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# Works of Annual Meeting of the Association for Computational Linguistics (ACL)

1,021 works · page 1 of 11 · the most cited first · [← Annual Meeting of the Association for…](https://md.research.elamur.ai/free/en/venues/acl/)

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1. [**Bleu: a Method for Automatic Evaluation of Machine Translation**Kishore Papineni, Salim Roukos, Todd Ward, et al.*2002 · 32,065 citations*](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/)
2. [**BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension**Mike Lewis, Yinhan Liu, Naman Goyal, et al.*2020 · 12,752 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2020-bart-denoising-sequence-sequence-pre/)
3. [**The Stanford CoreNLP Natural Language Processing Toolkit**Christopher Manning, Mihai Surdeanu, John Bauer, et al.*2014 · 8,620 citations*](https://md.research.elamur.ai/free/en/papers/manning-2014-stanford-corenlp-natural-language-processing/)
4. [**Learning Word Vectors for Sentiment Analysis**Andrew L. Maas, Raymond E. Daly, Peter T. Pham, et al.*2011 · 4,272 citations*](https://md.research.elamur.ai/free/en/papers/maas-2011-learning-word-vectors-sentiment-analysis/)
5. [**Energy and Policy Considerations for Deep Learning in NLP**Emma Strubell, Ananya Ganesh, Andrew McCallum*2019 · 4,049 citations*](https://md.research.elamur.ai/free/en/papers/strubell-2019-energy-policy-considerations-deep-learning/)
6. [**Accurate Unlexicalized Parsing**Dan Klein, Christopher D. Manning*2003 · 3,942 citations*](https://md.research.elamur.ai/free/en/papers/klein-2003-accurate-unlexicalized-parsing/)
7. [**A Sentimental Education: Sentiment Analysis Using Subjectivity Summarization Based on Minimum Cuts**Bo Pang, Lillian Lee*2004 · 3,842 citations*](https://md.research.elamur.ai/free/en/papers/pang-2004-sentimental-education-sentiment-analysis-subjectivity/)
8. [**Incorporating Non-local Information into Information Extraction Systems by Gibbs Sampling**Jenny Rose Finkel, Trond Grenager, Christopher Manning*2005 · 3,618 citations*](https://md.research.elamur.ai/free/en/papers/finkel-2005-incorporating-non-local-information-into/)
9. [**The Berkeley FrameNet Project**Collin F. Baker, Charles J. Fillmore, John B. Lowe*1998 · 3,544 citations*](https://md.research.elamur.ai/free/en/papers/baker-1998-berkeley-framenet/)
10. [**Neural Machine Translation of Rare Words with Subword Units**Rico Sennrich, Barry Haddow, Alexandra Birch*2016 · 3,409 citations*](https://md.research.elamur.ai/free/en/papers/sennrich-2016-neural-machine-translation-rare-words/)
11. [**Know What You Don't Know: Unanswerable Questions for SQuAD**Pranav Rajpurkar, Robin Jia, Percy Liang*2018 · 3,360 citations*](https://md.research.elamur.ai/free/en/papers/rajpurkar-2018-know-what-you-don-t/)
12. [**Verb Semantics and Lexical Selection**Zhibiao Wu, Martha Palmer*1994 · 3,276 citations*](https://md.research.elamur.ai/free/en/papers/wu-1994-verb-semantics-lexical-selection/)
13. [**TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension**Mandar Joshi, Eunsol Choi, Daniel Weld, et al.*2017 · 3,204 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2017-triviaqa-large-scale-distantly-supervised/)
14. [**Unsupervised Word Sense Disambiguation Rivaling Supervised Methods**David Yarowsky*1995 · 2,840 citations*](https://md.research.elamur.ai/free/en/papers/yarowsky-1995-unsupervised-word-sense-disambiguation-rivaling/)
15. [**Thumbs Up or Thumbs Down? Semantic Orientation Applied to Unsupervised Classification of Reviews**Peter Turney*2002 · 2,826 citations*](https://md.research.elamur.ai/free/en/papers/turney-2002-thumbs-up-or-thumbs-down/)
16. [**Seeing Stars: Exploiting Class Relationships for Sentiment Categorization with Respect to Rating Scales**Bo Pang, Lillian Lee*2005 · 2,722 citations*](https://md.research.elamur.ai/free/en/papers/pang-2005-seeing-stars-exploiting-class-relationships/)
