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Who cites Eric Tang

2,177 citations of their works from 2,153 papers of our library (of the 150,927 whose bibliographies we read) · 844 with a page here, the most cited first · page 4 of 9 · 301–400 · ← Eric Tang

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  1. Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI SynergyarXiv:2507.01352Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.2025 · 48 citations
  2. Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language ModelsarXiv:2406.02061Marianna Nezhurina, Lucia Cipolina-Kun, Mehdi Cherti, et al.2024 · 48 citations
  3. DeepSeek-R1 Thoughtology: Let's think about LLM ReasoningarXiv:2504.07128Sara Vera Marjanovic, Arkil Patel, Vaibhav Adlakha, et al.2025 · 47 citations
  4. The Unreasonable Effectiveness of Entropy Minimization in LLM ReasoningConference on Neural Information Processing Systems (NeurIPS)Shivam Agarwal, Zimin Zhang, Lifan Yuan, et al.2025 · 47 citations
  5. Towards System 2 Reasoning in LLMs: Learning How to Think With Meta Chain-of-ThoughtarXiv:2501.04682Violet Xiang, Charlie Snell, Kanishk Gandhi, et al.2025 · 47 citations
  6. MixEval: Deriving Wisdom of the Crowd from LLM Benchmark MixturesConference on Neural Information Processing Systems (NeurIPS)Jinjie Ni, Fuzhao Xue, Xiang Yue, et al.2024 · 47 citations
  7. NPHardEval: Dynamic Benchmark on Reasoning Ability of Large Language Models via Complexity ClassesAnnual Meeting of the Association for Computational Linguistics (ACL)Lizhou Fan, Wenyue Hua, Lingyao Li, et al.2024 · 47 citations
  8. An In-Context Learning Agent for Formal Theorem-ProvingarXiv:2310.04353Amitayush Thakur, George Tsoukalas, Yeming Wen, et al.2023 · 47 citations
  9. MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math DataScientific DataMeng Fang, Xiangpeng Wan, Fei Lu, et al.2024 · 46 citations
  10. MathChat: Converse to Tackle Challenging Math Problems with LLM AgentsarXiv:2306.01337Yiran Wu; Feiran Jia; Shaokun Zhang; Hangyu Li; Erkang Zhu; Yue Wang; Yin Tat Lee; Richard Peng; Qingyun Wu;, Chi Wang2023 · 46 citations
  11. EuroLLM-9B: Technical ReportarXiv:2506.04079Pedro Henrique Martins, Joao Alves, Patrick Fernandes, et al.2025 · 45 citations
  12. Don't Trust: Verify — Grounding LLM Quantitative Reasoning with AutoformalizationarXiv:2403.18120Jin Peng Zhou, Charles Staats, Wenda Li, et al.2024 · 45 citations
  13. 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
  14. Key-Point-Driven Data Synthesis with its Enhancement on Mathematical ReasoningProceedings of the AAAI Conference on Artificial IntelligenceYiming Huang, Xiao Liu, Yeyun Gong, et al.2024 · 45 citations
  15. Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem SolvingarXiv:2405.12205Aniket Didolkar, Anirudh Goyal, Nan Rosemary Ke, et al.2024 · 45 citations
  16. TinyGSM: achieving >80% on GSM8k with small language modelsarXiv:2312.09241Bingbin Liu, Sebastien Bubeck, Ronen Eldan, et al.2023 · 45 citations
  17. Entropy-Aware On-Policy Distillation of Language ModelsarXiv:2603.07079Woogyeol Jin, Taywon Min, Yongjin Yang, et al.2026 · 44 citations
  18. 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 · 44 citations
  19. Learning to Reason without External RewardsarXiv:2505.19590Xuandong Zhao, Zhewei Kang, Aosong Feng, et al.2025 · 44 citations
  20. Thought Anchors: Which LLM Reasoning Steps Matter?arXiv:2506.19143Paul C. Bogdan, Uzay Macar, Neel Nanda, et al.2025 · 44 citations
  21. 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
  22. DSBench: How Far Are Data Science Agents from Becoming Data Science Experts?arXiv:2409.07703Liqiang Jing, Zhehui Huang, Xiaoyang Wang, et al.2024 · 44 citations
  23. HyperCLOVA X Technical ReportarXiv:2404.01954Kang Min Yoo, Jaegeun Han, Sookyo In, et al.2024 · 44 citations
  24. MAP-Neo: Highly Capable and Transparent Bilingual Large Language Model SeriesarXiv:2405.19327Ge Zhang, Scott Qu, Jiaheng Liu, et al.2024 · 44 citations
  25. NVLM: Open Frontier-Class Multimodal LLMsarXiv:2409.11402Wenliang Dai, Nayeon Lee, Boxin Wang, et al.2024 · 44 citations
