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Large language models (LLMs) have demonstrated remarkable reasoning capability in solving mathematical problems.
Thinking mathematically
Kaye Stacey, L Burton, and J Mason. 1982 · 1982
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Mawps: A math word problem repository
Rik Koncel-Kedziorski, Subhro Roy, Aida Amini, Nate Kushman, and Hannaneh Hajishirzi. 2016 · 2016
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Stimulating reflection and self-correcting reasoning through argument mapping: Three approaches
Michael HG Hoffmann. 2018 · 2018
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A diverse corpus for evaluating and developing English math word problem solvers
Shen-yun Miao, Chao-Chun Liang, and Keh-Yih Su. 2020 · 2020
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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 · 2021
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Advancing mathematics by guiding human intuition with ai
Alex Davies, Petar Veličković, Lars Buesing, Sam Blackwell, Daniel Zheng, Nenad Tomašev, Richard Tanburn, Peter Battaglia, Charles Blundell, András Juhász, et al. 2021 · 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 · 2021
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Star: Bootstrapping reasoning with reasoning
Eric Zelikman, Yuhuai Wu, Jesse Mu, and Noah Goodman. 2022 · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
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Learning from mistakes makes llm better reasoner
Shengnan An, Zexiong Ma, Zeqi Lin, Nanning Zheng, Jian-Guang Lou, and Weizhu Chen. 2023 · 2023
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Reflection-tuning: Recycling data for better instruction-tuning
Ming Li, Lichang Chen, Jiuhai Chen, Shwai He, and Tianyi Zhou. 2023 · 2023
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Wizardmath: Empowering mathematical reasoning for large language models via reinforced evol-instruct
Haipeng Luo, Qingfeng Sun, Can Xu, Pu Zhao, Jianguang Lou, Chongyang Tao, Xiubo Geng, Qingwei Lin, Shifeng Chen, and Dongmei Zhang. 2023 · 2023
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Teaching small language models to reason
Lucie Charlotte Magister, Jonathan Mallinson, Jakub Dominik Adamek, Eric Malmi, and Aliaksei Severyn. 2023 · 2023
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A comprehensive survey of few-shot learning: Evolution, applications, challenges, and opportunities
Yisheng Song, Ting Wang, Puyu Cai, Subrota K Mondal, and Jyoti Prakash Sahoo. 2023 · 2023
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Large language models are better reasoners with self-verification
Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Shengping Liu, Bin Sun, Kang Liu, and Jun Zhao · 2023
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Large language models are better reasoners with self-verification
Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Shengping Liu, Bin Sun, Kang Liu, and Jun Zhao. 2023 · 2023
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Scaling relationship on learning mathematical reasoning with large language models
Zheng Yuan, Hongyi Yuan, Chengpeng Li, Guanting Dong, Keming Lu, Chuanqi Tan, Chang Zhou, and Jingren Zhou. 2023 · 2023
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Unleashing reasoning capability of llms via scalable question synthesis from scratch
Yuyang Ding, Xinyu Shi, Xiaobo Liang, Juntao Li, Qiaoming Zhu, and Min Zhang. 2024 · 2024
Cited alongside, same era.
Improving factuality and reasoning in language models through multiagent debate
Yilun Du, Shuang Li, Antonio Torralba, Joshua B Tenenbaum, and Igor Mordatch. 2024 · 2024
Cited alongside, same era.
Small language model can self-correct
Haixia Han, Jiaqing Liang, Jie Shi, Qianyu He, and Yanghua Xiao. 2024 · 2024
Cited alongside, same era.
Key-point-driven data synthesis with its enhancement on mathematical reasoning
Yiming Huang, Xiao Liu, Yeyun Gong, Zhibin Gou, Yelong Shen, Nan Duan, and Weizhu Chen. 2024 · 2024
Cited alongside, same era.
Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, et al. 2024 · 2024
The effect of sampling temperature on problem solving in large language models
Matthew Renze. 2024 · 2024
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Self-reflection in llm agents: Effects on problem-solving performance
Matthew Renze and Erhan Guven. 2024 · 2024
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Reflexion: Language agents with verbal reinforcement learning
Noah Shinn, Federico Cassano, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2024 · 2024
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Beyond human data: Scaling self-training for problem-solving with language models
Avi Singh, John D Co-Reyes, Rishabh Agarwal, Ankesh Anand, Piyush Patil, Xavier Garcia, Peter J Liu, James Harrison, Jaehoon Lee, Kelvin Xu, et al. 2024 · 2024
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Mathscale: Scaling instruction tuning for mathematical reasoning
Zhengyang Tang, Xingxing Zhang, Benyou Wang, and Furu Wei. 2024 · 2024
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Cited alongside, same era.
