassano, J Lamy-Poirier… - arXiv preprint arXiv …, 2024"],"snippet":"The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership with Software Heritage (SWH), we build The Stack v2 on …","url":["https://arxiv.org/pdf/2402.19173"]}
-{"year":"2024","title":"Strategies for Corpus Development for Low‐Resource Languages: Insights from Nepal","authors":["BK Bal, B Prasain, RR Ghimire, P Acharya - Automatic Speech Recognition and …, 2024"],"snippet":"… 25 whereas the monolingual dataset were derived from Wikipedia and Common Crawl for languages under consideration. They also experimented with four variations of training settings: fully supervised, fully unsupervised, semisupervised …","url":["https://onlinelibrary.wiley.com/doi/abs/10.1002/9781394214624.ch15"]}
-{"year":"2024","title":"Strengthening the WiC: New Polysemy Dataset in Hindi and Lack of Cross Lingual Transfer","authors":["H Dubossarsky, F Dairkee - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"… TB of filtered CommonCrawl data as opposed to mBERT which was trained on Wikipedia data, and reported to outperform mBERT in a variety of cross-lingual benchmarks like XNLI, MLQA and NER. HindiBERT is a monolingual model trained …","url":["https://aclanthology.org/2024.lrec-main.1332.pdf"]}
-{"year":"2024","title":"Structured Packing in LLM Training Improves Long Context Utilization","authors":["K Staniszewski, S Tworkowski, S Jaszczur… - arXiv preprint arXiv …, 2023"],"snippet":"Recent advances in long-context Large Language Models (LCLMs) have generated significant interest, especially in applications such as querying scientific research papers. However, their potential is often limited by inadequate context utilization. We …","url":["https://arxiv.org/pdf/2312.17296"]}
-{"year":"2024","title":"Studies in conversational AI: multilingual capabilities, world knowledge, and evaluation strategies","authors":["M De Bruyn - 2024"],"snippet":"This thesis studies the evolving landscape of conversational AI. The main research objective is to improve the conversational abilities of conversational agents, with a focus on integrating real-time knowledge and expanding multilingual capabil-ities …","url":["https://repository.uantwerpen.be/docstore/d:irua:21301"]}
-{"year":"2024","title":"Studying Peer Effects in Divergent Thinking: Theory and Method","authors":["CH Wong, I Juvina, PS Popescu"],"snippet":"In designing technology that supports user learning, an important first step is to understand how interactions among humans shape mutual learning. Much qualitative research in the realm of peer-assisted learning (PAL) has advanced the …","url":["https://rochi.utcluj.ro/articole/11/RoCHI2023-Wong.pdf"]}
-{"year":"2024","title":"SUBLLM: A Novel Efficient Architecture with Token Sequence Subsampling for LLM","authors":["Q Wang, Y Yuan, X Yang, R Zhang, K Zhao, W Liu… - arXiv preprint arXiv …, 2024"],"snippet":"While Large Language Models (LLMs) have achieved remarkable success in various fields, the efficiency of training and inference remains a major challenge. To address this issue, we propose SUBLLM, short for Subsampling-Upsampling-Bypass …","url":["https://arxiv.org/pdf/2406.06571"]}
-{"year":"2024","title":"Supervised Learning","authors":["ER Vankov, K Gadhoumi - Statistical Methods in Epilepsy, 2024"],"snippet":"… A corpus such as Common Crawl, which contains roughly 840 billion tokens of over two million unique words, provides such scale. There are other corpora used in these unsupervised processes, one such common candidate being a collection of all …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Khj5EAAAQBAJ&oi=fnd&pg=PT331&dq=commoncrawl&ots=zkHFEaxxbb&sig=j_lgK0J9A3vlHt3tIE3yX5TTAK8"]}
-{"year":"2024","title":"SuRe: Summarizing Retrievals using Answer Candidates for Open-domain QA of LLMs","authors":["J Kim, J Nam, S Mo, J Park, SW Lee, M Seo, JW Ha… - arXiv preprint arXiv …, 2024"],"snippet":"Large language models (LLMs) have made significant advancements in various natural language processing tasks, including question answering (QA) tasks. While incorporating new information with the retrieval of relevant passages is a promising …","url":["https://arxiv.org/pdf/2404.13081"]}
-{"year":"2024","title":"Synthetic Data Generation and Joint Learning for Robust Code-Mixed Translation","authors":["S Soni, A Kunchukuttan, T Chakraborty, MS Akhtar - arXiv preprint arXiv …, 2024"],"snippet":"The widespread online communication in a modern multilingual world has provided opportunities to blend more than one language (aka code-mixed language) in a single utterance. This has resulted a formidable challenge for the computational …","url":["https://arxiv.org/pdf/2403.16771"]}
-{"year":"2024","title":"Systematic Evaluation of Linear Transformations for Cross-lingual Semantic Spaces","authors":["A Mištera, T Brychcín, J Šmíd - 2024"],"snippet":"In the field of natural language understanding (NLU), a fundamental element is the representation of word meanings, a process that is integral to a wide range of applications. These applications span numerous domains including machine …","url":["https://www.researchsquare.com/article/rs-3913165/latest.pdf"]}
-{"year":"2024","title":"Table Representation Learning","authors":["M Hulsebos - 2024"],"snippet":"The increasing amount of data being collected, stored, and analyzed, induces a need for efficient, scalable, and robust methods to handle this data. Representation learning, ie, the practice of leveraging neural networks to obtain generic vector …","url":["https://pure.uva.nl/ws/files/155198398/Thesis.pdf"]}
-{"year":"2024","title":"Tackling an Unbalanced Dataset for Classifying Indonesian E-Commerce Reviews Using Multi Word Embedding Model","authors":["R Adi, BR Irnawan, J Li - 2023 Eighth International Conference on Informatics …, 2023"],"snippet":"… Our research used a pre-trained FastText that was trained on Indonesian Common Crawl and Wikipedia provided by [24]. 3) GloVe: GloVe is an unsupervised algorithm that can produce a vector representation of words created by [22]. Besides …","url":["https://ieeexplore.ieee.org/abstract/document/10381997/"]}
-{"year":"2024","title":"Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization","authors":["X Chen, Z Wang, D Sow, J Yang, T Chen, Y Liang… - arXiv preprint arXiv …, 2024"],"snippet":"… subset of the Common Crawl’s web crawl corpus. More recently, LLaMA (Touvron et al.… datasets to encompass multiple domains such as Common Crawl, C4, and source codes from … contents are mostly unintelligible” in the Common Crawl. All …","url":["https://arxiv.org/html/2402.14270v1"]}
-{"year":"2024","title":"TEA+: A Novel Temporal Graph Random Walk Engine With Hybrid Storage Architecture","authors":["C Huan, Y Liu, H Zhang, S Song, S Pandey, S Chen… - ACM Transactions on Architecture …"],"snippet":"Many real-world networks are characterized by being temporal and dynamic, wherein the temporal information signifies the changes in connections, such as the addition or removal of links between nodes. Employing random walks on these …","url":["https://dl.acm.org/doi/pdf/10.1145/3652604"]}
-{"year":"2024","title":"TeClass: A Human-Annotated Relevance-based Headline Classification and Generation Dataset for Telugu","authors":["G Kanumolu, L Madasu, N Surange, M Shrivastava - arXiv preprint arXiv:2404.11349, 2024"],"snippet":"… 2019) is a multilingual version of the RoBERTa model, and it was pre-trained on a vast 2.5TB CommonCrawl dataset, which included text from 100 languages. For our experiments, we utilized the xlm-roberta-base variant, boasting 270 million parameters. …","url":["https://arxiv.org/pdf/2404.11349"]}
-{"year":"2024","title":"Tele-FLM Technical Report","authors":["X Li, Y Yao, X Jiang, X Fang, C Wang, X Liu, Z Wang… - arXiv preprint arXiv …, 2024"],"snippet":"… CommonCrawl1 is often considered to be a repository containing diverse human experience … CommonCrawl are primarily concentrated in the English segment, with the Chinese content exhibiting relatively lower information density and quality …","url":["https://arxiv.org/pdf/2404.16645"]}
-{"year":"2024","title":"Tell me a story: a framework for critically investigating AI language models","authors":["L Munn, L Henrickson - Learning, Media and Technology, 2024"],"snippet":"Large language models are rapidly being rolled out into high-stakes fields like healthcare, law, and education. However, understanding of their design considerations, operational logics, and implicit biases remains limited. How might …","url":["https://www.tandfonline.com/doi/pdf/10.1080/17439884.2024.2327024"]}
-{"year":"2024","title":"Temporal Blind Spots in Large Language Models","authors":["J Wallat, A Jatowt, A Anand - arXiv preprint arXiv:2401.12078, 2024"],"snippet":"… A mixture of training datasets has been used: a filtered version of CommonCrawl, an expanded version of WebText [44], two not further specified internet-based book corpora, and the English Wikipedia. The most recent information in text-davinci-003’s …","url":["https://arxiv.org/pdf/2401.12078"]}
-{"year":"2024","title":"Temporally-Varied News Headline Generation with GPT-3","authors":["V Graf, E Tian, R Zhu"],"url":["https://richardzhu123.github.io/assets/pdf/Temporally-Varied_News_Headline_Generation_with_GPT-3.pdf"]}
-{"year":"2024","title":"Text Emotion Recognition Using Fast Text Word Embedding in Bi-Directional Gated Recurrent Unit","authors":["C Akalya Devi, D Karthika Renuka, T Harisudhan…"],"snippet":"Emotions are states of readiness in the mind that result from evaluations of one's own thinking or events. Although almost all of the important events in our lives are marked by emotions, the nature, causes, and effects of emotions are some of the …","url":["https://imanagerpublications.com/assets/htmlfiles/JIT11(4)September-November202219119.html"]}
-{"year":"2024","title":"Text Filtering Classifiers for Medium-Resource Languages","authors":["J Daðason, H Loftsson - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"… Online texts are often obtained from large datasets, such as those published by Common Crawl (CC).The GPT-3 model was pre-trained on 499B tokens, 410B of which were obtained from CC (Brown et al.… The Icelandic Common Crawl Corpus (IC3) …","url":["https://aclanthology.org/2024.lrec-main.1372.pdf"]}
