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659 papers of our library cite it (of the 149,439 whose bibliographies we read) · 152 with a page here, the most cited first · page 1 of 2 · 1–100 · ← back to «Adversarial NLI: A New Benchmark for Natural Language Understanding»

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  1. Language Models are Few-Shot LearnersarXiv:2005.14165Tom B. Brown, Benjamin Mann, Nick Ryder, et al.2020 · 14,178 citations
  2. PaLM: Scaling Language Modeling with PathwaysarXiv:2204.02311Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.2022 · 4,753 citations
  3. SimCSE: Simple Contrastive Learning of Sentence EmbeddingsConference on Empirical Methods in Natural Language Processing (EMNLP)Tianyu Gao, Xingcheng Yao, Danqi Chen2021 · 3,942 citations
  4. A Survey on Evaluation of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyYupeng Chang, Xu Wang, Jindong Wang, et al.2023 · 3,648 citations
  5. Self-Consistency Improves Chain of Thought Reasoning in Language ModelsarXiv:2203.11171Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.2022 · 3,121 citations
  6. Finetuned Language Models Are Zero-Shot LearnersarXiv:2109.01652Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.2021 · 1,954 citations
  7. Multitask Prompted Training Enables Zero-Shot Task GeneralizationarXiv:2110.08207Victor Sanh, Albert Webson, Colin Raffel, et al.2021 · 1,612 citations
  8. Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A SurveyACM Computing SurveysBonan Min, Hayley Ross, Elior Sulem, et al.2021 · 1,556 citations
  9. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
  10. Phi-3 Technical Report: A Highly Capable Language Model Locally on Your PhonearXiv:2404.14219Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.2024 · 1,134 citations
  11. PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 1,000 citations
  12. Are NLP Models really able to Solve Simple Math Word Problems?Arkil Patel, Satwik Bhattamishra, Navin Goyal2021 · 890 citations
  13. GPT-NeoX-20B: An Open-Source Autoregressive Language ModelBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsSidney Black, Stella Biderman, Eric Hallahan, et al.2022 · 831 citations
  14. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and BeyondACM Transactions on Knowledge Discovery from DataJingfeng Yang, Hongye Jin, Ruixiang Tang, et al.2023 · 814 citations
  15. Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Haokun Liu, Derek Tam, Mohammed Muqeeth, et al.2022 · 754 citations
  16. Red Teaming Language Models with Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Ethan Perez, Saffron Huang, Francis Song, et al.2022 · 700 citations
  17. Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model SizesFindings of the Association for Computational LinguisticsCheng-Yu Hsieh, Chun-Liang Li, Chih-kuan Yeh, et al.2023 · 690 citations
  18. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 618 citations
  19. Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language ModelarXiv:2201.11990Shaden Smith, Mostofa Patwary, Brandon Norick, et al.2022 · 615 citations
  20. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 607 citations
  21. Large Language Models Can Self-ImproveConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Huang, Shixiang Gu, Le Hou, et al.2023 · 575 citations
  22. Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Armen Aghajanyan, Sonal Gupta, Luke Zettlemoyer2021 · 542 citations
  23. Evaluating Models' Local Decision Boundaries via Contrast SetsMatt Gardner, Yoav Artzi, Victoria Basmov, et al.2020 · 531 citations
  24. Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons LearnedarXiv:2209.07858Deep Ganguli, Liane Lovitt, Jackson Kernion, et al.2022 · 485 citations
  25. oLMpics — On what Language Model Pre-training CapturesTransactions of the Association for Computational Linguistics (TACL)Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.2019 · 440 citations
  26. Do Prompt-Based Models Really Understand the Meaning of Their Prompts?Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Albert Webson, Ellie Pavlick2022 · 407 citations
  27. Unnatural Instructions: Tuning Language Models with (Almost) No Human LaborAnnual Meeting of the Association for Computational Linguistics (ACL)Or Honovich, Thomas Scialom, Omer Levy, et al.2023 · 366 citations
