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id stringlengths 10 10	title stringlengths 28 136	text stringlengths 5.62k 98.6k	num_sections int64 4 44
1601.02403	Argumentation Mining in User-Generated Web Discourse	# Argumentation Mining in User-Generated Web Discourse ## Abstract The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways. (i) We deal with actual We...	19
1603.00968	MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification	# MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification ## Abstract We introduce a novel, simple convolution neural network (CNN) architecture - multi-group norm constraint CNN (MGNC-CNN) that capitalizes on multiple sets of word embeddings for sentence classification. MGNC-CN...	9
1603.01417	Dynamic Memory Networks for Visual and Textual Question Answering	# Dynamic Memory Networks for Visual and Textual Question Answering ## Abstract Neural network architectures with memory and attention mechanisms exhibit certain reasoning capabilities required for question answering. One such architecture, the dynamic memory network (DMN), obtained high accuracy on a variety of lang...	15
1603.01514	A Bayesian Model of Multilingual Unsupervised Semantic Role Induction	# A Bayesian Model of Multilingual Unsupervised Semantic Role Induction ## Abstract We propose a Bayesian model of unsupervised semantic role induction in multiple languages, and use it to explore the usefulness of parallel corpora for this task. Our joint Bayesian model consists of individual models for each languag...	15
1603.04513	Multichannel Variable-Size Convolution for Sentence Classification	# Multichannel Variable-Size Convolution for Sentence Classification ## Abstract We propose MVCNN, a convolution neural network (CNN) architecture for sentence classification. It (i) combines diverse versions of pretrained word embeddings and (ii) extracts features of multigranular phrases with variable-size convolut...	10
1604.00400	Revisiting Summarization Evaluation for Scientific Articles	# Revisiting Summarization Evaluation for Scientific Articles ## Abstract Evaluation of text summarization approaches have been mostly based on metrics that measure similarities of system generated summaries with a set of human written gold-standard summaries. The most widely used metric in summarization evaluation h...	14
1604.05781	What we write about when we write about causality: Features of causal statements across large-scale social discourse	# What we write about when we write about causality: Features of causal statements across large-scale social discourse ## Abstract Identifying and communicating relationships between causes and effects is important for understanding our world, but is affected by language structure, cognitive and emotional biases, and...	9
1605.03481	Tweet2Vec: Character-Based Distributed Representations for Social Media	# Tweet2Vec: Character-Based Distributed Representations for Social Media ## Abstract Text from social media provides a set of challenges that can cause traditional NLP approaches to fail. Informal language, spelling errors, abbreviations, and special characters are all commonplace in these posts, leading to a prohib...	9
1605.07333	Combining Recurrent and Convolutional Neural Networks for Relation Classification	# Combining Recurrent and Convolutional Neural Networks for Relation Classification ## Abstract This paper investigates two different neural architectures for the task of relation classification: convolutional neural networks and recurrent neural networks. For both models, we demonstrate the effect of different archi...	17
1606.05320	Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models	# Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models ## Abstract As deep neural networks continue to revolutionize various application domains, there is increasing interest in making these powerful models more understandable and interpretable, and narrowing down the causes of good...	7
1608.04917	Cohesion and Coalition Formation in the European Parliament: Roll-Call Votes and Twitter Activities	# Cohesion and Coalition Formation in the European Parliament: Roll-Call Votes and Twitter Activities ## Abstract We study the cohesion within and the coalitions between political groups in the Eighth European Parliament (2014--2019) by analyzing two entirely different aspects of the behavior of the Members of the Eu...	12
1610.00879	A Computational Approach to Automatic Prediction of Drunk Texting	# A Computational Approach to Automatic Prediction of Drunk Texting ## Abstract Alcohol abuse may lead to unsociable behavior such as crime, drunk driving, or privacy leaks. We introduce automatic drunk-texting prediction as the task of identifying whether a text was written when under the influence of alcohol. We ex...	10
1610.05243	Pre-Translation for Neural Machine Translation	# Pre-Translation for Neural Machine Translation ## Abstract Recently, the development of neural machine translation (NMT) has significantly improved the translation quality of automatic machine translation. While most sentences are more accurate and fluent than translations by statistical machine translation (SMT)-b...	14
