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Who cites Michael Zhang

1,166 citations of their works from 1,156 papers of our library (of the 141,840 whose bibliographies we read) · 133 with a page here, the most cited first · page 1 of 2 · 1–100 · ← Michael Zhang

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  1. GPT-4 Technical ReportarXiv:2303.08774OpenAI, Josh Achiam, Steven Adler, et al.2023 · 12,732 citations
  2. Training language models to follow instructions with human feedbackarXiv:2203.02155Long Ouyang, Jeff Wu, Xu Jiang, et al.2022 · 10,005 citations
  3. PaLM: Scaling Language Modeling with PathwaysarXiv:2204.02311Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.2022 · 4,680 citations
    Large Language Models Encode Clinical KnowledgeNatureKaran Singhal, Shekoofeh Azizi, Tao Tu, et al.2022 · 4,477 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
  4. Scaling Instruction-Finetuned Language ModelsarXiv:2210.11416Hyung Won Chung, Le Hou, Shayne Longpre, et al.2022 · 3,339 citations
    A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,222 citations
  5. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,229 citations
    TruthfulQA: Measuring How Models Mimic Human FalsehoodsAnnual Meeting of the Association for Computational Linguistics (ACL)Stephanie Lin, Jacob Hilton, Owain Evans2022 · 2,052 citations
  6. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,720 citations
  7. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,703 citations
  8. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,645 citations
  9. Multitask Prompted Training Enables Zero-Shot Task GeneralizationarXiv:2110.08207Victor Sanh, Albert Webson, Colin Raffel, et al.2021 · 1,581 citations
  10. DINOv2: Learning Robust Visual Features without SupervisionarXiv:2304.07193Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.2023 · 1,426 citations
    The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,264 citations
    Bias and Fairness in Large Language Models: A SurveyComputational LinguisticsIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,074 citations
  11. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 959 citations
  12. A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPTarXiv:2302.11382Jules White, Quchen Fu, Sam Hays, et al.2023 · 902 citations
  13. Do As I Can, Not As I Say: Grounding Language in Robotic AffordancesarXiv:2204.01691Michael Ahn, Anthony Brohan, Noah Brown, et al.2022 · 876 citations
  14. Segment AnythingarXiv:2304.02643Alexander Kirillov, Eric Mintun, Nikhila Ravi, et al.2023 · 868 citations
  15. 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
  16. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 779 citations
    Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 778 citations
    Can Large Language Models Transform Computational Social Science?Computational LinguisticsCaleb Ziems, William Held, Omar Shaikh, et al.2023 · 777 citations
  17. Capabilities of GPT-4 on Medical Challenge ProblemsarXiv:2303.13375Harsha Nori, Nicholas King, Scott Mayer McKinney, et al.2023 · 711 citations
  18. Crosslingual Generalization through Multitask FinetuningarXiv:2211.01786Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.2022 · 695 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
    Jailbroken: How Does LLM Safety Training Fail?Conference on Neural Information Processing Systems (NeurIPS)Alexander Wei, Nika Haghtalab, Jacob Steinhardt2023 · 659 citations
  19. CoCa: Contrastive Captioners are Image-Text Foundation ModelsarXiv:2205.01917Jiahui Yu, Zirui Wang, Vijay Vasudevan, et al.2022 · 649 citations
  20. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 612 citations
  21. 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
  22. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 592 citations
  23. Few-shot Learning with Multilingual Language ModelsarXiv:2112.10668Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, et al.2021 · 497 citations
  24. GLaM: Efficient Scaling of Language Models with Mixture-of-ExpertsarXiv:2112.06905Nan Du, Yanping Huang, Andrew M. Dai, et al.2021 · 479 citations
  25. Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference timearXiv:2203.05482Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, et al.2022 · 476 citations
  26. 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
  27. MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual ContextsarXiv:2310.02255Pan Lu, Hritik Bansal, Tony Xia, et al.2023 · 441 citations
  28. Large Legal Fictions: Profiling Legal Hallucinations in Large Language ModelsarXiv:2401.01301 · Journal of Legal Analysis 16, no. 1 (2024): 64-93Matthew Dahl, Varun Magesh, Mirac Suzgun, et al.2024 · 432 citations
  29. Ethical and social risks of harm from Language ModelsarXiv:2112.04359Laura Weidinger, John Mellor, Maribeth Rauh, et al.2021 · 429 citations
