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Who cites Ryan Teehan

2,294 citations of their works from 2,175 papers of our library (of the 149,439 whose bibliographies we read) · 628 with a page here, the most cited first · page 1 of 7 · 1–100 · ← Ryan Teehan

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  1. Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsarXiv:2201.11903Jason Wei, Xuezhi Wang, Dale Schuurmans, et al.2022 · 11,499 citations
  2. Training language models to follow instructions with human feedbackarXiv:2203.02155Long Ouyang, Jeff Wu, Xu Jiang, et al.2022 · 10,224 citations
  3. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  4. PaLM: Scaling Language Modeling with PathwaysarXiv:2204.02311Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, et al.2022 · 4,753 citations
  5. Judging LLM-as-a-Judge with MT-Bench and Chatbot ArenaConference on Neural Information Processing Systems (NeurIPS)Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, et al.2023 · 4,573 citations
  6. Large language models are zero-shot reasonersConference on Neural Information Processing Systems (NeurIPS)Takeshi Kojima, Shixiang Shane Gu, Machel Reid, et al.2022 · 3,832 citations
  7. 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
  8. Gemini: A Family of Highly Capable Multimodal ModelsarXiv:2312.11805Gemini Team, Rohan Anil, Sebastian Borgeaud, et al.2023 · 3,050 citations
  9. QLoRA: Efficient Finetuning of Quantized LLMsConference on Neural Information Processing Systems (NeurIPS)Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, et al.2023 · 2,929 citations
  10. Direct Preference Optimization: Your Language Model is Secretly a Reward ModelarXiv:2305.18290Rafael Rafailov, Archit Sharma, Eric Mitchell, et al.2023 · 2,896 citations
  11. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
  12. Sparks of Artificial General Intelligence: Early experiments with GPT-4arXiv:2303.12712Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, et al.2023 · 2,439 citations
  13. Emergent Abilities of Large Language ModelsarXiv:2206.07682Jason Wei, Yi Tay, Rishi Bommasani, et al.2022 · 2,269 citations
  14. Flamingo: a Visual Language Model for Few-Shot LearningarXiv:2204.14198Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, et al.2022 · 2,246 citations
  15. Finetuned Language Models Are Zero-Shot LearnersarXiv:2109.01652Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.2021 · 1,954 citations
  16. 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 · 1,756 citations
  17. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
  18. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,669 citations
  19. Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextarXiv:2403.05530Gemini Team, Petko Georgiev, Ving Ian Lei, et al.2024 · 1,589 citations
  20. 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
  21. Unifying Large Language Models and Knowledge Graphs: A RoadmapIEEE Transactions on Knowledge and Data EngineeringShirui Pan, Linhao Luo, Yufei Wang, et al.2023 · 1,551 citations
  22. Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?Conference on Empirical Methods in Natural Language Processing (EMNLP)Sewon Min, Xinxi Lyu, Ari Holtzman, et al.2022 · 1,444 citations
  23. 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
  24. The Rise and Potential of Large Language Model Based Agents: A SurveyScience China Information SciencesZhiheng Xi, Wenxiang Chen, Xin Guo, et al.2023 · 1,272 citations
  25. 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
  26. Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve ThemFindings of the Association for Computational LinguisticsMirac Suzgun, Nathan Scales, Nathanael Schärli, et al.2023 · 1,119 citations
  27. InstructBLIP: Towards General-purpose Vision-Language Models with Instruction TuningarXiv:2305.06500Wenliang Dai, Junnan Li, Dongxu Li, et al.2023 · 1,100 citations
  28. MTEB: Massive Text Embedding BenchmarkConference of the European Chapter of the Association for Computational Linguistics (EACL)Niklas Muennighoff, Nouamane Tazi, Loïc Magne, et al.2022 · 1,032 citations
  29. Constitutional AI: Harmlessness from AI FeedbackarXiv:2212.08073Yuntao Bai, Saurav Kadavath, Sandipan Kundu, et al.2022 · 1,028 citations
  30. GPQA: A Graduate-Level Google-Proof Q&A BenchmarkarXiv:2311.12022David Rein, Betty Li Hou, Asa Cooper Stickland, et al.2023 · 1,018 citations
  31. PaLM 2 Technical ReportarXiv:2305.10403Rohan Anil, Andrew M. Dai, Orhan Firat, et al.2023 · 1,000 citations
  32. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
  33. C-Pack: Packed Resources For General Chinese EmbeddingsInternational ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)Shitao Xiao, Zheng Liu, Peitian Zhang, et al.2023 · 922 citations
