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Large reasoning models (LRMs) are proficient at generating explicit, step-by-step reasoning sequences before producing final answers.
Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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Token-budget-aware llm reasoning
Tingxu Han, Zhenting Wang, Chunrong Fang, Shiyu Zhao, Shiqing Ma, and Zhenyu Chen · 2024
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Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, et al · 2024
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Imitate, explore, and self-improve: A reproduction report on slow-thinking reasoning systems
Yingqian Min, Zhipeng Chen, Jinhao Jiang, Jie Chen, Jia Deng, Yiwen Hu, Yiru Tang, Jiapeng Wang, Xiaoxue Cheng, Huatong Song, et al · 2024
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The benefits of a concise chain of thought on problem-solving in large language models
Matthew Renze and Erhan Guven · 2024
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Deepseekmath: Pushing the limits of mathematical reasoning in open language models
Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Xiao Bi, Haowei Zhang, Mingchuan Zhang, YK Li, Y Wu, et al · 2024
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Reft: Reasoning with reinforced fine-tuning
Luong Trung, Xinbo Zhang, Zhanming Jie, Peng Sun, Xiaoran Jin, and Hang Li · 2024
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Automatic curriculum expert iteration for reliable llm reasoning
Zirui Zhao, Hanze Dong, Amrita Saha, Caiming Xiong, and Doyen Sahoo · 2024
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L1: Controlling how long a reasoning model thinks with reinforcement learning
Pranjal Aggarwal and Sean Welleck · 2025
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Claude 3.7 sonnet, 2025
Anthropic · 2025
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Do not think that much for 2+ 3=? on the overthinking of o1-like llms
Xingyu Chen, Jiahao Xu, Tian Liang, Zhiwei He, Jianhui Pang, Dian Yu, Linfeng Song, Qiuzhi Liu, Mengfei Zhou, Zhuosheng Zhang, et al · 2025
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Stop summation: Min-form credit assignment is all process reward model needs for reasoning
Jie Cheng, Ruixi Qiao, Lijun Li, Chao Guo, Junle Wang, Gang Xiong, Yisheng Lv, and Fei-Yue Wang · 2025
Cited alongside, same era.
Reinforcement learning for reasoning in small llms: What works and what doesn’t
Quy-Anh Dang and Chris Ngo · 2025
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Concise reasoning via reinforcement learning
Mehdi Fatemi, Banafsheh Rafiee, Mingjie Tang, and Kartik Talamadupula · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al · 2025
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Skywork open reasoner series
Satori: Reinforcement learning with chain-of-action-thought enhances llm reasoning via autoregressive search
Maohao Shen, Guangtao Zeng, Zhenting Qi, Zhang-Wei Hong, Zhenfang Chen, Wei Lu, Gregory W Wornell, Subhro Das, David Daniel Cox, and Chuang Gan · 2025
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Hybridflow: A flexible and efficient rlhf framework
Guangming Sheng, Chi Zhang, Zilingfeng Ye, Xibin Wu, Wang Zhang, Ru Zhang, Yanghua Peng, Haibin Lin, and Chuan Wu · 2025
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Mingyang Song, Mao Zheng, Zheng Li, Wenjie Yang, Xuan Luo, Yue Pan, and Feng Zhang · 2025
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Stop overthinking: A survey on efficient reasoning for large language models
Yang Sui, Yu-Neng Chuang, Guanchu Wang, Jiamu Zhang, Tianyi Zhang, Jiayi Yuan, Hongyi Liu, Andrew Wen, Shaochen Zhong, Hanjie Chen, et al · 2025
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Efficient reasoning for llms through speculative chain-of-thought
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Jujie He, Jiacai Liu, Chris Yuhao Liu, Rui Yan, Chaojie Wang, Peng Cheng, Xiaoyu Zhang, Fuxiang Zhang, Jiacheng Xu, Wei Shen, Siyuan Li, Liang Zeng, Tianwen Wei, Cheng Cheng, Bo An, Yang Liu, and Yahui Zhou · 2025
Cited alongside, same era.
Thinkprune: Pruning long chain-of-thought of llms via reinforcement learning
Bairu Hou, Yang Zhang, Jiabao Ji, Yujian Liu, Kaizhi Qian, Jacob Andreas, and Shiyu Chang · 2025
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Overthink: Slowdown attacks on reasoning llms
Abhinav Kumar, Jaechul Roh, Ali Naseh, Marzena Karpinska, Mohit Iyyer, Amir Houmansadr, and Eugene Bagdasarian · 2025
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Thought manipulation: External thought can be efficient for large reasoning models
Yule Liu, Jingyi Zheng, Zhen Sun, Zifan Peng, Wenhan Dong, Zeyang Sha, Shiwen Cui, Weiqiang Wang, and Xinlei He · 2025
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Real: Efficient rlhf training of large language models with parameter reallocation
Zhiyu Mei, Wei Fu, Kaiwei Li, Guangju Wang, Huanchen Zhang, and Yi Wu · 2025
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Optimizing test-time compute via meta reinforcement fine-tuning
Yuxiao Qu, Matthew YR Yang, Amrith Setlur, Lewis Tunstall, Edward Emanuel Beeching, Ruslan Salakhutdinov, and Aviral Kumar · 2025
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Srft: A single-stage method with supervised and reinforcement fine-tuning for reasoning
Yuqian Fu, Tinghong Chen, Jiajun Chai, Xihuai Wang, Songjun Tu, Guojun Yin, Wei Lin, Qichao Zhang, Yuanheng Zhu, and Dongbin Zhao
Cited in the paper.
Rlae: Reinforcement learning-assisted ensemble for llms
Yuqian Fu, Yuanheng Zhu, Jiajun Chai, Guojun Yin, Wei Lin, Qichao Zhang, and Dongbin Zhao
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Jikai Wang, Juntao Li, Lijun Wu, and Min Zhang · 2025
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Light-r1: Curriculum sft, dpo and rl for long cot from scratch and beyond
Liang Wen, Yunke Cai, Fenrui Xiao, Xin He, Qi An, Zhenyu Duan, Yimin Du, Junchen Liu, Lifu Tang, Xiaowei Lv, et al · 2025
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Shorterbetter: Guiding reasoning models to find optimal inference length for efficient reasoning
Jingyang Yi and Jiazheng Wang · 2025
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Simplerl-zoo: Investigating and taming zero reinforcement learning for open base models in the wild
Weihao Zeng, Yuzhen Huang, Qian Liu, Wei Liu, Keqing He, Zejun Ma, and Junxian He · 2025
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Jixiao Zhang and Chunsheng Zuo · 2025
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Online preference-based reinforcement learning with self-augmented feedback from large language model
Songjun Tu, Jingbo Sun, Qichao Zhang, Xiangyuan Lan, and Dongbin Zhao · 2077
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