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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 3 of 7 · 201–300 · ← Ryan Teehan

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  1. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 138 citations
  2. InFoBench: Evaluating Instruction Following Ability in Large Language ModelsFindings of the Association for Computational LinguisticsYiwei Qin, Kaiqiang Song, Yebowen Hu, et al.2024 · 136 citations
  3. SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and DialectsarXiv:2309.07445David Ifeoluwa Adelani, Hannah Liu, Xiaoyu Shen, et al.2023 · 136 citations
  4. 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 · 135 citations
  5. Self-Knowledge Guided Retrieval Augmentation for Large Language ModelsFindings of the Association for Computational LinguisticsYile Wang, Peng Li, Maosong Sun, et al.2023 · 135 citations
  6. 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
  7. Simple synthetic data reduces sycophancy in large language modelsarXiv:2308.03958Jerry Wei, Da Huang, Yifeng Lu, et al.2023 · 134 citations
  8. FLUTE: Figurative Language Understanding through Textual ExplanationsConference on Empirical Methods in Natural Language Processing (EMNLP)Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.2022 · 133 citations
  9. Task-aware Retrieval with InstructionsFindings of the Association for Computational LinguisticsAkari Asai, Timo Schick, Patrick Lewis, et al.2023 · 132 citations
  10. ZeroSCROLLS: A Zero-Shot Benchmark for Long Text UnderstandingFindings of the Association for Computational LinguisticsUri Shaham, Maor Ivgi, Avia Efrat, et al.2023 · 132 citations
  11. Progressive-Hint Prompting Improves Reasoning in Large Language ModelsarXiv:2304.09797Chuanyang Zheng, Zhengying Liu, Enze Xie, et al.2023 · 131 citations
  12. Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 130 citations
  13. Natural Language Reasoning, A SurveyACM Computing SurveysFei Yu, Hongbo Zhang, Prayag Tiwari, et al.2023 · 130 citations
  14. You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual SettingsBigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language ModelsZeerak Talat, Aurélie Névéol, Stella Biderman, et al.2022 · 130 citations
  15. Faithful Logical Reasoning via Symbolic Chain-of-ThoughtAnnual Meeting of the Association for Computational Linguistics (ACL)Jundong Xu, Hao Fei, Liangming Pan, et al.2024 · 129 citations
  16. MAGE: Machine-generated Text Detection in the WildAnnual Meeting of the Association for Computational Linguistics (ACL)Yafu Li, Qintong Li, Leyang Cui, et al.2024 · 129 citations
  17. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 129 citations
  18. Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataFindings of the Association for Computational LinguisticsKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
  19. Time Travel in LLMs: Tracing Data Contamination in Large Language ModelsarXiv:2308.08493Shahriar Golchin, Mihai Surdeanu2023 · 128 citations
  20. Chain of Hindsight Aligns Language Models with FeedbackarXiv:2302.02676Hao Liu, Carmelo Sferrazza, Pieter Abbeel2023 · 126 citations
  21. PEER: A Collaborative Language ModelarXiv:2208.11663Timo Schick, Jane Dwivedi-Yu, Zhengbao Jiang, et al.2022 · 126 citations
  22. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and FuturearXiv:2309.15402Zheng Chu, Jingchang Chen, Qianglong Chen, et al.2023 · 125 citations
  23. Can Language Models Solve Graph Problems in Natural Language?Conference on Neural Information Processing Systems (NeurIPS)Heng Wang, Shangbin Feng, Tianxing He, et al.2023 · 124 citations
  24. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  25. Unlearn What You Want to Forget: Efficient Unlearning for LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaao Chen, Diyi Yang2023 · 124 citations
  26. 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
