-
Marjanović, Sara Vera, et al. "DeepSeek-R1 Thoughtology: Let's< think> about LLM Reasoning." arXiv preprint arXiv:2504.07128 (2025). [Paper]
-
Chu, Zheng, et al. "Navigate through enigmatic labyrinth a survey of chain of thought reasoning: Advances, frontiers and future." Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2024. [Paper] [Code]
-
Logical Reasoning in Large Language Models: A Survey, Hanmeng Liu, Zhizhang Fu, Mengru Ding, Ruoxi Ning, Chaoli Zhang, Xiaozhang Liu, Yue Zhang [Paper]
-
From System 1 to System 2: A Survey of Reasoning Large Language Models, Zhong-Zhi Li, Duzhen Zhang, Ming-Liang Zhang, Jiaxin Zhang, Zengyan Liu, Yuxuan Yao, Haotian Xu, Junhao Zheng, Pei-Jie Wang, Xiuyi Chen, Yingying Zhang, Fei Yin, Jiahua Dong, Zhijiang Guo, Le Song, Cheng-Lin Liu [Paper]
-
Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models， Qiguang Chen, Libo Qin, Jinhao Liu, Dengyun Peng, Jiannan Guan, Peng Wang, Mengkang Hu, Yuhang Zhou, Te Gao, Wanxiang Che [Paper] [Code]
-
Wang G, Zhang S, Zhan T, et al. Unlocking the Mysteries of OpenAI o1: A Survey of the Reasoning Abilities of Large Language Models[J]. [Paper]
-
Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey, Yaoting Wang, Shengqiong Wu, Yuecheng Zhang, William Wang, Ziwei Liu, Jiebo Luo, Hao Fei [Paper] [Github]
-
Chain of Thought论文、代码和资源【论文精读】 [Youtube-跟李沐学AI]
-
[arXiv:2505.14362] DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning, Ziwei Zheng, Michael Yang, Jack Hong, Chenxiao Zhao, Guohai Xu, Le Yang, Chao Shen, Xing Yu [Paper]
-
Visionary-R1: Mitigating Shortcuts in Visual Reasoning with Reinforcement Learning, Jiaer Xia, Yuhang Zang, Peng Gao, Yixuan Li, Kaiyang Zhou [Paper]
-
ChestX-Reasoner: Advancing Radiology Foundation Models with Reasoning through Step-by-Step Verification, Ziqing Fan, Cheng Liang, Chaoyi Wu, Ya Zhang, Yanfeng Wang, Weidi Xie [Paper] [Code]
-
T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT [Paper] [Code]
-
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning, Bowen Jin, Hansi Zeng, Zhenrui Yue, Dong Wang, Hamed Zamani, Jiawei Han [Paper]
-
S2R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning， Ruotian Ma, Peisong Wang, Cheng Liu, Xingyan Liu, Jiaqi Chen, Bang Zhang, Xin Zhou, Nan Du, Jia Li [Paper] [Code]
-
LLaVA-CoT: Let Vision Language Models Reason Step-by-Step, Guowei Xu, Peng Jin, Hao Li, Yibing Song, Lichao Sun, Li Yuan [Paper] [Code]
-
A Comparison of DeepSeek and Other LLMs, Tianchen Gao, Jiashun Jin, Zheng Tracy Ke, Gabriel Moryoussef [Paper]
-
JingFang: A Traditional Chinese Medicine Large Language Model of Expert-Level Medical Diagnosis and Syndrome Differentiation-Based Treatment, Yehan Yan, Tianhao Ma, Ruotai Li, Xinhan Zheng, Guodong Shan, Chisheng Li [Paper]
-
Unveiling the Mechanisms of Explicit CoT Training: How Chain-of-Thought Enhances Reasoning Generalization, Xinhao Yao, Ruifeng Ren, Yun Liao, Yong Liu [Paper] [Code]
-
Agentic Reasoning: Reasoning LLMs with Tools for the Deep Research, Junde Wu, Jiayuan Zhu, Yuyuan Liu [Paper]
-
Fino1: On the Transferability of Reasoning Enhanced LLMs to Finance, Lingfei Qian, Weipeng Zhou, Yan Wang, Xueqing Peng, Jimin Huang, Qianqian Xie [Paper] [Code]
-
LawGPT: Knowledge-Guided Data Generation and Its Application to Legal LLM, Zhi Zhou, Kun-Yang Yu, Shi-Yu Tian, Xiao-Wen Yang, Jiang-Xin Shi, Pengxiao Song, Yi-Xuan Jin, Lan-Zhe Guo, Yu-Feng Li [Paper] [Code]
-
On the Emergence of Thinking in LLMs I: Searching for the Right Intuition, Guanghao Ye, Khiem Duc Pham, Xinzhi Zhang, Sivakanth Gopi, Baolin Peng, Beibin Li, Janardhan Kulkarni, Huseyin A. Inan [Paper] [Code]
-
ReasonFlux: Hierarchical LLM Reasoning via Scaling Thought Templates, Ling Yang, Zhaochen Yu, Bin Cui, Mengdi Wang [Paper] [Code]
-
Adaptive Graph of Thoughts: Test-Time Adaptive Reasoning Unifying Chain, Tree, and Graph Structures, Tushar Pandey, Ara Ghukasyan, Oktay Goktas, Santosh Kumar Radha [Paper]
-
CoT-Valve: Length-Compressible Chain-of-Thought Tuning, Xinyin Ma, Guangnian Wan, Runpeng Yu, Gongfan Fang, Xinchao Wang [Paper] [Code]
-
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency, Dongzhi Jiang, Renrui Zhang, Ziyu Guo, Yanwei Li, Yu Qi, Xinyan Chen, Liuhui Wang, Jianhan Jin, Claire Guo, Shen Yan, Bo Zhang, Chaoyou Fu, Peng Gao, Hongsheng Li [Paper] [Project Page]
-