  34. A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and InteractivityarXiv:2302.04023Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, et al.2023 · 882 citations
  35. ChatGPT: Jack of all trades, master of nonearXiv:2302.10724 · Information Fusion 101,861 (2023)Jan Kocon, Igor Cichecki, Oliwier Kaszyca, et al.2023 · 866 citations
  36. 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
  37. Is ChatGPT a General-Purpose Natural Language Processing Task Solver?Conference on Empirical Methods in Natural Language Processing (EMNLP)Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.2023 · 828 citations
  38. 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
  39. Can Large Language Models Transform Computational Social Science?Computational LinguisticsCaleb Ziems, William Held, Omar Shaikh, et al.2023 · 790 citations
  40. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 786 citations
  41. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 780 citations
  42. MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding BenchmarkConference on Neural Information Processing Systems (NeurIPS)Yubo Wang, Xueguang Ma, Ge Zhang, et al.2024 · 761 citations
  43. 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
  44. WizardLM: Empowering large pre-trained language models to follow complex instructionsInternational Conference on Learning Representations (ICLR)Can Xu, Qingfeng Sun, Kai Zheng, et al.2023 · 741 citations
  45. SWE-bench: Can Language Models Resolve Real-World GitHub Issues?arXiv:2310.06770Carlos E. Jimenez, John Yang, Alexander Wettig, et al.2024 · 704 citations
  46. Crosslingual Generalization through Multitask FinetuningarXiv:2211.01786Niklas Muennighoff, Thomas Wang, Lintang Sutawika, et al.2022 · 703 citations
  47. Large Language Models Are Human-Level Prompt EngineersarXiv:2211.01910Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, et al.2022 · 701 citations
  48. ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All ToolsarXiv:2406.12793Team GLM, Aohan Zeng, Bin Xu, et al.2024 · 691 citations
  49. Self-RAG: Learning to Retrieve, Generate, and Critique through Self-ReflectionarXiv:2310.11511Akari Asai, Zeqiu Wu, Yizhong Wang, et al.2023 · 677 citations
  50. Instruction Tuning with GPT-4arXiv:2304.03277Baolin Peng, Chunyuan Li, Pengcheng He, et al.2023 · 662 citations
  51. Encouraging Divergent Thinking in Large Language Models through Multi-Agent DebateConference on Empirical Methods in Natural Language Processing (EMNLP)Tian Liang, Zhiwei He, Wenxiang Jiao, et al.2023 · 651 citations
  52. BloombergGPT: A Large Language Model for FinancearXiv:2303.17564Shijie Wu, Ozan Irsoy, Steven Lu, et al.2023 · 618 citations
  53. Instruction-Following Evaluation for Large Language ModelsarXiv:2311.07911Jeffrey Zhou, Tianjian Lu, Swaroop Mishra, et al.2023 · 615 citations
  54. 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
  55. s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (EMNLP)Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.2025 · 608 citations
  56. The Flan Collection: Designing Data and Methods for Effective Instruction TuningarXiv:2301.13688Shayne Longpre, Le Hou, Tu Vu, et al.2023 · 607 citations
  57. Improving Factuality and Reasoning in Language Models through Multiagent DebatearXiv:2305.14325Yilun Du, Shuang Li, Antonio Torralba, et al.2023 · 587 citations
  58. Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought PromptingConference on Neural Information Processing Systems (NeurIPS)Miles Turpin, Julian Michael, Ethan Perez, et al.2023 · 586 citations
  59. 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
  60. Precise Zero-Shot Dense Retrieval without Relevance LabelsAnnual Meeting of the Association for Computational Linguistics (ACL)Luyu Gao, Xueguang Ma, Jimmy Lin, et al.2022 · 549 citations
  61. Chatbot Arena: An Open Platform for Evaluating LLMs by Human PreferencearXiv:2403.04132Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, et al.2024 · 546 citations
  62. Gorilla: Large Language Model Connected with Massive APIsConference on Neural Information Processing Systems (NeurIPS)Shishir G. Patil, Tianjun Zhang, Xin Wang, et al.2023 · 546 citations
  63. Unleashing the potential of prompt engineering for large language modelsarXiv:2310.14735 · Patterns 6(6) 101,260 (2025)Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.2023 · 536 citations
  64. Large Language Models Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
  65. TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with RecommendationarXiv:2305.00447Keqin Bao; Jizhi Zhang; Yang Zhang; Wenjie Wang; Fuli Feng;, Xiangnan He2023 · 531 citations
  66. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  67. Baichuan 2: Open Large-scale Language ModelsarXiv:2309.10305Aiyuan Yang, Bin Xiao, Bingning Wang, et al.2023 · 517 citations
