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Who cites Eric Tang

2,176 citations of their works from 2,152 papers of our library (of the 149,439 whose bibliographies we read) · 844 with a page here, the most cited first · page 2 of 9 · 101–200 · ← Eric Tang

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  1. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
  2. Chameleon: Mixed-Modal Early-Fusion Foundation ModelsarXiv:2405.09818Chameleon Team2024 · 159 citations
  3. Training Language Models to Self-Correct via Reinforcement LearningarXiv:2409.12917Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024 · 159 citations
  4. Stop Overthinking: A Survey on Efficient Reasoning for Large Language ModelsarXiv:2503.16419Yang Sui, Yu-Neng Chuang, Guanchu Wang, et al.2025 · 157 citations
  5. LayerSkip: Enabling Early Exit Inference and Self-Speculative DecodingAnnual Meeting of the Association for Computational Linguistics (ACL)Mostafa Elhoushi, Akshat Shrivastava, Diana Liskovich, et al.2024 · 156 citations
  6. 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
  7. ROSCOE: A Suite of Metrics for Scoring Step-by-Step ReasoningarXiv:2212.07919Olga Golovneva, Moya Chen, Spencer Poff, et al.2022 · 155 citations
  8. SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the WildarXiv:2503.18892Weihao Zeng, Yuzhen Huang, Qian Liu, et al.2025 · 154 citations
  9. Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
  10. Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM ReasoningConference on Neural Information Processing Systems (NeurIPS)Shenzhi Wang, Le Yu, Chang Gao, et al.2025 · 152 citations
  11. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 152 citations
  12. Generative Verifiers: Reward Modeling as Next-Token PredictionarXiv:2408.15240Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.2024 · 152 citations
  13. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
  14. RA-DIT: Retrieval-Augmented Dual Instruction TuningarXiv:2310.01352Xi Victoria Lin, Xilun Chen, Mingda Chen, et al.2023 · 149 citations
  15. SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language ModelsarXiv:2307.10635Xiaoxuan Wang, Ziniu Hu, Pan Lu, et al.2023 · 149 citations
  16. TALM: Tool Augmented Language ModelsarXiv:2205.12255Aaron Parisi, Yao Zhao, Noah Fiedel2022 · 149 citations
  17. Justice or Prejudice? Quantifying Biases in LLM-as-a-JudgearXiv:2410.02736Jiayi Ye, Yanbo Wang, Yue Huang, et al.2024 · 148 citations
  18. Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
  19. 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
  20. How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data CompositionAnnual Meeting of the Association for Computational Linguistics (ACL)Guanting Dong, Hongyi Yuan, Keming Lu, et al.2024 · 145 citations
  21. Many-Shot In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.2024 · 142 citations
  22. ProofNet: Autoformalizing and Formally Proving Undergraduate-Level MathematicsarXiv:2302.12433Zhangir Azerbayev, Bartosz Piotrowski, Hailey Schoelkopf, et al.2023 · 142 citations
  23. MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language FeedbackarXiv:2309.10691Xingyao Wang, Zihan Wang, Jiateng Liu, et al.2023 · 141 citations
  24. Exploring Length Generalization in Large Language ModelsarXiv:2207.04901Cem Anil, Yuhuai Wu, Anders Andreassen, et al.2022 · 139 citations
  25. Representing Numbers in NLP: a Survey and a VisionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Avijit Thawani, Jay Pujara, Filip Ilievski, et al.2021 · 139 citations
  26. 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
  27. 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
  28. ReFT: Reasoning with Reinforced Fine-TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Luong Trung, Xinbo Zhang, Zhanming Jie, et al.2024 · 134 citations
  29. EuroLLM: Multilingual Language Models for EuropearXiv:2409.16235Pedro Henrique Martins, Patrick Fernandes, Joao Alves, et al.2024 · 133 citations
  30. Formal Mathematics Statement Curriculum LearningarXiv:2202.01344Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.2022 · 133 citations
  31. OpenWebMath: An Open Dataset of High-Quality Mathematical Web TextarXiv:2310.06786Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, et al.2023 · 132 citations
  32. Progressive-Hint Prompting Improves Reasoning in Large Language ModelsarXiv:2304.09797Chuanyang Zheng, Zhengying Liu, Enze Xie, et al.2023 · 131 citations
  33. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  34. Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 130 citations
  35. Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base ModelConference on Neural Information Processing Systems (NeurIPS)Jingcheng Hu, Yinmin Zhang, Qi Han, et al.2025 · 128 citations
