├── README.md
├── accepted_papers.md
├── data
    ├── oral_paper_by_topic.json
    └── poster_demo_paper_by_topic.json
├── figure
    ├── rate.png
    ├── stat.png
    └── wordcloud.png
├── generate_accepted_paper.ipynb
└── paper_statistics.ipynb


/accepted_papers.md:
--------------------------------------------------------------------------------
  1 | ### Oral Session
  2 | #### Machine Learning
  3 | - Attending to Future Tokens for Bidirectional Sequence Generation (#1443) [[arXiv]](https://arxiv.org/abs/1908.05915)
  4 | - Attention is Not Not Explanation (#526) [[arXiv]](https://arxiv.org/abs/1908.04626)
  5 | - Practical Obstacles to Deploying Active Learning (#1176) [[arXiv]](https://arxiv.org/abs/1807.04801)
  6 | - Transfer Learning Between Related Tasks Using Expected Label Proportions (#1207) [[arXiv]](https://arxiv.org/abs/1909.00430)
  7 | - Insertion-based Decoding with automatically Inferred Generation Order (#TACL-1732) [[arXiv]](https://arxiv.org/abs/1902.01370)
  8 | - Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets (#1092) [[arXiv]](https://arxiv.org/abs/1908.07898)
  9 | - Robust Text Classifier on Test-Time Budgets (#1128) [[arXiv]](https://arxiv.org/abs/1808.08270)
 10 | - Commonsense Knowledge Mining from Pretrained Models (#3289) [[arXiv]](https://arxiv.org/abs/1909.00505)
 11 | - RNN Architecture Learning with Sparse Regularization (#3428) [[arXiv]](https://arxiv.org/abs/1909.03011)
 12 | - Universal Trigger Sequences for Attacking and Analyzing NLP (#1515) [[arXiv]](https://arxiv.org/abs/1908.07125)
 13 | - To Annotate or Not? Unsupervised Prediction of Performance Drop due to Domain Shift (#2756)
 14 | - Adaptively Sparse Transformers (#2900) [[arXiv]](https://arxiv.org/abs/1909.00015)
 15 | - Show Your Work: Improved Reporting of Experimental Results (#3277) [[arXiv]](https://arxiv.org/abs/1909.03004)
 16 | - A Deep Factorization of Style and Structure in Fonts (#3999) [[arXiv]](https://arxiv.org/abs/1910.00748)
 17 | 
 18 | #### Lexical Semantics
 19 | - Knowledge Enhanced Contextual Word Representations (#3403) [[arXiv]](https://arxiv.org/abs/1909.04164)
 20 | - How Contextual are Contextualized Word Representations? (#208)
 21 | - Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings (#783)
 22 | - On Correlations between Word Vector Sets (#3976) [[arXiv]](https://arxiv.org/abs/1910.02902)
 23 | - Game Theory Meets Embeddings: a Unified Framework for Word Sense Disambiguation (#1724)
 24 | - Cross-lingual Semantic Specialization via Lexical Relation Induction (#1735)
 25 | - Modelling the interplay of metaphor and emotion through multitask learning (#2670)
 26 | - How well do NLI models capture verb veridicality? (#3460)
 27 | - Modeling Color Terminology Across Thousands of Languages (#3515) [[arXiv]](https://arxiv.org/abs/1910.01531)
 28 | - Negative Focus Detection via Contextual Attention Mechanisms (#1314)
 29 | - Exploring Human Gender Stereotypes with Word Association Test (#1912)
 30 | - Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition (#TACL-1729) [[arXiv]](https://arxiv.org/abs/1902.10618)
 31 | - Where''s My Head? Definition, Dataset and Models for Numeric Fused-Heads Identification and Resolution (#TACL-1648) [[arXiv]](https://arxiv.org/abs/1905.10886)
 32 | 
 33 | #### Dialog and Interactive Systems
 34 | - Guided Dialog Policy Learning: Reward Estimation for Multi-Domain Task-Oriented Dialog (#166) [[arXiv]](https://arxiv.org/abs/1908.10719)
 35 | - Multi-hop Selector Network for Multi-turn Response Selection in Retrieval-based Chatbots (#554)
 36 | - MoEL: Mixture of Empathetic Listeners (#1053) [[arXiv]](https://arxiv.org/abs/1908.07687)
 37 | - Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever (#2430) [[arXiv]](https://arxiv.org/abs/1909.06762)
 38 | - Building Task-Oriented Visual Dialog Systems Through Alternative Optimization Between Dialog Policy and Language Generation (#3756) [[arXiv]](https://arxiv.org/abs/1909.05365)
 39 | - TaskMaster Dialog Corpus: Toward a Realistic and Diverse Dataset (#510)
 40 | - MultiDoGO: Multi-Domain Goal-Oriented Dialogues (#1564)
 41 | - Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack (#1186) [[arXiv]](https://arxiv.org/abs/1908.06083)
 42 | - GECOR: An End-to-End Generative Ellipsis and Co-reference Resolution Model for Task-Oriented Dialogue (#1853) [[arXiv]](https://arxiv.org/abs/1909.12086)
 43 | - Task-Oriented Conversation Generation Using Heterogeneous Memory Networks (#496) [[arXiv]](https://arxiv.org/abs/1909.11287)
 44 | 
 45 | #### Sentiment Analysis and Argument Mining
 46 | - DialogueGCN: A Graph-based Network for Emotion Recognition in Conversation (#2092) [[arXiv]](http://arxiv.org/abs/1908.11540)
 47 | - Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations (#1814) [[arXiv]](https://arxiv.org/abs/1909.10681)
 48 | - Interpretable Relevant Emotion Ranking with Event-Driven Attention (#3544)
 49 | - Justifying Recommendations using Distantly-Labeled Reviews and Fined-Grained Aspects (#518)
 50 | - Using Customer Service Dialogues for Satisfaction Analysis with Context-Assisted Multiple Instance Learning (#204)
 51 | - What Gets Echoed? Understanding the “Pointers” in Explanations of Persuasive Arguments (#2089)
 52 | - Modeling Frames in Argumentation (#2267)
 53 | - AMPERSAND: Argument Mining for PERSuAsive oNline Discussions (#3321)
 54 | - Evaluating adversarial attacks against multiple fact verification systems (#427)
 55 | - Nonsense!: Quality Control via Two-Step Reason Selection for Annotating Local Acceptability and Related Attributes in News Editorials (#564)
 56 | - On the Importance of Delexicalization for Fact Verification (#2984) [[arXiv]](https://arxiv.org/abs/1909.09868)
 57 | - Towards Debiasing Fact Verification Models (#3338) [[arXiv]](https://arxiv.org/abs/1908.05267)
 58 | - Recognizing Conflict Opinions in Aspect-level Sentiment Classification with Dual Attention Networks (#911)
 59 | - Investigating Dynamic Routing in Tree-Structured LSTM for Sentiment Analysis (#1395)
 60 | - Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks (#381) [[arXiv]](https://arxiv.org/abs/1909.03477)
 61 | - Coupling Global and Local Context for Unsupervised Aspect Extraction (#1988)
 62 | - Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning (#65)
 63 | - CAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis (#1995) [[arXiv]](https://arxiv.org/abs/1812.10735)
 64 | - Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training (#3207) [[arXiv]](http://arxiv.org/abs/1909.00415)
 65 | 
 66 | #### Summarization and Generation
 67 | - Neural Text Summarization: A Critical Evaluation (#3687) [[arXiv]](https://arxiv.org/abs/1908.08960)
 68 | - Neural data-to-text generation: A comparison between pipeline and end-to-end architectures (#2586) [[arXiv]](https://arxiv.org/abs/1908.09022)
 69 | - MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance (#1175) [[arXiv]](https://arxiv.org/abs/1909.02622)
 70 | - Select and Attend: Towards Controllable Content Selection in Text Generation (#3049) [[arXiv]](https://arxiv.org/abs/1909.04453)
 71 | - Sentence-Level Content Planning and Style Specification for Neural Text Generation (#3357) [[arXiv]](https://arxiv.org/abs/1909.00734)
 72 | 
 73 | #### Sentence-level Semantics
 74 | - Translate and Label! An Encoder-Decoder Approach for Cross-lingual Semantic Role Labeling (#2740) [[arXiv]](https://arxiv.org/abs/1908.11326)
 75 | - Syntax-Enhanced Self-Attention-Based Semantic Role Labeling (#2106)
 76 | - VerbAtlas: a Novel Large-Scale Verbal Semantic Resource and Its Application to Semantic Role Labeling (#2213)
 77 | - Parameter-free Sentence Embedding via Orthogonal Basis (#1099)
 78 | - Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations (#3807) [[arXiv]](https://arxiv.org/abs/1909.00142)
 79 | - Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs (#2676) [[arXiv]](https://arxiv.org/abs/1909.04165)
 80 | - Broad-Coverage Semantic Parsing as Transduction (#263) [[arXiv]](https://arxiv.org/abs/1909.02607)
 81 | - Core Semantic First: A Top-down Approach for AMR Parsing (#1544) [[arXiv]](https://arxiv.org/abs/1909.04303)
 82 | - Don't paraphrase, detect! Rapid and Effective Data Collection for Semantic Parsing (#2904) [[arXiv]](https://arxiv.org/abs/1908.09940)
 83 | - Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond (#TACL-1742) [[arXiv]](https://arxiv.org/abs/1812.10464)
 84 | 
 85 | #### Speech, Vision, Robotics, Multimodal and Grounding
 86 | - Extracting Possessions from Social Media: Images Complement Language (#3013)
 87 | - Learning to Speak and Act in a Fantasy Text Adventure Game (#1243) [[arXiv]](https://arxiv.org/abs/1903.03094)
 88 | - Help, Anna! Vision-based Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learning (#1542) [[arXiv]](https://arxiv.org/abs/1909.01871)
 89 | - Incorporating Visual Semantics into Sentence Representations within a Grounded Space (#2247)
 90 | - Neural Naturalist: Generating Fine-Grained Image Comparisons (#3024) [[arXiv]](https://arxiv.org/abs/1909.04101)
 91 | - LXMERT: Learning Cross-Modality Encoder Representations from Transformers (#3048) [[arXiv]](https://arxiv.org/abs/1908.07490)
 92 | - Phrase Grounding by Soft-Label Chain Conditional Random Field (#3765) [[arXiv]](https://arxiv.org/abs/1909.00301)
 93 | - What You See is What You Get: Visual Pronoun Coreference Resolution in Conversations (#549) [[arXiv]](https://arxiv.org/abs/1909.00421)
 94 | - YouMakeup: A Large-Scale Domain-Specific Multimodal Dataset for Fine-Grained Semantic Comprehension (#122)
 95 | - DEBUG: A Dense Bottom-Up Grounding Approach for Natural Language Video Localization (#167)
 96 | 
 97 | #### Information Extraction
 98 | - Fine-Grained Evaluation for Entity Linking (#116)
 99 | - Supervising Unsupervised Open Information Extraction Models (#3069)
100 | - Neural Cross-Lingual Event Detection with Minimal Parallel Resources (#1723) [[arXiv]](https://arxiv.org/abs/1808.09861)
101 | - KnowledgeNet: A Benchmark Dataset for Knowledge Base Population (#1258)
102 | - Effective Use of Transformer Networks for Entity Tracking (#3308) [[arXiv]](https://arxiv.org/abs/1909.02635)
103 | - Improving Distantly-Supervised Relation Extraction with Joint Label Embedding (#337)
104 | - Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network (#566)
105 | - Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction (#1057) [[arXiv]](https://arxiv.org/abs/1904.09331)
106 | - Easy First Relation Extraction with Information Redundancy (#1640)
107 | - Dependency-Guided LSTM-CRF for Named Entity Recognition (#2509) [[arXiv]](https://arxiv.org/abs/1909.10148)
108 | - CrossWeigh: Training Named Entity Tagger from Imperfect Annotations (#2712) [[arXiv]](https://arxiv.org/abs/1909.01441)
109 | - A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers (#3259) [[arXiv]](https://arxiv.org/abs/1908.08983)
110 | - Open Domain Web Keyphrase Extraction Beyond Language Modeling (#1119)
111 | - TuckER: Tensor Factorization for Knowledge Graph Completion (#990) [[arXiv]](https://arxiv.org/abs/1901.09590)
112 | - Weakly Supervised Domain Detection (#TACL-1712) [[arXiv]](https://arxiv.org/abs/1907.11499)
113 | - Event Detection with Multi-Order Graph Convolution and Aggregated Attention (#835)
114 | - Coverage of Information Extraction from Sentences and Paragraphs (#1285)
115 | - HMEAE: Hierarchical Modular Event Argument Extraction (#2354)
116 | - Entity, Relation, and Event Extraction with Contextualized Span Representations (#3930) [[arXiv]](https://arxiv.org/abs/1909.03546)
117 | 
118 | #### Semantics
119 | - Analytical Methods for Interpretable Ultradense Word Embeddings (#75) [[arXiv]](https://arxiv.org/abs/1904.08654)
120 | - Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks (#3142) [[arXiv]](https://arxiv.org/abs/1908.10423)
121 | - Retrofitting Contextualized Word Embeddings with Paraphrases (#3045) [[arXiv]](https://arxiv.org/abs/1909.09700)
122 | - Incorporating Contextual and Syntactic Structures Improves Semantic Similarity Modeling (#3508)
123 | 
124 | #### Discourse, Summarization, and Generation
125 | - Neural Linguistic Steganography (#3399) [[arXiv]](http://arxiv.org/abs/1909.01496)
126 | - The Feasibility of Embedding Based Automatic Evaluation for Single Document Summarization (#3018)
127 | - Attention Optimization for Abstractive Document Summarization (#1918)
128 | - Rewarding Coreference Resolvers for Being Consistent with World Knowledge (#2020) [[arXiv]](https://arxiv.org/abs/1909.02392)
129 | 
130 | #### Text Mining and NLP Applications
131 | - An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction (#740) [[arXiv]](https://arxiv.org/abs/1909.00502)
132 | - A Multilingual Topic Model for Learning Weighted Topic Links Across Incomparable Corpora (#1257)
133 | - Measure Country-Level Socio-Economic Indicators with Streaming News: An Empirical Study (#3730)
134 | - Towards Extracting Medical Family History from Natural Language Interactions: A New Dataset and Baselines (#2903)
135 | - (Male, Bachelor) and (Female, Ph.D) have different connotations: Parallelly Annotated Stylistic Language Dataset with Multiple Personas (#3793) [[arXiv]](https://arxiv.org/abs/1909.00098)
136 | - Movie Plot Analysis via Turning Point Identification (#244) [[arXiv]](https://arxiv.org/abs/1908.10328)
137 | - Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention (#2488)
138 | - Deep Ordinal Regression for Pledge Specificity Prediction (#1903) [[arXiv]](https://arxiv.org/abs/1909.00187)
139 | - Enabling Robust Grammatical Error Correction in New Domains: Datasets, Metrics, and Analyses (#TACL-1677)
140 | - The Myth of Blind Review Revisited: Experiments on ACL vs. EMNLP (#2233)
141 | - Uncover Sexual Harassment Patterns from Personal Stories by Joint Key Element Extraction and Categorization (#2653)
142 | - Identifying Predictive Causal Factors from News Streams (#2864)
143 | - Training Data Augmentation for Detecting Adverse Drug Reactions in User-Generated Content (#3011)
144 | - Deep Reinforcement Learning-based Text Anonymization against Private-Attribute Inference (#3160)
145 | 
146 | #### Neural Machine Translation
147 | - Enhancing Context Modeling with a Query-Guided Capsule Network for Document-level NMT (#2416) [[arXiv]](http://arxiv.org/abs/1909.00564)
148 | - Simple, Scalable Adaptation for Neural Machine Translation (#3252) [[arXiv]](http://arxiv.org/abs/1909.08478)
149 | - Controlling Text Complexity in Neural Machine Translation (#3177)
150 | - Investigating Multilingual NMT Representations at Scale (#1388) [[arXiv]](https://arxiv.org/abs/1909.02197)
151 | - Hierarchical Modeling of Global Context for Document-Level Neural Machine Translation (#1423)
152 | 
153 | #### Question Answering
154 | - Cross-Lingual Machine Reading Comprehension (#8) [[arXiv]](https://arxiv.org/abs/1909.00361)
155 | - A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning (#582) [[arXiv]](https://arxiv.org/abs/1908.05514)
156 | - Neural Duplicate Question Detection without Labeled Training Data (#880)
157 | - Asking Clarification Questions in Knowledge-Based Question Answering (#889)
158 | - Multi-View Domain Adapted Sentence Embeddings for Low-Resource Unsupervised Duplicate Question Detection (#1646)
159 | - Interactive Language Learning by Question Answering (#1367) [[arXiv]](https://arxiv.org/abs/1908.10909)
160 | - What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering (#3238) [[arXiv]](https://arxiv.org/abs/1909.09253)
161 | - KagNet: Learning to Answer Commonsense Questions with Knowledge-Aware Graph Networks (#436)
162 | - Learning with Limited Data for Multilingual Reading Comprehension (#3518)
163 | - A Discrete Hard EM Approach for Weakly Supervised Question Answering (#3778) [[arXiv]](https://arxiv.org/abs/1909.04849)
164 | 
165 | #### Social Media and Computational Social Science
166 | - Multi-label Categorization of Accounts of Sexism using a Neural Framework (#172) [[arXiv]](http://arxiv.org/abs/1910.04602)
167 | - The Trumpiest Trump? Identifying a Subject's Most Characteristic Tweets (#1462) [[arXiv]](https://arxiv.org/abs/1909.04002)
168 | - Finding Microaggressions in the Wild: A Case for Locating Elusive Phenomena in Social Media Posts (#2950)
169 | - Reinforced Product Metadata Selection for Helpfulness Assessment of Customer Reviews (#694)
170 | - Learning Invariant Representations of Social Media Users (#3557) [[arXiv]](https://arxiv.org/abs/1910.04979)
171 | 
172 | #### Discourse and Pragmatics
173 | - A Unified Neural Coherence Model (#1792) [[arXiv]](https://arxiv.org/abs/1909.00349)
174 | - Topic-Guided Coherence Modeling for Sentence Ordering by Preserving Global and Local Information (#2642)
175 | - Neural Generative Rhetorical Structure Parsing (#4060) [[arXiv]](https://arxiv.org/abs/1909.11049)
176 | - Weak Supervision for Learning Discourse Structure (#2453)
177 | - Predicting Discourse Structure using Distant Supervision from Sentiment (#2625)
178 | 
179 | #### Tagging, Chunking, Syntax and Parsing
180 | - Designing and Interpreting Probes with Control Tasks (#4063) [[arXiv]](https://arxiv.org/abs/1909.03368)
181 | - Specializing Word Embeddings (for Parsing) by Information Bottleneck (#1357) [[arXiv]](https://arxiv.org/abs/1910.00163)
182 | - Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing - A Tale of Two Parsers Revisited (#2799) [[arXiv]](https://arxiv.org/abs/1908.07397)
183 | - Semantic graph parsing with recurrent neural network DAG grammars (#2863) [[arXiv]](https://arxiv.org/abs/1910.00051)
184 | - 75 Languages, 1 Model: Parsing Universal Dependencies Universally (#1221) [[arXiv]](http://arxiv.org/abs/1904.02099)
185 | 
186 | #### Linguistic Theories, Cognitive Modeling and Psycholinguistics
187 | - Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts (#2585) [[arXiv]](https://arxiv.org/abs/1908.10285)
188 | - Investigating BERT's Knowledge of Language: Five Analysis Methods with NPIs (#3650) [[arXiv]](https://arxiv.org/abs/1909.02597)
189 | - Representation of Constituents in Neural Language Models: - Coordination Phrase as a Case Study (#3929) [[arXiv]](https://arxiv.org/abs/1909.04625)
190 | - Towards Zero-shot Language Modelling (#1745)
191 | - Neural Network Acceptability Judgments (#TACL-1710) [[arXiv]](https://arxiv.org/abs/1805.12471)
192 | 
193 | #### Machine Translation and Multilinguality
194 | - Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary Induction (#1131) [[arXiv]](http://arxiv.org/abs/1909.05708)
195 | - Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set (#1266) [[arXiv]](https://arxiv.org/abs/1909.01522)
196 | - Synchronously Generating Two Languages with Interactive Decoding (#1478)
197 | - On NMT Search Errors and Model Errors: Cat Got Your Tongue? (#1868) [[arXiv]](https://arxiv.org/abs/1908.10090)
198 | - Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? (#2459) [[arXiv]](https://arxiv.org/abs/1909.01638)
199 | - Weakly-Supervised Concept-based Adversarial Learning for Cross-lingual Word Embeddings (#2491) [[arXiv]](https://arxiv.org/abs/1904.09446)
200 | - Aligning Cross-lingual Entities with Multi-Aspect Information (#3541) [[arXiv]](http://arxiv.org/abs/1910.06575)
201 | - Contrastive Language Adaptation for Cross-Lingual Stance Detection (#2498) [[arXiv]](https://arxiv.org/abs/1910.02076)
202 | - Jointly Learning to Align and Translate with Transformer Models (#422) [[arXiv]](https://arxiv.org/abs/1909.02074)
203 | - Understanding Data Augmentation in Neural Machine Translation: Two Perspectives towards Generalization (#2192)
204 | - Simple and Effective Noisy Channel Modeling for Neural Machine Translation (#2869) [[arXiv]](https://arxiv.org/abs/1908.05731)
205 | - MultiFiT: Efficient Multi-lingual Language Model Fine-tuning (#745) [[arXiv]](https://arxiv.org/abs/1909.04761)
206 | - Hint-based Training for Non-AutoRegressive Machine Translation (#1064)
207 | - Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala English (#3349) [[arXiv]](https://arxiv.org/abs/1902.01382)
208 | - Constant-Time Machine Translation with Conditional Masked Language Models (#1204)
209 | - Learning to Copy for Automatic Post-Editing (#777)
210 | 
211 | #### Reasoning and Question Answering
212 | - Going on a vacation takes longer than “Going for a walk”: A Study of Temporal Commonsense Understanding (#2533) [[arXiv]](https://arxiv.org/abs/1909.03065)
213 | - QAInfomax: Learning Robust Question Answering System by Mutual Information Maximization (#2798) [[arXiv]](https://arxiv.org/abs/1909.00215)
214 | - Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations (#329) [[arXiv]](https://arxiv.org/abs/1908.11513)
215 | - How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG (#586) [[arXiv]](https://arxiv.org/abs/1811.01778)
216 | 
217 | #### Generation
218 | - Pun-GAN: Generative Adversarial Network for Pun Generation (#267)
219 | - Multi-Task Learning with Language Modeling for Question Generation (#3820) [[arXiv]](https://arxiv.org/abs/1908.11813)
220 | - Autoregressive Text Generation beyond Feedback Loops (#3506) [[arXiv]](https://arxiv.org/abs/1908.11658)
221 | - The Woman Worked as a Babysitter: On Biases in Language Generation (#3874) [[arXiv]](https://arxiv.org/abs/1909.01326)
222 | - Counterfactual Story Reasoning and Generation (#3328) [[arXiv]](https://arxiv.org/abs/1909.04076)
223 | - Encode, Tag, Realize: High-Precision Text Editing (#2395) [[arXiv]](https://arxiv.org/abs/1909.01187)
224 | - Answer-guided and Semantic Coherent Question Generation in Open-domain Conversation (#128)
225 | - Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation (#1947) [[arXiv]](https://arxiv.org/abs/1909.11974)
226 | - A Topic Augmented Text Generation Model: Joint Learning of Semantics and Structural Features (#2822)
227 | - A Modular Architecture for Unsupervised Sarcasm Generation (#2725)
228 | - Interpoetry: Generating Classical Chinese Poems from Vernacular Chinese (#2534) [[arXiv]](https://arxiv.org/abs/1909.00279)
229 | - Set to Ordered Text: Generating Discharge Instructions from Medical Billing Codes (#724)
230 | 
231 | #### Summarization
232 | - Summary Cloze: A New Task for Content Selection in Topic-Focused Summarization (#1178)
233 | - Text Summarization with Pretrained Encoders (#392) [[arXiv]](https://arxiv.org/abs/1908.08345)
234 | - How to Write Summaries with Patterns? Learning towards Abstractive Summarization through Prototype Editing (#609) [[arXiv]](https://arxiv.org/abs/1909.08837)
235 | - Unsupervised Sentence Summarization using the Information Bottleneck Principle (#3219) [[arXiv]](https://arxiv.org/abs/1909.07405)
236 | - Improving Latent Alignment in Text Summarization by Generalizing the Pointer Generator (#3043)
237 | 
238 | #### Information Retrieval and Document Analysis
239 | - Cross-Cultural Transfer Learning for Text Classification (#1036)
240 | - Combining Unsupervised Pre-training and Annotator Rationales to Improve Low-shot Text Classification (#1190)
241 | - Projection Sequence Networks for On-Device Text Classification (#3202)
242 | - Induction Networks for Few-Shot Text Classification (#3562) [[arXiv]](https://arxiv.org/abs/1902.10482)
243 | - Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach (#2899) [[arXiv]](https://arxiv.org/abs/1909.00161)
244 | - Human-grounded Evaluations of Explanation Methods for Text Classification (#425) [[arXiv]](https://arxiv.org/abs/1908.11355)
245 | - A Context-based Framework for Modeling the Role and Function of On-line Resource Citations in Scientific Literature (#793)
246 | - Adversarial Reprogramming of Text Classification Neural Networks (#28) [[arXiv]](https://arxiv.org/abs/1809.01829)
247 | - Document Hashing with Mixture-Prior Generative Models (#1676) [[arXiv]](https://arxiv.org/abs/1908.11078)
248 | - Efficient Vector Retrieval under Maximum Inner Product (#3421)
249 | 
250 | #### Reasoning
251 | - Social IQa: Commonsense Reasoning about Social Interactions (#1334) [[arXiv]](https://arxiv.org/abs/1904.09728)
