🧑‍🔬 Who cites Zheng Yuan

983 citations of their works from 896 papers of our library (of the 141,840 whose bibliographies we read) · 74 with a page here, the most cited first · ← Zheng Yuan

1. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,593 citations
2. A Survey on Evaluation of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyYupeng Chang, Xu Wang, Jindong Wang, et al.2023 · 3,641 citations
3. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,863 citations
4. DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsarXiv:2402.03300Zhihong Shao, Peiyi Wang, Qihao Zhu, et al.2024 · 2,013 citations
5. Qwen Technical ReportarXiv:2309.16609Jinze Bai, Shuai Bai, Yunfei Chu, et al.2023 · 1,645 citations
6. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,286 citations
7. A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the UglyarXiv:2312.02003Yifan Yao, Jinhao Duan, Kaidi Xu, et al.2023 · 1,182 citations
8. WizardLM: Empowering large pre-trained language models to follow complex instructionsInternational Conference on Learning Representations (ICLR)Can Xu, Qingfeng Sun, Kai Zheng, et al.2023 · 731 citations
9. HybridFlow: A Flexible and Efficient RLHF FrameworkarXiv:2409.19256Guangming Sheng, Chi Zhang, Zilingfeng Ye, et al.2024 · 598 citations
10. MetaMath: Bootstrap Your Own Mathematical Questions for Large Language ModelsarXiv:2309.12284Longhui Yu, Weisen Jiang, Han Shi, et al.2023 · 556 citations
11. Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model ParametersarXiv:2408.03314Charlie Snell, Jaehoon Lee, Kelvin Xu, et al.2024 · 524 citations
12. 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 · 482 citations
13. Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-ImprovementarXiv:2409.12122An Yang, Beichen Zhang, Binyuan Hui, et al.2024 · 410 citations
14. Yi: Open Foundation Models by 01.AIarXiv:2403.04652Alex Young, Bei Chen, Chao Li, et al.2024 · 402 citations
15. A Survey on Large Language Models for Code GenerationarXiv:2406.00515Juyong Jiang, Fan Wang, Jiasi Shen, et al.2024 · 366 citations
16. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-InstructarXiv:2308.09583Haipeng Luo, Qingfeng Sun, Can Xu, et al.2023 · 366 citations
17. MAmmoTH: Building Math Generalist Models through Hybrid Instruction TuningarXiv:2309.05653Xiang Yue, Xingwei Qu, Ge Zhang, et al.2023 · 288 citations
18. HuatuoGPT, Towards Taming Language Model to Be a DoctorFindings of the Association for Computational LinguisticsHongbo Zhang, Junying Chen, Feng Jiang, et al.2023 · 282 citations
19. 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 · 279 citations
20. Scaling Relationship on Learning Mathematical Reasoning with Large Language ModelsarXiv:2308.01825Zheng Yuan, Hongyi Yuan, Chengpeng Li, et al.2023 · 252 citations
21. RAFT: Reward rAnked FineTuning for Generative Foundation Model AlignmentarXiv:2304.06767Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.2023 · 239 citations
22. TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 226 citations
23. ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem SolvingarXiv:2309.17452Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.2023 · 222 citations
24. 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 · 220 citations
25. Fine-Grained Human Feedback Gives Better Rewards for Language Model TrainingarXiv:2306.01693Zeqiu Wu, Yushi Hu, Weijia Shi, et al.2023 · 212 citations
26. Safe RLHF: Safe Reinforcement Learning from Human FeedbackarXiv:2310.12773Josef Dai, Xuehai Pan, Ruiyang Sun, et al.2023 · 207 citations
27. 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 · 205 citations
28. Aligning Large Language Models with Human: A SurveyarXiv:2307.12966Yufei Wang, Wanjun Zhong, Liangyou Li, et al.2023 · 199 citations
29. 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 · 197 citations
30. RRHF: Rank Responses to Align Language Models with Human Feedback without tearsarXiv:2304.05302Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.2023 · 194 citations
31. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 189 citations
32. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesarXiv:2406.06608Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 187 citations
33. Preference Ranking Optimization for Human AlignmentProceedings of the AAAI Conference on Artificial IntelligenceFeifan Song, Bowen Yu, Minghao Li, et al.2023 · 183 citations
34. Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 179 citations
35. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 178 citations
36. OpenChat: Advancing Open-source Language Models with Mixed-Quality DataarXiv:2309.11235Guan Wang, Sijie Cheng, Xianyuan Zhan, et al.2023 · 172 citations
37. Large Language Model UnlearningConference on Neural Information Processing Systems (NeurIPS)Yuanshun Yao, Xiaojun Xu, Yang Liu2023 · 165 citations
38. 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
39. 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
40. Many-Shot In-Context LearningConference on Neural Information Processing Systems (NeurIPS)Rishabh Agarwal, Avi Singh, Lei M. Zhang, et al.2024 · 134 citations
41. Beyond Human Data: Scaling Self-Training for Problem-Solving with Language ModelsarXiv:2312.06585Avi Singh, John D. Co-Reyes, Rishabh Agarwal, et al.2023 · 134 citations
42. Understanding the Effects of RLHF on LLM Generalisation and DiversityarXiv:2310.06452Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, et al.2023 · 131 citations
43. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 123 citations
44. LEXTREME: A Multi-Lingual and Multi-Task Benchmark for the Legal DomainFindings of the Association for Computational LinguisticsJoel Niklaus, Veton Matoshi, Pooja Rani, et al.2023 · 123 citations
45. Encode, Tag, Realize: High-Precision Text EditingarXiv:1909.01187Eric Malmi, Sebastian Krause, Sascha Rothe, et al.2019 · 118 citations
46. Demystifying Long Chain-of-Thought Reasoning in LLMsarXiv:2502.03373Edward Yeo, Yuxuan Tong, Morry Niu, et al.2025 · 113 citations
47. V-STaR: Training Verifiers for Self-Taught ReasonersarXiv:2402.06457Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.2024 · 111 citations
48. Statistical Rejection Sampling Improves Preference OptimizationarXiv:2309.06657Tianqi Liu, Yao Zhao, Rishabh Joshi, et al.2023 · 101 citations
49. MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical ReasoningarXiv:2310.03731Ke Wang, Houxing Ren, Aojun Zhou, et al.2023 · 98 citations
50. Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Keming Lu, Bowen Yu, Chang Zhou, et al.2024 · 86 citations
51. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 85 citations
52. Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language GenerationTransactions of the Association for Computational Linguistics (TACL)Patrick Fernandes, Aman Madaan, Emmy Liu, et al.2023 · 84 citations
53. Mitigating the Alignment Tax of RLHFConference on Empirical Methods in Natural Language Processing (EMNLP)Yong Lin, Hangyu Lin, Wei Xiong, et al.2024 · 82 citations
54. Artificial Error Generation with Machine Translation and Syntactic PatternsWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Marek Rei, Mariano Felice, Zheng Yuan, et al.2017 · 82 citations
55. Neural Network Translation Models for Grammatical Error CorrectionarXiv:1606.00189Shamil Chollampatt, Kaveh Taghipour, Hwee Tou Ng2016 · 79 citations
56. SynGEC: Syntax-Enhanced Grammatical Error Correction with a Tailored GEC-Oriented ParserConference on Empirical Methods in Natural Language Processing (EMNLP)Yue Zhang, Bo Zhang, Zhenghua Li, et al.2022 · 76 citations
57. 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
58. SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-ScalingarXiv:2312.15166Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.2023 · 75 citations
59. Wider and Deeper LLM Networks are Fairer LLM EvaluatorsarXiv:2308.01862Xinghua Zhang, Bowen Yu, Haiyang Yu, et al.2023 · 74 citations
60. BRIGHT: A Realistic and Challenging Benchmark for Reasoning-Intensive RetrievalarXiv:2407.12883Hongjin Su, Howard Yen, Mengzhou Xia, et al.2024 · 70 citations
61. Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Haoxiang Wang, Yong Lin, Wei Xiong, et al.2024 · 66 citations
62. Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-TuningarXiv:2402.00530Ming Li, Yong Zhang, Shwai He, et al.2024 · 60 citations
63. CMB: A Comprehensive Medical Benchmark in ChinesearXiv:2308.08833Xidong Wang, Guiming Hardy Chen, Dingjie Song, et al.2023 · 54 citations
64. The Unreasonable Effectiveness of Transformer Language Models in Grammatical Error CorrectionWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Dimitris Alikaniotis, Vipul Raheja2019 · 52 citations
65. Interpretability for Language Learners Using Example-Based Grammatical Error CorrectionAnnual Meeting of the Association for Computational Linguistics (ACL)Masahiro Kaneko, Sho Takase, Ayana Niwa, et al.2022 · 47 citations
66. Advancements in Arabic Grammatical Error Detection and Correction: An Empirical InvestigationConference on Empirical Methods in Natural Language Processing (EMNLP)Bashar Alhafni, Go Inoue, Christian Khairallah, et al.2023 · 38 citations
67. Machine Translation Meta Evaluation through Translation Accuracy Challenge SetsComputational LinguisticsNikita Moghe, Arnisa Fazla, Chantal Amrhein, et al.2025 · 28 citations
68. Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal SamplingarXiv:2408.16737Hritik Bansal, Arian Hosseini, Rishabh Agarwal, et al.2024 · 26 citations
69. Skywork-Math: Data Scaling Laws for Mathematical Reasoning in Large Language Models — The Story Goes OnarXiv:2407.08348Liang Zeng, Liangjun Zhong, Liang Zhao, et al.2024 · 14 citations
70. Targeted Syntactic Evaluation for Grammatical Error CorrectionAomi Koyama, Masato Mita, Su-Youn Yoon, et al.2025 · 3 citations
71. Beyond Error Categories: A Contextual Approach of Evaluating Emerging Spell and Grammar CheckersSIGUL Joint Workshop with ELE, EURALI, and DCLRL: Towards Inclusivity and Equality: Language Resources and Technologies for Under-Resourced and Endangered LanguagesÞórunn Arnardóttir, Svanhvít Lilja Ingólfsdóttir, Haukur Barri Símonarson, et al.2024 · 1 citation
72. Development of an Extractive Title Generation System Using Titles of Papers of Top Conferences for Intermediate English StudentsarXiv:2110.04204 · 2021 10th International Congress on Advanced Applied Informatics (IIAI-AAI), pp.59-64, 2021Kento Kaku, Masato Kikuchi, Tadachika Ozono, et al.2021 · 1 citation
73. Corpora Generation for Urdu Grammatical Error CorrectionFindings of the Association for Computational LinguisticsSyed Ahad, Burhanuddin Aliasghar Ezzi, Muhammad Arsalan Hussain, et al.2026
74. STAGEET: Stage-wise Typed Edit Tagging for Grammatical Error Correction with Arabic as a Case StudyarXiv:2608.28614Wenjie Lou, Alaa Mamdouh Akef2026

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