  68. LongBench: A Bilingual, Multitask Benchmark for Long Context UnderstandingarXiv:2308.14508Yushi Bai, Xin Lv, Jiajie Zhang, et al.2023 · 514 citations
  69. Few-shot Learning with Multilingual Language ModelsarXiv:2112.10668Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, et al.2021 · 500 citations
  70. OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning FrameworkarXiv:2202.03052Peng Wang, An Yang, Rui Men, et al.2022 · 467 citations
  71. 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 · 456 citations
  72. Large language models are few-shot clinical information extractorsConference on Empirical Methods in Natural Language Processing (EMNLP)Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.2022 · 454 citations
  73. The Falcon Series of Open Language ModelsarXiv:2311.16867Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.2023 · 443 citations
  74. AgentBench: Evaluating LLMs as AgentsarXiv:2308.03688Xiao Liu, Hao Yu, Hanchen Zhang, et al.2023 · 432 citations
  75. C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation ModelsarXiv:2305.08322Yuzhen Huang, Yuzhuo Bai, Zhihao Zhu, et al.2023 · 428 citations
  76. Tulu 3: Pushing Frontiers in Open Language Model Post-TrainingarXiv:2411.15124Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.2024 · 423 citations
  77. Whose Opinions Do Language Models Reflect?arXiv:2303.17548Shibani Santurkar, Esin Durmus, Faisal Ladhak, et al.2023 · 414 citations
  78. Large Language Models as OptimizersarXiv:2309.03409Chengrun Yang, Xuezhi Wang, Yifeng Lu, et al.2023 · 413 citations
  79. Yi: Open Foundation Models by 01.AIarXiv:2403.04652Alex Young, Bei Chen, Chao Li, et al.2024 · 408 citations
  80. 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
  81. UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Tianbao Xie, Chen Henry Wu, Peng Shi, et al.2022 · 407 citations
  82. Enhancing Chat Language Models by Scaling High-quality Instructional ConversationsarXiv:2305.14233Ning Ding, Yulin Chen, Bokai Xu, et al.2023 · 402 citations
  83. Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
  84. 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 · 389 citations
  85. CMMLU: Measuring massive multitask language understanding in ChinesearXiv:2306.09212Haonan Li, Yixuan Zhang, Fajri Koto, et al.2023 · 387 citations
  86. Large Language Models are Few-Shot Clinical Information ExtractorsConference on Empirical Methods in Natural Language Processing (EMNLP)Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.2022 · 384 citations
  87. Tool Learning with Foundation ModelsACM Computing SurveysYujia Qin, Shengding Hu, Yankai Lin, et al.2023 · 383 citations
  88. A Survey on Model Compression for Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Xunyu Zhu, Jian Li, Yong Liu, et al.2024 · 381 citations
  89. Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical ReasoningarXiv:2305.12295Liangming Pan, Alon Albalak, Xinyi Wang, et al.2023 · 374 citations
  90. Augmented Language Models: a SurveyarXiv:2302.07842Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.2023 · 369 citations
  91. Orca: Progressive Learning from Complex Explanation Traces of GPT-4arXiv:2306.02707Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, et al.2023 · 369 citations
  92. A Survey on Large Language Models for Code GenerationACM Transactions on Software Engineering and MethodologyJuyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 367 citations
  93. 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
  94. BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference DatasetConference on Neural Information Processing Systems (NeurIPS)Jiaming Ji, Mickel Liu, Juntao Dai, et al.2023 · 362 citations
  95. ChatEval: Towards Better LLM-based Evaluators through Multi-Agent DebatearXiv:2308.07201Chi-Min Chan, Weize Chen, Yusheng Su, et al.2023 · 359 citations
  96. TinyLlama: An Open-Source Small Language ModelarXiv:2401.02385Peiyuan Zhang, Guangtao Zeng, Tianduo Wang, et al.2024 · 352 citations
  97. UL2: Unifying Language Learning ParadigmsarXiv:2205.05131Yi Tay, Mostafa Dehghani, Vinh Q. Tran, et al.2022 · 347 citations
  98. Are Emergent Abilities of Large Language Models a Mirage?Conference on Neural Information Processing Systems (NeurIPS)Rylan Schaeffer, Brando Miranda, Sanmi Koyejo2023 · 342 citations
  99. RLPrompt: Optimizing Discrete Text Prompts with Reinforcement LearningConference on Empirical Methods in Natural Language Processing (EMNLP)Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.2022 · 338 citations
  100. Empowering Biomedical Discovery with AI AgentsarXiv:2404.02831Shanghua Gao, Ada Fang, Yepeng Huang, et al.2024 · 333 citations

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