252 | - Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning (#2866) [[arXiv]](http://arxiv.org/abs/1909.05803)
253 | - Posing Fair Generalization Tasks for Natural Language Inference (#1413)
254 | - Everything Happens for a Reason: Discovering the Purpose of Actions in Procedural Text (#3279) [[arXiv]](https://arxiv.org/abs/1909.04745)
255 | - CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text (#3183) [[arXiv]](https://arxiv.org/abs/1908.06177)
256 | 
257 | #### Syntax, Parsing, and Linguistic Theories
258 | - Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers (#3860) [[arXiv]](https://arxiv.org/abs/1909.09279)
259 | - Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing (#1832) [[arXiv]](https://arxiv.org/abs/1909.06775)
260 | - Multilingual Grammar Induction with Continuous Language Identification (#3883)
261 | - Quantifying the Semantic Core of Gender Systems (#2637)
262 | 
263 | #### Sentiment and Social Media
264 | - Perturbation Sensitivity Analysis for Detecting Unintended Model Biases (#3447) [[arXiv]](https://arxiv.org/abs/1910.04210)
265 | - Automatically Inferring Gender Associations from Language (#3519) [[arXiv]](https://arxiv.org/abs/1909.00091)
266 | - Reporting the Unreported: Event Extraction for Analyzing the Local Representation of Hate Crimes (#3715) [[arXiv]](https://arxiv.org/abs/1909.02126)
267 | - Minimally Supervised Learning of Affective Events Using Discourse Relations (#3493) [[arXiv]](https://arxiv.org/abs/1909.00694)
268 | 
269 | #### Phonology, Word Segmentation, and Parsing
270 | - Constraint-based Learning of Phonological Processes (#451)
271 | - Detect Camouflaged Spam Content via StoneSkipping: Graph and Text Joint Embedding for Chinese Character Variation Representation (#1340) [[arXiv]](https://arxiv.org/abs/1908.11561)
272 | - A Generative Model for Punctuation in Dependency Trees (#TACL-1582) [[arXiv]](https://arxiv.org/abs/1906.11298)
273 | 
274 | ### Poster & Demo Session
275 | #### Information Extraction, Information Retrieval and Document Analysis, Linguistic Theories
276 | - Leveraging Dependency Forest for Neural Medical Relation Extraction (#249)
277 | - Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised Data (#569)
278 | - Improving Relation Extraction with Knowledge-attention (#710) [[arXiv]](https://arxiv.org/abs/1910.02724)
279 | - Jointly Learning Entity and Relation Representations for Entity Alignment (#782) [[arXiv]](https://arxiv.org/abs/1909.09317)
280 | - Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph Completion (#796) [[arXiv]](https://arxiv.org/abs/1909.11359)
281 | - Low-Resource Name Tagging Learned with Weakly Labeled Data (#821) [[arXiv]](https://arxiv.org/abs/1908.09659)
282 | - Learning Dynamic Context Augmentation for Global Entity Linking (#841) [[arXiv]](http://arxiv.org/abs/1909.02117)
283 | - Open Event Extraction from Online Texts using a Generative Adversarial Network (#859) [[arXiv]](https://arxiv.org/abs/1908.09246)
284 | - Learning to Bootstrap for Entity Set Expansion (#1001)
285 | - Multi-input Multi-output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text (#1149)
286 | - Cross-lingual Structure Transfer for Relation and Event Extraction (#1210)
287 | - Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation Maximization Framework (#1365) [[arXiv]](http://arxiv.org/abs/1909.05448)
288 | - Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction (#1736) [[arXiv]](http://arxiv.org/abs/1904.07535)
289 | - Event Detection with Trigger-Aware Lattice Neural Network (#1816)
290 | - A Boundary-aware Neural Model for Nested Named Entity Recognition (#1874)
291 | - Learning the Extraction Order of Multiple Relational Facts in a Sentence with Reinforcement Learning (#2024)
292 | - CaRe: Open Knowledge Graph Embeddings (#2439)
293 | - Self-Attention Enhanced CNNs and Collaborative Curriculum Learning for Distantly Supervised Relation Extraction (#2793)
294 | - Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping (#3014)
295 | - Leveraging 2-hop Distant Supervision from Table Entity Pairs for Relation Extraction (#3059) [[arXiv]](http://arxiv.org/abs/1909.06007)
296 | - EntEval: A Holistic Evaluation Benchmark for Entity Representations (#3317) [[arXiv]](https://arxiv.org/abs/1909.00137)
297 | - Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction (#3646) [[arXiv]](https://arxiv.org/abs/1909.05360)
298 | - Hierarchical Text Classification with Reinforced Label Assignment (#32) [[arXiv]](https://arxiv.org/abs/1908.10419)
299 | - Investigating Capsule Network and Semantic Feature on Hyperplanes for Text Classification (#314)
300 | - Label-Specific Document Representation for Multi-Label Text Classification (#721)
301 | - Hierarchical Attention Prototypical Networks for Few-Shot Text Classification (#729)
302 | - Many Faces of Feature Importance: Comparing Built-in and Post-hoc Feature Importance in Text Classification (#2087)
303 | - Enhancing Local Feature Extraction with Global Representation for Neural Text Classification (#2273)
304 | - Latent-Variable Generative Text Classifiers for Data-Efficient NLP (#3004)
305 | - PaRe: A Paper-Reviewer Matching Approach Using a Common Topic Space (#3239) [[arXiv]](http://arxiv.org/abs/1909.11258)
306 | - Linking artificial and human neural representations of language (#2750) [[arXiv]](https://arxiv.org/abs/1910.01244)
307 | 
308 | #### Machine Translation and Mulitilinguality, Phonology, Morphology and Word Segmentation, Tagging, Chunking, Syntax and Parsing
309 | - Explicit Cross-lingual Pre-training for Unsupervised Machine Translation (#233) [[arXiv]](https://arxiv.org/abs/1909.00180)
310 | - Latent Part-of-Speech Sequences for Neural Machine Translation (#410) [[arXiv]](https://arxiv.org/abs/1908.11782)
311 | - Improving Back-Translation with Uncertainty-based Confidence Estimation (#798) [[arXiv]](https://arxiv.org/abs/1909.00157)
312 | - Towards Linear Time Neural Machine Translation with Capsule Networks (#846) [[arXiv]](https://arxiv.org/abs/1811.00287)
313 | - Modeling Multi-mapping relations for Precise Cross-lingual Entity Alignment (#985)
314 | - Supervised and Nonlinear Alignment of Two Embedding Spaces for Dictionary Induction in Low Resourced Languages (#1226)
315 | - Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT (#1414) [[arXiv]](https://arxiv.org/abs/1904.09077)
316 | - Iterative Dual Domain Adaptation for Neural Machine Translation (#1427)
317 | - Multi-agent Learning for Neural Machine Translation (#1484) [[arXiv]](https://arxiv.org/abs/1909.01101)
318 | - Pivot-based Transfer Learning for Neural Machine Translation between non-English Languages (#1869) [[arXiv]](https://arxiv.org/abs/1909.09524)
319 | - Context-Aware Monolingual Repair for Neural Machine Translation (#1967) [[arXiv]](https://arxiv.org/abs/1909.01383)
320 | - Multi-Granularity Self-Attention for Neural Machine Translation (#2330) [[arXiv]](https://arxiv.org/abs/1909.02222)
321 | - The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives (#2415) [[arXiv]](https://arxiv.org/abs/1909.01380)
322 | - Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention (#2537) [[arXiv]](https://arxiv.org/abs/1908.11365)
323 | - A Discriminative Neural Model for Cross-Lingual Word Alignment (#2961) [[arXiv]](https://arxiv.org/abs/1909.00444)
324 | - One Model to Learn Both: Zero Pronoun Prediction and Translation (#3571) [[arXiv]](https://arxiv.org/abs/1909.00369)
325 | - Dynamic Past and Future for Neural Machine Translation (#3601) [[arXiv]](https://arxiv.org/abs/1904.09646)
326 | - Revisit Automatic Error Detection for Wrong and Missing Translation ‐ A Supervised Approach (#3770)
327 | - Towards Understanding Neural Machine Translation with Word Importance (#3857) [[arXiv]](https://arxiv.org/abs/1909.00326)
328 | - Multilingual Neural Machine Translation with Language Clustering (#4056) [[arXiv]](https://arxiv.org/abs/1908.09324)
329 | - Don't Forget the Long Tail! A Comprehensive Analysis of Morphological Generalization in Bilingual Lexicon Induction (#1065) [[arXiv]](https://arxiv.org/abs/1909.02855)
330 | - A Functionalist Account of Vowel System Typology (#1268)
331 | - Pushing the Limits of Low-Resource Morphological Inflection (#2230) [[arXiv]](https://arxiv.org/abs/1908.05838)
332 | - Morphological Analysis Using a Sequence Decoder (#TACL-1654)
333 | - Cross-Lingual Dependency Parsing Using Code-Mixed TreeBank (#205) [[arXiv]](https://arxiv.org/abs/1909.02235)
334 | - Hierarchical Pointer Net Parsing (#531) [[arXiv]](https://arxiv.org/abs/1908.11571)
335 | - Semi-Supervised Semantic Role Labeling with Cross-View Training (#719)
336 | - Low-Resource Sequence Labeling via Unsupervised Multilingual Contextualized Representations (#809)
337 | - A Lexicon-Based Graph Neural Network for Chinese NER (#863)
338 | - CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding (#1556) [[arXiv]](https://arxiv.org/abs/1909.06937)
339 | - Tree Transformer: Integrating Tree Structures into Self-Attention (#1794) [[arXiv]](https://arxiv.org/abs/1909.06639)
340 | - Semantic Role Labeling with Iterative Structure Refinement (#2179) [[arXiv]](https://arxiv.org/abs/1909.03285)
341 | - Entity Projection via Machine-Translation for Cross-Lingual NER (#2724) [[arXiv]](https://arxiv.org/abs/1909.05356)
342 | - A Bayesian Approach for Sequence Tagging with Crowds (#2738) [[arXiv]](https://arxiv.org/abs/1811.00780)
343 | - A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages (#3091) [[arXiv]](http://arxiv.org/abs/1909.02857)
344 | - Target Language-Aware Constrained Inference for Cross-lingual Dependency Parsing (#3368) [[arXiv]](https://arxiv.org/abs/1909.01482)
345 | - Look-up and Adapt: A One-shot Semantic Parser (#3711)
346 | - Similarity Based Auxiliary Classifier for Named Entity Recognition (#3886)
347 | - Variable beam search for generative neural parsing and its relevance for neuro-imaging signal analysis (#4015)
348 | 
349 | #### Dialog and Interactive Systems, Machine Translation and Multilinuality, Phonology, Morphology, and Word Segmentation, Speech, Vision, Robotics, Multimodal and Grounding, Tagging, Chunking, Syntax and Parsing
350 | - Multi-task Learning for Natural Language Generation in Task-Oriented Dialogue (#242)
351 | - Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation (#622)
352 | - Semi-Supervised Bootstrapping of Dialogue State Trackers for Task-Oriented Modelling (#1011)
353 | - A Progressive Model to Enable Continual Learning for Semantic Slot Filling (#1289)
354 | - CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots (#1447) [[arXiv]](https://arxiv.org/abs/1909.08705)
355 | - Sampling Matters! An Empirical Study of Negative Sampling Strategies for Learning of Matching Models in Retrieval-based Dialogue Systems (#2050)
356 | - Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variables (#2329)
357 | - Modeling Multi-Action Policy for Task-Oriented Dialogues (#2650) [[arXiv]](https://arxiv.org/abs/1908.11546)
358 | - An Evaluation for Intent Classification and Out-of-Scope Prediction (#3471) [[arXiv]](https://arxiv.org/abs/1909.02027)
359 | - Automatically Learning Data Augmentation Policies for Dialogue Tasks (#3528) [[arXiv]](https://arxiv.org/abs/1909.12868)
360 | - uniblock: Scoring and Filtering Corpus with Unicode Block Information (#351) [[arXiv]](https://arxiv.org/abs/1908.09716)
361 | - Multilingual word translation using auxiliary languages (#533)
362 | - Towards Better Modeling Hierarchical Structure for Self-Attention with Ordered Neurons (#801) [[arXiv]](https://arxiv.org/abs/1909.01562)
363 | - Improved Sentence Alignment in Linear Time and Space (#1284)
364 | - Simpler and Faster Learning of Adaptive Policies for Simultaneous Translation (#1603) [[arXiv]](https://arxiv.org/abs/1909.01559)
365 | - Adversarial Learning with Contextual Embeddings for Zero-resource Cross-lingual Classification and NER (#1889) [[arXiv]](https://arxiv.org/abs/1909.00153)
366 | - Recurrent Embedding for Neural Machine Translation (#2114)
367 | - Machine Translation for Machines: the Sentiment Classification Use Case (#2413) [[arXiv]](http://arxiv.org/abs/1910.00478)
368 | - Investigating the Effectiveness of BPE: The Power of Shorter Sequences (#2552)
369 | - HABLex: Human Annotated Bilingual Lexicons for Experiments in Machine Translation (#3022)
370 | - Handling Syntactic Divergence in Low-resource Machine Translation (#3336) [[arXiv]](https://arxiv.org/abs/1909.00040)
371 | - Speculative Beam Search for Simultaneous Translation (#3487) [[arXiv]](https://arxiv.org/abs/1909.05421)
372 | - Self-Attention with Structural Position Representations (#3548) [[arXiv]](http://arxiv.org/abs/1909.00383)
373 | - Low-Resource Neural Machine Translation by Exploiting Multilingualism through Multi-Step Fine-Tuning Using N-way Parallel Corpora (#3590)
374 | - Unsupervised Domain Adaptation for Neural Machine Translation with Domain-Aware Feature Embeddings (#3716) [[arXiv]](https://arxiv.org/abs/1908.10430)
375 | - A Regularization-based Framework for Bilingual Grammar Induction (#4061)
376 | - Encoders Help You Disambiguate Word Senses in Neural Machine Translation (#4083) [[arXiv]](https://arxiv.org/abs/1908.11771)
377 | - Korean Morphological Analysis with Tied Sequence-to-Sequence Multi-Task Model (#2376)
378 | - Convolutional Neural Networks for Diacritic Restoration (#3733)
379 | - Improving Visual Dialog by Learning to Answer Diverse Questions (#459)
380 | - Cross-lingual Transfer Learning with Data Selection for Large-Scale Spoken Language Understanding (#790) [[arXiv]](https://arxiv.org/abs/1904.01825)
381 | - Multi-Head Attention with Diversity for Learning Grounded Multilingual Multimodal Representations (#2786) [[arXiv]](https://arxiv.org/abs/1910.00058)
382 | - Decoupled Box Proposal and Featurization with Ultrafine-Grained Semantic Labels Improve Image Captioning and Visual Question Answering (#3263) [[arXiv]](https://arxiv.org/abs/1909.02097)
383 | - REO-Relevance, Extraness, Omission: A Fine-grained Evaluation for Image Captioning (#3293) [[arXiv]](https://arxiv.org/abs/1909.02217)
384 | - WSLLN: Weakly Supervised Natural Language Localization Networks (#3398) [[arXiv]](https://arxiv.org/abs/1909.00239)
385 | - Grounding learning of modifier dynamics: An application to colour naming. (#3748) [[arXiv]](http://arxiv.org/abs/1909.07586)
386 | - Efficient Navigation with Language Pre-training and Stochastic Sampling (#3830) [[arXiv]](https://arxiv.org/abs/1909.02244)
387 | - Towards Making a Dependency Parser See (#413) [[arXiv]](https://arxiv.org/abs/1909.01053)
388 | - Unsupervised Labeled Parsing with Deep Inside-Outside Recursive Autoencoders (#1234) [[arXiv]](https://arxiv.org/abs/1904.02142)
389 | - Dependency Parsing for Spoken Dialog Systems (#3171) [[arXiv]](https://arxiv.org/abs/1909.03317)
390 | - Span-based Hierarchical Semantic Parsing for Task-Oriented Dialog (#3240)
391 | 
392 | #### Dialog and Interactive Systems, Speech, Vision, Robotics, Multimodal and Grounding
393 | - Data-Efficient Goal-Oriented Conversation with Dialogue Knowledge Transfer Networks (#9) [[arXiv]](https://arxiv.org/abs/1910.01302)
394 | - Multi-Granularity Representations of Dialog (#64) [[arXiv]](https://arxiv.org/abs/1908.09890)
395 | - Are You for Real? Detecting Identity Fraud via Dialogue Interactions (#111) [[arXiv]](https://arxiv.org/abs/1908.06820)
396 | - Hierarchy Response Learning for Neural Conversation Generation (#124)
397 | - Knowledge Aware Conversation Generation with Explainable Reasoning on Augmented Graphs (#138) [[arXiv]](https://arxiv.org/abs/1903.10245)
398 | - Adaptive Parameterization for Neural Dialogue Generation (#298)
399 | - Towards Knowledge-Based Recommender Dialog System (#316) [[arXiv]](https://arxiv.org/abs/1908.05391)
400 | - Structuring latent spaces for stylized response generation (#419) [[arXiv]](https://arxiv.org/abs/1909.05361)
401 | - Improving Open-Domain Dialogue Systems via Multi-Turn Incomplete Utterance Restoration (#537)
402 | - Unsupervised Context Rewriting for Open Domain Conversation (#771)
403 | - Dually Interactive Matching Network for Personalized Response Selection in Retrieval-Based Chatbots (#866) [[arXiv]](https://arxiv.org/abs/1908.05859)
404 | - DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphs (#1432) [[arXiv]](https://arxiv.org/abs/1910.00610)
405 | - Retrieval-guided Dialogue Response Generation via a Matching-to-Generation Framework (#1550)
406 | - Scalable and Accurate Dialogue State Tracking via Hierarchical Sequence Generation (#1842) [[arXiv]](https://arxiv.org/abs/1909.00754)
407 | - Low-Resource Response Generation with Template Prior (#1931) [[arXiv]](https://arxiv.org/abs/1909.11968)
408 | - A Discrete CVAE for Response Generation on Short-Text Conversation (#2039)
409 | - Who Is Speaking to Whom? Learning to Identify Utterance Addressee in Multi-Party Conversations (#2495)
410 | - A Semi-Supervised Stable Variational Network for Promoting Replier-Consistency in Dialogue Generation (#2594)
411 | - Modeling Personalization in Continuous Space for Response Generation via Augmented Wasserstein Autoencoders (#2685)
412 | - Variational Hierarchical User-based Conversation Model (#3513)
413 | - Recommendation as a Communication Game: Self-Supervised Role-Playing for Goal-oriented Dialogue (#3727) [[arXiv]](https://arxiv.org/abs/1909.03922)
414 | - CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases (#3881) [[arXiv]](https://arxiv.org/abs/1909.05378)
415 | - A Practical Dialogue-Act-Driven Conversation Model for Multi-Turn Response Selection (#3954)
416 | - How to Build User Simulators to Train RL-based Dialog Systems (#4003) [[arXiv]](https://arxiv.org/abs/1909.01388)
417 | - Graph Convolutional Network with Sequential Attention for Goal-Oriented Dialogue Systems (#TACL-1676)
418 | - Low-Rank HOCA: Efficient High-Order Cross-Modal Attention for Video Captioning (#294)
419 | - Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach (#370) [[arXiv]](https://arxiv.org/abs/1909.02201)
420 | - Dual Attention Networks for Visual Reference Resolution in Visual Dialog (#401) [[arXiv]](https://arxiv.org/abs/1902.09368)
421 | - Unsupervised Discovery of Multimodal Links in Multi-image, Multi-sentence Documents (#942) [[arXiv]](https://arxiv.org/abs/1904.07826)
422 | - UR-FUNNY: A Multimodal Language Dataset for Understanding Humor (#996) [[arXiv]](https://arxiv.org/abs/1904.06618)
423 | - Partners in Crime: Multi-view Sequential Inference for Movie Understanding (#1923)
424 | - Guiding the Flowing of Semantics: Interpretable Video Captioning via POS Tag (#2097)
425 | - A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding (#2414) [[arXiv]](https://arxiv.org/abs/1909.02188)
426 | - Talk2Car: Taking Control Of Your Self Driving Car (#2718) [[arXiv]](http://arxiv.org/abs/1909.10838)
427 | - Fact-Checking Meets Fauxtography: Verifying Claims About Images (#2739) [[arXiv]](https://arxiv.org/abs/1908.11722)
428 | - Video Dialog via Progressive Inference and Cross-Transformer (#2766)
429 | - Executing Instructions in Situated Collaborative Interactions (#2884) [[arXiv]](https://arxiv.org/abs/1910.03655)
430 | - Fusion of Detected Objects in Text for Visual Question Answering (#3099) [[arXiv]](https://arxiv.org/abs/1908.05054)
431 | - TIGEr: Text-to-Image Grounding for Image Caption Evaluation (#3260) [[arXiv]](https://arxiv.org/abs/1909.02050)
432 | 
433 | #### Question Answering, Textual Inference and Other Areas of Semantics
434 | - Tree-structured Decoding for Solving Math Word Problems (#56)
435 | - PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text (#86) [[arXiv]](https://arxiv.org/abs/1904.09537)
436 | - Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning (#107) [[arXiv]](https://arxiv.org/abs/1909.00277)
437 | - Finding Generalizable Evidence by Learning to Convince Q&A Models (#179) [[arXiv]](https://arxiv.org/abs/1909.05863)
438 | - Ranking and Sampling in Open-domain Question Answering (#468)
439 | - A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs (#618) [[arXiv]](https://arxiv.org/abs/1909.01567)
440 | - Generating Questions for Knowledge Bases via Incorporating Diversified Contexts and Answer-Aware Loss (#807)
441 | - Multi-task Learning for Conversational Question Answering Over a Large-Scale Knowledge Base (#924) [[arXiv]](http://arxiv.org/abs/1910.05069)
442 | - BiPaR: A Bilingual Parallel Dataset for Multilingual and Cross-lingual Reading Comprehension on Novels (#1930) [[arXiv]](https://arxiv.org/abs/1910.05040)
443 | - Language Models as Knowledge Bases? (#2085) [[arXiv]](https://arxiv.org/abs/1909.01066)
444 | - NumNet: Machine Reading Comprehension with Numerical Reasoning (#2237) [[arXiv]](https://arxiv.org/abs/1910.06701)
445 | - Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks (#2277) [[arXiv]](https://arxiv.org/abs/1909.00964)
446 | - Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering (#2390) [[arXiv]](https://arxiv.org/abs/1909.06356)
447 | - Adversarial Domain Adaptation for Machine Reading Comprehension (#2764) [[arXiv]](https://arxiv.org/abs/1908.09209)
448 | - Incorporating External Knowledge into Machine Reading for Generative Question Answering (#2820) [[arXiv]](https://arxiv.org/abs/1909.02745)
449 | - Answering questions by learning to rank - Learning to rank by answering questions (#2825) [[arXiv]](http://arxiv.org/abs/1909.00596)
450 | - Discourse-Aware Semantic Self-Attention for Narrative Reading Comprehension (#2940) [[arXiv]](https://arxiv.org/abs/1908.10721)
451 | - Revealing the Importance of Semantic Retrieval for Machine Reading at Scale (#2945) [[arXiv]](https://arxiv.org/abs/1909.08041)
452 | - PubMedQA: A Dataset for Biomedical Research Question Answering (#2978) [[arXiv]](https://arxiv.org/abs/1909.06146)
453 | - Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering (#3164)
454 | - Answering Complex Open-domain Questions Through Iterative Query Generation (#3417) [[arXiv]](https://arxiv.org/abs/1910.07000)
455 | - NL2pSQL: Generating Pseudo-SQL Queries from Under-specified Natural Language Questions (#3489)
456 | - Leveraging Frequent Query Substructures to Generate Formal Queries for Complex Question Answering (#4004) [[arXiv]](https://arxiv.org/abs/1908.11053)
457 | - Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning (#147)
458 | - Learning to Update Knowledge Graph by Reading News (#493)
459 | - DIVINE: A Generative Adversarial Imitation Learning Framework for Knowledge Graph Reasoning (#709)
460 | - Original Semantics-Oriented Attention and Deep Fusion Network for Sentence Matching (#829)
461 | - Representation Learning with Ordered Relation Paths for Knowledge Graph Completion (#972) [[arXiv]](http://arxiv.org/abs/1909.11864)
462 | - Collaborative Policy Learning for Open Knowledge Graph Reasoning (#1018) [[arXiv]](https://arxiv.org/abs/1909.00230)
463 | - Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder (#1444) [[arXiv]](https://arxiv.org/abs/1909.08824)
464 | - Asynchronous Deep Interaction Network for Natural Language Inference (#2257)
465 | - Keep Calm and Switch On! Preserving Sentiment and Fluency in Semantic Text Exchange (#2830) [[arXiv]](https://arxiv.org/abs/1909.00088)
466 | - Query-focused Scenario Construction (#3550) [[arXiv]](https://arxiv.org/abs/1909.06877)
467 | - Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model (#3819)
468 | 
469 | #### Discourse and Pragmatics, Summarization and Generation
470 | - Evaluating Pronominal Anaphora in Machine Translation: An Evaluation Measure and a Test Suite (#723) [[arXiv]](https://arxiv.org/abs/1909.00131)
471 | - A Regularization Approach for Incorporating Event Knowledge and Coreference Relations into Neural Discourse Parsing (#2916)
472 | - Weakly Supervised Multilingual Causality Extraction fromWikipedia (#3994)
473 | - Attribute-aware Sequence Network for Review Summarization (#210)
474 | - Extractive Summarization of Long Documents by Combining Global and Local Context (#268) [[arXiv]](https://arxiv.org/abs/1909.08089)
