🔗 Who cites «ODIN: Disentangled Reward Mitigates Hacking in RLHF»

37 papers of our library cite it (of the 149,439 whose bibliographies we read) · 16 with a page here, the most cited first · ← back to «ODIN: Disentangled Reward Mitigates Hacking in RLHF»

1. Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-ExpertsFindings of the Association for Computational LinguisticsHaoxiang Wang, Wei Xiong, Tengyang Xie, et al.2024 · 153 citations
2. Disentangling Length from Quality in Direct Preference OptimizationFindings of the Association for Computational LinguisticsRyan Park, Rafael Rafailov, Stefano Ermon, et al.2024 · 105 citations
3. Goedel-Prover: A Frontier Model for Open-Source Automated Theorem ProvingarXiv:2502.07640Yong Lin, Shange Tang, Bohan Lyu, et al.2025 · 84 citations
4. Rubrics as Rewards: Reinforcement Learning Beyond Verifiable DomainsarXiv:2507.17746Anisha Gunjal, Anthony Wang, Elaine Lau, et al.2025 · 73 citations
5. 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 · 68 citations
6. SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language ModelsarXiv:2504.11468Hardy Chen, Haoqin Tu, Fali Wang, et al.2025 · 37 citations
7. Following Length Constraints in InstructionsConference on Empirical Methods in Natural Language Processing (EMNLP)Weizhe Yuan, Ilia Kulikov, Ping Yu, et al.2025 · 22 citations
8. Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language ModelsarXiv:2503.24377Rui Wang, Hongru Wang, Boyang Xue, et al.2025 · 16 citations
9. JuStRank: Benchmarking LLM Judges for System RankingAnnual Meeting of the Association for Computational Linguistics (ACL)Ariel Gera, Odellia Boni, Yotam Perlitz, et al.2025 · 15 citations
10. Rethinking Rubric Generation for Improving LLM Judge and Reward Modeling for Open-ended TasksarXiv:2602.05125William F. Shen, Xinchi Qiu, Chenxi Whitehouse, et al.2026 · 9 citations
11. Bias Fitting to Mitigate Length Bias of Reward Model in RLHFAnnual Meeting of the Association for Computational Linguistics (ACL)Kangwen Zhao, Jianfeng Cai, Jinhua Zhu, et al.2026 · 2 citations
12. HARM: Learning Hate-Aware Reward Model for Evaluating Natural Language Explanations of Offensive ContentFindings of the Association for Computational LinguisticsLorenzo Puppi Vecchi, Alceu de Souza Britto Jr, Emerson Cabrera Paraiso, et al.2026 · 1 citation
13. Debiasing Reward Models via Causally Motivated Inference-Time InterventionAnnual Meeting of the Association for Computational Linguistics (ACL)Kazutoshi Shinoda, Kosuke Nishida, Kyosuke Nishida2026
14. InstructSum: A Benchmark to Evaluate Instruction-Following Capability of Large Language Models in SummarizationLanguage Resources and Evaluation Conference (LREC)Kosuke Nishida, Kyosuke Nishida, Itsumi Saito2026
15. Teach a Reward Model to Correct Itself: Reward Guided Adversarial Failure Discovery for Robust Reward ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Pankayaraj Pathmanathan, Furong Huang2026
16. WildReward: Learning Reward Models from In-the-Wild Human InteractionsAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.2026

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