  26. 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
  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. Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM ReasoningarXiv:2412.09078Zhenni Bi, Kai Han, Chuanjian Liu, et al.2024 · 43 citations
  29. MuggleMath: Assessing the Impact of Query and Response Augmentation on Math ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Chengpeng Li, Zheng Yuan, Hongyi Yuan, et al.2024 · 43 citations
  30. Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process SupervisionFindings of the Association for Computational LinguisticsZihan Wang, Yunxuan Li, Yuexin Wu, et al.2024 · 43 citations
  31. MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard PerturbationsarXiv:2502.06453Kaixuan Huang, Jiacheng Guo, Zihao Li, et al.2025 · 42 citations
  32. AgentInstruct: Toward Generative Teaching with Agentic FlowsarXiv:2407.03502Arindam Mitra, Luciano Del Corro, Guoqing Zheng, et al.2024 · 42 citations
  33. Programming Refusal with Conditional Activation SteeringarXiv:2409.05907Bruce W. Lee, Inkit Padhi, Karthikeyan Natesan Ramamurthy, et al.2024 · 42 citations
  34. 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
  35. Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time ScalingarXiv:2502.06703Runze Liu, Junqi Gao, Jian Zhao, et al.2025 · 41 citations
  36. DynaMath: A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language ModelsarXiv:2411.00836Chengke Zou, Xingang Guo, Rui Yang, et al.2024 · 41 citations
  37. Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved SamplingarXiv:2410.11325Wenda Xu, Rujun Han, Zifeng Wang, et al.2024 · 41 citations
  38. GPT Can Solve Mathematical Problems Without a CalculatorarXiv:2309.03241Zhen Yang, Ming Ding, Qingsong Lv, et al.2023 · 41 citations
  39. SALMON: Self-Alignment with Instructable Reward ModelsarXiv:2310.05910Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.2023 · 41 citations
  40. A Systematic Survey of Automatic Prompt Optimization TechniquesConference on Empirical Methods in Natural Language Processing (EMNLP)Kiran Ramnath, Kang Zhou, Sheng Guan, et al.2025 · 40 citations
  41. Towards Robust Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Thang Luong, Dawsen Hwang, Hoang H Nguyen, et al.2025 · 40 citations
  42. Observational Scaling Laws and the Predictability of Language Model PerformancearXiv:2405.10938Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 40 citations
  43. Let's reward step by step: Step-Level reward model as the Navigators for ReasoningarXiv:2310.10080Qianli Ma, Haotian Zhou, Tingkai Liu, et al.2023 · 40 citations
  44. A Survey of Frontiers in LLM Reasoning: Inference Scaling, Learning to Reason, and Agentic SystemsarXiv:2504.09037Zixuan Ke, Fangkai Jiao, Yifei Ming, et al.2025 · 39 citations
  45. 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
  46. Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer ModelsarXiv:2504.03624NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.2025 · 38 citations
  47. Code Execution with Pre-trained Language ModelsFindings of the Association for Computational LinguisticsChenxiao Liu, Shuai Lu, Weizhu Chen, et al.2023 · 38 citations
  48. AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward ModelingFindings of the Association for Computational LinguisticsZihan Liu, Yang Chen, Mohammad Shoeybi, et al.2025 · 37 citations
  49. Efficient Reasoning Models: A SurveyarXiv:2504.10903Sicheng Feng, Gongfan Fang, Xinyin Ma, et al.2025 · 37 citations
  50. MiMo: Unlocking the Reasoning Potential of Language Model — From Pretraining to PosttrainingarXiv:2505.07608LLM-Core Xiaomi, Bingquan Xia, Bowen Shen, et al.2025 · 37 citations
  51. RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?arXiv:2501.11284Haotian Xu, Xing Wu, Weinong Wang, et al.2025 · 37 citations
  52. Reinforcement Learning for Reasoning in Small LLMs: What Works and What Doesn'tarXiv:2503.16219Quy-Anh Dang, Chris Ngo2025 · 37 citations