475 | - Enhancing Neural Data-To-Text Generation Models with External Background Knowledge (#313)
476 | - Reading Like HER: Human Reading Inspired Extractive Summarization (#346)
477 | - Contrastive Attention Mechanism for Abstractive Sentence Summarization (#361)
478 | - NCLS: Neural Cross-Lingual Summarization (#703) [[arXiv]](https://arxiv.org/abs/1909.00156)
479 | - Clickbait? Sensational Headline Generation with Auto-tuned Reinforcement Learning (#749) [[arXiv]](https://arxiv.org/abs/1909.03582)
480 | - Concept Pointer Network for Abstractive Summarization (#845)
481 | - Surface Realisation Using Full Delexicalisation (#1139)
482 | - Unsupervised Text Attribute Transfer via Iterative Matching and Translation (#1169) [[arXiv]](https://arxiv.org/abs/1901.11333)
483 | - Better Rewards Yield Better Summaries: Learning to Summarise Without References (#1191) [[arXiv]](https://arxiv.org/abs/1909.01214)
484 | - Mixture Content Selection for Diverse Sequence Generation (#1369) [[arXiv]](https://arxiv.org/abs/1909.01953)
485 | - An End-to-End Generative Architecture for Paraphrase Generation (#1375)
486 | - Table-to-Text Generation with Effective Hierarchical Encoder on Three dimensions (Row, Column and Time) (#1726) [[arXiv]](http://arxiv.org/abs/1909.02304)
487 | - Subtopic-Driven Multi-Document Summarization (#1779)
488 | - Referring Expression Generation Using Entity Profiles (#1805) [[arXiv]](https://arxiv.org/abs/1909.01528)
489 | - Exploring Diverse Expressions for Paraphrase Generation (#1834)
490 | - Enhancing AMR-to-Text Generation with Dual Graph Representations (#1852) [[arXiv]](https://arxiv.org/abs/1909.00352)
491 | - Keeping Consistency of Sentence Generation and Document Classification with Multi-Task Learning (#1881)
492 | - Toward a task of feedback comment generation for writing learning (#2031)
493 | - Improving Question Generation With to the Point Context (#2033) [[arXiv]](https://arxiv.org/abs/1910.06036)
494 | - Deep Copycat Networks for Text-to-Text Generation (#2121)
495 | - Towards Controllable and Personalized Review Generation (#2412) [[arXiv]](https://arxiv.org/abs/1910.03506)
496 | - Answers Unite! Unsupervised Metrics for Reinforced Summarization Models (#2604) [[arXiv]](https://arxiv.org/abs/1909.01610)
497 | - Long and Diverse Text Generation with Planning-based Hierarchical Variational Model (#2746) [[arXiv]](https://arxiv.org/abs/1908.06605)
498 | - “Transforming” Delete, Retrieve, Generate Approach for Controlled Text Style Transfer (#2932) [[arXiv]](https://arxiv.org/abs/1908.09368)
499 | - An Entity-Driven Framework for Abstractive Summarization (#3275) [[arXiv]](https://arxiv.org/abs/1909.02059)
500 | - Neural Extractive Text Summarization with Syntactic Compression (#3334) [[arXiv]](https://arxiv.org/abs/1902.00863)
501 | - Domain Adaptive Text Style Transfer (#3511) [[arXiv]](https://arxiv.org/abs/1908.09395)
502 | - Let's Ask Again: Refine Network for Automatic Question Generation (#3754) [[arXiv]](https://arxiv.org/abs/1909.05355)
503 | - Earlier Isn't Always Better: Submodular Analysis on Corpus and System Biases in Summarization (#3846) [[arXiv]](https://arxiv.org/abs/1908.11723)
504 | 
505 | #### Information Retrieval and Document Analysis, Lexical Semantics, Sentence-level Semantics, Machine Learning
506 | - A Label Informative Wide & Deep Classifier for Scientific Publications (#542)
507 | - Text Level Graph Neural Network for Text Classification (#573) [[arXiv]](https://arxiv.org/abs/1910.02356)
508 | - Semantic Relatedness based Re-ranker for Text Spotting (#875) [[arXiv]](http://arxiv.org/abs/1909.07950)
509 | - Delta-training: Simple Semi-Supervised Text Classification using Pretrained Word Embeddings (#1306) [[arXiv]](https://arxiv.org/abs/1901.07651)
510 | - Visual Detection with Context for Document Layout Analysis (#1342)
511 | - Evaluating Topic Quality with Posterior Variability (#1562) [[arXiv]](https://arxiv.org/abs/1909.03524)
512 | - Neural Topic Model with Reinforcement Learning (#2494)
513 | - Modelling Stopping Criteria using Poisson Processes (#2705) [[arXiv]](https://arxiv.org/abs/1909.06239)
514 | - Cross-Domain Modeling of Sentence-Level Evidence for Document Retrieval (#3533)
515 | - The Challenges of Optimizing Machine Translation for Low Resource Cross-Language Information Retrieval (#4151)
516 | - Rotate King to get Queen: Word Relationships as Orthogonal Transformations in Embedding Space (#170) [[arXiv]](http://arxiv.org/abs/1909.00504)
517 | - GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge (#362) [[arXiv]](https://arxiv.org/abs/1908.07245)
518 | - Leveraging Adjective-Noun Phrasing Knowledge for Comparison Relation Prediction in Text-to-SQL (#670)
519 | - Bridging the Defined and the Defining: Exploiting Implicit Lexical Semantic Relations in Definition Modeling (#1461)
520 | - Don't Just Scratch the Surface: Enhancing Word Representations for Korean with Hanja (#1615) [[arXiv]](https://arxiv.org/abs/1908.09282)
521 | - Challenging Supervised Word Sense Disambiguation with Lexical-Semantic Combinations (#2219)
522 | - Hierarchical Meta-Embeddings for Code-switching Named Entity Recognition (#2419) [[arXiv]](https://arxiv.org/abs/1909.08504)
523 | - Context-Aware Conversation Thread Detection in Group Chat (#162)
524 | - Fine-tune BERT with Sparse Self-Attention Mechanism (#327)
525 | - Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels (#806) [[arXiv]](https://arxiv.org/abs/1910.06061)
526 | - A Multi-Pairwise Extension of Procrustes Analysis for Multilingual Word Translation (#819)
527 | - Out-of-Domain Detection for Low-Resource Text Classification Tasks (#1063) [[arXiv]](https://arxiv.org/abs/1909.05357)
528 | - An Empirical Study of Harnessing Pre-Trained Neural Networks with Rules for Formality Style Transfer (#1877)
529 | - Multiple Text Style Transfer by using Word-level Conditional Generative Adversarial Network with Two-Phase Training (#1925)
530 | - Improved Differentiable Architecture Search for Language Model and Named Entity Recognition (#2104)
531 | - Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets (#2696)
532 | - Single Training Dimension Selection for Word Embedding with PCA (#2741) [[arXiv]](https://arxiv.org/abs/1909.01761)
533 | - A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text (#3040) [[arXiv]](https://arxiv.org/abs/1909.00868)
534 | - SciBERT: A Pretrained Language Model for Scientific Text (#3115) [[arXiv]](https://arxiv.org/abs/1903.10676)
535 | - Humor Detection: A Transformer Gets the Last Laugh (#3265) [[arXiv]](https://arxiv.org/abs/1909.00252)
536 | - Combining Global Sparse Gradients with Local Gradients in Distributed Neural Network Training (#3585)
537 | - Small and Practical BERT models for Sequence Labeling (#3631) [[arXiv]](https://arxiv.org/abs/1909.00100)
538 | - Data Augmentation with Atomic Templates for Spoken Language Understanding (#3776) [[arXiv]](https://arxiv.org/abs/1908.10770)
539 | - PaLM: A Hybrid Parser and Language Model (#4026) [[arXiv]](https://arxiv.org/abs/1909.02134)
540 | - A Pilot Study for Chinese SQL Semantic Parsing (#1593) [[arXiv]](https://arxiv.org/abs/1909.13293)
541 | - Global Reasoning over Database Structures for Text-to-SQL Parsing (#1616) [[arXiv]](https://arxiv.org/abs/1908.11214)
542 | - Transductive Learning of Neural Language Models for Syntactic and Semantic Analysis (#1712)
543 | - Efficient Sentence Embedding using Discrete Cosine Transform (#2287) [[arXiv]](https://arxiv.org/abs/1909.03104)
544 | - A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection (#2393)
545 | - PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification (#3233) [[arXiv]](https://arxiv.org/abs/1908.11828)
546 | - Pretrained Language Models for Sequential Sentence Classification (#3887) [[arXiv]](https://arxiv.org/abs/1909.04054)
547 | - Emergent Linguistic Phenomena in Multi-Agent Communication Games (#2402) [[arXiv]](https://arxiv.org/abs/1901.08706)
548 | 
549 | #### Machine Learning
550 | - A Logic-Driven Framework for Consistency of Neural Models (#6) [[arXiv]](https://arxiv.org/abs/1909.00126)
551 | - Style Transfer for Texts: to Err is Human, but Error Margins Matter (#109)
552 | - Implicit Deep Latent Variable Models for Text Generation (#161) [[arXiv]](https://arxiv.org/abs/1908.11527)
553 | - Text Emotion Distribution Learning from Small Sample: A Meta-Learning Approach (#200)
554 | - Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation (#247) [[arXiv]](https://arxiv.org/abs/1901.00398)
555 | - Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks (#373) [[arXiv]](https://arxiv.org/abs/1908.10084)
556 | - Learning Only from Relevant Keywords and Unlabeled Documents (#399) [[arXiv]](http://arxiv.org/abs/1910.04385)
557 | - Denoising-based Sequence-to-Sequence Pre-training for Text Generation (#592) [[arXiv]](https://arxiv.org/abs/1908.08206)
558 | - Dialog Intent Induction with Deep Multi-View Clustering (#686) [[arXiv]](https://arxiv.org/abs/1908.11487)
559 | - Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction (#718) [[arXiv]](https://arxiv.org/abs/1909.03881)
560 | - Auditing Deep Learning processes through Kernel-based Explanatory Models (#888)
561 | - Enhancing Recurrent Variational Autoencoders with Mutual Information Estimation for Text Generation (#1060)
562 | - Sampling Bias in Deep Active Classification: An Empirical Study (#1286) [[arXiv]](https://arxiv.org/abs/1909.09389)
563 | - Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases (#1321) [[arXiv]](https://arxiv.org/abs/1909.03683)
564 | - Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation (#1360) [[arXiv]](https://arxiv.org/abs/1909.01492)
565 | - Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control (#1422)
566 | - Experimenting with Power Divergences for Language Modeling (#1435)
567 | - Hierarchically-Refined Label Attention Network for Sequence Labeling (#1590) [[arXiv]](https://arxiv.org/abs/1908.08676)
568 | - Certified Robustness to Adversarial Word Substitutions (#1709) [[arXiv]](https://arxiv.org/abs/1909.00986)
569 | - Visualizing and Understanding the Effectiveness of BERT (#1846) [[arXiv]](https://arxiv.org/abs/1908.05620)
570 | - Topics to Avoid: Demoting Latent Confounds in Text Classification (#2147) [[arXiv]](https://arxiv.org/abs/1909.00453)
571 | - Learning to Ask for Conversational Machine Learning (#2168)
572 | - Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative Training (#2270) [[arXiv]](https://arxiv.org/abs/1810.11895)
573 | - Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs (#2394)
574 | - Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation (#2441) [[arXiv]](https://arxiv.org/abs/1909.04315)
575 | - Exploiting Monolingual Data at Scale for Neural Machine Translation (#2477)
576 | - Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs (#2554) [[arXiv]](https://arxiv.org/abs/1909.01515)
577 | - Distributionally Robust Language Modeling (#2660) [[arXiv]](https://arxiv.org/abs/1909.02060)
578 | - Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling (#2686) [[arXiv]](https://arxiv.org/abs/1904.02817)
579 | - Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds (#2706) [[arXiv]](https://arxiv.org/abs/1908.11421)
580 | - Parallel Iterative Edit Models for Local Sequence Transduction (#2716) [[arXiv]](https://arxiv.org/abs/1910.02893)
581 | - ARAML: A Stable Adversarial Training Framework for Text Generation (#2882) [[arXiv]](https://arxiv.org/abs/1908.07195)
582 | - FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow (#2905) [[arXiv]](https://arxiv.org/abs/1909.02480)
583 | - Compositional Generalization for Premitive Substitutions (#3039) [[arXiv]](https://arxiv.org/abs/1910.02612)
584 | - WikiCREM: A large unsupervised corpus for co-reference resolution (#3089) [[arXiv]](https://arxiv.org/abs/1908.08025)
585 | - Identifying and Explaining Discriminative Attributes (#3146) [[arXiv]](https://arxiv.org/abs/1909.05363)
586 | - Patient Knowledge Distillation for BERT Model Compression (#3194) [[arXiv]](https://arxiv.org/abs/1908.09355)
587 | - Neural Gaussian Copula for Variational Autoencoder (#3254) [[arXiv]](https://arxiv.org/abs/1909.03569)
588 | - Empirical Study of Transformer's Attention Mechanism via the Lens of Kernel (#3261)
589 | - Learning to Learn and Predict: A Meta-Learning Approach for Multi-Label Classification (#3478) [[arXiv]](https://arxiv.org/abs/1909.04176)
590 | - Revealing the Dark Secrets of BERT (#3494) [[arXiv]](https://arxiv.org/abs/1908.08593)
591 | - Machine Translation With Weakly Paired Documents (#4149)
592 | - Countering Language Drift via Grounding (#2201)
593 | 
594 | #### Social Media and Computational Social Science, Text Mining and NLP Applications
595 | - Integrating Text and Image: Determining Multimodal Document Intent in Instagram Posts (#52) [[arXiv]](http://arxiv.org/abs/1904.09073)
596 | - Neural Conversation Recommendation with Online Interaction Modeling (#705)
597 | - Different Acquisition from the Same Sharing: Sifting Multi-task Learning for Fake News Detection (#720) [[arXiv]](https://arxiv.org/abs/1909.01720)
598 | - Text-based inference of moral sentiment change (#965)
599 | - Detecting Causal Language Use in Science Findings (#1439)
600 | - Multilingual and Multi-aspect Hate Speech Analysis (#1468) [[arXiv]](https://arxiv.org/abs/1908.11049)
601 | - MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims (#1969) [[arXiv]](https://arxiv.org/abs/1909.03242)
602 | - A Deep Neural Information Fusion Architecture for Textual Network Embeddings (#2006) [[arXiv]](https://arxiv.org/abs/1908.11057)
603 | - You Shall Know a User by the Company It Keeps: Dynamic Representations for Social Media Users in NLP (#2186) [[arXiv]](https://arxiv.org/abs/1909.00412)
604 | - Unsupervised Domain Adaptation for Political Document Analysis (#2606)
605 | - Macrocosm: Social Media Persona Linking for OSINT Applications (#2659)
606 | - A Hierarchical Location Prediction Neural Network for Twitter User Geolocation (#2693)
607 | - Trouble on the Horizon: Forecasting the Derailment of Online Conversations as they Develop (#2828) [[arXiv]](https://arxiv.org/abs/1909.01362)
608 | - A Benchmark Dataset for Learning to Intervene in Online Hate Speech (#3391) [[arXiv]](https://arxiv.org/abs/1909.04251)
609 | - Detecting and Reducing Bias in a High Stakes Domain (#3461) [[arXiv]](https://arxiv.org/abs/1908.11474)
610 | - CodeSwitch-Reddit: Exploration of Written Multilingual Discourse in Online Discussion Forums (#3566) [[arXiv]](https://arxiv.org/abs/1908.11841)
611 | - Modeling Conversation Structure and Temporal Dynamics for Jointly Predicting Rumor Stance and Veracity (#3592) [[arXiv]](https://arxiv.org/abs/1909.08211)
612 | - Measuring Online Debaters' Persuasive Skill from Text over Time (#TACL-1639)
613 | - Reconstructing Capsule Networks for Zero-shot Intent Classification (#142)
614 | - Domain Adaptation for Person-Job Fit with Transferable Deep Global Match Network (#239)
615 | - Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification (#299)
616 | - Comparing and Developing Tools to Measure the Readability of Domain-Specific Texts (#438)
617 | - News2vec: News Network Embedding with Subnode Information (#473)
618 | - Recursive Context-Aware Lexical Simplification (#732)
619 | - Transfer Learning from Medical Literature for Section Prediction in Electronic Health Records (#1103)
620 | - Neural News Recommendation with Heterogeneous User Behavior (#1459)
621 | - Reviews Meet Graphs: Enhancing User and Item Representations for Recommendation with Hierarchical Attentive Graph Neural Network (#1470)
622 | - Event Representation Learning Enhanced with External Commonsense Knowledge (#1551) [[arXiv]](https://arxiv.org/abs/1909.05190)
623 | - Learning to Discriminate Perturbations for Blocking Adversarial Attacks in Text Classification (#1572) [[arXiv]](https://arxiv.org/abs/1909.03084)
624 | - A Neural Citation Count Prediction Model based on Peer Review Text (#1661)
625 | - Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs (#2044) [[arXiv]](http://arxiv.org/abs/1909.00228)
626 | - Semi-supervised Text Style Transfer: Cross Projection in Latent Space (#2052) [[arXiv]](https://arxiv.org/abs/1909.11493)
627 | - Question Answering for Privacy Policies: Combining Computational and Legal Perspectives (#2129)
628 | - Stick to the Facts: Learning towards a Fidelity-oriented E-Commerce Product Description Generation (#2381)
629 | - Fine-Grained Entity Typing via Hierarchical Multi Graph Convolutional Networks (#2389)
630 | - Learning to Infer Entities, Properties and their Relations from Clinical Conversations (#2942) [[arXiv]](https://arxiv.org/abs/1908.11536)
631 | - Practical Correlated Topic Modeling via the Rectified Anchor Word Algorithm (#3072)
632 | - Modeling the Relationship between User Comments and Edits in Document Revision (#3128)
633 | - PRADO: Projection Attention Networks for Document Classification On-Device (#3218)
634 | - Subword Language Model for Query Auto-Completion (#3873) [[arXiv]](https://arxiv.org/abs/1909.00599)
635 | - Enhancing Dialogue Symptom Diagnosis with Global Attention and Symptom Graph (#4069)
636 | 
637 | #### Sentiment Analysis and Argument Mining, Lexical Semantics, Sentence-level Semantics
638 | - Multi-Relational Word Embeddings for Selectional Preferences (#623)
639 | - MulCode: A Multiplicative Multi-way Model for Compressing Neural Language Model (#700)
640 | - It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Augmentation (#1220) [[arXiv]](http://arxiv.org/abs/1909.00871)
641 | - Examining Gender Bias in Languages with Grammatical Gender (#1741) [[arXiv]](https://arxiv.org/abs/1909.02224)
642 | - Weakly Supervised Cross-lingual Semantic Relation Classification via Knowledge Distillation (#3071)
643 | - Improved Word Sense Disambiguation Using Pre-Trained Contextualized Word Representations (#3702) [[arXiv]](https://arxiv.org/abs/1910.00194)
644 | - Do Neural NLP Models Know Numbers? Probing Numeracy in Embeddings (#3972) [[arXiv]](https://arxiv.org/abs/1909.07940)
645 | - A Split-and-Recombine Approach for Follow-up Query Analysis (#552) [[arXiv]](https://arxiv.org/abs/1909.08905)
646 | - Text2Math: End-to-end Parsing Text into Math Expressions (#1086) [[arXiv]](https://arxiv.org/abs/1910.06571)
647 | - Editing-based SQL Query Generation for Cross-Domain Context-Dependent Questions (#1287) [[arXiv]](https://arxiv.org/abs/1909.00786)
648 | - Syntax-aware Multilingual Semantic Role Labeling (#1351) [[arXiv]](https://arxiv.org/abs/1909.00310)
649 | - Cloze-driven Pretraining of Self-attention Networks (#1446) [[arXiv]](https://arxiv.org/abs/1903.07785)
650 | - Bridging the Gap between Relevance Matching and Semantic Matching for Short Text Similarity Modeling (#1558)
651 | - A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling (#1836)
652 | - Injecting Phrasal Paraphrase Relation into Sentence Representation for Semantic Equivalence Assessment (#2060)
653 | - Data-Anonymous Encoding for Text-to-SQL Generation (#2231)
654 | - Capturing Argument Interaction in Semantic Role Labeling with Capsule Networks (#2993) [[arXiv]](https://arxiv.org/abs/1910.03136)
655 | - Learning Programmatic Idioms for Scalable Semantic Parsing (#3121) [[arXiv]](http://arxiv.org/abs/1904.09086)
656 | - Jupyter: A Large Scale Distantly Supervised Dataset for Open Domain Context Based Code Generation (#3451) [[arXiv]](https://arxiv.org/abs/1910.02216)
657 | - Model-based Interactive Semantic Parsing: A Unified Formulation and A Text-to-SQL Case Study (#3527) [[arXiv]](https://arxiv.org/abs/1910.05389)
658 | - Modeling Graph Structure in Transformer for Better AMR-to-Text Generation (#3835) [[arXiv]](https://arxiv.org/abs/1909.00136)
659 | - Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks (#72) [[arXiv]](https://arxiv.org/abs/1909.02606)
660 | - Learning Explicit and Implicit Structures for Targeted Sentiment Analysis (#281) [[arXiv]](https://arxiv.org/abs/1909.07593)
661 | - Capsule Network with Interactive Attention for Aspect-Level Sentiment Classification (#317)
662 | - Emotion Detection with Neural Personal Discrimination (#402) [[arXiv]](https://arxiv.org/abs/1908.10703)
663 | - Specificity-Driven Cascading Approach for Unsupervised Sentiment Modification (#475)
664 | - Lexical-Based Adversarial Reinforcement Training for Robust Sentiment Classification (#891)
665 | - Leveraging Structural and Semantic Correspondence for Attribute-Oriented Aspect Sentiment Discovery (#896) [[arXiv]](http://arxiv.org/abs/1908.10970)
666 | - From the Token to the Review: A Hierarchical Multimodal approach to Opinion Mining (#936) [[arXiv]](https://arxiv.org/abs/1908.11216)
667 | - Shallow Domain Adaptive Embeddings for Sentiment Analysis (#1477) [[arXiv]](https://arxiv.org/abs/1908.06082)
668 | - Domain-Invariant Feature Distillation for Cross-Domain Sentiment Classification (#1691) [[arXiv]](https://arxiv.org/abs/1908.09122)
669 | - A Novel Aspect-Guided Deep Transition Model for Aspect Based Sentiment Analysis (#1705) [[arXiv]](https://arxiv.org/abs/1909.00324)
670 | - Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning (#1713)
671 | - A Dataset of General-Purpose Rebuttal (#1840) [[arXiv]](https://arxiv.org/abs/1909.00393)
672 | - Rethinking Attribute Representation and Injection for Sentiment Classification (#1992) [[arXiv]](https://arxiv.org/abs/1908.09590)
673 | - A Knowledge Regularized Hierarchical Approach for Emotion Cause Analysis (#2236)
674 | - Automatic Argument Quality Assessment - New Datasets and Methods (#2447) [[arXiv]](https://arxiv.org/abs/1909.01007)
675 | - Fine-Grained Analysis of Propaganda in News Articles (#2493)
676 | - Context-aware Interactive Attention for Multi-modal Sentiment and Emotion Analysis (#2707)
677 | - Sequential Learning of Convolutional Features for Effective Text Classification (#3182) [[arXiv]](https://arxiv.org/abs/1909.00080)
678 | - The Role of Pragmatic and Discourse Context in Determining Argument Impact (#3909)
679 | - Aspect-Level Sentiment Analysis Via Convolution over Dependency Tree (#4182)
680 | 
681 | #### Discourse and Pragmatics, Linguistic Theories, Textual Inference, Question Answering, Summarization and Generation
682 | - Next Sentence Prediction helps Implicit Discourse Relation Classification within and across Domains (#982)
683 | - Split or Merge: Which is Better for Unsupervised RST Parsing? (#1701)
684 | - BERT for Coreference Resolution: Baselines and Analysis (#3731) [[arXiv]](https://arxiv.org/abs/1908.09091)
685 | - Linguistic Versus Latent Relations for Modeling a Flow in Paragraphs (#3815) [[arXiv]](https://arxiv.org/abs/1908.11790)
686 | - Event Causality Recognition Exploiting Multiple Annotators' Judgments and Background Knowledge (#4125)
687 | - What Part of the Neural Network Does This? Understanding LSTMs by Measuring and Dissecting Memory Cells (#1181)
688 | - Quantity doesn't buy quality syntax with neural language models (#1227) [[arXiv]](https://arxiv.org/abs/1909.00111)
689 | - Higher-order Comparisons of Sentence Encoder Representations (#2000) [[arXiv]](https://arxiv.org/abs/1909.00303)
690 | - Text Genre and Training Data Size in Human-Like Parsing (#2379)
691 | - Feature2Vec: Distributional semantic modelling of human property knowledge (#2535) [[arXiv]](https://arxiv.org/abs/1908.11439)
692 | - Has Pepperoni and Still Vegan?! Improving Answer Consistency in VQA through Entailed Question Generation (#424) [[arXiv]](https://arxiv.org/abs/1909.04696)
693 | - GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level (#961) [[arXiv]](https://arxiv.org/abs/1908.07855)
694 | - Revisiting the Evaluation of Theory of Mind through Question Answering (#1069)
695 | - Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering (#1319) [[arXiv]](https://arxiv.org/abs/1908.08167)
696 | - A Span-Extraction Dataset for Chinese Machine Reading Comprehension (#2131) [[arXiv]](https://arxiv.org/abs/1810.07366)
697 | - CLAR: Contextualized and Lexicalized Aspect Representation for Non-factoid Question Answering (#2177)
