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Who cites Eric Zelikman

1,597 citations of their works from 1,551 papers of our library (of the 149,439 whose bibliographies we read) · 458 with a page here, the most cited first · page 3 of 5 · 201–300 · ← Eric Zelikman

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  1. HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMsarXiv:2412.18925Junying Chen, Zhenyang Cai, Ke Ji, et al.2024 · 87 citations
  2. 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
  3. Machine Unlearning of Pre-trained Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jin Yao, Eli Chien, Minxin Du, et al.2024 · 86 citations
  4. O1 Replication Journey: A Strategic Progress Report — Part 1arXiv:2410.18982Yiwei Qin, Xuefeng Li, Haoyang Zou, et al.2024 · 86 citations
  5. 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
  6. Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD ExamplesConference on Neural Information Processing Systems (NeurIPS)Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, et al.2023 · 84 citations
  7. PRD: Peer Rank and Discussion Improve Large Language Model based EvaluationsarXiv:2307.02762Ruosen Li, Teerth Patel, Xinya Du2023 · 83 citations
  8. Survey of Vulnerabilities in Large Language Models Revealed by Adversarial AttacksarXiv:2310.10844Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.2023 · 83 citations
  9. Does Writing with Language Models Reduce Content Diversity?arXiv:2309.05196Vishakh Padmakumar, He He2023 · 82 citations
  10. Style Over Substance: Evaluation Biases for Large Language ModelsInternational Conference on Computational Linguistics (COLING)Minghao Wu, Alham Fikri Aji2025 · 81 citations
  11. DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-SolvingarXiv:2407.13690Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.2024 · 81 citations
  12. AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Harsh Trivedi, Tushar Khot, Mareike Hartmann, et al.2024 · 80 citations
  13. Toward Self-Improvement of LLMs via Imagination, Searching, and CriticizingConference on Neural Information Processing Systems (NeurIPS)Ye Tian, Baolin Peng, Linfeng Song, et al.2024 · 80 citations
  14. A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?arXiv:2503.24235Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.2025 · 79 citations
  15. KoBBQ: Korean Bias Benchmark for Question AnsweringTransactions of the Association for Computational Linguistics (TACL)Jiho Jin, Jiseon Kim, Nayeon Lee, et al.2024 · 78 citations
  16. Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMsarXiv:2308.13387Yuxia Wang, Haonan Li, Xudong Han, et al.2023 · 78 citations
  17. Recursive Introspection: Teaching Language Model Agents How to Self-ImproveConference on Neural Information Processing Systems (NeurIPS)Yuxiao Qu, Tianjun Zhang, Naman Garg, et al.2024 · 75 citations
  18. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
  19. MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and TasksConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.2024 · 74 citations
  20. When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model LeaderboardsarXiv:2402.01781Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay, et al.2024 · 74 citations
  21. AlignBench: Benchmarking Chinese Alignment of Large Language ModelsarXiv:2311.18743Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.2023 · 74 citations
  22. Large Language Models as Analogical ReasonersarXiv:2310.01714Michihiro Yasunaga, Xinyun Chen, Yujia Li, et al.2023 · 74 citations
  23. MuSR: Testing the Limits of Chain-of-thought with Multistep Soft ReasoningInternational Conference on Learning Representations (ICLR)Zayne Sprague, Xi Ye, Kaj Bostrom, et al.2023 · 74 citations
  24. Benchmarking Benchmark Leakage in Large Language ModelsarXiv:2404.18824Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.2024 · 73 citations
  25. From r to Q*: Your Language Model is Secretly a Q-FunctionarXiv:2404.12358Rafael Rafailov, Joey Hejna, Ryan Park, et al.2024 · 72 citations
  26. Towards Safer Large Language Models through Machine UnlearningFindings of the Association for Computational LinguisticsZheyuan Liu, Guangyao Dou, Zhaoxuan Tan, et al.2024 · 72 citations