  36. MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual DataAnnual Meeting of the Association for Computational Linguistics (ACL)Yilun Zhao, Yunxiang Li, Chenying Li, et al.2022 · 128 citations
  37. L1: Controlling How Long A Reasoning Model Thinks With Reinforcement LearningarXiv:2503.04697Pranjal Aggarwal, Sean Welleck2025 · 125 citations
  38. 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
  39. 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
  40. DeepSeek-V4: Towards Highly Efficient Million-Token Context IntelligencearXiv:2606.19348DeepSeek-AI, Anyi Xu, Bangcai Lin, et al.2026 · 122 citations
  41. DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal DecompositionarXiv:2504.21801Z. Z. Ren, Zhihong Shao, Junxiao Song, et al.2025 · 122 citations
  42. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
  43. Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language ModelsarXiv:2408.00724Yangzhen Wu, Zhiqing Sun, Shanda Li, et al.2024 · 122 citations
  44. 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
  45. AlphaMath Almost Zero: Process Supervision without ProcessConference on Neural Information Processing Systems (NeurIPS)Guoxin Chen, Minpeng Liao, Chengxi Li, et al.2024 · 120 citations
  46. #InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language ModelsarXiv:2308.07074Keming Lu, Hongyi Yuan, Zheng Yuan, et al.2023 · 120 citations
  47. Demystifying Long Chain-of-Thought Reasoning in LLMsarXiv:2502.03373Edward Yeo, Yuxuan Tong, Morry Niu, et al.2025 · 119 citations
  48. Platypus: Quick, Cheap, and Powerful Refinement of LLMsarXiv:2308.07317Ariel N. Lee, Cole J. Hunter, Nataniel Ruiz2023 · 117 citations
  49. ProcessBench: Identifying Process Errors in Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Chujie Zheng, Zhenru Zhang, Beichen Zhang, et al.2025 · 116 citations
  50. Mixture-of-Agents Enhances Large Language Model CapabilitiesarXiv:2406.04692Junlin Wang, Jue Wang, Ben Athiwaratkun, et al.2024 · 116 citations
  51. V-STaR: Training Verifiers for Self-Taught ReasonersarXiv:2402.06457Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024 · 114 citations
  52. A Dynamic LLM-Powered Agent Network for Task-Oriented Agent CollaborationarXiv:2310.02170Zijun Liu, Yanzhe Zhang, Peng Li, et al.2023 · 114 citations
  53. ALLaM: Large Language Models for Arabic and EnglisharXiv:2407.15390M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, et al.2024 · 113 citations
  54. Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-VerificationarXiv:2308.07921Aojun Zhou, Ke Wang, Zimu Lu, et al.2023 · 110 citations
  55. GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem SolversAnnual Meeting of the Association for Computational Linguistics (ACL)Qintong Li, Leyang Cui, Xueliang Zhao, et al.2024 · 108 citations
  56. Nemotron-4 340B Technical ReportarXiv:2406.11704Nvidia: Bo Adler, Niket Agarwal, Ashwath Aithal, et al.2024 · 107 citations
  57. Pixtral 12BarXiv:2410.07073Pravesh Agrawal, Szymon Antoniak, Emma Bou Hanna, et al.2024 · 107 citations
  58. Have LLMs Advanced Enough? A Challenging Problem Solving Benchmark For Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Daman Arora, Himanshu Singh, Mausam2023 · 107 citations
  59. TokenSkip: Controllable Chain-of-Thought Compression in LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Heming Xia, Chak Tou Leong, Wenjie Wang, et al.2025 · 106 citations
  60. Multi-Step Reasoning with Large Language Models, a SurveyACM Computing SurveysAske Plaat, Annie Wong, Suzan Verberne, et al.2024 · 106 citations
  61. 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
  62. The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem ComplexityConference on Neural Information Processing Systems (NeurIPS)Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.2025 · 104 citations
  63. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
  64. Rethinking Benchmark and Contamination for Language Models with Rephrased SamplesarXiv:2311.04850Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, et al.2023 · 103 citations
  65. Qwen2.5-1M Technical ReportarXiv:2501.15383An Yang, Bowen Yu, Chengyuan Li, et al.2025 · 102 citations
  66. The Entropy Mechanism of Reinforcement Learning for Reasoning Language ModelsarXiv:2505.22617Ganqu Cui, Yuchen Zhang, Jiacheng Chen, et al.2025 · 101 citations
  67. A Careful Examination of Large Language Model Performance on Grade School ArithmeticConference on Neural Information Processing Systems (NeurIPS)Hugh Zhang, Jeff Da, Dean Lee, et al.2024 · 101 citations
  68. Large language models for education: A survey and outlookWang2024 · 101 citations