698 | - Machine Reading Comprehension Using Structural Knowledge Graph-aware Network (#2229)
699 | - Answering Conversational Questions on Structured Data without Logical Forms (#2851) [[arXiv]](https://arxiv.org/abs/1908.11787)
700 | - Improving Answer Selection and Answer Triggering using Hard Negatives (#2859)
701 | - Can You Unpack That? Learning to Rewrite Questions-in-Context (#3163)
702 | - Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning (#3203) [[arXiv]](https://arxiv.org/abs/1908.05803)
703 | - Zero-shot Reading Comprehension by Cross-lingual Transfer Learning with Multi-lingual Language Representation Model (#3303) [[arXiv]](https://arxiv.org/abs/1909.09587)
704 | - QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions (#3355) [[arXiv]](https://arxiv.org/abs/1909.03553)
705 | - Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension (#3470) [[arXiv]](https://arxiv.org/abs/1909.00109)
706 | - A Gated Self-attention Memory Network for Answer Selection (#4067) [[arXiv]](https://arxiv.org/abs/1909.09696)
707 | - Polly Want a Cracker: Analyzing Performance of Parroting on Paraphrase Generation Datasets (#91) [[arXiv]](https://arxiv.org/abs/1908.07831)
708 | - Query-focused Sentence Compression in Linear Time (#482) [[arXiv]](https://arxiv.org/abs/1904.09051)
709 | - Generating Personalized Recipes from Historical User Preferences (#1255) [[arXiv]](https://arxiv.org/abs/1909.00105)
710 | - Generating Highly Relevant Questions (#1644) [[arXiv]](http://arxiv.org/abs/1910.03401)
711 | - Improving Neural Story Generation by Targeted Common Sense Grounding (#1674) [[arXiv]](https://arxiv.org/abs/1908.09451)
712 | - Abstract Text Summarization: A Low Resource Challenge (#1963)
713 | - Generating Modern Poetry Automatically in Finnish (#2083)
714 | - SUM-QE: a BERT-based Summary Quality Estimation Model (#2422) [[arXiv]](https://arxiv.org/abs/1909.00578)
715 | - An Empirical Comparison on Imitation Learning and Reinforcement Learning for Paraphrase Generation (#2870) [[arXiv]](https://arxiv.org/abs/1908.10835)
716 | - Countering the effects of lead bias in news summarization via multi-stage training and auxiliary losses (#3236) [[arXiv]](http://arxiv.org/abs/1909.04028)
717 | - Learning Rhyming Constraints using Structured Adversaries (#3950) [[arXiv]](https://arxiv.org/abs/1909.06743)
718 | - Question-type Driven Question Generation (#4105) [[arXiv]](https://arxiv.org/abs/1909.00140)
719 | - Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization (#4107) [[arXiv]](https://arxiv.org/abs/1909.00141)
720 | - Clause-Wise and Recursive Decoding for Complex and Cross-Domain Text-to-SQL Generation (#285) [[arXiv]](https://arxiv.org/abs/1904.08835)
721 | - Do Nuclear Submarines Have Nuclear Captains? A Challenge Dataset for Commonsense Reasoning over Adjectives and Objects (#1774)
722 | - Aggregating Bidirectional Encoder Representations Using MatchLSTM for Sequence Matching (#2244)
723 | - What Does This Word Mean? Explaining Contextualized Embeddings with Natural Language Definition (#2765)
724 | - Pre-Training BERT on Domain Resources for Short Answer Grading (#3058)
725 | - WIQA: A dataset for “What if...” reasoning over procedural text (#3276) [[arXiv]](https://arxiv.org/abs/1909.04739)
726 | - Evaluating BERT for natural language inference: a case study on the CommitmentBank (#3606)
727 | - Incorporating Domain Knowledge into Medical NLI using Knowledge Graphs (#3974) [[arXiv]](https://arxiv.org/abs/1909.00160)
728 | 
729 | #### Information Extraction, Text Mining and NLP Applications, Social Media and Computational Social Science, Sentiment Analysis and Argument Mining
730 | - An Attentive Fine-Grained Entity Typing Model with Latent Type Representation (#189)
731 | - An Improved Neural Baseline for Temporal Relation Extraction (#193) [[arXiv]](https://arxiv.org/abs/1909.00429)
732 | - Improving Fine-grained Entity Typing with Entity Linking (#822) [[arXiv]](https://arxiv.org/abs/1909.12079)
733 | - Combining Spans into Entities: A Neural Two-Stage Approach for Recognizing Discontiguous Entities (#1222) [[arXiv]](http://arxiv.org/abs/1909.00930)
734 | - Cross-Sentence N-ary Relation Extraction using Lower-Arity Universal Schemas (#1686)
735 | - GEANN: Gazetteer-Enhanced Attentive Neural Networks for Named Entity Recognition (#1760)
736 | - “A Buster Keaton of Linguistics”: First Automated Approaches for the Extraction of Vossian Antonomasia (#1782)
737 | - Multi-Task Learning for Chemical Named Entity Recognition with Chemical Compound Paraphrase (#1799)
738 | - FewRel 2.0: Towards More Challenging Few-Shot Relation Classification (#2697) [[arXiv]](https://arxiv.org/abs/1910.07124)
739 | - ner and pos when nothing is capitalized (#2992) [[arXiv]](https://arxiv.org/abs/1903.11222)
740 | - CaRB: A Crowdsourced Benchmark for Open IE (#4099)
741 | - Weakly Supervised Attention Networks for Entity Extraction (#4158)
742 | - Revealing and Predicting Online Persuasion Strategy with Elementary Units (#19)
743 | - A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis (#849)
744 | - Learning with Noisy Labels for Sentence-level Sentiment Classification (#1157) [[arXiv]](https://arxiv.org/abs/1909.00124)
745 | - DENS: A Dataset for Multi-class Emotion Analysis (#1347)
746 | - Multi-Task Stance Detection with Sentiment and Stance Lexicons (#3016)
747 | - A Robust Self-Learning Framework for Cross-Lingual Text Classification (#3085)
748 | - Learning to Flip the Sentiment of Reviews from Non-Parallel Corpora (#3869)
749 | - Label Embedding using Hierarchical Structure of Labels for Twitter Classification (#80)
750 | - Interpretable Word Embeddings via Informative Priors (#393) [[arXiv]](http://arxiv.org/abs/1909.01459)
751 | - TalkDown: A Corpus for Condescension Detection in Context (#1526) [[arXiv]](https://arxiv.org/abs/1909.11272)
752 | - Adversarial Removal of Demographic Attributes Revisited (#2101) [[arXiv]](https://arxiv.org/abs/1808.06640)
753 | - A deep-learning framework to detect sarcasm targets (#2170)
754 | - In Plain Sight: Media Bias through the Lens of Factual Reporting (#2759) [[arXiv]](https://arxiv.org/abs/1909.02670)
755 | - Incorporating Label Dependencies in Multilabel Stance Detection (#3333)
756 | - Investigating Sports Commentator Bias within a Large Corpus of American Football Broadcasts (#3345)
757 | - Charge-Based Prison Term Prediction with Deep Gating Network (#759) [[arXiv]](https://arxiv.org/abs/1908.11521)
758 | - Restoring ancient text using deep learning: a case study on Greek epigraphy (#1020) [[arXiv]](https://arxiv.org/abs/1910.06262)
759 | - Embedding Lexical Features via Tensor Decomposition for Small Sample Humor Recognition (#1068)
760 | - EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks (#1192) [[arXiv]](https://arxiv.org/abs/1901.11196)
761 | - Neural News Recommendation with Multi-Head Self-Attention (#1581)
762 | - What Matters for Neural Cross-Lingual Named Entity Recognition: An Empirical Analysis (#1611) [[arXiv]](https://arxiv.org/abs/1909.03598)
763 | - Telling the Whole Story: A Manually Annotated Chinese Dataset for the Analysis of Humor in Jokes (#1737)
764 | - Generating Natural Anagrams: Towards Language Generation under Hard Combinatorial Constraints (#1763)
765 | - STANCY: Stance Classification Based on Consistency Cues (#2013) [[arXiv]](https://arxiv.org/abs/1910.06048)
766 | - Cross-lingual intent classification in a low resource industrial setting (#2551)
767 | - SoftRegex: Generating Regex from Natural Language Description using Softened Regex Equivalence (#2839)
768 | - Using Clinical Notes with Multimodal Learning for ICU Management. (#2907)
769 | - Spelling-Aware Construction of Mixed-Language Texts for Teaching Foreign-Language Vocabulary (#3639)
770 | - Towards Machine Reading for Interventions from Humanitarian-Assistance Program Literature (#3718)
771 | - RUN through the Streets: Dataset and Models for Realistic Urban Navigation (#4014) [[arXiv]](https://arxiv.org/abs/1909.08970)
772 | 
773 | 


--------------------------------------------------------------------------------
/data/oral_paper_by_topic.json:
--------------------------------------------------------------------------------
  1 | {
  2 |     "Machine Learning": [
  3 |         "Attending to Future Tokens for Bidirectional Sequence Generation (#1443)",
  4 |         "Attention is Not Not Explanation (#526)",
  5 |         "Practical Obstacles to Deploying Active Learning (#1176)",
  6 |         "Transfer Learning Between Related Tasks Using Expected Label Proportions (#1207)",
  7 |         "Insertion-based Decoding with automatically Inferred Generation Order (#TACL-1732)",
  8 |         "Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets (#1092)",
  9 |         "Robust Text Classifier on Test-Time Budgets (#1128)",
 10 |         "Commonsense Knowledge Mining from Pretrained Models (#3289)",
 11 |         "RNN Architecture Learning with Sparse Regularization (#3428)",
 12 |         "Universal Trigger Sequences for Attacking and Analyzing NLP (#1515)",
 13 |         "To Annotate or Not? Unsupervised Prediction of Performance Drop due to Domain Shift (#2756)",
 14 |         "Adaptively Sparse Transformers (#2900)",
 15 |         "Show Your Work: Improved Reporting of Experimental Results (#3277)",
 16 |         "A Deep Factorization of Style and Structure in Fonts (#3999)"
 17 |     ],
 18 |     "Lexical Semantics": [
 19 |         "Knowledge Enhanced Contextual Word Representations (#3403)",
 20 |         "How Contextual are Contextualized Word Representations? (#208)",
 21 |         "Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings (#783)",
 22 |         "On Correlations between Word Vector Sets (#3976)",
 23 |         "Game Theory Meets Embeddings: a Unified Framework for Word Sense Disambiguation (#1724)",
 24 |         "Cross-lingual Semantic Specialization via Lexical Relation Induction (#1735)",
 25 |         "Modelling the interplay of metaphor and emotion through multitask learning (#2670)",
 26 |         "How well do NLI models capture verb veridicality? (#3460)",
 27 |         "Modeling Color Terminology Across Thousands of Languages (#3515)",
 28 |         "Negative Focus Detection via Contextual Attention Mechanisms (#1314)",
 29 |         "Exploring Human Gender Stereotypes with Word Association Test (#1912)",
 30 |         "Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition (#TACL-1729)",
 31 |         "Where''s My Head? Definition, Dataset and Models for Numeric Fused-Heads Identification and Resolution (#TACL-1648)"
 32 |     ],
 33 |     "Dialog and Interactive Systems": [
 34 |         "Guided Dialog Policy Learning: Reward Estimation for Multi-Domain Task-Oriented Dialog (#166)",
 35 |         "Multi-hop Selector Network for Multi-turn Response Selection in Retrieval-based Chatbots (#554)",
 36 |         "MoEL: Mixture of Empathetic Listeners (#1053)",
 37 |         "Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever (#2430)",
 38 |         "Building Task-Oriented Visual Dialog Systems Through Alternative Optimization Between Dialog Policy and Language Generation (#3756)",
 39 |         "TaskMaster Dialog Corpus: Toward a Realistic and Diverse Dataset (#510)",
 40 |         "MultiDoGO: Multi-Domain Goal-Oriented Dialogues (#1564)",
 41 |         "Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack (#1186)",
 42 |         "GECOR: An End-to-End Generative Ellipsis and Co-reference Resolution Model for Task-Oriented Dialogue (#1853)",
 43 |         "Task-Oriented Conversation Generation Using Heterogeneous Memory Networks (#496)"
 44 |     ],
 45 |     "Sentiment Analysis and Argument Mining": [
 46 |         "DialogueGCN: A Graph-based Network for Emotion Recognition in Conversation (#2092)",
 47 |         "Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations (#1814)",
 48 |         "Interpretable Relevant Emotion Ranking with Event-Driven Attention (#3544)",
 49 |         "Justifying Recommendations using Distantly-Labeled Reviews and Fined-Grained Aspects (#518)",
 50 |         "Using Customer Service Dialogues for Satisfaction Analysis with Context-Assisted Multiple Instance Learning (#204)",
 51 |         "What Gets Echoed? Understanding the \u201cPointers\u201d in Explanations of Persuasive Arguments (#2089)",
 52 |         "Modeling Frames in Argumentation (#2267)",
 53 |         "AMPERSAND: Argument Mining for PERSuAsive oNline Discussions (#3321)",
 54 |         "Evaluating adversarial attacks against multiple fact verification systems (#427)",
 55 |         "Nonsense!: Quality Control via Two-Step Reason Selection for Annotating Local Acceptability and Related Attributes in News Editorials (#564)",
 56 |         "On the Importance of Delexicalization for Fact Verification (#2984)",
 57 |         "Towards Debiasing Fact Verification Models (#3338)",
 58 |         "Recognizing Conflict Opinions in Aspect-level Sentiment Classification with Dual Attention Networks (#911)",
 59 |         "Investigating Dynamic Routing in Tree-Structured LSTM for Sentiment Analysis (#1395)",
 60 |         "Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks (#381)",
 61 |         "Coupling Global and Local Context for Unsupervised Aspect Extraction (#1988)",
 62 |         "Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning (#65)",
 63 |         "CAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis (#1995)",
 64 |         "Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training (#3207)"
 65 |     ],
 66 |     "Summarization and Generation": [
 67 |         "Neural Text Summarization: A Critical Evaluation (#3687)",
 68 |         "Neural data-to-text generation: A comparison between pipeline and end-to-end architectures (#2586)",
 69 |         "MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance (#1175)",
 70 |         "Select and Attend: Towards Controllable Content Selection in Text Generation (#3049)",
 71 |         "Sentence-Level Content Planning and Style Specification for Neural Text Generation (#3357)"
 72 |     ],
 73 |     "Sentence-level Semantics": [
 74 |         "Translate and Label! An Encoder-Decoder Approach for Cross-lingual Semantic Role Labeling (#2740)",
 75 |         "Syntax-Enhanced Self-Attention-Based Semantic Role Labeling (#2106)",
 76 |         "VerbAtlas: a Novel Large-Scale Verbal Semantic Resource and Its Application to Semantic Role Labeling (#2213)",
 77 |         "Parameter-free Sentence Embedding via Orthogonal Basis (#1099)",
 78 |         "Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations (#3807)",
 79 |         "Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs (#2676)",
 80 |         "Broad-Coverage Semantic Parsing as Transduction (#263)",
 81 |         "Core Semantic First: A Top-down Approach for AMR Parsing (#1544)",
 82 |         "Don't paraphrase, detect! Rapid and Effective Data Collection for Semantic Parsing (#2904)",
 83 |         "Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond (#TACL-1742)"
 84 |     ],
 85 |     "Speech, Vision, Robotics, Multimodal and Grounding": [
 86 |         "Extracting Possessions from Social Media: Images Complement Language (#3013)",
 87 |         "Learning to Speak and Act in a Fantasy Text Adventure Game (#1243)",
 88 |         "Help, Anna! Vision-based Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learning (#1542)",
 89 |         "Incorporating Visual Semantics into Sentence Representations within a Grounded Space (#2247)",
 90 |         "Neural Naturalist: Generating Fine-Grained Image Comparisons (#3024)",
 91 |         "LXMERT: Learning Cross-Modality Encoder Representations from Transformers (#3048)",
 92 |         "Phrase Grounding by Soft-Label Chain Conditional Random Field (#3765)",
 93 |         "What You See is What You Get: Visual Pronoun Coreference Resolution in Conversations (#549)",
 94 |         "YouMakeup: A Large-Scale Domain-Specific Multimodal Dataset for Fine-Grained Semantic Comprehension (#122)",
 95 |         "DEBUG: A Dense Bottom-Up Grounding Approach for Natural Language Video Localization (#167)"
 96 |     ],
 97 |     "Information Extraction": [
 98 |         "Fine-Grained Evaluation for Entity Linking (#116)",
 99 |         "Supervising Unsupervised Open Information Extraction Models (#3069)",
100 |         "Neural Cross-Lingual Event Detection with Minimal Parallel Resources (#1723)",
101 |         "KnowledgeNet: A Benchmark Dataset for Knowledge Base Population (#1258)",
102 |         "Effective Use of Transformer Networks for Entity Tracking (#3308)",
103 |         "Improving Distantly-Supervised Relation Extraction with Joint Label Embedding (#337)",
104 |         "Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network (#566)",
105 |         "Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction (#1057)",
106 |         "Easy First Relation Extraction with Information Redundancy (#1640)",
107 |         "Dependency-Guided LSTM-CRF for Named Entity Recognition (#2509)",
108 |         "CrossWeigh: Training Named Entity Tagger from Imperfect Annotations (#2712)",
109 |         "A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers (#3259)",
110 |         "Open Domain Web Keyphrase Extraction Beyond Language Modeling (#1119)",
111 |         "TuckER: Tensor Factorization for Knowledge Graph Completion (#990)",
112 |         "Weakly Supervised Domain Detection (#TACL-1712)",
113 |         "Event Detection with Multi-Order Graph Convolution and Aggregated Attention (#835)",
114 |         "Coverage of Information Extraction from Sentences and Paragraphs (#1285)",
115 |         "HMEAE: Hierarchical Modular Event Argument Extraction (#2354)",
116 |         "Entity, Relation, and Event Extraction with Contextualized Span Representations (#3930)"
117 |     ],
118 |     "Semantics": [
119 |         "Analytical Methods for Interpretable Ultradense Word Embeddings (#75)",
120 |         "Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks (#3142)",
121 |         "Retrofitting Contextualized Word Embeddings with Paraphrases (#3045)",
122 |         "Incorporating Contextual and Syntactic Structures Improves Semantic Similarity Modeling (#3508)"
123 |     ],
124 |     "Discourse, Summarization, and Generation": [
125 |         "Neural Linguistic Steganography (#3399)",
126 |         "The Feasibility of Embedding Based Automatic Evaluation for Single Document Summarization (#3018)",
127 |         "Attention Optimization for Abstractive Document Summarization (#1918)",
128 |         "Rewarding Coreference Resolvers for Being Consistent with World Knowledge (#2020)"
129 |     ],
130 |     "Text Mining and NLP Applications": [
131 |         "An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction (#740)",
132 |         "A Multilingual Topic Model for Learning Weighted Topic Links Across Incomparable Corpora (#1257)",
133 |         "Measure Country-Level Socio-Economic Indicators with Streaming News: An Empirical Study (#3730)",
134 |         "Towards Extracting Medical Family History from Natural Language Interactions: A New Dataset and Baselines (#2903)",
135 |         "(Male, Bachelor) and (Female, Ph.D) have different connotations: Parallelly Annotated Stylistic Language Dataset with Multiple Personas (#3793)",
136 |         "Movie Plot Analysis via Turning Point Identification (#244)",
137 |         "Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention (#2488)",
138 |         "Deep Ordinal Regression for Pledge Specificity Prediction (#1903)",
139 |         "Enabling Robust Grammatical Error Correction in New Domains: Datasets, Metrics, and Analyses (#TACL-1677)",
140 |         "The Myth of Blind Review Revisited: Experiments on ACL vs. EMNLP (#2233)",
141 |         "Uncover Sexual Harassment Patterns from Personal Stories by Joint Key Element Extraction and Categorization (#2653)",
142 |         "Identifying Predictive Causal Factors from News Streams (#2864)",
143 |         "Training Data Augmentation for Detecting Adverse Drug Reactions in User-Generated Content (#3011)",
144 |         "Deep Reinforcement Learning-based Text Anonymization against Private-Attribute Inference (#3160)"
145 |     ],
146 |     "Neural Machine Translation": [
147 |         "Enhancing Context Modeling with a Query-Guided Capsule Network for Document-level NMT (#2416)",
148 |         "Simple, Scalable Adaptation for Neural Machine Translation (#3252)",
149 |         "Controlling Text Complexity in Neural Machine Translation (#3177)",
150 |         "Investigating Multilingual NMT Representations at Scale (#1388)",
151 |         "Hierarchical Modeling of Global Context for Document-Level Neural Machine Translation (#1423)"
152 |     ],
153 |     "Question Answering": [
154 |         "Cross-Lingual Machine Reading Comprehension (#8)",
155 |         "A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning (#582)",
156 |         "Neural Duplicate Question Detection without Labeled Training Data (#880)",
157 |         "Asking Clarification Questions in Knowledge-Based Question Answering (#889)",
158 |         "Multi-View Domain Adapted Sentence Embeddings for Low-Resource Unsupervised Duplicate Question Detection (#1646)",
159 |         "Interactive Language Learning by Question Answering (#1367)",
160 |         "What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering (#3238)",
161 |         "KagNet: Learning to Answer Commonsense Questions with Knowledge-Aware Graph Networks (#436)",
162 |         "Learning with Limited Data for Multilingual Reading Comprehension (#3518)",
163 |         "A Discrete Hard EM Approach for Weakly Supervised Question Answering (#3778)"
164 |     ],
165 |     "Social Media and Computational Social Science": [
166 |         "Multi-label Categorization of Accounts of Sexism using a Neural Framework (#172)",
167 |         "The Trumpiest Trump? Identifying a Subject's Most Characteristic Tweets (#1462)",
168 |         "Finding Microaggressions in the Wild: A Case for Locating Elusive Phenomena in Social Media Posts (#2950)",
169 |         "Reinforced Product Metadata Selection for Helpfulness Assessment of Customer Reviews (#694)",
170 |         "Learning Invariant Representations of Social Media Users (#3557)"
171 |     ],
172 |     "Discourse and Pragmatics": [
173 |         "A Unified Neural Coherence Model (#1792)",
174 |         "Topic-Guided Coherence Modeling for Sentence Ordering by Preserving Global and Local Information (#2642)",
175 |         "Neural Generative Rhetorical Structure Parsing (#4060)",
176 |         "Weak Supervision for Learning Discourse Structure (#2453)",
177 |         "Predicting Discourse Structure using Distant Supervision from Sentiment (#2625)"
178 |     ],
179 |     "Tagging, Chunking, Syntax and Parsing": [
180 |         "Designing and Interpreting Probes with Control Tasks (#4063)",
181 |         "Specializing Word Embeddings (for Parsing) by Information Bottleneck (#1357)",
182 |         "Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing - A Tale of Two Parsers Revisited (#2799)",
183 |         "Semantic graph parsing with recurrent neural network DAG grammars (#2863)",
184 |         "75 Languages, 1 Model: Parsing Universal Dependencies Universally (#1221)"
185 |     ],
186 |     "Linguistic Theories, Cognitive Modeling and Psycholinguistics": [
187 |         "Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts (#2585)",
188 |         "Investigating BERT's Knowledge of Language: Five Analysis Methods with NPIs (#3650)",
189 |         "Representation of Constituents in Neural Language Models: - Coordination Phrase as a Case Study (#3929)",
190 |         "Towards Zero-shot Language Modelling (#1745)",
191 |         "Neural Network Acceptability Judgments (#TACL-1710)"
192 |     ],
193 |     "Machine Translation and Multilinguality": [
194 |         "Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary Induction (#1131)",
195 |         "Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set (#1266)",
