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1,906.03741 | BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent
Summarization | ['Eva Sharma', 'Chen Li', 'Lu Wang'] | ['cs.CL', 'cs.LG'] | Most existing text summarization datasets are compiled from the news domain,
where summaries have a flattened discourse structure. In such datasets,
summary-worthy content often appears in the beginning of input articles.
Moreover, large segments from input articles are present verbatim in their
respective summaries. T... | 2019-06-10T00:24:26Z | Proceedings of the 57th Annual Meeting of the Association for
Computational Linguistics. ACL 2019 (10 pages) | null | null | BIGPATENT: A Large-Scale Dataset for Abstractive and Coherent Summarization | ['Eva Sharma', 'Chen Li', 'Lu Wang'] | 2,019 | Annual Meeting of the Association for Computational Linguistics | 224 | 40 | ['Computer Science'] |
1,906.04032 | Neural Spline Flows | ['Conor Durkan', 'Artur Bekasov', 'Iain Murray', 'George Papamakarios'] | ['stat.ML', 'cs.LG'] | A normalizing flow models a complex probability density as an invertible
transformation of a simple base density. Flows based on either coupling or
autoregressive transforms both offer exact density evaluation and sampling, but
rely on the parameterization of an easily invertible elementwise
transformation, whose choic... | 2019-06-10T14:43:23Z | Published at the 33rd Conference on Neural Information Processing
Systems (NeurIPS 2019), Vancouver, Canada | null | null | null | null | null | null | null | null | null |
1,906.04571 | Counterfactual Data Augmentation for Mitigating Gender Stereotypes in
Languages with Rich Morphology | ['Ran Zmigrod', 'Sabrina J. Mielke', 'Hanna Wallach', 'Ryan Cotterell'] | ['cs.CL'] | Gender stereotypes are manifest in most of the world's languages and are
consequently propagated or amplified by NLP systems. Although research has
focused on mitigating gender stereotypes in English, the approaches that are
commonly employed produce ungrammatical sentences in morphologically rich
languages. We present... | 2019-06-11T13:22:24Z | ACL 2019 | null | null | null | null | null | null | null | null | null |
1,906.05317 | COMET: Commonsense Transformers for Automatic Knowledge Graph
Construction | ['Antoine Bosselut', 'Hannah Rashkin', 'Maarten Sap', 'Chaitanya Malaviya', 'Asli Celikyilmaz', 'Yejin Choi'] | ['cs.CL', 'cs.AI'] | We present the first comprehensive study on automatic knowledge base
construction for two prevalent commonsense knowledge graphs: ATOMIC (Sap et
al., 2019) and ConceptNet (Speer et al., 2017). Contrary to many conventional
KBs that store knowledge with canonical templates, commonsense KBs only store
loosely structured ... | 2019-06-12T18:11:20Z | Accepted to ACL 2019 | null | null | null | null | null | null | null | null | null |
1,906.05474 | Transfer Learning in Biomedical Natural Language Processing: An
Evaluation of BERT and ELMo on Ten Benchmarking Datasets | ['Yifan Peng', 'Shankai Yan', 'Zhiyong Lu'] | ['cs.CL'] | Inspired by the success of the General Language Understanding Evaluation
benchmark, we introduce the Biomedical Language Understanding Evaluation (BLUE)
benchmark to facilitate research in the development of pre-training language
representations in the biomedicine domain. The benchmark consists of five tasks
with ten d... | 2019-06-13T04:07:12Z | Accepted by BioNLP 2019 | null | null | Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets | ['Yifan Peng', 'Shankai Yan', 'Zhiyong Lu'] | 2,019 | BioNLP@ACL | 847 | 44 | ['Computer Science'] |
1,906.05856 | Detecting Photoshopped Faces by Scripting Photoshop | ['Sheng-Yu Wang', 'Oliver Wang', 'Andrew Owens', 'Richard Zhang', 'Alexei A. Efros'] | ['cs.CV'] | Most malicious photo manipulations are created using standard image editing
tools, such as Adobe Photoshop. We present a method for detecting one very
popular Photoshop manipulation -- image warping applied to human faces -- using
a model trained entirely using fake images that were automatically generated by
scripting... | 2019-06-13T17:59:02Z | null | null | null | null | null | null | null | null | null | null |
1,906.05963 | Image Captioning: Transforming Objects into Words | ['Simao Herdade', 'Armin Kappeler', 'Kofi Boakye', 'Joao Soares'] | ['cs.CV', 'cs.CL'] | Image captioning models typically follow an encoder-decoder architecture
which uses abstract image feature vectors as input to the encoder. One of the
most successful algorithms uses feature vectors extracted from the region
proposals obtained from an object detector. In this work we introduce the
Object Relation Trans... | 2019-06-14T00:00:29Z | 10 pages | null | null | Image Captioning: Transforming Objects into Words | ['Simão Herdade', 'Armin Kappeler', 'K. Boakye', 'Joao Soares'] | 2,019 | Neural Information Processing Systems | 476 | 31 | ['Computer Science'] |
1,906.06972 | EnlightenGAN: Deep Light Enhancement without Paired Supervision | ['Yifan Jiang', 'Xinyu Gong', 'Ding Liu', 'Yu Cheng', 'Chen Fang', 'Xiaohui Shen', 'Jianchao Yang', 'Pan Zhou', 'Zhangyang Wang'] | ['cs.CV', 'eess.IV'] | Deep learning-based methods have achieved remarkable success in image
restoration and enhancement, but are they still competitive when there is a
lack of paired training data? As one such example, this paper explores the
low-light image enhancement problem, where in practice it is extremely
challenging to simultaneousl... | 2019-06-17T11:54:20Z | null | null | null | EnlightenGAN: Deep Light Enhancement Without Paired Supervision | ['Yifan Jiang', 'Xinyu Gong', 'Ding Liu', 'Yu Cheng', 'Chen Fang', 'Xiaohui Shen', 'Jianchao Yang', 'Pan Zhou', 'Zhangyang Wang'] | 2,019 | IEEE Transactions on Image Processing | 1,602 | 60 | ['Computer Science', 'Medicine', 'Engineering'] |
1,906.07348 | Zero-Shot Entity Linking by Reading Entity Descriptions | ['Lajanugen Logeswaran', 'Ming-Wei Chang', 'Kenton Lee', 'Kristina Toutanova', 'Jacob Devlin', 'Honglak Lee'] | ['cs.CL', 'cs.LG'] | We present the zero-shot entity linking task, where mentions must be linked
to unseen entities without in-domain labeled data. The goal is to enable robust
transfer to highly specialized domains, and so no metadata or alias tables are
assumed. In this setting, entities are only identified by text descriptions,
and mode... | 2019-06-18T02:36:39Z | ACL 2019 | null | null | null | null | null | null | null | null | null |
1,906.08101 | Pre-Training with Whole Word Masking for Chinese BERT | ['Yiming Cui', 'Wanxiang Che', 'Ting Liu', 'Bing Qin', 'Ziqing Yang'] | ['cs.CL', 'cs.LG'] | Bidirectional Encoder Representations from Transformers (BERT) has shown
marvelous improvements across various NLP tasks, and its consecutive variants
have been proposed to further improve the performance of the pre-trained
language models. In this paper, we aim to first introduce the whole word
masking (wwm) strategy ... | 2019-06-19T13:54:25Z | 11 pages. Journal extension to arXiv:2004.13922 | IEEE/ACM Transactions on Audio, Speech, and Language Processing
(2021) | 10.1109/TASLP.2021.3124365 | Pre-Training With Whole Word Masking for Chinese BERT | ['Yiming Cui', 'Wanxiang Che', 'Ting Liu', 'Bing Qin', 'Ziqing Yang'] | 2,019 | IEEE/ACM Transactions on Audio Speech and Language Processing | 186 | 46 | ['Computer Science'] |
1,906.08237 | XLNet: Generalized Autoregressive Pretraining for Language Understanding | ['Zhilin Yang', 'Zihang Dai', 'Yiming Yang', 'Jaime Carbonell', 'Ruslan Salakhutdinov', 'Quoc V. Le'] | ['cs.CL', 'cs.LG'] | With the capability of modeling bidirectional contexts, denoising
autoencoding based pretraining like BERT achieves better performance than
pretraining approaches based on autoregressive language modeling. However,
relying on corrupting the input with masks, BERT neglects dependency between
the masked positions and suf... | 2019-06-19T17:35:48Z | Pretrained models and code are available at
https://github.com/zihangdai/xlnet | null | null | null | null | null | null | null | null | null |
1,906.12021 | Densely Residual Laplacian Super-Resolution | ['Saeed Anwar', 'Nick Barnes'] | ['eess.IV', 'cs.CV'] | Super-Resolution convolutional neural networks have recently demonstrated
high-quality restoration for single images. However, existing algorithms often
require very deep architectures and long training times. Furthermore, current
convolutional neural networks for super-resolution are unable to exploit
features at mult... | 2019-06-28T02:32:44Z | null | null | null | Densely Residual Laplacian Super-Resolution | ['Saeed Anwar', 'Nick Barnes'] | 2,019 | IEEE Transactions on Pattern Analysis and Machine Intelligence | 230 | 57 | ['Computer Science', 'Engineering', 'Medicine'] |
1,907.00409 | Evaluating Language Model Finetuning Techniques for Low-resource
Languages | ['Jan Christian Blaise Cruz', 'Charibeth Cheng'] | ['cs.CL'] | Unlike mainstream languages (such as English and French), low-resource
languages often suffer from a lack of expert-annotated corpora and benchmark
resources that make it hard to apply state-of-the-art techniques directly. In
this paper, we alleviate this scarcity problem for the low-resourced Filipino
language in two ... | 2019-06-30T16:32:28Z | Pretrained models and datasets available at
https://github.com/jcblaisecruz02/Tagalog-BERT | null | 10.13140/RG.2.2.23028.40322 | null | null | null | null | null | null | null |
1,907.00837 | XNect: Real-time Multi-Person 3D Motion Capture with a Single RGB Camera | ['Dushyant Mehta', 'Oleksandr Sotnychenko', 'Franziska Mueller', 'Weipeng Xu', 'Mohamed Elgharib', 'Pascal Fua', 'Hans-Peter Seidel', 'Helge Rhodin', 'Gerard Pons-Moll', 'Christian Theobalt'] | ['cs.CV', 'cs.GR'] | We present a real-time approach for multi-person 3D motion capture at over 30
fps using a single RGB camera. It operates successfully in generic scenes which
