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Who cites Han Shi

717 citations of their works from 709 papers of our library (of the 149,439 whose bibliographies we read) · 211 with a page here, the most cited first · page 1 of 3 · 1–100 · ← Han Shi

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  1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
  2. A Survey on Evaluation of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyYupeng Chang, Xu Wang, Jindong Wang, et al.2023 · 3,648 citations
  3. DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsarXiv:2402.03300Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.2024 · 2,115 citations
  4. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,669 citations
  5. s1: Simple test-time scalingConference on Empirical Methods in Natural Language Processing (EMNLP)Niklas Muennighoff, Zitong Yang, Weijia Shi, et al.2025 · 608 citations
  6. MetaMath: Bootstrap Your Own Mathematical Questions for Large Language ModelsarXiv:2309.12284Longhui Yu, Weisen Jiang, Han Shi, et al.2023 · 565 citations
  7. How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source SuitesScience China Information SciencesZhe Chen, Weiyun Wang, Hao Tian, et al.2024 · 541 citations
  8. Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human AnnotationsAnnual Meeting of the Association for Computational Linguistics (ACL)Peiyi Wang, Lei Li, Zhihong Shao, et al.2024 · 497 citations
  9. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructarXiv:2308.09583Haipeng Luo, Qingfeng Sun, Can Xu, et al.2023 · 372 citations
  10. MAmmoTH: Building Math Generalist Models through Hybrid Instruction TuningarXiv:2309.05653Xiang Yue, Xingwei Qu, Ge Zhang, et al.2023 · 295 citations
  11. Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time ScalingarXiv:2412.05271Zhe Chen, Weiyun Wang, Yue Cao, et al.2024 · 287 citations
  12. Llemma: An Open Language Model For MathematicsarXiv:2310.10631Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.2023 · 286 citations
  13. Large Language Models for Mathematical Reasoning: Progresses and ChallengesConference of the European Chapter of the Association for Computational Linguistics (EACL)Janice Ahn, Rishu Verma, Renze Lou, et al.2024 · 280 citations
  14. On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A SurveyFindings of the Association for Computational LinguisticsLin Long, Rui Wang, Ruixuan Xiao, et al.2024 · 237 citations
  15. What matters when building vision-language models?Conference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.2024 · 212 citations
  16. LIMO: Less is More for ReasoningarXiv:2502.03387Yixin Ye, Zhen Huang, Yang Xiao, et al.2025 · 209 citations
  17. ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree SearchConference on Neural Information Processing Systems (NeurIPS)Dan Zhang, Sining Zhoubian, Ziniu Hu, et al.2024 · 200 citations
  18. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
  19. 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
  20. Scaling Synthetic Data Creation with 1,000,000,000 PersonasarXiv:2406.20094Tao Ge, Xin Chan, Xiaoyang Wang, et al.2024 · 171 citations
  21. Improve Mathematical Reasoning in Language Models by Automated Process SupervisionarXiv:2406.06592Liangchen Luo, Yinxiao Liu, Rosanne Liu, et al.2024 · 168 citations
  22. CultureLLM: Incorporating Cultural Differences into Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Cheng Li, Mengzhou Chen, Jindong Wang, et al.2024 · 162 citations
  23. 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
  24. Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
  25. 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
  26. 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
  27. JudgeLM: Fine-tuned Large Language Models are Scalable JudgesarXiv:2310.17631Lianghui Zhu, Xinggang Wang, Xinlong Wang2023 · 145 citations
  28. DeepInception: Hypnotize Large Language Model to Be JailbreakerarXiv:2311.03191Xuan Li, Zhanke Zhou, Jianing Zhu, et al.2023 · 141 citations
  29. DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal UnderstandingarXiv:2412.10302Zhiyu Wu, Xiaokang Chen, Zizheng Pan, et al.2024 · 137 citations
  30. 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
  31. 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
  32. 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
  33. 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