-{"year":"2024","title":"Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challenges","authors":["J Becker, JP Wahle, B Gipp, T Ruas - arXiv preprint arXiv:2405.15604, 2024"],"snippet":"Text generation has become more accessible than ever, and the increasing interest in these systems, especially those using large language models, has spurred an increasing number of related publications. We provide a systematic literature review …","url":["https://arxiv.org/pdf/2405.15604"]}
-{"year":"2024","title":"TEXT SUMMARIZATION SYSTEM USING NATURAL LANGUAGE PROCESSING AND MACHINE LEARNING","authors":["M NARAYAN - 2023"],"snippet":"Information overload, caused by the rapid growth of the Internet, has become a significant issue. The abundance of information available online necessitates the simplification of relevant content through summarization. Manual summarization of …","url":["http://dspace.dtu.ac.in:8080/jspui/bitstream/repository/20400/1/MANEESH%20NARAYAN%20M.Tech..pdf"]}
-{"year":"2024","title":"TextGram: Towards a Better Domain-Adaptive Pretraining","authors":["O Dhekane, S Hiwarkhedkar, R Joshi, A Ladkat - … , Perundurai, Erode, India, December 6–8 …"],"snippet":"… The RealNews Dataset is a large corpus of news articles scraped from Common Crawl [16]. It consists of 5000 news domains that are indexed by Google news. IMDb Movie Reviews is a binary sentiment analysis dataset made up of 50000 reviews …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=Rs0DEQAAQBAJ&oi=fnd&pg=PA161&dq=commoncrawl&ots=l6SKt6PjDk&sig=eAtYThwZwGzNMXk0LzGOBEGThUM"]}
-{"year":"2024","title":"Textual Coverage of Eventive Entries in Lexical Semantic Resources","authors":["E Fucikova, CF Alcaina, J Hajic, Z Urešová - Proceedings of the 2024 Joint …, 2024"],"snippet":"This short paper focuses on the coverage of eventive entries (verbs, predicates, etc.) of some well-known lexical semantic resources when applied to random running texts taken from the internet. While coverage gaps are often reported for manually …","url":["https://aclanthology.org/2024.lrec-main.1375.pdf"]}
-{"year":"2024","title":"The AI Companion in Education: Analyzing the Pedagogical Potential of ChatGPT in Computer Science and Engineering","authors":["Z He, T Nguyen, T Miari, M Aliasgari, S Rafatirad…"],"snippet":"… ChatGPT3 employs a pre-trained large language model [29] trained over the Common Crawl dataset [30]. During its training process, it first preprocess data from the Common Crawl dataset, data quality is refined by eliminating irrelevant or noisy …","url":["https://www.researchgate.net/profile/Zhangying-He/publication/380210828_The_AI_Companion_in_Education_Analyzing_the_Pedagogical_Potential_of_ChatGPT_in_Computer_Science_and_Engineering/links/663175407091b94e93e9cf70/The-AI-Companion-in-Education-Analyzing-the-Pedagogical-Potential-of-ChatGPT-in-Computer-Science-and-Engineering.pdf"]}
-{"year":"2024","title":"The AI Did My Job Well","authors":["CM Moran, M Coward"],"snippet":"Artificial intelligence (AI), an idea first proposed back in 1955 (McCarthy, Minsky, & Rochester) seemingly has burst into public consciousness nearly 70 years later. Like the chained prisoners emerging from Plato’s allegorical cave, many of us find …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=HtIDEQAAQBAJ&oi=fnd&pg=PA15&dq=commoncrawl&ots=Wd6CuXLoH8&sig=E1TnJeb3liWF_UQel1vg_9SX-fA"]}
-{"year":"2024","title":"The Case for Developing a Foundation Model for Planning-like Tasks from Scratch","authors":["B Srivastava, V Pallagani - arXiv preprint arXiv:2404.04540, 2024"],"snippet":"Foundation Models (FMs) have revolutionized many areas of computing, including Automated Planning and Scheduling (APS). For example, a recent study found them useful for planning problems: plan generation, language translation, model …","url":["https://arxiv.org/html/2404.04540v1"]}
-{"year":"2024","title":"The correlation between nativelike selection and prototypicality: a multilingual onomasiological case study using semantic embedding","authors":["H Zhang - arXiv preprint arXiv:2405.13529, 2024"],"snippet":"In native speakers' lexical choices, a concept can be more readily expressed by one expression over another grammatical one, a phenomenon known as nativelike selection (NLS). In previous research, arbitrary chunks such as collocations have …","url":["https://arxiv.org/pdf/2405.13529"]}
-{"year":"2024","title":"The Dark Side of Dataset Scaling: Evaluating Racial Classification in Multimodal Models","authors":["A Birhane, S Dehdashtian, VU Prabhu, V Boddeti - arXiv preprint arXiv:2405.04623, 2024"],"snippet":"… This is particularly important in the context of multimodal datasets whose main source is the World Wide Web, condensed and packaged as the Common Crawl dump, which is known to exhibit numerous drawbacks. In this paper, we evaluate the …","url":["https://arxiv.org/pdf/2405.04623"]}
-{"year":"2024","title":"The Dark Side of Language Models: Exploring the Potential of LLMs in Multimedia Disinformation Generation and Dissemination","authors":["D Barman, Z Guo, O Conlan - Machine Learning with Applications, 2024"],"snippet":"Disinformation - the deliberate spread of false or misleading information poses a significant threat to our society by undermining trust, exacerbating polarization, and manipulating public opinion. With the rapid advancement of artificial intelligence and …","url":["https://www.sciencedirect.com/science/article/pii/S2666827024000215"]}
-{"year":"2024","title":"The effect of generative artificial intelligence on managerial behavior across functions","authors":["ST OZTURK"],"snippet":"GAI is becoming readily available and easily accessible for those who are willing to take advantage of it. As a result, the world is witnessing a transformation regarding how managers perform their daily tasks. This study aims to understand the …","url":["https://thesis.unipd.it/bitstream/20.500.12608/62859/1/Ozturk_Safak_Tanir.pdf"]}
-{"year":"2024","title":"THE ENHANCEMENT OF OPEN DATA USABILITY BY DEFINING A CATEGORIZATION METHOD BASED ON THE OPEN DATA PORTAL METADATA","authors":["MBF Gligorijević"],"snippet":"Due to numerous data transparency and open government initiatives, a large volume of data was published on open data portals. To make it more accessible and visible, these portals have introduced data filtering by category, tags, format …","url":["https://www.elfak.ni.ac.rs/downloads/informacije/studenti/doktorske-magistarske/2023/dus-uni-frtunic-gligorijevic-b-milena-2023-sa-napomenom.pdf"]}
-{"year":"2024","title":"The ethical situation of DALL-E 2","authors":["E Hogea, J Rocafortf - arXiv preprint arXiv:2405.19176, 2024"],"snippet":"A hot topic of Artificial Intelligence right now is image generation from prompts. DALL-E 2 is one of the biggest names in this domain, as it allows people to create images from simple text inputs, to even more complicated ones. The company that made this …","url":["https://arxiv.org/pdf/2405.19176"]}
-{"year":"2024","title":"The Ethics and Challenges of Legal Personhood for AI","authors":["HKB Forrest - Ethics, 2024"],"snippet":"Hon. Katherine B. Forrest (Fmr.) abstract. AI’s increasing cognitive abilities will raise challenges for judges.“Legal personhood” is a flexible and political concept that has evolved throughout American history. In determining whether to expand that concept …","url":["https://www.yalelawjournal.org/pdf/ForrestYLJForumEssay_at8hdu63.pdf"]}
-{"year":"2024","title":"The Evolution of Multimodal Model Architectures","authors":["SN Wadekar, A Chaurasia, A Chadha, E Culurciello - arXiv preprint arXiv:2405.17927, 2024"],"snippet":"This work uniquely identifies and characterizes four prevalent multimodal model architectural patterns in the contemporary multimodal landscape. Systematically categorizing models by architecture type facilitates monitoring of developments in …","url":["https://arxiv.org/pdf/2405.17927"]}
-{"year":"2024","title":"The Fill-Mask Association Test (FMAT): Measuring Propositions in Natural Language","authors":["HWS Bao - Journal of Personality and Social Psychology, 2024","L Lin, B Wang, X Wang, ZX Wang, A Wiśniowski…"],"snippet":"Recent advances in large language models are enabling the computational intelligent analysis of psychology in natural language. Here, the Fill-Mask Association Test (FMAT) is introduced as a novel and integrative method leveraging …","url":["https://files.osf.io/v1/resources/bgsxr/providers/osfstorage/66189ed0943bee4457dfec9e?action=download&direct&version=2","https://psychbruce.github.io/paper/Bao_Accepted_JPSP_FMAT_Manuscript.pdf"]}
-{"year":"2024","title":"The Future of Data Science in Materials Science","authors":["P Chundi, V Bommanapally, V Gadhamshetty - Machine Learning in 2D Materials …, 2023"],"snippet":"… GPT-3 is an autoregressive model built with 96 layers [31], increased embedding vector dimension of 12888, trained with 175B parameters on five datasets including Common crawl, WebText2, Books1, Books2, and Wikipedia. Though GPT-3 has …","url":["https://www.taylorfrancis.com/chapters/edit/10.1201/9781003132981-12/future-data-science-materials-science-parvathi-chundi-vidya-bommanapally-venkataramana-gadhamshetty"]}
-{"year":"2024","title":"The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG)","authors":["S Zeng, J Zhang, P He, Y Xing, Y Liu, H Xu, J Ren… - arXiv preprint arXiv …, 2024"],"snippet":"… 2021), we randomly select chunks from the Common Crawl dataset to serve as the {information} component. … 2021), we randomly select chunks from the Common Crawl dataset to serve as the {information} component. Due to the random …","url":["https://arxiv.org/pdf/2402.16893"]}
-{"year":"2024","title":"The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis","authors":["M Zhang, V Gautam, M Wang, JO Alabi, X Shen… - arXiv preprint arXiv …, 2024"],"snippet":"… The order of languages follows their data ratio in the CommonCrawl corpus10 from high-resource to low-resource. We observe large variations in model performance across different languages. For instance, there exists a large …","url":["https://arxiv.org/pdf/2402.12976"]}