  27. Chain-of-Thought Hub: A Continuous Effort to Measure Large Language Models' Reasoning PerformancearXiv:2305.17306Yao Fu, Litu Ou, Mingyu Chen, et al.2023 · 72 citations
  28. Skeleton-of-Thought: Prompting LLMs for Efficient Parallel GenerationarXiv:2307.15337Xuefei Ning, Zinan Lin, Zixuan Zhou, et al.2023 · 72 citations
  29. RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement LearningarXiv:2504.20073Zihan Wang, Kangrui Wang, Qineng Wang, et al.2025 · 71 citations
  30. Aligning Large and Small Language Models via Chain-of-Thought ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Leonardo Ranaldi, Andre Freitas2024 · 70 citations
  31. Agent Q: Advanced Reasoning and Learning for Autonomous AI AgentsarXiv:2408.07199Pranav Putta, Edmund Mills, Naman Garg, et al.2024 · 68 citations
  32. Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Haoxiang Wang, Yong Lin, Wei Xiong, et al.2024 · 68 citations
  33. Branch-Solve-Merge Improves Large Language Model Evaluation and GenerationarXiv:2310.15123Swarnadeep Saha, Omer Levy, Asli Celikyilmaz, et al.2023 · 68 citations
  34. Phoenix: Democratizing ChatGPT across LanguagesarXiv:2304.10453Zhihong Chen, Feng Jiang, Junying Chen, et al.2023 · 68 citations
  35. Learning by Distilling ContextarXiv:2209.15189Charlie Snell, Dan Klein, Ruiqi Zhong2022 · 67 citations
  36. Imitate, Explore, and Self-Improve: A Reproduction Report on Slow-thinking Reasoning SystemsarXiv:2412.09413Yingqian Min, Zhipeng Chen, Jinhao Jiang, et al.2024 · 66 citations
  37. ARB: Advanced Reasoning Benchmark for Large Language ModelsarXiv:2307.13692Tomohiro Sawada, Daniel Paleka, Alexander Havrilla, et al.2023 · 66 citations
  38. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
  39. Evaluation of OpenAI o1: Opportunities and Challenges of AGIarXiv:2409.18486Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.2024 · 64 citations
  40. CValues: Measuring the Values of Chinese Large Language Models from Safety to ResponsibilityarXiv:2307.09705Guohai Xu, Jiayi Liu, Ming Yan, et al.2023 · 64 citations
  41. Monitoring Reasoning Models for Misbehavior and the Risks of Promoting ObfuscationarXiv:2503.11926Bowen Baker, Joost Huizinga, Leo Gao, et al.2025 · 63 citations
  42. What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt EngineeringConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Federico Errica, Davide Sanvito, Giuseppe Siracusano, et al.2025 · 63 citations
  43. Leveraging Large Language Models for NLG Evaluation: Advances and ChallengesConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Li, Xiaohan Xu, Tao Shen, et al.2024 · 63 citations
  44. Large Language Model Routing with Benchmark DatasetsarXiv:2309.15789Tal Shnitzer, Anthony Ou, Mirian Silva, et al.2023 · 63 citations
  45. LAB-Bench: Measuring Capabilities of Language Models for Biology ResearcharXiv:2407.10362Jon M. Laurent, Joseph D. Janizek, Michael Ruzo, et al.2024 · 62 citations
  46. Meta-Prompting: Enhancing Language Models with Task-Agnostic ScaffoldingarXiv:2401.12954Mirac Suzgun, Adam Tauman Kalai2024 · 62 citations
  47. Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use CasesarXiv:2303.14742Yunjie Ji, Yong Deng, Yan Gong, et al.2023 · 62 citations
  48. SatLM: Satisfiability-Aided Language Models Using Declarative PromptingConference on Neural Information Processing Systems (NeurIPS)Xi Ye, Qiaochu Chen, Isil Dillig, et al.2023 · 62 citations
  49. Small Models Struggle to Learn from Strong ReasonersFindings of the Association for Computational LinguisticsYuetai Li, Xiang Yue, Zhangchen Xu, et al.2025 · 61 citations
  50. Teaching Large Language Models to Reason with Reinforcement LearningarXiv:2403.04642Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.2024 · 61 citations
  51. Generalizing Verifiable Instruction FollowingConference on Neural Information Processing Systems (NeurIPS)Valentina Pyatkin, Saumya Malik, Victoria Graf, et al.2025 · 59 citations
  52. ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Mingjie Liu, Shizhe Diao, Ximing Lu, et al.2025 · 58 citations
