---
title: "Association for Computational Linguistics — works"
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# Works of Association for Computational Linguistics

3,691 works · page 1 of 37 · the most cited first · [← Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/)

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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. [**Transformers: State-of-the-Art Natural Language Processing**Thomas Wolf, Lysandre Debut, Victor Sanh, et al.*2020 · 15,591 citations*](https://md.research.elamur.ai/free/en/papers/wolf-2020-transformers-state-art-natural-language/)
3. [**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/)
4. [**SQuAD: 100,000+ Questions for Machine Comprehension of Text**Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, et al.*2016 · 9,488 citations*](https://md.research.elamur.ai/free/en/papers/rajpurkar-2016-squad-100-000-questions-machine/)
5. [**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/)
6. [**Thumbs up? Sentiment Classification using Machine Learning Techniques**Bo Pang, Lillian Lee, Shivakumar Vaithyanathan*2002 · 7,756 citations*](https://md.research.elamur.ai/free/en/papers/pang-2002-thumbs-up-sentiment-classification-machine/)
7. [**GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding**Alex Wang, Amanpreet Singh, Julian Michael, et al.*2018 · 7,141 citations*](https://md.research.elamur.ai/free/en/papers/wang-2018-glue-multi-task-benchmark-analysis/)
8. [**METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments**Satanjeev Banerjee, Alon Lavie*2005 · 5,483 citations*](https://md.research.elamur.ai/free/en/papers/banerjee-2005-meteor-automatic-metric-mt-evaluation/)
9. [**Hierarchical Attention Networks for Document Classification**Zichao Yang, Diyi Yang, Chris Dyer, et al.*2016 · 5,409 citations*](https://md.research.elamur.ai/free/en/papers/yang-2016-hierarchical-attention-networks-document-classification/)
10. [**Dense Passage Retrieval for Open-Domain Question Answering**Vladimir Karpukhin, Barlas Oguz, Sewon Min, et al.*2020 · 5,370 citations*](https://md.research.elamur.ai/free/en/papers/karpukhin-2020-dense-passage-retrieval-open-domain/)
11. [**SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing**Taku Kudo, John Richardson*2018 · 4,461 citations*](https://md.research.elamur.ai/free/en/papers/kudo-2018-sentencepiece-simple-language-independent-subword/)
12. [**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/)
13. [**A Call for Clarity in Reporting BLEU Scores**Matt Post*2018 · 4,130 citations*](https://md.research.elamur.ai/free/en/papers/post-2018-call-clarity-reporting-bleu-scores/)
14. [**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/)
15. [**Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis**Theresa Wilson, Janyce Wiebe, Paul Hoffmann*2005 · 3,979 citations*](https://md.research.elamur.ai/free/en/papers/wilson-2005-recognizing-contextual-polarity-phrase-level/)
16. [**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/)
17. [**fairseq: A Fast, Extensible Toolkit for Sequence Modeling**Myle Ott, Sergey Edunov, Alexei Baevski, et al.*2019 · 3,941 citations*](https://md.research.elamur.ai/free/en/papers/ott-2019-fairseq-fast-extensible-toolkit-sequence/)
18. [**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/)
19. [**SciBERT: A Pretrained Language Model for Scientific Text**Iz Beltagy, Kyle Lo, Arman Cohan*2019 · 3,548 citations*](https://md.research.elamur.ai/free/en/papers/beltagy-2019-scibert-pretrained-language-model-scientific/)
20. [**HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering**Zhilin Yang, Peng Qi, Saizheng Zhang, et al.*2018 · 3,489 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-hotpotqa-dataset-diverse-explainable-multi/)
21. [**Linguistic Regularities in Continuous Space Word Representations**Tomas Mikolov, Wen-tau Yih, Geoffrey Zweig*2013 · 3,482 citations*](https://md.research.elamur.ai/free/en/papers/mikolov-2013-linguistic-regularities-continuous-space-word/)
22. [**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/)
23. [**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/)