  27. Large Language Models as Tool MakersarXiv:2305.17126Tianle Cai, Xuezhi Wang, Tengyu Ma, et al.2023 · 123 citations
  28. ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft PromptsConference on Empirical Methods in Natural Language Processing (EMNLP)Akari Asai, Mohammadreza Salehi, Matthew Peters, et al.2022 · 122 citations
  29. Pretraining Language Models with Human PreferencesarXiv:2302.08582Tomasz Korbak, Kejian Shi, Angelica Chen, et al.2023 · 121 citations
  30. Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language ModelsarXiv:2501.09686Fengli Xu, Qianyue Hao, Zefang Zong, et al.2025 · 120 citations
  31. UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity RecognitionarXiv:2308.03279Wenxuan Zhou, Sheng Zhang, Yu Gu, et al.2023 · 120 citations
  32. Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question AnsweringarXiv:2306.04136Jinheon Baek, Alham Fikri Aji, Amir Saffari2023 · 119 citations
  33. Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation ExtractorsFindings of the Association for Computational LinguisticsKai Zhang, Bernal Jimenez Gutierrez, Yu Su2023 · 118 citations
  34. The CoT Collection: Improving Zero-shot and Few-shot Learning of Language Models via Chain-of-Thought Fine-TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Seungone Kim, Se Joo, Doyoung Kim, et al.2023 · 118 citations
  35. A Critical Evaluation of Evaluations for Long-form Question AnsweringAnnual Meeting of the Association for Computational Linguistics (ACL)Fangyuan Xu, Yixiao Song, Mohit Iyyer, et al.2023 · 117 citations
  36. Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human EvaluationarXiv:2212.07981Yixin Liu, Alexander R. Fabbri, Pengfei Liu, et al.2022 · 117 citations
  37. Large Language Models Understand and Can be Enhanced by Emotional StimuliarXiv:2307.11760Cheng Li, Jindong Wang, Yixuan Zhang, et al.2023 · 116 citations
  38. LMMs-Eval: Reality Check on the Evaluation of Large Multimodal ModelsFindings of the Association for Computational LinguisticsKaichen Zhang, Bo Li, Peiyuan Zhang, et al.2025 · 115 citations
  39. PandaGPT: One Model To Instruction-Follow Them AllarXiv:2305.16355Yixuan Su, Tian Lan, Huayang Li, et al.2023 · 115 citations
  40. Ground-Truth Labels Matter: A Deeper Look into Input-Label DemonstrationsConference on Empirical Methods in Natural Language Processing (EMNLP)Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.2022 · 114 citations
  41. ALLaM: Large Language Models for Arabic and EnglisharXiv:2407.15390M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.2024 · 113 citations
  42. Don't Make Your LLM an Evaluation Benchmark CheaterarXiv:2311.01964Kun Zhou, Yutao Zhu, Zhipeng Chen, et al.2023 · 112 citations
  43. EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt OptimizersarXiv:2309.08532Qingyan Guo, Rui Wang, Junliang Guo, et al.2023 · 111 citations
  44. Reframing Human-AI Collaboration for Generating Free-Text ExplanationsarXiv:2112.08674Sarah Wiegreffe, Jack Hessel, Swabha Swayamdipta, et al.2021 · 111 citations
  45. Better Zero-Shot Reasoning with Role-Play PromptingarXiv:2308.07702Aobo Kong, Shiwan Zhao, Hao Chen, et al.2023 · 110 citations
  46. Evaluating the Performance of Large Language Models on GAOKAO BenchmarkarXiv:2305.12474Xiaotian Zhang, Chunyang Li, Yi Zong, et al.2023 · 109 citations
  47. LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA CompositionarXiv:2307.13269Chengsong Huang, Qian Liu, Bill Yuchen Lin, et al.2023 · 108 citations
  48. Multi-Step Reasoning with Large Language Models, a SurveyACM Computing SurveysAske Plaat, Annie Wong, Suzan Verberne, et al.2024 · 106 citations
  49. Arcee's MergeKit: A Toolkit for Merging Large Language ModelsarXiv:2403.13257Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, et al.2024 · 105 citations
  50. WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the WildarXiv:2406.04770Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, et al.2024 · 105 citations