  53. Absolute Zero: Reinforced Self-play Reasoning with Zero DataConference on Neural Information Processing Systems (NeurIPS)Andrew Zhao, Yiran Wu, Yang Yue, et al.2025 · 57 citations
  54. Can LLMs Learn from Previous Mistakes? Investigating LLMs' Errors to Boost for ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Yongqi Tong, Dawei Li, Sizhe Wang, et al.2024 · 57 citations
  55. Dialect prejudice predicts AI decisions about people's character, employability, and criminalityarXiv:2403.00742Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, et al.2024 · 57 citations
  56. SuperCLUE: A Comprehensive Chinese Large Language Model BenchmarkarXiv:2307.15020Liang Xu, Anqi Li, Lei Zhu, et al.2023 · 57 citations
  57. Parsel: Algorithmic Reasoning with Language Models by Composing DecompositionsConference on Neural Information Processing Systems (NeurIPS)Eric Zelikman, Qian Huang, Gabriel Poesia, et al.2023 · 56 citations
  58. AI Agents That MatterarXiv:2407.01502Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, et al.2024 · 55 citations
  59. A Chain-of-Thought Is as Strong as Its Weakest Link: A Benchmark for Verifiers of Reasoning ChainsAnnual Meeting of the Association for Computational Linguistics (ACL)Alon Jacovi, Yonatan Bitton, Bernd Bohnet, et al.2024 · 54 citations
  60. M³CoT: A Novel Benchmark for Multi-Domain Multi-step Multi-modal Chain-of-ThoughtAnnual Meeting of the Association for Computational Linguistics (ACL)Qiguang Chen, Libo Qin, Jin Zhang, et al.2024 · 54 citations
  61. Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question?Annual Meeting of the Association for Computational Linguistics (ACL)Nishant Balepur, Abhilasha Ravichander, Rachel Rudinger2024 · 52 citations
  62. AutoML-GPT: Automatic Machine Learning with GPTarXiv:2305.02499Shujian Zhang, Chengyue Gong, Lemeng Wu, et al.2023 · 52 citations
  63. On the application of Large Language Models for language teaching and assessment technologyarXiv:2307.08393Andrew Caines, Luca Benedetto, Shiva Taslimipoor, et al.2023 · 51 citations
  64. Can Multiple-choice Questions Really Be Useful in Detecting the Abilities of LLMs?Language Resources and Evaluation Conference (LREC)Wangyue Li, Liangzhi Li, Tong Xiang, et al.2024 · 47 citations
  65. Metaphor Understanding Challenge Dataset for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyu Tong, Rochelle Choenni, Martha Lewis, et al.2024 · 47 citations
  66. RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon GenerationarXiv:2403.05313Zihao Wang, Anji Liu, Haowei Lin, et al.2024 · 46 citations
  67. On Memorization of Large Language Models in Logical ReasoningInternational Joint Conference on Natural Language Processing (IJCNLP)Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.2025 · 45 citations
  68. GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local RefinementsarXiv:2402.10963Alex Havrilla, Sharath Raparthy, Christoforus Nalmpantis, et al.2024 · 45 citations
  69. HyperCLOVA X Technical ReportarXiv:2404.01954Kang Min Yoo, Jaegeun Han, Sookyo In, et al.2024 · 44 citations
  70. Towards Thinking-Optimal Scaling of Test-Time Compute for LLM ReasoningConference on Neural Information Processing Systems (NeurIPS)Wenkai Yang, Shuming Ma, Yankai Lin, et al.2025 · 43 citations
  71. Paloma: A Benchmark for Evaluating Language Model FitConference on Neural Information Processing Systems (NeurIPS)Ian Magnusson, Akshita Bhagia, Valentin Hofmann, et al.2023 · 42 citations
  72. When does In-context Learning Fall Short and Why? A Study on Specification-Heavy TasksarXiv:2311.08993Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.2023 · 42 citations
  73. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
  74. DeepSeek: Paradigm Shifts and Technical Evolution in Large AI ModelsarXiv:2507.09955Luolin Xiong, Haofen Wang, Xi Chen, et al.2025 · 41 citations
  75. FollowIR: Evaluating and Teaching Information Retrieval Models to Follow InstructionsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Orion Weller, Benjamin Chang, Sean MacAvaney, et al.2025 · 40 citations
  76. Observational Scaling Laws and the Predictability of Language Model PerformancearXiv:2405.10938Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 40 citations