17. [**OpenNMT: Open-Source Toolkit for Neural Machine Translation**Guillaume Klein, Yoon Kim, Yuntian Deng, et al.*2017 · 2,460 citations*](https://md.research.elamur.ai/free/en/papers/klein-2017-opennmt-open-source-toolkit-neural/)
18. [**Word Representations: A Simple and General Method for Semi-Supervised Learning**Joseph Turian, Lev-Arie Ratinov, Yoshua Bengio*2010 · 2,421 citations*](https://md.research.elamur.ai/free/en/papers/turian-2010-word-representations-simple-general-method/)
19. [**Stanza: A Python Natural Language Processing Toolkit for Many Human Languages**Peng Qi, Yuhao Zhang, Yuhui Zhang, et al.*2020 · 2,347 citations*](https://md.research.elamur.ai/free/en/papers/qi-2020-stanza-python-natural-language-processing/)
20. [**Biographies, Bollywood, Boom-boxes and Blenders: Domain Adaptation for Sentiment Classification**John Blitzer, Mark Dredze, Fernando Pereira*2007 · 2,329 citations*](https://md.research.elamur.ai/free/en/papers/blitzer-2007-biographies-bollywood-boom-boxes-blenders/)
21. [**Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning**Piyush Sharma, Nan Ding, Sebastian Goodman, et al.*2018 · 2,278 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2018-conceptual-captions-cleaned-hypernymed-image/)
22. [**Reading Wikipedia to Answer Open-Domain Questions**Danqi Chen, Adam Fisch, Jason Weston, et al.*2017 · 2,250 citations*](https://md.research.elamur.ai/free/en/papers/chen-2017-reading-wikipedia-answer-open-domain/)
23. [**Attention-Based Bidirectional Long Short-Term Memory Networks for Relation Classification**Peng Zhou, Wei Shi, Jun Tian, et al.*2016 · 2,216 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2016-attention-based-bidirectional-long-short/)
24. [**Multimodal Transformer for Unaligned Multimodal Language Sequences**Yao-Hung Hubert Tsai, Shaojie Bai, Paul Pu Liang, et al.*2019 · 2,170 citations*](https://md.research.elamur.ai/free/en/papers/tsai-2019-multimodal-transformer-unaligned-multimodal-language/)
25. [**How Multilingual is Multilingual BERT?**Telmo Pires, Eva Schlinger, Dan Garrette*2019 · 2,095 citations*](https://md.research.elamur.ai/free/en/papers/pires-2019-how-multilingual-is-multilingual-bert/)
26. [**Automatic Retrieval and Clustering of Similar Words**Dekang Lin*1998 · 2,060 citations*](https://md.research.elamur.ai/free/en/papers/lin-1998-automatic-retrieval-clustering-similar-words/)
27. [**TruthfulQA: Measuring How Models Mimic Human Falsehoods**Stephanie Lin, Jacob Hilton, Owain Evans*2022 · 2,047 citations*](https://md.research.elamur.ai/free/en/papers/lin-2022-truthfulqa-measuring-how-models-mimic/)
28. [**BERT Rediscovers the Classical NLP Pipeline**Ian Tenney, Dipanjan Das, Ellie Pavlick*2019 · 1,993 citations*](https://md.research.elamur.ai/free/en/papers/tenney-2019-bert-rediscovers-classical-nlp-pipeline/)
29. [**Making Pre-trained Language Models Better Few-shot Learners**Tianyu Gao, Adam Fisch, Danqi Chen*2021 · 1,952 citations*](https://md.research.elamur.ai/free/en/papers/gao-2021-making-pre-trained-language-models/)
30. [**Knowledge Graph Embedding via Dynamic Mapping Matrix**Guoliang Ji, Shizhu He, Liheng Xu, et al.*2015 · 1,936 citations*](https://md.research.elamur.ai/free/en/papers/ji-2015-knowledge-graph-embedding-dynamic-mapping/)
31. [**Incorporating Copying Mechanism in Sequence-to-Sequence Learning**Jiatao Gu, Zhengdong Lu, Hang Li, et al.*2016 · 1,895 citations*](https://md.research.elamur.ai/free/en/papers/gu-2016-incorporating-copying-mechanism-sequence-sequence/)
32. [**Personalizing Dialogue Agents: I have a dog, do you have pets too?**Saizheng Zhang, Emily Dinan, Jack Urbanek, et al.*2018 · 1,839 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-personalizing-dialogue-agents-i-have/)
33. [**“Liar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection**William Yang Wang*2017 · 1,801 citations*](https://md.research.elamur.ai/free/en/papers/wang-2017-liar-liar-pants-fire-new/)
