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Who cites Hunter Lightman

2,758 citations of their works from 2,420 papers of our library (of the 149,439 whose bibliographies we read) · 745 with a page here, the most cited first · page 2 of 8 · 101–200 · ← Hunter Lightman

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  1. Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language ModelsarXiv:2601.18734Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.2026 · 97 citations
  2. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
  3. Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
  4. Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement LearningarXiv:2504.11354Haiming Wang, Mert Unsal, Xiaohan Lin, et al.2025 · 92 citations
  5. Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language ModelsarXiv:2503.06749Wenxuan Huang, Bohan Jia, Zijie Zhai, et al.2025 · 92 citations
  6. InternLM-Math: Open Math Large Language Models Toward Verifiable ReasoningarXiv:2402.06332Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.2024 · 90 citations
  7. Dream 7B: Diffusion Large Language ModelsarXiv:2508.15487Jiacheng Ye; Zhihui Xie; Lin Zheng; Jiahui Gao; Zirui Wu; Xin Jiang; Zhenguo Li;, Lingpeng Kong2025 · 89 citations
  8. GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement LearningarXiv:2507.01006GLM-V Team, Wenyi Hong, Wenmeng Yu, et al.2025 · 89 citations
  9. SuperGPQA: Scaling LLM Evaluation across 285 Graduate DisciplinesarXiv:2502.14739M-A-P Team, Xinrun Du, Yifan Yao, et al.2025 · 89 citations
  10. ADaPT: As-Needed Decomposition and Planning with Language ModelsFindings of the Association for Computational LinguisticsArchiki Prasad, Alexander Koller, Mareike Hartmann, et al.2024 · 89 citations
  11. ReTool: Reinforcement Learning for Strategic Tool Use in LLMsarXiv:2504.11536Jiazhan Feng, Shijue Huang, Xingwei Qu, et al.2025 · 88 citations
  12. 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
  13. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  14. HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMsarXiv:2412.18925Junying Chen, Zhenyang Cai, Ke Ji, et al.2024 · 87 citations
  15. O1 Replication Journey: A Strategic Progress Report — Part 1arXiv:2410.18982Yiwei Qin, Xuefeng Li, Haoyang Zou, et al.2024 · 86 citations
  16. Evaluating Mathematical Reasoning Beyond AccuracyProceedings of the AAAI Conference on Artificial IntelligenceShijie Xia, Xuefeng Li, Yixin Liu, et al.2024 · 85 citations
  17. 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
  18. 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
  19. HelpSteer2: Open-source dataset for training top-performing reward modelsarXiv:2406.08673Zhilin Wang, Yi Dong, Olivier Delalleau, et al.2024 · 82 citations
  20. Marco-o1: Towards Open Reasoning Models for Open-Ended SolutionsarXiv:2411.14405Yu Zhao, Huifeng Yin, Bo Zeng, et al.2024 · 82 citations
  21. DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-SolvingarXiv:2407.13690Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.2024 · 81 citations
  22. 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
  23. 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
  24. Common 7B Language Models Already Possess Strong Math CapabilitiesarXiv:2403.04706Chen Li, Weiqi Wang, Jingcheng Hu, et al.2024 · 79 citations
  25. OVM, Outcome-supervised Value Models for Planning in Mathematical ReasoningFindings of the Association for Computational LinguisticsFei Yu, Anningzhe Gao, Benyou Wang2023 · 78 citations
  26. Llama-Nemotron: Efficient Reasoning ModelsarXiv:2505.00949Akhiad Bercovich, Itay Levy, Izik Golan, et al.2025 · 76 citations
  27. TTRL: Test-Time Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.2025 · 76 citations
  28. 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
  29. Self-Contrast: Better Reflection Through Inconsistent Solving PerspectivesAnnual Meeting of the Association for Computational Linguistics (ACL)Wenqi Zhang, Yongliang Shen, Linjuan Wu, et al.2024 · 75 citations
  30. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
  31. Training Language Models to Reason EfficientlyConference on Neural Information Processing Systems (NeurIPS)Daman Arora, Andrea Zanette2025 · 74 citations
  32. Mutual Reasoning Makes Smaller LLMs Stronger Problem-SolversarXiv:2408.06195Zhenting Qi, Mingyuan Ma, Jiahang Xu, et al.2024 · 74 citations
  33. Cumulative Reasoning with Large Language ModelsarXiv:2308.04371Yifan Zhang, Jingqin Yang, Yang Yuan, et al.2023 · 74 citations
  34. Rubrics as Rewards: Reinforcement Learning Beyond Verifiable DomainsarXiv:2507.17746Anisha Gunjal, Anthony Wang, Elaine Lau, et al.2025 · 73 citations
  35. WebThinker: Empowering Large Reasoning Models with Deep Research CapabilityConference on Neural Information Processing Systems (NeurIPS)Xiaoxi Li, Jiajie Jin, Guanting Dong, et al.2025 · 72 citations
