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958 citations of their works from 888 papers of our library (of the 141,840 whose bibliographies we read) · 126 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Yixin Nie

Language Models are Few-Shot LearnersarXiv:2005.14165Tom B. Brown, Benjamin Mann, Nick Ryder, et al.2020 · 13,703 citations
Dense Passage Retrieval for Open-Domain Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Vladimir Karpukhin, Barlas Oguz, Sewon Min, et al.2020 · 5,375 citations
PaLM: Scaling Language Modeling with PathwaysarXiv:2204.02311Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.2022 · 4,680 citations
SimCSE: Simple Contrastive Learning of Sentence EmbeddingsConference on Empirical Methods in Natural Language Processing (EMNLP)Tianyu Gao, Xingcheng Yao, Danqi Chen2021 · 3,922 citations
A Survey on Evaluation of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyYupeng Chang, Xu Wang, Jindong Wang, et al.2023 · 3,641 citations
Self-Consistency Improves Chain of Thought Reasoning in Language ModelsarXiv:2203.11171Xuezhi Wang, Jason Wei, Dale Schuurmans, et al.2022 · 3,041 citations
Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language InferenceR. Thomas McCoy, Ellie Pavlick, Tal Linzen2019 · 1,635 citations
Multitask Prompted Training Enables Zero-Shot Task GeneralizationarXiv:2110.08207Victor Sanh, Albert Webson, Colin Raffel, et al.2021 · 1,581 citations
Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A SurveyACM Computing SurveysBonan Min, Hayley Ross, Elior Sulem, et al.2021 · 1,552 citations
A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,286 citations
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your PhonearXiv:2404.14219Marah Abdin, Jyoti Aneja, Hany Awadalla, et al.2024 · 1,113 citations
PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 977 citations
Are NLP Models really able to Solve Simple Math Word Problems?Arkil Patel, Satwik Bhattamishra, Navin Goyal2021 · 883 citations
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 · 821 citations
Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and BeyondarXiv:2304.13712Jingfeng Yang, Hongye Jin, Ruixiang Tang, et al.2023 · 811 citations
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 · 736 citations
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 · 685 citations
Red Teaming Language Models with Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Ethan Perez, Saffron Huang, Francis Song, et al.2022 · 666 citations
A Survey on Automated Fact-CheckingTransactions of the Association for Computational Linguistics (TACL)Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos2022 · 646 citations
BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 612 citations
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 · 602 citations
The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 592 citations
Large Language Models Can Self-ImproveConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Huang, Shixiang Gu, Le Hou, et al.2023 · 563 citations
Intrinsic Dimensionality Explains the Effectiveness of Language Model Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Armen Aghajanyan, Sonal Gupta, Luke Zettlemoyer2021 · 531 citations
Evaluating Models' Local Decision Boundaries via Contrast SetsMatt Gardner, Yoav Artzi, Victoria Basmov, et al.2020 · 522 citations
Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons LearnedarXiv:2209.07858Deep Ganguli, Liane Lovitt, Jackson Kernion, et al.2022 · 460 citations
oLMpics — On what Language Model Pre-training CapturesTransactions of the Association for Computational Linguistics (TACL)Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.2019 · 435 citations
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 · 398 citations
The “Problem” of Human Label Variation: On Ground Truth in Data, Modeling and EvaluationConference on Empirical Methods in Natural Language Processing (EMNLP)Barbara Plank2022 · 364 citations
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 · 358 citations
UL2: Unifying Language Learning ParadigmsarXiv:2205.05131Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.2022 · 335 citations
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 · 320 citations
WANLI: Worker and AI Collaboration for Natural Language Inference Dataset CreationarXiv:2201.05955Alisa Liu, Swabha Swayamdipta, Noah A. Smith, et al.2022 · 314 citations
TIES-Merging: Resolving Interference When Merging ModelsConference on Neural Information Processing Systems (NeurIPS)Prateek Yadav, Derek Tam, Leshem Choshen, et al.2023 · 308 citations
Discovering Language Model Behaviors with Model-Written EvaluationsarXiv:2212.09251Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.2022 · 307 citations
PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial PromptsarXiv:2306.04528Kaijie Zhu, Jindong Wang, Jiaheng Zhou, et al.2023 · 303 citations
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 · 302 citations
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 · 299 citations
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 · 295 citations
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 · 289 citations
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 · 288 citations
Fine-grained Fact Verification with Kernel Graph Attention NetworkAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenghao Liu, Chenyan Xiong, Maosong Sun, et al.2020 · 282 citations
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 · 280 citations
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 · 276 citations
Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question AnsweringarXiv:1911.10470Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, et al.2019 · 272 citations
HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Bernal Jimenez Gutierrez, Yiheng Shu, Yu Gu, et al.2024 · 264 citations
How Can We Accelerate Progress Towards Human-like Linguistic Generalization?Annual Meeting of the Association for Computational Linguistics (ACL)Tal Linzen2020 · 258 citations
RedPajama: an Open Dataset for Training Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Maurice Weber, Daniel Fu, Quentin Anthony, et al.2024 · 247 citations
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT ModelsConference on Neural Information Processing Systems (NeurIPS)Boxin Wang, Weixin Chen, Hengzhi Pei, et al.2023 · 246 citations
