---
title: "EMNLP 2016 — all papers: 57 in our library, the most cited first"
description: "57 works of EMNLP 2016 in our library, the most cited first. Among them: SQuAD: 100,000+ Questions for Machine Comprehension of Text…"
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---
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# EMNLP 2016: all papers in our library

57 works · the most cited first · [← EMNLP 2016](https://md.research.elamur.ai/free/en/venues/emnlp/2016/)

1. **[SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://md.research.elamur.ai/free/en/papers/rajpurkar-2016-squad-100-000-questions-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, et al.*2016 · 9,513 citations*
2. **[Attention-based LSTM for Aspect-level Sentiment Classification](https://md.research.elamur.ai/free/en/papers/wang-2016-attention-based-lstm-aspect-level/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yequan Wang, Minlie Huang, Xiaoyan Zhu, et al.*2016 · 2,619 citations*
3. **[How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation](https://md.research.elamur.ai/free/en/papers/liu-2016-how-not-evaluate-your-dialogue/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chia-Wei Liu, Ryan Lowe, Iulian Serban, et al.*2016 · 1,744 citations*
4. **[Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding](https://md.research.elamur.ai/free/en/papers/fukui-2016-multimodal-compact-bilinear-pooling-visual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Akira Fukui, Dong Huk Park, Daylen Yang, et al.*2016 · 1,653 citations*
5. **[A Decomposable Attention Model for Natural Language Inference](https://md.research.elamur.ai/free/en/papers/parikh-2016-decomposable-attention-model-natural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ankur Parikh, Oscar Täckström, Dipanjan Das, et al.*2016 · 1,601 citations*
6. **[Deep Reinforcement Learning for Dialogue Generation](https://md.research.elamur.ai/free/en/papers/li-2016-deep-reinforcement-learning-dialogue-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiwei Li, Will Monroe, Alan Ritter, et al.*2016 · 1,495 citations*
7. **[Sequence-Level Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/kim-2016-sequence-level-knowledge-distillation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yoon Kim, Alexander M. Rush*2016 · 1,445 citations*
8. **[Long Short-Term Memory-Networks for Machine Reading](https://md.research.elamur.ai/free/en/papers/cheng-2016-long-short-term-memory-networks/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jianpeng Cheng, Li Dong, Mirella Lapata*2016 · 1,307 citations*
9. **[Aspect Level Sentiment Classification with Deep Memory Network](https://md.research.elamur.ai/free/en/papers/tang-2016-aspect-level-sentiment-classification-deep/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Duyu Tang, Bing Qin, Ting Liu*2016 · 1,194 citations*
10. **[Rationalizing Neural Predictions](https://md.research.elamur.ai/free/en/papers/lei-2016-rationalizing-neural-predictions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tao Lei, Regina Barzilay, Tommi Jaakkola*2016 · 935 citations*
11. **[Neural Text Generation from Structured Data with Application to the Biography Domain](https://md.research.elamur.ai/free/en/papers/lebret-2016-neural-text-generation-structured-data/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Remi Lebret, David Grangier, Michael Auli*2016 · 697 citations*
12. **[A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks](https://md.research.elamur.ai/free/en/papers/hashimoto-2016-joint-many-task-model-growing/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kazuma Hashimoto, Caiming Xiong, Yoshimasa Tsuruoka, et al.*2016 · 668 citations*
13. **[A Neural Approach to Automated Essay Scoring](https://md.research.elamur.ai/free/en/papers/taghipour-2016-neural-approach-automated-essay-scoring/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kaveh Taghipour, Hwee Tou Ng*2016 · 652 citations*