24. [**The Proposition Bank: An Annotated Corpus of Semantic Roles**Martha Palmer, Daniel Gildea, Paul Kingsbury*2005 · 3,208 citations*](https://md.research.elamur.ai/free/en/papers/palmer-2005-proposition-bank-annotated-corpus-semantic/)
25. [**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/)
26. [**Language Models as Knowledge Bases?**Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, et al.*2019 · 2,977 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2019-language-models-as-knowledge-bases/)
27. [**CodeBERT: A Pre-Trained Model for Programming and Natural Languages**Zhangyin Feng, Daya Guo, Duyu Tang, et al.*2020 · 2,954 citations*](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/)
28. [**A Diversity-Promoting Objective Function for Neural Conversation Models**Jiwei Li, Michel Galley, Chris Brockett, et al.*2016 · 2,925 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-diversity-promoting-objective-function-neural/)
29. [**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/)
30. [**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/)
31. [**Self-Attention with Relative Position Representations**Peter Shaw, Jakob Uszkoreit, Ashish Vaswani*2018 · 2,811 citations*](https://md.research.elamur.ai/free/en/papers/shaw-2018-self-attention-relative-position-representations/)
32. [**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/)
33. [**LXMERT: Learning Cross-Modality Encoder Representations from Transformers**Hao Tan, Mohit Bansal*2019 · 2,714 citations*](https://md.research.elamur.ai/free/en/papers/tan-2019-lxmert-learning-cross-modality-encoder/)
34. [**Attention-based LSTM for Aspect-level Sentiment Classification**Yequan Wang, Minlie Huang, Xiaoyan Zhu, et al.*2016 · 2,609 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-attention-based-lstm-aspect-level/)
35. [**SpanBERT: Improving Pre-training by Representing and Predicting Spans**Mandar Joshi, Danqi Chen, Yinhan Liu, et al.*2019 · 2,580 citations*](https://md.research.elamur.ai/free/en/papers/joshi-2019-spanbert-improving-pre-training-representing/)
36. [**Lost in the Middle: How Language Models Use Long Contexts**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,540 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/)
37. [**Discriminative Training Methods for Hidden Markov Models: Theory and Experiments with Perceptron Algorithms**Michael Collins*2002 · 2,510 citations*](https://md.research.elamur.ai/free/en/papers/collins-2002-discriminative-training-methods-hidden-markov/)
38. [**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/)
39. [**Statistical Significance Tests for Machine Translation Evaluation**Philipp Koehn*2004 · 2,444 citations*](https://md.research.elamur.ai/free/en/papers/koehn-2004-statistical-significance-tests-machine-translation/)
40. [**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/)
41. [**SemEval-2014 Task 4: Aspect Based Sentiment Analysis**Maria Pontiki, Dimitris Galanis, John Pavlopoulos, et al.*2014 · 2,405 citations*](https://md.research.elamur.ai/free/en/papers/pontiki-2014-semeval-2014-task-4-aspect/)
42. [**Meteor Universal: Language Specific Translation Evaluation for Any Target Language**Michael Denkowski, Alon Lavie*2014 · 2,392 citations*](https://md.research.elamur.ai/free/en/papers/denkowski-2014-meteor-universal-language-specific-translation/)
43. [**Generating Sentences from a Continuous Space**Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, et al.*2016 · 2,367 citations*](https://md.research.elamur.ai/free/en/papers/bowman-2016-generating-sentences-continuous-space/)
44. [**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/)
45. [**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/)
46. [**A Fast and Accurate Dependency Parser using Neural Networks**Danqi Chen, Christopher Manning*2014 · 2,301 citations*](https://md.research.elamur.ai/free/en/papers/chen-2014-fast-accurate-dependency-parser-neural/)
47. [**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/)
48. [**Named Entity Recognition with Bidirectional LSTM-CNNs**Jason P. C. Chiu, Eric Nichols*2015 · 2,276 citations*](https://md.research.elamur.ai/free/en/papers/chiu-2015-named-entity-recognition-bidirectional-lstm/)