  28. UL2: Unifying Language Learning ParadigmsarXiv:2205.05131Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.2022 · 347 citations
  29. The Next Decade in AI: Four Steps Towards Robust Artificial IntelligencearXiv:2002.06177Gary Marcus2020 · 332 citations
  30. Discovering Language Model Behaviors with Model-Written EvaluationsarXiv:2212.09251Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.2022 · 328 citations
  31. Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate DetectionAnnual Meeting of the Association for Computational Linguistics (ACL)Bertie Vidgen, Tristan Thrush, Zeerak Waseem, et al.2021 · 325 citations
  32. TIES-Merging: Resolving Interference When Merging ModelsConference on Neural Information Processing Systems (NeurIPS)Prateek Yadav, Derek Tam, Leshem Choshen, et al.2023 · 324 citations
  33. WANLI: Worker and AI Collaboration for Natural Language Inference Dataset CreationarXiv:2201.05955Alisa Liu, Swabha Swayamdipta, Noah A. Smith, et al.2022 · 317 citations
  34. Muppet: Massive Multi-task Representations with Pre-FinetuningConference on Empirical Methods in Natural Language Processing (EMNLP)Armen Aghajanyan, Anchit Gupta, Akshat Shrivastava, et al.2021 · 307 citations
  35. SPoT: Better Frozen Model Adaptation through Soft Prompt TransferAnnual Meeting of the Association for Computational Linguistics (ACL)Tu Vu, Brian Lester, Noah Constant, et al.2022 · 306 citations
  36. PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial PromptsarXiv:2306.04528Kaijie Zhu, Jindong Wang, Jiaheng Zhou, et al.2023 · 305 citations
  37. SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Haoming Jiang, Pengcheng He, Weizhu Chen, et al.2020 · 304 citations
  38. QAFactEval: Improved QA-Based Factual Consistency Evaluation for SummarizationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, et al.2022 · 292 citations
  39. Get Your Vitamin C! Robust Fact Verification with Contrastive EvidenceConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Tal Schuster, Adam Fisch, Regina Barzilay2021 · 290 citations
  40. AlignScore: Evaluating Factual Consistency with A Unified Alignment FunctionAnnual Meeting of the Association for Computational Linguistics (ACL)Yuheng Zha, Yichi Yang, Ruichen Li, et al.2023 · 284 citations
  41. TRUE: Re-evaluating Factual Consistency EvaluationConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Or Honovich, Roee Aharoni, Jonathan Herzig, et al.2022 · 279 citations
  42. How Can We Accelerate Progress Towards Human-like Linguistic Generalization?Annual Meeting of the Association for Computational Linguistics (ACL)Tal Linzen2020 · 263 citations
  43. RedPajama: an Open Dataset for Training Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Maurice Weber, Daniel Fu, Quentin Anthony, et al.2024 · 260 citations
  44. DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT ModelsConference on Neural Information Processing Systems (NeurIPS)Boxin Wang, Weixin Chen, Hengzhi Pei, et al.2023 · 259 citations
  45. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
  46. Syntactic Data Augmentation Increases Robustness to Inference HeuristicsAnnual Meeting of the Association for Computational Linguistics (ACL)Junghyun Min, R. Thomas McCoy, Dipanjan Das, et al.2020 · 220 citations
  47. “Kelly is a Warm Person, Joseph is a Role Model”: Gender Biases in LLM-Generated Reference LettersFindings of the Association for Computational LinguisticsYixin Wan, George Pu, Jiao Sun, et al.2023 · 208 citations
  48. HateCheck: Functional Tests for Hate Speech Detection ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Paul Röttger, Bertie Vidgen, Dong Nguyen, et al.2021 · 204 citations
  49. Recipes for Safety in Open-domain ChatbotsarXiv:2010.07079Jing Xu, Da Ju, Margaret Li, et al.2020 · 201 citations
  50. A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark DatasetsFindings of the Association for Computational LinguisticsMd Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.2023 · 200 citations
  51. What Can We Learn from Collective Human Opinions on Natural Language Inference Data?Conference on Empirical Methods in Natural Language Processing (EMNLP)Yixin Nie, Xiang Zhou, Mohit Bansal2020 · 196 citations
