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Large Reasoning Models (LRMs) have achieved impressive performance on complex reasoning tasks by generating detailed chain-of-thought (CoT) explanations.
A mathematical theory of communication
Claude E Shannon · 1948
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Training verifiers to solve math word problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, et al · 2021
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Measuring mathematical problem solving with the MATH dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt · 2021
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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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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 · 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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Numinamath: The largest public dataset in ai4maths with 860k pairs of competition math problems and solutions
Jia Li, Edward Beeching, Lewis Tunstall, Ben Lipkin, Roman Soletskyi, Shengyi Huang, Kashif Rasul, Longhui Yu, Albert Q Jiang, Ziju Shen, et al · 2024
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Deepseekmath: Pushing the limits of mathematical reasoning in open language models, 2024
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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An Yang, Baosong Yang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Zhou, Chengpeng Li, Chengyuan Li, Dayiheng Liu, Fei Huang, et al · 2024
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The unreasonable effectiveness of entropy minimization in llm reasoning
Shivam Agarwal, Zimin Zhang, Lifan Yuan, Jiawei Han, and Hao Peng · 2025
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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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Don’t think longer, think wisely: Optimizing thinking dynamics for large reasoning models
Sohyun An, Ruochen Wang, Tianyi Zhou, and Cho-Jui Hsieh · 2025
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The entropy mechanism of reinforcement learning for reasoning language models
Ganqu Cui, Yuchen Zhang, Jiacheng Chen, Lifan Yuan, Zhi Wang, Yuxin Zuo, Haozhan Li, Yuchen Fan, Huayu Chen, Weize Chen, et al · 2025
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S-grpo: Early exit via reinforcement learning in reasoning models
Muzhi Dai, Chenxu Yang, and Qingyi Si · 2025
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Does thinking more always help? understanding test-time scaling in reasoning models
Soumya Suvra Ghosal, Souradip Chakraborty, Avinash Reddy, Yifu Lu, Mengdi Wang, Dinesh Manocha, Furong Huang, Mohammad Ghavamzadeh, and Amrit Singh Bedi · 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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Don’t overthink it. preferring shorter thinking chains for improved llm reasoning
Michael Hassid, Gabriel Synnaeve, Yossi Adi, and Roy Schwartz · 2025
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A survey of efficient reasoning for large reasoning models: Language, multimodality, and beyond
Xiaoye Qu, Yafu Li, Zhaochen Su, Weigao Sun, Jianhao Yan, Dongrui Liu, Ganqu Cui, Daizong Liu, Shuxian Liang, Junxian He, et al · 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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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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Kimi k1. 5: Scaling reinforcement learning with llms
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Qwq-32b: Embracing the power of reinforcement learning, March 2025
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Shijue Huang, Hongru Wang, Wanjun Zhong, Zhaochen Su, Jiazhan Feng, Bowen Cao, and Yi R Fung · 2025
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Think only when you need with large hybrid-reasoning models
Lingjie Jiang, Xun Wu, Shaohan Huang, Qingxiu Dong, Zewen Chi, Li Dong, Xingxing Zhang, Tengchao Lv, Lei Cui, and Furu Wei · 2025
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Martin Kuo, Jianyi Zhang, Aolin Ding, Qinsi Wang, Louis DiValentin, Yujia Bao, Wei Wei, Hai Li, and Yiran Chen · 2025
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Revisiting llm reasoning via information bottleneck
Shiye Lei, Zhihao Cheng, Kai Jia, and Dacheng Tao · 2025
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Compressing chain-of-thought in llms via step entropy
Zeju Li, Jianyuan Zhong, Ziyang Zheng, Xiangyu Wen, Zhijian Xu, Yingying Cheng, Fan Zhang, and Qiang Xu · 2025
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Fractured chain-of-thought reasoning
Baohao Liao, Hanze Dong, Yuhui Xu, Doyen Sahoo, Christof Monz, Junnan Li, and Caiming Xiong · 2025
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Answer convergence as a signal for early stopping in reasoning
Xin Liu and Lu Wang · 2025
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Self-training elicits concise reasoning in large language models
Tergel Munkhbat, Namgyu Ho, Seo Hyun Kim, Yongjin Yang, Yujin Kim, and Se-Young Yun · 2025
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Tokenskip: Controllable chain-of-thought compression in llms
Heming Xia, Chak Tou Leong, Wenjie Wang, Yongqi Li, and Wenjie Li · 2025
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Scalable chain of thoughts via elastic reasoning
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Not all tokens are what you need in thinking
Hang Yuan, Bin Yu, Haotian Li, Shijun Yang, Christina Dan Wang, Zhou Yu, Xueyin Xu, Weizhen Qi, and Kai Chen · 2025
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Don’t overthink it: A survey of efficient r1-style large reasoning models
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Done is better than perfect: Unlocking efficient reasoning by structured multi-turn decomposition
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Entropy-based exploration conduction for multi-step reasoning
Jinghan Zhang, Xiting Wang, Fengran Mo, Yeyang Zhou, Wanfu Gao, and Kunpeng Liu · 2025
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To think or not to think: Exploring the unthinking vulnerability in large reasoning models
Zihao Zhu, Hongbao Zhang, Ruotong Wang, Ke Xu, Siwei Lyu, and Baoyuan Wu · 2025
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