  36. RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement LearningarXiv:2504.20073Zihan Wang, Kangrui Wang, Qineng Wang, et al.2025 · 71 citations
  37. Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoying Zhang, Baolin Peng, Ye Tian, et al.2024 · 69 citations
  38. Apertus: Democratizing Open and Compliant LLMs for Global Language EnvironmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.2026 · 68 citations
  39. Competitive Programming with Large Reasoning ModelsarXiv:2502.06807OpenAI: Ahmed El-Kishky, Alexander Wei, Andre Saraiva, et al.2025 · 68 citations
  40. Learning to Reason under Off-Policy GuidanceConference on Neural Information Processing Systems (NeurIPS)Jianhao Yan, Yafu Li, Zican Hu, et al.2025 · 68 citations
  41. Agent Q: Advanced Reasoning and Learning for Autonomous AI AgentsarXiv:2408.07199Pranav Putta, Edmund Mills, Naman Garg, et al.2024 · 68 citations
  42. Goedel-Prover-V2: Scaling Formal Theorem Proving with Scaffolded Data Synthesis and Self-CorrectionarXiv:2508.03613Yong Lin, Shange Tang, Bohan Lyu, et al.2025 · 67 citations
  43. Seed1.5-VL Technical ReportarXiv:2505.07062Dong Guo, Faming Wu, Feida Zhu, et al.2025 · 67 citations
  44. ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement LearningarXiv:2504.01296Bairu Hou, Yang Zhang, Jiabao Ji, et al.2025 · 67 citations
  45. 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
  46. ARB: Advanced Reasoning Benchmark for Large Language ModelsarXiv:2307.13692Tomohiro Sawada, Daniel Paleka, Alexander Havrilla, et al.2023 · 66 citations
  47. Routing to the Expert: Efficient Reward-guided Ensemble of Large Language ModelsarXiv:2311.08692Keming Lu, Hongyi Yuan, Runji Lin, et al.2023 · 66 citations
  48. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
  49. MedXpertQA: Benchmarking Expert-Level Medical Reasoning and UnderstandingarXiv:2501.18362Yuxin Zuo, Shang Qu, Yifei Li, et al.2025 · 65 citations
  50. CoT-Valve: Length-Compressible Chain-of-Thought TuningAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyin Ma, Guangnian Wan, Runpeng Yu, et al.2025 · 64 citations
  51. Phi-4-reasoning Technical ReportarXiv:2504.21318Marah Abdin, Sahaj Agarwal, Ahmed Awadallah, et al.2025 · 64 citations
  52. SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software EvolutionConference on Neural Information Processing Systems (NeurIPS)Yuxiang Wei, Olivier Duchenne, Jade Copet, et al.2025 · 64 citations
  53. MARIO: MAth Reasoning with code Interpreter Output - A Reproducible PipelineFindings of the Association for Computational LinguisticsMinpeng Liao, Chengxi Li, Wei Luo, et al.2024 · 64 citations
  54. Learning From Mistakes Makes LLM Better ReasonerarXiv:2310.20689Shengnan An, Zexiong Ma, Zeqi Lin, et al.2023 · 64 citations
  55. Monitoring Reasoning Models for Misbehavior and the Risks of Promoting ObfuscationarXiv:2503.11926Bowen Baker, Joost Huizinga, Leo Gao, et al.2025 · 63 citations
  56. PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mingyang Song, Zhaochen Su, Xiaoye Qu, et al.2025 · 63 citations
  57. VinePPO: Refining Credit Assignment in RL Training of LLMsarXiv:2410.01679Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, et al.2024 · 63 citations
  58. Rephrase and Respond: Let Large Language Models Ask Better Questions for ThemselvesarXiv:2311.04205Yihe Deng, Weitong Zhang, Zixiang Chen, et al.2023 · 62 citations
  59. Deep Think with ConfidencearXiv:2508.15260Yichao Fu, Xuewei Wang, Yuandong Tian, et al.2025 · 61 citations
  60. Teaching Large Language Models to Reason with Reinforcement LearningarXiv:2403.04642Alex Havrilla, Yuqing Du, Sharath Chandra Raparthy, et al.2024 · 61 citations
  61. ZebraLogic: On the Scaling Limits of LLMs for Logical ReasoningarXiv:2502.01100Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, et al.2025 · 60 citations
  62. Rho-1: Not All Tokens Are What You NeedarXiv:2404.07965Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.2024 · 59 citations
  63. 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
  64. Free Process Rewards without Process LabelsarXiv:2412.01981Lifan Yuan, Wendi Li, Huayu Chen, et al.2024 · 58 citations
  65. Does Circuit Analysis Interpretability Scale? Evidence from Multiple Choice Capabilities in ChinchillaarXiv:2307.09458Tom Lieberum, Matthew Rahtz, Janos Kramar, et al.2023 · 58 citations
  66. 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
  67. 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
  68. Teaching Arithmetic to Small TransformersarXiv:2307.03381Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, et al.2023 · 57 citations
  69. OlympicArena: Benchmarking Multi-discipline Cognitive Reasoning for Superintelligent AIConference on Neural Information Processing Systems (NeurIPS)Zhen Huang, Zengzhi Wang, Shijie Xia, et al.2024 · 56 citations