-{"year":"2024","title":"The Impact of Geometric Complexity on Neural Collapse in Transfer Learning","authors":["M Munn, B Dherin, J Gonzalvo - arXiv preprint arXiv:2405.15706, 2024"],"snippet":"Many of the recent remarkable advances in computer vision and language models can be attributed to the success of transfer learning via the pre-training of large foundation models. However, a theoretical framework which explains this empirical …","url":["https://arxiv.org/pdf/2405.15706"]}
-{"year":"2024","title":"The Impact of Infrastructure: Considerations of Generative AI in the Classroom","authors":["ES Kehlenbach - Journal of Political Science Education, 2024"],"snippet":"How are we to grapple with the increasing intrusion of technology in the classroom? What considerations need to be addressed before we begin bringing advanced technological systems like ChatGPT into our classroom spaces? A close attention to …","url":["https://www.tandfonline.com/doi/abs/10.1080/15512169.2024.2359439"]}
-{"year":"2024","title":"The Impact of OpenAI on the Work Environment located in Finland","authors":["J Laiho, K Varttila - 2023"],"snippet":"In the modern era, technology has undergone a rapid transformation that touches every aspect of our lives. At the forefront of this transformation stands artificial intelligence (AI), a field rapidly evolving through groundbreaking innovations, and …","url":["https://www.theseus.fi/bitstream/handle/10024/818052/Laiho_Varttila.pdf?sequence=2"]}
-{"year":"2024","title":"The model student: GPT-4 performance on graduate biomedical science exams","authors":["D Stribling, Y Xia, MK Amer, KS Graim, CJ Mulligan… - Scientific Reports, 2024"],"snippet":"… As these study materials may have been incorporated into the GPT-4 training data such as the Common Crawl 43 , standardized examinations may not be an accurate assessment of domain-specific model knowledgebase and capability …","url":["https://www.nature.com/articles/s41598-024-55568-7"]}
-{"year":"2024","title":"The OECD-UNSD Multinational Enterprise Information Platform","authors":["G Pilgrim, S Ang - 2024"],"snippet":"… (3) Common Crawl is an open source initiative to provide a monthly snapshot of the internet through web scraping. As part of the project, they provide a quarterly network graph of hyperlinks between domains, which can be used to determine …","url":["https://www.oecd-ilibrary.org/economics/the-oecd-unsd-multinational-enterprise-information-platform_b7d90a06-en"]}
-{"year":"2024","title":"The Open Web Index","authors":["G Hendriksen, M Dinzinger, SM Farzana, NA Fathima…"],"snippet":"… To operationalize our crawling pipeline, we introduce a re-crawl mechanism specifically for Common Crawl dumps. Unlike Common Crawl, we crawl on a daily basis and save the results as WARC (Web ARChive) files.This approach allows us …","url":["https://djoerdhiemstra.com/wp-content/uploads/ecir2024ir4good.pdf"]}
-{"year":"2024","title":"The Open Web Index: Crawling and Indexing the Web for Public Use","authors":["G Hendriksen, M Dinzinger, SM Farzana, NA Fathima… - European Conference on …, 2024"],"snippet":"… To operationalize our crawling pipeline, we introduce a re-crawl mechanism specifically for Common Crawl dumps. Unlike Common Crawl, we crawl on a daily basis and save the results as WARC (Web ARChive) files. Footnote 11 This …","url":["https://link.springer.com/chapter/10.1007/978-3-031-56069-9_10"]}
-{"year":"2024","title":"The Power of Absence: Thinking with Archival Theory in Algorithmic Design","authors":["J Sherman, R Morrison, L Klein, DK Rosner - arXiv preprint arXiv:2405.05420, 2024"],"snippet":"… , for example–but also of datasets like the Colossal Clean Common Crawl corpus, or C4, which explicitly documents its decision to include … [33] have shown how the quality filters imposed on the original Common Crawl dataset exhibit a preference …","url":["https://arxiv.org/pdf/2405.05420"]}
-{"year":"2024","title":"The Practical Epistemologies of Design and Artificial Intelligence","authors":["W Billingsley - Science & Education, 2024"],"snippet":"This article explores the epistemological trade-offs that practical and technology design fields make by exploring past philosophical discussions of design, practitioner research, and pragmatism. It argues that as technologists apply Artificial …","url":["https://link.springer.com/article/10.1007/s11191-024-00517-z"]}
-{"year":"2024","title":"The Right Prompts for the Job: Repair Code-Review Defects with Large Language Model","authors":["Z Zhao, Z Xu, J Zhu, P Di, Y Yao, X Ma - arXiv preprint arXiv:2312.17485, 2023"],"snippet":"Automatic program repair (APR) techniques have the potential to reduce manual efforts in uncovering and repairing program defects during the code review (CR) process. However, the limited accuracy and considerable time costs associated with …","url":["https://arxiv.org/pdf/2312.17485"]}
-{"year":"2024","title":"The Right to Scrap Data on the Internet: From the US Case hiQLabs, Inc. v. LinkedIn Corp. to the ChatGPT Scraping Cases: Differences Between US and EU Law [pre …","authors":["JTS y López - Global Privacy Law Review, 2024"],"snippet":"… a doctor when she was undergoing treatment for a rare genetic condition ended up in the Common Crawl’s archive and LAION’s dataset, and therefore in the GhatGPT datasets (because the Common Crawl is one of the ChatGPT training …","url":["https://kluwerlawonline.com/journalarticle/Global+Privacy+Law+Review/5.1/GPLR2024001"]}
-{"year":"2024","title":"The Role and Prospects of Using ChatGPT Artificial Intelligence-Based Chatbots in Healthcare Improvement","authors":["NA Mumtaz - ISWOPHA, 2024"],"snippet":"In the age of digital transformation, healthcare is undergoing a revolution through information technology and artificial intelligence (AI). This article explores the role of AI-based chatbots, like ChatGPT, in healthcare enhancement. Utilizing a literature …","url":["https://healthscience.dinus.ac.id/category/index.php/iswopha/article/download/147/20"]}
-{"year":"2024","title":"The Science of Data Filtering: Data Curation cannot be Compute Agnostic","authors":["S Goyal, P Maini, ZC Lipton, A Raghunathan, JZ Kolter - ICLR 2024 Workshop on …"],"snippet":"… In fact, we show that even a model trained on *unfiltered common crawl* obtains higher accuracy than that trained on the LAION dataset post 40 or more repetitions. While past research in neural scaling laws has considered web data to be …","url":["https://openreview.net/forum?id=9wzo4EjEGM"]}
-{"year":"2024","title":"The science of implicit race bias: Evidence from the Implicit Association Test","authors":["KN Morehouse, MR Banaji - Daedalus, 2024"],"snippet":"Beginning in the mid-1980s, scientific psychology underwent a revolution–the implicit revolution–that led to the development of methods to capture implicit bias: attitudes, stereotypes, and identities that operate without full conscious awareness …","url":["https://www.amacad.org/sites/default/files/publication/downloads/Daedalus_Wi24_05_Morehouse_Banaji.pdf"]}
-{"year":"2024","title":"The Shape of Word Embeddings: Recognizing Language Phylogenies through Topological Data Analysis","authors":["O Draganov, S Skiena - arXiv preprint arXiv:2404.00500, 2024"],"snippet":"Word embeddings represent language vocabularies as clouds of $d$-dimensional points. We investigate how information is conveyed by the general shape of these clouds, outside of representing the semantic meaning of each token. Specifically, we …","url":["https://arxiv.org/html/2404.00500v1"]}
-{"year":"2024","title":"The Silicone Ceiling: Auditing GPT's Race and Gender Biases in Hiring","authors":["L Armstrong, A Liu, S MacNeil, D Metaxa - arXiv preprint arXiv:2405.04412, 2024"],"snippet":"Large language models (LLMs) are increasingly being introduced in workplace settings, with the goals of improving efficiency and fairness. However, concerns have arisen regarding these models' potential to reflect or exacerbate social biases …","url":["https://arxiv.org/pdf/2405.04412"]}
-{"year":"2024","title":"The Trade-off between Performance, Efficiency, and Fairness in Adapter Modules for Text Classification","authors":["MD Bui, K von der Wense - arXiv preprint arXiv:2405.02010, 2024"],"snippet":"… 2019) is derived from 393,423 online biographies in English from the Common Crawl corpus, each including the subject’s occupation and gender. The dataset contains 28 occupations, assuming a binary gender classification. Gender identification …","url":["https://arxiv.org/pdf/2405.02010"]}
-{"year":"2024","title":"The use of machine learning and deep learning models in detecting depression on social media: A systematic literature review","authors":["WA Gadzama, D Gabi, MS Argungu, HU Suru - Personalized Medicine in Psychiatry, 2024"],"snippet":"Depression is regarded as one of the world's primary concerns. Recent researchers use artificial intelligence techniques like machine learning and deep learning to identify depressive symptoms automatically. This literature review focuses on using …","url":["https://www.sciencedirect.com/science/article/pii/S2468171724000115"]}
-{"year":"2024","title":"The Web Data Commons Schema. org Table Corpora","authors":["R Peeters, A Brinkmann, C Bizer - Companion Proceedings of the ACM on Web …, 2024"],"snippet":"… This paper presented the WDC Schema.org Table Corpora that we extracted from the Common Crawl. To the best of our knowledge, the corpora are the largest public table corpora that contain tables from many different sources which all share a …","url":["https://dl.acm.org/doi/pdf/10.1145/3589335.3651441"]}
-{"year":"2024","title":"The Web Is Missing an Essential Part of Infrastructure: An Open Web Index A proposal for building an index of the Web that separates the infrastructure part of the …","authors":["D Lewandowski"],"snippet":"The web as it currently exists would not be possible without search engines. They are an integral part of the Web and can also be seen as a part of the Web’s infrastructure. Google alone now serves over two trillion search queries per year. 11 …","url":["https://cacm.acm.org/opinion/the-web-is-missing-an-essential-part-of-infrastructure/"]}
