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Who cites Cyprien de Masson d'Autume

1,404 citations of their works from 1,364 papers of our library (of the 149,439 whose bibliographies we read) · 438 with a page here, the most cited first · page 2 of 5 · 101–200 · ← Cyprien de Masson d'Autume

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  1. Towards Measuring the Representation of Subjective Global Opinions in Language ModelsarXiv:2306.16388Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.2023 · 270 citations
  2. MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training StrategiesarXiv:2404.06395Shengding Hu, Yuge Tu, Xu Han, et al.2024 · 269 citations
  3. Predictability and Surprise in Large Generative ModelsACM Conference on Fairness, Accountability, and Transparency (FAccT)Deep Ganguli, Danny Hernandez, Liane Lovitt, et al.2022 · 268 citations
  4. 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
  5. Aya Model: An Instruction Finetuned Open-Access Multilingual Language ModelarXiv:2402.07827Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.2024 · 253 citations
  6. Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and ToxicityarXiv:2301.12867Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.2023 · 249 citations
  7. Can You Unpack That? Learning to Rewrite Questions-in-ContextConference on Empirical Methods in Natural Language Processing (EMNLP)Ahmed Elgohary, Denis Peskov, Jordan Boyd-Graber2019 · 245 citations
  8. LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation DatasetarXiv:2309.11998Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.2023 · 242 citations
  9. BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagearXiv:2208.03188Kurt Shuster, Jing Xu, Mojtaba Komeili, et al.2022 · 241 citations
  10. Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence LabelingConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaochuang Han, Jacob Eisenstein2019 · 241 citations
  11. MultiQA: An Empirical Investigation of Generalization and Transfer in Reading ComprehensionAnnual Meeting of the Association for Computational Linguistics (ACL)Alon Talmor, Jonathan Berant2019 · 236 citations
  12. Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical StudyACM International Conference on Web Search and Data Mining (WSDM)Yuan Sui, Mengyu Zhou, Mingjie Zhou, et al.2023 · 235 citations
  13. Reinforced Self-Training (ReST) for Language ModelingarXiv:2308.08998Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.2023 · 224 citations
  14. Self-planning Code Generation with Large Language ModelsACM Transactions on Software Engineering and MethodologyXue Jiang, Yihong Dong, Lecheng Wang, et al.2023 · 223 citations
  15. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
  16. PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about ChangeConference on Neural Information Processing Systems (NeurIPS)Karthik Valmeekam, Matthew Marquez, Alberto Olmo, et al.2022 · 222 citations
  17. 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
  18. What Happens To BERT Embeddings During Fine-tuning?BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLPAmil Merchant, Elahe Rahimtoroghi, Ellie Pavlick, et al.2020 · 220 citations
  19. Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language ModelsarXiv:2308.16149Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.2023 · 218 citations
  20. Teaching language models to support answers with verified quotesarXiv:2203.11147Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.2022 · 218 citations
  21. Prompting GPT-3 To Be ReliablearXiv:2210.09150Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.2022 · 210 citations
  22. CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLPConference on Empirical Methods in Natural Language Processing (EMNLP)Qinyuan Ye, Bill Yuchen Lin, Xiang Ren2021 · 210 citations
  23. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
  24. Active Example Selection for In-Context LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Yiming Zhang, Shi Feng, Chenhao Tan2022 · 209 citations
  25. Internet-augmented language models through few-shot prompting for open-domain question answeringarXiv:2203.05115Angeliki Lazaridou, Elena Gribovskaya, Wojciech Stokowiec, et al.2022 · 209 citations
  26. What Can Transformers Learn In-Context? A Case Study of Simple Function ClassesConference on Neural Information Processing Systems (NeurIPS)Shivam Garg, Dimitris Tsipras, Percy Liang, et al.2022 · 209 citations
  27. Autoformalization with Large Language ModelsarXiv:2205.12615Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.2022 · 204 citations
  28. AlphaEvolve: A coding agent for scientific and algorithmic discoveryarXiv:2506.13131Alexander Novikov, Ngân Vũ, Marvin Eisenberger, et al.2025 · 202 citations
  29. RRHF: Rank Responses to Align Language Models with Human Feedback without tearsarXiv:2304.05302Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 201 citations
  30. ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree SearchConference on Neural Information Processing Systems (NeurIPS)Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.2024 · 200 citations
  31. 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
