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# Works of Conference on Empirical Methods in Natural Language Processing (EMNLP)

703 works · page 1 of 8 · the most cited first · [← Conference on Empirical Methods in Natural…](https://md.research.elamur.ai/free/en/venues/emnlp/)

**1** [2](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/2/) … [8](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/8/) [next →](https://md.research.elamur.ai/free/en/venues/emnlp/works/page/2/)

1. [**Convolutional Neural Networks for Sentence Classification**Yoon Kim*2014 · 16,218 citations*](https://md.research.elamur.ai/free/en/papers/kim-2014-convolutional-neural-networks-sentence-classification/)
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. [**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/)
4. [**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/)
5. [**GloVe: Global Vectors for Word Representation**Jeffrey Pennington, Richard Socher, Christopher Manning*2014 · 5,962 citations*](https://md.research.elamur.ai/free/en/papers/pennington-2014-glove-global-vectors-word-representation/)
6. [**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/)
7. [**Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks**Nils Reimers, Iryna Gurevych*2019 · 4,838 citations*](https://md.research.elamur.ai/free/en/papers/reimers-2019-sentence-bert-sentence-embeddings-siamese/)
8. [**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/)
9. [**SimCSE: Simple Contrastive Learning of Sentence Embeddings**Tianyu Gao, Xingcheng Yao, Danqi Chen*2021 · 3,921 citations*](https://md.research.elamur.ai/free/en/papers/gao-2021-simcse-simple-contrastive-learning-sentence/)
10. [**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/)
11. [**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/)
12. [**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/)
13. [**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/)
14. [**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/)
15. [**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/)
16. [**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/)
17. [**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/)
18. [**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/)
19. [**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/)
20. [**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/)
21. [**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/)
22. [**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/)
23. [**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/)
24. [**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/)
25. [**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/)
26. [**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/)
27. [**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/)
28. [**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/)
29. [**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/)
30. [**A Maximum Entropy Model for Part-Of-Speech Tagging**Adwait Ratnaparkhi*1996 · 1,554 citations*](https://md.research.elamur.ai/free/en/papers/ratnaparkhi-1996-maximum-entropy-model-part-speech/)
31. [**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/)
32. [**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/)
33. [**Deep Reinforcement Learning for Dialogue Generation**Jiwei Li, Will Monroe, Alan Ritter, et al.*2016 · 1,479 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-deep-reinforcement-learning-dialogue-generation/)
34. [**Effective Approaches to Attention-based Neural Machine Translation**Thang Luong, Hieu Pham, Christopher D. Manning*2015 · 1,474 citations*](https://md.research.elamur.ai/free/en/papers/luong-2015-effective-approaches-attention-based-neural/)