may contain occlusions by objects and by other people. Our method operates in
subsequent stages. The first stage is a convolutional neural network (CNN) that
esti... | 2019-07-01T14:59:02Z | To appear in ACM Transactions on Graphics (SIGGRAPH) 2020 | null | 10.1145/3386569.3392410 | null | null | null | null | null | null | null |
1,907.01341 | Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot
Cross-dataset Transfer | ['René Ranftl', 'Katrin Lasinger', 'David Hafner', 'Konrad Schindler', 'Vladlen Koltun'] | ['cs.CV'] | The success of monocular depth estimation relies on large and diverse
training sets. Due to the challenges associated with acquiring dense
ground-truth depth across different environments at scale, a number of datasets
with distinct characteristics and biases have emerged. We develop tools that
enable mixing multiple d... | 2019-07-02T13:16:52Z | To appear in TPAMI (accepted August 2020) | null | null | Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-Shot Cross-Dataset Transfer | ['René Ranftl', 'Katrin Lasinger', 'David Hafner', 'K. Schindler', 'V. Koltun'] | 2,019 | IEEE Transactions on Pattern Analysis and Machine Intelligence | 1,814 | 67 | ['Computer Science', 'Medicine'] |
1,907.0147 | Augmenting Self-attention with Persistent Memory | ['Sainbayar Sukhbaatar', 'Edouard Grave', 'Guillaume Lample', 'Herve Jegou', 'Armand Joulin'] | ['cs.LG', 'cs.CL', 'stat.ML'] | Transformer networks have lead to important progress in language modeling and
machine translation. These models include two consecutive modules, a
feed-forward layer and a self-attention layer. The latter allows the network to
capture long term dependencies and are often regarded as the key ingredient in
the success of... | 2019-07-02T15:56:20Z | null | null | null | null | null | null | null | null | null | null |
1,907.04307 | Multilingual Universal Sentence Encoder for Semantic Retrieval | ['Yinfei Yang', 'Daniel Cer', 'Amin Ahmad', 'Mandy Guo', 'Jax Law', 'Noah Constant', 'Gustavo Hernandez Abrego', 'Steve Yuan', 'Chris Tar', 'Yun-Hsuan Sung', 'Brian Strope', 'Ray Kurzweil'] | ['cs.CL'] | We introduce two pre-trained retrieval focused multilingual sentence encoding
models, respectively based on the Transformer and CNN model architectures. The
models embed text from 16 languages into a single semantic space using a
multi-task trained dual-encoder that learns tied representations using
translation based b... | 2019-07-09T17:46:17Z | 6 pages, 6 tables, 2 listings, and 1 figure | null | null | null | null | null | null | null | null | null |
1,907.05047 | BlazeFace: Sub-millisecond Neural Face Detection on Mobile GPUs | ['Valentin Bazarevsky', 'Yury Kartynnik', 'Andrey Vakunov', 'Karthik Raveendran', 'Matthias Grundmann'] | ['cs.CV'] | We present BlazeFace, a lightweight and well-performing face detector
tailored for mobile GPU inference. It runs at a speed of 200-1000+ FPS on
flagship devices. This super-realtime performance enables it to be applied to
any augmented reality pipeline that requires an accurate facial region of
interest as an input for... | 2019-07-11T08:40:08Z | 4 pages, 3 figures; CVPR Workshop on Computer Vision for Augmented
and Virtual Reality, Long Beach, CA, USA, 2019 | null | null | null | null | null | null | null | null | null |
1,907.05791 | WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from
Wikipedia | ['Holger Schwenk', 'Vishrav Chaudhary', 'Shuo Sun', 'Hongyu Gong', 'Francisco Guzmán'] | ['cs.CL'] | We present an approach based on multilingual sentence embeddings to
automatically extract parallel sentences from the content of Wikipedia articles
in 85 languages, including several dialects or low-resource languages. We do
not limit the the extraction process to alignments with English, but
systematically consider al... | 2019-07-10T23:57:30Z | 13 pages, 3 figures, 6 tables | null | null | null | null | null | null | null | null | null |
1,907.06292 | TWEETQA: A Social Media Focused Question Answering Dataset | ['Wenhan Xiong', 'Jiawei Wu', 'Hong Wang', 'Vivek Kulkarni', 'Mo Yu', 'Shiyu Chang', 'Xiaoxiao Guo', 'William Yang Wang'] | ['cs.CL'] | With social media becoming increasingly pop-ular on which lots of news and
real-time eventsare reported, developing automated questionanswering systems is
critical to the effective-ness of many applications that rely on real-time
knowledge. While previous datasets haveconcentrated on question answering (QA)
forformal t... | 2019-07-14T22:20:59Z | ACL 2019 | null | null | null | null | null | null | null | null | null |
1,907.06616 | Facebook FAIR's WMT19 News Translation Task Submission | ['Nathan Ng', 'Kyra Yee', 'Alexei Baevski', 'Myle Ott', 'Michael Auli', 'Sergey Edunov'] | ['cs.CL'] | This paper describes Facebook FAIR's submission to the WMT19 shared news
translation task. We participate in two language pairs and four language
directions, English <-> German and English <-> Russian. Following our
submission from last year, our baseline systems are large BPE-based transformer
models trained with the ... | 2019-07-15T17:22:54Z | 7 pages; WMT | null | null | Facebook FAIR’s WMT19 News Translation Task Submission | ['Nathan Ng', 'Kyra Yee', 'Alexei Baevski', 'Myle Ott', 'Michael Auli', 'Sergey Edunov'] | 2,019 | Conference on Machine Translation | 397 | 12 | ['Computer Science'] |
1,907.09006 | Forward-Backward Decoding for Regularizing End-to-End TTS | ['Yibin Zheng', 'Xi Wang', 'Lei He', 'Shifeng Pan', 'Frank K. Soong', 'Zhengqi Wen', 'Jianhua Tao'] | ['eess.AS', 'cs.CL', 'cs.SD'] | Neural end-to-end TTS can generate very high-quality synthesized speech, and
even close to human recording within similar domain text. However, it performs
unsatisfactory when scaling it to challenging test sets. One concern is that
the encoder-decoder with attention-based network adopts autoregressive
generative seque... | 2019-07-18T12:24:30Z | Accepted by INTERSPEECH2019. arXiv admin note: text overlap with
arXiv:1808.04064, arXiv:1804.05374 by other authors | null | null | null | null | null | null | null | null | null |
1,907.09595 | MixConv: Mixed Depthwise Convolutional Kernels | ['Mingxing Tan', 'Quoc V. Le'] | ['cs.CV', 'cs.LG'] | Depthwise convolution is becoming increasingly popular in modern efficient
ConvNets, but its kernel size is often overlooked. In this paper, we
systematically study the impact of different kernel sizes, and observe that
combining the benefits of multiple kernel sizes can lead to better accuracy and
efficiency. Based on... | 2019-07-22T21:49:25Z | BMVC 2019 | BMVC 2019 | null | null | null | null | null | null | null | null |
1,907.10529 | SpanBERT: Improving Pre-training by Representing and Predicting Spans | ['Mandar Joshi', 'Danqi Chen', 'Yinhan Liu', 'Daniel S. Weld', 'Luke Zettlemoyer', 'Omer Levy'] | ['cs.CL', 'cs.LG'] | We present SpanBERT, a pre-training method that is designed to better
represent and predict spans of text. Our approach extends BERT by (1) masking
contiguous random spans, rather than random tokens, and (2) training the span
boundary representations to predict the entire content of the masked span,
without relying on ... | 2019-07-24T15:43:40Z | Accepted at TACL | null | null | SpanBERT: Improving Pre-training by Representing and Predicting Spans | ['Mandar Joshi', 'Danqi Chen', 'Yinhan Liu', 'Daniel S. Weld', 'Luke Zettlemoyer', 'Omer Levy'] | 2,019 | Transactions of the Association for Computational Linguistics | 1,974 | 58 | ['Computer Science'] |
1,907.10641 | WinoGrande: An Adversarial Winograd Schema Challenge at Scale | ['Keisuke Sakaguchi', 'Ronan Le Bras', 'Chandra Bhagavatula', 'Yejin Choi'] | ['cs.CL'] | The Winograd Schema Challenge (WSC) (Levesque, Davis, and Morgenstern 2011),
a benchmark for commonsense reasoning, is a set of 273 expert-crafted pronoun
resolution problems originally designed to be unsolvable for statistical models
that rely on selectional preferences or word associations. However, recent
advances i... | 2019-07-24T18:11:59Z | null | null | null | null | null | null | null | null | null | null |
1,907.11692 | RoBERTa: A Robustly Optimized BERT Pretraining Approach | ['Yinhan Liu', 'Myle Ott', 'Naman Goyal', 'Jingfei Du', 'Mandar Joshi', 'Danqi Chen', 'Omer Levy', 'Mike Lewis', 'Luke Zettlemoyer', 'Veselin Stoyanov'] | ['cs.CL'] | Language model pretraining has led to significant performance gains but
careful comparison between different approaches is challenging. Training is
computationally expensive, often done on private datasets of different sizes,
and, as we will show, hyperparameter choices have significant impact on the
final results. We ... | 2019-07-26T17:48:29Z | null | null | null | null | null | null | null | null | null | null |
1,907.12237 | KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks | ['Aleksei Tiulpin', 'Iaroslav Melekhov', 'Simo Saarakkala'] | ['cs.CV'] | This paper addresses the challenge of localization of anatomical landmarks in
knee X-ray images at different stages of osteoarthritis (OA). Landmark
localization can be viewed as regression problem, where the landmark position
is directly predicted by using the region of interest or even full-size images
leading to lar... | 2019-07-29T07:18:54Z | Accepted for Publication at ICCV 2019 VRMI Workshop | null | null | KNEEL: Knee Anatomical Landmark Localization Using Hourglass Networks | ['A. Tiulpin', 'Iaroslav Melekhov', 'S. Saarakkala'] | 2,019 | 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW) | 45 | 47 | ['Computer Science'] |
1,907.12412 | ERNIE 2.0: A Continual Pre-training Framework for Language Understanding | ['Yu Sun', 'Shuohuan Wang', 'Yukun Li', 'Shikun Feng', 'Hao Tian', 'Hua Wu', 'Haifeng Wang'] | ['cs.CL'] | Recently, pre-trained models have achieved state-of-the-art results in
various language understanding tasks, which indicates that pre-training on
large-scale corpora may play a crucial role in natural language processing.