  53. SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language ModelsConference on Neural Information Processing Systems (NeurIPS)Dan Zhang, Ziniu Hu, Sining Zhoubian, et al.2024 · 37 citations
  54. A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to ReproducibilityarXiv:2504.07086Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao, et al.2025 · 36 citations
  55. KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for CodingFindings of the Association for Computational LinguisticsZhangchen Xu, Yang Liu, Yueqin Yin, et al.2025 · 36 citations
  56. Evaluating Frontier Models for Dangerous CapabilitiesarXiv:2403.13793Mary Phuong, Matthew Aitchison, Elliot Catt, et al.2024 · 36 citations
  57. MR-GSM8K: A Meta-Reasoning Benchmark for Large Language Model EvaluationarXiv:2312.17080Zhongshen Zeng, Pengguang Chen, Shu Liu, et al.2023 · 36 citations
  58. AbstentionBench: Reasoning LLMs Fail on Unanswerable QuestionsConference on Neural Information Processing Systems (NeurIPS)Polina Kirichenko, Mark Ibrahim, Kamalika Chaudhuri, et al.2025 · 35 citations
  59. MasRouter: Learning to Route LLMs for Multi-Agent SystemsAnnual Meeting of the Association for Computational Linguistics (ACL)Yanwei Yue, Guibin Zhang, Boyang Liu, et al.2025 · 35 citations
  60. Vision-Language Models Can Self-Improve Reasoning via ReflectionConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Kanzhi Cheng, Li YanTao, Fangzhi Xu, et al.2025 · 35 citations
  61. Functional Benchmarks for Robust Evaluation of Reasoning Performance, and the Reasoning GaparXiv:2402.19450Saurabh Srivastava, Annarose M B, Anto P, et al.2024 · 35 citations
  62. Self-Refine Instruction-Tuning for Aligning Reasoning in Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Leonardo Ranaldi, Andre Freitas2024 · 35 citations
  63. Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model TutorsConference on Empirical Methods in Natural Language Processing (EMNLP)Nico Daheim, Jakub Macina, Manu Kapur, et al.2024 · 35 citations
  64. Echo Chamber: RL Post-training Amplifies Behaviors Learned in PretrainingarXiv:2504.07912Rosie Zhao, Alexandru Meterez, Sham Kakade, et al.2025 · 34 citations
  65. CHAMP: A Competition-level Dataset for Fine-Grained Analyses of LLMs' Mathematical Reasoning CapabilitiesFindings of the Association for Computational LinguisticsYujun Mao, Yoon Kim, Yilun Zhou2024 · 34 citations
  66. Symbolic Learning Enables Self-Evolving AgentsarXiv:2406.18532Wangchunshu Zhou, Yixin Ou, Shengwei Ding, et al.2024 · 34 citations
  67. MiMo-VL Technical ReportarXiv:2506.03569Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.2025 · 33 citations
  68. OpenCodeReasoning: Advancing Data Distillation for Competitive CodingarXiv:2504.01943Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar, et al.2025 · 33 citations
  69. Process-Driven Autoformalization in Lean 4arXiv:2406.01940Jianqiao Lu, Yingjia Wan, Zhengying Liu, et al.2024 · 33 citations
  70. Evaluating Language Models as Synthetic Data GeneratorsAnnual Meeting of the Association for Computational Linguistics (ACL)Seungone Kim, Juyoung Suk, Xiang Yue, et al.2025 · 32 citations
  71. Revisiting On-Policy Distillation: Empirical Failure Modes and Simple FixesarXiv:2603.25562Yuqian Fu, Haohuan Huang, Kaiwen Jiang, et al.2026 · 31 citations
  72. How to Evaluate Reward Models for RLHFarXiv:2410.14872Evan Frick, Tianle Li, Connor Chen, et al.2024 · 31 citations
  73. Learning Planning-based Reasoning by Trajectories Collection and Process Reward SynthesizingConference on Empirical Methods in Natural Language Processing (EMNLP)Fangkai Jiao, Chengwei Qin, Zhengyuan Liu, et al.2024 · 31 citations
  74. AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Yang Chen, Zhuolin Yang, Zihan Liu, et al.2025 · 30 citations
  75. ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique PipelinearXiv:2404.02893Yifan Xu, Xiao Liu, Xinghan Liu, et al.2024 · 30 citations
  76. Language Models as Science TutorsarXiv:2402.11111Alexis Chevalier, Jiayi Geng, Alexander Wettig, et al.2024 · 30 citations
