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Explicit Chain-of-Thought improves the reasoning performance of large language models but often incurs high inference cost due to verbose token-level traces.
Sinkhorn Distances: Lightspeed Computation of Optimal Transport. In Advances in Neural Information Processing Systems , C.J. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K.Q. Weinberger (Eds.), Vol. 26. Curran Associates, Inc
Marco Cuturi. 2013 · 2013
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Computational Optimal Transport with Applications to Data Sciences
Peyré Gabriel and Cuturi Marco. 2019 · 2019
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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, Christopher Hesse, and John Schulman. 2021 · 2021
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Measuring Mathematical Problem Solving With the MATH Dataset. In Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021
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Learned Token Pruning for Transformers. In Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’22) . Association for Computing Machinery, New York, NY, USA, 784–794
Sehoon Kim, Sheng Shen, David Thorsley, Amir Gholami, Woosuk Kwon, Joseph Hassoun, and Kurt Keutzer. 2022 · 2022
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Large Language Models are Zero-Shot Reasoners. In Advances in Neural Information Processing Systems , S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Vol. 35. Curran Associates, Inc., 22199–22213
Takeshi Kojima, Shixiang (Shane) Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. In Advances in Neural Information Processing Systems , S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, and A. Oh (Eds.), Vol. 35. Curran Associates, Inc., 24824–24837
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, brian ichter, Fei Xia, Ed Chi, Quoc V Le, and Denny Zhou. 2022 · 2022
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Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks
Wenhu Chen, Xueguang Ma, Xinyi Wang, and William W. Cohen. 2023 · 2023
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Think before you speak: Training Language Models With Pause Tokens
Sachin Goyal, Ziwei Ji, Ankit Singh Rawat, Aditya Krishna Menon, Sanjiv Kumar, and Vaishnavh Nagarajan. 2023 · 2023
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Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference. In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’23) . Association for Computing Machinery, New York, NY, USA, 1280–1290
Junyan Li, Li Lyna Zhang, Jiahang Xu, Yujing Wang, Shaoguang Yan, Yunqing Xia, Yuqing Yang, Ting Cao, Hao Sun, Weiwei Deng, Qi Zhang, and Mao Yang. 2023 · 2023
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Reflexion: language agents with verbal reinforcement learning. In Advances in Neural Information Processing Systems , A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, and S. Levine (Eds.), Vol. 36. Curran Associates, Inc., 8634–8652
Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2023 · 2023
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Self-Consistency Improves Chain of Thought Reasoning in Language Models. In The Eleventh International Conference on Learning Representations
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2023 · 2023
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Tree of Thoughts: Deliberate Problem Solving with Large Language Models. In Advances in Neural Information Processing Systems , A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, and S. Levine (Eds.), Vol. 36. Curran Associates, Inc., 11809–11822
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan. 2023a · 2023
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Compressed Chain of Thought: Efficient Reasoning Through Dense Representations
Jeffrey Cheng and Benjamin Van Durme. 2024 · 2024
Cited alongside, same era.
Thinking Tokens for Language Modeling
David Herel and Tomas Mikolov. 2024 · 2024
Cited alongside, same era.
Let’s Think Dot by Dot: Hidden computation in transformer language models. In First Conference on Language Modeling
Jacob Pfau, William Merrill, and Samuel R. Bowman. 2024 · 2024
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GPQA: A Graduate-Level Google-Proof Q&A Benchmark. In First Conference on Language Modeling
David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R. Bowman. 2024 · 2024
Cited alongside, same era.
The Benefits of a Concise Chain of Thought on Problem-Solving in Large Language Models. In 2024 2nd International Conference on Foundation and Large Language Models (FLLM) . 476–483
SpiralThinker: Latent Reasoning through an Iterative Process with Text-Latent Interleaving
Shengmin Piao and Sanghyun Park. 2025 · 2025
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DarkDistill: Difficulty-Aligned Federated Early-Exit Network Training on Heterogeneous Devices. In Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 (KDD ’25) . Association for Computing Machinery, New York, NY, USA, 2374–2385
Lehao Qu, Shuyuan Li, Zimu Zhou, Boyi Liu, Yi Xu, and Yongxin Tong. 2025 · 2025
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Qwen, :, An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, Huan Lin, Jian Yang, Jianhong Tu, Jianwei Zhang, Jianxin Yang, Jiaxi Yang, Jingren Zhou, Junyang Lin, Kai Dang, Keming Lu, Keqin Bao, Kexin Yang, Le Yu, Mei Li, Mingfeng Xue, Pei Zhang, Qin Zhu, Rui Men, Runji Lin, Tianhao Li, Tianyi Tang, Tingyu Xia, Xingzhang Ren, Xuancheng Ren, Yang Fan, Yang Su, Yichang Zhang, Yu Wan, Yuqiong Liu, Zeyu Cui, Zhenru Zhang, and Zihan Qiu. 2025 · 2025
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Matthew Renze and Erhan Guven. 2024 · 2024
Cited alongside, same era.
