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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) · 372 with a page here, the most cited first · page 2 of 4 · 101–200 · ← Eric Zelikman

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  1. LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic ProversConference on Empirical Methods in Natural Language Processing (EMNLP)Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.2023 · 172 citations
  2. When Can LLMs Actually Correct Their Own Mistakes? A Critical Survey of Self-Correction of LLMsTransactions of the Association for Computational Linguistics (TACL)Ryo Kamoi, Yusen Zhang, Nan Zhang, et al.2024 · 161 citations
  3. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
  4. SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-trainingarXiv:2501.17161Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.2025 · 160 citations
  5. Training Language Models to Self-Correct via Reinforcement LearningarXiv:2409.12917Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024 · 159 citations
  6. Large Language Models with Controllable Working MemoryFindings of the Association for Computational LinguisticsDaliang Li, Ankit Singh Rawat, Manzil Zaheer, et al.2023 · 158 citations
  7. ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Justin Chen, Swarnadeep Saha, Mohit Bansal2024 · 156 citations
  8. REFINER: Reasoning Feedback on Intermediate RepresentationsarXiv:2304.01904Debjit Paul, Mete Ismayilzada, Maxime Peyrard, et al.2023 · 156 citations
  9. ROSCOE: A Suite of Metrics for Scoring Step-by-Step ReasoningarXiv:2212.07919Olga Golovneva, Moya Chen, Spencer Poff, et al.2022 · 155 citations
  10. Can GPT-3 Perform Statutory Reasoning?arXiv:2302.06100Andrew Blair-Stanek, Nils Holzenberger, Benjamin Van Durme2023 · 154 citations
  11. Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
  12. Generative Verifiers: Reward Modeling as Next-Token PredictionarXiv:2408.15240Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.2024 · 152 citations
  13. Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and MitigationarXiv:2305.15852Niels Mundler, Jingxuan He, Slobodan Jenko, et al.2023 · 152 citations
  14. 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 · 148 citations
  15. Beyond Human Data: Scaling Self-Training for Problem-Solving with Language ModelsarXiv:2312.06585Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.2023 · 147 citations
  16. JudgeLM: Fine-tuned Large Language Models are Scalable JudgesarXiv:2310.17631Lianghui Zhu, Xinggang Wang, Xinlong Wang2023 · 145 citations
  17. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 143 citations
  18. Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse AttentionarXiv:2502.11089Jingyang Yuan, Huazuo Gao, Damai Dai, et al.2025 · 142 citations
  19. SLiC-HF: Sequence Likelihood Calibration with Human FeedbackarXiv:2305.10425Yao Zhao, Rishabh Joshi, Tianqi Liu, et al.2023 · 141 citations
  20. Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction StrategiesTransactions of the Association for Computational Linguistics (TACL)Liangming Pan, Michael Saxon, Wenda Xu, et al.2024 · 140 citations
  21. Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-StepAnnual Meeting of the Association for Computational Linguistics (ACL)Liunian Harold Li, Jack Hessel, Youngjae Yu, et al.2023 · 140 citations
  22. SOTOPIA: Interactive Evaluation for Social Intelligence in Language AgentsarXiv:2310.11667Xuhui Zhou, Hao Zhu, Leena Mathur, et al.2023 · 138 citations
  23. 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
  24. Few-Shot Self-Rationalization with Natural Language PromptsFindings of the Association for Computational LinguisticsAna Marasovic, Iz Beltagy, Doug Downey, et al.2022 · 134 citations
  25. Improving Language Model Negotiation with Self-Play and In-Context Learning from AI FeedbackarXiv:2305.10142Yao Fu, Hao Peng, Tushar Khot, et al.2023 · 132 citations
  26. 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
  27. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 129 citations
  28. 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
  29. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
  30. Unlearn What You Want to Forget: Efficient Unlearning for LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaao Chen, Diyi Yang2023 · 124 citations
  31. Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRsarXiv:2503.01307Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.2025 · 123 citations
  32. LEXTREME: A Multi-Lingual and Multi-Task Benchmark for the Legal DomainFindings of the Association for Computational LinguisticsJoel Niklaus, Veton Matoshi, Pooja Rani, et al.2023 · 123 citations
  33. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 122 citations
  34. Cross-lingual Prompting: Improving Zero-shot Chain-of-Thought Reasoning across LanguagesConference on Empirical Methods in Natural Language Processing (EMNLP)Libo Qin, Qiguang Chen, Fuxuan Wei, et al.2023 · 122 citations
  35. Demystifying Long Chain-of-Thought Reasoning in LLMsarXiv:2502.03373Edward Yeo, Yuxuan Tong, Morry Niu, et al.2025 · 119 citations
  36. 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
  37. 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
  38. Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human EvaluationarXiv:2212.07981Yixin Liu, Alexander R. Fabbri, Pengfei Liu, et al.2022 · 117 citations
  39. 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
  40. V-STaR: Training Verifiers for Self-Taught ReasonersarXiv:2402.06457Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024 · 114 citations
  41. RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text DetectorsAnnual Meeting of the Association for Computational Linguistics (ACL)Liam Dugan, Alyssa Hwang, Filip Trhlík, et al.2024 · 110 citations