  77. InftyThink: Breaking the Length Limits of Long-Context Reasoning in Large Language ModelsarXiv:2503.06692Yuchen Yan, Yongliang Shen, Yang Liu, et al.2025 · 29 citations
  78. SEA-LION: Southeast Asian Languages in One NetworkInternational Joint Conference on Natural Language Processing (IJCNLP)Raymond Ng, Thanh Ngan Nguyen, Huang Yuli, et al.2025 · 29 citations
  79. Towards Effective and Efficient Continual Pre-training of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.2025 · 29 citations
  80. JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis ModelsConference on Neural Information Processing Systems (NeurIPS)Kun Zhou, Beichen Zhang, Jiapeng Wang, et al.2024 · 29 citations
  81. LangBridge: Multilingual Reasoning Without Multilingual SupervisionAnnual Meeting of the Association for Computational Linguistics (ACL)Dongkeun Yoon, Joel Jang, Sungdong Kim, et al.2024 · 29 citations
  82. MUSTARD: Mastering Uniform Synthesis of Theorem and Proof DataarXiv:2402.08957 (ICLR 2024 spotlight)Yinya Huang, Xiaohan Lin, Zhengying Liu, et al.2024 · 29 citations
  83. Decomposing the Enigma: Subgoal-based Demonstration Learning for Formal Theorem ProvingarXiv:2305.16366Xueliang Zhao, Wenda Li, Lingpeng Kong2023 · 29 citations
  84. T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference ScalingarXiv:2501.11651Zhenyu Hou, Xin Lv, Rui Lu, et al.2025 · 28 citations
  85. AutoPSV: Automated Process-Supervised VerifierConference on Neural Information Processing Systems (NeurIPS)Jianqiao Lu, Zhiyang Dou, Hongru Wang, et al.2024 · 28 citations
  86. SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific LiteratureConference on Empirical Methods in Natural Language Processing (EMNLP)David Wadden, Kejian Shi, Jacob Morrison, et al.2025 · 27 citations
  87. MATHSENSEI: A Tool-Augmented Large Language Model for Mathematical ReasoningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Debrup Das, Debopriyo Banerjee, Somak Aditya, et al.2024 · 27 citations
  88. Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal SamplingarXiv:2408.16737Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.2024 · 27 citations
  89. A Survey on Large Language Models for Mathematical ReasoningACM Computing SurveysPeng-Yuan Wang, Tian-Shuo Liu, Chenyang Wang, et al.2025 · 26 citations
  90. NaturalReasoning: Reasoning in the Wild with 2.8M Challenging QuestionsConference on Neural Information Processing Systems (NeurIPS)Weizhe Yuan, Jane Yu, Song Jiang, et al.2025 · 26 citations
  91. Scaling Test-Time Compute Without Verification or RL is SuboptimalarXiv:2502.12118Amrith Setlur, Nived Rajaraman, Sergey Levine, et al.2025 · 26 citations
  92. 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
  93. TreeRL: LLM Reinforcement Learning with On-Policy Tree SearchAnnual Meeting of the Association for Computational Linguistics (ACL)Zhenyu Hou, Ziniu Hu, Yujiang Li, et al.2025 · 26 citations
  94. 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
  95. Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM ReasoningarXiv:2507.00432Maggie Huan, Yuetai Li, Tuney Zheng, et al.2025 · 25 citations
  96. FuseChat: Knowledge Fusion of Chat ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Fanqi Wan, Longguang Zhong, Ziyi Yang, et al.2025 · 25 citations
  97. Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept SpaceConference on Neural Information Processing Systems (NeurIPS)Zhen Zhang, Xuehai He, Weixiang Yan, et al.2025 · 25 citations
  98. CiteME: Can Language Models Accurately Cite Scientific Claims?Conference on Neural Information Processing Systems (NeurIPS)Ori Press, Andreas Hochlehnert, Ameya Prabhu, et al.2024 · 25 citations
  99. Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by TencentarXiv:2411.02265Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.2024 · 25 citations
  100. IberoBench: A Benchmark for LLM Evaluation in Iberian LanguagesInternational Conference on Computational Linguistics (COLING)Irene Baucells, Javier Aula-Blasco, Iria de-Dios-Flores, et al.2025 · 24 citations

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