Current pre-training procedures usually focus on training the model with
several simple tasks to g... | 2019-07-29T13:25:37Z | 11 pages, 3 figures and 7 tables; Accepted by AAAI 2020 | null | null | null | null | null | null | null | null | null |
1,907.12461 | Leveraging Pre-trained Checkpoints for Sequence Generation Tasks | ['Sascha Rothe', 'Shashi Narayan', 'Aliaksei Severyn'] | ['cs.CL'] | Unsupervised pre-training of large neural models has recently revolutionized
Natural Language Processing. By warm-starting from the publicly released
checkpoints, NLP practitioners have pushed the state-of-the-art on multiple
benchmarks while saving significant amounts of compute time. So far the focus
has been mainly ... | 2019-07-29T14:42:30Z | To be published in Transactions of the Association for Computational
Linguistics (TACL) | null | 10.1162/tacl_a_00313 | Leveraging Pre-trained Checkpoints for Sequence Generation Tasks | ['S. Rothe', 'Shashi Narayan', 'A. Severyn'] | 2,019 | Transactions of the Association for Computational Linguistics | 438 | 67 | ['Computer Science'] |
1,908.0266 | SpatialSense: An Adversarially Crowdsourced Benchmark for Spatial
Relation Recognition | ['Kaiyu Yang', 'Olga Russakovsky', 'Jia Deng'] | ['cs.CV'] | Understanding the spatial relations between objects in images is a
surprisingly challenging task. A chair may be "behind" a person even if it
appears to the left of the person in the image (depending on which way the
person is facing). Two students that appear close to each other in the image
may not in fact be "next t... | 2019-08-07T14:41:30Z | Accepted to ICCV 2019 | null | null | null | null | null | null | null | null | null |
1,908.03557 | VisualBERT: A Simple and Performant Baseline for Vision and Language | ['Liunian Harold Li', 'Mark Yatskar', 'Da Yin', 'Cho-Jui Hsieh', 'Kai-Wei Chang'] | ['cs.CV', 'cs.CL', 'cs.LG'] | We propose VisualBERT, a simple and flexible framework for modeling a broad
range of vision-and-language tasks. VisualBERT consists of a stack of
Transformer layers that implicitly align elements of an input text and regions
in an associated input image with self-attention. We further propose two
visually-grounded lang... | 2019-08-09T17:57:13Z | Work in Progress | null | null | VisualBERT: A Simple and Performant Baseline for Vision and Language | ['Liunian Harold Li', 'Mark Yatskar', 'Da Yin', 'Cho-Jui Hsieh', 'Kai-Wei Chang'] | 2,019 | arXiv.org | 1,975 | 42 | ['Computer Science'] |
1,908.03636 | Star-convex Polyhedra for 3D Object Detection and Segmentation in
Microscopy | ['Martin Weigert', 'Uwe Schmidt', 'Robert Haase', 'Ko Sugawara', 'Gene Myers'] | ['cs.CV'] | Accurate detection and segmentation of cell nuclei in volumetric (3D)
fluorescence microscopy datasets is an important step in many biomedical
research projects. Although many automated methods for these tasks exist, they
often struggle for images with low signal-to-noise ratios and/or dense packing
of nuclei. It was r... | 2019-08-09T21:22:29Z | Conference paper at WACV 2020 | null | 10.1109/WACV45572.2020.9093435 | null | null | null | null | null | null | null |
1,908.04212 | A Finnish News Corpus for Named Entity Recognition | ['Teemu Ruokolainen', 'Pekka Kauppinen', 'Miikka Silfverberg', 'Krister Lindén'] | ['cs.CL'] | We present a corpus of Finnish news articles with a manually prepared named
entity annotation. The corpus consists of 953 articles (193,742 word tokens)
with six named entity classes (organization, location, person, product, event,
and date). The articles are extracted from the archives of Digitoday, a Finnish
online t... | 2019-08-12T15:49:57Z | null | null | 10.1007/s10579-019-09471-7 | A Finnish news corpus for named entity recognition | ['T. Ruokolainen', 'Pekka Kauppinen', 'Miikka Silfverberg', 'Krister Lindén'] | 2,019 | Language Resources and Evaluation | 67 | 65 | ['Computer Science'] |
1,908.04577 | StructBERT: Incorporating Language Structures into Pre-training for Deep
Language Understanding | ['Wei Wang', 'Bin Bi', 'Ming Yan', 'Chen Wu', 'Zuyi Bao', 'Jiangnan Xia', 'Liwei Peng', 'Luo Si'] | ['cs.CL'] | Recently, the pre-trained language model, BERT (and its robustly optimized
version RoBERTa), has attracted a lot of attention in natural language
understanding (NLU), and achieved state-of-the-art accuracy in various NLU
tasks, such as sentiment classification, natural language inference, semantic
textual similarity an... | 2019-08-13T11:12:58Z | 10 Pages | null | null | null | null | null | null | null | null | null |
1,908.04913 | FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age | ['Kimmo Kärkkäinen', 'Jungseock Joo'] | ['cs.CV', 'cs.LG'] | Existing public face datasets are strongly biased toward Caucasian faces, and
other races (e.g., Latino) are significantly underrepresented. This can lead to
inconsistent model accuracy, limit the applicability of face analytic systems
to non-White race groups, and adversely affect research findings based on such
skewe... | 2019-08-14T01:42:41Z | null | null | null | null | null | null | null | null | null | null |
1,908.0676 | Self-Attention Based Molecule Representation for Predicting Drug-Target
Interaction | ['Bonggun Shin', 'Sungsoo Park', 'Keunsoo Kang', 'Joyce C. Ho'] | ['cs.LG', 'stat.ML'] | Predicting drug-target interactions (DTI) is an essential part of the drug
discovery process, which is an expensive process in terms of time and cost.