  51. 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 · 105 citations
  52. LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale InstructionsarXiv:2304.14402Minghao Wu, Abdul Waheed, Chiyu Zhang, et al.2023 · 105 citations
  53. Zero-Shot Listwise Document Reranking with a Large Language ModelarXiv:2305.02156Xueguang Ma, Xinyu Zhang, Ronak Pradeep, et al.2023 · 105 citations
  54. Chain of Agents: Large Language Models Collaborating on Long-Context TasksConference on Neural Information Processing Systems (NeurIPS)Yusen Zhang, Ruoxi Sun, Yanfei Chen, et al.2024 · 104 citations
  55. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
  56. Can we trust the evaluation on ChatGPT?Workshop on Trustworthy NLPRachith Aiyappa, Jisun An, Haewoon Kwak, et al.2023 · 103 citations
  57. PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt OptimizationarXiv:2310.16427Xinyuan Wang, Chenxi Li, Zhen Wang, et al.2023 · 102 citations
  58. FireAct: Toward Language Agent Fine-tuningarXiv:2310.05915Baian Chen, Chang Shu, Ehsan Shareghi, et al.2023 · 101 citations
  59. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  60. MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical ReasoningarXiv:2310.03731Ke Wang, Houxing Ren, Aojun Zhou, et al.2023 · 99 citations
  61. Chain of Draft: Thinking Faster by Writing LessarXiv:2502.18600Silei Xu, Wenhao Xie, Lingxiao Zhao, et al.2025 · 98 citations
  62. Hybrid LLM: Cost-Efficient and Quality-Aware Query RoutingarXiv:2404.14618Dujian Ding, Ankur Mallick, Chi Wang, et al.2024 · 98 citations
  63. Text and Patterns: For Effective Chain of Thought, It Takes Two to TangoarXiv:2209.07686Aman Madaan, Amir Yazdanbakhsh2022 · 98 citations
  64. MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 96 citations
  65. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
  66. The Platonic Representation HypothesisarXiv:2405.07987Minyoung Huh, Brian Cheung, Tongzhou Wang, et al.2024 · 96 citations
  67. Bactrian-X: Multilingual Replicable Instruction-Following Models with Low-Rank AdaptationarXiv:2305.15011Haonan Li, Fajri Koto, Minghao Wu, et al.2023 · 96 citations
  68. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 96 citations
  69. True Few-Shot Learning with Prompts–-A Real-World PerspectiveTransactions of the Association for Computational Linguistics (TACL)Timo Schick, Hinrich Schütze2022 · 96 citations
  70. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 95 citations
  71. NLPositionality: Characterizing Design Biases of Datasets and ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Sebastin Santy, Jenny Liang, Ronan Le Bras, et al.2023 · 95 citations
  72. Boosting Language Models Reasoning with Chain-of-Knowledge PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianing Wang, Qiushi Sun, Xiang Li, et al.2024 · 94 citations
  73. Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via DebateFindings of the Association for Computational LinguisticsKai Xiong, Xiao Ding, Yixin Cao, et al.2023 · 94 citations
  74. LLMs Are Few-Shot In-Context Low-Resource Language LearnersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Samuel Cahyawijaya, Holy Lovenia, Pascale Fung2024 · 93 citations
  75. LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mihir Parmar, Nisarg Patel, Neeraj Varshney, et al.2024 · 93 citations
  76. How well do Large Language Models perform in Arithmetic tasks?arXiv:2304.02015Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 93 citations
  77. WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language ModelsConference on Neural Information Processing Systems (NeurIPS)Liwei Jiang, Kavel Rao, Seungju Han, et al.2024 · 92 citations
  78. ChatHaruhi: Reviving Anime Character in Reality via Large Language ModelarXiv:2308.09597Cheng Li, Ziang Leng, Chenxi Yan, et al.2023 · 92 citations