34. [**What Does BERT Learn about the Structure of Language?**Ganesh Jawahar, Benoît Sagot, Djamé Seddah*2019 · 1,789 citations*](https://md.research.elamur.ai/free/en/papers/jawahar-2019-what-does-bert-learn-about/)
35. [**Language (Technology) is Power: A Critical Survey of “Bias” in NLP**Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.*2020 · 1,700 citations*](https://md.research.elamur.ai/free/en/papers/blodgett-2020-language-technology-is-power-critical/)
36. [**A Hierarchical Phrase-Based Model for Statistical Machine Translation**David Chiang*2005 · 1,683 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2005-hierarchical-phrase-based-model-statistical/)
37. [**Don't count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors**Marco Baroni, Georgiana Dinu, Germán Kruszewski*2014 · 1,678 citations*](https://md.research.elamur.ai/free/en/papers/baroni-2014-don-t-count-predict-systematic/)
38. [**MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations**Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, et al.*2018 · 1,668 citations*](https://md.research.elamur.ai/free/en/papers/poria-2018-meld-multimodal-multi-party-dataset/)
39. [**Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference**R. Thomas McCoy, Ellie Pavlick, Tal Linzen*2019 · 1,630 citations*](https://md.research.elamur.ai/free/en/papers/mccoy-2019-right-wrong-reasons-diagnosing-syntactic/)
40. [**End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures**Makoto Miwa, Mohit Bansal*2016 · 1,596 citations*](https://md.research.elamur.ai/free/en/papers/miwa-2016-end-end-relation-extraction-lstms/)
41. [**Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned**Elena Voita, David Talbot, Fedor Moiseev, et al.*2019 · 1,511 citations*](https://md.research.elamur.ai/free/en/papers/voita-2019-analyzing-multi-head-self-attention/)
42. [**Multimodal Language Analysis in the Wild: CMU-MOSEI Dataset and Interpretable Dynamic Fusion Graph**AmirAli Bagher Zadeh, Paul Pu Liang, Soujanya Poria, et al.*2018 · 1,506 citations*](https://md.research.elamur.ai/free/en/papers/zadeh-2018-multimodal-language-analysis-wild-cmu/)
43. [**Multi-Task Deep Neural Networks for Natural Language Understanding**Xiaodong Liu, Pengcheng He, Weizhu Chen, et al.*2019 · 1,501 citations*](https://md.research.elamur.ai/free/en/papers/liu-2019-multi-task-deep-neural-networks/)
44. [**The State and Fate of Linguistic Diversity and Inclusion in the NLP World**Pratik Joshi, Sebastin Santy, Amar Budhiraja, et al.*2020 · 1,492 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2020-state-fate-linguistic-diversity-inclusion/)
45. [**Improved Statistical Alignment Models**Franz Josef Och, Hermann Ney*2000 · 1,467 citations*](https://md.research.elamur.ai/free/en/papers/och-2000-improved-statistical-alignment-models/)
46. [**Discriminative Training and Maximum Entropy Models for Statistical Machine Translation**Franz Josef Och, Hermann Ney*2002 · 1,461 citations*](https://md.research.elamur.ai/free/en/papers/och-2002-discriminative-training-maximum-entropy-models/)
47. [**GLM: General Language Model Pretraining with Autoregressive Blank Infilling**Zhengxiao Du, Yujie Qian, Xiao Liu, et al.*2022 · 1,449 citations*](https://md.research.elamur.ai/free/en/papers/du-2022-glm-general-language-model-pretraining/)
48. [**Language-agnostic BERT Sentence Embedding**Fangxiaoyu Feng, Yinfei Yang, Daniel Cer, et al.*2020 · 1,412 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-language-agnostic-bert-sentence-embedding/)
49. [**NLTK: The Natural Language Toolkit**Steven Bird*2006 · 1,372 citations*](https://md.research.elamur.ai/free/en/papers/bird-2006-nltk-natural-language-toolkit/)
50. [**Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data**Emily M. Bender, Alexander Koller*2020 · 1,371 citations*](https://md.research.elamur.ai/free/en/papers/bender-2020-climbing-nlu-meaning-form-understanding/)