  70. A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and BeyondarXiv:2503.21614Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.2025 · 55 citations
  71. PlanGenLLMs: A Modern Survey of LLM Planning CapabilitiesAnnual Meeting of the Association for Computational Linguistics (ACL)Hui Wei, Zihao Zhang, Shenghua He, et al.2025 · 55 citations
  72. 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
  73. Spurious Rewards: Rethinking Training Signals in RLVRarXiv:2506.10947Rulin Shao, Shuyue Stella Li, Rui Xin, et al.2025 · 53 citations
  74. Q*: Improving Multi-step Reasoning for LLMs with Deliberative PlanningarXiv:2406.14283Chaojie Wang, Yanchen Deng, Zhiyi Lyu, et al.2024 · 53 citations
  75. RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and StylearXiv:2410.16184Yantao Liu, Zijun Yao, Rui Min, et al.2024 · 53 citations
  76. Trial and Error: Exploration-Based Trajectory Optimization of LLM AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Yifan Song, Da Yin, Xiang Yue, et al.2024 · 53 citations
  77. From Decoding to Meta-Generation: Inference-time Algorithms for Large Language ModelsarXiv:2406.16838Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.2024 · 51 citations
  78. LightThinker: Thinking Step-by-Step CompressionConference on Empirical Methods in Natural Language Processing (EMNLP)Jintian Zhang, Yuqi Zhu, Mengshu Sun, et al.2025 · 50 citations
  79. ZeroSearch: Incentivize the Search Capability of LLMs without SearchingarXiv:2505.04588Hao Sun, Zile Qiao, Jiayan Guo, et al.2025 · 50 citations
  80. Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference FeedbackConference on Neural Information Processing Systems (NeurIPS)Hamish Ivison, Yizhong Wang, Jiacheng Liu, et al.2024 · 50 citations
  81. Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI SynergyarXiv:2507.01352Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.2025 · 48 citations
  82. ARGS: Alignment as Reward-Guided SearcharXiv:2402.01694Maxim Khanov, Jirayu Burapacheep, Yixuan Li2024 · 46 citations
  83. Don't throw away your value model! Generating more preferable text with Value-Guided Monte-Carlo Tree Search decodingarXiv:2309.15028Jiacheng Liu, Andrew Cohen, Ramakanth Pasunuru, et al.2023 · 46 citations
  84. Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic ToolsAnnual Meeting of the Association for Computational Linguistics (ACL)Junde Wu, Jiayuan Zhu, Yuyuan Liu, et al.2025 · 45 citations
  85. 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
  86. AdaptThink: Reasoning Models Can Learn When to ThinkConference on Empirical Methods in Natural Language Processing (EMNLP)Jiajie Zhang, Nianyi Lin, Lei Hou, et al.2025 · 44 citations
  87. Augmenting Math Word Problems via Iterative Question ComposingProceedings of the AAAI Conference on Artificial IntelligenceHaoxiong Liu, Yifan Zhang, Yifan Luo, et al.2024 · 44 citations
  88. General-Reasoner: Advancing LLM Reasoning Across All DomainsConference on Neural Information Processing Systems (NeurIPS)Xueguang Ma, Qian Liu, Dongfu Jiang, et al.2025 · 43 citations
  89. 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
  90. Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM ReasoningarXiv:2412.09078Zhenni Bi, Kai Han, Chuanjian Liu, et al.2024 · 43 citations
  91. 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
  92. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
  93. DeepResearch Bench: A Comprehensive Benchmark for Deep Research AgentsarXiv:2506.11763Mingxuan Du, Benfeng Xu, Chiwei Zhu, et al.2025 · 41 citations
  94. Towards Robust Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Thang Luong, Dawsen Hwang, Hoang H Nguyen, et al.2025 · 40 citations
  95. Conifer: Improving Complex Constrained Instruction-Following Ability of Large Language ModelsarXiv:2404.02823Haoran Sun, Lixin Liu, Junjie Li, et al.2024 · 40 citations
  96. NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning ModelarXiv:2508.14444NVIDIA: Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, et al.2025 · 39 citations
  97. Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?Annual Meeting of the Association for Computational Linguistics (ACL)Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, et al.2025 · 38 citations
  98. Efficient Reasoning Models: A SurveyarXiv:2504.10903Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.2025 · 37 citations
  99. SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language ModelsarXiv:2504.11468Hardy Chen, Haoqin Tu, Fali Wang, et al.2025 · 37 citations
  100. Direct Judgement Preference OptimizationConference on Empirical Methods in Natural Language Processing (EMNLP)PeiFeng Wang, Austin Xu, Yilun Zhou, et al.2025 · 35 citations

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