[arXiv:2502.06428] CoS: Chain-of-Shot Prompting for Long Video Understanding, Jian Hu, Zixu Cheng, Chenyang Si, Wei Li, Shaogang Gong [Paper]
-
Can We Generate Images with CoT? Let’s Verify and Reinforce Image Generation Step by Step, ZiyuGuo∗1,RenruiZhang∗†2,ChengzhuoTong∗4,ZhizhengZhao∗3 PengGao4,HongshengLi‡2,Pheng-AnnHeng‡ [Paper] [Code]
-
Liu, Yuecheng, et al. "SpatialCoT: Advancing Spatial Reasoning through Coordinate Alignment and Chain-of-Thought for Embodied Task Planning." arXiv preprint arXiv:2501.10074 (2025). [Paper]
-
Thawakar, Omkar, et al. "LlamaV-o1: Rethinking Step-by-step Visual Reasoning in LLMs." arXiv preprint arXiv:2501.06186 (2025). [Paper]
-
[arXiv:2412.06769] Training Large Language Models to Reason in a Continuous Latent Space, Shibo Hao, Sainbayar Sukhbaatar, DiJia Su, Xian Li, Zhiting Hu, Jason Weston, Yuandong Tian [Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[Paper]
-
[AAAI 2024] T-SciQ: Teaching Multimodal Chain-of-Thought Reasoning via Mixed Large Language Model Signals for Science Question Answering Lei Wang, Yi Hu, Jiabang He, Xing Xu, Ning Liu, Hui Liu, Heng Tao Shen [Paper] [Code]
-
[ECCV 2024] Boosting the Power of Small Multimodal Reasoning Models to Match Larger Models with Self-Consistency Training Cheng Tan, Jingxuan Wei, Zhangyang Gao, Linzhuang Sun, Siyuan Li, Ruifeng Guo, Bihui Yu, Stan Z. Li [Paper] [Code]
-
KAM-CoT: Knowledge Augmented Multimodal Chain-of-Thoughts Reasoning Debjyoti Mondal, Suraj Modi, Subhadarshi Panda, Rituraj Singh, Godawari Sudhakar Rao [Paper]
-
Uncovering Latent Chain of Thought Vectors in Language Models, Jason Zhang, Scott Viteri [Paper]
-
Exploring Defeasible Reasoning in Large Language Models: A Chain-of-Thought Approach, Zhaoqun Lia, Chen Chena and Beishui Liaoa, [Paper]
-
MasonTigers at SemEval-2024 Task 9: Solving Puzzles with an Ensemble of Chain-of-Thoughts, Md Nishat Raihan, Dhiman Goswami, Al Nahian Bin Emran, Sadiya Sayara Chowdhury Puspo, Amrita Ganguly, Marcos Zampieri [Paper]
-
NLPeople at TextGraphs-17 Shared Task: Chain of Thought Questioning to Elicit Decompositional Reasoning, Movina Moses, Vishnudev Kuruvanthodi, Mohab Elkaref, Shinnosuke Tanaka, James Barry, Geeth Mel, Campbell Watson [Paper]
-
K. Hu et al., "Ladder-of-Thought: Using Knowledge as Steps to Elevate Stance Detection," 2024 International Joint Conference on Neural Networks (IJCNN), Yokohama, Japan, 2024, pp. 1-8, doi: 10.1109/IJCNN60899.2024.10650428. [Paper]
-
Fine-Tuning with Divergent Chains of Thought Boosts Reasoning Through Self-Correction in Language Models, Haritz Puerto, Tilek Chubakov, Xiaodan Zhu, Harish Tayyar Madabushi, Iryna Gurevych [Paper]
-
HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs, Junying Chen, Zhenyang Cai, Ke Ji, Xidong Wang, Wanlong Liu, Rongsheng Wang, Jianye Hou, Benyou Wang [Paper] [Code] [Wechat Blog]
-
Feng, Guhao, et al. "Towards revealing the mystery behind chain of thought: a theoretical perspective." Advances in Neural Information Processing Systems 36 (2024). [Paper]
-
He, Liqi, et al. "Multi-modal latent space learning for chain-of-thought reasoning in language models." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 38. No. 16. 2024. [Paper] [Code]
-
Yin, Han, et al. "Answering Spatial Commonsense Questions Based on Chain-of-Thought Reasoning with Adaptive Complexity." Asia-Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data. Singapore: Springer Nature Singapore, 2024. [Paper]
-
Hu, H., Lu, H., Zhang, H., Song, Y. Z., Lam, W., & Zhang, Y. Chain-of-Symbol Prompting for Spatial Relationships in Large Language Models. COLM 2024 [Paper] [Code]
-
Multimodal Chain-of-Thought Reasoning in Language Models. Zhang, Z.; Zhang, A.; Li, M.; Zhao, H.; Karypis, G.; and Smola. [Paper] [Code]
-
Wang, Keheng, et al. "Knowledge-driven cot: Exploring faithful reasoning in llms for knowledge-intensive question answering." arXiv preprint arXiv:2308.13259 (2023). [Paper]
-
[ICLR 2023]Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou [Paper]
-
Automatic Chain of Thought Prompting in Large Language Models Zhuosheng Zhang, Aston Zhang, Mu Li, Alex Smola [Paper]
-
[NeurIPS 2022]Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering Pan Lu, Swaroop Mishra, Tony Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, Ashwin Kalyan [Paper] [Code] [Leaderboard]
-
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, Denny Zhou [Paper]