  52. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
  53. Translation Artifacts in Cross-lingual Transfer LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Mikel Artetxe, Gorka Labaka, Eneko Agirre2020 · 176 citations
  54. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 172 citations
  55. QuALITY: Question Answering with Long Input Texts, Yes!Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Richard Yuanzhe Pang, Alicia Parrish, Nitish Joshi, et al.2022 · 167 citations
  56. MiniCheck: Efficient Fact-Checking of LLMs on Grounding DocumentsConference on Empirical Methods in Natural Language Processing (EMNLP)Liyan Tang, Philippe Laban, Greg Durrett2024 · 166 citations
  57. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
  58. ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Justin Chen, Swarnadeep Saha, Mohit Bansal2024 · 156 citations
  59. INFOTABS: Inference on Tables as Semi-structured DataAnnual Meeting of the Association for Computational Linguistics (ACL)Vivek Gupta, Maitrey Mehta, Pegah Nokhiz, et al.2020 · 150 citations
  60. Measure and Improve Robustness in NLP Models: A SurveyConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Xuezhi Wang, Haohan Wang, Diyi Yang2022 · 148 citations
  61. Out of Order: How important is the sequential order of words in a sentence in Natural Language Understanding tasks?Findings of the Association for Computational LinguisticsThang Pham, Trung Bui, Long Mai, et al.2021 · 148 citations
  62. OCNLI: Original Chinese Natural Language InferencearXiv:2010.05444Hai Hu, Kyle Richardson, Liang Xu, et al.2020 · 148 citations
  63. A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Tianyu Liu, Yizhe Zhang, Chris Brockett, et al.2022 · 142 citations
  64. Bot-Adversarial Dialogue for Safe Conversational AgentsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jing Xu, Da Ju, Margaret Li, et al.2021 · 141 citations
  65. UnNatural Language InferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, et al.2021 · 135 citations
  66. What to Pre-Train on? Efficient Intermediate Task SelectionConference on Empirical Methods in Natural Language Processing (EMNLP)Clifton Poth, Jonas Pfeiffer, Andreas Rücklé, et al.2021 · 132 citations
  67. Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and NegationAtticus Geiger, Kyle Richardson, Christopher Potts2020 · 123 citations
  68. DocNLI: A Large-scale Dataset for Document-level Natural Language InferenceFindings of the Association for Computational LinguisticsWenpeng Yin, Dragomir Radev, Caiming Xiong2021 · 121 citations
  69. Testing the Ability of Language Models to Interpret Figurative LanguageConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Emmy Liu, Chenxuan Cui, Kenneth Zheng, et al.2022 · 114 citations
  70. WiCE: Real-World Entailment for Claims in WikipediaConference on Empirical Methods in Natural Language Processing (EMNLP)Ryo Kamoi, Tanya Goyal, Juan Diego Rodriguez, et al.2023 · 113 citations
  71. GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLPConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tawkat Islam Khondaker, Abdul Waheed, El Moatez Billah Nagoudi, et al.2023 · 110 citations
  72. TrueTeacher: Learning Factual Consistency Evaluation with Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Zorik Gekhman, Jonathan Herzig, Roee Aharoni, et al.2023 · 106 citations
  73. I like fish, especially dolphins: Addressing Contradictions in Dialogue ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Yixin Nie, Mary Williamson, Mohit Bansal, et al.2021 · 101 citations
  74. Mapping global dynamics of benchmark creation and saturation in artificial intelligenceNature CommunicationsSimon Ott, Adriano Barbosa-Silva, Kathrin Blagec, et al.2022 · 93 citations
  75. Conditional Generation with a Question-Answering BlueprintTransactions of the Association for Computational Linguistics (TACL)Shashi Narayan, Joshua Maynez, Reinald Kim Amplayo, et al.2023 · 70 citations
  76. Factually Consistent Summarization via Reinforcement Learning with Textual Entailment FeedbackAnnual Meeting of the Association for Computational Linguistics (ACL)Paul Roit, Johan Ferret, Lior Shani, et al.2023 · 70 citations
  77. English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer TooConference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)Jason Phang, Iacer Calixto, Phu Mon Htut, et al.2020 · 70 citations
