🔗 Who cites «ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models»

57 papers of our library cite it (of the 149,439 whose bibliographies we read) · 21 with a page here, the most cited first · ← back to «ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models»

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. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
3. Training Language Models to Reason EfficientlyConference on Neural Information Processing Systems (NeurIPS)Daman Arora, Andrea Zanette2025 · 74 citations
4. Rethinking Entropy Interventions in RLVR: An Entropy Change PerspectiveAnnual Meeting of the Association for Computational Linguistics (ACL)Zhezheng Hao, Hong Wang, Haoyang Liu, et al.2026 · 22 citations
5. AceReason-Nemotron 1.1: Advancing Math and Code Reasoning through SFT and RL SynergyarXiv:2506.13284Zihan Liu, Zhuolin Yang, Yang Chen, et al.2025 · 21 citations
6. CriticLean: Critic-Guided Reinforcement Learning for Mathematical FormalizationAnnual Meeting of the Association for Computational Linguistics (ACL)Zhongyuan Peng, Yifan Yao, Kaijing Ma, et al.2026 · 12 citations
7. ERNIE 5.0 Technical ReportarXiv:2602.04705Haifeng Wang, Hua Wu, Tian Wu, et al.2026 · 7 citations
8. Scaling Behaviors of LLM Reinforcement Learning Post-Training: An Empirical Study in Mathematical ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Zelin Tan, Hejia Geng, Xiaohang Yu, et al.2026 · 6 citations
9. rStar2-Agent: Agentic Reasoning Technical ReportarXiv:2508.20722Ning Shang, Yifei Liu, Yi Zhu, et al.2025 · 6 citations
10. Learning to Optimize Multi-Objective Alignment Through Dynamic Reward WeightingTransactions of the Association for Computational Linguistics (TACL)Yining Lu, Zilong Wang, Shiyang Li, et al.2026 · 4 citations
11. Rethinking Sample Polarity in Reinforcement Learning with Verifiable RewardsAnnual Meeting of the Association for Computational Linguistics (ACL)Xinyu Tang, Yuliang Zhan, Zhixun Li, et al.2026 · 4 citations
12. Gained in Translation: Privileged Pairwise Judges Enhance Multilingual ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Lintang Sutawika, Gokul Swamy, Steven Wu, et al.2026 · 2 citations
13. Entropy Ratio Clipping as a Soft Global Constraint for Stable Reinforcement LearningFindings of the Association for Computational LinguisticsZhenpeng Su, Leiyu Pan, Minxuan Lv, et al.2026 · 1 citation
14. Beyond Reasoning Gains: Mitigating General-Capability Forgetting in Large Reasoning ModelsFindings of the Association for Computational LinguisticsHoang Phan, Xianjun Yang, Yuanshun Yao, et al.2026
15. Is Micro Domain-Adaptive Pre-Training Effective for Real-World Operations? Multi-Step Evaluation Reveals Potential and BottlenecksConference of the European Chapter of the Association for Computational Linguistics (EACL)Masaya Tsunokake, Yuta Koreeda, Terufumi Morishita, et al.2026
16. Memorization, Emergence, and Explaining Reversal Failures: A Controlled Study of Relational Semantics in LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Yihua Zhu, Qianying Liu, Jiaxin Wang, et al.2026
17. Revisiting Entropy Regularization: Adaptive Coefficient Unlocks Its Potential for LLM Reinforcement LearningFindings of the Association for Computational LinguisticsXiaoyun Zhang, Xiaojian Yuan, Di Huang, et al.2026
18. ScaleBox: Enabling High-Fidelity and Scalable Code Verification for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jiasheng Zheng, Xin Zheng, Boxi Cao, et al.2026
19. Tailored Primitive Initialization is the Secret Key to Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Yihang Yao, Guangtao Zeng, Raina Wu, et al.2026
20. Teaching Language Models to Forecast Research Success Through Comparative Idea EvaluationFindings of the Association for Computational LinguisticsSrujan P Mule, Aniketh Garikaparthi, Manasi Patwardhan2026
21. Understanding and Preventing Entropy Collapse in RLVR with On-Policy Entropy Flow OptimizationFindings of the Association for Computational LinguisticsHuimin Xu, Shuai Zhao, Xiaobao Wu, et al.2026

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

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