196 |         "Synchronously Generating Two Languages with Interactive Decoding (#1478)",
197 |         "On NMT Search Errors and Model Errors: Cat Got Your Tongue? (#1868)",
198 |         "Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? (#2459)",
199 |         "Weakly-Supervised Concept-based Adversarial Learning for Cross-lingual Word Embeddings (#2491)",
200 |         "Aligning Cross-lingual Entities with Multi-Aspect Information (#3541)",
201 |         "Contrastive Language Adaptation for Cross-Lingual Stance Detection (#2498)",
202 |         "Jointly Learning to Align and Translate with Transformer Models (#422)",
203 |         "Understanding Data Augmentation in Neural Machine Translation: Two Perspectives towards Generalization (#2192)",
204 |         "Simple and Effective Noisy Channel Modeling for Neural Machine Translation (#2869)",
205 |         "MultiFiT: Efficient Multi-lingual Language Model Fine-tuning (#745)",
206 |         "Hint-based Training for Non-AutoRegressive Machine Translation (#1064)",
207 |         "Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala English (#3349)",
208 |         "Constant-Time Machine Translation with Conditional Masked Language Models (#1204)",
209 |         "Learning to Copy for Automatic Post-Editing (#777)"
210 |     ],
211 |     "Reasoning and Question Answering": [
212 |         "Going on a vacation takes longer than \u201cGoing for a walk\u201d: A Study of Temporal Commonsense Understanding (#2533)",
213 |         "QAInfomax: Learning Robust Question Answering System by Mutual Information Maximization (#2798)",
214 |         "Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations (#329)",
215 |         "How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG (#586)"
216 |     ],
217 |     "Generation": [
218 |         "Pun-GAN: Generative Adversarial Network for Pun Generation (#267)",
219 |         "Multi-Task Learning with Language Modeling for Question Generation (#3820)",
220 |         "Autoregressive Text Generation beyond Feedback Loops (#3506)",
221 |         "The Woman Worked as a Babysitter: On Biases in Language Generation (#3874)",
222 |         "Counterfactual Story Reasoning and Generation (#3328)",
223 |         "Encode, Tag, Realize: High-Precision Text Editing (#2395)",
224 |         "Answer-guided and Semantic Coherent Question Generation in Open-domain Conversation (#128)",
225 |         "Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation (#1947)",
226 |         "A Topic Augmented Text Generation Model: Joint Learning of Semantics and Structural Features (#2822)",
227 |         "A Modular Architecture for Unsupervised Sarcasm Generation (#2725)",
228 |         "Interpoetry: Generating Classical Chinese Poems from Vernacular Chinese (#2534)",
229 |         "Set to Ordered Text: Generating Discharge Instructions from Medical Billing Codes (#724)"
230 |     ],
231 |     "Summarization": [
232 |         "Summary Cloze: A New Task for Content Selection in Topic-Focused Summarization (#1178)",
233 |         "Text Summarization with Pretrained Encoders (#392)",
234 |         "How to Write Summaries with Patterns? Learning towards Abstractive Summarization through Prototype Editing (#609)",
235 |         "Unsupervised Sentence Summarization using the Information Bottleneck Principle (#3219)",
236 |         "Improving Latent Alignment in Text Summarization by Generalizing the Pointer Generator (#3043)"
237 |     ],
238 |     "Information Retrieval and Document Analysis": [
239 |         "Cross-Cultural Transfer Learning for Text Classification (#1036)",
240 |         "Combining Unsupervised Pre-training and Annotator Rationales to Improve Low-shot Text Classification (#1190)",
241 |         "Projection Sequence Networks for On-Device Text Classification (#3202)",
242 |         "Induction Networks for Few-Shot Text Classification (#3562)",
243 |         "Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach (#2899)",
244 |         "Human-grounded Evaluations of Explanation Methods for Text Classification (#425)",
245 |         "A Context-based Framework for Modeling the Role and Function of On-line Resource Citations in Scientific Literature (#793)",
246 |         "Adversarial Reprogramming of Text Classification Neural Networks (#28)",
247 |         "Document Hashing with Mixture-Prior Generative Models (#1676)",
248 |         "Efficient Vector Retrieval under Maximum Inner Product (#3421)"
249 |     ],
250 |     "Reasoning": [
251 |         "Social IQa: Commonsense Reasoning about Social Interactions (#1334)",
252 |         "Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning (#2866)",
253 |         "Posing Fair Generalization Tasks for Natural Language Inference (#1413)",
254 |         "Everything Happens for a Reason: Discovering the Purpose of Actions in Procedural Text (#3279)",
255 |         "CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text (#3183)"
256 |     ],
257 |     "Syntax, Parsing, and Linguistic Theories": [
258 |         "Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers (#3860)",
259 |         "Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing (#1832)",
260 |         "Multilingual Grammar Induction with Continuous Language Identification (#3883)",
261 |         "Quantifying the Semantic Core of Gender Systems (#2637)"
262 |     ],
263 |     "Sentiment and Social Media": [
264 |         "Perturbation Sensitivity Analysis for Detecting Unintended Model Biases (#3447)",
265 |         "Automatically Inferring Gender Associations from Language (#3519)",
266 |         "Reporting the Unreported: Event Extraction for Analyzing the Local Representation of Hate Crimes (#3715)",
267 |         "Minimally Supervised Learning of Affective Events Using Discourse Relations (#3493)"
268 |     ],
269 |     "Phonology, Word Segmentation, and Parsing": [
270 |         "Constraint-based Learning of Phonological Processes (#451)",
271 |         "Detect Camouflaged Spam Content via StoneSkipping: Graph and Text Joint Embedding for Chinese Character Variation Representation (#1340)",
272 |         "A Generative Model for Punctuation in Dependency Trees (#TACL-1582)"
273 |     ]
274 | }


--------------------------------------------------------------------------------
/data/poster_demo_paper_by_topic.json:
--------------------------------------------------------------------------------
  1 | {
  2 |     "Information Extraction, Information Retrieval and Document Analysis, Linguistic Theories": [
  3 |         "Leveraging Dependency Forest for Neural Medical Relation Extraction (#249)",
  4 |         "Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised Data (#569)",
  5 |         "Improving Relation Extraction with Knowledge-attention (#710)",
  6 |         "Jointly Learning Entity and Relation Representations for Entity Alignment (#782)",
  7 |         "Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph Completion (#796)",
  8 |         "Low-Resource Name Tagging Learned with Weakly Labeled Data (#821)",
  9 |         "Learning Dynamic Context Augmentation for Global Entity Linking (#841)",
 10 |         "Open Event Extraction from Online Texts using a Generative Adversarial Network (#859)",
 11 |         "Learning to Bootstrap for Entity Set Expansion (#1001)",
 12 |         "Multi-input Multi-output Sequence Labeling for Joint Extraction of Fact and Condition Tuples from Scientific Text (#1149)",
 13 |         "Cross-lingual Structure Transfer for Relation and Event Extraction (#1210)",
 14 |         "Uncover the Ground-Truth Relations in Distant Supervision: A Neural Expectation Maximization Framework (#1365)",
 15 |         "Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction (#1736)",
 16 |         "Event Detection with Trigger-Aware Lattice Neural Network (#1816)",
 17 |         "A Boundary-aware Neural Model for Nested Named Entity Recognition (#1874)",
 18 |         "Learning the Extraction Order of Multiple Relational Facts in a Sentence with Reinforcement Learning (#2024)",
 19 |         "CaRe: Open Knowledge Graph Embeddings (#2439)",
 20 |         "Self-Attention Enhanced CNNs and Collaborative Curriculum Learning for Distantly Supervised Relation Extraction (#2793)",
 21 |         "Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping (#3014)",
 22 |         "Leveraging 2-hop Distant Supervision from Table Entity Pairs for Relation Extraction (#3059)",
 23 |         "EntEval: A Holistic Evaluation Benchmark for Entity Representations (#3317)",
 24 |         "Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction (#3646)",
 25 |         "Hierarchical Text Classification with Reinforced Label Assignment (#32)",
 26 |         "Investigating Capsule Network and Semantic Feature on Hyperplanes for Text Classification (#314)",
 27 |         "Label-Specific Document Representation for Multi-Label Text Classification (#721)",
 28 |         "Hierarchical Attention Prototypical Networks for Few-Shot Text Classification (#729)",
 29 |         "Many Faces of Feature Importance: Comparing Built-in and Post-hoc Feature Importance in Text Classification (#2087)",
 30 |         "Enhancing Local Feature Extraction with Global Representation for Neural Text Classification (#2273)",
 31 |         "Latent-Variable Generative Text Classifiers for Data-Efficient NLP (#3004)",
 32 |         "PaRe: A Paper-Reviewer Matching Approach Using a Common Topic Space (#3239)",
 33 |         "Linking artificial and human neural representations of language (#2750)"
 34 |     ],
 35 |     "Machine Translation and Mulitilinguality, Phonology, Morphology and Word Segmentation, Tagging, Chunking, Syntax and Parsing": [
 36 |         "Explicit Cross-lingual Pre-training for Unsupervised Machine Translation (#233)",
 37 |         "Latent Part-of-Speech Sequences for Neural Machine Translation (#410)",
 38 |         "Improving Back-Translation with Uncertainty-based Confidence Estimation (#798)",
 39 |         "Towards Linear Time Neural Machine Translation with Capsule Networks (#846)",
 40 |         "Modeling Multi-mapping relations for Precise Cross-lingual Entity Alignment (#985)",
 41 |         "Supervised and Nonlinear Alignment of Two Embedding Spaces for Dictionary Induction in Low Resourced Languages (#1226)",
 42 |         "Beto, Bentz, Becas: The Surprising Cross-Lingual Effectiveness of BERT (#1414)",
 43 |         "Iterative Dual Domain Adaptation for Neural Machine Translation (#1427)",
 44 |         "Multi-agent Learning for Neural Machine Translation (#1484)",
 45 |         "Pivot-based Transfer Learning for Neural Machine Translation between non-English Languages (#1869)",
 46 |         "Context-Aware Monolingual Repair for Neural Machine Translation (#1967)",
 47 |         "Multi-Granularity Self-Attention for Neural Machine Translation (#2330)",
 48 |         "The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives (#2415)",
 49 |         "Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention (#2537)",
 50 |         "A Discriminative Neural Model for Cross-Lingual Word Alignment (#2961)",
 51 |         "One Model to Learn Both: Zero Pronoun Prediction and Translation (#3571)",
 52 |         "Dynamic Past and Future for Neural Machine Translation (#3601)",
 53 |         "Revisit Automatic Error Detection for Wrong and Missing Translation ‐ A Supervised Approach (#3770)",
 54 |         "Towards Understanding Neural Machine Translation with Word Importance (#3857)",
 55 |         "Multilingual Neural Machine Translation with Language Clustering (#4056)",
 56 |         "Don't Forget the Long Tail! A Comprehensive Analysis of Morphological Generalization in Bilingual Lexicon Induction (#1065)",
 57 |         "A Functionalist Account of Vowel System Typology (#1268)",
 58 |         "Pushing the Limits of Low-Resource Morphological Inflection (#2230)",
 59 |         "Morphological Analysis Using a Sequence Decoder (#TACL-1654)",
 60 |         "Cross-Lingual Dependency Parsing Using Code-Mixed TreeBank (#205)",
 61 |         "Hierarchical Pointer Net Parsing (#531)",
 62 |         "Semi-Supervised Semantic Role Labeling with Cross-View Training (#719)",
 63 |         "Low-Resource Sequence Labeling via Unsupervised Multilingual Contextualized Representations (#809)",
 64 |         "A Lexicon-Based Graph Neural Network for Chinese NER (#863)",
 65 |         "CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding (#1556)",
 66 |         "Tree Transformer: Integrating Tree Structures into Self-Attention (#1794)",
 67 |         "Semantic Role Labeling with Iterative Structure Refinement (#2179)",
 68 |         "Entity Projection via Machine-Translation for Cross-Lingual NER (#2724)",
 69 |         "A Bayesian Approach for Sequence Tagging with Crowds (#2738)",
 70 |         "A systematic comparison of methods for low-resource dependency parsing on genuinely low-resource languages (#3091)",
 71 |         "Target Language-Aware Constrained Inference for Cross-lingual Dependency Parsing (#3368)",
 72 |         "Look-up and Adapt: A One-shot Semantic Parser (#3711)",
 73 |         "Similarity Based Auxiliary Classifier for Named Entity Recognition (#3886)",
 74 |         "Variable beam search for generative neural parsing and its relevance for neuro-imaging signal analysis (#4015)"
 75 |     ],
 76 |     "Dialog and Interactive Systems, Machine Translation and Multilinuality, Phonology, Morphology, and Word Segmentation, Speech, Vision, Robotics, Multimodal and Grounding, Tagging, Chunking, Syntax and Parsing": [
 77 |         "Multi-task Learning for Natural Language Generation in Task-Oriented Dialogue (#242)",
 78 |         "Dirichlet Latent Variable Hierarchical Recurrent Encoder-Decoder in Dialogue Generation (#622)",
 79 |         "Semi-Supervised Bootstrapping of Dialogue State Trackers for Task-Oriented Modelling (#1011)",
 80 |         "A Progressive Model to Enable Continual Learning for Semantic Slot Filling (#1289)",
 81 |         "CASA-NLU: Context-Aware Self-Attentive Natural Language Understanding for Task-Oriented Chatbots (#1447)",
 82 |         "Sampling Matters! An Empirical Study of Negative Sampling Strategies for Learning of Matching Models in Retrieval-based Dialogue Systems (#2050)",
 83 |         "Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variables (#2329)",
 84 |         "Modeling Multi-Action Policy for Task-Oriented Dialogues (#2650)",
 85 |         "An Evaluation for Intent Classification and Out-of-Scope Prediction (#3471)",
 86 |         "Automatically Learning Data Augmentation Policies for Dialogue Tasks (#3528)",
 87 |         "uniblock: Scoring and Filtering Corpus with Unicode Block Information (#351)",
 88 |         "Multilingual word translation using auxiliary languages (#533)",
 89 |         "Towards Better Modeling Hierarchical Structure for Self-Attention with Ordered Neurons (#801)",
 90 |         "Improved Sentence Alignment in Linear Time and Space (#1284)",
 91 |         "Simpler and Faster Learning of Adaptive Policies for Simultaneous Translation (#1603)",
 92 |         "Adversarial Learning with Contextual Embeddings for Zero-resource Cross-lingual Classification and NER (#1889)",
 93 |         "Recurrent Embedding for Neural Machine Translation (#2114)",
 94 |         "Machine Translation for Machines: the Sentiment Classification Use Case (#2413)",
 95 |         "Investigating the Effectiveness of BPE: The Power of Shorter Sequences (#2552)",
 96 |         "HABLex: Human Annotated Bilingual Lexicons for Experiments in Machine Translation (#3022)",
 97 |         "Handling Syntactic Divergence in Low-resource Machine Translation (#3336)",
 98 |         "Speculative Beam Search for Simultaneous Translation (#3487)",
 99 |         "Self-Attention with Structural Position Representations (#3548)",
100 |         "Low-Resource Neural Machine Translation by Exploiting Multilingualism through Multi-Step Fine-Tuning Using N-way Parallel Corpora (#3590)",
101 |         "Unsupervised Domain Adaptation for Neural Machine Translation with Domain-Aware Feature Embeddings (#3716)",
102 |         "A Regularization-based Framework for Bilingual Grammar Induction (#4061)",
103 |         "Encoders Help You Disambiguate Word Senses in Neural Machine Translation (#4083)",
104 |         "Korean Morphological Analysis with Tied Sequence-to-Sequence Multi-Task Model (#2376)",
105 |         "Convolutional Neural Networks for Diacritic Restoration (#3733)",
106 |         "Improving Visual Dialog by Learning to Answer Diverse Questions (#459)",
107 |         "Cross-lingual Transfer Learning with Data Selection for Large-Scale Spoken Language Understanding (#790)",
108 |         "Multi-Head Attention with Diversity for Learning Grounded Multilingual Multimodal Representations (#2786)",
109 |         "Decoupled Box Proposal and Featurization with Ultrafine-Grained Semantic Labels Improve Image Captioning and Visual Question Answering (#3263)",
110 |         "REO-Relevance, Extraness, Omission: A Fine-grained Evaluation for Image Captioning (#3293)",
111 |         "WSLLN: Weakly Supervised Natural Language Localization Networks (#3398)",
112 |         "Grounding learning of modifier dynamics: An application to colour naming. (#3748)",
113 |         "Efficient Navigation with Language Pre-training and Stochastic Sampling (#3830)",
114 |         "Towards Making a Dependency Parser See (#413)",
115 |         "Unsupervised Labeled Parsing with Deep Inside-Outside Recursive Autoencoders (#1234)",
116 |         "Dependency Parsing for Spoken Dialog Systems (#3171)",
117 |         "Span-based Hierarchical Semantic Parsing for Task-Oriented Dialog (#3240)"
118 |     ],
119 |     "Dialog and Interactive Systems, Speech, Vision, Robotics, Multimodal and Grounding": [
120 |         "Data-Efficient Goal-Oriented Conversation with Dialogue Knowledge Transfer Networks (#9)",
121 |         "Multi-Granularity Representations of Dialog (#64)",
122 |         "Are You for Real? Detecting Identity Fraud via Dialogue Interactions (#111)",
123 |         "Hierarchy Response Learning for Neural Conversation Generation (#124)",
124 |         "Knowledge Aware Conversation Generation with Explainable Reasoning on Augmented Graphs (#138)",
125 |         "Adaptive Parameterization for Neural Dialogue Generation (#298)",
126 |         "Towards Knowledge-Based Recommender Dialog System (#316)",
127 |         "Structuring latent spaces for stylized response generation (#419)",
128 |         "Improving Open-Domain Dialogue Systems via Multi-Turn Incomplete Utterance Restoration (#537)",
129 |         "Unsupervised Context Rewriting for Open Domain Conversation (#771)",
130 |         "Dually Interactive Matching Network for Personalized Response Selection in Retrieval-Based Chatbots (#866)",
131 |         "DyKgChat: Benchmarking Dialogue Generation Grounding on Dynamic Knowledge Graphs (#1432)",
132 |         "Retrieval-guided Dialogue Response Generation via a Matching-to-Generation Framework (#1550)",
133 |         "Scalable and Accurate Dialogue State Tracking via Hierarchical Sequence Generation (#1842)",
134 |         "Low-Resource Response Generation with Template Prior (#1931)",
135 |         "A Discrete CVAE for Response Generation on Short-Text Conversation (#2039)",
136 |         "Who Is Speaking to Whom? Learning to Identify Utterance Addressee in Multi-Party Conversations (#2495)",
137 |         "A Semi-Supervised Stable Variational Network for Promoting Replier-Consistency in Dialogue Generation (#2594)",
138 |         "Modeling Personalization in Continuous Space for Response Generation via Augmented Wasserstein Autoencoders (#2685)",
139 |         "Variational Hierarchical User-based Conversation Model (#3513)",
140 |         "Recommendation as a Communication Game: Self-Supervised Role-Playing for Goal-oriented Dialogue (#3727)",
141 |         "CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases (#3881)",
142 |         "A Practical Dialogue-Act-Driven Conversation Model for Multi-Turn Response Selection (#3954)",
143 |         "How to Build User Simulators to Train RL-based Dialog Systems (#4003)",
144 |         "Graph Convolutional Network with Sequential Attention for Goal-Oriented Dialogue Systems (#TACL-1676)",
145 |         "Low-Rank HOCA: Efficient High-Order Cross-Modal Attention for Video Captioning (#294)",
146 |         "Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach (#370)",
147 |         "Dual Attention Networks for Visual Reference Resolution in Visual Dialog (#401)",
148 |         "Unsupervised Discovery of Multimodal Links in Multi-image, Multi-sentence Documents (#942)",
149 |         "UR-FUNNY: A Multimodal Language Dataset for Understanding Humor (#996)",
150 |         "Partners in Crime: Multi-view Sequential Inference for Movie Understanding (#1923)",
151 |         "Guiding the Flowing of Semantics: Interpretable Video Captioning via POS Tag (#2097)",
152 |         "A Stack-Propagation Framework with Token-Level Intent Detection for Spoken Language Understanding (#2414)",
153 |         "Talk2Car: Taking Control Of Your Self Driving Car (#2718)",
154 |         "Fact-Checking Meets Fauxtography: Verifying Claims About Images (#2739)",
155 |         "Video Dialog via Progressive Inference and Cross-Transformer (#2766)",
156 |         "Executing Instructions in Situated Collaborative Interactions (#2884)",
157 |         "Fusion of Detected Objects in Text for Visual Question Answering (#3099)",
158 |         "TIGEr: Text-to-Image Grounding for Image Caption Evaluation (#3260)"
159 |     ],
160 |     "Question Answering, Textual Inference and Other Areas of Semantics": [
161 |         "Tree-structured Decoding for Solving Math Word Problems (#56)",
162 |         "PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text (#86)",
163 |         "Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning (#107)",
164 |         "Finding Generalizable Evidence by Learning to Convince Q&A Models (#179)",
165 |         "Ranking and Sampling in Open-domain Question Answering (#468)",
166 |         "A Non-commutative Bilinear Model for Answering Path Queries in Knowledge Graphs (#618)",
167 |         "Generating Questions for Knowledge Bases via Incorporating Diversified Contexts and Answer-Aware Loss (#807)",
168 |         "Multi-task Learning for Conversational Question Answering Over a Large-Scale Knowledge Base (#924)",
169 |         "BiPaR: A Bilingual Parallel Dataset for Multilingual and Cross-lingual Reading Comprehension on Novels (#1930)",
170 |         "Language Models as Knowledge Bases? (#2085)",
171 |         "NumNet: Machine Reading Comprehension with Numerical Reasoning (#2237)",
172 |         "Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks (#2277)",
173 |         "Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering (#2390)",
174 |         "Adversarial Domain Adaptation for Machine Reading Comprehension (#2764)",
175 |         "Incorporating External Knowledge into Machine Reading for Generative Question Answering (#2820)",
176 |         "Answering questions by learning to rank - Learning to rank by answering questions (#2825)",
177 |         "Discourse-Aware Semantic Self-Attention for Narrative Reading Comprehension (#2940)",
178 |         "Revealing the Importance of Semantic Retrieval for Machine Reading at Scale (#2945)",
179 |         "PubMedQA: A Dataset for Biomedical Research Question Answering (#2978)",
180 |         "Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering (#3164)",
181 |         "Answering Complex Open-domain Questions Through Iterative Query Generation (#3417)",
182 |         "NL2pSQL: Generating Pseudo-SQL Queries from Under-specified Natural Language Questions (#3489)",
183 |         "Leveraging Frequent Query Substructures to Generate Formal Queries for Complex Question Answering (#4004)",
184 |         "Incorporating Graph Attention Mechanism into Knowledge Graph Reasoning Based on Deep Reinforcement Learning (#147)",