  32. A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and ValidationArtificial Intelligence ReviewXiaowei Huang, Wenjie Ruan, Wei Huang, et al.2023 · 199 citations
  33. MiniGPT-v2: large language model as a unified interface for vision-language multi-task learningarXiv:2310.09478Jun Chen, Deyao Zhu, Xiaoqian Shen, et al.2023 · 199 citations
  34. Improving Passage Retrieval with Zero-Shot Question GenerationConference on Empirical Methods in Natural Language Processing (EMNLP)Devendra Sachan, Mike Lewis, Mandar Joshi, et al.2022 · 199 citations
  35. OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text DocumentsConference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.2023 · 197 citations
  36. Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP ResearchersarXiv:2409.04109Chenglei Si, Diyi Yang, Tatsunori Hashimoto2024 · 196 citations
  37. Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human FeedbackConference on Empirical Methods in Natural Language Processing (EMNLP)Viet Lai, Chien Nguyen, Nghia Ngo, et al.2023 · 195 citations
  38. RAPTOR: Recursive Abstractive Processing for Tree-Organized RetrievalarXiv:2401.18059Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.2024 · 193 citations
  39. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 191 citations
  40. Memorization Without Overfitting: Analyzing the Training Dynamics of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Kushal Tirumala, Aram H. Markosyan, Luke Zettlemoyer, et al.2022 · 190 citations
  41. SGPT: GPT Sentence Embeddings for Semantic SearcharXiv:2202.08904Niklas Muennighoff2022 · 189 citations
  42. VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Jing Yu Koh, Robert Lo, Lawrence Jang, et al.2024 · 184 citations
  43. Large Language Models are few(1)-shot Table ReasonersFindings of the Association for Computational LinguisticsWenhu Chen2023 · 182 citations
  44. CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 LanguagesLanguage Resources and Evaluation Conference (LREC)Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, et al.2023 · 181 citations
  45. KernelBench: Can LLMs Write Efficient GPU Kernels?arXiv:2502.10517Anne Ouyang, Simon Guo, Simran Arora, et al.2025 · 178 citations
  46. Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal ProofsarXiv:2210.12283Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.2022 · 178 citations
  47. What Artificial Neural Networks Can Tell Us About Human Language AcquisitionarXiv:2208.07998Alex Warstadt, Samuel R. Bowman2022 · 177 citations
  48. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
  49. BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex InstructionsarXiv:2406.15877Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, et al.2024 · 176 citations
  50. Do All Languages Cost the Same? Tokenization in the Era of Commercial Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.2023 · 174 citations
  51. Generative Representational Instruction TuningarXiv:2402.09906Niklas Muennighoff, Hongjin Su, Liang Wang, et al.2024 · 172 citations
  52. AudioPaLM: A Large Language Model That Can Speak and ListenarXiv:2306.12925Paul K. Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen, et al.2023 · 171 citations
  53. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 171 citations
  54. Quark: Controllable Text Generation with Reinforced UnlearningConference on Neural Information Processing Systems (NeurIPS)Ximing Lu, Sean Welleck, Jack Hessel, et al.2022 · 170 citations
  55. Factuality Enhanced Language Models for Open-Ended Text GenerationConference on Neural Information Processing Systems (NeurIPS)Nayeon Lee, Wei Ping, Peng Xu, et al.2022 · 168 citations
  56. SantaCoder: don't reach for the stars!arXiv:2301.03988Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al.2023 · 167 citations
  57. “I'm sorry to hear that”: Finding New Biases in Language Models with a Holistic Descriptor DatasetConference on Empirical Methods in Natural Language Processing (EMNLP)Eric Michael Smith, Melissa Hall, Melanie Kambadur, et al.2022 · 167 citations
  58. Long-form factuality in large language modelsConference on Neural Information Processing Systems (NeurIPS)Jerry Wei, Chengrun Yang, Xinying Song, et al.2024 · 165 citations
  59. Language models show human-like content effects on reasoning tasksarXiv:2207.07051Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, et al.2022 · 162 citations
  60. Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and OrderingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhiyong Wu, Yaoxiang Wang, Jiacheng Ye, et al.2022 · 159 citations
  61. Large Language Models with Controllable Working MemoryFindings of the Association for Computational LinguisticsDaliang Li, Ankit Singh Rawat, Manzil Zaheer, et al.2023 · 158 citations
  62. TheoremQA: A Theorem-driven Question Answering DatasetConference on Empirical Methods in Natural Language Processing (EMNLP)Wenhu Chen, Ming Yin, Max Ku, et al.2023 · 158 citations
  63. Are aligned neural networks adversarially aligned?Conference on Neural Information Processing Systems (NeurIPS)Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, et al.2023 · 157 citations
  64. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
  65. AnnoLLM: Making Large Language Models to Be Better Crowdsourced AnnotatorsarXiv:2303.16854Xingwei He, Zhenghao Lin, Yeyun Gong, et al.2023 · 152 citations
