🔗 Who cites «RM-R1: Reward Modeling as Reasoning»

47 papers of our library cite it (of the 149,439 whose bibliographies we read) · 25 with a page here, the most cited first · ← back to «RM-R1: Reward Modeling as Reasoning»

1. Rubrics as Rewards: Reinforcement Learning Beyond Verifiable DomainsarXiv:2507.17746Anisha Gunjal, Anthony Wang, Elaine Lau, et al.2025 · 73 citations
2. Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI SynergyarXiv:2507.01352Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao, et al.2025 · 48 citations
3. Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic ReasoningarXiv:2512.20848NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.2025 · 27 citations
4. 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
5. 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
6. 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
7. PAG: Multi-Turn Reinforced LLM Self-Correction with Policy as Generative VerifierarXiv:2506.10406Yuhua Jiang, Yuwen Xiong, Yufeng Yuan, et al.2025 · 8 citations
8. mR3: Multilingual Rubric-Agnostic Reward Reasoning ModelsarXiv:2510.01146David Anugraha, Shou-Yi Hung, Zilu Tang, et al.2025 · 5 citations
9. 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
10. 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
11. RubricBench: Aligning Model-Generated Rubrics with Human StandardsAnnual Meeting of the Association for Computational Linguistics (ACL)Junyi Zhou, Qiyuan Zhang, Yufei Wang, et al.2026 · 3 citations
12. OpenGenAlign: A Preference Dataset and Benchmark for Trustworthy Reward Modeling in Open-Ended, Long-Context GenerationFindings of the Association for Computational LinguisticsHanning Zhang, Juntong Song, Juno Zhu, et al.2026 · 2 citations
13. 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
14. 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
15. Scaling Test-Time Compute to Achieve IOI Gold Medal with Open-Weight ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Mehrzad Samadi, Aleksander Ficek, Sean Narenthiran, et al.2026 · 1 citation
16. SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data UtilityAnnual Meeting of the Association for Computational Linguistics (ACL)Xuyang Zhi, Peilun Zhou, Chengqiang Lu, et al.2026 · 1 citation
17. UniCreative: Unifying Long-form Logic and Short-form Sparkle via Reference-Free Reinforcement LearningFindings of the Association for Computational LinguisticsXiaolong Wei, Zerun Zhu, Simin Niu, et al.2026 · 1 citation
18. AgentV-RL: Scaling Reward Modeling with Agentic VerifierFindings of the Association for Computational LinguisticsJiazheng Zhang, Ziche Fu, Zhiheng Xi, et al.2026
19. Aligning Agents via Planning: A Benchmark for Trajectory-Level Reward ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Jiaxuan Wang, Yulan Hu, Wenjin Yang, et al.2026
20. Beyond Length Scaling: Synergizing Breadth and Depth for Generative Reward ModelsFindings of the Association for Computational LinguisticsQiyuan Zhang, Yufei Wang, Tianhe Wu, et al.2026
21. Learning to Refine: Self-Refinement of Parallel Reasoning in LLMsFindings of the Association for Computational LinguisticsQibin Wang, Pu Zhao, Shaohan Huang, et al.2026
22. ReflectRM: Boosting Generative Reward Models via Self-Reflection within a Unified Judgment FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Kai Qin, Liangxin Liu, Yu Liang, et al.2026
23. Reward Modeling for Scientific Writing EvaluationAnnual Meeting of the Association for Computational Linguistics (ACL)Furkan Şahinuç, Subhabrata Dutta, Iryna Gurevych2026
24. Teaching Language Models to Forecast Research Success Through Comparative Idea EvaluationFindings of the Association for Computational LinguisticsSrujan P Mule, Aniketh Garikaparthi, Manasi Patwardhan2026
25. 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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