185 |         "Learning to Update Knowledge Graph by Reading News (#493)",
186 |         "DIVINE: A Generative Adversarial Imitation Learning Framework for Knowledge Graph Reasoning (#709)",
187 |         "Original Semantics-Oriented Attention and Deep Fusion Network for Sentence Matching (#829)",
188 |         "Representation Learning with Ordered Relation Paths for Knowledge Graph Completion (#972)",
189 |         "Collaborative Policy Learning for Open Knowledge Graph Reasoning (#1018)",
190 |         "Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder (#1444)",
191 |         "Asynchronous Deep Interaction Network for Natural Language Inference (#2257)",
192 |         "Keep Calm and Switch On! Preserving Sentiment and Fluency in Semantic Text Exchange (#2830)",
193 |         "Query-focused Scenario Construction (#3550)",
194 |         "Semi-supervised Entity Alignment via Joint Knowledge Embedding Model and Cross-graph Model (#3819)"
195 |     ],
196 |     "Discourse and Pragmatics, Summarization and Generation": [
197 |         "Evaluating Pronominal Anaphora in Machine Translation: An Evaluation Measure and a Test Suite (#723)",
198 |         "A Regularization Approach for Incorporating Event Knowledge and Coreference Relations into Neural Discourse Parsing (#2916)",
199 |         "Weakly Supervised Multilingual Causality Extraction fromWikipedia (#3994)",
200 |         "Attribute-aware Sequence Network for Review Summarization (#210)",
201 |         "Extractive Summarization of Long Documents by Combining Global and Local Context (#268)",
202 |         "Enhancing Neural Data-To-Text Generation Models with External Background Knowledge (#313)",
203 |         "Reading Like HER: Human Reading Inspired Extractive Summarization (#346)",
204 |         "Contrastive Attention Mechanism for Abstractive Sentence Summarization (#361)",
205 |         "NCLS: Neural Cross-Lingual Summarization (#703)",
206 |         "Clickbait? Sensational Headline Generation with Auto-tuned Reinforcement Learning (#749)",
207 |         "Concept Pointer Network for Abstractive Summarization (#845)",
208 |         "Surface Realisation Using Full Delexicalisation (#1139)",
209 |         "Unsupervised Text Attribute Transfer via Iterative Matching and Translation (#1169)",
210 |         "Better Rewards Yield Better Summaries: Learning to Summarise Without References (#1191)",
211 |         "Mixture Content Selection for Diverse Sequence Generation (#1369)",
212 |         "An End-to-End Generative Architecture for Paraphrase Generation (#1375)",
213 |         "Table-to-Text Generation with Effective Hierarchical Encoder on Three dimensions (Row, Column and Time) (#1726)",
214 |         "Subtopic-Driven Multi-Document Summarization (#1779)",
215 |         "Referring Expression Generation Using Entity Profiles (#1805)",
216 |         "Exploring Diverse Expressions for Paraphrase Generation (#1834)",
217 |         "Enhancing AMR-to-Text Generation with Dual Graph Representations (#1852)",
218 |         "Keeping Consistency of Sentence Generation and Document Classification with Multi-Task Learning (#1881)",
219 |         "Toward a task of feedback comment generation for writing learning (#2031)",
220 |         "Improving Question Generation With to the Point Context (#2033)",
221 |         "Deep Copycat Networks for Text-to-Text Generation (#2121)",
222 |         "Towards Controllable and Personalized Review Generation (#2412)",
223 |         "Answers Unite! Unsupervised Metrics for Reinforced Summarization Models (#2604)",
224 |         "Long and Diverse Text Generation with Planning-based Hierarchical Variational Model (#2746)",
225 |         "\u201cTransforming\u201d Delete, Retrieve, Generate Approach for Controlled Text Style Transfer (#2932)",
226 |         "An Entity-Driven Framework for Abstractive Summarization (#3275)",
227 |         "Neural Extractive Text Summarization with Syntactic Compression (#3334)",
228 |         "Domain Adaptive Text Style Transfer (#3511)",
229 |         "Let's Ask Again: Refine Network for Automatic Question Generation (#3754)",
230 |         "Earlier Isn't Always Better: Submodular Analysis on Corpus and System Biases in Summarization (#3846)"
231 |     ],
232 |     "Information Retrieval and Document Analysis, Lexical Semantics, Sentence-level Semantics, Machine Learning": [
233 |         "A Label Informative Wide & Deep Classifier for Scientific Publications (#542)",
234 |         "Text Level Graph Neural Network for Text Classification (#573)",
235 |         "Semantic Relatedness based Re-ranker for Text Spotting (#875)",
236 |         "Delta-training: Simple Semi-Supervised Text Classification using Pretrained Word Embeddings (#1306)",
237 |         "Visual Detection with Context for Document Layout Analysis (#1342)",
238 |         "Evaluating Topic Quality with Posterior Variability (#1562)",
239 |         "Neural Topic Model with Reinforcement Learning (#2494)",
240 |         "Modelling Stopping Criteria using Poisson Processes (#2705)",
241 |         "Cross-Domain Modeling of Sentence-Level Evidence for Document Retrieval (#3533)",
242 |         "The Challenges of Optimizing Machine Translation for Low Resource Cross-Language Information Retrieval (#4151)",
243 |         "Rotate King to get Queen: Word Relationships as Orthogonal Transformations in Embedding Space (#170)",
244 |         "GlossBERT: BERT for Word Sense Disambiguation with Gloss Knowledge (#362)",
245 |         "Leveraging Adjective-Noun Phrasing Knowledge for Comparison Relation Prediction in Text-to-SQL (#670)",
246 |         "Bridging the Defined and the Defining: Exploiting Implicit Lexical Semantic Relations in Definition Modeling (#1461)",
247 |         "Don't Just Scratch the Surface: Enhancing Word Representations for Korean with Hanja (#1615)",
248 |         "Challenging Supervised Word Sense Disambiguation with Lexical-Semantic Combinations (#2219)",
249 |         "Hierarchical Meta-Embeddings for Code-switching Named Entity Recognition (#2419)",
250 |         "Context-Aware Conversation Thread Detection in Group Chat (#162)",
251 |         "Fine-tune BERT with Sparse Self-Attention Mechanism (#327)",
252 |         "Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels (#806)",
253 |         "A Multi-Pairwise Extension of Procrustes Analysis for Multilingual Word Translation (#819)",
254 |         "Out-of-Domain Detection for Low-Resource Text Classification Tasks (#1063)",
255 |         "An Empirical Study of Harnessing Pre-Trained Neural Networks with Rules for Formality Style Transfer (#1877)",
256 |         "Multiple Text Style Transfer by using Word-level Conditional Generative Adversarial Network with Two-Phase Training (#1925)",
257 |         "Improved Differentiable Architecture Search for Language Model and Named Entity Recognition (#2104)",
258 |         "Using Pairwise Occurrence Information to Improve Knowledge Graph Completion on Large-Scale Datasets (#2696)",
259 |         "Single Training Dimension Selection for Word Embedding with PCA (#2741)",
260 |         "A Surprisingly Effective Fix for Deep Latent Variable Modeling of Text (#3040)",
261 |         "SciBERT: A Pretrained Language Model for Scientific Text (#3115)",
262 |         "Humor Detection: A Transformer Gets the Last Laugh (#3265)",
263 |         "Combining Global Sparse Gradients with Local Gradients in Distributed Neural Network Training (#3585)",
264 |         "Small and Practical BERT models for Sequence Labeling (#3631)",
265 |         "Data Augmentation with Atomic Templates for Spoken Language Understanding (#3776)",
266 |         "PaLM: A Hybrid Parser and Language Model (#4026)",
267 |         "A Pilot Study for Chinese SQL Semantic Parsing (#1593)",
268 |         "Global Reasoning over Database Structures for Text-to-SQL Parsing (#1616)",
269 |         "Transductive Learning of Neural Language Models for Syntactic and Semantic Analysis (#1712)",
270 |         "Efficient Sentence Embedding using Discrete Cosine Transform (#2287)",
271 |         "A Search-based Neural Model for Biomedical Nested and Overlapping Event Detection (#2393)",
272 |         "PAWS-X: A Cross-lingual Adversarial Dataset for Paraphrase Identification (#3233)",
273 |         "Pretrained Language Models for Sequential Sentence Classification (#3887)",
274 |         "Emergent Linguistic Phenomena in Multi-Agent Communication Games (#2402)"
275 |     ],
276 |     "Machine Learning": [
277 |         "A Logic-Driven Framework for Consistency of Neural Models (#6)",
278 |         "Style Transfer for Texts: to Err is Human, but Error Margins Matter (#109)",
279 |         "Implicit Deep Latent Variable Models for Text Generation (#161)",
280 |         "Text Emotion Distribution Learning from Small Sample: A Meta-Learning Approach (#200)",
281 |         "Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation (#247)",
282 |         "Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks (#373)",
283 |         "Learning Only from Relevant Keywords and Unlabeled Documents (#399)",
284 |         "Denoising-based Sequence-to-Sequence Pre-training for Text Generation (#592)",
285 |         "Dialog Intent Induction with Deep Multi-View Clustering (#686)",
286 |         "Nearly-Unsupervised Hashcode Representations for Biomedical Relation Extraction (#718)",
287 |         "Auditing Deep Learning processes through Kernel-based Explanatory Models (#888)",
288 |         "Enhancing Recurrent Variational Autoencoders with Mutual Information Estimation for Text Generation (#1060)",
289 |         "Sampling Bias in Deep Active Classification: An Empirical Study (#1286)",
290 |         "Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases (#1321)",
291 |         "Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation (#1360)",
292 |         "Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control (#1422)",
293 |         "Experimenting with Power Divergences for Language Modeling (#1435)",
294 |         "Hierarchically-Refined Label Attention Network for Sequence Labeling (#1590)",
295 |         "Certified Robustness to Adversarial Word Substitutions (#1709)",
296 |         "Visualizing and Understanding the Effectiveness of BERT (#1846)",
297 |         "Topics to Avoid: Demoting Latent Confounds in Text Classification (#2147)",
298 |         "Learning to Ask for Conversational Machine Learning (#2168)",
299 |         "Language Modeling for Code-Switching: Evaluation, Integration of Monolingual Data, and Discriminative Training (#2270)",
300 |         "Using Local Knowledge Graph Construction to Scale Seq2Seq Models to Multi-Document Inputs (#2394)",
301 |         "Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation (#2441)",
302 |         "Exploiting Monolingual Data at Scale for Neural Machine Translation (#2477)",
303 |         "Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs (#2554)",
304 |         "Distributionally Robust Language Modeling (#2660)",
305 |         "Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling (#2686)",
306 |         "Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds (#2706)",
307 |         "Parallel Iterative Edit Models for Local Sequence Transduction (#2716)",
308 |         "ARAML: A Stable Adversarial Training Framework for Text Generation (#2882)",
309 |         "FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow (#2905)",
310 |         "Compositional Generalization for Premitive Substitutions (#3039)",
311 |         "WikiCREM: A large unsupervised corpus for co-reference resolution (#3089)",
312 |         "Identifying and Explaining Discriminative Attributes (#3146)",
313 |         "Patient Knowledge Distillation for BERT Model Compression (#3194)",
314 |         "Neural Gaussian Copula for Variational Autoencoder (#3254)",
315 |         "Empirical Study of Transformer's Attention Mechanism via the Lens of Kernel (#3261)",
316 |         "Learning to Learn and Predict: A Meta-Learning Approach for Multi-Label Classification (#3478)",
317 |         "Revealing the Dark Secrets of BERT (#3494)",
318 |         "Machine Translation With Weakly Paired Documents (#4149)",
319 |         "Countering Language Drift via Grounding (#2201)"
320 |     ],
321 |     "Social Media and Computational Social Science, Text Mining and NLP Applications": [
322 |         "Integrating Text and Image: Determining Multimodal Document Intent in Instagram Posts (#52)",
323 |         "Neural Conversation Recommendation with Online Interaction Modeling (#705)",
324 |         "Different Acquisition from the Same Sharing: Sifting Multi-task Learning for Fake News Detection (#720)",
325 |         "Text-based inference of moral sentiment change (#965)",
326 |         "Detecting Causal Language Use in Science Findings (#1439)",
327 |         "Multilingual and Multi-aspect Hate Speech Analysis (#1468)",
328 |         "MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims (#1969)",
329 |         "A Deep Neural Information Fusion Architecture for Textual Network Embeddings (#2006)",
330 |         "You Shall Know a User by the Company It Keeps: Dynamic Representations for Social Media Users in NLP (#2186)",
331 |         "Unsupervised Domain Adaptation for Political Document Analysis (#2606)",
332 |         "Macrocosm: Social Media Persona Linking for OSINT Applications (#2659)",
333 |         "A Hierarchical Location Prediction Neural Network for Twitter User Geolocation (#2693)",
334 |         "Trouble on the Horizon: Forecasting the Derailment of Online Conversations as they Develop (#2828)",
335 |         "A Benchmark Dataset for Learning to Intervene in Online Hate Speech (#3391)",
336 |         "Detecting and Reducing Bias in a High Stakes Domain (#3461)",
337 |         "CodeSwitch-Reddit: Exploration of Written Multilingual Discourse in Online Discussion Forums (#3566)",
338 |         "Modeling Conversation Structure and Temporal Dynamics for Jointly Predicting Rumor Stance and Veracity (#3592)",
339 |         "Measuring Online Debaters' Persuasive Skill from Text over Time (#TACL-1639)",
340 |         "Reconstructing Capsule Networks for Zero-shot Intent Classification (#142)",
341 |         "Domain Adaptation for Person-Job Fit with Transferable Deep Global Match Network (#239)",
342 |         "Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification (#299)",
343 |         "Comparing and Developing Tools to Measure the Readability of Domain-Specific Texts (#438)",
344 |         "News2vec: News Network Embedding with Subnode Information (#473)",
345 |         "Recursive Context-Aware Lexical Simplification (#732)",
346 |         "Transfer Learning from Medical Literature for Section Prediction in Electronic Health Records (#1103)",
347 |         "Neural News Recommendation with Heterogeneous User Behavior (#1459)",
348 |         "Reviews Meet Graphs: Enhancing User and Item Representations for Recommendation with Hierarchical Attentive Graph Neural Network (#1470)",
349 |         "Event Representation Learning Enhanced with External Commonsense Knowledge (#1551)",
350 |         "Learning to Discriminate Perturbations for Blocking Adversarial Attacks in Text Classification (#1572)",
351 |         "A Neural Citation Count Prediction Model based on Peer Review Text (#1661)",
352 |         "Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs (#2044)",
353 |         "Semi-supervised Text Style Transfer: Cross Projection in Latent Space (#2052)",
354 |         "Question Answering for Privacy Policies: Combining Computational and Legal Perspectives (#2129)",
355 |         "Stick to the Facts: Learning towards a Fidelity-oriented E-Commerce Product Description Generation (#2381)",
356 |         "Fine-Grained Entity Typing via Hierarchical Multi Graph Convolutional Networks (#2389)",
357 |         "Learning to Infer Entities, Properties and their Relations from Clinical Conversations (#2942)",
358 |         "Practical Correlated Topic Modeling via the Rectified Anchor Word Algorithm (#3072)",
359 |         "Modeling the Relationship between User Comments and Edits in Document Revision (#3128)",
360 |         "PRADO: Projection Attention Networks for Document Classification On-Device (#3218)",
361 |         "Subword Language Model for Query Auto-Completion (#3873)",
362 |         "Enhancing Dialogue Symptom Diagnosis with Global Attention and Symptom Graph (#4069)"
363 |     ],
364 |     "Sentiment Analysis and Argument Mining, Lexical Semantics, Sentence-level Semantics": [
365 |         "Multi-Relational Word Embeddings for Selectional Preferences (#623)",
366 |         "MulCode: A Multiplicative Multi-way Model for Compressing Neural Language Model (#700)",
367 |         "It's All in the Name: Mitigating Gender Bias with Name-Based Counterfactual Data Augmentation (#1220)",
368 |         "Examining Gender Bias in Languages with Grammatical Gender (#1741)",
369 |         "Weakly Supervised Cross-lingual Semantic Relation Classification via Knowledge Distillation (#3071)",
370 |         "Improved Word Sense Disambiguation Using Pre-Trained Contextualized Word Representations (#3702)",
371 |         "Do Neural NLP Models Know Numbers? Probing Numeracy in Embeddings (#3972)",
372 |         "A Split-and-Recombine Approach for Follow-up Query Analysis (#552)",
373 |         "Text2Math: End-to-end Parsing Text into Math Expressions (#1086)",
374 |         "Editing-based SQL Query Generation for Cross-Domain Context-Dependent Questions (#1287)",
375 |         "Syntax-aware Multilingual Semantic Role Labeling (#1351)",
376 |         "Cloze-driven Pretraining of Self-attention Networks (#1446)",
377 |         "Bridging the Gap between Relevance Matching and Semantic Matching for Short Text Similarity Modeling (#1558)",
378 |         "A Syntax-aware Multi-task Learning Framework for Chinese Semantic Role Labeling (#1836)",
379 |         "Injecting Phrasal Paraphrase Relation into Sentence Representation for Semantic Equivalence Assessment (#2060)",
380 |         "Data-Anonymous Encoding for Text-to-SQL Generation (#2231)",
381 |         "Capturing Argument Interaction in Semantic Role Labeling with Capsule Networks (#2993)",
382 |         "Learning Programmatic Idioms for Scalable Semantic Parsing (#3121)",
383 |         "Jupyter: A Large Scale Distantly Supervised Dataset for Open Domain Context Based Code Generation (#3451)",
384 |         "Model-based Interactive Semantic Parsing: A Unified Formulation and A Text-to-SQL Case Study (#3527)",
385 |         "Modeling Graph Structure in Transformer for Better AMR-to-Text Generation (#3835)",
386 |         "Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks (#72)",
387 |         "Learning Explicit and Implicit Structures for Targeted Sentiment Analysis (#281)",
388 |         "Capsule Network with Interactive Attention for Aspect-Level Sentiment Classification (#317)",
389 |         "Emotion Detection with Neural Personal Discrimination (#402)",
390 |         "Specificity-Driven Cascading Approach for Unsupervised Sentiment Modification (#475)",
391 |         "Lexical-Based Adversarial Reinforcement Training for Robust Sentiment Classification (#891)",
392 |         "Leveraging Structural and Semantic Correspondence for Attribute-Oriented Aspect Sentiment Discovery (#896)",
393 |         "From the Token to the Review: A Hierarchical Multimodal approach to Opinion Mining (#936)",
394 |         "Shallow Domain Adaptive Embeddings for Sentiment Analysis (#1477)",
395 |         "Domain-Invariant Feature Distillation for Cross-Domain Sentiment Classification (#1691)",
396 |         "A Novel Aspect-Guided Deep Transition Model for Aspect Based Sentiment Analysis (#1705)",
397 |         "Human-Like Decision Making: Document-level Aspect Sentiment Classification via Hierarchical Reinforcement Learning (#1713)",
398 |         "A Dataset of General-Purpose Rebuttal (#1840)",
399 |         "Rethinking Attribute Representation and Injection for Sentiment Classification (#1992)",
400 |         "A Knowledge Regularized Hierarchical Approach for Emotion Cause Analysis (#2236)",
401 |         "Automatic Argument Quality Assessment - New Datasets and Methods (#2447)",
402 |         "Fine-Grained Analysis of Propaganda in News Articles (#2493)",
403 |         "Context-aware Interactive Attention for Multi-modal Sentiment and Emotion Analysis (#2707)",
404 |         "Sequential Learning of Convolutional Features for Effective Text Classification (#3182)",
405 |         "The Role of Pragmatic and Discourse Context in Determining Argument Impact (#3909)",
406 |         "Aspect-Level Sentiment Analysis Via Convolution over Dependency Tree (#4182)"
407 |     ],
408 |     "Discourse and Pragmatics, Linguistic Theories, Textual Inference, Question Answering, Summarization and Generation": [
409 |         "Next Sentence Prediction helps Implicit Discourse Relation Classification within and across Domains (#982)",
410 |         "Split or Merge: Which is Better for Unsupervised RST Parsing? (#1701)",
411 |         "BERT for Coreference Resolution: Baselines and Analysis (#3731)",
412 |         "Linguistic Versus Latent Relations for Modeling a Flow in Paragraphs (#3815)",
413 |         "Event Causality Recognition Exploiting Multiple Annotators' Judgments and Background Knowledge (#4125)",
414 |         "What Part of the Neural Network Does This? Understanding LSTMs by Measuring and Dissecting Memory Cells (#1181)",
415 |         "Quantity doesn't buy quality syntax with neural language models (#1227)",
416 |         "Higher-order Comparisons of Sentence Encoder Representations (#2000)",
417 |         "Text Genre and Training Data Size in Human-Like Parsing (#2379)",
418 |         "Feature2Vec: Distributional semantic modelling of human property knowledge (#2535)",
419 |         "Has Pepperoni and Still Vegan?! Improving Answer Consistency in VQA through Entailed Question Generation (#424)",
420 |         "GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level (#961)",
421 |         "Revisiting the Evaluation of Theory of Mind through Question Answering (#1069)",
422 |         "Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering (#1319)",
423 |         "A Span-Extraction Dataset for Chinese Machine Reading Comprehension (#2131)",
424 |         "CLAR: Contextualized and Lexicalized Aspect Representation for Non-factoid Question Answering (#2177)",
425 |         "Machine Reading Comprehension Using Structural Knowledge Graph-aware Network (#2229)",
426 |         "Answering Conversational Questions on Structured Data without Logical Forms (#2851)",
427 |         "Improving Answer Selection and Answer Triggering using Hard Negatives (#2859)",
428 |         "Can You Unpack That? Learning to Rewrite Questions-in-Context (#3163)",
429 |         "Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning (#3203)",
430 |         "Zero-shot Reading Comprehension by Cross-lingual Transfer Learning with Multi-lingual Language Representation Model (#3303)",
431 |         "QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions (#3355)",
432 |         "Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension (#3470)",
433 |         "A Gated Self-attention Memory Network for Answer Selection (#4067)",
434 |         "Polly Want a Cracker: Analyzing Performance of Parroting on Paraphrase Generation Datasets (#91)",
435 |         "Query-focused Sentence Compression in Linear Time (#482)",
436 |         "Generating Personalized Recipes from Historical User Preferences (#1255)",
437 |         "Generating Highly Relevant Questions (#1644)",
438 |         "Improving Neural Story Generation by Targeted Common Sense Grounding (#1674)",
439 |         "Abstract Text Summarization: A Low Resource Challenge (#1963)",
440 |         "Generating Modern Poetry Automatically in Finnish (#2083)",
441 |         "SUM-QE: a BERT-based Summary Quality Estimation Model (#2422)",