  77. Sociodemographic Bias in Language Models: A Survey and Forward PathWorkshop on Gender Bias in Natural Language ProcessingVipul Gupta, Pranav Narayanan Venkit, Shomir Wilson, et al.2023 · 40 citations
  78. Aligning Language Models with Preferences through f-divergence MinimizationarXiv:2302.08215Dongyoung Go, Tomasz Korbak, German Kruszewski, et al.2023 · 39 citations
  79. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
  80. Dynamic Cheatsheet: Test-Time Learning with Adaptive MemoryConference of the European Chapter of the Association for Computational Linguistics (EACL)Mirac Suzgun, Mert Yuksekgonul, Federico Bianchi, et al.2026 · 37 citations
  81. Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and ParaphrasingarXiv:2305.16635Jaehun Jung, Peter West, Liwei Jiang, et al.2023 · 36 citations
  82. Vision-Language Models Can Self-Improve Reasoning via ReflectionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Kanzhi Cheng, Li YanTao, Fangzhi Xu, et al.2025 · 35 citations
  83. On the Diversity of Synthetic Data and its Impact on Training Large Language ModelsarXiv:2410.15226Hao Chen, Abdul Waheed, Xiang Li, et al.2024 · 35 citations
  84. Self-Refine Instruction-Tuning for Aligning Reasoning in Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Leonardo Ranaldi, Andre Freitas2024 · 35 citations
  85. Through the Lens of Core Competency: Survey on Evaluation of Large Language ModelsarXiv:2308.07902Ziyu Zhuang, Qiguang Chen, Longxuan Ma, et al.2023 · 35 citations
  86. mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Huiyuan Lai, Malvina Nissim2024 · 34 citations
  87. Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge EvaluationarXiv:2306.05783Zhouhong Gu, Xiaoxuan Zhu, Haoning Ye, et al.2023 · 34 citations
  88. SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model SafetyarXiv:2404.05399Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.2024 · 33 citations
  89. BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language ModelsarXiv:2309.06085Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.2023 · 33 citations
  90. Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM EvaluationInternational Conference on Computational Linguistics (COLING)Siyuan Wang, Zhuohan Long, Zhihao Fan, et al.2025 · 30 citations
  91. Contextualization Distillation from Large Language Model for Knowledge Graph CompletionFindings of the Association for Computational LinguisticsDawei Li, Zhen Tan, Tianlong Chen, et al.2024 · 30 citations
  92. Jamba-1.5: Hybrid Transformer-Mamba Models at ScalearXiv:2408.12570Jamba Team: Barak Lenz, Alan Arazi, Amir Bergman, et al.2024 · 30 citations
  93. Analyzing Chain-of-Thought Prompting in Large Language Models via Gradient-based Feature AttributionsarXiv:2307.13339Skyler Wu, Eric Meng Shen, Charumathi Badrinath, et al.2023 · 30 citations
  94. Reasoning Aware Self-Consistency: Leveraging Reasoning Paths for Efficient LLM SamplingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Guangya Wan, Yuqi Wu, Jie Chen, et al.2025 · 29 citations
  95. Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learningConference on Computational Natural Language Learning (CoNLL)Lucas Weber, Elia Bruni, Dieuwke Hupkes2023 · 29 citations
  96. Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the AboveAnnual Meeting of the Association for Computational Linguistics (ACL)Nishant Balepur, Rachel Rudinger, Jordan Boyd-Graber2025 · 28 citations
  97. Can Language Models Solve Olympiad Programming?arXiv:2404.10952Quan Shi, Michael Tang, Karthik Narasimhan, et al.2024 · 28 citations
  98. Pushing the Limits of ChatGPT on NLP TasksarXiv:2306.09719Xiaofei Sun, Linfeng Dong, Xiaoya Li, et al.2023 · 28 citations
  99. L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language ModelsTransactions of the Association for Computational Linguistics (TACL)Ansong Ni, Pengcheng Yin, Yilun Zhao, et al.2024 · 27 citations
  100. Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal SamplingarXiv:2408.16737Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.2024 · 27 citations

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