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. In International Conference on Learning Representations , B. Kim, Y. Yue, S. Chaudhuri, K. Fragkiadaki, M. Khan, and Y. Sun (Eds.), Vol. 2024. 20279–20316
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V Le, and Denny Zhou. 2024 · 2024
Cited alongside, same era.
L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning. In Second Conference on Language Modeling
Pranjal Aggarwal and Sean Welleck. 2025 · 2025
Cited alongside, same era.
Training Language Models to Reason Efficiently. In The Thirty-ninth Annual Conference on Neural Information Processing Systems
Daman Arora and Andrea Zanette. 2025 · 2025
Cited alongside, same era.
Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching
Simon A. Aytes, Jinheon Baek, and Sung Ju Hwang. 2025 · 2025
Cited alongside, same era.
Latent Reasoning in LLMs as a Vocabulary-Space Superposition
Jingcheng Deng, Liang Pang, Zihao Wei, Shichen Xu, Zenghao Duan, Kun Xu, Yang Song, Huawei Shen, and Xueqi Cheng. 2025 · 2025
Cited alongside, same era.
DeepSeek-R1 incentivizes reasoning in LLMs through reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Peiyi Wang, Qihao Zhu, Runxin Xu, Ruoyu Zhang, Shirong Ma, Xiao Bi, Zhen Zhang, Yishi Piao, Fuli Luo, Jie Fu, Yuxiang Huang, Yuchen Liu, Zhihao Fan, Zhiheng Xi, Zhiqiang Xie, Zhiyuan Liu, Zhiyuan Chen, Zhongqiang Huang, Zhongyu Wei, Zhuoer Feng, Zijun Liu, Zongsheng Yue, Zongyuan Li, Zhiyuan Liu, and Wenfeng Liang. 2025 · 2025
Cited alongside, same era.
PEAR: Phase Entropy Aware Reward for Efficient Reasoning
Chen Huang, Wei Lu, and Wenxuan Zhang. 2025 · 2025
Cited alongside, same era.
Zhenyi Shen, Hanqi Yan, Linhai Zhang, Zhanghao Hu, Yali Du, and Yulan He. 2025 · 2025
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Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning. In Forty-second International Conference on Machine Learning
DiJia Su, Hanlin Zhu, Yingchen Xu, Jiantao Jiao, Yuandong Tian, and Qinqing Zheng. 2025 · 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, Na Zou, Hanjie Chen, and Xia Hu. 2025 · 2025
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Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning Chains. In The Thirty-ninth Annual Conference on Neural Information Processing Systems
Wenhui Tan, Jiaze Li, Jianzhong Ju, Zhenbo Luo, Ruihua Song, and Jian Luan. 2025 · 2025
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ConciseHint: Boosting Efficient Reasoning via Continuous Concise Hints during Generation
Siao Tang, Xinyin Ma, Gongfan Fang, and Xinchao Wang. 2025 · 2025
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System-1.5 Reasoning: Traversal in Language and Latent Spaces with Dynamic Shortcuts
Xiaoqiang Wang, Suyuchen Wang, Yun Zhu, and Bang Liu. 2025 · 2025
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Concise Reasoning, Big Gains: Pruning Long Reasoning Trace with Difficulty-Aware Prompting
Yifan Wu, Jingze Shi, Bingheng Wu, Jiayi Zhang, Xiaotian Lin, Nan Tang, and Yuyu Luo. 2025 · 2025
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Dynamic Early Exit in Reasoning Models
Chenxu Yang, Qingyi Si, Yongjie Duan, Zheliang Zhu, Chenyu Zhu, Qiaowei Li, Minghui Chen, Zheng Lin, and Weiping Wang. 2025 · 2025
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LightThinker: Thinking Step-by-Step Compression. In Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Jintian Zhang, Yuqi Zhu, Mengshu Sun, Yujie Luo, Shuofei Qiao, Lun Du, Da Zheng, Huajun Chen, and Ningyu Zhang. 2025 · 2025
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