35. [**Named Entity Recognition in Tweets: An Experimental Study**Alan Ritter, Sam Clark, Mausam, et al.*2011 · 1,451 citations*](https://md.research.elamur.ai/free/en/papers/ritter-2011-named-entity-recognition-tweets-experimental/)
36. [**Sequence-Level Knowledge Distillation**Yoon Kim, Alexander M. Rush*2016 · 1,440 citations*](https://md.research.elamur.ai/free/en/papers/kim-2016-sequence-level-knowledge-distillation/)
37. [**Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?**Sewon Min, Xinxi Lyu, Ari Holtzman, et al.*2022 · 1,423 citations*](https://md.research.elamur.ai/free/en/papers/min-2022-rethinking-role-demonstrations-what-makes/)
38. [**Justifying Recommendations using Distantly-Labeled Reviews and Fine-Grained Aspects**Jianmo Ni, Jiacheng Li, Julian McAuley*2019 · 1,421 citations*](https://md.research.elamur.ai/free/en/papers/ni-2019-justifying-recommendations-distantly-labeled-reviews/)
39. [**Semi-Supervised Recursive Autoencoders for Predicting Sentiment Distributions**Richard Socher, Jeffrey Pennington, Eric H. Huang, et al.*2011 · 1,411 citations*](https://md.research.elamur.ai/free/en/papers/socher-2011-semi-supervised-recursive-autoencoders-predicting/)
40. [**Optimizing Semantic Coherence in Topic Models**David Mimno, Hanna Wallach, Edmund Talley, et al.*2011 · 1,334 citations*](https://md.research.elamur.ai/free/en/papers/mimno-2011-optimizing-semantic-coherence-topic-models/)
41. [**Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation**Nils Reimers, Iryna Gurevych*2020 · 1,320 citations*](https://md.research.elamur.ai/free/en/papers/reimers-2020-making-monolingual-sentence-embeddings-multilingual/)
42. [**Long Short-Term Memory-Networks for Machine Reading**Jianpeng Cheng, Li Dong, Mirella Lapata*2016 · 1,300 citations*](https://md.research.elamur.ai/free/en/papers/cheng-2016-long-short-term-memory-networks/)
43. [**V-Measure: A Conditional Entropy-Based External Cluster Evaluation Measure**Andrew Rosenberg, Julia Hirschberg*2007 · 1,279 citations*](https://md.research.elamur.ai/free/en/papers/rosenberg-2007-vmeasure-conditional-entropy-cluster-evaluation/)
44. [**End-to-end Neural Coreference Resolution**Kenton Lee, Luheng He, Mike Lewis, et al.*2017 · 1,277 citations*](https://md.research.elamur.ai/free/en/papers/lee-2017-end-end-neural-coreference-resolution/)
45. [**ReferItGame: Referring to Objects in Photographs of Natural Scenes**Sahar Kazemzadeh, Vicente Ordonez, Mark Matten, et al.*2014 · 1,276 citations*](https://md.research.elamur.ai/free/en/papers/kazemzadeh-2014-referitgame-referring-objects-photographs-natural/)
46. [**Learning Extraction Patterns for Subjective Expressions**Ellen Riloff, Janyce Wiebe*2003 · 1,217 citations*](https://md.research.elamur.ai/free/en/papers/riloff-2003-learning-extraction-patterns-subjective-expressions/)
47. [**Attention is not not Explanation**Sarah Wiegreffe, Yuval Pinter*2019 · 1,192 citations*](https://md.research.elamur.ai/free/en/papers/wiegreffe-2019-attention-is-not-not-explanation/)
48. [**Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems**Tsung-Hsien Wen, Milica Gašić, Nikola Mrkšić, et al.*2015 · 1,192 citations*](https://md.research.elamur.ai/free/en/papers/wen-2015-semantically-conditioned-lstm-based-natural/)
49. [**Aspect Level Sentiment Classification with Deep Memory Network**Duyu Tang, Bing Qin, Ting Liu*2016 · 1,187 citations*](https://md.research.elamur.ai/free/en/papers/tang-2016-aspect-level-sentiment-classification-deep/)
50. [**PubMedQA: A Dataset for Biomedical Research Question Answering**Qiao Jin, Bhuwan Dhingra, Zhengping Liu, et al.*2019 · 1,152 citations*](https://md.research.elamur.ai/free/en/papers/jin-2019-pubmedqa-dataset-biomedical-research-question/)
51. [**BERTweet: A pre-trained language model for English Tweets**Dat Quoc Nguyen, Thanh Vu, Anh Tuan Nguyen*2020 · 1,139 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2020-bertweet-pre-trained-language-model/)
