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Who cites Lorenz Kuhn

1,758 citations of their works from 1,695 papers of our library (of the 149,439 whose bibliographies we read) · 493 with a page here, the most cited first · page 1 of 5 · 1–100 · ← Lorenz Kuhn

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  1. Instruction Tuning for Large Language Models: A SurveyACM Computing SurveysShengyu Zhang, Linfeng Dong, Xiaoya Li, et al.2023 · 520 citations
  2. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
  3. CRITIC: Large Language Models Can Self-Correct with Tool-Interactive CritiquingarXiv:2305.11738Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 326 citations
  4. Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement LearningarXiv:2503.09516Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.2025 · 322 citations
  5. Accelerating scientific discovery with Co-ScientistNatureJuraj Gottweis, Wei-Hung Weng, Alexander Daryin, et al.2025 · 224 citations
  6. Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
  7. Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?arXiv:2504.13837 · NeurIPS 2025 Oral; ICML 2025 AI4MATH workshop best paperYang Yue, Zhiqi Chen, Rui Lu, et al.2025 · 216 citations
  8. Search-o1: Agentic Search-Enhanced Large Reasoning ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Xiaoxi Li, Guanting Dong, Jiajie Jin, et al.2025 · 211 citations
  9. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
  10. InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and EfficiencyarXiv:2508.18265Weiyun Wang, Zhangwei Gao, Lixin Gu, et al.2025 · 179 citations
  11. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 176 citations
  12. GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation ModelsarXiv:2508.06471Aohan Zeng, Xin Lv, Qinkai Zheng, et al.2025 · 166 citations
  13. SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-trainingarXiv:2501.17161Tianzhe Chu, Yuexiang Zhai, Jihan Yang, et al.2025 · 160 citations
  14. A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
  15. 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
  16. Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and MitigationarXiv:2305.15852Niels Mundler, Jingxuan He, Slobodan Jenko, et al.2023 · 152 citations
  17. Process Reinforcement through Implicit RewardsarXiv:2502.01456Ganqu Cui, Lifan Yuan, Zefan Wang, et al.2025 · 151 citations
  18. Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 149 citations
  19. rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep ThinkingarXiv:2501.04519Xinyu Guan, Li Lyna Zhang, Yifei Liu, et al.2025 · 146 citations
  20. R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement LearningarXiv:2503.05592Huatong Song, Jinhao Jiang, Yingqian Min, et al.2025 · 141 citations
  21. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
  22. The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree SearcharXiv:2504.08066Yutaro Yamada, Robert Tjarko Lange, Cong Lu, et al.2025 · 129 citations
  23. Evaluating the Moral Beliefs Encoded in LLMsConference on Neural Information Processing Systems (NeurIPS)Nino Scherrer, Claudia Shi, Amir Feder, et al.2023 · 129 citations
  24. Fine-tuning Language Models for FactualityarXiv:2311.08401Katherine Tian, Eric Mitchell, Huaxiu Yao, et al.2023 · 127 citations
  25. LM vs LM: Detecting Factual Errors via Cross ExaminationConference on Empirical Methods in Natural Language Processing (EMNLP)Roi Cohen, May Hamri, Mor Geva, et al.2023 · 126 citations
  26. L1: Controlling How Long A Reasoning Model Thinks With Reinforcement LearningarXiv:2503.04697Pranjal Aggarwal, Sean Welleck2025 · 125 citations
  27. Mem0: Building Production-Ready AI Agents with Scalable Long-Term MemoryarXiv:2504.19413Prateek Chhikara, Dev Khant, Saket Aryan, et al.2025 · 125 citations
  28. 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
  29. 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
  30. The Alignment Problem from a Deep Learning PerspectivearXiv:2209.00626Richard Ngo, Lawrence Chan, Soren Mindermann2022 · 121 citations
  31. Agentless: Demystifying LLM-based Software Engineering AgentsarXiv:2407.01489Chunqiu Steven Xia, Yinlin Deng, Soren Dunn, et al.2024 · 117 citations
  32. UI-TARS: Pioneering Automated GUI Interaction with Native AgentsarXiv:2501.12326Yujia Qin, Yining Ye, Junjie Fang, et al.2025 · 112 citations
