🧑‍🔬 Who cites Nick Haber

198 citations of their works from 194 papers of our library (of the 149,439 whose bibliographies we read) · 80 with a page here, the most cited first · ← Nick Haber

1. s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (EMNLP)Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.2025 · 608 citations
2. LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for CodearXiv:2403.07974Naman Jain, King Han, Alex Gu, et al.2024 · 578 citations
3. SWE-agent: Agent-Computer Interfaces Enable Automated Software EngineeringConference on Neural Information Processing Systems (NeurIPS)John Yang, Carlos E. Jimenez, Alexander Wettig, et al.2024 · 552 citations
4. Self-collaboration Code Generation via ChatGPTACM Transactions on Software Engineering and MethodologyYihong Dong; Xue Jiang; Zhi Jin;, Ge Li2023 · 319 citations
5. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
6. 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
7. Can Language Models Solve Graph Problems in Natural Language?Conference on Neural Information Processing Systems (NeurIPS)Heng Wang, Shangbin Feng, Tianxing He, et al.2023 · 124 citations
8. 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
9. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 122 citations
10. Large Language Models as General Pattern MachinesarXiv:2307.04721Suvir Mirchandani, Fei Xia, Pete Florence, et al.2023 · 88 citations
11. 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
12. 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
13. DeepMath-103K: A Large-Scale, Challenging, Decontaminated, and Verifiable Mathematical Dataset for Advancing ReasoningarXiv:2504.11456Zhiwei He, Tian Liang, Jiahao Xu, et al.2025 · 78 citations
14. Large Language Models as Analogical ReasonersarXiv:2310.01714Michihiro Yasunaga, Xinyun Chen, Yujia Li, et al.2023 · 74 citations
15. Kevin: Multi-Turn RL for Generating CUDA KernelsarXiv 2025Carlo Baronio, Pietro Marsella, Ben Pan, et al.2025 · 69 citations
16. Evaluation of OpenAI o1: Opportunities and Challenges of AGIarXiv:2409.18486Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.2024 · 64 citations
17. 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
18. Clover: Closed-Loop Verifiable Code GenerationLecture notes in computer scienceChuyue Sun, Ying Sheng, Oded Padon, et al.2024 · 56 citations
19. DeepReview: Improving LLM-based Paper Review with Human-like Deep Thinking ProcessAnnual Meeting of the Association for Computational Linguistics (ACL)Minjun Zhu, Yixuan Weng, Linyi Yang, et al.2025 · 52 citations
20. Formal Mathematical Reasoning: A New Frontier in AIarXiv:2412.16075Kaiyu Yang, Gabriel Poesia, Jingxuan He, et al.2024 · 49 citations
21. DeepSeek-R1 Thoughtology: Let's think about LLM ReasoningarXiv:2504.07128Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, et al.2025 · 47 citations
22. Seed-Prover: Deep and Broad Reasoning for Automated Theorem ProvingarXiv:2507.23726Luoxin Chen, Jinming Gu, Liankai Huang, et al.2025 · 46 citations
23. A Survey on Deep Learning for Theorem ProvingarXiv:2404.09939Zhaoyu Li, Jialiang Sun, Logan Murphy, et al.2024 · 46 citations
24. Learning to Reason without External RewardsarXiv:2505.19590Xuandong Zhao, Zhewei Kang, Aosong Feng, et al.2025 · 44 citations
25. Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language ModelsarXiv:2502.17387Alon Albalak, Duy Phung, Nathan Lile, et al.2025 · 43 citations
26. STP: Self-play LLM Theorem Provers with Iterative Conjecturing and ProvingarXiv:2502.00212Kefan Dong, Tengyu Ma2025 · 43 citations
27. 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
28. Evaluating Language Models for Mathematics through InteractionsarXiv:2306.01694Katherine M. Collins, Albert Q. Jiang, Simon Frieder, et al.2023 · 40 citations
29. Lean Copilot: Large Language Models as Copilots for Theorem Proving in LeanarXiv:2404.12534Peiyang Song, Kaiyu Yang, Anima Anandkumar2024 · 39 citations
30. A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super IntelligencearXiv:2507.21046Huan-ang Gao, Jiayi Geng, Wenyue Hua, et al.2025 · 36 citations
31. OpenCodeReasoning: Advancing Data Distillation for Competitive CodingarXiv:2504.01943Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar, et al.2025 · 33 citations