  69. SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step ReasoningarXiv:2308.00436Ning Miao, Yee Whye Teh, Tom Rainforth2023 · 101 citations
  70. MathArena: Evaluating LLMs on Uncontaminated Math CompetitionsConference on Neural Information Processing Systems (NeurIPS)Mislav Balunović, Jasper Dekoninck, Ivo Petrov, et al.2025 · 99 citations
  71. FELM: Benchmarking Factuality Evaluation of Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Shiqi Chen, Yiran Zhao, Jinghan Zhang, et al.2023 · 99 citations
  72. MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical ReasoningarXiv:2310.03731Ke Wang, Houxing Ren, Aojun Zhou, et al.2023 · 99 citations
  73. OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning DatasetConference on Neural Information Processing Systems (NeurIPS)Shubham Toshniwal, Ivan Moshkov, Sean Narenthiran, et al.2024 · 98 citations
  74. FrontierMath: A Benchmark for Evaluating Advanced Mathematical Reasoning in AIarXiv:2411.04872Elliot Glazer, Ege Erdil, Tamay Besiroglu, et al.2024 · 97 citations
  75. Make Your LLM Fully Utilize the ContextConference on Neural Information Processing Systems (NeurIPS)Shengnan An, Zexiong Ma, Zeqi Lin, et al.2024 · 97 citations
  76. MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 96 citations
  77. Teaching Algorithmic Reasoning via In-context LearningarXiv:2211.09066Hattie Zhou, Azade Nova, Hugo Larochelle, et al.2022 · 96 citations
  78. AFlow: Automating Agentic Workflow GenerationarXiv:2410.10762Jiayi Zhang, Jinyu Xiang, Zhaoyang Yu, et al.2024 · 95 citations
  79. Advancing LLM Reasoning Generalists with Preference TreesarXiv:2404.02078Lifan Yuan, Ganqu Cui, Hanbin Wang, et al.2024 · 94 citations
  80. PutnamBench: Evaluating Neural Theorem-Provers on the Putnam Mathematical CompetitionConference on Neural Information Processing Systems (NeurIPS)George Tsoukalas, Jasper Lee, John Jennings, et al.2024 · 93 citations
  81. Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
  82. How well do Large Language Models perform in Arithmetic tasks?arXiv:2304.02015Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 93 citations
  83. SeaLLMs — Large Language Models for Southeast AsiaarXiv:2312.00738Xuan-Phi Nguyen, Wenxuan Zhang, Xin Li, et al.2023 · 92 citations
  84. Universal Self-Consistency for Large Language Model GenerationarXiv:2311.17311Xinyun Chen, Renat Aksitov, Uri Alon, et al.2023 · 92 citations
  85. Data Interpreter: An LLM Agent for Data ScienceFindings of the Association for Computational LinguisticsSirui Hong, Yizhang Lin, Bang Liu, et al.2025 · 91 citations
  86. 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
  87. InternLM-Math: Open Math Large Language Models Toward Verifiable ReasoningarXiv:2402.06332Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.2024 · 90 citations
  88. 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
  89. Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xudong Lu, Qi Liu, Yuhui Xu, et al.2024 · 88 citations
  90. Pride and Prejudice: LLM Amplifies Self-Bias in Self-RefinementAnnual Meeting of the Association for Computational Linguistics (ACL)Wenda Xu, Guanglei Zhu, Xuandong Zhao, et al.2024 · 88 citations
  91. Reinforcement Learning for Reasoning in Large Language Models with One Training ExampleConference on Neural Information Processing Systems (NeurIPS)Yiping Wang, Qing Yang, Zhiyuan Zeng, et al.2025 · 87 citations
  92. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  93. PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language ModelsarXiv:2404.02948Fanxu Meng, Zhaohui Wang, Muhan Zhang2024 · 86 citations
  94. More Agents Is All You NeedarXiv:2402.05120Junyou Li, Qin Zhang, Yangbin Yu, et al.2024 · 85 citations
  95. OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction DataarXiv:2410.01560Shubham Toshniwal, Wei Du, Ivan Moshkov, et al.2024 · 85 citations
  96. Goedel-Prover: A Frontier Model for Open-Source Automated Theorem ProvingarXiv:2502.07640Yong Lin, Shange Tang, Bohan Lyu, et al.2025 · 84 citations
  97. Light-R1: Curriculum SFT, DPO and RL for Long COT from Scratch and BeyondAnnual Meeting of the Association for Computational Linguistics (ACL)Liang Wen, Yunke Cai, Fenrui Xiao, et al.2025 · 84 citations
  98. MathScale: Scaling Instruction Tuning for Mathematical ReasoningarXiv:2403.02884Zhengyang Tang, Xingxing Zhang, Benyou Wang, et al.2024 · 83 citations
  99. CodeGemma: Open Code Models Based on GemmaarXiv:2406.11409CodeGemma Team: Heri Zhao, Jeffrey Hui, Joshua Howland, et al.2024 · 82 citations
  100. OpenCoder: The Open Cookbook for Top-Tier Code Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Siming Huang, Tianhao Cheng, Jason Klein Liu, et al.2025 · 81 citations

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