  78. Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction TuningarXiv:2309.05444Ted Zadouri, Ahmet Ustun, Arash Ahmadian, et al.2023 · 69 citations
  79. VALUE: Understanding Dialect Disparity in NLUCaleb Ziems, Jiaao Chen, Camille Harris, et al.2022 · 67 citations
  80. Evaluation of OpenAI o1: Opportunities and Challenges of AGIarXiv:2409.18486Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.2024 · 64 citations
  81. Exploring the Benefits of Training Expert Language Models over Instruction TuningarXiv:2302.03202Joel Jang, Seungone Kim, Seonghyeon Ye, et al.2023 · 63 citations
  82. Shepherd: A Critic for Language Model GenerationarXiv:2308.04592Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, et al.2023 · 60 citations
  83. ConjNLI: Natural Language Inference Over Conjunctive SentencesConference on Empirical Methods in Natural Language Processing (EMNLP)Swarnadeep Saha, Yixin Nie, Mohit Bansal2020 · 51 citations
  84. Counterfactually-Augmented SNLI Training Data Does Not Yield Better Generalization Than Unaugmented DataWorkshop on Insights from Negative Results in NLPWilliam Huang, Haokun Liu, Samuel R. Bowman2020 · 51 citations
  85. ANLIzing the Adversarial Natural Language Inference DatasetSociety for Computation in Linguistics (SCiL)Adina Williams, Tristan Thrush, Douwe Kiela2022 · 48 citations
  86. On Memorization of Large Language Models in Logical ReasoningInternational Joint Conference on Natural Language Processing (IJCNLP)Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.2025 · 45 citations
  87. SciNLI: A Corpus for Natural Language Inference on Scientific TextAnnual Meeting of the Association for Computational Linguistics (ACL)Mobashir Sadat, Cornelia Caragea2022 · 43 citations
  88. Auxiliary task demands mask the capabilities of smaller language modelsarXiv:2404.02418Jennifer Hu, Michael C. Frank2024 · 41 citations
  89. A Systematic Survey of Automatic Prompt Optimization TechniquesConference on Empirical Methods in Natural Language Processing (EMNLP)Kiran Ramnath, Kang Zhou, Sheng Guan, et al.2025 · 40 citations
  90. NOPE: A Corpus of Naturally-Occurring Presuppositions in EnglishAlicia Parrish, Sebastian Schuster, Alex Warstadt, et al.2021 · 40 citations
  91. An Empirical Study on Model-agnostic Debiasing Strategies for Robust Natural Language InferenceConference on Computational Natural Language Learning (CoNLL)Tianyu Liu, Xin Zheng, Xiaoan Ding, et al.2020 · 37 citations
  92. Distributed NLI: Learning to Predict Human Opinion Distributions for Language ReasoningFindings of the Association for Computational LinguisticsXiang Zhou, Yixin Nie, Mohit Bansal2022 · 36 citations
  93. Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learningConference on Computational Natural Language Learning (CoNLL)Lucas Weber, Elia Bruni, Dieuwke Hupkes2023 · 29 citations
  94. HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language InferenceLanguage Resources and Evaluation Conference (LREC)Tianyu Liu, Xin Zheng, Baobao Chang, et al.2020 · 28 citations
  95. Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical Reasoning Capabilities of Language ModelsarXiv:2310.00836Man Luo, Shrinidhi Kumbhar, Ming shen, et al.2023 · 27 citations
  96. New Protocols and Negative Results for Textual Entailment Data CollectionConference on Empirical Methods in Natural Language Processing (EMNLP)Samuel R. Bowman, Jennimaria Palomaki, Livio Baldini Soares, et al.2020 · 27 citations
  97. Understanding Retrieval Augmentation for Long-Form Question AnsweringarXiv:2310.12150Hung-Ting Chen, Fangyuan Xu, Shane Arora, et al.2023 · 24 citations
  98. Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and modelsarXiv:2005.14709Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro2020 · 24 citations
  99. Compositionality and Sentence Meaning: Comparing Semantic Parsing and Transformers on a Challenging Sentence Similarity DatasetComputational LinguisticsJames Fodor, Simon De Deyne, Shinsuke Suzuki2025 · 22 citations
  100. Efficiently Adapting Pretrained Language Models To New LanguagesarXiv:2311.05741Zoltan Csaki, Pian Pawakapan, Urmish Thakker, et al.2023 · 21 citations

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