Hierarchical Graph Network for Multi-hop Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Yuwei Fang, Siqi Sun, Zhe Gan, et al.2020 · 241 citations
TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 226 citations
Coreferential Reasoning Learning for Language RepresentationConference on Empirical Methods in Natural Language Processing (EMNLP)Deming Ye, Yankai Lin, Jiaju Du, et al.2020 · 225 citations
HoVer: A Dataset for Many-Hop Fact Extraction And Claim VerificationFindings of the Association for Computational LinguisticsYichen Jiang, Shikha Bordia, Zheng Zhong, et al.2020 · 221 citations
Unsupervised Question Decomposition for Question AnsweringConference on Empirical Methods in Natural Language Processing (EMNLP)Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.2020 · 218 citations
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 · 217 citations
Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4arXiv:2304.03439Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, et al.2023 · 215 citations
“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 · 206 citations
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 · 203 citations
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
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 · 193 citations
Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 178 citations
Translation Artifacts in Cross-lingual Transfer LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Mikel Artetxe, Gorka Labaka, Eneko Agirre2020 · 175 citations
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 163 citations
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 · 162 citations
Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESuppositionPaloma Jeretic, Alex Warstadt, Suvrat Bhooshan, et al.2020 · 161 citations
MiniCheck: Efficient Fact-Checking of LLMs on Grounding DocumentsConference on Empirical Methods in Natural Language Processing (EMNLP)Liyan Tang, Philippe Laban, Greg Durrett2024 · 159 citations
Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
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 · 154 citations
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
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
OCNLI: Original Chinese Natural Language InferencearXiv:2010.05444Hai Hu, Kyle Richardson, Liang Xu, et al.2020 · 147 citations
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 · 145 citations
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 · 140 citations
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 · 139 citations
FaithDial: A Faithful Benchmark for Information-Seeking DialogueTransactions of the Association for Computational Linguistics (TACL)Nouha Dziri, Ehsan Kamalloo, Sivan Milton, et al.2022 · 138 citations
A fine-grained comparison of pragmatic language understanding in humans and language modelsJennifer Hu, Sammy Floyd, Olessia Jouravlev, et al.2023 · 136 citations
UnNatural Language InferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Koustuv Sinha, Prasanna Parthasarathi, Joelle Pineau, et al.2021 · 132 citations
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
DocNLI: A Large-scale Dataset for Document-level Natural Language InferenceFindings of the Association for Computational LinguisticsWenpeng Yin, Dragomir Radev, Caiming Xiong2021 · 121 citations
Neural Natural Language Inference Models Partially Embed Theories of Lexical Entailment and NegationAtticus Geiger, Kyle Richardson, Christopher Potts2020 · 112 citations
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 · 111 citations
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
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 · 109 citations
We're Afraid Language Models Aren't Modeling AmbiguityConference on Empirical Methods in Natural Language Processing (EMNLP)Alisa Liu, Zhaofeng Wu, Julian Michael, et al.2023 · 108 citations
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
Investigating Reasons for Disagreement in Natural Language InferenceTransactions of the Association for Computational Linguistics (TACL)Nan-Jiang Jiang, Marie-Catherine de Marneffe2022 · 104 citations
Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Mingkai Deng, Bowen Tan, Zhengzhong Liu, et al.2021 · 101 citations
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
DialFact: A Benchmark for Fact-Checking in DialogueAnnual Meeting of the Association for Computational Linguistics (ACL)Prakhar Gupta, Chien-Sheng Wu, Wenhao Liu, et al.2022 · 97 citations
Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language GenerationTransactions of the Association for Computational Linguistics (TACL)Patrick Fernandes, Aman Madaan, Emmy Liu, et al.2023 · 84 citations
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
Towards Robustifying NLI Models Against Lexical Dataset BiasesAnnual Meeting of the Association for Computational Linguistics (ACL)Xiang Zhou, Mohit Bansal2020 · 70 citations
IMPLI: Investigating NLI Models' Performance on Figurative LanguageKevin Stowe, Prasetya Utama, Iryna Gurevych2022 · 68 citations
Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction TuningarXiv:2309.05444Ted Zadouri, Ahmet Ustun, Arash Ahmadian, et al.2023 · 66 citations
VALUE: Understanding Dialect Disparity in NLUCaleb Ziems, Jiaao Chen, Camille Harris, et al.2022 · 65 citations
Culturally Aware Natural Language InferenceFindings of the Association for Computational LinguisticsJing Huang, Diyi Yang2023 · 61 citations
Shepherd: A Critic for Language Model GenerationarXiv:2308.04592Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, et al.2023 · 59 citations
Posing Fair Generalization Tasks for Natural Language InferenceConference on Empirical Methods in Natural Language Processing (EMNLP)Atticus Geiger, Ignacio Cases, Lauri Karttunen, et al.2019 · 58 citations
VariErr NLI: Separating Annotation Error from Human Label VariationAnnual Meeting of the Association for Computational Linguistics (ACL)Leon Weber-Genzel, Siyao Peng, Marie-Catherine De Marneffe, et al.2024 · 51 citations
ConjNLI: Natural Language Inference Over Conjunctive SentencesConference on Empirical Methods in Natural Language Processing (EMNLP)Swarnadeep Saha, Yixin Nie, Mohit Bansal2020 · 50 citations

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