32. Can Language Models Solve Olympiad Programming?arXiv:2404.10952Quan Shi, Michael Tang, Karthik Narasimhan, et al.2024 · 28 citations
33. Scaling Test-Time Compute Without Verification or RL is SuboptimalarXiv:2502.12118Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.2025 · 26 citations
34. Linguistic Generalizability of Test-Time Scaling in Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Guijin Son, Jiwoo Hong, Hyunwoo Ko, et al.2025 · 24 citations
35. Symbolic Regression with a Learned Concept LibraryConference on Neural Information Processing Systems (NeurIPS)Arya Grayeli, Atharva Sehgal, Omar Costilla-Reyes, et al.2024 · 23 citations
36. AI4Research: A Survey of Artificial Intelligence for Scientific ResearchScience China Information SciencesQiguang Chen, Mingda Yang, Libo Qin, et al.2025 · 21 citations
37. CodeI/O: Condensing Reasoning Patterns via Code Input-Output PredictionarXiv:2502.07316Junlong Li, Daya Guo, Dejian Yang, et al.2025 · 21 citations
38. From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement LearningConference on Empirical Methods in Natural Language Processing (EMNLP)David Dinucu-Jianu, Jakub Macina, Nico Daheim, et al.2025 · 19 citations
39. Seed-Prover 1.5: Mastering Undergraduate-Level Theorem Proving via Learning from ExperiencearXiv:2512.17260Jiangjie Chen, Wenxiang Chen, Jiacheng Du, et al.2025 · 19 citations
40. The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research IdeasarXiv:2506.20803Chenglei Si, Tatsunori Hashimoto, Diyi Yang2025 · 19 citations
41. Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning ChainsConference on Neural Information Processing Systems (NeurIPS)Wenhui Tan, Jiaze Li, Jianzhong Ju, et al.2025 · 19 citations
42. Evaluating statistical language models as pragmatic reasonersarXiv:2305.01020Benjamin Lipkin, Lionel Wong, Gabriel Grand, et al.2023 · 18 citations
43. LLM-Assisted Code Cleaning For Training Accurate Code GeneratorsarXiv:2311.14904Naman Jain, Tianjun Zhang, Wei-Lin Chiang, et al.2023 · 17 citations
44. Can Large Reasoning Models Self-Train?arXiv:2505.21444Sheikh Shafayat, Fahim Tajwar, Ruslan Salakhutdinov, et al.2025 · 16 citations
45. From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical DebuggingIEEE/ACM International Conference on Software Engineering (ICSE)Yuling Shi, Songsong Wang, Chengcheng Wan, et al.2024 · 15 citations
46. Generating Code World Models with Large Language Models Guided by Monte Carlo Tree SearcharXiv:2405.15383Nicola Dainese, Matteo Merler, Minttu Alakuijala, et al.2024 · 14 citations
47. CodeR: Issue Resolving with Multi-Agent and Task GraphsarXiv:2406.01304Dong Chen, Shaoxin Lin, Muhan Zeng, et al.2024 · 13 citations
48. Psychometric Alignment: Capturing Human Knowledge Distributions via Language ModelsarXiv:2407.15645Joy He-Yueya, Wanjing Anya Ma, Kanishk Gandhi, et al.2024 · 12 citations
49. The Open Proof Corpus: A Large-Scale Study of LLM-Generated Mathematical ProofsarXiv:2506.21621Jasper Dekoninck, Ivo Petrov, Kristian Minchev, et al.2025 · 11 citations
50. 100 Days After DeepSeek-R1: A Survey on Replication Studies and More Directions for Reasoning Language ModelsarXiv:2505.00551Chong Zhang, Yue Deng, Xiang Lin, et al.2025 · 9 citations
51. CodeS: Natural Language to Code Repository via Multi-Layer SketcharXiv:2403.16443Daoguang Zan, Ailun Yu, Wei Liu, et al.2024 · 9 citations
52. Brains vs. Bytes: Evaluating LLM Proficiency in Olympiad MathematicsarXiv:2504.01995Hamed Mahdavi, Alireza Hashemi, Majid Daliri, et al.2025 · 8 citations
53. ReForm: Reflective Autoformalization with Prospective Bounded Sequence OptimizationarXiv:2510.24592Guoxin Chen, Jing Wu, Xinjie Chen, et al.2025 · 8 citations
54. Evaluating and Optimizing Educational Content with Large Language Model JudgmentsarXiv:2403.02795Joy He-Yueya, Noah D. Goodman, Emma Brunskill2024 · 7 citations
55. Language Models as Compilers: Simulating Pseudocode Execution Improves Algorithmic Reasoning in Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Hyungjoo Chae, Yeonghyeon Kim, Seungone Kim, et al.2024 · 7 citations
56. InnovatorBench: Evaluating Agents' Ability to Conduct Innovative LLM ResearcharXiv:2510.27598Yunze Wu, Dayuan Fu, Weiye Si, et al.2025 · 6 citations