Therefore, reducing DTI cost could lead to reduced healthcare costs for a
patient. In addition, a precisely learned molecule representation in a DTI
model could contribu... | 2019-08-15T21:39:15Z | 18 pages, Proceedings of Machine Learning for Healthcare, 2019
(MLHC'19) | null | null | Self-Attention Based Molecule Representation for Predicting Drug-Target Interaction | ['Bonggun Shin', 'Sungsoo Park', 'Keunsoo Kang', 'Joyce Ho'] | 2,019 | Machine Learning in Health Care | 140 | 44 | ['Computer Science', 'Mathematics'] |
1,908.07245 | GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge | ['Luyao Huang', 'Chi Sun', 'Xipeng Qiu', 'Xuanjing Huang'] | ['cs.CL'] | Word Sense Disambiguation (WSD) aims to find the exact sense of an ambiguous
word in a particular context. Traditional supervised methods rarely take into
consideration the lexical resources like WordNet, which are widely utilized in
knowledge-based methods. Recent studies have shown the effectiveness of
incorporating ... | 2019-08-20T09:37:42Z | EMNLP-IJCNLP 2019 | null | null | GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge | ['Luyao Huang', 'Chi Sun', 'Xipeng Qiu', 'Xuanjing Huang'] | 2,019 | Conference on Empirical Methods in Natural Language Processing | 244 | 20 | ['Computer Science'] |
1,908.0749 | LXMERT: Learning Cross-Modality Encoder Representations from
Transformers | ['Hao Tan', 'Mohit Bansal'] | ['cs.CL', 'cs.CV', 'cs.LG'] | Vision-and-language reasoning requires an understanding of visual concepts,
language semantics, and, most importantly, the alignment and relationships
between these two modalities. We thus propose the LXMERT (Learning
Cross-Modality Encoder Representations from Transformers) framework to learn
these vision-and-language... | 2019-08-20T17:05:18Z | EMNLP 2019 (14 pages; with new attention visualizations) | null | null | null | null | null | null | null | null | null |
1,908.07836 | PubLayNet: largest dataset ever for document layout analysis | ['Xu Zhong', 'Jianbin Tang', 'Antonio Jimeno Yepes'] | ['cs.CL'] | Recognizing the layout of unstructured digital documents is an important step
when parsing the documents into structured machine-readable format for
downstream applications. Deep neural networks that are developed for computer
vision have been proven to be an effective method to analyze layout of document
images. Howev... | 2019-08-16T00:40:08Z | null | null | null | PubLayNet: Largest Dataset Ever for Document Layout Analysis | ['Xu Zhong', 'Jianbin Tang', 'Antonio Jimeno-Yepes'] | 2,019 | IEEE International Conference on Document Analysis and Recognition | 465 | 22 | ['Computer Science'] |
1,908.07919 | Deep High-Resolution Representation Learning for Visual Recognition | ['Jingdong Wang', 'Ke Sun', 'Tianheng Cheng', 'Borui Jiang', 'Chaorui Deng', 'Yang Zhao', 'Dong Liu', 'Yadong Mu', 'Mingkui Tan', 'Xinggang Wang', 'Wenyu Liu', 'Bin Xiao'] | ['cs.CV'] | High-resolution representations are essential for position-sensitive vision
problems, such as human pose estimation, semantic segmentation, and object
detection. Existing state-of-the-art frameworks first encode the input image as
a low-resolution representation through a subnetwork that is formed by
connecting high-to... | 2019-08-20T10:47:46Z | To appear in TPAMI. State-of-the-art performance on human pose
estimation, semantic segmentation, object detection, instance segmentation,
and face alignment. Full version of arXiv:1904.04514. (arXiv admin note: text
overlap with arXiv:1904.04514) | null | null | null | null | null | null | null | null | null |
1,908.08962 | Well-Read Students Learn Better: On the Importance of Pre-training
Compact Models | ['Iulia Turc', 'Ming-Wei Chang', 'Kenton Lee', 'Kristina Toutanova'] | ['cs.CL'] | Recent developments in natural language representations have been accompanied
by large and expensive models that leverage vast amounts of general-domain text
through self-supervised pre-training. Due to the cost of applying such models
to down-stream tasks, several model compression techniques on pre-trained
language r... | 2019-08-23T18:02:05Z | Added comparison to concurrent work | null | null | Well-Read Students Learn Better: The Impact of Student Initialization on Knowledge Distillation | ['Iulia Turc', 'Ming-Wei Chang', 'Kenton Lee', 'Kristina Toutanova'] | 2,019 | arXiv.org | 225 | 41 | ['Computer Science'] |
1,908.09203 | Release Strategies and the Social Impacts of Language Models | ['Irene Solaiman', 'Miles Brundage', 'Jack Clark', 'Amanda Askell', 'Ariel Herbert-Voss', 'Jeff Wu', 'Alec Radford', 'Gretchen Krueger', 'Jong Wook Kim', 'Sarah Kreps', 'Miles McCain', 'Alex Newhouse', 'Jason Blazakis', 'Kris McGuffie', 'Jasmine Wang'] | ['cs.CL', 'cs.AI', 'cs.CY', 'I.2; I.2.7; K.4'] | Large language models have a range of beneficial uses: they can assist in
prose, poetry, and programming; analyze dataset biases; and more. However,
their flexibility and generative capabilities also raise misuse concerns. This
report discusses OpenAI's work related to the release of its GPT-2 language
model. It discus... | 2019-08-24T20:41:40Z | 71 pages, report | null | null | Release Strategies and the Social Impacts of Language Models | ['Irene Solaiman', 'Miles Brundage', 'Jack Clark', 'Amanda Askell', 'Ariel Herbert-Voss', 'Jeff Wu', 'Alec Radford', 'Jasmine Wang'] | 2,019 | arXiv.org | 635 | 98 | ['Computer Science'] |
1,908.10063 | FinBERT: Financial Sentiment Analysis with Pre-trained Language Models | ['Dogu Araci'] | ['cs.CL', 'cs.LG'] | Financial sentiment analysis is a challenging task due to the specialized
language and lack of labeled data in that domain. General-purpose models are
not effective enough because of the specialized language used in a financial
context. We hypothesize that pre-trained language models can help with this
problem because ... | 2019-08-27T07:40:48Z | This thesis is submitted in partial fulfillment for the degree of
Master of Science in Information Studies: Data Science, University of
Amsterdam. June 25, 2019 | null | null | null | null | null | null | null | null | null |
1,908.10084 | Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks | ['Nils Reimers', 'Iryna Gurevych'] | ['cs.CL'] | BERT (Devlin et al., 2018) and RoBERTa (Liu et al., 2019) has set a new
state-of-the-art performance on sentence-pair regression tasks like semantic
textual similarity (STS). However, it requires that both sentences are fed into
the network, which causes a massive computational overhead: Finding the most
similar pair i... | 2019-08-27T08:50:17Z | Published at EMNLP 2019 | null | null | Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks | ['Nils Reimers', 'Iryna Gurevych'] | 2,019 | Conference on Empirical Methods in Natural Language Processing | 12,366 | 38 | ['Computer Science'] |
1,908.11828 | PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase
Identification | ['Yinfei Yang', 'Yuan Zhang', 'Chris Tar', 'Jason Baldridge'] | ['cs.CL'] | Most existing work on adversarial data generation focuses on English. For
example, PAWS (Paraphrase Adversaries from Word Scrambling) consists of
challenging English paraphrase identification pairs from Wikipedia and Quora.
We remedy this gap with PAWS-X, a new dataset of 23,659 human translated PAWS
evaluation pairs i... | 2019-08-30T16:40:00Z | Accepted by EMNLP2019 | null | null | null | null | null | null | null | null | null |
1,909.00161 | Benchmarking Zero-shot Text Classification: Datasets, Evaluation and
Entailment Approach | ['Wenpeng Yin', 'Jamaal Hay', 'Dan Roth'] | ['cs.CL'] | Zero-shot text classification (0Shot-TC) is a challenging NLU problem to
which little attention has been paid by the research community. 0Shot-TC aims
to associate an appropriate label with a piece of text, irrespective of the
text domain and the aspect (e.g., topic, emotion, event, etc.) described by the
label. And th... | 2019-08-31T07:42:11Z | EMNLP2019 camera-ready, 10 pages | null | null | Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach | ['Wenpeng Yin', 'Jamaal Hay', 'D. Roth'] | 2,019 | Conference on Empirical Methods in Natural Language Processing | 553 | 29 | ['Computer Science'] |
1,909.00204 | NEZHA: Neural Contextualized Representation for Chinese Language
Understanding | ['Junqiu Wei', 'Xiaozhe Ren', 'Xiaoguang Li', 'Wenyong Huang', 'Yi Liao', 'Yasheng Wang', 'Jiashu Lin', 'Xin Jiang', 'Xiao Chen', 'Qun Liu'] | ['cs.CL'] | The pre-trained language models have achieved great successes in various
natural language understanding (NLU) tasks due to its capacity to capture the
deep contextualized information in text by pre-training on large-scale corpora.
In this technical report, we present our practice of pre-training language
models named N... | 2019-08-31T12:08:53Z | null | null | null | null | null | null | null | null | null | null |
1,909.00277 | Cosmos QA: Machine Reading Comprehension with Contextual Commonsense
Reasoning | ['Lifu Huang', 'Ronan Le Bras', 'Chandra Bhagavatula', 'Yejin Choi'] | ['cs.CL', 'cs.AI'] | Understanding narratives requires reading between the lines, which in turn,
requires interpreting the likely causes and effects of events, even when they
are not mentioned explicitly. In this paper, we introduce Cosmos QA, a
large-scale dataset of 35,600 problems that require commonsense-based reading