-{"year":"2024","title":"The work of art in the age of artificial intelligibility","authors":["J McLoughlin - AI & SOCIETY, 2024"],"snippet":"The emergence of complex deep-learning models capable of producing novel images on a practically innumerable number of subjects and in an equally wide variety of artistic styles is beginning to highlight serious inadequacies in the ethical …","url":["https://link.springer.com/article/10.1007/s00146-023-01845-4"]}
-{"year":"2024","title":"Time for a Pause: Without Effective Public Oversight, AI in Schools Will Do More Harm Than Good.","authors":["B Williamson, A Molnar, F Boninger - 2024"],"snippet":"Public education is a public and private good essential to democratic civic life. The public must, therefore, be able to provide meaningful direction over schools through transparent democratic governance structures. And yet artificial intelligence (AI) 1 …","url":["https://nepc.colorado.edu/sites/default/files/publications/PB%20Williamson_0.pdf"]}
-{"year":"2024","title":"Time Machine GPT","authors":["F Drinkall, E Rahimikia, JB Pierrehumbert, S Zohren - arXiv preprint arXiv:2404.18543, 2024"],"snippet":"… To scale to even larger models, processing the annual Common Crawl datasets is a necessary step, though the dataset has proved problematic due to its scale and lack of … Aside from this, cleaning Common Crawl would also demand significant …","url":["https://arxiv.org/pdf/2404.18543"]}
-{"year":"2024","title":"To store or not: Online cost optimization for running big data jobs on the cloud","authors":["X Fu, L Pan, S Liu - Future Generation Computer Systems, 2024"],"snippet":"As businesses increasingly rely on cloud-based big data analytics services to drive insights, reducing the cost of storing and analyzing large volumes of data in the cloud has become a major concern. During the execution of big data analysis jobs …","url":["https://www.sciencedirect.com/science/article/pii/S0167739X24000803"]}
-{"year":"2024","title":"TOFU: A Task of Fictitious Unlearning for LLMs","authors":["P Maini, Z Feng, A Schwarzschild, ZC Lipton, JZ Kolter - arXiv preprint arXiv …, 2024"],"snippet":"… LLMs trained on Common Crawl data1 may be able to correctly answer factual questions about this person and they may wish to have their data removed from an LLM. In fact, regulations around the Right to be Forgotten that focus on this situation …","url":["https://arxiv.org/pdf/2401.06121"]}
-{"year":"2024","title":"TOMGPT: Reliable Text-Only Training Approach for Cost-Effective Multi-modal Large Language Model","authors":["Y Chen, Q Wang, S Wu, Y Gao, T Xu, Y Hu - ACM Transactions on Knowledge …, 2024"],"snippet":"… For instance, c4 [37] dataset, a colossal and cleaned version of the web crawl corpus from Common Crawl, serves as a suitable option. Since the CLIP text encoder has limitations in processing long text, we subdivided the text in the c4 …","url":["https://dl.acm.org/doi/pdf/10.1145/3654674"]}
-{"year":"2024","title":"Toward Inference-optimal Mixture-of-Expert Large Language Models","authors":["L Yun, Y Zhuang, Y Fu, EP Xing, H Zhang - arXiv preprint arXiv:2404.02852, 2024"],"snippet":"Mixture-of-Expert (MoE) based large language models (LLMs), such as the recent Mixtral and DeepSeek-MoE, have shown great promise in scaling model size without suffering from the quadratic growth of training cost of dense transformers …","url":["https://arxiv.org/html/2404.02852v1"]}
-{"year":"2024","title":"Towards a Framework for Openness in Foundation Models: Proceedings from the Columbia Convening on Openness in Artificial Intelligence","authors":["A Basdevant, C François, V Storchan, K Bankston… - arXiv preprint arXiv …, 2024"],"snippet":"Over the past year, there has been a robust debate about the benefits and risks of open sourcing foundation models. However, this discussion has often taken place at a high level of generality or with a narrow focus on specific technical attributes. In …","url":["https://arxiv.org/pdf/2405.15802"]}
-{"year":"2024","title":"Towards a Scalable Geoparsing Approach for the Web","authors":["SM Farzana, T Hecking - 2024"],"snippet":"The ongoing surge in web data generation and storage, coupled with embedded geographic information, holds immense potential for enhancing search applications across diverse domains. However, extracting geographic information for further …","url":["https://ceur-ws.org/Vol-3683/paper4.pdf"]}
-{"year":"2024","title":"Towards a small language model powered chain‐of‐reasoning for open‐domain question answering","authors":["J Roh, M Kim, K Bae - ETRI Journal, 2024"],"snippet":"… Unlike the ONUS approach [10], which extracts simple sub-question examples from a Common Crawl, our method emphasizes the autonomous generation of a dataset without human intervention facilitated by the use of LLMs. Consequently, we …","url":["https://onlinelibrary.wiley.com/doi/abs/10.4218/etrij.2023-0355"]}
-{"year":"2024","title":"Towards a sociology of recurrent events. Constellations of cultural change around Eurovision in 18 countries (1981–2021)","authors":["L Carbone, J Mijs, T van Dooremalen, S Daenekindt - Poetics, 2024"],"snippet":"… First, we used CMD with a corpus that was pre-trained on Common Crawl data using fastText English embeddings. Common Crawl is a vast and heterogeneous source of information that crawls web archives and freely provides their data to the …","url":["https://www.sciencedirect.com/science/article/pii/S0304422X24000287"]}
-{"year":"2024","title":"Towards adaptive support for self‐regulated learning of causal relations: Evaluating four Dutch word vector models","authors":["HJ Pijeira‐Díaz, S Braumann, J van de Pol, T van Gog… - British Journal of …, 2024"],"snippet":"Advances in computational language models increasingly enable adaptive support for self‐regulated learning (SRL) in digital learning environments (DLEs; eg, via automated feedback). However, the accuracy of those models is a common concern …","url":["https://bera-journals.onlinelibrary.wiley.com/doi/pdf/10.1111/bjet.13431"]}
-{"year":"2024","title":"Towards automatic question generation using pre-trained model in academic field for Bahasa Indonesia","authors":["D Suhartono, MRN Majiid, R Fredyan - Education and Information Technologies, 2024"],"snippet":"… This model is a potent tool for transforming our text data into numerical representations because it was previously trained on the sizable Common Crawl Dataset in Indonesian. These embeddings are essential for later modeling and …","url":["https://link.springer.com/article/10.1007/s10639-024-12717-9"]}
-{"year":"2024","title":"Towards Better Statistical Understanding of Watermarking LLMs","authors":["Z Cai, S Liu, H Wang, H Zhong, X Li - arXiv preprint arXiv:2403.13027, 2024"],"snippet":"In this paper, we study the problem of watermarking large language models (LLMs). We consider the trade-off between model distortion and detection ability and formulate it as a constrained optimization problem based on the green-red algorithm …","url":["https://arxiv.org/html/2403.13027v1"]}
-{"year":"2024","title":"Towards Building Multilingual Language Model for Medicine","authors":["P Qiu, C Wu, X Zhang, W Lin, H Wang, Y Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"In this paper, we aim to develop an open-source, multilingual language model for medicine, that the benefits a wider, linguistically diverse audience from different regions. In general, we present the contribution from the following aspects: first, for …","url":["https://arxiv.org/pdf/2402.13963"]}
-{"year":"2024","title":"Towards Chapterisation of Podcasts Detection of Host and Structuring Questions in Radio Transcripts","authors":["M Piguet - 2024"],"snippet":"This Master thesis investigates the application of Bidirectional Encoder Representations from Transformers (BERT) on podcast to identify the host and detect structuring questions within each episode. This research is conducted on an …","url":["https://infoscience.epfl.ch/record/310625/files/Towards_Chapterisation_of_Podcasts___Master_Thesis___28_03_2024.pdf"]}
-{"year":"2024","title":"Towards Disfluency Annotated Corpora for Indian Languages","authors":["C Kochar, V Mujadia, P Mishra, DM Sharma"],"snippet":"In the natural course of spoken language, individuals often engage in thinking and self-correction during speech production. These instances of interruption or correction are commonly referred to as disfluencies. When preparing data for …","url":["http://sanskrit.jnu.ac.in/conf/wildre7/pdf/2024.wildre-1.1.pdf"]}
-{"year":"2024","title":"Towards Effective Time-Aware Language Representation: Exploring Enhanced Temporal Understanding in Language Models","authors":["J Wang, A Jatowt, Y Cai - arXiv preprint arXiv:2406.01863, 2024"],"snippet":"In the evolving field of Natural Language Processing, understanding the temporal context of text is increasingly crucial. This study investigates methods to incorporate temporal information during pre-training, aiming to achieve effective time-aware …","url":["https://arxiv.org/pdf/2406.01863"]}
-{"year":"2024","title":"Towards Green AI. A methodological survey of the scientific literature","authors":["E Barbierato, A Gatti - IEEE Access, 2024"],"snippet":"The pervasive deployment of Deep Learning models has recently prompted apprehensions regarding their ecological footprint, owing to the exorbitant levels of energy consumption necessitated by the training and inference processes. The term …","url":["https://ieeexplore.ieee.org/iel7/6287639/6514899/10418137.pdf"]}
-{"year":"2024","title":"Towards interactive information seeking: conversational question answering","authors":["Y Li - 2024"],"snippet":"… To further advance the field, additional conversational search benchmarks have been introduced, such as ORQuAC [93], which extends CAsT and QuAC with more conversations constructed from Natural Questions and additional passages from …","url":["https://theses.lib.polyu.edu.hk/bitstream/200/12892/3/7339.pdf"]}