49. [**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/)
50. [**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/)
51. [**FEVER: a Large-scale Dataset for Fact Extraction and VERification**James Thorne, Andreas Vlachos, Christos Christodoulopoulos, et al.*2018 · 2,205 citations*](https://md.research.elamur.ai/free/en/papers/thorne-2018-fever-large-scale-dataset-fact/)
52. [**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/)
53. [**Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter**Zeerak Waseem, Dirk Hovy*2016 · 2,158 citations*](https://md.research.elamur.ai/free/en/papers/waseem-2016-hateful-symbols-or-hateful-people/)
54. [**Tensor Fusion Network for Multimodal Sentiment Analysis**Amir Zadeh, Minghai Chen, Soujanya Poria, et al.*2017 · 2,107 citations*](https://md.research.elamur.ai/free/en/papers/zadeh-2017-tensor-fusion-network-multimodal-sentiment/)
55. [**chrF: character n-gram F-score for automatic MT evaluation**Maja Popović*2015 · 2,105 citations*](https://md.research.elamur.ai/free/en/papers/popovic-2015-chrf-character-n-gram-f/)
56. [**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/)
57. [**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/)
58. [**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/)
59. [**Head-Driven Statistical Models for Natural Language Parsing**Michael Collins*2003 · 2,001 citations*](https://md.research.elamur.ai/free/en/papers/collins-2003-head-driven-statistical-models-natural/)
60. [**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/)
61. [**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/)
62. [**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/)
63. [**Adversarial Examples for Evaluating Reading Comprehension Systems**Robin Jia, Percy Liang*2017 · 1,935 citations*](https://md.research.elamur.ai/free/en/papers/jia-2017-adversarial-examples-evaluating-reading-comprehension/)
64. [**Abstract Meaning Representation for Sembanking**Laura Banarescu, Claire Bonial, Shu Cai, et al.*2013 · 1,915 citations*](https://md.research.elamur.ai/free/en/papers/banarescu-2013-abstract-meaning-representation-sembanking/)
65. [**Extracting Product Features and Opinions from Reviews**Ana-Maria Popescu, Oren Etzioni*2005 · 1,904 citations*](https://md.research.elamur.ai/free/en/papers/popescu-2005-extracting-product-features-opinions-reviews/)
66. [**AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts**Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, et al.*2020 · 1,879 citations*](https://md.research.elamur.ai/free/en/papers/shin-2020-autoprompt-eliciting-knowledge-language-models/)
67. [**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/)
68. [**Design Challenges and Misconceptions in Named Entity Recognition**Lev Ratinov, Dan Roth*2009 · 1,836 citations*](https://md.research.elamur.ai/free/en/papers/ratinov-2009-design-challenges-misconceptions-named-entity/)
69. [**“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/)
70. [**A Survey on Hate Speech Detection using Natural Language Processing**Anna Schmidt, Michael Wiegand*2017 · 1,799 citations*](https://md.research.elamur.ai/free/en/papers/schmidt-2017-survey-hate-speech-detection-natural/)
71. [**Exploiting Cloze-Questions for Few-Shot Text Classification and Natural Language Inference**Timo Schick, Hinrich Schütze*2021 · 1,796 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-exploiting-cloze-questions-few-shot/)
72. [**Domain Adaptation with Structural Correspondence Learning**John Blitzer, Ryan McDonald, Fernando Pereira*2006 · 1,792 citations*](https://md.research.elamur.ai/free/en/papers/blitzer-2006-domain-adaptation-structural-correspondence-learning/)
73. [**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/)
74. [**COMET: A Neural Framework for MT Evaluation**Ricardo Rei, Craig Stewart, Ana C Farinha, et al.*2020 · 1,784 citations*](https://md.research.elamur.ai/free/en/papers/rei-2020-comet-neural-framework-mt-evaluation/)
75. [**Survey Article: Inter-Coder Agreement for Computational Linguistics**Ron Artstein, Massimo Poesio*2008 · 1,770 citations*](https://md.research.elamur.ai/free/en/papers/artstein-2008-survey-article-inter-coder-agreement/)