57. Metastable Dynamics of Chain-of-Thought Reasoning: Provable Benefits of Search, RL and DistillationarXiv:2502.01694Juno Kim, Denny Wu, Jason Lee, et al.2025 · 6 citations
58. AI for Auto-Research: Roadmap & User GuidearXiv:2605.18661Lingdong Kong, Xian Sun, Wei Chow, et al.2026 · 5 citations
59. PaCoRe: Learning to Scale Test-Time Compute with Parallel Coordinated ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Jingcheng Hu, Yinmin Zhang, Shijie Shang, et al.2026 · 5 citations
60. Ring-lite: Scalable Reasoning via C3PO-Stabilized Reinforcement Learning for LLMsarXiv:2506.14731Ling Team, Bin Hu, Cai Chen, et al.2025 · 5 citations
61. EngiBench: A Benchmark for Evaluating Large Language Models on Engineering Problem SolvingFindings of the Association for Computational LinguisticsXiyuan Zhou, Xinlei Wang, Yirui He, et al.2026 · 3 citations
62. SHAPE: Unifying Safety, Helpfulness and Pedagogy for Educational LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Sihang Zhao, Kangrui Yu, Youliang Yuan, et al.2026 · 2 citations
63. Training AI Scientists to Replicate ResearcharXiv:2608.13331Damon Falck, Samer Sabri, Anja Surina, et al.2026 · 2 citations
64. Distillation Traps and Guards: A Calibration Knob for LLM DistillabilityAnnual Meeting of the Association for Computational Linguistics (ACL)Weixiao Zhan, Yongcheng Jing, Leszek Rutkowski, et al.2026 · 1 citation
65. Evaluating Answer Leakage Robustness of LLM Tutors against Adversarial Student AttacksAnnual Meeting of the Association for Computational Linguistics (ACL)Jin Zhao, Marta Knežević, Tanja Käser2026 · 1 citation
66. Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Yifan Wang, Shiyu Li, Peiming Li, et al.2026 · 1 citation
67. Consistency of LLMs to Comparative Statements in Mathematical Reasoning TasksLanguage Resources and Evaluation Conference (LREC)Aidan W. San, Daniel Juyoung Son, Xiaodong Liu, et al.2026
68. Contract-Coding: Towards Repo-Level Generation via Structured Symbolic ParadigmFindings of the Association for Computational LinguisticsYilin, Lujin Zhao, Yijie Shi2026
69. Entropy Scheduling in Reinforcement Learning for Large Language ModelsFindings of the Association for Computational LinguisticsXingjin Wang, Howe Tissue, Lu Wang, et al.2026
70. GR1: Reinforcement-Enhanced LLM for Geoscience ReasoningFindings of the Association for Computational LinguisticsYule Xie, Jiaxin Ding, Cheng Deng, et al.2026
71. MMSciCode: Real-world Evaluation of Multilingual Multi-Discipline Scientific Research CodingAnnual Meeting of the Association for Computational Linguistics (ACL)Xue Xia, Zheyuan Yang, Arman Cohan, et al.2026
72. Model-Based Imaginative Planning for Embodied AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Junru Song, Hengzhe Jin, Yucong Huang, et al.2026
73. RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Jize Wang, Han Wu, Zhiyuan You, et al.2026
74. SD-E2: Semantic Exploration for Reasoning Under Token BudgetsFindings of the Association for Computational LinguisticsKshitij Mishra, Nils Lukas, Salem Lahlou2026
75. Social Welfare Function Leaderboard: On the Emergence of LLM Agents as the Welfare DictatorFindings of the Association for Computational LinguisticsZhengliang Shi, Ruotian Ma, Jen-tse Huang, et al.2026
76. STCOR: A Trilevel Syllogism-Driven Reasoning FrameworkWorkshop on Argument MiningKeying Yang, Hao Wang, Chengtao Jian, et al.2026
77. Tracing the Light of Thought: A Probabilistic Self- and Cross-Consistency Verification Mechanism Improving Mathematical Reasoning in LLMsFindings of the Association for Computational LinguisticsXiaoyang Liu, Dawei Wang, Tian Li, et al.2026
78. Training Verifier to Assessing Complex Real-World Tool-Use TrajectoriesFindings of the Association for Computational LinguisticsLinzhuang Sun, Mingyang Chen, Hao Liang, et al.2026
79. WildSci: Advancing Scientific Reasoning from In-the-Wild LiteratureFindings of the Association for Computational LinguisticsTengxiao Liu, Deepak Nathani, Zekun Li, et al.2026
80. 🧑‍🍳 Cooking Up Creativity: Enhancing LLM Creativity through Structured RecombinationTransactions of the Association for Computational Linguistics (TACL)Moran Mizrahi, Chen Shani, Gabriel Stanovsky, et al.2026

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