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Large Language Models (LLMs) have demonstrated remarkable performance in solving complex reasoning tasks through mechanisms like Chain-of-Thought (CoT) prompting, which emphasizes verbose, step-by-step reasoning.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
Earlier work this paper cites.
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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Name dataset
Philippe Remy. 2021 · 2021
Earlier work this paper cites.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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Self-consistency improves chain of thought reasoning in language models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2022 · 2022
Earlier work this paper cites.
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 V Le, and Denny Zhou. 2022 · 2022
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao. 2022 · 2022
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Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
BIG bench authors. 2023 · 2023
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Resprompt: Residual connection prompting advances multi-step reasoning in large language models
Song Jiang, Zahra Shakeri, Aaron Chan, Maziar Sanjabi, Hamed Firooz, Yinglong Xia, Bugra Akyildiz, Yizhou Sun, Jinchao Li, Qifan Wang, et al. 2023 · 2023
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Boosting logical reasoning in large language models through a new framework: The graph of thought
Bin Lei, Chunhua Liao, Caiwen Ding, et al. 2023 · 2023
Cited alongside, same era.
Skeleton-of-thought: Large language models can do parallel decoding
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, and Yu Wang. 2023 · 2023
Cited alongside, same era.
Thought propagation: An analogical approach to complex reasoning with large language models
Junchi Yu, Ran He, and Rex Ying. 2023 · 2023
Cited alongside, same era.
Draft & verify: Lossless large language model acceleration via self-speculative decoding
Jun Zhang, Jue Wang, Huan Li, Lidan Shou, Ke Chen, Gang Chen, and Sharad Mehrotra. 2023 · 2023
Cited alongside, same era.
Graph of thoughts: Solving elaborate problems with large language models
Maciej Besta, Nils Blach, Ales Kubicek, Robert Gerstenberger, Michal Podstawski, Lukas Gianinazzi, Joanna Gajda, Tomasz Lehmann, Hubert Niewiadomski, Piotr Nyczyk, et al. 2024 · 2024
Concise thoughts: Impact of output length on llm reasoning and cost
Sania Nayab, Giulio Rossolini, Giorgio Buttazzo, Nicolamaria Manes, and Fabrizio Giacomelli. 2024 · 2024
Later among the works it cites.
Openai o1 system card
OpenAI. 2024 · 2024
Later among the works it cites.
Qwq: Reflect deeply on the boundaries of the unknown
Qwen Team. 2024 · 2024
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Reasoning in token economies: Budget-aware evaluation of llm reasoning strategies
Junlin Wang, Siddhartha Jain, Dejiao Zhang, Baishakhi Ray, Varun Kumar, and Ben Athiwaratkun. 2024 · 2024
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An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al. 2024 · 2024
Later among the works it cites.
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Cited alongside, same era.
Over-reasoning and redundant calculation of large language models
Cheng-Han Chiang and Hung-yi Lee. 2024 · 2024
Cited alongside, same era.
Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al. 2024 · 2024
Cited alongside, same era.
Token-budget-aware llm reasoning
Tingxu Han, Chunrong Fang, Shiyu Zhao, Shiqing Ma, Zhenyu Chen, and Zhenting Wang. 2024 · 2024
Cited alongside, same era.
Training large language models to reason in a continuous latent space
Shibo Hao, Sainbayar Sukhbaatar, DiJia Su, Xian Li, Zhiting Hu, Jason Weston, and Yuandong Tian. 2024 · 2024
Cited alongside, same era.
Boosting of thoughts: Trial-and-error problem solving with large language models
Sijia Chen, Baochun Li, and Di Niu. 2024a
Cited in the paper.
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. 2024b
Cited in the paper.
Tree of thoughts: Deliberate problem solving with large language models
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Tom Griffiths, Yuan Cao, and Karthik Narasimhan. 2024 · 2024
Later among the works it cites.
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 · 2025
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Zoom. 2025 · 2025
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