Who cites «Teaching Large Language Models to Reason with Reinforcement Learning»
- Training Language Models to Self-Correct via Reinforcement LearningarXiv:2409.12917Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, et al.2024 · 159 citations
- 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
- Iterative Reasoning Preference OptimizationConference on Neural Information Processing Systems (NeurIPS)Richard Yuanzhe Pang, Weizhe Yuan, Kyunghyun Cho, et al.2024 · 153 citations
- Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRsarXiv:2503.01307Kanishk Gandhi, Ayush Chakravarthy, Anikait Singh, et al.2025 · 123 citations
- Rewarding Progress: Scaling Automated Process Verifiers for LLM ReasoningarXiv:2410.08146Amrith Setlur, Chirag Nagpal, Adam Fisch, et al.2024 · 93 citations
- RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement LearningarXiv:2504.20073Zihan Wang, Kangrui Wang, Qineng Wang, et al.2025 · 71 citations
- S²R: Teaching LLMs to Self-verify and Self-correct via Reinforcement LearningAnnual Meeting of the Association for Computational Linguistics (ACL)Ruotian Ma, Peisong Wang, Cheng Liu, et al.2025 · 26 citations
- Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept SpaceConference on Neural Information Processing Systems (NeurIPS)Zhen Zhang, Xuehai He, Weixiang Yan, et al.2025 · 25 citations
- Online Difficulty Filtering for Reasoning Oriented Reinforcement LearningConference of the European Chapter of the Association for Computational Linguistics (EACL)Sanghwan Bae, Jiwoo Hong, Min Young Lee, et al.2026 · 22 citations
- StepTool: Enhancing Multi-Step Tool Usage in LLMs via Step-Grained Reinforcement LearningACM International Conference on Information and Knowledge Management (CIKM)Yuanqing Yu, Zhefan Wang, Weizhi Ma, et al.2024 · 20 citations
- RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Yihong Dong, Xue Jiang, Yongding Tao, et al.2026 · 6 citations
- CODERL+: Improving Code Generation via Reinforcement with Execution Semantics AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Xue Jiang, Yihong Dong, Mengyang Liu, et al.2026 · 5 citations
- Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute ScalingFindings of the Association for Computational LinguisticsIvan Rodkin, Daniil Orel, Konstantin Smirnov, et al.2026
- LoVeC: Reinforcement Learning for Better Verbalized Confidence in Long-Form GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Caiqi Zhang, Xiaochen Zhu, Chengzu Li, et al.2026
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