-{"year":"2024","title":"Towards Machine Translation Based on Monolingual Texts","authors":["I Kvapilíková - 2024"],"snippet":"… The CommonCrawl1 project carries out periodic web crawls and publishes the crawled data in an open … the CommonCrawl corpus. For example, the open source OSCAR2 project compiled a large multilingual corpus by language …","url":["https://dspace.cuni.cz/bitstream/handle/20.500.11956/188428/140116518.pdf?sequence=1"]}
-{"year":"2024","title":"Towards Privacy Preserving LLMs Training","authors":["B Buesser - Large Language Models in Cybersecurity: Threats …, 2024"],"snippet":"Privacy-preserving training of machine learning models aims to avoid or minimize (mitigate) the exact or similar reproduction (leakage) of information contained in the training data. This chapter introduces pre-processing methods (filtering and de-duplication) …","url":["https://link.springer.com/content/pdf/10.1007/978-3-031-54827-7_19.pdf"]}
-{"year":"2024","title":"Towards quantifying politicization in foreign aid project reports","authors":["S Wang, G Eggers, ART Georgiadis, TA Đo, L Gontard… - Proceedings of the Second …, 2024"],"snippet":"We aim to develop a metric of politicization by investigating whether this concept can be operationalized computationally using document embeddings. We are interested in measuring the extent to which foreign aid is politicized. Textual reports of foreign …","url":["https://aclanthology.org/2024.politicalnlp-1.9.pdf"]}
-{"year":"2024","title":"Towards reliability and interactive debugging for large language models","authors":["B Paranjape - 2024"],"snippet":"Large language models (LLMs) have permeated our everyday lives and are used in critical decision-making scenarios that can affect millions of people. Despite their impressive progress, model deficiencies may result in exacerbating harmful biases …","url":["https://digital.lib.washington.edu/researchworks/bitstream/handle/1773/51339/Paranjape_washington_0250E_26573.pdf?sequence=1"]}
-{"year":"2024","title":"Towards the automatic creation of NER systems for new domains","authors":["E Matos, M Rodrigues, A Teixeira - Proceedings of the 16th International Conference …, 2024"],"snippet":"… ner-roberta (ROBERTA): xlm-roberta-base-trimmed-pt-600002 model based in xlm-roberta-base, pretrained on 2.5TB of filtered CommonCrawl data containing 100 languages. It was introduced in the paper Unsupervised Crosslingual …","url":["https://aclanthology.org/2024.propor-1.22.pdf"]}
-{"year":"2024","title":"Toxicity Detection for Free","authors":["Z Hu, J Piet, G Zhao, J Jiao, D Wagner - arXiv preprint arXiv:2405.18822, 2024"],"snippet":"… An analysis of undesirable content in the common crawl corpus. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 2 …","url":["https://arxiv.org/pdf/2405.18822"]}
-{"year":"2024","title":"Training and evaluation of vector models for Galician","authors":["M Garcia - Language Resources and Evaluation, 2024"],"snippet":"This paper presents a large and systematic assessment of distributional models for Galician. To this end, we have first trained and evaluated static word embeddings (eg, word2vec, GloVe), and then compared their performance with that of current …","url":["https://link.springer.com/article/10.1007/s10579-024-09740-0"]}
-{"year":"2024","title":"Training BERT Models to Carry over a Coding System Developed on One Corpus to Another","authors":["D Galambos, P Zsamboki - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"This paper describes how we train BERT models to carry over a coding system developed on the paragraphs of a Hungarian literary journal to another. The aim of the coding system is to track trends in the perception of literary translation around …","url":["https://aclanthology.org/2024.lrec-main.1452.pdf"]}
-{"year":"2024","title":"Training Data for the Price of a Sandwich1","authors":["S Baack, M Insights - 2024"],"snippet":"… , this report sheds light on the implications of Common Crawl’s popularity by exploring the values that guide Common Crawl itself in-depth. … ) whether Common Crawl’s data had been used and b) what specific version of Common Crawl was …","url":["https://foundation.mozilla.org/documents/350/2024CommonCrawlMozillaFoundation.pdf"]}
-{"year":"2024","title":"Transformer-Based Named Entity Recognition Model-Tamil Language Check for updates","authors":["K Dhayalan, N Sultanova, J Mustafina, P Daud - Data Science and Emerging Technologies …"],"snippet":"This work presents different transformer-based approaches to the named entity recognition problem in the Tamil language. The WikiANN-ta dataset is used for training, validating and testing the model. Person, organization and location tags are …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=SeoEEQAAQBAJ&oi=fnd&pg=PA251&dq=commoncrawl&ots=LpNtMEhFcV&sig=rvIZ8MAeX1vawwV5W0MYS8VUePk"]}
-{"year":"2024","title":"Transformers and large language models in healthcare: A review","authors":["S Nerella, S Bandyopadhyay, J Zhang, M Contreras… - Artificial Intelligence in …, 2024"],"snippet":"With Artificial Intelligence (AI) increasingly permeating various aspects of society, including healthcare, the adoption of the Transformers neural network architecture is rapidly changing many applications. Transformer is a type of deep learning …","url":["https://www.sciencedirect.com/science/article/pii/S0933365724001428"]}
-{"year":"2024","title":"Transformers at HSD-2Lang 2024: Hate Speech Detection in Arabic and Turkish Tweets Using BERT Based Architectures","authors":["K Singhal, J Bedi - Proceedings of the 7th Workshop on Challenges and …, 2024"],"snippet":"Over the past years, researchers across the globe have made significant efforts to develop systems capable of identifying the presence of hate speech in different languages. This paper describes the team Transformers’ submission to the subtasks …","url":["https://aclanthology.org/2024.case-1.26.pdf"]}
-{"year":"2024","title":"Transformers for Detection of Distressed Cardiac Patients with an ICD Based on Danish Text Messages","authors":["JDW Andersen, ML Jensen, UK Wiil, S Skovbakke… - 2023 IEEE International …, 2023"],"snippet":"Cardiac patients with implantable cardioverter defibrillator devices frequently exhibit signs of anxiety and depression (termed \"Distressed\"). Early detection of these patients is vital for evaluation, intervention, and prevention against relapse …","url":["https://ieeexplore.ieee.org/abstract/document/10385964/"]}
-{"year":"2024","title":"Transformers on Dynamical Systems-An Exploration of In-context Learning","authors":["S Sanghavi - 2023"],"snippet":"Large Language Models (LLMs) have shown to be highly effective at performing in-context learning, where, given a prompt, the model can learn from the prompt and complete the sequence without needing to perform additional gradient steps or fine-tuning. In …","url":["https://www2.eecs.berkeley.edu/Pubs/TechRpts/2023/EECS-2023-287.pdf"]}
-{"year":"2024","title":"Transformers@ DravidianLangTech-EACL2024: Sentiment Analysis of Code-Mixed Tamil Using RoBERTa","authors":["K Singhal, J Bedi - Proceedings of the Fourth Workshop on Speech, Vision …, 2024"],"snippet":"In recent years, there has been a persistent focus on developing systems that can automatically identify the hate speech content circulating on diverse social media platforms. This paper describes the team Transformers’ submission to the Caste/Immigration …","url":["https://aclanthology.org/2024.dravidianlangtech-1.25.pdf"]}
-{"year":"2024","title":"Transformers@ LT-EDI-EACL2024: Caste and Migration Hate Speech Detection in Tamil Using Ensembling on Transformers","authors":["K Singhal, J Bedi - Proceedings of the Fourth Workshop on Language …, 2024"],"snippet":"In recent years, there has been a persistent focus on developing systems that can automatically identify the hate speech content circulating on diverse social media platforms. This paper describes the team “Transformers” submission to the Caste …","url":["https://aclanthology.org/2024.ltedi-1.32.pdf"]}
-{"year":"2024","title":"Transforming Conversational AI","authors":["M McTear, M Ashurkina"],"snippet":"We were motivated to write this book by the launch in November 2022 of ChatGPT and by the ensuing excitement and disruption across the world of Conversational AI. The book is written for a broad audience who are already working, starting to work …","url":["https://link.springer.com/content/pdf/10.1007/979-8-8688-0110-5.pdf"]}
-{"year":"2024","title":"Transforming Dutch: Debiasing Dutch Corefence Resolution Systems for Non-binary Pronouns","authors":["G Boven - 2024"],"snippet":"Gender-neutral pronouns are increasingly being introduced across Western languages, and are continuously more frequently being adopted by non-binary individuals. Recent evaluations have however demonstrated that English language …","url":["https://studenttheses.uu.nl/bitstream/handle/20.500.12932/45908/Transforming_Dutch_ThesisAI_GoyavanBoven_Final.pdf?sequence=1&isAllowed=y"]}
-{"year":"2024","title":"TransGPT: Multi-modal Generative Pre-trained Transformer for Transportation","authors":["P Wang, X Wei, F Hu, W Han - arXiv preprint arXiv:2402.07233, 2024"],"snippet":"Natural language processing (NLP) is a key component of intelligent transportation systems (ITS), but it faces many challenges in the transportation domain, such as domain-specific knowledge and data, and multi-modal inputs and outputs. This …","url":["https://arxiv.org/pdf/2402.07233"]}
-{"year":"2024","title":"Translate-Distill: Learning Cross-Language Dense Retrieval by Translation and Distillation","authors":["E Yang, D Lawrie, J Mayfield, DW Oard, S Miller - arXiv preprint arXiv:2401.04810, 2024"],"snippet":"Prior work on English monolingual retrieval has shown that a cross-encoder trained using a large number of relevance judgments for query-document pairs can be used as a teacher to train more efficient, but similarly effective, dual-encoder student …","url":["https://arxiv.org/pdf/2401.04810"]}