51. [**Improving Word Representations via Global Context and Multiple Word Prototypes**Eric Huang, Richard Socher, Christopher Manning, et al.*2012 · 1,349 citations*](https://md.research.elamur.ai/free/en/papers/huang-2012-improving-word-representations-global-context/)
52. [**Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification**Duyu Tang, Furu Wei, Nan Yang, et al.*2014 · 1,341 citations*](https://md.research.elamur.ai/free/en/papers/tang-2014-learning-sentiment-specific-word-embedding/)
53. [**Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking**Eugene Charniak, Mark Johnson*2005 · 1,312 citations*](https://md.research.elamur.ai/free/en/papers/charniak-2005-coarse-fine-n-best-parsing/)
54. [**COMET: Commonsense Transformers for Automatic Knowledge Graph Construction**Antoine Bosselut, Hannah Rashkin, Maarten Sap, et al.*2019 · 1,282 citations*](https://md.research.elamur.ai/free/en/papers/bosselut-2019-comet-commonsense-transformers-automatic-knowledge/)
55. [**Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change**William L. Hamilton, Jure Leskovec, Dan Jurafsky*2016 · 1,270 citations*](https://md.research.elamur.ai/free/en/papers/hamilton-2016-diachronic-word-embeddings-reveal-statistical/)
56. [**CamemBERT: a Tasty French Language Model**Louis Martin, Benjamin Muller, Pedro Javier Ortiz Suárez, et al.*2019 · 1,262 citations*](https://md.research.elamur.ai/free/en/papers/martin-2019-camembert-tasty-french-language-model/)
57. [**Neural Responding Machine for Short-Text Conversation**Lifeng Shang, Zhengdong Lu, Hang Li*2015 · 1,242 citations*](https://md.research.elamur.ai/free/en/papers/shang-2015-neural-responding-machine-short-text/)
58. [**Learning Accurate, Compact, and Interpretable Tree Annotation**Slav Petrov, Leon Barrett, Romain Thibaux, et al.*2006 · 1,242 citations*](https://md.research.elamur.ai/free/en/papers/petrov-2006-learning-accurate-compact-interpretable-tree/)
59. [**Latent Retrieval for Weakly Supervised Open Domain Question Answering**Kenton Lee, Ming-Wei Chang, Kristina Toutanova*2019 · 1,234 citations*](https://md.research.elamur.ai/free/en/papers/lee-2019-latent-retrieval-weakly-supervised-open/)
60. [**Online Large-Margin Training of Dependency Parsers**Ryan McDonald, Koby Crammer, Fernando Pereira*2005 · 1,212 citations*](https://md.research.elamur.ai/free/en/papers/mcdonald-2005-online-large-margin-training-dependency/)
61. [**Adaptive Recursive Neural Network for Target-dependent Twitter Sentiment Classification**Li Dong, Furu Wei, Chuanqi Tan, et al.*2014 · 1,211 citations*](https://md.research.elamur.ai/free/en/papers/dong-2014-adaptive-recursive-neural-network-target/)
62. [**An Empirical Study of Smoothing Techniques for Language Modeling**Stanley F. Chen, Joshua Goodman*1996 · 1,209 citations*](https://md.research.elamur.ai/free/en/papers/chen-1996-empirical-study-smoothing-techniques-language/)
63. [**Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity**Yao Lu, Max Bartolo, Alastair Moore, et al.*2022 · 1,187 citations*](https://md.research.elamur.ai/free/en/papers/lu-2022-fantastically-ordered-prompts-where-find/)
64. [**Efficient Low-rank Multimodal Fusion With Modality-Specific Factors**Zhun Liu, Ying Shen, Varun Bharadhwaj Lakshminarasimhan, et al.*2018 · 1,174 citations*](https://md.research.elamur.ai/free/en/papers/liu-2018-efficient-low-rank-multimodal-fusion/)
65. [**Event Extraction via Dynamic Multi-Pooling Convolutional Neural Networks**Yubo Chen, Liheng Xu, Kang Liu, et al.*2015 · 1,170 citations*](https://md.research.elamur.ai/free/en/papers/chen-2015-event-extraction-dynamic-multi-pooling/)
66. [**On the Cross-lingual Transferability of Monolingual Representations**Mikel Artetxe, Sebastian Ruder, Dani Yogatama*2020 · 1,168 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2020-cross-lingual-transferability-monolingual-representations/)