52. [**WikiQA: A Challenge Dataset for Open-Domain Question Answering**Yi Yang, Wen-tau Yih, Christopher Meek*2015 · 1,117 citations*](https://md.research.elamur.ai/free/en/papers/yang-2015-wikiqa-challenge-dataset-open-domain/)
53. [**Recurrent Attention Network on Memory for Aspect Sentiment Analysis**Peng Chen, Zhongqian Sun, Lidong Bing, et al.*2017 · 1,113 citations*](https://md.research.elamur.ai/free/en/papers/chen-2017-recurrent-attention-network-memory-aspect/)
54. [**Generating Natural Language Adversarial Examples**Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, et al.*2018 · 1,102 citations*](https://md.research.elamur.ai/free/en/papers/alzantot-2018-generating-natural-language-adversarial-examples/)
55. [**Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling**Diego Marcheggiani, Ivan Titov*2017 · 1,101 citations*](https://md.research.elamur.ai/free/en/papers/marcheggiani-2017-encoding-sentences-graph-convolutional-networks/)
56. [**Improved Automatic Keyword Extraction Given More Linguistic Knowledge**Anette Hulth*2003 · 1,097 citations*](https://md.research.elamur.ai/free/en/papers/hulth-2003-improved-automatic-keyword-extraction-given/)
57. [**Enriching the Knowledge Sources Used in a Maximum Entropy Part-of-Speech Tagger**Kristina Toutanova, Christopher D. Manning*2000 · 1,082 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2000-enriching-knowledge-sources-used-maximum/)
58. [**Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking**Hannah Rashkin, Eunsol Choi, Jin Yea Jang, et al.*2017 · 1,072 citations*](https://md.research.elamur.ai/free/en/papers/rashkin-2017-truth-varying-shades-analyzing-language/)
59. [**QuAC: Question Answering in Context**Eunsol Choi, He He, Mohit Iyyer, et al.*2018 · 1,057 citations*](https://md.research.elamur.ai/free/en/papers/choi-2018-quac-question-answering-context/)
60. [**Graph Convolution over Pruned Dependency Trees Improves Relation Extraction**Yuhao Zhang, Peng Qi, Christopher D. Manning*2018 · 1,046 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-graph-convolution-over-pruned-dependency/)
61. [**Adversarial Learning for Neural Dialogue Generation**Jiwei Li, Will Monroe, Tianlin Shi, et al.*2017 · 1,044 citations*](https://md.research.elamur.ai/free/en/papers/li-2017-adversarial-learning-neural-dialogue-generation/)
62. [**Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints**Jieyu Zhao, Tianlu Wang, Mark Yatskar, et al.*2017 · 1,030 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2017-men-also-like-shopping-reducing/)
63. [**GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints**Joshua Ainslie, James Lee-Thorp, Michiel de Jong, et al.*2023 · 1,012 citations*](https://md.research.elamur.ai/free/en/papers/ainslie-2023-gqa-training-generalized-multi-query/)
64. [**The CoNLL 2007 Shared Task on Dependency Parsing**Joakim Nivre, Johan Hall, Sandra Kübler, et al.*2007 · 1,010 citations*](https://md.research.elamur.ai/free/en/papers/nivre-2007-conll-2007-shared-task-dependency/)
65. [**Unsupervised Models for Named Entity Classification**Michael Collins, Yoram Singer*1999 · 991 citations*](https://md.research.elamur.ai/free/en/papers/collins-1999-unsupervised-models-named-entity-classification/)
66. [**Evaluating Object Hallucination in Large Vision-Language Models**Yifan Li, Yifan Du, Kun Zhou, et al.*2023 · 986 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-evaluating-object-hallucination-large-vision/)
67. [**FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation**Sewon Min, Kalpesh Krishna, Xinxi Lyu, et al.*2023 · 970 citations*](https://md.research.elamur.ai/free/en/papers/min-2023-factscore-fine-grained-atomic-evaluation/)
68. [**Bottom-Up Abstractive Summarization**Sebastian Gehrmann, Yuntian Deng, Alexander Rush*2018 · 939 citations*](https://md.research.elamur.ai/free/en/papers/gehrmann-2018-bottom-up-abstractive-summarization/)