    AlpacaFarm: A Simulation Framework for Methods that Learn from Human FeedbackConference on Neural Information Processing Systems (NeurIPS)Yann Dubois, Xuechen Li, Rohan Taori, et al.2023 · 424 citations
  30. Language Models as Zero-Shot Planners: Extracting Actionable Knowledge for Embodied AgentsarXiv:2201.07207Wenlong Huang, Pieter Abbeel, Deepak Pathak, et al.2022 · 422 citations
  31. FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPUarXiv:2303.06865Ying Sheng, Lianmin Zheng, Binhang Yuan, et al.2023 · 399 citations
  32. Enhancing Chat Language Models by Scaling High-quality Instructional ConversationsarXiv:2305.14233Ning Ding, Yulin Chen, Bokai Xu, et al.2023 · 383 citations
  33. LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language ModelsarXiv:2308.11462Neel Guha; Julian Nyarko; Daniel E. Ho; Christopher Re; Adam Chilton; Aditya Narayana; Alex Chohlas-Wood; Austin Peters; Brandon Waldon; Daniel N. Rockmore; Diego Zambrano; Dmitry Talisman; Enam Hoque; Faiz Surani; Frank Fagan; Galit Sarfaty; Gregory M. Dickinson; Haggai Porat; Jason Hegland; Jessica Wu; Joe Nudell; Joel Niklaus; John Nay; Jonathan H. Choi; Kevin Tobia; Margaret Hagan; Megan Ma; Michael Livermore; Nikon Rasumov-Rahe; Nils Holzenberger; Noam Kolt; Peter Henderson; Sean Rehaag; Sharad Goel; Shang Gao; Spencer Williams; Sunny Gandhi; Tom Zur; Varun Iyer;, Zehua Li2023 · 381 citations
    Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 378 citations
    Mind2Web: Towards a Generalist Agent for the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Deng, Yu Gu, Boyuan Zheng, et al.2023 · 376 citations
  34. A Survey on Large Language Models for Code GenerationarXiv:2406.00515Juyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 366 citations
  35. Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated FeedbackarXiv:2302.12813Baolin Peng, Michel Galley, Pengcheng He, et al.2023 · 354 citations
  36. Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To!arXiv:2310.03693Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.2023 · 331 citations
  37. MEDITRON-70B: Scaling Medical Pretraining for Large Language ModelsarXiv:2311.16079Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.2023 · 311 citations
  38. Hallucination is Inevitable: An Innate Limitation of Large Language ModelsarXiv:2401.11817Ziwei Xu, Sanjay Jain, Mohan Kankanhalli2024 · 309 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
    Character-LLM: A Trainable Agent for Role-PlayingConference on Empirical Methods in Natural Language Processing (EMNLP)Yunfan Shao, Linyang Li, Junqi Dai, et al.2023 · 300 citations
    Challenges and Strategies in Cross-Cultural NLPAnnual Meeting of the Association for Computational Linguistics (ACL)Daniel Hershcovich, Stella Frank, Heather Lent, et al.2022 · 290 citations
  39. Socratic Models: Composing Zero-Shot Multimodal Reasoning with LanguagearXiv:2204.00598Andy Zeng, Maria Attarian, Brian Ichter, et al.2022 · 287 citations
  40. Hallucination-Free? Assessing the Reliability of Leading AI Legal Research ToolsarXiv:2405.20362Varun Magesh, Faiz Surani, Matthew Dahl, et al.2024 · 267 citations
  41. Towards Measuring the Representation of Subjective Global Opinions in Language ModelsarXiv:2306.16388Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.2023 · 262 citations
  42. DSPy: Compiling Declarative Language Model Calls into Self-Improving PipelinesarXiv:2310.03714Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.2023 · 261 citations
  43. LexGLUE: A Benchmark Dataset for Legal Language Understanding in EnglisharXiv:2110.00976Ilias Chalkidis; Abhik Jana; Dirk Hartung; Michael Bommarito; Ion Androutsopoulos; Daniel Martin Katz;, Nikolaos Aletras2021 · 254 citations
  44. The Curse of Recursion: Training on Generated Data Makes Models ForgetarXiv:2305.17493Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, et al.2023 · 250 citations
    Tree of Attacks: Jailbreaking Black-Box LLMs AutomaticallyConference on Neural Information Processing Systems (NeurIPS)Anay Mehrotra, Manolis Zampetakis, Paul Kassianik, et al.2023 · 245 citations
    Trusting Your Evidence: Hallucinate Less with Context-aware DecodingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Weijia Shi, Xiaochuang Han, Mike Lewis, et al.2024 · 240 citations
  45. RAFT: Reward rAnked FineTuning for Generative Foundation Model AlignmentarXiv:2304.06767Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.2023 · 239 citations
  46. BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagearXiv:2208.03188Kurt Shuster, Jing Xu, Mojtaba Komeili, et al.2022 · 237 citations
  47. A Survey of Hallucination in Large Foundation ModelsarXiv:2309.05922Vipula Rawte, Amit Sheth, Amitava Das2023 · 222 citations
  48. Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt InjectionarXiv:2302.12173Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, et al.2023 · 220 citations