1610.08597	Word Embeddings to Enhance Twitter Gang Member Profile Identification	# Word Embeddings to Enhance Twitter Gang Member Profile Identification ## Abstract Gang affiliates have joined the masses who use social media to share thoughts and actions publicly. Interestingly, they use this public medium to express recent illegal actions, to intimidate others, and to share outrageous images and...	10
1610.09516	Finding Street Gang Members on Twitter	# Finding Street Gang Members on Twitter ## Abstract Most street gang members use Twitter to intimidate others, to present outrageous images and statements to the world, and to share recent illegal activities. Their tweets may thus be useful to law enforcement agencies to discover clues about recent crimes or to anti...	11
1611.01400	Learning to Rank Scientific Documents from the Crowd	# Learning to Rank Scientific Documents from the Crowd ## Abstract Finding related published articles is an important task in any science, but with the explosion of new work in the biomedical domain it has become especially challenging. Most existing methodologies use text similarity metrics to identify whether two a...	11
1611.02550	Discriminative Acoustic Word Embeddings: Recurrent Neural Network-Based Approaches	# Discriminative Acoustic Word Embeddings: Recurrent Neural Network-Based Approaches ## Abstract Acoustic word embeddings --- fixed-dimensional vector representations of variable-length spoken word segments --- have begun to be considered for tasks such as speech recognition and query-by-example search. Such embeddin...	13
1611.03599	UTCNN: a Deep Learning Model of Stance Classificationon on Social Media Text	# UTCNN: a Deep Learning Model of Stance Classificationon on Social Media Text ## Abstract Most neural network models for document classification on social media focus on text infor-mation to the neglect of other information on these platforms. In this paper, we classify post stance on social media channels and devel...	14
1611.09441	Sentiment Analysis for Twitter : Going Beyond Tweet Text	# Sentiment Analysis for Twitter : Going Beyond Tweet Text ## Abstract Analysing sentiment of tweets is important as it helps to determine the users' opinion. Knowing people's opinion is crucial for several purposes starting from gathering knowledge about customer base, e-governance, campaigning and many more. In thi...	16
1612.05270	A Simple Approach to Multilingual Polarity Classification in Twitter	# A Simple Approach to Multilingual Polarity Classification in Twitter ## Abstract Recently, sentiment analysis has received a lot of attention due to the interest in mining opinions of social media users. Sentiment analysis consists in determining the polarity of a given text, i.e., its degree of positiveness or neg...	11
1612.05310	Modeling Trolling in Social Media Conversations	# Modeling Trolling in Social Media Conversations ## Abstract Social media websites, electronic newspapers and Internet forums allow visitors to leave comments for others to read and interact. This exchange is not free from participants with malicious intentions, who troll others by positing messages that are intende...	10
1612.08205	Predicting the Industry of Users on Social Media	# Predicting the Industry of Users on Social Media ## Abstract Automatic profiling of social media users is an important task for supporting a multitude of downstream applications. While a number of studies have used social media content to extract and study collective social attributes, there is a lack of substantia...	13
1701.00185	Self-Taught Convolutional Neural Networks for Short Text Clustering	# Self-Taught Convolutional Neural Networks for Short Text Clustering ## Abstract Short text clustering is a challenging problem due to its sparseness of text representation. Here we propose a flexible Self-Taught Convolutional neural network framework for Short Text Clustering (dubbed STC^2), which can flexibly and ...	17
1701.06538	Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer	# Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer ## Abstract The capacity of a neural network to absorb information is limited by its number of parameters. Conditional computation, where parts of the network are active on a per-example basis, has been proposed in theory as a way of dr...	21
1703.04617	Exploring Question Understanding and Adaptation in Neural-Network-Based Question Answering	# Exploring Question Understanding and Adaptation in Neural-Network-Based Question Answering ## Abstract The last several years have seen intensive interest in exploring neural-network-based models for machine comprehension (MC) and question answering (QA). In this paper, we approach the problems by closely modelling...	7
1703.10344	Automated News Suggestions for Populating Wikipedia Entity Pages	# Automated News Suggestions for Populating Wikipedia Entity Pages ## Abstract Wikipedia entity pages are a valuable source of information for direct consumption and for knowledge-base construction, update and maintenance. Facts in these entity pages are typically supported by references. Recent studies show that as ...	13
1704.00939	Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines	# Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines ## Abstract In this paper, we describe a methodology to infer Bullish or Bearish sentiment towards companies/brands. More specifically, our approach leverages affective lexica and word embeddings ...	8