69. [**Multi-Task Identification of Entities, Relations, and Coreference for Scientific Knowledge Graph Construction**Yi Luan, Luheng He, Mari Ostendorf, et al.*2018 · 933 citations*](https://md.research.elamur.ai/free/en/papers/luan-2018-multi-task-identification-entities-relations/)
70. [**Rationalizing Neural Predictions**Tao Lei, Regina Barzilay, Tommi Jaakkola*2016 · 928 citations*](https://md.research.elamur.ai/free/en/papers/lei-2016-rationalizing-neural-predictions/)
71. [**Applying Conditional Random Fields to Japanese Morphological Analysis**Taku Kudo, Kaoru Yamamoto, Yuji Matsumoto*2004 · 909 citations*](https://md.research.elamur.ai/free/en/papers/kudo-2004-applying-conditional-random-fields-japanese/)
72. [**Representing Text for Joint Embedding of Text and Knowledge Bases**Kristina Toutanova, Danqi Chen, Patrick Pantel, et al.*2015 · 904 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2015-representing-text-joint-embedding-text/)
73. [**CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models**Nikita Nangia, Clara Vania, Rasika Bhalerao, et al.*2020 · 886 citations*](https://md.research.elamur.ai/free/en/papers/nangia-2020-crows-pairs-challenge-dataset-measuring/)
74. [**MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text**Matthew Richardson, Christopher J.C. Burges, Erin Renshaw*2013 · 873 citations*](https://md.research.elamur.ai/free/en/papers/richardson-2013-mctest-challenge-dataset-open-domain/)
75. [**TextAttack: A Framework for Adversarial Attacks, Data Augmentation, and Adversarial Training in NLP**John X. Morris, Eli Lifland, Jin Yong Yoo, et al.*2020 · 857 citations*](https://md.research.elamur.ai/free/en/papers/morris-2020-textattack-framework-adversarial-attacks-data/)
76. [**DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation**Deepanway Ghosal, Navonil Majumder, Soujanya Poria, et al.*2019 · 850 citations*](https://md.research.elamur.ai/free/en/papers/ghosal-2019-dialoguegcn-graph-convolutional-neural-network/)
77. [**Challenges in Data-to-Document Generation**Sam Wiseman, Stuart M. Shieber, Alexander M. Rush*2017 · 846 citations*](https://md.research.elamur.ai/free/en/papers/wiseman-2017-challenges-data-document-generation/)
78. [**BERT-ATTACK: Adversarial Attack Against BERT Using BERT**Linyang Li, Ruotian Ma, Qipeng Guo, et al.*2020 · 840 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-bert-attack-adversarial-attack-against/)
79. [**MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer**Jonas Pfeiffer, Ivan Vulić, Iryna Gurevych, et al.*2020 · 831 citations*](https://md.research.elamur.ai/free/en/papers/pfeiffer-2020-mad-x-adapter-based-framework/)
80. [**On the Sentence Embeddings from Pre-trained Language Models**Bohan Li, Hao Zhou, Junxian He, et al.*2020 · 830 citations*](https://md.research.elamur.ai/free/en/papers/li-2020-sentence-embeddings-pre-trained-language/)
81. [**Kernel Methods for Relation Extraction**Dmitry Zelenko, Chinatsu Aone, Anthony Richardella*2002 · 829 citations*](https://md.research.elamur.ai/free/en/papers/zelenko-2002-kernel-methods-relation-extraction/)
82. [**MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance**Wei Zhao, Maxime Peyrard, Fei Liu, et al.*2019 · 822 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2019-moverscore-text-generation-evaluating-contextualized/)
83. [**Is ChatGPT a General-Purpose Natural Language Processing Task Solver?**Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.*2023 · 818 citations*](https://md.research.elamur.ai/free/en/papers/qin-2023-chatgpt-general-purpose-natural-language/)
84. [**Entity, Relation, and Event Extraction with Contextualized Span Representations**David Wadden, Ulme Wennberg, Yi Luan, et al.*2019 · 818 citations*](https://md.research.elamur.ai/free/en/papers/wadden-2019-entity-relation-event-extraction-contextualized/)