442 |         "An Empirical Comparison on Imitation Learning and Reinforcement Learning for Paraphrase Generation (#2870)",
443 |         "Countering the effects of lead bias in news summarization via multi-stage training and auxiliary losses (#3236)",
444 |         "Learning Rhyming Constraints using Structured Adversaries (#3950)",
445 |         "Question-type Driven Question Generation (#4105)",
446 |         "Deep Reinforcement Learning with Distributional Semantic Rewards for Abstractive Summarization (#4107)",
447 |         "Clause-Wise and Recursive Decoding for Complex and Cross-Domain Text-to-SQL Generation (#285)",
448 |         "Do Nuclear Submarines Have Nuclear Captains? A Challenge Dataset for Commonsense Reasoning over Adjectives and Objects (#1774)",
449 |         "Aggregating Bidirectional Encoder Representations Using MatchLSTM for Sequence Matching (#2244)",
450 |         "What Does This Word Mean? Explaining Contextualized Embeddings with Natural Language Definition (#2765)",
451 |         "Pre-Training BERT on Domain Resources for Short Answer Grading (#3058)",
452 |         "WIQA: A dataset for \u201cWhat if...\u201d reasoning over procedural text (#3276)",
453 |         "Evaluating BERT for natural language inference: a case study on the CommitmentBank (#3606)",
454 |         "Incorporating Domain Knowledge into Medical NLI using Knowledge Graphs (#3974)"
455 |     ],
456 |     "Information Extraction, Text Mining and NLP Applications, Social Media and Computational Social Science, Sentiment Analysis and Argument Mining": [
457 |         "An Attentive Fine-Grained Entity Typing Model with Latent Type Representation (#189)",
458 |         "An Improved Neural Baseline for Temporal Relation Extraction (#193)",
459 |         "Improving Fine-grained Entity Typing with Entity Linking (#822)",
460 |         "Combining Spans into Entities: A Neural Two-Stage Approach for Recognizing Discontiguous Entities (#1222)",
461 |         "Cross-Sentence N-ary Relation Extraction using Lower-Arity Universal Schemas (#1686)",
462 |         "GEANN: Gazetteer-Enhanced Attentive Neural Networks for Named Entity Recognition (#1760)",
463 |         "\u201cA Buster Keaton of Linguistics\u201d: First Automated Approaches for the Extraction of Vossian Antonomasia (#1782)",
464 |         "Multi-Task Learning for Chemical Named Entity Recognition with Chemical Compound Paraphrase (#1799)",
465 |         "FewRel 2.0: Towards More Challenging Few-Shot Relation Classification (#2697)",
466 |         "ner and pos when nothing is capitalized (#2992)",
467 |         "CaRB: A Crowdsourced Benchmark for Open IE (#4099)",
468 |         "Weakly Supervised Attention Networks for Entity Extraction (#4158)",
469 |         "Revealing and Predicting Online Persuasion Strategy with Elementary Units (#19)",
470 |         "A Challenge Dataset and Effective Models for Aspect-Based Sentiment Analysis (#849)",
471 |         "Learning with Noisy Labels for Sentence-level Sentiment Classification (#1157)",
472 |         "DENS: A Dataset for Multi-class Emotion Analysis (#1347)",
473 |         "Multi-Task Stance Detection with Sentiment and Stance Lexicons (#3016)",
474 |         "A Robust Self-Learning Framework for Cross-Lingual Text Classification (#3085)",
475 |         "Learning to Flip the Sentiment of Reviews from Non-Parallel Corpora (#3869)",
476 |         "Label Embedding using Hierarchical Structure of Labels for Twitter Classification (#80)",
477 |         "Interpretable Word Embeddings via Informative Priors (#393)",
478 |         "TalkDown: A Corpus for Condescension Detection in Context (#1526)",
479 |         "Adversarial Removal of Demographic Attributes Revisited (#2101)",
480 |         "A deep-learning framework to detect sarcasm targets (#2170)",
481 |         "In Plain Sight: Media Bias through the Lens of Factual Reporting (#2759)",
482 |         "Incorporating Label Dependencies in Multilabel Stance Detection (#3333)",
483 |         "Investigating Sports Commentator Bias within a Large Corpus of American Football Broadcasts (#3345)",
484 |         "Charge-Based Prison Term Prediction with Deep Gating Network (#759)",
485 |         "Restoring ancient text using deep learning: a case study on Greek epigraphy (#1020)",
486 |         "Embedding Lexical Features via Tensor Decomposition for Small Sample Humor Recognition (#1068)",
487 |         "EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks (#1192)",
488 |         "Neural News Recommendation with Multi-Head Self-Attention (#1581)",
489 |         "What Matters for Neural Cross-Lingual Named Entity Recognition: An Empirical Analysis (#1611)",
490 |         "Telling the Whole Story: A Manually Annotated Chinese Dataset for the Analysis of Humor in Jokes (#1737)",
491 |         "Generating Natural Anagrams: Towards Language Generation under Hard Combinatorial Constraints (#1763)",
492 |         "STANCY: Stance Classification Based on Consistency Cues (#2013)",
493 |         "Cross-lingual intent classification in a low resource industrial setting (#2551)",
494 |         "SoftRegex: Generating Regex from Natural Language Description using Softened Regex Equivalence (#2839)",
495 |         "Using Clinical Notes with Multimodal Learning for ICU Management. (#2907)",
496 |         "Spelling-Aware Construction of Mixed-Language Texts for Teaching Foreign-Language Vocabulary (#3639)",
497 |         "Towards Machine Reading for Interventions from Humanitarian-Assistance Program Literature (#3718)",
498 |         "RUN through the Streets: Dataset and Models for Realistic Urban Navigation (#4014)"
499 |     ]
500 | }


--------------------------------------------------------------------------------
/figure/rate.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/roomylee/EMNLP-2019-Papers/6b4adcd3f3c6fa96b802fe6ce3144a6e4454910c/figure/rate.png


--------------------------------------------------------------------------------
/figure/stat.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/roomylee/EMNLP-2019-Papers/6b4adcd3f3c6fa96b802fe6ce3144a6e4454910c/figure/stat.png


--------------------------------------------------------------------------------
/figure/wordcloud.png:
--------------------------------------------------------------------------------
https://raw.githubusercontent.com/roomylee/EMNLP-2019-Papers/6b4adcd3f3c6fa96b802fe6ce3144a6e4454910c/figure/wordcloud.png


--------------------------------------------------------------------------------
/generate_accepted_paper.ipynb:
--------------------------------------------------------------------------------
  1 | {
  2 |  "cells": [
  3 |   {
  4 |    "cell_type": "code",
  5 |    "execution_count": 1,
  6 |    "metadata": {},
  7 |    "outputs": [],
  8 |    "source": [
  9 |     "import json\n",
 10 |     "\n",
 11 |     "\n",
 12 |     "with open('data/oral_paper_by_topic.json') as json_file:\n",
 13 |     "    oral_papers = json.load(json_file)\n",
 14 |     "with open('data/poster_demo_paper_by_topic.json') as json_file:\n",
 15 |     "    poster_demo_papers = json.load(json_file)"
 16 |    ]
 17 |   },
 18 |   {
 19 |    "cell_type": "code",
 20 |    "execution_count": 2,
 21 |    "metadata": {},
 22 |    "outputs": [
 23 |     {
 24 |      "data": {
 25 |       "text/plain": [
 26 |        "{'Machine Learning': ['Attending to Future Tokens for Bidirectional Sequence Generation (#1443)',\n",
 27 |        "  'Attention is Not Not Explanation (#526)',\n",
 28 |        "  'Practical Obstacles to Deploying Active Learning (#1176)',\n",
 29 |        "  'Transfer Learning Between Related Tasks Using Expected Label Proportions (#1207)',\n",
 30 |        "  'Insertion-based Decoding with automatically Inferred Generation Order (#TACL-1732)',\n",
 31 |        "  'Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets (#1092)',\n",
 32 |        "  'Robust Text Classifier on Test-Time Budgets (#1128)',\n",
 33 |        "  'Commonsense Knowledge Mining from Pretrained Models (#3289)',\n",
 34 |        "  'RNN Architecture Learning with Sparse Regularization (#3428)',\n",
 35 |        "  'Universal Trigger Sequences for Attacking and Analyzing NLP (#1515)',\n",
 36 |        "  'To Annotate or Not? Unsupervised Prediction of Performance Drop due to Domain Shift (#2756)',\n",
 37 |        "  'Adaptively Sparse Transformers (#2900)',\n",
 38 |        "  'Show Your Work: Improved Reporting of Experimental Results (#3277)',\n",
 39 |        "  'A Deep Factorization of Style and Structure in Fonts (#3999)'],\n",
 40 |        " 'Lexical Semantics': ['Knowledge Enhanced Contextual Word Representations (#3403)',\n",
 41 |        "  'How Contextual are Contextualized Word Representations? (#208)',\n",
 42 |        "  'Room to Glo: A Systematic Comparison of Semantic Change Detection Approaches with Word Embeddings (#783)',\n",
 43 |        "  'On Correlations between Word Vector Sets (#3976)',\n",
 44 |        "  'Game Theory Meets Embeddings: a Unified Framework for Word Sense Disambiguation (#1724)',\n",
 45 |        "  'Cross-lingual Semantic Specialization via Lexical Relation Induction (#1735)',\n",
 46 |        "  'Modelling the interplay of metaphor and emotion through multitask learning (#2670)',\n",
 47 |        "  'How well do NLI models capture verb veridicality? (#3460)',\n",
 48 |        "  'Modeling Color Terminology Across Thousands of Languages (#3515)',\n",
 49 |        "  'Negative Focus Detection via Contextual Attention Mechanisms (#1314)',\n",
 50 |        "  'Exploring Human Gender Stereotypes with Word Association Test (#1912)',\n",
 51 |        "  'Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition (#TACL-1729)',\n",
 52 |        "  \"Where''s My Head? Definition, Dataset and Models for Numeric Fused-Heads Identification and Resolution (#TACL-1648)\"],\n",
 53 |        " 'Dialog and Interactive Systems': ['Guided Dialog Policy Learning: Reward Estimation for Multi-Domain Task-Oriented Dialog (#166)',\n",
 54 |        "  'Multi-hop Selector Network for Multi-turn Response Selection in Retrieval-based Chatbots (#554)',\n",
 55 |        "  'MoEL: Mixture of Empathetic Listeners (#1053)',\n",
 56 |        "  'Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever (#2430)',\n",
 57 |        "  'Building Task-Oriented Visual Dialog Systems Through Alternative Optimization Between Dialog Policy and Language Generation (#3756)',\n",
 58 |        "  'TaskMaster Dialog Corpus: Toward a Realistic and Diverse Dataset (#510)',\n",
 59 |        "  'MultiDoGO: Multi-Domain Goal-Oriented Dialogues (#1564)',\n",
 60 |        "  'Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack (#1186)',\n",
 61 |        "  'GECOR: An End-to-End Generative Ellipsis and Co-reference Resolution Model for Task-Oriented Dialogue (#1853)',\n",
 62 |        "  'Task-Oriented Conversation Generation Using Heterogeneous Memory Networks (#496)'],\n",
 63 |        " 'Sentiment Analysis and Argument Mining': ['DialogueGCN: A Graph-based Network for Emotion Recognition in Conversation (#2092)',\n",
 64 |        "  'Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations (#1814)',\n",
 65 |        "  'Interpretable Relevant Emotion Ranking with Event-Driven Attention (#3544)',\n",
 66 |        "  'Justifying Recommendations using Distantly-Labeled Reviews and Fined-Grained Aspects (#518)',\n",
 67 |        "  'Using Customer Service Dialogues for Satisfaction Analysis with Context-Assisted Multiple Instance Learning (#204)',\n",
 68 |        "  'What Gets Echoed? Understanding the “Pointers” in Explanations of Persuasive Arguments (#2089)',\n",
 69 |        "  'Modeling Frames in Argumentation (#2267)',\n",
 70 |        "  'AMPERSAND: Argument Mining for PERSuAsive oNline Discussions (#3321)',\n",
 71 |        "  'Evaluating adversarial attacks against multiple fact verification systems (#427)',\n",
 72 |        "  'Nonsense!: Quality Control via Two-Step Reason Selection for Annotating Local Acceptability and Related Attributes in News Editorials (#564)',\n",
 73 |        "  'On the Importance of Delexicalization for Fact Verification (#2984)',\n",
 74 |        "  'Towards Debiasing Fact Verification Models (#3338)',\n",
 75 |        "  'Recognizing Conflict Opinions in Aspect-level Sentiment Classification with Dual Attention Networks (#911)',\n",
 76 |        "  'Investigating Dynamic Routing in Tree-Structured LSTM for Sentiment Analysis (#1395)',\n",
 77 |        "  'Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks (#381)',\n",
 78 |        "  'Coupling Global and Local Context for Unsupervised Aspect Extraction (#1988)',\n",
 79 |        "  'Transferable End-to-End Aspect-based Sentiment Analysis with Selective Adversarial Learning (#65)',\n",
 80 |        "  'CAN: Constrained Attention Networks for Multi-Aspect Sentiment Analysis (#1995)',\n",
 81 |        "  'Leveraging Just a Few Keywords for Fine-Grained Aspect Detection Through Weakly Supervised Co-Training (#3207)'],\n",
 82 |        " 'Summarization and Generation': ['Neural Text Summarization: A Critical Evaluation (#3687)',\n",
 83 |        "  'Neural data-to-text generation: A comparison between pipeline and end-to-end architectures (#2586)',\n",
 84 |        "  'MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance (#1175)',\n",
 85 |        "  'Select and Attend: Towards Controllable Content Selection in Text Generation (#3049)',\n",
 86 |        "  'Sentence-Level Content Planning and Style Specification for Neural Text Generation (#3357)'],\n",
 87 |        " 'Sentence-level Semantics': ['Translate and Label! An Encoder-Decoder Approach for Cross-lingual Semantic Role Labeling (#2740)',\n",
 88 |        "  'Syntax-Enhanced Self-Attention-Based Semantic Role Labeling (#2106)',\n",
 89 |        "  'VerbAtlas: a Novel Large-Scale Verbal Semantic Resource and Its Application to Semantic Role Labeling (#2213)',\n",
 90 |        "  'Parameter-free Sentence Embedding via Orthogonal Basis (#1099)',\n",
 91 |        "  'Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations (#3807)',\n",
 92 |        "  'Learning Semantic Parsers from Denotations with Latent Structured Alignments and Abstract Programs (#2676)',\n",
 93 |        "  'Broad-Coverage Semantic Parsing as Transduction (#263)',\n",
 94 |        "  'Core Semantic First: A Top-down Approach for AMR Parsing (#1544)',\n",
 95 |        "  \"Don't paraphrase, detect! Rapid and Effective Data Collection for Semantic Parsing (#2904)\",\n",
 96 |        "  'Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond (#TACL-1742)'],\n",
 97 |        " 'Speech, Vision, Robotics, Multimodal and Grounding': ['Extracting Possessions from Social Media: Images Complement Language (#3013)',\n",
 98 |        "  'Learning to Speak and Act in a Fantasy Text Adventure Game (#1243)',\n",
 99 |        "  'Help, Anna! Vision-based Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learning (#1542)',\n",
100 |        "  'Incorporating Visual Semantics into Sentence Representations within a Grounded Space (#2247)',\n",
101 |        "  'Neural Naturalist: Generating Fine-Grained Image Comparisons (#3024)',\n",
102 |        "  'LXMERT: Learning Cross-Modality Encoder Representations from Transformers (#3048)',\n",
103 |        "  'Phrase Grounding by Soft-Label Chain Conditional Random Field (#3765)',\n",
104 |        "  'What You See is What You Get: Visual Pronoun Coreference Resolution in Conversations (#549)',\n",
105 |        "  'YouMakeup: A Large-Scale Domain-Specific Multimodal Dataset for Fine-Grained Semantic Comprehension (#122)',\n",
106 |        "  'DEBUG: A Dense Bottom-Up Grounding Approach for Natural Language Video Localization (#167)'],\n",
107 |        " 'Information Extraction': ['Fine-Grained Evaluation for Entity Linking (#116)',\n",
108 |        "  'Supervising Unsupervised Open Information Extraction Models (#3069)',\n",
109 |        "  'Neural Cross-Lingual Event Detection with Minimal Parallel Resources (#1723)',\n",
110 |        "  'KnowledgeNet: A Benchmark Dataset for Knowledge Base Population (#1258)',\n",
111 |        "  'Effective Use of Transformer Networks for Entity Tracking (#3308)',\n",
112 |        "  'Improving Distantly-Supervised Relation Extraction with Joint Label Embedding (#337)',\n",
113 |        "  'Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network (#566)',\n",
114 |        "  'Looking Beyond Label Noise: Shifted Label Distribution Matters in Distantly Supervised Relation Extraction (#1057)',\n",
115 |        "  'Easy First Relation Extraction with Information Redundancy (#1640)',\n",
116 |        "  'Dependency-Guided LSTM-CRF for Named Entity Recognition (#2509)',\n",
117 |        "  'CrossWeigh: Training Named Entity Tagger from Imperfect Annotations (#2712)',\n",
118 |        "  'A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers (#3259)',\n",
119 |        "  'Open Domain Web Keyphrase Extraction Beyond Language Modeling (#1119)',\n",
120 |        "  'TuckER: Tensor Factorization for Knowledge Graph Completion (#990)',\n",
121 |        "  'Weakly Supervised Domain Detection (#TACL-1712)',\n",
122 |        "  'Event Detection with Multi-Order Graph Convolution and Aggregated Attention (#835)',\n",
123 |        "  'Coverage of Information Extraction from Sentences and Paragraphs (#1285)',\n",
124 |        "  'HMEAE: Hierarchical Modular Event Argument Extraction (#2354)',\n",
125 |        "  'Entity, Relation, and Event Extraction with Contextualized Span Representations (#3930)'],\n",
126 |        " 'Semantics': ['Analytical Methods for Interpretable Ultradense Word Embeddings (#75)',\n",
127 |        "  'Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks (#3142)',\n",
128 |        "  'Retrofitting Contextualized Word Embeddings with Paraphrases (#3045)',\n",
129 |        "  'Incorporating Contextual and Syntactic Structures Improves Semantic Similarity Modeling (#3508)'],\n",
130 |        " 'Discourse, Summarization, and Generation': ['Neural Linguistic Steganography (#3399)',\n",
131 |        "  'The Feasibility of Embedding Based Automatic Evaluation for Single Document Summarization (#3018)',\n",
132 |        "  'Attention Optimization for Abstractive Document Summarization (#1918)',\n",
133 |        "  'Rewarding Coreference Resolvers for Being Consistent with World Knowledge (#2020)'],\n",
134 |        " 'Text Mining and NLP Applications': ['An Empirical Study of Incorporating Pseudo Data into Grammatical Error Correction (#740)',\n",
135 |        "  'A Multilingual Topic Model for Learning Weighted Topic Links Across Incomparable Corpora (#1257)',\n",
136 |        "  'Measure Country-Level Socio-Economic Indicators with Streaming News: An Empirical Study (#3730)',\n",
137 |        "  'Towards Extracting Medical Family History from Natural Language Interactions: A New Dataset and Baselines (#2903)',\n",
138 |        "  '(Male, Bachelor) and (Female, Ph.D) have different connotations: Parallelly Annotated Stylistic Language Dataset with Multiple Personas (#3793)',\n",
139 |        "  'Movie Plot Analysis via Turning Point Identification (#244)',\n",
140 |        "  'Latent Suicide Risk Detection on Microblog via Suicide-Oriented Word Embeddings and Layered Attention (#2488)',\n",
141 |        "  'Deep Ordinal Regression for Pledge Specificity Prediction (#1903)',\n",
142 |        "  'Enabling Robust Grammatical Error Correction in New Domains: Datasets, Metrics, and Analyses (#TACL-1677)',\n",
143 |        "  'The Myth of Blind Review Revisited: Experiments on ACL vs. EMNLP (#2233)',\n",
144 |        "  'Uncover Sexual Harassment Patterns from Personal Stories by Joint Key Element Extraction and Categorization (#2653)',\n",
145 |        "  'Identifying Predictive Causal Factors from News Streams (#2864)',\n",
146 |        "  'Training Data Augmentation for Detecting Adverse Drug Reactions in User-Generated Content (#3011)',\n",
147 |        "  'Deep Reinforcement Learning-based Text Anonymization against Private-Attribute Inference (#3160)'],\n",
148 |        " 'Neural Machine Translation': ['Enhancing Context Modeling with a Query-Guided Capsule Network for Document-level NMT (#2416)',\n",
149 |        "  'Simple, Scalable Adaptation for Neural Machine Translation (#3252)',\n",
150 |        "  'Controlling Text Complexity in Neural Machine Translation (#3177)',\n",
151 |        "  'Investigating Multilingual NMT Representations at Scale (#1388)',\n",
152 |        "  'Hierarchical Modeling of Global Context for Document-Level Neural Machine Translation (#1423)'],\n",
153 |        " 'Question Answering': ['Cross-Lingual Machine Reading Comprehension (#8)',\n",
154 |        "  'A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning (#582)',\n",
155 |        "  'Neural Duplicate Question Detection without Labeled Training Data (#880)',\n",
156 |        "  'Asking Clarification Questions in Knowledge-Based Question Answering (#889)',\n",
157 |        "  'Multi-View Domain Adapted Sentence Embeddings for Low-Resource Unsupervised Duplicate Question Detection (#1646)',\n",
158 |        "  'Interactive Language Learning by Question Answering (#1367)',\n",
159 |        "  \"What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering (#3238)\",\n",
160 |        "  'KagNet: Learning to Answer Commonsense Questions with Knowledge-Aware Graph Networks (#436)',\n",
161 |        "  'Learning with Limited Data for Multilingual Reading Comprehension (#3518)',\n",
162 |        "  'A Discrete Hard EM Approach for Weakly Supervised Question Answering (#3778)'],\n",
163 |        " 'Social Media and Computational Social Science': ['Multi-label Categorization of Accounts of Sexism using a Neural Framework (#172)',\n",
164 |        "  \"The Trumpiest Trump? Identifying a Subject's Most Characteristic Tweets (#1462)\",\n",
165 |        "  'Finding Microaggressions in the Wild: A Case for Locating Elusive Phenomena in Social Media Posts (#2950)',\n",
166 |        "  'Reinforced Product Metadata Selection for Helpfulness Assessment of Customer Reviews (#694)',\n",
167 |        "  'Learning Invariant Representations of Social Media Users (#3557)'],\n",
168 |        " 'Discourse and Pragmatics': ['A Unified Neural Coherence Model (#1792)',\n",
169 |        "  'Topic-Guided Coherence Modeling for Sentence Ordering by Preserving Global and Local Information (#2642)',\n",
170 |        "  'Neural Generative Rhetorical Structure Parsing (#4060)',\n",
171 |        "  'Weak Supervision for Learning Discourse Structure (#2453)',\n",
172 |        "  'Predicting Discourse Structure using Distant Supervision from Sentiment (#2625)'],\n",
173 |        " 'Tagging, Chunking, Syntax and Parsing': ['Designing and Interpreting Probes with Control Tasks (#4063)',\n",
174 |        "  'Specializing Word Embeddings (for Parsing) by Information Bottleneck (#1357)',\n",
175 |        "  'Deep Contextualized Word Embeddings in Transition-Based and Graph-Based Dependency Parsing - A Tale of Two Parsers Revisited (#2799)',\n",
176 |        "  'Semantic graph parsing with recurrent neural network DAG grammars (#2863)',\n",
177 |        "  '75 Languages, 1 Model: Parsing Universal Dependencies Universally (#1221)'],\n",
178 |        " 'Linguistic Theories, Cognitive Modeling and Psycholinguistics': ['Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts (#2585)',\n",
179 |        "  \"Investigating BERT's Knowledge of Language: Five Analysis Methods with NPIs (#3650)\",\n",
180 |        "  'Representation of Constituents in Neural Language Models: - Coordination Phrase as a Case Study (#3929)',\n",
181 |        "  'Towards Zero-shot Language Modelling (#1745)',\n",
182 |        "  'Neural Network Acceptability Judgments (#TACL-1710)'],\n",
183 |        " 'Machine Translation and Multilinguality': ['Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary Induction (#1131)',\n",
184 |        "  'Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set (#1266)',\n",