-{"year":"2024","title":"Translating and predicting document structure for medical domain scientific abstracts","authors":["SA Rauf, F Yvon - Computer Speech & Language, 2024"],"snippet":"Abstract Machine Translation (MT) technologies have improved in many ways and generate usable outputs for a growing number of domains and language pairs. Yet, most sentence based MT systems struggle with contextual dependencies …","url":["https://www.sciencedirect.com/science/article/pii/S0885230824000068"]}
-{"year":"2024","title":"Translating scientific abstracts in the bio-medical domain with structure-aware models","authors":["SA Rauf, F Yvon - Computer Speech and Language, 2024"],"snippet":"Machine Translation (MT) technologies have improved in many ways and generate usable outputs for a growing number of domains and language pairs. Yet, most sentence based MT systems struggle with contextual dependencies, processing …","url":["https://hal.science/hal-04476788/document"]}
-{"year":"2024","title":"Translation from Historical to Contemporary Japanese Using Japanese T5","authors":["H Usui, K Komiya - Proceedings of the Joint 3rd International Conference …, 2023"],"snippet":"This paper presents machine translation from historical Japanese to contemporary Japanese using a Text-to-Text Transfer Transformer (T5). The result of the previous study that used neural machine translation (NMT), Long Short Term Memory (LSTM) …","url":["https://aclanthology.org/2023.nlp4dh-1.4.pdf"]}
-{"year":"2024","title":"Treading water: new data on the impact of AI ethics information sessions in classics and ancient language pedagogy","authors":["EAS Ross, J Baines - Journal of Classics Teaching, 2024"],"snippet":"Over 2023, many universities and policy organisations in the higher education (HE) sector are working to create guiding principles and guidelines for the use of generative artificial intelligence (AI) in HE Teaching and Learning (T&L). Despite …","url":["https://www.cambridge.org/core/services/aop-cambridge-core/content/view/7EC62BAA5E593C81DB991897729D16DF/S2058631024000412a.pdf/treading_water_new_data_on_the_impact_of_ai_ethics_information_sessions_in_classics_and_ancient_language_pedagogy.pdf"]}
-{"year":"2024","title":"Understanding College Students' Satisfaction With ChatGPT: An Exploratory And Predictive Machine Learning Approach Using Feature Engineering","authors":["K Pabreja, N Pabreja - MIER Journal of Educational Studies Trends and …, 2024"],"snippet":"Artificial Intelligence (AI) technologies are continually improving and becoming more pervasive in many facets of our lives. ChatGPT is one such cutting-edge artificial intelligence application, and it has received a lot of worldwide media attention …","url":["https://mierjs.in/index.php/mjestp/article/download/2568/1593"]}
-{"year":"2024","title":"Understanding Emergent Abilities of Language Models from the Loss Perspective","authors":["Z Du, A Zeng, Y Dong, J Tang - arXiv preprint arXiv:2403.15796, 2024"],"snippet":"Recent studies have put into question the belief that emergent abilities in language models are exclusive to large models. This skepticism arises from two observations: 1) smaller models can also exhibit high performance on emergent abilities and 2) …","url":["https://arxiv.org/pdf/2403.15796"]}
-{"year":"2024","title":"Understanding Large Language Models","authors":["T Amaratunga"],"snippet":"Today, finding someone who hasn’t heard of ChatGPT, the AI chatbot that took the world by storm, is hard. ChatGPT—and its competitors such as Google Bard, Microsoft Bing Chat, etc.—are part of a broader area in AI known as large language …","url":["https://link.springer.com/content/pdf/10.1007/979-8-8688-0017-7.pdf"]}
-{"year":"2024","title":"Understanding latent affective bias in large pre-trained neural language models","authors":["A Kadan, P Deepak, S Bhadra, MP Gangan, VL Lajish - Natural Language …, 2024"],"snippet":"Groundbreaking inventions and highly significant performance improvements in deep learning based Natural Language Processing are witnessed through the development of transformer based large Pre-trained Language Models (PLMs). The …","url":["https://www.sciencedirect.com/science/article/pii/S2949719124000104"]}
-{"year":"2024","title":"Understanding LLMs: A Comprehensive Overview from Training to Inference","authors":["Y Liu, H He, T Han, X Zhang, M Liu, J Tian, Y Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"… from the CommonCrawl. However, due to the presence of a substantial amount of low-quality data in web archives, preprocessing is essential when working with CommonCrawl data. Currently, four commonly used filtered datasets based on …","url":["https://arxiv.org/pdf/2401.02038"]}
-{"year":"2024","title":"Understanding New Machine Learning Architectures: Practical Generative Artificial Intelligence for Anesthesiologists","authors":["CW Connor - Anesthesiology, 2024"],"snippet":"Recent advances in neural networks have given rise to generative artificial intelligence, systems able to produce fluent responses to natural questions or attractive and even photorealistic images from text prompts. These systems were …","url":["https://pubs.asahq.org/anesthesiology/article/140/3/599/139780"]}
-{"year":"2024","title":"Understanding Privacy Risks of Embeddings Induced by Large Language Models","authors":["Z Zhu, N Shao, D Lian, C Wu, Z Liu, Y Yang, E Chen - arXiv preprint arXiv …, 2024"],"snippet":"… CC-News (CommonCrawl News dataset) is a dataset containing news articles from international news websites. It contains 708241 English-language news articles published between January 2017 and December 2019. Pile-PubMed is a …","url":["https://arxiv.org/pdf/2404.16587"]}
-{"year":"2024","title":"UNIVERSAL IMITATION GAMES","authors":["S Mahadevan - 2024"],"snippet":"In 1950, Alan Turing proposed a framework called an imitation game in which the participants are to be classified Human or Machine solely from natural language interactions. Using mathematics largely developed since Turing–category theory–we …","url":["https://people.cs.umass.edu/~mahadeva/papers/Universal_Imitation_Games_Final_Arxiv.pdf"]}
-{"year":"2024","title":"Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset","authors":["H Laurençon, L Tronchon, V Sanh - arXiv preprint arXiv:2403.09029, 2024"],"snippet":"… available online (and often captured in web crawls like Common Crawl) presents a tempting resource for generating pairs of screenshots and corresponding HTML codes by simply rendering the HTML and capturing the output. However, this …","url":["https://arxiv.org/pdf/2403.09029"]}
-{"year":"2024","title":"Unraveling the Mystery of Scaling Laws: Part I","authors":["H Su, Z Tian, X Shen, X Cai - arXiv preprint arXiv:2403.06563, 2024"],"snippet":"Scaling law principles indicate a power-law correlation between loss and variables such as model size, dataset size, and computational resources utilized during training. These principles play a vital role in optimizing various aspects of model pre-training …","url":["https://arxiv.org/html/2403.06563v1"]}
-{"year":"2024","title":"Unseen but influential associates: Properties of words' associates influence lexical and semantic processing","authors":["EJ Muraki, PM Pexman - Psychonomic Bulletin & Review, 2024"],"snippet":"In many models of lexical and semantic processing, it is assumed that single word processing is a function of the characteristics of the words presented and the distributional properties of the words’ networks. Recent research suggests that …","url":["https://link.springer.com/article/10.3758/s13423-024-02485-5"]}
-{"year":"2024","title":"Unsupervised LLM Adaptation for Question Answering","authors":["K Saito, K Sohn, CY Lee, Y Ushiku - arXiv preprint arXiv:2402.12170, 2024"],"snippet":"… Commoncrawl 2. The topics cover politics, sports, business, etc. To reduce the number of tokens, we ask ChatGPT to generate summaries. … We employ NewsFetch7 to crawl the news from Commoncrawl. The published date of the article …","url":["https://arxiv.org/pdf/2402.12170"]}
-{"year":"2024","title":"Unsupervised Outlier Detection for Language-Independent Text Quality Filtering","authors":["J Daðason, H Loftsson - Proceedings of the 3rd Annual Meeting of the Special …, 2024"],"snippet":"… Common Crawl (CC) is an organization that maintains a massive repository of data crawled … corpora, all of which are derived from Common Crawl. It consists of 6.3 trillion tokens in 167 … crawled sources, such as Common Crawl. The total size …","url":["https://aclanthology.org/2024.sigul-1.46.pdf"]}
-{"year":"2024","title":"UNVEILING THE COGNITIVE CAPACITY OF CHATGPT: ASSESSING ITS HUMAN-LIKE REASONING ABILITIES","authors":["J Oyeniyi"],"snippet":"… OpenAI utilizes a dataset termed Common Crawl, which is a collection of publicly available websites. This dataset includes billions of web pages and is one of the largest text datasets available. Meanwhile, this dataset is just a starting line. …","url":["https://www.researchgate.net/profile/Johnson-Oyeniyi/publication/379810137_UNVEILING_THE_COGNITIVE_CAPACITY_OF_CHATGPT_ASSESSING_ITS_HUMAN-LIKE_REASONING_ABILITIES/links/661ce53439e7641c0bc8fbf8/Unveiling-the-Cognitive-Capacity-of-ChatGPT-Assessing-its-Human-Like-Reasoning-Abilities.pdf"]}
-{"year":"2024","title":"Using Large Language Models to Probe Cognitive Constructs, Augment Data, and Design Instructional Materials","authors":["F Kieser, P Wulff - … in Educational Sciences: Approaches, Applications and …, 2024"],"snippet":"… It was shown that transformer-based large language models (LLMs could be pretrained on large language data sets such as the Common Crawl of the Internet, the Books Corpus, or Wikipedia, and then further fine-tuned in specific tasks [9, 10] …","url":["https://link.springer.com/chapter/10.1007/978-981-99-9379-6_14"]}
-{"year":"2024","title":"Using Large Language Models to Understand Telecom Standards","authors":["A Karapantelakis, M Shakur, A Nikou, F Moradi… - arXiv preprint arXiv …, 2024"],"snippet":"… They have billions of parameters and are trained on corpora such as Common Crawl [5]. For foundation models to adapt to application domains, such as telecommunications, prompt engineering and fine-tuning approaches are used …","url":["https://arxiv.org/pdf/2404.02929"]}