14. **[Learning principled bilingual mappings of word embeddings while preserving monolingual invariance](https://md.research.elamur.ai/free/en/papers/artetxe-2016-learning-principled-bilingual-mappings-word/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mikel Artetxe, Gorka Labaka, Eneko Agirre*2016 · 535 citations*
15. **[Stance Detection with Bidirectional Conditional Encoding](https://md.research.elamur.ai/free/en/papers/augenstein-2016-stance-detection-bidirectional-conditional-encoding/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Isabelle Augenstein, Tim Rocktäschel, Andreas Vlachos, et al.*2016 · 522 citations*
16. **[Recursive Neural Conditional Random Fields for Aspect-based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/wang-2016-recursive-neural-conditional-random-fields/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenya Wang, Sinno Jialin Pan, Daniel Dahlmeier, et al.*2016 · 515 citations*
17. **[Does String-Based Neural MT Learn Source Syntax?](https://md.research.elamur.ai/free/en/papers/shi-2016-does-string-based-neural-mt/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xing Shi, Inkit Padhi, Kevin Knight*2016 · 496 citations*
18. **[Demographic Dialectal Variation in Social Media: A Case Study of African-American English](https://md.research.elamur.ai/free/en/papers/blodgett-2016-demographic-dialectal-variation-social-media/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Su Lin Blodgett, Lisa Green, Brendan O'Connor*2016 · 471 citations*
19. **[Deep Reinforcement Learning for Mention-Ranking Coreference Models](https://md.research.elamur.ai/free/en/papers/clark-2016-deep-reinforcement-learning-mention-ranking/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kevin Clark, Christopher D. Manning*2016 · 463 citations*
20. **[Neural versus Phrase-Based Machine Translation Quality: a Case Study](https://md.research.elamur.ai/free/en/papers/bentivogli-2016-neural-versus-phrase-based-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Luisa Bentivogli, Arianna Bisazza, Mauro Cettolo, et al.*2016 · 437 citations*
21. **[Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora](https://md.research.elamur.ai/free/en/papers/hamilton-2016-inducing-domain-specific-sentiment-lexicons/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**William L. Hamilton, Kevin Clark, Jure Leskovec, et al.*2016 · 434 citations*
22. **[Exploiting Source-side Monolingual Data in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2016-exploiting-source-side-monolingual-data/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiajun Zhang, Chengqing Zong*2016 · 409 citations*
23. **[Analyzing the Behavior of Visual Question Answering Models](https://md.research.elamur.ai/free/en/papers/agrawal-2016-analyzing-behavior-visual-question-answering/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aishwarya Agrawal, Dhruv Batra, Devi Parikh*2016 · 360 citations*
24. **[Zero-Resource Translation with Multi-Lingual Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/firat-2016-zero-resource-translation-multi-lingual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Orhan Firat, Baskaran Sankaran, Yaser Al-onaizan, et al.*2016 · 352 citations*
25. **[How Transferable are Neural Networks in NLP Applications?](https://md.research.elamur.ai/free/en/papers/mou-2016-how-transferable-are-neural-networks/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lili Mou, Zhao Meng, Rui Yan, et al.*2016 · 327 citations*
26. **[Cultural Shift or Linguistic Drift? Comparing Two Computational Measures of Semantic Change](https://md.research.elamur.ai/free/en/papers/hamilton-2016-cultural-shift-or-linguistic-drift/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**William L. Hamilton, Jure Leskovec, Dan Jurafsky*2016 · 325 citations*
27. **[Controlling Output Length in Neural Encoder-Decoders](https://md.research.elamur.ai/free/en/papers/kikuchi-2016-controlling-output-length-neural-encoder/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuta Kikuchi, Graham Neubig, Ryohei Sasano, et al.*2016 · 323 citations*
28. **[SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity](https://md.research.elamur.ai/free/en/papers/gerz-2016-simverb-3500-large-scale-evaluation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Daniela Gerz, Ivan Vulić, Felix Hill, et al.*2016 · 319 citations*