    Beyond neural scaling laws: beating power law scaling via data pruningConference on Neural Information Processing Systems (NeurIPS)Ben Sorscher, Robert Geirhos, Shashank Shekhar, et al.2022 · 220 citations
  49. Self-critiquing models for assisting human evaluatorsarXiv:2206.05802William Saunders, Catherine Yeh, Jeff Wu, et al.2022 · 220 citations
    MADLAD-400: A Multilingual And Document-Level Large Audited DatasetConference on Neural Information Processing Systems (NeurIPS)Sneha Kudugunta, Isaac Caswell, Biao Zhang, et al.2023 · 211 citations
    Towards Faithful Model Explanation in NLP: A SurveyComputational LinguisticsQing Lyu, Marianna Apidianaki, Chris Callison-Burch2024 · 195 citations
  50. Making Retrieval-Augmented Language Models Robust to Irrelevant ContextarXiv:2310.01558Ori Yoran, Tomer Wolfson, Ori Ram, et al.2023 · 193 citations
  51. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 187 citations
  52. SGPT: GPT Sentence Embeddings for Semantic SearcharXiv:2202.08904Niklas Muennighoff2022 · 187 citations
    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 · 180 citations
    Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 179 citations
    On the Risk of Misinformation Pollution with Large Language ModelsFindings of the Association for Computational LinguisticsYikang Pan, Liangming Pan, Wenhu Chen, et al.2023 · 177 citations
    RealTime QA: What's the Answer Right Now?Conference on Neural Information Processing Systems (NeurIPS)Jungo Kasai, Keisuke Sakaguchi, Yoichi Takahashi, et al.2022 · 176 citations
  53. KernelBench: Can LLMs Write Efficient GPU Kernels?arXiv:2502.10517Anne Ouyang, Simon Guo, Simran Arora, et al.2025 · 170 citations
  54. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 170 citations
  55. Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge ConflictsarXiv:2305.13300Jian Xie, Kai Zhang, Jiangjie Chen, et al.2023 · 165 citations
  56. GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via CipherarXiv:2308.06463Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.2023 · 158 citations
  57. Leveraging Large Language Models for Multiple Choice Question AnsweringarXiv:2210.12353Joshua Robinson, Christopher Michael Rytting, David Wingate2022 · 157 citations
    Large Language Models Effectively Leverage Document-level Context for Literary Translation, but Critical Errors PersistConference on Machine Translation (WMT)Marzena Karpinska, Mohit Iyyer2023 · 156 citations
    Large Language Models with Controllable Working MemoryFindings of the Association for Computational LinguisticsDaliang Li, Ankit Singh Rawat, Manzil Zaheer, et al.2023 · 155 citations
    Draft & Verify: Lossless Large Language Model Acceleration via Self-Speculative DecodingAnnual Meeting of the Association for Computational Linguistics (ACL)Jun Zhang, Jue Wang, Huan Li, et al.2024 · 146 citations
  58. MiniLLM: On-Policy Distillation of Large Language ModelsarXiv:2306.08543Yuxian Gu, Li Dong, Furu Wei, et al.2023 · 143 citations
  59. DeepInception: Hypnotize Large Language Model to Be JailbreakerarXiv:2311.03191Xuan Li, Zhanke Zhou, Jianing Zhu, et al.2023 · 138 citations
  60. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 135 citations
  61. Secrets of RLHF in Large Language Models Part I: PPOarXiv:2307.04964Rui Zheng, Shihan Dou, Songyang Gao, et al.2023 · 130 citations
  62. InternVideo: General Video Foundation Models via Generative and Discriminative LearningarXiv:2212.03191Yi Wang, Kunchang Li, Yizhuo Li, et al.2022 · 128 citations
    InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context MemoryConference on Neural Information Processing Systems (NeurIPS)Chaojun Xiao, Pengle Zhang, Xu Han, et al.2024 · 125 citations
  63. Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow InstructionsarXiv:2309.07875Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al.2023 · 124 citations
  64. Fine-tuning Language Models for FactualityarXiv:2311.08401Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.2023 · 120 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
  65. Inverse Scaling: When Bigger Isn't BetterarXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQFIan R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.2023 · 99 citations
  66. Language Modeling Is CompressionarXiv:2309.10668Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne, et al.2023 · 89 citations
  67. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 88 citations
    SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural ReasoningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bin Wang, Zhengyuan Liu, Xin Huang, et al.2024 · 85 citations
  68. Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOMarXiv:2303.01911Rachel Bawden, François Yvon2023 · 85 citations
    How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 84 citations

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