  33. INSIDE: LLMs' Internal States Retain the Power of Hallucination DetectionarXiv:2402.03744Chao Chen, Kai Liu, Ze Chen, et al.2024 · 108 citations
  34. Reasoning Models Don't Always Say What They ThinkarXiv:2505.05410Yanda Chen, Joe Benton, Ansh Radhakrishnan, et al.2025 · 106 citations
  35. 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
  36. 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
  37. The Entropy Mechanism of Reinforcement Learning for Reasoning Language ModelsarXiv:2505.22617Ganqu Cui, Yuchen Zhang, Jiacheng Chen, et al.2025 · 101 citations
  38. MathArena: Evaluating LLMs on Uncontaminated Math CompetitionsConference on Neural Information Processing Systems (NeurIPS)Mislav Balunović, Jasper Dekoninck, Ivo Petrov, et al.2025 · 99 citations
  39. Chain of Draft: Thinking Faster by Writing LessarXiv:2502.18600Silei Xu, Wenhao Xie, Lingxiao Zhao, et al.2025 · 98 citations
  40. A Survey of Confidence Estimation and Calibration in Large Language ModelsarXiv:2311.08298Jiahui Geng, Fengyu Cai, Yuxia Wang, et al.2023 · 97 citations
  41. Fact-Checking the Output of Large Language Models via Token-Level Uncertainty QuantificationFindings of the Association for Computational LinguisticsEkaterina Fadeeva, Aleksandr Rubashevskii, Artem Shelmanov, et al.2024 · 96 citations
  42. Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement LearningarXiv:2504.11354Haiming Wang, Mert Unsal, Xiaohan Lin, et al.2025 · 92 citations
  43. Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language ModelsarXiv:2503.06749Wenxuan Huang, Bohan Jia, Zijie Zhai, et al.2025 · 92 citations
  44. 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
  45. 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
  46. SuperGPQA: Scaling LLM Evaluation across 285 Graduate DisciplinesarXiv:2502.14739M-A-P Team, Xinrun Du, Yifan Yao, et al.2025 · 89 citations
  47. ReTool: Reinforcement Learning for Strategic Tool Use in LLMsarXiv:2504.11536Jiazhan Feng, Shijue Huang, Xingwei Qu, et al.2025 · 88 citations
  48. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
  49. Selectively Answering Ambiguous QuestionsConference on Empirical Methods in Natural Language Processing (EMNLP)Jeremy Cole, Michael Zhang, Daniel Gillick, et al.2023 · 84 citations
  50. 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
  51. TTRL: Test-Time Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Yuxin Zuo, Kaiyan Zhang, Li Sheng, et al.2025 · 76 citations
  52. Reinforcement Learning via Self-DistillationarXiv:2601.20802Jonas Hubotter, Frederike Lubeck, Lejs Behric, et al.2026 · 74 citations
  53. Training Language Models to Reason EfficientlyConference on Neural Information Processing Systems (NeurIPS)Daman Arora, Andrea Zanette2025 · 74 citations
  54. Rubrics as Rewards: Reinforcement Learning Beyond Verifiable DomainsarXiv:2507.17746Anisha Gunjal, Anthony Wang, Elaine Lau, et al.2025 · 73 citations
  55. 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
  56. Quantifying Uncertainty in Answers from any Language Model and Enhancing their TrustworthinessAnnual Meeting of the Association for Computational Linguistics (ACL)Jiuhai Chen, Jonas Mueller2024 · 72 citations
  57. 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
  58. 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
  59. Competitive Programming with Large Reasoning ModelsarXiv:2502.06807OpenAI: Ahmed El-Kishky, Alexander Wei, Andre Saraiva, et al.2025 · 68 citations
  60. Learning to Reason under Off-Policy GuidanceConference on Neural Information Processing Systems (NeurIPS)Jianhao Yan, Yafu Li, Zican Hu, et al.2025 · 68 citations
  61. LLMs Know More Than They Show: On the Intrinsic Representation of LLM HallucinationsarXiv:2410.02707Hadas Orgad, Michael Toker, Zorik Gekhman, et al.2024 · 68 citations
  62. 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
  63. Seed1.5-VL Technical ReportarXiv:2505.07062Dong Guo, Faming Wu, Feida Zhu, et al.2025 · 67 citations
  64. ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement LearningarXiv:2504.01296Bairu Hou, Yang Zhang, Jiabao Ji, et al.2025 · 67 citations
  65. Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language ModelsFindings of the Association for Computational LinguisticsAlfonso Amayuelas, Kyle Wong, Liangming Pan, et al.2024 · 66 citations