comprehension, fo... | 2019-08-31T19:55:44Z | EMNLP'2019 | null | null | null | null | null | null | null | null | null |
1,909.01247 | Introducing RONEC -- the Romanian Named Entity Corpus | ['Stefan Daniel Dumitrescu', 'Andrei-Marius Avram'] | ['cs.CL'] | We present RONEC - the Named Entity Corpus for the Romanian language. The
corpus contains over 26000 entities in ~5000 annotated sentences, belonging to
16 distinct classes. The sentences have been extracted from a copy-right free
newspaper, covering several styles. This corpus represents the first initiative
in the Ro... | 2019-09-03T15:20:44Z | 8 pages + annex, accepted to LREC2020 in the main conference | null | null | Introducing RONEC - the Romanian Named Entity Corpus | ['Stefan Daniel Dumitrescu', 'Andrei-Marius Avram'] | 2,019 | International Conference on Language Resources and Evaluation | 23 | 17 | ['Computer Science'] |
1,909.01326 | The Woman Worked as a Babysitter: On Biases in Language Generation | ['Emily Sheng', 'Kai-Wei Chang', 'Premkumar Natarajan', 'Nanyun Peng'] | ['cs.CL', 'cs.AI'] | We present a systematic study of biases in natural language generation (NLG)
by analyzing text generated from prompts that contain mentions of different
demographic groups. In this work, we introduce the notion of the regard towards
a demographic, use the varying levels of regard towards different demographics
as a def... | 2019-09-03T17:50:44Z | EMNLP 2019 short paper (5 pages); Updated references and examples,
changed figure 2 & 3 order, fixed grammar, results unmodified | null | null | null | null | null | null | null | null | null |
1,909.02027 | An Evaluation Dataset for Intent Classification and Out-of-Scope
Prediction | ['Stefan Larson', 'Anish Mahendran', 'Joseph J. Peper', 'Christopher Clarke', 'Andrew Lee', 'Parker Hill', 'Jonathan K. Kummerfeld', 'Kevin Leach', 'Michael A. Laurenzano', 'Lingjia Tang', 'Jason Mars'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Task-oriented dialog systems need to know when a query falls outside their
range of supported intents, but current text classification corpora only define
label sets that cover every example. We introduce a new dataset that includes
queries that are out-of-scope---i.e., queries that do not fall into any of the
system's... | 2019-09-04T18:04:56Z | Accepted to EMNLP-IJCNLP 2019 | null | null | null | null | null | null | null | null | null |
1,909.03601 | Unbiased Recommender Learning from Missing-Not-At-Random Implicit
Feedback | ['Yuta Saito', 'Suguru Yaginuma', 'Yuta Nishino', 'Hayato Sakata', 'Kazuhide Nakata'] | ['stat.ML', 'cs.IR', 'cs.LG'] | Recommender systems widely use implicit feedback such as click data because
of its general availability. Although the presence of clicks signals the users'
preference to some extent, the lack of such clicks does not necessarily
indicate a negative response from the users, as it is possible that the users
were not expos... | 2019-09-09T02:54:20Z | accepted at WSDM'20 | null | null | Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback | ['Yuta Saito', 'Suguru Yaginuma', 'Yuta Nishino', 'Hayato Sakata', 'K. Nakata'] | 2,019 | Web Search and Data Mining | 268 | 39 | ['Computer Science', 'Mathematics'] |
1,909.05645 | Learning Alignment for Multimodal Emotion Recognition from Speech | ['Haiyang Xu', 'Hui Zhang', 'Kun Han', 'Yun Wang', 'Yiping Peng', 'Xiangang Li'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Speech emotion recognition is a challenging problem because human convey
emotions in subtle and complex ways. For emotion recognition on human speech,
one can either extract emotion related features from audio signals or employ
speech recognition techniques to generate text from speech and then apply
natural language p... | 2019-09-06T03:06:38Z | InterSpeech 2019 | null | null | null | null | null | null | null | null | null |
1,909.05658 | UER: An Open-Source Toolkit for Pre-training Models | ['Zhe Zhao', 'Hui Chen', 'Jinbin Zhang', 'Xin Zhao', 'Tao Liu', 'Wei Lu', 'Xi Chen', 'Haotang Deng', 'Qi Ju', 'Xiaoyong Du'] | ['cs.CL', 'cs.LG'] | Existing works, including ELMO and BERT, have revealed the importance of
pre-training for NLP tasks. While there does not exist a single pre-training
model that works best in all cases, it is of necessity to develop a framework
that is able to deploy various pre-training models efficiently. For this
purpose, we propose... | 2019-09-12T13:46:58Z | null | null | null | null | null | null | null | null | null | null |
1,909.05858 | CTRL: A Conditional Transformer Language Model for Controllable
Generation | ['Nitish Shirish Keskar', 'Bryan McCann', 'Lav R. Varshney', 'Caiming Xiong', 'Richard Socher'] | ['cs.CL'] | Large-scale language models show promising text generation capabilities, but
users cannot easily control particular aspects of the generated text. We
release CTRL, a 1.63 billion-parameter conditional transformer language model,
trained to condition on control codes that govern style, content, and
task-specific behavio... | 2019-09-11T17:57:18Z | null | null | null | null | null | null | null | null | null | null |
1,909.06146 | PubMedQA: A Dataset for Biomedical Research Question Answering | ['Qiao Jin', 'Bhuwan Dhingra', 'Zhengping Liu', 'William W. Cohen', 'Xinghua Lu'] | ['cs.CL', 'cs.LG', 'q-bio.QM'] | We introduce PubMedQA, a novel biomedical question answering (QA) dataset
collected from PubMed abstracts. The task of PubMedQA is to answer research
questions with yes/no/maybe (e.g.: Do preoperative statins reduce atrial
fibrillation after coronary artery bypass grafting?) using the corresponding
abstracts. PubMedQA ... | 2019-09-13T11:18:20Z | EMNLP 2019 | null | null | PubMedQA: A Dataset for Biomedical Research Question Answering | ['Qiao Jin', 'Bhuwan Dhingra', 'Zhengping Liu', 'William W. Cohen', 'Xinghua Lu'] | 2,019 | Conference on Empirical Methods in Natural Language Processing | 918 | 23 | ['Computer Science', 'Biology'] |
1,909.07005 | KorQuAD1.0: Korean QA Dataset for Machine Reading Comprehension | ['Seungyoung Lim', 'Myungji Kim', 'Jooyoul Lee'] | ['cs.CL'] | Machine Reading Comprehension (MRC) is a task that requires machine to
understand natural language and answer questions by reading a document. It is
the core of automatic response technology such as chatbots and automatized
customer supporting systems. We present Korean Question Answering
Dataset(KorQuAD), a large-scal... | 2019-09-16T06:15:27Z | null | null | null | null | null | null | null | null | null | null |
1,909.07528 | Emergent Tool Use From Multi-Agent Autocurricula | ['Bowen Baker', 'Ingmar Kanitscheider', 'Todor Markov', 'Yi Wu', 'Glenn Powell', 'Bob McGrew', 'Igor Mordatch'] | ['cs.LG', 'cs.AI', 'cs.MA', 'stat.ML'] | Through multi-agent competition, the simple objective of hide-and-seek, and
standard reinforcement learning algorithms at scale, we find that agents create
a self-supervised autocurriculum inducing multiple distinct rounds of emergent
strategy, many of which require sophisticated tool use and coordination. We
find clea... | 2019-09-17T00:17:02Z | null | null | null | null | null | null | null | null | null | null |
1,909.07846 | Multimodal Multitask Representation Learning for Pathology Biobank
Metadata Prediction | ['Wei-Hung Weng', 'Yuannan Cai', 'Angela Lin', 'Fraser Tan', 'Po-Hsuan Cameron Chen'] | ['cs.CV', 'cs.LG'] | Metadata are general characteristics of the data in a well-curated and
condensed format, and have been proven to be useful for decision making,
knowledge discovery, and also heterogeneous data organization of biobank. Among
all data types in the biobank, pathology is the key component of the biobank
and also serves as ... | 2019-09-17T14:34:37Z | preprint version | null | null | null | null | null | null | null | null | null |
1,909.0793 | Ludwig: a type-based declarative deep learning toolbox | ['Piero Molino', 'Yaroslav Dudin', 'Sai Sumanth Miryala'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CV', 'cs.SE', 'stat.ML'] | In this work we present Ludwig, a flexible, extensible and easy to use
toolbox which allows users to train deep learning models and use them for
obtaining predictions without writing code. Ludwig implements a novel approach
to deep learning model building based on two main abstractions: data types and
declarative confi... | 2019-09-17T16:54:29Z | null | null | null | null | null | null | null | null | null | null |
1,909.08053 | Megatron-LM: Training Multi-Billion Parameter Language Models Using
Model Parallelism | ['Mohammad Shoeybi', 'Mostofa Patwary', 'Raul Puri', 'Patrick LeGresley', 'Jared Casper', 'Bryan Catanzaro'] | ['cs.CL'] | Recent work in language modeling demonstrates that training large transformer
models advances the state of the art in Natural Language Processing
applications. However, very large models can be quite difficult to train due to
memory constraints. In this work, we present our techniques for training very
large transforme... | 2019-09-17T19:42:54Z | null | null | null | Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism | ['M. Shoeybi', 'M. Patwary', 'Raul Puri', 'P. LeGresley', 'J. Casper', 'Bryan Catanzaro'] | 2,019 | arXiv.org | 1,926 | 62 | ['Computer Science'] |