-{"year":"2024","title":"Using rhetorical strategies to design prompts: a human-in-the-loop approach to make AI useful","authors":["N Ranade, M Saravia, A Johri - AI & SOCIETY, 2024"],"snippet":"… It consumed the text content of the popular CommonCrawl dataset of web pages from 2016 to 2019. Although OpenAI curated it to eliminate redundancy and improve quality, it is nominally 45-terabytes worth of compressed text data. …","url":["https://link.springer.com/article/10.1007/s00146-024-01905-3"]}
-{"year":"2024","title":"UzRoberta: A pre-trained language model for Uzbek","authors":["R Davronov, F Adilova - AIP Conference Proceedings, 2024"],"snippet":"… Common Crawl datasets, was generated distributed word representations for 157 different languages [8]. Author’s Uzbek Wikipedia model has 110K words, compared to -830K words in the Common Crawl … It is pre-trained on 2.5TB of filtered …","url":["https://pubs.aip.org/aip/acp/article/3004/1/050001/3270462"]}
-{"year":"2024","title":"UZROBERTA: AN UZBEK LANGUAGE PRE-TRAINED MODEL","authors":["F Adilova, R Davronov, R Safarov - Universum: технические науки, 2023"],"snippet":"… Distributed word representations for 157 distinct languages were created using the Wikipedia and Common Crawl databases [8]. The author's Uzbek Wikipedia model has 110K words, but the Common Crawl model only has 830K words. They …","url":["https://cyberleninka.ru/article/n/uzroberta-an-uzbek-language-pre-trained-model"]}
-{"year":"2024","title":"Validating and Exploring Large Geographic Corpora","authors":["J Dunn - arXiv preprint arXiv:2403.08198, 2024"],"snippet":"… Beginning with a 427 billion word corpus derived from the Common Crawl, three methods are used to improve the quality of sub-corpora representing specific language-country pairs … This paper starts with an existing web corpus derived …","url":["https://arxiv.org/pdf/2403.08198"]}
-{"year":"2024","title":"VERB: Visualizing and Interpreting Bias Mitigation Techniques Geometrically for Word Representations","authors":["YAN ZHENG, CCM YEH, J WANG, WEI ZHANG - 2024"],"snippet":"Complicated and massive datasets are becoming more and more commonly represented as vectorized embeddings. They are part of a de facto model for words in word vector embeddings such as Word2Vec [51] and GloVe [54], and are …","url":["https://scholar.archive.org/work/2ppdkjgmevgzhe4lcnrni2nqaa/access/wayback/https://dl.acm.org/doi/pdf/10.1145/3604433"]}
-{"year":"2024","title":"Verifying Claims About Metaphors with Large-Scale Automatic Metaphor Identification","authors":["K Aono, R Sasano, K Takeda - arXiv preprint arXiv:2404.01029, 2024"],"snippet":"… Third, in this study, the examples were collected from CommonCrawl, which is a corpus of texts on the Web, and thus contains mostly written language. It is unknown whether similar results can be obtained when analyzing examples collected from a …","url":["https://arxiv.org/pdf/2404.01029"]}
-{"year":"2024","title":"ViHateT5: Enhancing Hate Speech Detection in Vietnamese With A Unified Text-to-Text Transformer Model","authors":["LT Nguyen - arXiv preprint arXiv:2405.14141, 2024"],"snippet":"… Leveraging a Transformer architecture and trained on a massive dataset of 2.5TB filtered CommonCrawl text across 100 languages, it employs a masked language modeling (MLM) objective to learn crosslingual representations. This approach …","url":["https://arxiv.org/pdf/2405.14141"]}
-{"year":"2024","title":"ViLLM-Eval: A Comprehensive Evaluation Suite for Vietnamese Large Language Models","authors":["TH Nguyen, AC Le, VC Nguyen - arXiv preprint arXiv:2404.11086, 2024"],"snippet":"The rapid advancement of large language models (LLMs) necessitates the development of new benchmarks to accurately assess their capabilities. To address this need for Vietnamese, this work aims to introduce ViLLM-Eval, the …","url":["https://arxiv.org/pdf/2404.11086"]}
-{"year":"2024","title":"VISION2UI: A Real-World Dataset with Layout for Code Generation from UI Designs","authors":["Y Gui, Z Li, Y Wan, Y Shi, H Zhang, Y Su, S Dong… - arXiv preprint arXiv …, 2024"],"snippet":"… we opt to create our dataset on top of the Common Crawl3 dataset. The Common Crawl dataset is a vast collection of Web page data from … This partial dataset from the original Common Crawl dataset includes 3.35 billion pages, amounting to a total …","url":["https://arxiv.org/pdf/2404.06369"]}
-{"year":"2024","title":"Visual Instruction Tuning towards General-Purpose Multimodal Model: A Survey","authors":["J Huang, J Zhang, K Jiang, H Qiu, S Lu - arXiv preprint arXiv:2312.16602, 2023"],"snippet":"Traditional computer vision generally solves each single task independently by a dedicated model with the task instruction implicitly designed in the model architecture, arising two limitations: (1) it leads to task-specific models, which require …","url":["https://arxiv.org/pdf/2312.16602"]}
-{"year":"2024","title":"VLUE: A New Benchmark and Multi-task Knowledge Transfer Learning for Vietnamese Natural Language Understanding","authors":["PNT Do, SQ Tran, PG Hoang, K Van Nguyen… - arXiv preprint arXiv …, 2024"],"snippet":"… 250002 multilingual CommonCrawl XLM-Robertalarge … This model was trained on a Transformers-based masked language task using two terabytes of CommonCrawl data across more than a hundred languages. The model has two …","url":["https://arxiv.org/html/2403.15882v1"]}
-{"year":"2024","title":"WaCadie: Towards an Acadian French Corpus","authors":["J Robichaud, P Cook - Proceedings of the 2024 Joint International Conference …, 2024"],"snippet":"… We treat each post as one document, similar to one website’s HTML from the Common Crawl corpus. We refer to this corpus as r/acadie. … We used CommonCrawl’s extensive database and scraped New Brunswick (.nb.ca) websites …","url":["https://aclanthology.org/2024.lrec-main.1514.pdf"]}
-{"year":"2024","title":"WanJuan-CC: A Safe and High-Quality Open-sourced English Webtext Dataset","authors":["J Qiu, H Lv, Z Jin, R Wang, W Ning, J Yu, CB Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"… Moreover, Common Crawl contains a large amount of unsafe content, such as toxic and pornographic … Common Crawl data, which includes data extraction, heuristic rule filtering, fuzzy deduplication, content safety filtering, and data quality …","url":["https://arxiv.org/pdf/2402.19282"]}
-{"year":"2024","title":"WCC-EC 2.0: Enhancing Neural Machine Translation with a 1.6 M+ Web-Crawled English-Chinese Parallel Corpus","authors":["J Zhang, K Su, Y Tian, T Matsumoto - Electronics, 2024"],"snippet":"This research introduces WCC-EC 2.0 (Web-Crawled Corpus—English and Chinese), a comprehensive parallel corpus designed for enhancing Neural Machine Translation (NMT), featuring over 1.6 million English-Chinese sentence pairs …","url":["https://www.mdpi.com/2079-9292/13/7/1381/pdf"]}
-{"year":"2024","title":"We have no idea what we are walking into: AI and ethical considerations","authors":["KB Forrest - Annals of the New York Academy of Sciences, 2024"],"snippet":"… called “Common Crawl” provide data, “C4” is a curated (de-duplicated and some nonsensical junk eliminated) set of the Common Crawl data, then there is a data set well named “The Pile”, and others that are compilations of books, music …","url":["https://nyaspubs.onlinelibrary.wiley.com/doi/abs/10.1111/nyas.15133"]}
-{"year":"2024","title":"Weakly supervised learning for an effective focused web crawler","authors":["PRJ Dhanith, K Saeed, G Rohith, SP Raja - Engineering Applications of Artificial …, 2024"],"snippet":"Focused crawler traverses the Web to only collect pages that are relevant to a particular topic, and is increasingly considered as a way to get around the scalability issues with current general-purpose search engines. But the data diversity in the …","url":["https://www.sciencedirect.com/science/article/pii/S0952197624001027"]}
-{"year":"2024","title":"Web Crawl Refusals: Insights From Common Crawl","authors":["M Ansar - 2024"],"snippet":"… Abstract: This study investigates server-side blocks encountered by Common Crawl, a major … that approximately 1.68% of websites in a Common Crawl snapshot exhibit some form of explicit … of these blocks and the effectiveness of …","url":["http://essay.utwente.nl/98890/"]}
-{"year":"2024","title":"Web Data Commons-RDFa, Microdata, Embedded JSON-LD, and Microformats Data Sets-October 2023","authors":["A Brinkmann, C Bizer - 2024"],"snippet":"The Web Data Commons RDFa, Microdata and Microformats data sets has been extracted from the September/October 2023 release of the Common Crawl. In summary, we found structured data within 1.7 billion HTML pages out of the 3.4 …","url":["https://madata.bib.uni-mannheim.de/429/"]}
-{"year":"2024","title":"Web Data Commons-Schema. org Table Corpus 2023","authors":["R Peeters, A Brinkmann, C Bizer - 2024"],"snippet":"The WDC schema.org Table Corpus consists of ~5 million relational tables which were generated by extracting schema.org data from the Common Crawl and grouping the data into seperate tables for each class/host combination, eg all …","url":["https://madata.bib.uni-mannheim.de/430/"]}
-{"year":"2024","title":"Web scraping and Generative Models training in the Directive 790/19","authors":["C Gallese - i-lex, 2023"],"snippet":"… The companies that created GM never disclosed the exact corpus of training data they employed to train their models; however, it has become clear sources that many copyrighted materials were employed as part of larger datasets such as the …","url":["https://i-lex.unibo.it/article/download/18871/17439"]}
-{"year":"2024","title":"WebCiteS: Attributed Query-Focused Summarization on Chinese Web Search Results with Citations","authors":["H Deng, C Wang, X Li, D Yuan, J Zhan, T Zhou, J Ma… - arXiv preprint arXiv …, 2024"],"snippet":"Enhancing the attribution in large language models (LLMs) is a crucial task. One feasible approach is to enable LLMs to cite external sources that support their generations. However, existing datasets and evaluation methods in this domain still …","url":["https://arxiv.org/pdf/2403.01774"]}