1704.02686	Word Embeddings via Tensor Factorization	# Word Embeddings via Tensor Factorization ## Abstract Most popular word embedding techniques involve implicit or explicit factorization of a word co-occurrence based matrix into low rank factors. In this paper, we aim to generalize this trend by using numerical methods to factor higher-order word co-occurrence based...	14
1704.04452	Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept Maps	# Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept Maps ## Abstract Concept maps can be used to concisely represent important information and bring structure into large document collections. Therefore, we study a variant of multi-document summarization that produces summaries in the form...	19
1704.05572	Answering Complex Questions Using Open Information Extraction	# Answering Complex Questions Using Open Information Extraction ## Abstract While there has been substantial progress in factoid question-answering (QA), answering complex questions remains challenging, typically requiring both a large body of knowledge and inference techniques. Open Information Extraction (Open IE) ...	14
1705.00108	Semi-supervised sequence tagging with bidirectional language models	# Semi-supervised sequence tagging with bidirectional language models ## Abstract Pre-trained word embeddings learned from unlabeled text have become a standard component of neural network architectures for NLP tasks. However, in most cases, the recurrent network that operates on word-level representations to produce...	10
1705.03261	Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers	# Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers ## Abstract Drug-drug interaction (DDI) is a vital information when physicians and pharmacists intend to co-administer two or more drugs. Thus, several DDI databases are constructed to avoid mistakenly combined use. In rece...	15
1705.07368	Mixed Membership Word Embeddings for Computational Social Science	# Mixed Membership Word Embeddings for Computational Social Science ## Abstract Word embeddings improve the performance of NLP systems by revealing the hidden structural relationships between words. Despite their success in many applications, word embeddings have seen very little use in computational social science N...	14
1705.09665	Community Identity and User Engagement in a Multi-Community Landscape	# Community Identity and User Engagement in a Multi-Community Landscape ## Abstract A community's identity defines and shapes its internal dynamics. Our current understanding of this interplay is mostly limited to glimpses gathered from isolated studies of individual communities. In this work we provide a systematic ...	14
1706.06894	Stance Detection in Turkish Tweets	# Stance Detection in Turkish Tweets ## Abstract Stance detection is a classification problem in natural language processing where for a text and target pair, a class result from the set {Favor, Against, Neither} is expected. It is similar to the sentiment analysis problem but instead of the sentiment of the text aut...	5
1706.07179	RelNet: End-to-End Modeling of Entities & Relations	# RelNet: End-to-End Modeling of Entities & Relations ## Abstract We introduce RelNet: a new model for relational reasoning. RelNet is a memory augmented neural network which models entities as abstract memory slots and is equipped with an additional relational memory which models relations between all memory pairs. ...	5
1706.08032	A Deep Neural Architecture for Sentence-level Sentiment Classification in Twitter Social Networking	# A Deep Neural Architecture for Sentence-level Sentiment Classification in Twitter Social Networking ## Abstract This paper introduces a novel deep learning framework including a lexicon-based approach for sentence-level prediction of sentiment label distribution. We propose to first apply semantic rules and then us...	12
1707.05236	Artificial Error Generation with Machine Translation and Syntactic Patterns	# Artificial Error Generation with Machine Translation and Syntactic Patterns ## Abstract Shortage of available training data is holding back progress in the area of automated error detection. This paper investigates two alternative methods for artificially generating writing errors, in order to create additional res...	8
1707.06806	Shallow reading with Deep Learning: Predicting popularity of online content using only its title	# Shallow reading with Deep Learning: Predicting popularity of online content using only its title ## Abstract With the ever decreasing attention span of contemporary Internet users, the title of online content (such as a news article or video) can be a major factor in determining its popularity. To take advantage of...	14
1708.00111	A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models	# A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models ## Abstract Beam search is a desirable choice of test-time decoding algorithm for neural sequence models because it potentially avoids search errors made by simpler greedy methods. However, typical cross entropy training proced...	14