Forward-backward reasoning in large language models for mathematical verification
Weisen Jiang, Han Shi, Longhui Yu, Zhengying Liu, Yu Zhang, Zhenguo Li, and James Kwok. 2024 · 2024
Cited alongside, same era.
Training language models to self-correct via reinforcement learning
Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, et al. 2024 · 2024
Cited alongside, same era.
Llm2llm: Boosting llms with novel iterative data enhancement
Nicholas Lee, Thanakul Wattanawong, Sehoon Kim, Karttikeya Mangalam, Sheng Shen, Gopala Anumanchipalli, Michael Mahoney, Kurt Keutzer, and Amir Gholami. 2024 · 2024
Cited alongside, same era.
Evaluating mathematical reasoning of large language models: A focus on error identification and correction
Xiaoyuan Li, Wenjie Wang, Moxin Li, Junrong Guo, Yang Zhang, and Fuli Feng. 2024d · 2024
Cited alongside, same era.
When hindsight is not 20/20: Testing limits on reflective thinking in large language models
Yanhong Li, Chenghao Yang, and Allyson Ettinger. 2024e · 2024
Cited alongside, same era.
Mathchat: Benchmarking mathematical reasoning and instruction following in multi-turn interactions
Zhenwen Liang, Dian Yu, Wenhao Yu, Wenlin Yao, Zhihan Zhang, Xiangliang Zhang, and Dong Yu. 2024 · 2024
Cited alongside, same era.
Let’s verify step by step
Hunter Lightman, Vineet Kosaraju, Yuri Burda, Harrison Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, and Karl Cobbe. 2024 · 2024
Cited alongside, same era.
Large language models can self-correct with key condition verification
Zhenyu Wu, Qingkai Zeng, Zhihan Zhang, Zhaoxuan Tan, Chao Shen, and Meng Jiang. 2024b · 2024
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ChatGLM-math: Improving math problem-solving in large language models with a self-critique pipeline
Yifan Xu, Xiao Liu, Xinghan Liu, Zhenyu Hou, Yueyan Li, Xiaohan Zhang, Zihan Wang, Aohan Zeng, Zhengxiao Du, Zhao Wenyi, Jie Tang, and Yuxiao Dong. 2024 · 2024
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Yuchen Yan, Jin Jiang, Yang Liu, Yixin Cao, Xin Xu, Xunliang Cai, Jian Shao, et al. 2024 · 2024
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Confidence vs critique: A decomposition of self-correction capability for llms
Zhe Yang, Yichang Zhang, Yudong Wang, Ziyao Xu, Junyang Lin, and Zhifang Sui. 2024 · 2024
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Small language models need strong verifiers to self-correct reasoning
Yunxiang Zhang, Muhammad Khalifa, Lajanugen Logeswaran, Jaekyeom Kim, Moontae Lee, Honglak Lee, and Lu Wang. 2024a · 2024
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Learn beyond the answer: Training language models with reflection for mathematical reasoning
Zhihan Zhang, Tao Ge, Zhenwen Liang, Wenhao Yu, Dian Yu, Mengzhao Jia, Dong Yu, and Meng Jiang. 2024b · 2024
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Jiuzhang3. 0: Efficiently improving mathematical reasoning by training small data synthesis models
Kun Zhou, Beichen Zhang, Jiapeng Wang, Zhipeng Chen, Wayne Xin Zhao, Jing Sha, Zhichao Sheng, Shijin Wang, and Ji-Rong Wen. 2024 · 2024
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rstar-math: Small llms can master math reasoning with self-evolved deep thinking
Xinyu Guan, Li Lyna Zhang, Yifei Liu, Ning Shang, Youran Sun, Yi Zhu, Fan Yang, and Mao Yang. 2025 · 2025
Closest in time.
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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On memory construction and retrieval for personalized conversational agents
Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Xufang Luo, Hao Cheng, Dongsheng Li, Yuqing Yang, Chin-Yew Lin, H Vicky Zhao, Lili Qiu, et al. 2025 · 2025
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Are nlp models really able to solve simple math word problems?
Arkil Patel, Satwik Bhattamishra, and Navin Goyal. 2021 · 2094
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