  66. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
  67. CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding ChallengesAnnual Meeting of the Association for Computational Linguistics (ACL)Kechi Zhang, Jia Li, Ge Li, et al.2024 · 150 citations
  68. The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual DatasetarXiv:2303.03915Hugo Laurençon, Lucile Saulnier, Thomas Wang, et al.2023 · 150 citations
  69. Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 149 citations
  70. Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
  71. GPT4Tools: Teaching Large Language Model to Use Tools via Self-instructionConference on Neural Information Processing Systems (NeurIPS)Rui Yang, Lin Song, Yanwei Li, et al.2023 · 147 citations
  72. Is GPT-3 a Good Data Annotator?arXiv:2212.10450Bosheng Ding, Chengwei Qin, Linlin Liu, et al.2022 · 147 citations
  73. Efficient Methods for Natural Language Processing: A SurveyTransactions of the Association for Computational Linguistics (TACL)Marcos Treviso, Ji-Ung Lee, Tianchu Ji, et al.2023 · 145 citations
  74. Efficient Training of Language Models to Fill in the MiddlearXiv:2207.14255Mohammad Bavarian, Heewoo Jun, Nikolas Tezak, et al.2022 · 144 citations
  75. Iteratively Prompt Pre-trained Language Models for Chain of ThoughtConference on Empirical Methods in Natural Language Processing (EMNLP)Boshi Wang, Xiang Deng, Huan Sun2022 · 144 citations
  76. A Stitch in Time Saves Nine: Detecting and Mitigating Hallucinations of LLMs by Validating Low-Confidence GenerationarXiv:2307.03987Neeraj Varshney; Wenlin Yao; Hongming Zhang; Jianshu Chen;, Dong Yu2023 · 143 citations
  77. Understanding the Effects of RLHF on LLM Generalisation and DiversityarXiv:2310.06452Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.2023 · 143 citations
  78. Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and FaithfulnessarXiv:2304.11633Bo Li, Gexiang Fang, Yang Yang, et al.2023 · 142 citations
  79. MLE-bench: Evaluating Machine Learning Agents on Machine Learning EngineeringarXiv:2410.07095Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, et al.2024 · 140 citations
  80. Attributed Question Answering: Evaluation and Modeling for Attributed Large Language ModelsarXiv:2212.08037Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.2022 · 138 citations
  81. Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology ViewAnnual Meeting of the Association for Computational Linguistics (ACL)Jintian Zhang, Xin Xu, Ningyu Zhang, et al.2024 · 134 citations
  82. Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal DatasetConference on Neural Information Processing Systems (NeurIPS)Peter Henderson, Mark S. Krass, Lucia Zheng, et al.2022 · 133 citations
  83. OpenWebMath: An Open Dataset of High-Quality Mathematical Web TextarXiv:2310.06786Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, et al.2023 · 132 citations
  84. 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
  85. Progressive-Hint Prompting Improves Reasoning in Large Language ModelsarXiv:2304.09797Chuanyang Zheng, Zhengying Liu, Enze Xie, et al.2023 · 131 citations
  86. A Survey on Recent Advances in LLM-Based Multi-turn Dialogue SystemsACM Computing SurveysZihao Yi, Jiarui Ouyang, Zhe Xu, et al.2024 · 130 citations
  87. Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Lei Li, Yuqi Wang, Runxin Xu, et al.2024 · 129 citations
  88. OpenCodeInterpreter: Integrating Code Generation with Execution and RefinementFindings of the Association for Computational LinguisticsTianyu Zheng, Ge Zhang, Tianhao Shen, et al.2024 · 129 citations
  89. LEVER: Learning to Verify Language-to-Code Generation with ExecutionarXiv:2302.08468Ansong Ni, Srini Iyer, Dragomir Radev, et al.2023 · 126 citations
  90. PEER: A Collaborative Language ModelarXiv:2208.11663Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, et al.2022 · 126 citations
  91. Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-steparXiv:2402.16906Li Zhong, Zilong Wang, Jingbo Shang2024 · 124 citations
  92. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  93. Unlearn What You Want to Forget: Efficient Unlearning for LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaao Chen, Diyi Yang2023 · 124 citations
  94. Emergent and Predictable Memorization in Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Stella Biderman, USVSN Sai Prashanth, Lintang Sutawika, et al.2023 · 123 citations
  95. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
  96. CRUXEval: A Benchmark for Code Reasoning, Understanding and ExecutionarXiv:2401.03065Alex Gu, Baptiste Rozière, Hugh Leather, et al.2024 · 122 citations
  97. Faithful Reasoning Using Large Language ModelsarXiv:2208.14271Antonia Creswell, Murray Shanahan2022 · 122 citations
  98. #InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language ModelsarXiv:2308.07074Keming Lu, Hongyi Yuan, Zheng Yuan, et al.2023 · 120 citations
  99. A Real-World WebAgent with Planning, Long Context Understanding, and Program SynthesisarXiv:2307.12856Izzeddin Gur, Hiroki Furuta, Austin Huang, et al.2023 · 120 citations
  100. Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations

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