1,909.08072 | Adversarial Attacks and Defenses in Images, Graphs and Text: A Review | ['Han Xu', 'Yao Ma', 'Haochen Liu', 'Debayan Deb', 'Hui Liu', 'Jiliang Tang', 'Anil K. Jain'] | ['cs.LG', 'cs.CR', 'stat.ML'] | Deep neural networks (DNN) have achieved unprecedented success in numerous
machine learning tasks in various domains. However, the existence of
adversarial examples has raised concerns about applying deep learning to
safety-critical applications. As a result, we have witnessed increasing
interests in studying attack an... | 2019-09-17T20:07:23Z | survey, adversarial attacks, defenses | null | null | null | null | null | null | null | null | null |
1,909.08593 | Fine-Tuning Language Models from Human Preferences | ['Daniel M. Ziegler', 'Nisan Stiennon', 'Jeffrey Wu', 'Tom B. Brown', 'Alec Radford', 'Dario Amodei', 'Paul Christiano', 'Geoffrey Irving'] | ['cs.CL', 'cs.LG', 'stat.ML'] | Reward learning enables the application of reinforcement learning (RL) to
tasks where reward is defined by human judgment, building a model of reward by
asking humans questions. Most work on reward learning has used simulated
environments, but complex information about values is often expressed in
natural language, and... | 2019-09-18T17:33:39Z | null | null | null | Fine-Tuning Language Models from Human Preferences | ['Daniel M. Ziegler', 'Nisan Stiennon', 'Jeff Wu', 'Tom B. Brown', 'Alec Radford', 'Dario Amodei', 'Paul Christiano', 'G. Irving'] | 2,019 | arXiv.org | 1,776 | 53 | ['Computer Science', 'Mathematics'] |
1,909.09436 | CodeSearchNet Challenge: Evaluating the State of Semantic Code Search | ['Hamel Husain', 'Ho-Hsiang Wu', 'Tiferet Gazit', 'Miltiadis Allamanis', 'Marc Brockschmidt'] | ['cs.LG', 'cs.IR', 'cs.SE', 'stat.ML'] | Semantic code search is the task of retrieving relevant code given a natural
language query. While related to other information retrieval tasks, it requires
bridging the gap between the language used in code (often abbreviated and
highly technical) and natural language more suitable to describe vague concepts
and ideas... | 2019-09-20T11:52:45Z | Updated evaluation numbers after fixing indexing bug | null | null | null | null | null | null | null | null | null |
1,909.09577 | NeMo: a toolkit for building AI applications using Neural Modules | ['Oleksii Kuchaiev', 'Jason Li', 'Huyen Nguyen', 'Oleksii Hrinchuk', 'Ryan Leary', 'Boris Ginsburg', 'Samuel Kriman', 'Stanislav Beliaev', 'Vitaly Lavrukhin', 'Jack Cook', 'Patrice Castonguay', 'Mariya Popova', 'Jocelyn Huang', 'Jonathan M. Cohen'] | ['cs.LG', 'cs.CL', 'cs.SD', 'eess.AS'] | NeMo (Neural Modules) is a Python framework-agnostic toolkit for creating AI
applications through re-usability, abstraction, and composition. NeMo is built
around neural modules, conceptual blocks of neural networks that take typed
inputs and produce typed outputs. Such modules typically represent data layers,
encoders... | 2019-09-14T03:51:46Z | 6 pages plus references | null | null | NeMo: a toolkit for building AI applications using Neural Modules | ['Oleksii Kuchaiev', 'Jason Li', 'Huyen Nguyen', 'Oleksii Hrinchuk', 'Ryan Leary', 'Boris Ginsburg', 'Samuel Kriman', 'Stanislav Beliaev', 'Vitaly Lavrukhin', 'Jack Cook', 'P. Castonguay', 'Mariya Popova', 'Jocelyn Huang', 'Jonathan M. Cohen'] | 2,019 | arXiv.org | 308 | 18 | ['Mathematics', 'Computer Science', 'Engineering'] |
1,909.10351 | TinyBERT: Distilling BERT for Natural Language Understanding | ['Xiaoqi Jiao', 'Yichun Yin', 'Lifeng Shang', 'Xin Jiang', 'Xiao Chen', 'Linlin Li', 'Fang Wang', 'Qun Liu'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Language model pre-training, such as BERT, has significantly improved the
performances of many natural language processing tasks. However, pre-trained
language models are usually computationally expensive, so it is difficult to
efficiently execute them on resource-restricted devices. To accelerate
inference and reduce ... | 2019-09-23T13:05:35Z | Findings of EMNLP 2020; results have been updated; code and model:
https://github.com/huawei-noah/Pretrained-Language-Model/tree/master/TinyBERT | null | null | null | null | null | null | null | null | null |
1,909.10649 | Portuguese Named Entity Recognition using BERT-CRF | ['Fábio Souza', 'Rodrigo Nogueira', 'Roberto Lotufo'] | ['cs.CL', 'cs.IR', 'cs.LG'] | Recent advances in language representation using neural networks have made it
viable to transfer the learned internal states of a trained model to downstream
natural language processing tasks, such as named entity recognition (NER) and
question answering. It has been shown that the leverage of pre-trained language
mode... | 2019-09-23T23:21:42Z | null | null | null | null | null | null | null | null | null | null |
1,909.11065 | Segmentation Transformer: Object-Contextual Representations for Semantic
Segmentation | ['Yuhui Yuan', 'Xiaokang Chen', 'Xilin Chen', 'Jingdong Wang'] | ['cs.CV'] | In this paper, we address the semantic segmentation problem with a focus on
the context aggregation strategy. Our motivation is that the label of a pixel
is the category of the object that the pixel belongs to. We present a simple
yet effective approach, object-contextual representations, characterizing a
pixel by expl... | 2019-09-24T17:39:23Z | We rephrase the object-contextual representation scheme using the
Transformer encoder-decoder framework. ECCV 2020 Spotlight. Project Page:
https://github.com/openseg-group/openseg.pytorch
https://github.com/HRNet/HRNet-Semantic-Segmentation/tree/HRNet-OCR | ECCV 2020 | null | null | null | null | null | null | null | null |
1,909.11229 | Pretraining boosts out-of-domain robustness for pose estimation | ['Alexander Mathis', 'Thomas Biasi', 'Steffen Schneider', 'Mert Yüksekgönül', 'Byron Rogers', 'Matthias Bethge', 'Mackenzie W. Mathis'] | ['cs.CV', 'cs.LG'] | Neural networks are highly effective tools for pose estimation. However, as
in other computer vision tasks, robustness to out-of-domain data remains a
challenge, especially for small training sets that are common for real-world
applications. Here, we probe the generalization ability with three architecture
classes (Mob... | 2019-09-24T23:40:39Z | A.M. and T.B. co-first authors. Dataset available at http://horse10.
deeplabcut.org . WACV 2021 conference | https://openaccess.thecvf.com/content/WACV2021/html/Mathis_Pretraining_Boosts_Out-of-Domain_Robustness_for_Pose_Estimation_WACV_2021_paper.html | null | null | null | null | null | null | null | null |
1,909.11646 | High Fidelity Speech Synthesis with Adversarial Networks | ['Mikołaj Bińkowski', 'Jeff Donahue', 'Sander Dieleman', 'Aidan Clark', 'Erich Elsen', 'Norman Casagrande', 'Luis C. Cobo', 'Karen Simonyan'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Generative adversarial networks have seen rapid development in recent years
and have led to remarkable improvements in generative modelling of images.
However, their application in the audio domain has received limited attention,
and autoregressive models, such as WaveNet, remain the state of the art in
generative mode... | 2019-09-25T17:47:49Z | null | null | null | null | null | null | null | null | null | null |
1,909.11687 | Extremely Small BERT Models from Mixed-Vocabulary Training | ['Sanqiang Zhao', 'Raghav Gupta', 'Yang Song', 'Denny Zhou'] | ['cs.CL'] | Pretrained language models like BERT have achieved good results on NLP tasks,
but are impractical on resource-limited devices due to memory footprint. A
large fraction of this footprint comes from the input embeddings with large
input vocabulary and embedding dimensions. Existing knowledge distillation
methods used for... | 2019-09-25T18:07:35Z | To appear at EACL 2021 | null | null | Extreme Language Model Compression with Optimal Subwords and Shared Projections | ['Sanqiang Zhao', 'Raghav Gupta', 'Yang Song', 'Denny Zhou'] | 2,019 | arXiv.org | 53 | 46 | ['Computer Science'] |
1,909.11942 | ALBERT: A Lite BERT for Self-supervised Learning of Language
Representations | ['Zhenzhong Lan', 'Mingda Chen', 'Sebastian Goodman', 'Kevin Gimpel', 'Piyush Sharma', 'Radu Soricut'] | ['cs.CL', 'cs.AI'] | Increasing model size when pretraining natural language representations often
results in improved performance on downstream tasks. However, at some point
further model increases become harder due to GPU/TPU memory limitations and
longer training times. To address these problems, we present two
parameter-reduction techn... | 2019-09-26T07:06:13Z | null | null | null | ALBERT: A Lite BERT for Self-supervised Learning of Language Representations | ['Zhenzhong Lan', 'Mingda Chen', 'Sebastian Goodman', 'Kevin Gimpel', 'Piyush Sharma', 'Radu Soricut'] | 2,019 | International Conference on Learning Representations | 6,488 | 72 | ['Computer Science'] |
1,909.12475 | Hidden Stratification Causes Clinically Meaningful Failures in Machine
Learning for Medical Imaging | ['Luke Oakden-Rayner', 'Jared Dunnmon', 'Gustavo Carneiro', 'Christopher Ré'] | ['cs.LG', 'stat.ML'] | Machine learning models for medical image analysis often suffer from poor
performance on important subsets of a population that are not identified during
training or testing. For example, overall performance of a cancer detection
model may be high, but the model still consistently misses a rare but
aggressive cancer su... | 2019-09-27T02:42:58Z | Machine Learning for Health (ML4H) at NeurIPS 2019 - Extended