67. [**Distributional Clustering of English Words**Fernando Pereira, Naftali Tishby, Lillian Lee*1993 · 1,160 citations*](https://md.research.elamur.ai/free/en/papers/pereira-1993-distributional-clustering-english-words/)
68. [**The Risk of Racial Bias in Hate Speech Detection**Maarten Sap, Dallas Card, Saadia Gabriel, et al.*2019 · 1,148 citations*](https://md.research.elamur.ai/free/en/papers/sap-2019-risk-racial-bias-hate-speech/)
69. [**StereoSet: Measuring stereotypical bias in pretrained language models**Moin Nadeem, Anna Bethke, Siva Reddy*2021 · 1,131 citations*](https://md.research.elamur.ai/free/en/papers/nadeem-2021-stereoset-measuring-stereotypical-bias-pretrained/)
70. [**Baselines and Bigrams: Simple, Good Sentiment and Topic Classification**Sida Wang, Christopher Manning*2012 · 1,116 citations*](https://md.research.elamur.ai/free/en/papers/wang-2012-baselines-bigrams-simple-good-sentiment/)
71. [**Quantifying Attention Flow in Transformers**Samira Abnar, Willem Zuidema*2020 · 1,049 citations*](https://md.research.elamur.ai/free/en/papers/abnar-2020-quantifying-attention-flow-transformers/)
72. [**Three Generative, Lexicalised Models for Statistical Parsing**Michael Collins*1997 · 1,045 citations*](https://md.research.elamur.ai/free/en/papers/collins-1997-three-generative-lexicalised-models-statistical/)
73. [**LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models**Yaowei Zheng, Richong Zhang, Junhao Zhang, et al.*2024 · 1,035 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-llamafactory-unified-efficient-fine-tuning/)
74. [**What you can cram into a single $&!#* vector: Probing sentence embeddings for linguistic properties**Alexis Conneau, German Kruszewski, Guillaume Lample, et al.*2018 · 1,021 citations*](https://md.research.elamur.ai/free/en/papers/conneau-2018-what-you-can-cram-into/)
75. [**Context-Dependent Sentiment Analysis in User-Generated Videos**Soujanya Poria, Erik Cambria, Devamanyu Hazarika, et al.*2017 · 1,019 citations*](https://md.research.elamur.ai/free/en/papers/poria-2017-context-dependent-sentiment-analysis-user/)
76. [**A Syntax-based Statistical Translation Model**Kenji Yamada, Kevin Knight*2001 · 1,018 citations*](https://md.research.elamur.ai/free/en/papers/yamada-2001-syntax-based-statistical-translation-model/)
77. [**P-Tuning: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks**Xiao Liu, Kaixuan Ji, Yicheng Fu, et al.*2022 · 1,013 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-p-tuning-prompt-tuning-can/)
78. [**MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices**Zhiqing Sun, Hongkun Yu, Xiaodan Song, et al.*2020 · 1,003 citations*](https://md.research.elamur.ai/free/en/papers/sun-2020-mobilebert-compact-task-agnostic-bert/)
79. [**Neural Summarization by Extracting Sentences and Words**Jianpeng Cheng, Mirella Lapata*2016 · 1,000 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2016-neural-summarization-extracting-sentences-words/)
80. [**On Using Very Large Target Vocabulary for Neural Machine Translation**Sébastien Jean, Kyunghyun Cho, Roland Memisevic, et al.*2015 · 999 citations*](https://md.research.elamur.ai/free/en/papers/jean-2015-very-large-target-vocabulary-neural/)
81. [**Dependency Tree Kernels for Relation Extraction**Aron Culotta, Jeffrey Sorensen*2004 · 998 citations*](https://md.research.elamur.ai/free/en/papers/culotta-2004-dependency-tree-kernels-relation-extraction/)
82. [**Chinese NER Using Lattice LSTM**Yue Zhang, Jie Yang*2018 · 990 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-chinese-ner-lattice-lstm/)
83. [**Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders**Tiancheng Zhao, Ran Zhao, Maxine Eskenazi*2017 · 986 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2017-learning-discourse-level-diversity-neural/)