85. [**Aspect-based Sentiment Classification with Aspect-specific Graph Convolutional Networks**Chen Zhang, Qiuchi Li, Dawei Song*2019 · 807 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-aspect-based-sentiment-classification-aspect/)
86. [**Semantic Parsing on Freebase from Question-Answer Pairs**Jonathan Berant, Andrew Chou, Roy Frostig, et al.*2013 · 785 citations*](https://md.research.elamur.ai/free/en/papers/berant-2013-semantic-parsing-freebase-question-answer/)
87. [**Supervised Learning of Universal Sentence Representations from Natural Language Inference Data**Alexis Conneau, Douwe Kiela, Holger Schwenk, et al.*2017 · 777 citations*](https://md.research.elamur.ai/free/en/papers/conneau-2017-supervised-learning-universal-sentence-representations/)
88. [**Domain Adaptation via Pseudo In-Domain Data Selection**Amittai Axelrod, Xiaodong He, Jianfeng Gao*2011 · 773 citations*](https://md.research.elamur.ai/free/en/papers/axelrod-2011-domain-adaptation-pseudo-domain-data/)
89. [**Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths**Yan Xu, Lili Mou, Ge Li, et al.*2015 · 769 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-classifying-relations-long-short-term/)
90. [**Rumor has it: Identifying Misinformation in Microblogs**Vahed Qazvinian, Emily Rosengren, Dragomir R. Radev, et al.*2011 · 764 citations*](https://md.research.elamur.ai/free/en/papers/qazvinian-2011-rumor-has-it-identifying-misinformation/)
91. [**Sarcasm as Contrast between a Positive Sentiment and Negative Situation**Ellen Riloff, Ashequl Qadir, Prafulla Surve, et al.*2013 · 752 citations*](https://md.research.elamur.ai/free/en/papers/riloff-2013-sarcasm-as-contrast-between-positive/)
92. [**The Woman Worked as a Babysitter: On Biases in Language Generation**Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, et al.*2019 · 751 citations*](https://md.research.elamur.ai/free/en/papers/sheng-2019-woman-worked-as-babysitter-biases/)
93. [**An Improved Non-monotonic Transition System for Dependency Parsing**Matthew Honnibal, Mark Johnson*2015 · 749 citations*](https://md.research.elamur.ai/free/en/papers/honnibal-2015-improved-non-monotonic-transition-system/)
94. [**AdapterHub: A Framework for Adapting Transformers**Jonas Pfeiffer, Andreas Rücklé, Clifton Poth, et al.*2020 · 747 citations*](https://md.research.elamur.ai/free/en/papers/pfeiffer-2020-adapterhub-framework-adapting-transformers/)
95. [**Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach**Wenpeng Yin, Jamaal Hay, Dan Roth*2019 · 731 citations*](https://md.research.elamur.ai/free/en/papers/yin-2019-benchmarking-zero-shot-text-classification/)
96. [**Fact or Fiction: Verifying Scientific Claims**David Wadden, Shanchuan Lin, Kyle Lo, et al.*2020 · 706 citations*](https://md.research.elamur.ai/free/en/papers/wadden-2020-fact-or-fiction-verifying-scientific/)
97. [**Large Language Models in Machine Translation**Thorsten Brants, Ashok C. Popat, Peng Xu, et al.*2007 · 701 citations*](https://md.research.elamur.ai/free/en/papers/brants-2007-large-language-models-machine-translation/)
98. [**Factored Translation Models**Philipp Koehn, Hieu Hoang*2007 · 699 citations*](https://md.research.elamur.ai/free/en/papers/koehn-2007-factored-translation-models/)
99. [**Neural Text Generation from Structured Data with Application to the Biography Domain**Remi Lebret, David Grangier, Michael Auli*2016 · 696 citations*](https://md.research.elamur.ai/free/en/papers/lebret-2016-neural-text-generation-structured-data/)
100. [**Modeling Relation Paths for Representation Learning of Knowledge Bases**Yankai Lin, Zhiyuan Liu, Huanbo Luan, et al.*2015 · 695 citations*](https://md.research.elamur.ai/free/en/papers/lin-2015-modeling-relation-paths-representation-learning/)

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