76. [**KenLM: Faster and Smaller Language Model Queries**Kenneth Heafield*2011 · 1,759 citations*](https://md.research.elamur.ai/free/en/papers/heafield-2011-kenlm-faster-smaller-language-model/)
77. [**TnT – A Statistical Part-of-Speech Tagger**Thorsten Brants*2000 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/brants-2000-tnt-statistical-part-speech-tagger/)
78. [**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/)
79. [**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/)
80. [**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/)
81. [**Document Modeling with Gated Recurrent Neural Network for Sentiment Classification**Duyu Tang, Bing Qin, Ting Liu*2015 · 1,675 citations*](https://md.research.elamur.ai/free/en/papers/tang-2015-document-modeling-gated-recurrent-neural/)
82. [**Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering**Gautier Izacard, Edouard Grave*2021 · 1,674 citations*](https://md.research.elamur.ai/free/en/papers/izacard-2021-leveraging-passage-retrieval-generative-models/)
83. [**SemEval-2016 Task 5: Aspect Based Sentiment Analysis**Maria Pontiki, Dimitris Galanis, Haris Papageorgiou, et al.*2016 · 1,656 citations*](https://md.research.elamur.ai/free/en/papers/pontiki-2016-semeval-2016-task-5-aspect/)
84. [**Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding**Akira Fukui, Dong Huk Park, Daylen Yang, et al.*2016 · 1,642 citations*](https://md.research.elamur.ai/free/en/papers/fukui-2016-multimodal-compact-bilinear-pooling-visual/)
85. [**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/)
86. [**Hierarchical Phrase-Based Translation**David Chiang*2007 · 1,628 citations*](https://md.research.elamur.ai/free/en/papers/chiang-2007-hierarchical-phrase-based-translation/)
87. [**RACE: Large-scale ReAding Comprehension Dataset From Examinations**Guokun Lai, Qizhe Xie, Hanxiao Liu, et al.*2017 · 1,619 citations*](https://md.research.elamur.ai/free/en/papers/lai-2017-race-large-scale-reading-comprehension/)
88. [**Evaluating WordNet-based Measures of Lexical Semantic Relatedness**Alexander Budanitsky, Graeme Hirst*2006 · 1,610 citations*](https://md.research.elamur.ai/free/en/papers/budanitsky-2006-evaluating-wordnet-based-measures-lexical/)
89. [**Recurrent Continuous Translation Models**Nal Kalchbrenner, Phil Blunsom*2013 · 1,597 citations*](https://md.research.elamur.ai/free/en/papers/kalchbrenner-2013-recurrent-continuous-translation-models/)
90. [**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/)
91. [**A Decomposable Attention Model for Natural Language Inference**Ankur Parikh, Oscar Täckström, Dipanjan Das, et al.*2016 · 1,589 citations*](https://md.research.elamur.ai/free/en/papers/parikh-2016-decomposable-attention-model-natural-language/)
92. [**Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task**Tao Yu, Rui Zhang, Kai Yang, et al.*2018 · 1,582 citations*](https://md.research.elamur.ai/free/en/papers/yu-2018-spider-large-scale-human-labeled/)
93. [**Semantic Compositionality through Recursive Matrix-Vector Spaces**Richard Socher, Brody Huval, Christopher D. Manning, et al.*2012 · 1,559 citations*](https://md.research.elamur.ai/free/en/papers/socher-2012-semantic-compositionality-through-recursive-matrix/)
94. [**Universal Sentence Encoder for English**Daniel Cer, Yinfei Yang, Sheng-yi Kong, et al.*2018 · 1,544 citations*](https://md.research.elamur.ai/free/en/papers/cer-2018-universal-sentence-encoder-english/)
95. [**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/)
96. [**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/)
97. [**CLIPScore: A Reference-free Evaluation Metric for Image Captioning**Jack Hessel, Ari Holtzman, Maxwell Forbes, et al.*2021 · 1,498 citations*](https://md.research.elamur.ai/free/en/papers/hessel-2021-clipscore-reference-free-evaluation-metric/)
98. [**LEGAL-BERT: The Muppets straight out of Law School**Ilias Chalkidis, Manos Fergadiotis, Prodromos Malakasiotis, et al.*2020 · 1,490 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2020-legal-bert-muppets-straight-out/)
99. [**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/)
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