-{"year":"2024","title":"WebGraph: The Next Generation (Is in Rust)","authors":["T Fontana, S Vigna, S Zacchiroli - ACM Web Conference 2024, 2024"],"snippet":"We report the results of a yearlong effort to port the WebGraph framework from Java to Rust. For two decades WebGraph has been instrumental in the analysis and distribution of large graphs for the research community of TheWebConf, but the …","url":["https://hal.science/hal-04494627/document"]}
-{"year":"2024","title":"What are Large Language Models Made of?","authors":["C Stinson - Leading the Way: Envisioning the Future of Higher …, 2024"],"snippet":"… CommonCrawl is the lowest quality but largest of these datasets, consisting of text scraped from all over the web. Their data from the years 2016 to 2019 were used to train GPT-3. OpenAI’s quality control measure for filtering CommonCrawl was to …","url":["https://ecampusontario.pressbooks.pub/futureofhighereducation/chapter/what-are-large-language-models-made-of/"]}
-{"year":"2024","title":"What's in a Name? Experimental Evidence of Gender Bias in Recommendation Letters Generated by ChatGPT","authors":["DM Kaplan, R Palitsky, SJ Arconada Alvarez… - Journal of Medical Internet …, 2024"],"snippet":"… In the case of GPT-3.5 (the current version at the time of this study), the model contains 175 billion parameters and was trained with commonly available text training sets that represent a broad swath of data on the internet (Common Crawl) …","url":["https://www.jmir.org/2024/1/e51837/"]}
-{"year":"2024","title":"When Young Scholars Cooperate with LLMs in Academic Tasks: The Influence of Individual Differences and Task Complexities","authors":["J Wang, C Huang, S Yan, W Xie, D He - International Journal of Human–Computer …, 2024"],"snippet":"As a novel AI-powered conversational system, large language models (LLMs) have the potential to be used in various applications. Recent advances in LLMs like ChatGPT have made LLM-based academic tools possible. However, most of the …","url":["https://www.tandfonline.com/doi/abs/10.1080/10447318.2024.2352919"]}
-{"year":"2024","title":"Where does In-context Translation Happen in Large Language Models","authors":["S Sia, D Mueller, K Duh - arXiv preprint arXiv:2403.04510, 2024"],"snippet":"Self-supervised large language models have demonstrated the ability to perform Machine Translation (MT) via in-context learning, but little is known about where the model performs the task with respect to prompt instructions and demonstration …","url":["https://arxiv.org/html/2403.04510v1"]}
-{"year":"2024","title":"Which Word Embeddings for Modeling Web Search Queries? Application to the Study of Search Strategies","authors":["C Ibarboure, L Tanguy, F Amadieu - 2023"],"snippet":"In order to represent the global strategies deployed by a user during an information retrieval session on the Web, we compare different pretrained vector models capable of representing the queries submitted to a search engine. More precisely …","url":["https://www.scitepress.org/Papers/2023/121776/121776.pdf"]}
-{"year":"2024","title":"Who's Afraid of ChatGPT?: Large Language Models and Conspiracies","authors":["J Laudun - Contemporary Legend, 2024"],"snippet":"… GPT-3 added Common Crawl to the training datasets, 570GB of text obtained after filtering from 45TB of plaintext. The filtering was done by comparing new documents to documents in WebText, with the latter acting as a proxy for high-quality …","url":["https://scholarworks.iu.edu/journals/index.php/cl/article/download/38419/40746"]}
-{"year":"2024","title":"Willkommens-Merkel, Chaos-Johnson, and Tore-Klose: Modeling the Evaluative Meaning of German Personal Name Compounds","authors":["AETDA Blessing, M Belosevic"],"snippet":"We present a comprehensive computational study of the under-investigated phenomenon of personal name compounds (PNCs) in German such as Willkommens-Merkel (‘Welcome-Merkel’). Prevalent in news, social media, and …","url":["https://openreview.net/pdf?id=GHLROxS7Fh"]}
-{"year":"2024","title":"Worldwide Federated Training of Language Models","authors":["A Iacob, L Sani, B Marino, P Aleksandrov, ND Lane - arXiv preprint arXiv:2405.14446, 2024"],"snippet":"… To simulate geographically distributed systems, we use a subset of Multilingual Colossal Common Crawl (mC4)[81], covering high and low-… For IID experiments, we use the standard Cleaned Colossal Common Crawl (C4) English dataset …","url":["https://arxiv.org/pdf/2405.14446"]}
-{"year":"2024","title":"WRITTEN IN PERSIAN USING A TRANSFORMER-BASED MODEL","authors":["T Firoozi, MJ Gierl - The Routledge International Handbook of Automated …, 2024"],"snippet":"… This model is created using contents from Common Crawl and Wikipedia. It is trained using CBOW with position weights, in dimension 300, with character n-grams of length 5, and a window of size 5 and 10. The model gives 300-dimensional vector …","url":["https://books.google.de/books?hl=en&lr=lang_en&id=3-UFEQAAQBAJ&oi=fnd&pg=PA55&dq=commoncrawl&ots=pOzjIBhsMA&sig=n-gWEJHSQ9_8r8O4JLKLSCq2r2M"]}
-{"year":"2024","title":"X-Phishing-Writer: A Framework for Cross-Lingual Phishing Email Generation","authors":["SW Guo, YC Fan - ACM Transactions on Asian and Low-Resource …, 2024"],"snippet":"… The mBART model employs various language corpora from the Common Crawl dataset and undergoes multilingual pretraining based on the BART architecture. The training data is a concatenation of data from � diferent languages, denoted as � = �1,�2...�� …","url":["https://dl.acm.org/doi/pdf/10.1145/3670402"]}
-{"year":"2024","title":"XLMR4MD: New Vietnamese dataset and framework for detecting the consistency of description and permission in Android applications using large language models","authors":["QN Nguyen, NT Cam, K Van Nguyen - Computers & Security, 2024"],"snippet":"… The most significant update that XLMRoBERTa provides compared to the original is that the amount of training data has increased significantly, the cleaned CommonCrawl data it was trained on takes up a considerable memory block of up to …","url":["https://www.sciencedirect.com/science/article/pii/S0167404824001159"]}
-{"year":"2024","title":"XLORE 3: A Large-scale Multilingual Knowledge Graph from Heterogeneous Wiki Knowledge Resources","authors":["K Zeng, H Jin, X Lv, F Zhu, L Hou, Y Zhang, F Pang… - ACM Transactions on …, 2024"],"snippet":"In recent years, Knowledge Graph (KG) has attracted significant attention from academia and industry, resulting in the development of numerous technologies for KG construction, completion, and application. XLORE is one of the largest …","url":["https://dl.acm.org/doi/pdf/10.1145/3660521"]}
-{"year":"2024","title":"Yi: Open Foundation Models by 01. AI","authors":["A Young, B Chen, C Li, C Huang, G Zhang, G Zhang… - arXiv preprint arXiv …, 2024"],"snippet":"… We start with web documents from Common Crawl, use the CCNet pipeline [79] for language identification and perplexity scoring. Then … Notably, the Chinese content extracted from Common Crawl present unique challenges, particularly with a …","url":["https://arxiv.org/pdf/2403.04652"]}
-{"year":"2024","title":"Yuan 2.0-M32: Mixture of Experts with Attention Router","authors":["S Wu, J Luo, X Chen, L Li, X Zhao, T Yu, C Wang… - arXiv preprint arXiv …, 2024"],"snippet":"Yuan 2.0-M32, with a similar base architecture as Yuan-2.0 2B, uses a mixture-of-experts architecture with 32 experts of which 2 experts are active. A new router network, Attention Router, is proposed and adopted for a more efficient selection of experts …","url":["https://arxiv.org/pdf/2405.17976"]}
-{"year":"2024","title":"Zero-Shot Distillation for Image Encoders: How to Make Effective Use of Synthetic Data","authors":["N Popp, JH Metzen, M Hein - arXiv preprint arXiv:2404.16637, 2024"],"snippet":"… The first one involves relying on large-scale data such as common crawl datasets [7,38]. While this approach is feasible for large foundation models, it poses challenges for smaller models as these lack the same level of generalization capabilities due to …","url":["https://arxiv.org/pdf/2404.16637"]}
-{"year":"2024","title":"Zero-shot learning for multilingual discourse relation classification","authors":["E Metheniti, P Muller, C Braud, M Hernández-Casas - 5th Workshop on …, 2024"],"snippet":"Classifying discourse relations is a hard task: discourse-annotated data is scarce, especially for languages other than English, and there exist different theoretical frameworks that affect textual spans to be linked and the label set used. Thus, work …","url":["https://hal.science/hal-04483805/document"]}
-{"year":"2024","title":"Zero-shot Sentiment Analysis in Low-Resource Languages Using a Multilingual Sentiment Lexicon","authors":["F Koto, T Beck, Z Talat, I Gurevych, T Baldwin - arXiv preprint arXiv:2402.02113, 2024"],"snippet":"Improving multilingual language models capabilities in low-resource languages is generally difficult due to the scarcity of large-scale data in those languages. In this paper, we relax the reliance on texts in low-resource languages by using …","url":["https://arxiv.org/pdf/2402.02113"]}
-{"year":"2024","title":"ZS4C: Zero-Shot Synthesis of Compilable Code for Incomplete Code Snippets using ChatGPT","authors":["A Kabir, S Wang, Y Tian, M Asaduzzaman, W Zhang - arXiv preprint arXiv …, 2024"],"snippet":"Technical question and answering (Q&A) sites such as Stack Overflow have become an important source for software developers to seek knowledge. However, code snippets on Q&A sites are usually uncompilable and semantically incomplete for …","url":["https://arxiv.org/pdf/2401.14279"]}
-{"year":"2024","title":"Zyda: A 1.3 T Dataset for Open Language Modeling","authors":["Y Tokpanov, B Millidge, P Glorioso, J Pilault, A Ibrahim… - arXiv preprint arXiv …, 2024"],"snippet":"… Additionally, unlike these works which directly filter from Common Crawl, we aim to instead collect and collate existing open-source datasets under one banner, and to uniformly filter and deduplicate them against one another so as to create a dataset …","url":["https://arxiv.org/pdf/2406.01981"]}