  34. AlphaMath Almost Zero: Process Supervision without ProcessConference on Neural Information Processing Systems (NeurIPS)Guoxin Chen, Minpeng Liao, Chengxi Li, et al.2024 · 120 citations
  35. Demystifying Long Chain-of-Thought Reasoning in LLMsarXiv:2502.03373Edward Yeo, Yuxuan Tong, Morry Niu, et al.2025 · 119 citations
  36. Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations
  37. SaulLM-7B: A pioneering Large Language Model for LawarXiv:2403.03883Pierre Colombo, Telmo Pessoa Pires, Malik Boudiaf, et al.2024 · 119 citations
  38. DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree SearcharXiv:2408.08152Huajian Xin, Z. Z. Ren, Junxiao Song, et al.2024 · 116 citations
  39. DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic DataarXiv:2405.14333Huajian Xin, Daya Guo, Zhihong Shao, et al.2024 · 111 citations
  40. Orca-Math: Unlocking the potential of SLMs in Grade School MatharXiv:2402.14830Arindam Mitra, Hamed Khanpour, Corby Rosset, et al.2024 · 111 citations
  41. 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
  42. Transformers for Tabular Data Representation: A Survey of Models and ApplicationsTransactions of the Association for Computational Linguistics (TACL)Gilbert Badaro, Mohammed Saeed, Paolo Papotti2023 · 104 citations
  43. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 103 citations
  44. 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
  45. ToolACE: Winning the Points of LLM Function CallingarXiv:2409.00920Weiwen Liu; Xu Huang; Xingshan Zeng; Xinlong Hao; Shuai Yu; Dexun Li; Shuai Wang; Weinan Gan; Zhengying Liu; Yuanqing Yu; Zezhong Wang; Yuxian Wang; Wu Ning; Yutai Hou; Bin Wang; Chuhan Wu; Xinzhi Wang; Yong Liu; Yasheng Wang; Duyu Tang; Dandan Tu; Lifeng Shang; Xin Jiang; Ruiming Tang; Defu Lian; Qun Liu;, Enhong Chen2024 · 101 citations
  46. 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
  47. Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language ModelsarXiv:2601.18734Siyan Zhao, Zhihui Xie, Mengchen Liu, et al.2026 · 97 citations
  48. MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 96 citations
  49. 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
  50. Kimina-Prover Preview: Towards Large Formal Reasoning Models with Reinforcement LearningarXiv:2504.11354Haiming Wang, Mert Unsal, Xiaohan Lin, et al.2025 · 92 citations
  51. SeaLLMs — Large Language Models for Southeast AsiaarXiv:2312.00738Xuan-Phi Nguyen, Wenxuan Zhang, Xin Li, et al.2023 · 92 citations
  52. InternLM-Math: Open Math Large Language Models Toward Verifiable ReasoningarXiv:2402.06332Huaiyuan Ying, Shuo Zhang, Linyang Li, et al.2024 · 90 citations
  53. 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
  54. Retrieval-Augmented Generation with Graphs (GraphRAG)arXiv:2501.00309Haoyu Han, Yu Wang, Harry Shomer, et al.2025 · 87 citations
  55. PiSSA: Principal Singular Values and Singular Vectors Adaptation of Large Language ModelsarXiv:2404.02948Fanxu Meng, Zhaohui Wang, Muhan Zhang2024 · 86 citations
  56. Evaluating Mathematical Reasoning Beyond AccuracyProceedings of the AAAI Conference on Artificial IntelligenceShijie Xia, Xuefeng Li, Yixin Liu, et al.2024 · 85 citations
  57. OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction DataarXiv:2410.01560Shubham Toshniwal, Wei Du, Ivan Moshkov, et al.2024 · 85 citations
  58. 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
  59. MathScale: Scaling Instruction Tuning for Mathematical ReasoningarXiv:2403.02884Zhengyang Tang, Xingxing Zhang, Benyou Wang, et al.2024 · 83 citations
  60. Smaug: Fixing Failure Modes of Preference Optimisation with DPO-PositivearXiv:2402.13228Arka Pal, Deep Karkhanis, Samuel Dooley, et al.2024 · 82 citations
  61. TableLlama: Towards Open Large Generalist Models for TablesarXiv:2311.09206Tianshu Zhang, Xiang Yue, Yifei Li, et al.2023 · 82 citations
  62. DART-Math: Difficulty-Aware Rejection Tuning for Mathematical Problem-SolvingarXiv:2407.13690Yuxuan Tong, Xiwen Zhang, Rui Wang, et al.2024 · 81 citations
  63. Lean Workbook: A large-scale Lean problem set formalized from natural language math problemsConference on Neural Information Processing Systems (NeurIPS)Huaiyuan Ying, Zijian Wu, Yihan Geng, et al.2024 · 80 citations
  64. 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
  65. 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
  66. Common 7B Language Models Already Possess Strong Math CapabilitiesarXiv:2403.04706Chen Li, Weiqi Wang, Jingcheng Hu, et al.2024 · 79 citations