  66. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
  67. MedXpertQA: Benchmarking Expert-Level Medical Reasoning and UnderstandingarXiv:2501.18362Yuxin Zuo, Shang Qu, Yifei Li, et al.2025 · 65 citations
  68. 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
  69. Phi-4-reasoning Technical ReportarXiv:2504.21318Marah Abdin, Sahaj Agarwal, Ahmed Awadallah, et al.2025 · 64 citations
  70. 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
  71. Monitoring Reasoning Models for Misbehavior and the Risks of Promoting ObfuscationarXiv:2503.11926Bowen Baker, Joost Huizinga, Leo Gao, et al.2025 · 63 citations
  72. VinePPO: Refining Credit Assignment in RL Training of LLMsarXiv:2410.01679Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance, et al.2024 · 63 citations
  73. Deep Think with ConfidencearXiv:2508.15260Yichao Fu, Xuewei Wang, Yuandong Tian, et al.2025 · 61 citations
  74. ZebraLogic: On the Scaling Limits of LLMs for Logical ReasoningarXiv:2502.01100Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, et al.2025 · 60 citations
  75. 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
  76. 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
  77. 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
  78. 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
  79. Explore, Establish, Exploit: Red Teaming Language Models from ScratcharXiv:2306.09442Stephen Casper, Jason Lin, Joe Kwon, et al.2023 · 52 citations
  80. 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
  81. ZeroSearch: Incentivize the Search Capability of LLMs without SearchingarXiv:2505.04588Hao Sun, Zile Qiao, Jiayan Guo, et al.2025 · 50 citations
  82. Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI SynergyarXiv:2507.01352Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.2025 · 48 citations
  83. Unfamiliar Finetuning Examples Control How Language Models HallucinateConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Katie Kang, Eric Wallace, Claire Tomlin, et al.2025 · 47 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. 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
  86. Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM ReasoningarXiv:2412.09078Zhenni Bi, Kai Han, Chuanjian Liu, et al.2024 · 43 citations
  87. LUQ: Long-text Uncertainty Quantification for LLMsConference on Empirical Methods in Natural Language Processing (EMNLP)Caiqi Zhang, Fangyu Liu, Marco Basaldella, et al.2024 · 42 citations
  88. DeepResearch Bench: A Comprehensive Benchmark for Deep Research AgentsarXiv:2506.11763Mingxuan Du, Benfeng Xu, Chiwei Zhu, et al.2025 · 41 citations
  89. Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?Conference on Empirical Methods in Natural Language Processing (EMNLP)Gal Yona, Roee Aharoni, Mor Geva2024 · 40 citations
  90. 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
  91. Efficient Reasoning Models: A SurveyarXiv:2504.10903Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.2025 · 37 citations
  92. 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
  93. 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
  94. People who frequently use ChatGPT for writing tasks are accurate and robust detectors of AI-generated textAnnual Meeting of the Association for Computational Linguistics (ACL)Jenna Russell, Marzena Karpinska, Mohit Iyyer2025 · 33 citations
  95. Knowledge Boundary of Large Language Models: A SurveyAnnual Meeting of the Association for Computational Linguistics (ACL)Moxin Li, Yong Zhao, Wenxuan Zhang, et al.2025 · 30 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. SAC3: Reliable Hallucination Detection in Black-Box Language Models via Semantic-aware Cross-check ConsistencyarXiv:2311.01740Jiaxin Zhang, Zhuohang Li, Kamalika Das, et al.2023 · 28 citations
  98. S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Ruotian Ma, Peisong Wang, Cheng Liu, et al.2025 · 26 citations
  99. UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement LearningarXiv:2509.02544Haoming Wang, Haoyang Zou, Huatong Song, et al.2025 · 26 citations
  100. Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Haoxiang Sun, Yingqian Min, Zhipeng Chen, et al.2026 · 25 citations

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