  42. Leveraging GPT-4 for Automatic Translation Post-EditingFindings of the Association for Computational LinguisticsVikas Raunak, Amr Sharaf, Yiren Wang, et al.2023 · 108 citations
  43. A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and RecommendationsConference on Empirical Methods in Natural Language Processing (EMNLP)Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.2024 · 105 citations
  44. Disentangling Length from Quality in Direct Preference OptimizationFindings of the Association for Computational LinguisticsRyan Park, Rafael Rafailov, Stefano Ermon, et al.2024 · 105 citations
  45. 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
  46. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
  47. BLOOM+1: Adding Language Support to BLOOM for Zero-Shot PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, et al.2023 · 102 citations
  48. FireAct: Toward Language Agent Fine-tuningarXiv:2310.05915Baian Chen, Chang Shu, Ehsan Shareghi, et al.2023 · 101 citations
  49. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 100 citations
  50. Answering Questions by Meta-Reasoning over Multiple Chains of ThoughtConference on Empirical Methods in Natural Language Processing (EMNLP)Ori Yoran, Tomer Wolfson, Ben Bogin, et al.2023 · 99 citations
  51. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
  52. On Learning to Summarize with Large Language Models as ReferencesConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yixin Liu, Kejian Shi, Katherine He, et al.2024 · 94 citations
  53. Do-Not-Answer: Evaluating Safeguards in LLMsFindings of the Association for Computational LinguisticsYuxia Wang, Haonan Li, Xudong Han, et al.2024 · 93 citations
  54. 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
  55. On the Tool Manipulation Capability of Open-source Large Language ModelsarXiv:2305.16504Qiantong Xu, Fenglu Hong, Bo Li, et al.2023 · 92 citations
  56. “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
  57. 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
  58. LAMBADA: Backward Chaining for Automated Reasoning in Natural LanguageAnnual Meeting of the Association for Computational Linguistics (ACL)Mehran Kazemi, Najoung Kim, Deepti Bhatia, et al.2023 · 89 citations
  59. 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
  60. 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
  61. 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
  62. 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
  63. Style Over Substance: Evaluation Biases for Large Language ModelsInternational Conference on Computational Linguistics (COLING)Minghao Wu, Alham Fikri Aji2025 · 81 citations
  64. 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
  65. 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
  66. Do-Not-Answer: A Dataset for Evaluating Safeguards in LLMsarXiv:2308.13387Yuxia Wang, Haonan Li, Xudong Han, et al.2023 · 78 citations
  67. 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
  68. AlignBench: Benchmarking Chinese Alignment of Large Language ModelsarXiv:2311.18743Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.2023 · 74 citations
  69. Towards Safer Large Language Models through Machine UnlearningFindings of the Association for Computational LinguisticsZheyuan Liu, Guangyao Dou, Zhaoxuan Tan, et al.2024 · 72 citations
  70. 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
  71. 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
  72. 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
  73. Phoenix: Democratizing ChatGPT across LanguagesarXiv:2304.10453Zhihong Chen, Feng Jiang, Junying Chen, et al.2023 · 68 citations
  74. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
  75. Evaluation of OpenAI o1: Opportunities and Challenges of AGIarXiv:2409.18486Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.2024 · 64 citations
  76. 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
  77. 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
  78. 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
  79. Large Language Model Routing with Benchmark DatasetsarXiv:2309.15789Tal Shnitzer, Anthony Ou, Mirian Silva, et al.2023 · 63 citations
  80. Meta-Prompting: Enhancing Language Models with Task-Agnostic ScaffoldingarXiv:2401.12954Mirac Suzgun, Adam Tauman Kalai2024 · 62 citations
  81. 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
  82. Generalizing Verifiable Instruction FollowingConference on Neural Information Processing Systems (NeurIPS)Valentina Pyatkin, Saumya Malik, Victoria Graf, et al.2025 · 59 citations
  83. 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
  84. 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
  85. SuperCLUE: A Comprehensive Chinese Large Language Model BenchmarkarXiv:2307.15020Liang Xu, Anqi Li, Lei Zhu, et al.2023 · 57 citations
  86. 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
  87. 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
  88. 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
  89. AutoML-GPT: Automatic Machine Learning with GPTarXiv:2305.02499Shujian Zhang, Chengyue Gong, Lemeng Wu, et al.2023 · 52 citations
  90. 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
  91. 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
  92. 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
  93. RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon GenerationarXiv:2403.05313Zihao Wang, Anji Liu, Haowei Lin, et al.2024 · 46 citations
  94. 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
  95. 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
  96. HyperCLOVA X Technical ReportarXiv:2404.01954Kang Min Yoo, Jaegeun Han, Sookyo In, et al.2024 · 44 citations
  97. 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
  98. 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
  99. 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
  100. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations

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