84. [**Learning surface text patterns for a Question Answering System**Deepak Ravichandran, Eduard Hovy*2002 · 970 citations*](https://md.research.elamur.ai/free/en/papers/ravichandran-2002-learning-surface-text-patterns-question/)
85. [**Exploring Various Knowledge in Relation Extraction**GuoDong Zhou, Jian Su, Jie Zhang, et al.*2005 · 937 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2005-exploring-various-knowledge-relation-extraction/)
86. [**Automatic Evaluation of Machine Translation Quality Using Longest Common Subsequence and Skip-Bigram Statistics**Chin-Yew Lin, Franz Josef Och*2004 · 937 citations*](https://md.research.elamur.ai/free/en/papers/lin-2004-automatic-evaluation-machine-translation-quality/)
87. [**Modeling Coverage for Neural Machine Translation**Zhaopeng Tu, Zhengdong Lu, Yang Liu, et al.*2016 · 927 citations*](https://md.research.elamur.ai/free/en/papers/tu-2016-modeling-coverage-neural-machine-translation/)
88. [**Collecting Highly Parallel Data for Paraphrase Evaluation**David Chen, William Dolan*2011 · 926 citations*](https://md.research.elamur.ai/free/en/papers/chen-2011-collecting-highly-parallel-data-paraphrase/)
89. [**Improving Machine Learning Approaches to Coreference Resolution**Vincent Ng, Claire Cardie*2002 · 923 citations*](https://md.research.elamur.ai/free/en/papers/ng-2002-improving-machine-learning-approaches-coreference/)
90. [**Leveraging Linguistic Structure For Open Domain Information Extraction**Gabor Angeli, Melvin Jose Johnson Premkumar, Christopher D. Manning*2015 · 921 citations*](https://md.research.elamur.ai/free/en/papers/angeli-2015-leveraging-linguistic-structure-open-domain/)
91. [**Clause Restructuring for Statistical Machine Translation**Michael Collins, Philipp Koehn, Ivona Kučerová*2005 · 918 citations*](https://md.research.elamur.ai/free/en/papers/collins-2005-clause-restructuring-statistical-machine-translation/)
92. [**Deep Unordered Composition Rivals Syntactic Methods for Text Classification**Mohit Iyyer, Varun Manjunatha, Jordan Boyd-Graber, et al.*2015 · 914 citations*](https://md.research.elamur.ai/free/en/papers/iyyer-2015-deep-unordered-composition-rivals-syntactic/)
93. [**Learning to Ask: Neural Question Generation for Reading Comprehension**Xinya Du, Junru Shao, Claire Cardie*2017 · 913 citations*](https://md.research.elamur.ai/free/en/papers/du-2017-learning-ask-neural-question-generation/)
94. [**Joint Extraction of Entities and Relations Based on a Novel Tagging Scheme**Suncong Zheng, Feng Wang, Hongyun Bao, et al.*2017 · 902 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2017-joint-extraction-entities-relations-based/)
95. [**Is Attention Interpretable?**Sofia Serrano, Noah A. Smith*2019 · 885 citations*](https://md.research.elamur.ai/free/en/papers/serrano-2019-is-attention-interpretable/)
96. [**Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency**Shuhuai Ren, Yihe Deng, Kun He, et al.*2019 · 884 citations*](https://md.research.elamur.ai/free/en/papers/ren-2019-generating-natural-language-adversarial-examples/)
97. [**Instance Weighting for Domain Adaptation in NLP**Jing Jiang, ChengXiang Zhai*2007 · 870 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2007-instance-weighting-domain-adaptation-nlp/)
98. [**Transition-Based Dependency Parsing with Stack Long Short-Term Memory**Chris Dyer, Miguel Ballesteros, Wang Ling, et al.*2015 · 857 citations*](https://md.research.elamur.ai/free/en/papers/dyer-2015-transition-based-dependency-parsing-stack/)
99. [**Intelligent Selection of Language Model Training Data**Robert C. Moore, William Lewis*2010 · 848 citations*](https://md.research.elamur.ai/free/en/papers/moore-2010-intelligent-selection-language-model-training/)
100. [**A robust self-learning method for fully unsupervised cross-lingual mappings of word embeddings**Mikel Artetxe, Gorka Labaka, Eneko Agirre*2018 · 847 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2018-vecmap-unsupervised/)

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