🔗 Who cites «Agentic Reward Modeling: Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems»

16 papers of our library cite it (of the 149,439 whose bibliographies we read) · 10 with a page here, the most cited first · ← back to «Agentic Reward Modeling: Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems»

1. 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
2. Inference-Time Scaling for Generalist Reward ModelingarXiv:2504.02495Zijun Liu, Peiyi Wang, Runxin Xu, et al.2025 · 65 citations
3. OpenRubrics: Towards Scalable Synthetic Rubric Generation for Reward Modeling and LLM AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Tianci Liu, Ran Xu, Tony Yu, et al.2026 · 25 citations
4. VerIF: Verification Engineering for Reinforcement Learning in Instruction FollowingConference on Empirical Methods in Natural Language Processing (EMNLP)Hao Peng, Yunjia Qi, Xiaozhi Wang, et al.2025 · 18 citations
5. 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
6. Beyond Literal Mapping: Benchmarking and Improving Non-Literal Translation EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Yanzhi Tian, Cunxiang Wang, Zeming Liu, et al.2026 · 5 citations
7. IF-RewardBench: Benchmarking Judge Models for Instruction-Following EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Bosi Wen, Yilin Niu, Cunxiang Wang, et al.2026 · 1 citation
8. AJ-Bench: Benchmarking Agent-as-a-Judge for Environment-Aware EvaluationFindings of the Association for Computational LinguisticsWentao Shi, Yu Wang, Yuyang Zhao, et al.2026
9. RiT: Rubrics-in-Thinking Reinforcement Learning for Improved Reasoning in Large Language ModelsFindings of the Association for Computational LinguisticsXiaobin Tian, Shuai Yuan, Muyun Ding, et al.2026
10. 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

6 more papers of our library cite it; they have no page here yet.

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