29. **[Globally Coherent Text Generation with Neural Checklist Models](https://md.research.elamur.ai/free/en/papers/kiddon-2016-globally-coherent-text-generation-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chloé Kiddon, Luke Zettlemoyer, Yejin Choi*2016 · 302 citations*
30. **[Incorporating Discrete Translation Lexicons into Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/arthur-2016-incorporating-discrete-translation-lexicons-into/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Philip Arthur, Graham Neubig, Satoshi Nakamura*2016 · 299 citations*
31. **[Variational Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2016-variational-neural-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Biao Zhang, Deyi Xiong, Jinsong Su, et al.*2016 · 279 citations*
32. **[Language as a Latent Variable: Discrete Generative Models for Sentence Compression](https://md.research.elamur.ai/free/en/papers/miao-2016-language-as-latent-variable-discrete/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yishu Miao, Phil Blunsom*2016 · 257 citations*
33. **[Charagram: Embedding Words and Sentences via Character n-grams](https://md.research.elamur.ai/free/en/papers/wieting-2016-charagram-embedding-words-sentences-character/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**John Wieting, Mohit Bansal, Kevin Gimpel, et al.*2016 · 241 citations*
34. **[Event-Driven Emotion Cause Extraction with Corpus Construction](https://md.research.elamur.ai/free/en/papers/gui-2016-event-driven-emotion-cause-extraction/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lin Gui, Dongyin Wu, Ruifeng Xu, et al.*2016 · 239 citations*
35. **[Are Word Embedding-based Features Useful for Sarcasm Detection?](https://md.research.elamur.ai/free/en/papers/joshi-2016-are-word-embedding-based-features/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aditya Joshi, Vaibhav Tripathi, Kevin Patel, et al.*2016 · 212 citations*
36. [**Universal Decompositional Semantics on Universal Dependencies**Aaron Steven White, Drew Reisinger, Keisuke Sakaguchi, et al.*2016 · 208 citations*](https://md.research.elamur.ai/free/en/papers/white-2016-universal-decompositional-semantics-universal-dependencies/)
37. **[Reasoning about Pragmatics with Neural Listeners and Speakers](https://md.research.elamur.ai/free/en/papers/andreas-2016-reasoning-about-pragmatics-neural-listeners/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jacob Andreas, Dan Klein*2016 · 198 citations*
38. **[Span-Based Constituency Parsing with a Structure-Label System and Provably Optimal Dynamic Oracles](https://md.research.elamur.ai/free/en/papers/cross-2016-span-based-constituency-parsing-structure/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**James Cross, Liang Huang*2016 · 191 citations*
39. **[Supervised Attentions for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/mi-2016-supervised-attentions-neural-machine-translation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Haitao Mi, Zhiguo Wang, Abe Ittycheriah*2016 · 183 citations*
40. **[Event Detection and Co-reference with Minimal Supervision](https://md.research.elamur.ai/free/en/papers/peng-2016-event-detection-co-reference-minimal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Haoruo Peng, Yangqiu Song, Dan Roth*2016 · 180 citations*
41. **[Who did What: A Large-Scale Person-Centered Cloze Dataset](https://md.research.elamur.ai/free/en/papers/onishi-2016-who-did-what-large-scale/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Takeshi Onishi, Hai Wang, Mohit Bansal, et al.*2016 · 173 citations*
42. **[What makes a convincing argument? Empirical analysis and detecting attributes of convincingness in Web argumentation](https://md.research.elamur.ai/free/en/papers/habernal-2016-what-makes-convincing-argument-empirical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ivan Habernal, Iryna Gurevych*2016 · 165 citations*