Abstract | null | null | Hidden stratification causes clinically meaningful failures in machine learning for medical imaging | ['Luke Oakden-Rayner', 'Jared A. Dunnmon', 'G. Carneiro', 'Christopher Ré'] | 2,019 | ACM Conference on Health, Inference, and Learning | 385 | 44 | ['Computer Science', 'Mathematics', 'Medicine'] |
1,909.13447 | DiPCo -- Dinner Party Corpus | ['Maarten Van Segbroeck', 'Ahmed Zaid', 'Ksenia Kutsenko', 'Cirenia Huerta', 'Tinh Nguyen', 'Xuewen Luo', 'Björn Hoffmeister', 'Jan Trmal', 'Maurizio Omologo', 'Roland Maas'] | ['eess.AS', 'cs.CL', 'cs.SD'] | We present a speech data corpus that simulates a "dinner party" scenario
taking place in an everyday home environment. The corpus was created by
recording multiple groups of four Amazon employee volunteers having a natural
conversation in English around a dining table. The participants were recorded
by a single-channel... | 2019-09-30T04:15:59Z | null | null | null | null | null | null | null | null | null | null |
1,909.13719 | RandAugment: Practical automated data augmentation with a reduced search
space | ['Ekin D. Cubuk', 'Barret Zoph', 'Jonathon Shlens', 'Quoc V. Le'] | ['cs.CV'] | Recent work has shown that data augmentation has the potential to
significantly improve the generalization of deep learning models. Recently,
automated augmentation strategies have led to state-of-the-art results in image
classification and object detection. While these strategies were optimized for
improving validatio... | 2019-09-30T14:05:14Z | Added ablation experiments | null | null | Randaugment: Practical automated data augmentation with a reduced search space | ['E. D. Cubuk', 'Barret Zoph', 'Jonathon Shlens', 'Quoc V. Le'] | 2,019 | 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) | 3,522 | 61 | ['Computer Science'] |
1,910.00523 | BillSum: A Corpus for Automatic Summarization of US Legislation | ['Anastassia Kornilova', 'Vlad Eidelman'] | ['cs.CL'] | Automatic summarization methods have been studied on a variety of domains,
including news and scientific articles. Yet, legislation has not previously
been considered for this task, despite US Congress and state governments
releasing tens of thousands of bills every year. In this paper, we introduce
BillSum, the first ... | 2019-10-01T16:25:12Z | null | null | 10.18653/v1/D19-5406 | null | null | null | null | null | null | null |
1,910.01108 | DistilBERT, a distilled version of BERT: smaller, faster, cheaper and
lighter | ['Victor Sanh', 'Lysandre Debut', 'Julien Chaumond', 'Thomas Wolf'] | ['cs.CL'] | As Transfer Learning from large-scale pre-trained models becomes more
prevalent in Natural Language Processing (NLP), operating these large models in
on-the-edge and/or under constrained computational training or inference
budgets remains challenging. In this work, we propose a method to pre-train a
smaller general-pur... | 2019-10-02T17:56:28Z | February 2020 - Revision: fix bug in evaluation metrics, updated
metrics, argumentation unchanged. 5 pages, 1 figure, 4 tables. Accepted at
the 5th Workshop on Energy Efficient Machine Learning and Cognitive Computing
- NeurIPS 2019 | null | null | null | null | null | null | null | null | null |
1,910.02054 | ZeRO: Memory Optimizations Toward Training Trillion Parameter Models | ['Samyam Rajbhandari', 'Jeff Rasley', 'Olatunji Ruwase', 'Yuxiong He'] | ['cs.LG', 'cs.DC', 'stat.ML'] | Large deep learning models offer significant accuracy gains, but training
billions to trillions of parameters is challenging. Existing solutions such as
data and model parallelisms exhibit fundamental limitations to fit these models
into limited device memory, while obtaining computation, communication and
development ... | 2019-10-04T17:29:39Z | null | null | null | null | null | null | null | null | null | null |
1,910.02677 | Controllable Sentence Simplification | ['Louis Martin', 'Benoît Sagot', 'Éric de la Clergerie', 'Antoine Bordes'] | ['cs.CL'] | Text simplification aims at making a text easier to read and understand by
simplifying grammar and structure while keeping the underlying information
identical. It is often considered an all-purpose generic task where the same
simplification is suitable for all; however multiple audiences can benefit from
simplified te... | 2019-10-07T09:00:26Z | Code and models: https://github.com/facebookresearch/access | null | null | Controllable Sentence Simplification | ['Louis Martin', 'Benoît Sagot', 'Eric Villemonte de la Clergerie', 'Antoine Bordes'] | 2,019 | International Conference on Language Resources and Evaluation | 147 | 63 | ['Computer Science'] |
1,910.03151 | ECA-Net: Efficient Channel Attention for Deep Convolutional Neural
Networks | ['Qilong Wang', 'Banggu Wu', 'Pengfei Zhu', 'Peihua Li', 'Wangmeng Zuo', 'Qinghua Hu'] | ['cs.CV'] | Recently, channel attention mechanism has demonstrated to offer great
potential in improving the performance of deep convolutional neural networks
(CNNs). However, most existing methods dedicate to developing more
sophisticated attention modules for achieving better performance, which
inevitably increase model complexi... | 2019-10-08T01:14:26Z | Accepted to CVPR 2020; Project Page:
https://github.com/BangguWu/ECANet | null | null | null | null | null | null | null | null | null |
1,910.03771 | HuggingFace's Transformers: State-of-the-art Natural Language Processing | ['Thomas Wolf', 'Lysandre Debut', 'Victor Sanh', 'Julien Chaumond', 'Clement Delangue', 'Anthony Moi', 'Pierric Cistac', 'Tim Rault', 'Rémi Louf', 'Morgan Funtowicz', 'Joe Davison', 'Sam Shleifer', 'Patrick von Platen', 'Clara Ma', 'Yacine Jernite', 'Julien Plu', 'Canwen Xu', 'Teven Le Scao', 'Sylvain Gugger', 'Mariama... | ['cs.CL'] | Recent progress in natural language processing has been driven by advances in
both model architecture and model pretraining. Transformer architectures have
facilitated building higher-capacity models and pretraining has made it
possible to effectively utilize this capacity for a wide variety of tasks.
\textit{Transform... | 2019-10-09T03:23:22Z | 8 pages, 4 figures, more details at
https://github.com/huggingface/transformers | null | null | HuggingFace's Transformers: State-of-the-art Natural Language Processing | ['Thomas Wolf', 'Lysandre Debut', 'Victor Sanh', 'Julien Chaumond', 'Clement Delangue', 'Anthony Moi', 'Pierric Cistac', 'Tim Rault', 'Rémi Louf', 'Morgan Funtowicz', 'Joe Davison', 'Sam Shleifer', 'Patrick von Platen', 'Clara Ma', 'Yacine Jernite', 'J. Plu', 'Canwen Xu', 'Teven Le Scao', 'Sylvain Gugger', 'Mariama Dra... | 2,019 | arXiv.org | 1,981 | 65 | ['Computer Science'] |
1,910.04073 | BHAAV- A Text Corpus for Emotion Analysis from Hindi Stories | ['Yaman Kumar', 'Debanjan Mahata', 'Sagar Aggarwal', 'Anmol Chugh', 'Rajat Maheshwari', 'Rajiv Ratn Shah'] | ['cs.CL'] | In this paper, we introduce the first and largest Hindi text corpus, named
BHAAV, which means emotions in Hindi, for analyzing emotions that a writer
expresses through his characters in a story, as perceived by a narrator/reader.
The corpus consists of 20,304 sentences collected from 230 different short
stories spannin... | 2019-10-09T15:42:25Z | null | null | 10.5281/zenodo.3457467 | BHAAV- A Text Corpus for Emotion Analysis from Hindi Stories | ['Yaman Kumar Singla', 'Debanjan Mahata', 'Sagar Aggarwal', 'Anmol Chugh', 'Rajat Maheshwari', 'R. Shah'] | 2,019 | arXiv.org | 23 | 53 | ['Computer Science'] |
1,910.04396 | On Recognizing Texts of Arbitrary Shapes with 2D Self-Attention | ['Junyeop Lee', 'Sungrae Park', 'Jeonghun Baek', 'Seong Joon Oh', 'Seonghyeon Kim', 'Hwalsuk Lee'] | ['cs.CV'] | Scene text recognition (STR) is the task of recognizing character sequences
in natural scenes. While there have been great advances in STR methods, current
methods still fail to recognize texts in arbitrary shapes, such as heavily
curved or rotated texts, which are abundant in daily life (e.g. restaurant
signs, product... | 2019-10-10T07:20:54Z | null | null | null | null | null | null | null | null | null | null |
1,910.04867 | A Large-scale Study of Representation Learning with the Visual Task
Adaptation Benchmark | ['Xiaohua Zhai', 'Joan Puigcerver', 'Alexander Kolesnikov', 'Pierre Ruyssen', 'Carlos Riquelme', 'Mario Lucic', 'Josip Djolonga', 'Andre Susano Pinto', 'Maxim Neumann', 'Alexey Dosovitskiy', 'Lucas Beyer', 'Olivier Bachem', 'Michael Tschannen', 'Marcin Michalski', 'Olivier Bousquet', 'Sylvain Gelly', 'Neil Houlsby'] | ['cs.CV', 'cs.LG', 'stat.ML'] | Representation learning promises to unlock deep learning for the long tail of
vision tasks without expensive labelled datasets. Yet, the absence of a unified
evaluation for general visual representations hinders progress. Popular
protocols are often too constrained (linear classification), limited in
diversity (ImageNe... | 2019-10-01T17:06:29Z | null | null | null | null | null | null | null | null | null | null |
1,910.0618 | KonIQ-10k: An ecologically valid database for deep learning of blind
image quality assessment | ['Vlad Hosu', 'Hanhe Lin', 'Tamas Sziranyi', 'Dietmar Saupe'] | ['cs.CV', 'cs.MM', 'I.4.9; I.4.m'] | Deep learning methods for image quality assessment (IQA) are limited due to
the small size of existing datasets. Extensive datasets require substantial
resources both for generating publishable content and annotating it accurately.