  67. LEGO-Prover: Neural Theorem Proving with Growing LibrariesarXiv:2310.00656Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.2023 · 79 citations
  68. 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
  69. OVM, Outcome-supervised Value Models for Planning in Mathematical ReasoningFindings of the Association for Computational LinguisticsFei Yu, Anningzhe Gao, Benyou Wang2023 · 78 citations
  70. SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-ScalingarXiv:2312.15166Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.2023 · 77 citations
  71. G-LLaVA: Solving Geometric Problem with Multi-Modal Large Language ModelarXiv:2312.11370Jiahui Gao, Renjie Pi, Jipeng Zhang, et al.2023 · 76 citations
  72. 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
  73. 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
  74. GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and BenchmarkingarXiv:2305.15066Jiayan Guo, Lun Du, Hengyu Liu, et al.2023 · 75 citations
  75. Benchmarking Benchmark Leakage in Large Language ModelsarXiv:2404.18824Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.2024 · 73 citations
  76. MathBench: Evaluating the Theory and Application Proficiency of LLMs with a Hierarchical Mathematics BenchmarkFindings of the Association for Computational LinguisticsHongwei Liu, Zilong Zheng, Yuxuan Qiao, et al.2024 · 70 citations
  77. Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language ModelsarXiv:2402.13064Haoran Li, Qingxiu Dong, Zhengyang Tang, et al.2024 · 65 citations
  78. We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?arXiv:2407.01284Runqi Qiao, Qiuna Tan, Guanting Dong, et al.2024 · 65 citations
  79. 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
  80. Learning From Mistakes Makes LLM Better ReasonerarXiv:2310.20689Shengnan An, Zexiong Ma, Zeqi Lin, et al.2023 · 64 citations
  81. 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
  82. Rephrase and Respond: Let Large Language Models Ask Better Questions for ThemselvesarXiv:2311.04205Yihe Deng, Weitong Zhang, Zixiang Chen, et al.2023 · 62 citations
  83. Small Models Struggle to Learn from Strong ReasonersFindings of the Association for Computational LinguisticsYuetai Li, Xiang Yue, Zhangchen Xu, et al.2025 · 61 citations
  84. MAPO: Advancing Multilingual Reasoning through Multilingual-Alignment-as-Preference OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Shuaijie She, Wei Zou, Shujian Huang, et al.2024 · 59 citations
  85. Rho-1: Not All Tokens Are What You NeedarXiv:2404.07965Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.2024 · 59 citations
  86. MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Zimu Lu, Aojun Zhou, Houxing Ren, et al.2024 · 58 citations
  87. LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuningarXiv:2308.03303Longteng Zhang, Lin Zhang, Shaohuai Shi, et al.2023 · 58 citations
  88. Unintended Impacts of LLM Alignment on Global RepresentationAnnual Meeting of the Association for Computational Linguistics (ACL)Michael J Ryan, William Held, Diyi Yang2024 · 57 citations
  89. 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
  90. SciAgent: Tool-augmented Language Models for Scientific ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Yubo Ma, Zhibin Gou, Junheng Hao, et al.2024 · 55 citations
  91. InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HDConference on Neural Information Processing Systems (NeurIPS)Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.2024 · 54 citations
  92. Q*: Improving Multi-step Reasoning for LLMs with Deliberative PlanningarXiv:2406.14283Chaojie Wang, Yanchen Deng, Zhiyi Lyu, et al.2024 · 53 citations
  93. Stable LM 2 1.6B Technical ReportarXiv:2402.17834Marco Bellagente, Jonathan Tow, Dakota Mahan, et al.2024 · 46 citations
  94. EuroLLM-9B: Technical ReportarXiv:2506.04079Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.2025 · 45 citations
  95. 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
  96. NVLM: Open Frontier-Class Multimodal LLMsarXiv:2409.11402Wenliang Dai, Nayeon Lee, Boxin Wang, 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. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
  99. InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and OutputarXiv:2407.03320Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.2024 · 39 citations
  100. Efficient Reasoning Models: A SurveyarXiv:2504.10903Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.2025 · 37 citations

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