🧑‍🔬 Who cites Run-Ze Fan

129 citations of their works from 129 papers of our library (of the 149,439 whose bibliographies we read) · 30 with a page here, the most cited first · ← Run-Ze Fan

1. Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive SurveyarXiv:2403.14608Zeyu Han, Chao Gao, Jinyang Liu, et al.2024 · 240 citations
2. Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language ModelsarXiv:2405.01535Seungone Kim, Juyoung Suk, Shayne Longpre, et al.2024 · 234 citations
3. LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation MethodsarXiv:2412.05579Haitao Li, Qian Dong, Junjie Chen, et al.2024 · 195 citations
4. JudgeLM: Fine-tuned Large Language Models are Scalable JudgesarXiv:2310.17631Lianghui Zhu, Xinggang Wang, Xinlong Wang2023 · 145 citations
5. Judging the Judges: A Systematic Study of Position Bias in LLM-as-a-JudgeInternational Joint Conference on Natural Language Processing (IJCNLP)Lin Shi, Chiyu Ma, Wenhua Liang, et al.2025 · 71 citations
6. 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
7. CritiqueLLM: Towards an Informative Critique Generation Model for Evaluation of Large Language Model GenerationarXiv:2311.18702Pei Ke, Bosi Wen, Zhuoer Feng, et al.2023 · 69 citations
8. VIEScore: Towards Explainable Metrics for Conditional Image Synthesis EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Max Ku, Dongfu Jiang, Cong Wei, et al.2024 · 68 citations
9. OffsetBias: Leveraging Debiased Data for Tuning EvaluatorsFindings of the Association for Computational LinguisticsJunsoo Park, Seungyeon Jwa, Ren Meiying, et al.2024 · 67 citations
10. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
11. Leveraging Large Language Models for NLG Evaluation: Advances and ChallengesConference on Empirical Methods in Natural Language Processing (EMNLP)Zhen Li, Xiaohan Xu, Tao Shen, et al.2024 · 63 citations
12. MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language BenchmarkarXiv:2402.04788Dongping Chen, Ruoxi Chen, Shilin Zhang, et al.2024 · 60 citations
13. Direct Judgement Preference OptimizationConference on Empirical Methods in Natural Language Processing (EMNLP)PeiFeng Wang, Austin Xu, Yilun Zhou, et al.2025 · 35 citations
14. CompassVerifier: A Unified and Robust Verifier for LLMs Evaluation and Outcome RewardConference on Empirical Methods in Natural Language Processing (EMNLP)Shudong Liu, Hongwei Liu, Junnan Liu, et al.2025 · 16 citations
15. Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual SettingsAnnual Meeting of the Association for Computational Linguistics (ACL)Austin Xu, Srijan Bansal, Yifei Ming, et al.2025 · 14 citations
16. CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Hongchao Jiang, Yiming Chen, Yushi Cao, et al.2026 · 13 citations
17. From Calculation to Adjudication: Examining LLM judges on Mathematical Reasoning TasksarXiv:2409.04168Andreas Stephan, Dawei Zhu, Matthias Aßenmacher, et al.2024 · 13 citations
18. Reason Only When Needed: Efficient Generative Reward Modeling via Model-Internal UncertaintyFindings of the Association for Computational LinguisticsChao Xue, Yao Wang, Mengqiao Liu, et al.2026 · 8 citations
19. Halu-J: Critique-Based Hallucination JudgearXiv:2407.12943Binjie Wang, Steffi Chern, Ethan Chern, et al.2024 · 8 citations
20. How Long Reasoning Chains Influence LLMs' Judgment of Answer FactualityAnnual Meeting of the Association for Computational Linguistics (ACL)Minzhu Tu, Shiyu Ni, Keping Bi2026 · 3 citations
21. J4R: Learning to Judge with Equivalent Initial State Group Relative Policy OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Austin Xu, Yilun Zhou, Xuan-Phi Nguyen, et al.2026 · 3 citations
22. Outcome Accuracy is Not Enough: Aligning the Reasoning Process of Reward ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Binghai Wang, Yantao Liu, Yuxuan Liu, et al.2026 · 3 citations
23. Graders Should Cheat: Privileged Information Enables Expert-Level Automated EvaluationsConference on Empirical Methods in Natural Language Processing (EMNLP)Jin Peng Zhou, Séb Arnold, Nan Ding, et al.2025 · 3 citations
24. Decentralized Arena: Towards Democratic and Scalable Automatic Evaluation of Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Yanbin Yin, Kun Zhou, Zhen Wang, et al.2026 · 1 citation
25. EvolvR: Self-Evolving Pairwise Reasoning for Story Evaluation to Enhance GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Xinda Wang, Zhengxu Hou, Yangshijie Zhang, et al.2026 · 1 citation
26. IF-CRITIC: Towards a Fine-Grained LLM Critic for Instruction-Following EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Bosi Wen, Yilin Niu, Cunxiang Wang, et al.2026 · 1 citation
27. A Survey on Parameter-efficient Fine-tuning of Large Models: Techniques, Trends, and Challenges (大模型参数高效微调方法综述: 技术、趋势与挑战)Acta Automatica Sinica (自动化学报)Anda Tang (唐岸达), Zhouchen Lin (林宙辰)2026
28. Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty EstimationAnnual Meeting of the Association for Computational Linguistics (ACL)Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.2026
29. Mitigating Judgment Preference Bias in Large Language Models through Group-Based PollingFindings of the Association for Computational LinguisticsShuliang Liu, Zhipeng Xu, Zhenghao Liu, et al.2026
30. Soft Orthogonal Low-Rank Adaptation for Knowledge Sharing in Large Language Model Continual LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yitong Wang, Xue Han, WenChun Gao, et al.2026

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