We present a systematic and scalable approach to creating KonIQ-10k, the
largest IQA dat... | 2019-10-14T14:38:48Z | Published | Trans. Image Proc. 29 (2020) 4041-4056 | 10.1109/TIP.2020.2967829 | null | null | null | null | null | null | null |
1,910.06711 | MelGAN: Generative Adversarial Networks for Conditional Waveform
Synthesis | ['Kundan Kumar', 'Rithesh Kumar', 'Thibault de Boissiere', 'Lucas Gestin', 'Wei Zhen Teoh', 'Jose Sotelo', 'Alexandre de Brebisson', 'Yoshua Bengio', 'Aaron Courville'] | ['eess.AS', 'cs.CL', 'cs.LG', 'cs.SD'] | Previous works (Donahue et al., 2018a; Engel et al., 2019a) have found that
generating coherent raw audio waveforms with GANs is challenging. In this
paper, we show that it is possible to train GANs reliably to generate high
quality coherent waveforms by introducing a set of architectural changes and
simple training te... | 2019-10-08T15:03:08Z | null | null | null | null | null | null | null | null | null | null |
1,910.06764 | Stabilizing Transformers for Reinforcement Learning | ['Emilio Parisotto', 'H. Francis Song', 'Jack W. Rae', 'Razvan Pascanu', 'Caglar Gulcehre', 'Siddhant M. Jayakumar', 'Max Jaderberg', 'Raphael Lopez Kaufman', 'Aidan Clark', 'Seb Noury', 'Matthew M. Botvinick', 'Nicolas Heess', 'Raia Hadsell'] | ['cs.LG', 'cs.AI', 'stat.ML'] | Owing to their ability to both effectively integrate information over long
time horizons and scale to massive amounts of data, self-attention
architectures have recently shown breakthrough success in natural language
processing (NLP), achieving state-of-the-art results in domains such as
language modeling and machine t... | 2019-10-13T20:02:15Z | null | null | null | null | null | null | null | null | null | null |
1,910.06827 | Learning Generalisable Omni-Scale Representations for Person
Re-Identification | ['Kaiyang Zhou', 'Yongxin Yang', 'Andrea Cavallaro', 'Tao Xiang'] | ['cs.CV'] | An effective person re-identification (re-ID) model should learn feature
representations that are both discriminative, for distinguishing
similar-looking people, and generalisable, for deployment across datasets
without any adaptation. In this paper, we develop novel CNN architectures to
address both challenges. First,... | 2019-10-15T14:44:16Z | TPAMI 2021. Journal extension of arXiv:1905.00953. Updates: added
appendix. arXiv admin note: text overlap with arXiv:1905.00953 | null | null | null | null | null | null | null | null | null |
1,910.07467 | Root Mean Square Layer Normalization | ['Biao Zhang', 'Rico Sennrich'] | ['cs.LG', 'cs.CL', 'stat.ML'] | Layer normalization (LayerNorm) has been successfully applied to various deep
neural networks to help stabilize training and boost model convergence because
of its capability in handling re-centering and re-scaling of both inputs and
weight matrix. However, the computational overhead introduced by LayerNorm
makes these... | 2019-10-16T16:44:22Z | NeurIPS 2019 | null | null | null | null | null | null | null | null | null |
1,910.07475 | MLQA: Evaluating Cross-lingual Extractive Question Answering | ['Patrick Lewis', 'Barlas Oğuz', 'Ruty Rinott', 'Sebastian Riedel', 'Holger Schwenk'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Question answering (QA) models have shown rapid progress enabled by the
availability of large, high-quality benchmark datasets. Such annotated datasets
are difficult and costly to collect, and rarely exist in languages other than
English, making training QA systems in other languages challenging. An
alternative to buil... | 2019-10-16T17:05:21Z | To appear in ACL 2020 | null | null | null | null | null | null | null | null | null |
1,910.097 | Quantifying the Carbon Emissions of Machine Learning | ['Alexandre Lacoste', 'Alexandra Luccioni', 'Victor Schmidt', 'Thomas Dandres'] | ['cs.CY', 'cs.LG'] | From an environmental standpoint, there are a few crucial aspects of training
a neural network that have a major impact on the quantity of carbon that it
emits. These factors include: the location of the server used for training and
the energy grid that it uses, the length of the training procedure, and even
the make a... | 2019-10-21T23:57:32Z | Machine Learning Emissions Calculator:
https://mlco2.github.io/impact/ | null | null | Quantifying the Carbon Emissions of Machine Learning | ['Alexandre Lacoste', 'A. Luccioni', 'Victor Schmidt', 'Thomas Dandres'] | 2,019 | arXiv.org | 715 | 26 | ['Computer Science'] |
1,910.10093 | Torchreid: A Library for Deep Learning Person Re-Identification in
Pytorch | ['Kaiyang Zhou', 'Tao Xiang'] | ['cs.CV'] | Person re-identification (re-ID), which aims to re-identify people across
different camera views, has been significantly advanced by deep learning in
recent years, particularly with convolutional neural networks (CNNs). In this
paper, we present Torchreid, a software library built on PyTorch that allows
fast developmen... | 2019-10-22T16:33:05Z | Tech report | null | null | null | null | null | null | null | null | null |
1,910.10261 | QuartzNet: Deep Automatic Speech Recognition with 1D Time-Channel
Separable Convolutions | ['Samuel Kriman', 'Stanislav Beliaev', 'Boris Ginsburg', 'Jocelyn Huang', 'Oleksii Kuchaiev', 'Vitaly Lavrukhin', 'Ryan Leary', 'Jason Li', 'Yang Zhang'] | ['eess.AS'] | We propose a new end-to-end neural acoustic model for automatic speech
recognition. The model is composed of multiple blocks with residual connections
between them. Each block consists of one or more modules with 1D time-channel
separable convolutional layers, batch normalization, and ReLU layers. It is
trained with CT... | 2019-10-22T22:34:04Z | Submitted to ICASSP 2020 | null | null | null | null | null | null | null | null | null |
1,910.10288 | Location-Relative Attention Mechanisms For Robust Long-Form Speech
Synthesis | ['Eric Battenberg', 'RJ Skerry-Ryan', 'Soroosh Mariooryad', 'Daisy Stanton', 'David Kao', 'Matt Shannon', 'Tom Bagby'] | ['cs.CL', 'cs.LG', 'cs.SD', 'eess.AS'] | Despite the ability to produce human-level speech for in-domain text,
attention-based end-to-end text-to-speech (TTS) systems suffer from text
alignment failures that increase in frequency for out-of-domain text. We show
that these failures can be addressed using simple location-relative attention
mechanisms that do aw... | 2019-10-23T00:21:33Z | Accepted to ICASSP 2020 | null | null | Location-Relative Attention Mechanisms for Robust Long-Form Speech Synthesis | ['Eric Battenberg', 'R. Skerry-Ryan', 'Soroosh Mariooryad', 'Daisy Stanton', 'David Kao', 'Matt Shannon', 'Tom Bagby'] | 2,019 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 114 | 16 | ['Computer Science', 'Engineering'] |
1,910.10655 | End-to-end Domain-Adversarial Voice Activity Detection | ['Marvin Lavechin', 'Marie-Philippe Gill', 'Ruben Bousbib', 'Hervé Bredin', 'Leibny Paola Garcia-Perera'] | ['eess.AS', 'I.2.7'] | Voice activity detection is the task of detecting speech regions in a given
audio stream or recording. First, we design a neural network combining
trainable filters and recurrent layers to tackle voice activity detection
directly from the waveform. Experiments on the challenging DIHARD dataset show
that the proposed en... | 2019-10-23T16:24:40Z | submitted to Interspeech 2020 | null | null | null | null | null | null | null | null | null |
1,910.10683 | Exploring the Limits of Transfer Learning with a Unified Text-to-Text
Transformer | ['Colin Raffel', 'Noam Shazeer', 'Adam Roberts', 'Katherine Lee', 'Sharan Narang', 'Michael Matena', 'Yanqi Zhou', 'Wei Li', 'Peter J. Liu'] | ['cs.LG', 'cs.CL', 'stat.ML'] | Transfer learning, where a model is first pre-trained on a data-rich task
before being fine-tuned on a downstream task, has emerged as a powerful
technique in natural language processing (NLP). The effectiveness of transfer
learning has given rise to a diversity of approaches, methodology, and
practice. In this paper, ... | 2019-10-23T17:37:36Z | null | null | null | Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer | ['Colin Raffel', 'Noam M. Shazeer', 'Adam Roberts', 'Katherine Lee', 'Sharan Narang', 'Michael Matena', 'Yanqi Zhou', 'Wei Li', 'Peter J. Liu'] | 2,019 | Journal of machine learning research | 20,462 | 134 | ['Mathematics', 'Computer Science'] |
1,910.10687 | Context-Aware Sentence/Passage Term Importance Estimation For First
Stage Retrieval | ['Zhuyun Dai', 'Jamie Callan'] | ['cs.IR'] | Term frequency is a common method for identifying the importance of a term in
a query or document. But it is a weak signal, especially when the frequency
distribution is flat, such as in long queries or short documents where the text
is of sentence/passage-length. This paper proposes a Deep Contextualized Term
Weightin... | 2019-10-23T17:42:35Z | null | null | null | Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval | ['Zhuyun Dai', 'Jamie Callan'] | 2,019 | arXiv.org | 192 | 38 | ['Computer Science'] |
1,910.1148 | Parallel WaveGAN: A fast waveform generation model based on generative
adversarial networks with multi-resolution spectrogram | ['Ryuichi Yamamoto', 'Eunwoo Song', 'Jae-Min Kim'] | ['eess.AS', 'cs.LG', 'cs.SD', 'eess.SP'] | We propose Parallel WaveGAN, a distillation-free, fast, and small-footprint
waveform generation method using a generative adversarial network. In the
proposed method, a non-autoregressive WaveNet is trained by jointly optimizing
multi-resolution spectrogram and adversarial loss functions, which can
effectively capture ... | 2019-10-25T01:16:38Z | Accepted to the conference of ICASSP 2020 | null | null | null | null | null | null | null | null | null |
1,910.11769 | DENS: A Dataset for Multi-class Emotion Analysis | ['Chen Liu', 'Muhammad Osama', 'Anderson de Andrade'] | ['cs.CL'] | We introduce a new dataset for multi-class emotion analysis from long-form
narratives in English. The Dataset for Emotions of Narrative Sequences (DENS)
was collected from both classic literature available on Project Gutenberg and
modern online narratives available on Wattpad, annotated using Amazon
Mechanical Turk. A ... | 2019-10-25T14:40:14Z | Accepted to EMNLP 2019 | null | null | DENS: A Dataset for Multi-class Emotion Analysis | ['Chen Cecilia Liu', 'Muhammad Osama', 'Anderson de Andrade'] | 2,019 | Conference on Empirical Methods in Natural Language Processing | 37 | 23 | ['Computer Science'] |
1,910.11856 | On the Cross-lingual Transferability of Monolingual Representations | ['Mikel Artetxe', 'Sebastian Ruder', 'Dani Yogatama'] | ['cs.CL', 'cs.AI', 'cs.LG'] | State-of-the-art unsupervised multilingual models (e.g., multilingual BERT)
have been shown to generalize in a zero-shot cross-lingual setting. This
generalization ability has been attributed to the use of a shared subword
vocabulary and joint training across multiple languages giving rise to deep
multilingual abstract... | 2019-10-25T17:30:20Z | ACL 2020 | null | 10.18653/v1/2020.acl-main.421 | null | null | null | null | null | null | null |
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