43. **[Discourse Parsing with Attention-based Hierarchical Neural Networks](https://md.research.elamur.ai/free/en/papers/li-2016-discourse-parsing-attention-based-hierarchical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qi Li, Tianshi Li, Baobao Chang*2016 · 150 citations*
44. **[Recognizing Implicit Discourse Relations via Repeated Reading: Neural Networks with Multi-Level Attention](https://md.research.elamur.ai/free/en/papers/liu-2016-recognizing-implicit-discourse-relations-repeated/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Liu, Sujian Li*2016 · 128 citations*
45. **[A Stacking Gated Neural Architecture for Implicit Discourse Relation Classification](https://md.research.elamur.ai/free/en/papers/qin-2016-stacking-gated-neural-architecture-implicit/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lianhui Qin, Zhisong Zhang, Hai Zhao*2016 · 98 citations*
46. **[Interpreting Neural Networks to Improve Politeness Comprehension](https://md.research.elamur.ai/free/en/papers/aubakirova-2016-interpreting-neural-networks-improve-politeness/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Malika Aubakirova, Mohit Bansal*2016 · 87 citations*
47. **[AMR Parsing with an Incremental Joint Model](https://md.research.elamur.ai/free/en/papers/zhou-2016-amr-parsing-incremental-joint-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junsheng Zhou, Feiyu Xu, Hans Uszkoreit, et al.*2016 · 79 citations*
48. [**HUME: Human UCCA-Based Evaluation of Machine Translation**Alexandra Birch, Omri Abend, Ondřej Bojar, et al.*2016 · 58 citations*](https://md.research.elamur.ai/free/en/papers/birch-2016-hume-human-ucca-based-evaluation/)
49. [**Joint Transition-based Dependency Parsing and Disfluency Detection for Automatic Speech Recognition Texts**Masashi Yoshikawa, Hiroyuki Shindo, Yuji Matsumoto*2016 · 56 citations*](https://md.research.elamur.ai/free/en/papers/yoshikawa-2016-joint-transition-based-dependency-parsing/)
50. **[Learning Connective-based Word Representations for Implicit Discourse Relation Identification](https://md.research.elamur.ai/free/en/papers/braud-2016-learning-connective-based-word-representations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chloé Braud, Pascal Denis*2016 · 56 citations*
51. **[Intra-Sentential Subject Zero Anaphora Resolution using Multi-Column Convolutional Neural Network](https://md.research.elamur.ai/free/en/papers/iida-2016-intra-sentential-subject-zero-anaphora/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ryu Iida, Kentaro Torisawa, Jong-Hoon Oh, et al.*2016 · 51 citations*
52. **[Bilingually-constrained Synthetic Data for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/wu-2016-bilingually-constrained-synthetic-data-implicit/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Changxing Wu, Xiaodong Shi, Yidong Chen, et al.*2016 · 34 citations*
53. **[Variational Neural Discourse Relation Recognizer](https://md.research.elamur.ai/free/en/papers/zhang-2016-variational-neural-discourse-relation-recognizer/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Biao Zhang, Deyi Xiong, Jinsong Su, et al.*2016 · 30 citations*
54. [**Verb Phrase Ellipsis Resolution Using Discriminative and Margin-Infused Algorithms**Kian Kenyon-Dean, Jackie Chi Kit Cheung, Doina Precup*2016 · 24 citations*](https://md.research.elamur.ai/free/en/papers/dean-2016-verb-phrase-ellipsis-resolution-discriminative/)
55. [**An Evaluation of Parser Robustness for Ungrammatical Sentences**Homa B. Hashemi, Rebecca Hwa*2016 · 18 citations*](https://md.research.elamur.ai/free/en/papers/hashemi-2016-evaluation-parser-robustness-ungrammatical-sentences/)
56. [**Antecedent Selection for Sluicing: Structure and Content**Pranav Anand, Daniel Hardt*2016 · 17 citations*](https://md.research.elamur.ai/free/en/papers/anand-2016-antecedent-selection-sluicing-structure-content/)
57. [**Automatic Cross-Lingual Similarization of Dependency Grammars for Tree-based Machine Translation**Wenbin Jiang, Wen Zhang, Jinan Xu, et al.*2016 · 1 citation*](https://md.research.elamur.ai/free/en/papers/jiang-2016-automatic-cross-lingual-similarization-dependency/)
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