  79. Do Language Models Know When They're Hallucinating References?Findings of the Association for Computational LinguisticsAyush Agrawal; Mirac Suzgun; Lester Mackey;, Adam Tauman Kalai2023 · 92 citations
  80. Foundation Models for Decision Making: Problems, Methods, and OpportunitiesarXiv:2303.04129Sherry Yang, Ofir Nachum, Yilun Du, et al.2023 · 92 citations
  81. On the Tool Manipulation Capability of Open-source Large Language ModelsarXiv:2305.16504Qiantong Xu, Fenglu Hong, Bo Li, et al.2023 · 92 citations
  82. PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM InferenceFindings of the Association for Computational LinguisticsDongjie Yang, Xiaodong Han, Yan Gao, et al.2024 · 91 citations
  83. “My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language ModelsFindings of the Association for Computational LinguisticsXinpeng Wang, Bolei Ma, Chengzhi Hu, et al.2024 · 91 citations
  84. Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language ModelsarXiv:2306.08018Yin Fang, Xiaozhuan Liang, Ningyu Zhang, et al.2023 · 91 citations
  85. SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific ResearchProceedings of the AAAI Conference on Artificial IntelligenceLiangtai Sun, Yang Han, Zihan Zhao, et al.2023 · 91 citations
  86. Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable SurveyConference of the European Chapter of the Association for Computational Linguistics (EACL)Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.2023 · 90 citations
  87. SuperGPQA: Scaling LLM Evaluation across 285 Graduate DisciplinesarXiv:2502.14739M-A-P Team, Xinrun Du, Yifan Yao, et al.2025 · 89 citations
  88. Evaluation Metrics in the Era of GPT-4: Reliably Evaluating Large Language Models on Sequence to Sequence TasksConference on Empirical Methods in Natural Language Processing (EMNLP)Andrea Sottana, Bin Liang, Kai Zou, et al.2023 · 89 citations
  89. Task Contamination: Language Models May Not Be Few-Shot AnymoreProceedings of the AAAI Conference on Artificial IntelligenceChangmao Li, Jeffrey Flanigan2023 · 89 citations
  90. Large Language Models as General Pattern MachinesarXiv:2307.04721Suvir Mirchandani, Fei Xia, Pete Florence, et al.2023 · 88 citations
  91. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  92. Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and ObservationsFindings of the Association for Computational LinguisticsNuo Chen, Zinan Zheng, Ning Wu, et al.2024 · 86 citations
  93. Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuningConference on Empirical Methods in Natural Language Processing (EMNLP)Zhaoxuan Tan, Qingkai Zeng, Yijun Tian, et al.2024 · 86 citations
  94. FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yuxin Jiang, Yufei Wang, Xingshan Zeng, et al.2024 · 86 citations
  95. Multilingual Large Language Models Are Not (Yet) Code-SwitchersConference on Empirical Methods in Natural Language Processing (EMNLP)Ruochen Zhang, Samuel Cahyawijaya, Jan Christian Blaise Cruz, et al.2023 · 86 citations
  96. NL-Augmenter: A Framework for Task-Sensitive Natural Language AugmentationNorthern European Journal of Language TechnologyKaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.2023 · 86 citations
  97. Solving Math Word Problems via Cooperative Reasoning induced Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyu Zhu, Junjie Wang, Lin Zhang, et al.2023 · 86 citations
  98. The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMsConference on Neural Information Processing Systems (NeurIPS)Laura Ruis, Akbir Khan, Stella Biderman, et al.2022 · 86 citations
  99. Benchmark Data Contamination of Large Language Models: A SurveyarXiv:2406.04244Cheng Xu, Shuhao Guan, Derek Greene, et al.2024 · 85 citations
  100. LLMs cannot find reasoning errors, but can correct them given the error locationFindings of the Association for Computational LinguisticsGladys Tyen, Hassan Mansoor, Victor Carbune, et al.2024 · 85 citations

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