185 |        "  'Synchronously Generating Two Languages with Interactive Decoding (#1478)',\n",
186 |        "  'On NMT Search Errors and Model Errors: Cat Got Your Tongue? (#1868)',\n",
187 |        "  'Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? (#2459)',\n",
188 |        "  'Weakly-Supervised Concept-based Adversarial Learning for Cross-lingual Word Embeddings (#2491)',\n",
189 |        "  'Aligning Cross-lingual Entities with Multi-Aspect Information (#3541)',\n",
190 |        "  'Contrastive Language Adaptation for Cross-Lingual Stance Detection (#2498)',\n",
191 |        "  'Jointly Learning to Align and Translate with Transformer Models (#422)',\n",
192 |        "  'Understanding Data Augmentation in Neural Machine Translation: Two Perspectives towards Generalization (#2192)',\n",
193 |        "  'Simple and Effective Noisy Channel Modeling for Neural Machine Translation (#2869)',\n",
194 |        "  'MultiFiT: Efficient Multi-lingual Language Model Fine-tuning (#745)',\n",
195 |        "  'Hint-based Training for Non-AutoRegressive Machine Translation (#1064)',\n",
196 |        "  'Two New Evaluation Datasets for Low-Resource Machine Translation: Nepali-English and Sinhala English (#3349)',\n",
197 |        "  'Constant-Time Machine Translation with Conditional Masked Language Models (#1204)',\n",
198 |        "  'Learning to Copy for Automatic Post-Editing (#777)'],\n",
199 |        " 'Reasoning and Question Answering': ['Going on a vacation takes longer than “Going for a walk”: A Study of Temporal Commonsense Understanding (#2533)',\n",
200 |        "  'QAInfomax: Learning Robust Question Answering System by Mutual Information Maximization (#2798)',\n",
201 |        "  'Adapting Meta Knowledge Graph Information for Multi-Hop Reasoning over Few-Shot Relations (#329)',\n",
202 |        "  'How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG (#586)'],\n",
203 |        " 'Generation': ['Pun-GAN: Generative Adversarial Network for Pun Generation (#267)',\n",
204 |        "  'Multi-Task Learning with Language Modeling for Question Generation (#3820)',\n",
205 |        "  'Autoregressive Text Generation beyond Feedback Loops (#3506)',\n",
206 |        "  'The Woman Worked as a Babysitter: On Biases in Language Generation (#3874)',\n",
207 |        "  'Counterfactual Story Reasoning and Generation (#3328)',\n",
208 |        "  'Encode, Tag, Realize: High-Precision Text Editing (#2395)',\n",
209 |        "  'Answer-guided and Semantic Coherent Question Generation in Open-domain Conversation (#128)',\n",
210 |        "  'Read, Attend and Comment: A Deep Architecture for Automatic News Comment Generation (#1947)',\n",
211 |        "  'A Topic Augmented Text Generation Model: Joint Learning of Semantics and Structural Features (#2822)',\n",
212 |        "  'A Modular Architecture for Unsupervised Sarcasm Generation (#2725)',\n",
213 |        "  'Interpoetry: Generating Classical Chinese Poems from Vernacular Chinese (#2534)',\n",
214 |        "  'Set to Ordered Text: Generating Discharge Instructions from Medical Billing Codes (#724)'],\n",
215 |        " 'Summarization': ['Summary Cloze: A New Task for Content Selection in Topic-Focused Summarization (#1178)',\n",
216 |        "  'Text Summarization with Pretrained Encoders (#392)',\n",
217 |        "  'How to Write Summaries with Patterns? Learning towards Abstractive Summarization through Prototype Editing (#609)',\n",
218 |        "  'Unsupervised Sentence Summarization using the Information Bottleneck Principle (#3219)',\n",
219 |        "  'Improving Latent Alignment in Text Summarization by Generalizing the Pointer Generator (#3043)'],\n",
220 |        " 'Information Retrieval and Document Analysis': ['Cross-Cultural Transfer Learning for Text Classification (#1036)',\n",
221 |        "  'Combining Unsupervised Pre-training and Annotator Rationales to Improve Low-shot Text Classification (#1190)',\n",
222 |        "  'Projection Sequence Networks for On-Device Text Classification (#3202)',\n",
223 |        "  'Induction Networks for Few-Shot Text Classification (#3562)',\n",
224 |        "  'Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach (#2899)',\n",
225 |        "  'Human-grounded Evaluations of Explanation Methods for Text Classification (#425)',\n",
226 |        "  'A Context-based Framework for Modeling the Role and Function of On-line Resource Citations in Scientific Literature (#793)',\n",
227 |        "  'Adversarial Reprogramming of Text Classification Neural Networks (#28)',\n",
228 |        "  'Document Hashing with Mixture-Prior Generative Models (#1676)',\n",
229 |        "  'Efficient Vector Retrieval under Maximum Inner Product (#3421)'],\n",
230 |        " 'Reasoning': ['Social IQa: Commonsense Reasoning about Social Interactions (#1334)',\n",
231 |        "  'Self-Assembling Modular Networks for Interpretable Multi-Hop Reasoning (#2866)',\n",
232 |        "  'Posing Fair Generalization Tasks for Natural Language Inference (#1413)',\n",
233 |        "  'Everything Happens for a Reason: Discovering the Purpose of Actions in Procedural Text (#3279)',\n",
234 |        "  'CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text (#3183)'],\n",
235 |        " 'Syntax, Parsing, and Linguistic Theories': ['Working Hard or Hardly Working: Challenges of Integrating Typology into Neural Dependency Parsers (#3860)',\n",
236 |        "  'Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing (#1832)',\n",
237 |        "  'Multilingual Grammar Induction with Continuous Language Identification (#3883)',\n",
238 |        "  'Quantifying the Semantic Core of Gender Systems (#2637)'],\n",
239 |        " 'Sentiment and Social Media': ['Perturbation Sensitivity Analysis for Detecting Unintended Model Biases (#3447)',\n",
240 |        "  'Automatically Inferring Gender Associations from Language (#3519)',\n",
241 |        "  'Reporting the Unreported: Event Extraction for Analyzing the Local Representation of Hate Crimes (#3715)',\n",
242 |        "  'Minimally Supervised Learning of Affective Events Using Discourse Relations (#3493)'],\n",
243 |        " 'Phonology, Word Segmentation, and Parsing': ['Constraint-based Learning of Phonological Processes (#451)',\n",
244 |        "  'Detect Camouflaged Spam Content via StoneSkipping: Graph and Text Joint Embedding for Chinese Character Variation Representation (#1340)',\n",
245 |        "  'A Generative Model for Punctuation in Dependency Trees (#TACL-1582)']}"
246 |       ]
247 |      },
248 |      "execution_count": 2,
249 |      "metadata": {},
250 |      "output_type": "execute_result"
251 |     }
252 |    ],
253 |    "source": [
254 |     "oral_papers"
255 |    ]
256 |   },
257 |   {
258 |    "cell_type": "code",
259 |    "execution_count": 3,
260 |    "metadata": {},
261 |    "outputs": [],
262 |    "source": [
263 |     "from googlesearch import search\n",
264 |     "import urllib\n",
265 |     "from bs4 import BeautifulSoup\n",
266 |     "from difflib import SequenceMatcher\n",
267 |     "from tqdm import tqdm\n",
268 |     "\n",
269 |     "\n",
270 |     "def similar(a, b):\n",
271 |     "    return SequenceMatcher(None, a, b).ratio()\n",
272 |     "\n",
273 |     "\n",
274 |     "def search_arxiv_link(title):\n",
275 |     "    link = None\n",
276 |     "    for j in search(title, tld=\"co.in\", num=10, stop=1, pause=0.5):\n",
277 |     "        if 'arxiv.org/abs' in j:\n",
278 |     "            thepage = urllib.request.urlopen(j)\n",
279 |     "            soup = BeautifulSoup(thepage, \"html.parser\")\n",
280 |     "            searched_title = ' '.join(soup.title.text.lower().split()[1:])\n",
281 |     "            if similar(title, searched_title) > 0.8:\n",
282 |     "                link = j\n",
283 |     "                break\n",
284 |     "            else:\n",
285 |     "                print(\"ERROR\")\n",
286 |     "                print(title)\n",
287 |     "                print(searched_title)\n",
288 |     "    return link"
289 |    ]
290 |   },
291 |   {
292 |    "cell_type": "code",
293 |    "execution_count": 4,
294 |    "metadata": {
295 |     "scrolled": false
296 |    },
297 |    "outputs": [
298 |     {
299 |      "name": "stderr",
300 |      "output_type": "stream",
301 |      "text": [
302 |       "  4%|▍         | 1/26 [00:57<24:05, 57.82s/it]"
303 |      ]
304 |     },
305 |     {
306 |      "name": "stdout",
307 |      "output_type": "stream",
308 |      "text": [
309 |       "ERROR\n",
310 |       "how contextual are contextualized word representations?\n",
311 |       "how contextual are contextualized word representations? comparing the geometry of bert, elmo, and gpt-2 embeddings\n",
312 |       "ERROR\n",
313 |       "game theory meets embeddings: a unified framework for word sense disambiguation\n",
314 |       "a game-theoretic approach to word sense disambiguation\n"
315 |      ]
316 |     },
317 |     {
318 |      "name": "stderr",
319 |      "output_type": "stream",
320 |      "text": [
321 |       "\r",
322 |       "  8%|▊         | 2/26 [01:49<22:25, 56.06s/it]"
323 |      ]
324 |     },
325 |     {
326 |      "name": "stdout",
327 |      "output_type": "stream",
328 |      "text": [
329 |       "ERROR\n",
330 |       "multidogo: multi-domain goal-oriented dialogues\n",
331 |       "transferable multi-domain state generator for task-oriented dialogue systems\n"
332 |      ]
333 |     },
334 |     {
335 |      "name": "stderr",
336 |      "output_type": "stream",
337 |      "text": [
338 |       "\r",
339 |       " 12%|█▏        | 3/26 [02:30<19:41, 51.39s/it]"
340 |      ]
341 |     },
342 |     {
343 |      "name": "stdout",
344 |      "output_type": "stream",
345 |      "text": [
346 |       "ERROR\n",
347 |       "evaluating adversarial attacks against multiple fact verification systems\n",
348 |       "adversarial attacks against fact extraction and verification\n"
349 |      ]
350 |     },
351 |     {
352 |      "name": "stderr",
353 |      "output_type": "stream",
354 |      "text": [
355 |       " 23%|██▎       | 6/26 [04:58<15:51, 47.57s/it]"
356 |      ]
357 |     },
358 |     {
359 |      "name": "stdout",
360 |      "output_type": "stream",
361 |      "text": [
362 |       "ERROR\n",
363 |       "youmakeup: a large-scale domain-specific multimodal dataset for fine-grained semantic comprehension\n",
364 |       "large scale fine-grained categorization and domain-specific transfer learning\n"
365 |      ]
366 |     },
367 |     {
368 |      "name": "stderr",
369 |      "output_type": "stream",
370 |      "text": [
371 |       "\r",
372 |       " 27%|██▋       | 7/26 [05:50<15:29, 48.91s/it]"
373 |      ]
374 |     },
375 |     {
376 |      "name": "stdout",
377 |      "output_type": "stream",
378 |      "text": [
379 |       "ERROR\n",
380 |       "fine-grained evaluation for entity linking\n",
381 |       "fine-grained entity typing for domain independent entity linking\n"
382 |      ]
383 |     },
384 |     {
385 |      "name": "stderr",
386 |      "output_type": "stream",
387 |      "text": [
388 |       " 46%|████▌     | 12/26 [09:01<08:21, 35.80s/it]"
389 |      ]
390 |     },
391 |     {
392 |      "name": "stdout",
393 |      "output_type": "stream",
394 |      "text": [
395 |       "ERROR\n",
396 |       "kagnet: learning to answer commonsense questions with knowledge-aware graph networks\n",
397 |       "kagnet: knowledge-aware graph networks for commonsense reasoning\n",
398 |       "ERROR\n",
399 |       "learning with limited data for multilingual reading comprehension\n",
400 |       "multilingual extractive reading comprehension by runtime machine translation\n"
401 |      ]
402 |     },
403 |     {
404 |      "name": "stderr",
405 |      "output_type": "stream",
406 |      "text": [
407 |       " 62%|██████▏   | 16/26 [10:56<04:48, 28.80s/it]"
408 |      ]
409 |     },
410 |     {
411 |      "name": "stdout",
412 |      "output_type": "stream",
413 |      "text": [
414 |       "ERROR\n",
415 |       "towards zero-shot language modelling\n",
416 |       "improving zero-shot translation with language-independent constraints\n"
417 |      ]
418 |     },
419 |     {
420 |      "name": "stderr",
421 |      "output_type": "stream",
422 |      "text": [
423 |       "\r",
424 |       " 65%|██████▌   | 17/26 [11:19<04:04, 27.17s/it]"
425 |      ]
426 |     },
427 |     {
428 |      "name": "stdout",
429 |      "output_type": "stream",
430 |      "text": [
431 |       "ERROR\n",
432 |       "constant-time machine translation with conditional masked language models\n",
433 |       "mask-predict: parallel decoding of conditional masked language models\n"
434 |      ]
435 |     },
436 |     {
437 |      "name": "stderr",
438 |      "output_type": "stream",
439 |      "text": [
440 |       "\r",
441 |       " 69%|██████▉   | 18/26 [12:36<05:37, 42.20s/it]"
442 |      ]
443 |     },
444 |     {
445 |      "name": "stdout",
446 |      "output_type": "stream",
447 |      "text": [
448 |       "ERROR\n",
449 |       "learning to copy for automatic post-editing\n",
450 |       "a simple and effective approach to automatic post-editing with transfer learning\n"
451 |      ]
452 |     },
453 |     {
454 |      "name": "stderr",
455 |      "output_type": "stream",
456 |      "text": [
457 |       "100%|██████████| 26/26 [15:48<00:00, 20.27s/it]\n",
458 |       "  0%|          | 0/12 [00:00<?, ?it/s]"
459 |      ]
460 |     },
461 |     {
462 |      "name": "stdout",
463 |      "output_type": "stream",
464 |      "text": [
465 |       "ERROR\n",
466 |       "self-attention enhanced cnns and collaborative curriculum learning for distantly supervised relation extraction\n",
467 |       "improving distantly supervised relation extraction using word and entity based attention\n",
468 |       "ERROR\n",
469 |       "investigating capsule network and semantic feature on hyperplanes for text classification\n",
470 |       "investigating capsule networks with dynamic routing for text classification\n",
471 |       "ERROR\n",
472 |       "label-specific document representation for multi-label text classification\n",
473 |       "label-aware document representation via hybrid attention for extreme multi-label text classification\n"
474 |      ]
475 |     },
476 |     {
477 |      "name": "stderr",
478 |      "output_type": "stream",
479 |      "text": [
480 |       "\r",
481 |       "  8%|▊         | 1/12 [02:17<25:13, 137.60s/it]"
482 |      ]
483 |     },
484 |     {
485 |      "name": "stdout",
486 |      "output_type": "stream",
487 |      "text": [
488 |       "ERROR\n",
489 |       "iterative dual domain adaptation for neural machine translation\n",
490 |       "domain adaptation of neural machine translation by lexicon induction\n"
491 |      ]
492 |     },
493 |     {
494 |      "name": "stderr",
495 |      "output_type": "stream",
496 |      "text": [
497 |       "\r",
498 |       " 17%|█▋        | 2/12 [05:33<25:50, 155.06s/it]"
499 |      ]
500 |     },
501 |     {
502 |      "name": "stdout",
503 |      "output_type": "stream",
504 |      "text": [
505 |       "ERROR\n",
506 |       "a progressive model to enable continual learning for semantic slot filling\n",
507 |       "bert for joint intent classification and slot filling\n",
508 |       "ERROR\n",
509 |       "sampling matters! an empirical study of negative sampling strategies for learning of matching models in retrieval-based dialogue systems\n",
510 |       "strategy of the negative sampling for training retrieval-based dialogue systems\n",
511 |       "ERROR\n",
512 |       "recurrent embedding for neural machine translation\n",
513 |       "understanding neural machine translation by simplification: the case of encoder-free models\n",
514 |       "ERROR\n",
515 |       "low-resource neural machine translation by exploiting multilingualism through multi-step fine-tuning using n-way parallel corpora\n",
516 |       "exploiting out-of-domain parallel data through multilingual transfer learning for low-resource neural machine translation\n",
517 |       "ERROR\n",
518 |       "improving visual dialog by learning to answer diverse questions\n",
519 |       "improving generative visual dialog by answering diverse questions\n"
520 |      ]
521 |     },
522 |     {
523 |      "name": "stderr",
524 |      "output_type": "stream",
525 |      "text": [
526 |       "\r",
527 |       " 25%|██▌       | 3/12 [08:40<24:41, 164.56s/it]"
528 |      ]
529 |     },
530 |     {
531 |      "name": "stdout",
532 |      "output_type": "stream",
533 |      "text": [
534 |       "ERROR\n",
535 |       "span-based hierarchical semantic parsing for task-oriented dialog\n",
536 |       "semantic parsing for task oriented dialog using hierarchical representations\n",
537 |       "ERROR\n",
538 |       "adaptive parameterization for neural dialogue generation\n",
539 |       "domain adaptive dialog generation via meta learning\n",
540 |       "ERROR\n",
541 |       "modeling personalization in continuous space for response generation via augmented wasserstein autoencoders\n",
542 |       "dialogwae: multimodal response generation with conditional wasserstein auto-encoder\n"
543 |      ]
544 |     },
545 |     {
546 |      "name": "stderr",
547 |      "output_type": "stream",
548 |      "text": [
549 |       " 50%|█████     | 6/12 [16:56<16:15, 162.57s/it]"
550 |      ]
551 |     },
552 |     {
553 |      "name": "stdout",
554 |      "output_type": "stream",
555 |      "text": [
556 |       "ERROR\n",
557 |       "bridging the defined and the defining: exploiting implicit lexical semantic relations in definition modeling\n",
558 |       "definition modeling: learning to define word embeddings in natural language\n",
559 |       "ERROR\n",
560 |       "improved differentiable architecture search for language model and named entity recognition\n",
561 |       "knowledge-augmented language model and its application to unsupervised named-entity recognition\n"
562 |      ]
563 |     },
564 |     {
565 |      "name": "stderr",
566 |      "output_type": "stream",
567 |      "text": [
568 |       "\r",
569 |       " 58%|█████▊    | 7/12 [20:04<14:11, 170.24s/it]"
570 |      ]
571 |     },
572 |     {
573 |      "name": "stdout",
574 |      "output_type": "stream",
575 |      "text": [
576 |       "ERROR\n",
577 |       "empirical study of transformer's attention mechanism via the lens of kernel\n",
578 |       "transformer dissection: an unified understanding for transformer's attention via the lens of kernel\n"
579 |      ]
580 |     },
581 |     {
582 |      "name": "stderr",
583 |      "output_type": "stream",
584 |      "text": [
585 |       "\r",
586 |       " 67%|██████▋   | 8/12 [23:26<11:58, 179.51s/it]"
587 |      ]
588 |     },
589 |     {
590 |      "name": "stdout",
591 |      "output_type": "stream",
592 |      "text": [
593 |       "ERROR\n",
594 |       "neural news recommendation with heterogeneous user behavior\n",
595 |       "neural news recommendation with attentive multi-view learning\n",
596 |       "ERROR\n",
597 |       "a neural citation count prediction model based on peer review text\n",
598 |       "modeling and predicting citation count via recurrent neural network with long short-term memory\n"
599 |      ]
600 |     },
601 |     {
602 |      "name": "stderr",
603 |      "output_type": "stream",
604 |      "text": [
605 |       "\r",
606 |       " 75%|███████▌  | 9/12 [26:02<08:38, 172.69s/it]"
607 |      ]
608 |     },
609 |     {
610 |      "name": "stdout",
611 |      "output_type": "stream",
612 |      "text": [
613 |       "ERROR\n",
614 |       "specificity-driven cascading approach for unsupervised sentiment modification\n",
615 |       "learning sentiment memories for sentiment modification without parallel data\n"
616 |      ]
617 |     },
618 |     {
619 |      "name": "stderr",
620 |      "output_type": "stream",
621 |      "text": [
622 |       "\r",
623 |       " 83%|████████▎ | 10/12 [29:04<05:50, 175.26s/it]"
624 |      ]
625 |     },
626 |     {
627 |      "name": "stdout",
628 |      "output_type": "stream",
629 |      "text": [
630 |       "ERROR\n",
631 |       "revisiting the evaluation of theory of mind through question answering\n",
632 |       "evaluating theory of mind in question answering\n",
633 |       "ERROR\n",
634 |       "clar: contextualized and lexicalized aspect representation for non-factoid question answering\n",
635 |       "answer interaction in non-factoid question answering systems\n"
636 |      ]
637 |     },
638 |     {
639 |      "name": "stderr",
640 |      "output_type": "stream",
641 |      "text": [
642 |       "\r",
643 |       " 92%|█████████▏| 11/12 [32:12<02:59, 179.15s/it]"
644 |      ]
645 |     },
646 |     {
647 |      "name": "stdout",
648 |      "output_type": "stream",
649 |      "text": [
650 |       "ERROR\n",
651 |       "cross-sentence n-ary relation extraction using lower-arity universal schemas\n",
652 |       "cross-sentence n-ary relation extraction with graph lstms\n",
653 |       "ERROR\n",
654 |       "weakly supervised attention networks for entity extraction\n",
655 |       "knowledge-guided pairwise reconstruction network for weakly supervised referring expression grounding\n",
656 |       "ERROR\n",
657 |       "a robust self-learning framework for cross-lingual text classification\n",
658 |       "a robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings\n",
659 |       "ERROR\n",
660 |       "label embedding using hierarchical structure of labels for twitter classification\n",
661 |       "hyperbolic interaction model for hierarchical multi-label classification\n",
662 |       "ERROR\n",
663 |       "neural news recommendation with multi-head self-attention\n",
664 |       "neural news recommendation with attentive multi-view learning\n"
665 |      ]
666 |     },
667 |     {
668 |      "name": "stderr",
669 |      "output_type": "stream",
670 |      "text": [
671 |       "100%|██████████| 12/12 [35:21<00:00, 182.27s/it]\n"
672 |      ]
673 |     }
674 |    ],
675 |    "source": [
676 |     "fo = open('accepted_papers.md', 'w')\n",
677 |     "\n",
678 |     "# Oral papers\n",
679 |     "fo.write('### Oral Session\\n')\n",
680 |     "for t in tqdm(oral_papers.keys()):\n",
681 |     "    fo.write(f'#### {t}\\n')\n",
682 |     "    for p in oral_papers[t]:\n",
683 |     "        link = search_arxiv_link(' '.join(p.lower().split()[:-1]))\n",
684 |     "        if link:\n",
685 |     "            fo.write(f'- {p} [[arXiv]]({link})\\n')\n",
686 |     "        else:\n",
687 |     "            fo.write(f'- {p}\\n')\n",
688 |     "    fo.write('\\n')\n",
689 |     "\n",
690 |     "# Poster & Demo papers\n",
691 |     "fo.write('### Poster & Demo Session\\n')\n",
692 |     "for t in tqdm(poster_demo_papers.keys()):\n",
693 |     "    fo.write(f'#### {t}\\n')\n",
694 |     "    for p in poster_demo_papers[t]:\n",
695 |     "        link = search_arxiv_link(' '.join(p.lower().split()[:-1]))\n",
696 |     "        if link:\n",
697 |     "            fo.write(f'- {p} [[arXiv]]({link})\\n')\n",
698 |     "        else:\n",
699 |     "            fo.write(f'- {p}\\n')\n",
700 |     "    fo.write('\\n')\n",
701 |     "    \n",
702 |     "fo.close()"
703 |    ]
704 |   },
705 |   {
706 |    "cell_type": "code",
707 |    "execution_count": null,
708 |    "metadata": {},
709 |    "outputs": [],
710 |    "source": []
711 |   }
712 |  ],
713 |  "metadata": {
714 |   "kernelspec": {
715 |    "display_name": "Python 3",
716 |    "language": "python",
717 |    "name": "python3"
718 |   },
719 |   "language_info": {
720 |    "codemirror_mode": {
721 |     "name": "ipython",
722 |     "version": 3
723 |    },
724 |    "file_extension": ".py",
725 |    "mimetype": "text/x-python",
726 |    "name": "python",
727 |    "nbconvert_exporter": "python",
728 |    "pygments_lexer": "ipython3",
729 |    "version": "3.6.8"
730 |   }
731 |  },
732 |  "nbformat": 4,
733 |  "nbformat_minor": 2
734 | }
735 | 


--------------------------------------------------------------------------------