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Reinforcement learning (RL) has become a prevailing approach for fine-tuning large language models (LLMs) on complex reasoning tasks.
Function optimization using connectionist reinforcement learning algorithms
Williams, R. J. and Peng, J. (1991) · 1991
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Thinking fast and slow with deep learning and tree search
Anthony, T., Tian, Z., and Barber, D. (2017) · 2017
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Proximal policy optimization algorithms
Schulman, J., Wolski, F., Dhariwal, P., Radford, A., and Klimov, O. (2017) · 2017
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Buy 4 reinforce samples, get a baseline for free!
Kool, W., van Hoof, H., and Welling, M. (2019) · 2019
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Measuring mathematical problem solving with the math dataset
Hendrycks, D., Burns, C., Kadavath, S., Arora, A., Basart, S., Tang, E., Song, D., and Steinhardt, J. (2021) · 2021
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Bai, Y., Jones, A., Ndousse, K., Askell, A., Chen, A., DasSarma, N., Drain, D., Fort, S., Ganguli, D., Henighan, T., et al. (2022) · 2022
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Solving quantitative reasoning problems with language models
Lewkowycz, A., Andreassen, A., Dohan, D., Dyer, E., Michalewski, H., Ramasesh, V., Slone, A., Anil, C., Schlag, I., Gutman-Solo, T., et al. (2022) · 2022
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Training language models to follow instructions with human feedback
Ouyang, L., Wu, J., Jiang, X., Almeida, D., Wainwright, C., Mishkin, P., Zhang, C., Agarwal, S., Slama, K., Ray, A., et al. (2022) · 2022
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Star: Bootstrapping reasoning with reasoning
Zelikman, E., Wu, Y., Mu, J., and Goodman, N. (2022) · 2022
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RAFT: Reward ranked finetuning for generative foundation model alignment
Dong, H., Xiong, W., Goyal, D., Zhang, Y., Chow, W., Pan, R., Diao, S., Zhang, J., SHUM, K., and Zhang, T. (2023) · 2023
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Tora: A tool-integrated reasoning agent for mathematical problem solving
Gou, Z., Shao, Z., Gong, Y., Yang, Y., Huang, M., Duan, N., Chen, W., et al. (2023) · 2023
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Remax: A simple, effective, and efficient reinforcement learning method for aligning large language models
Li, Z., Xu, T., Zhang, Y., Yu, Y., Sun, R., and Luo, Z.-Q. (2023) · 2023
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Statistical rejection sampling improves preference optimization
Liu, T., Zhao, Y., Joshi, R., Khalman, M., Saleh, M., Liu, P. J., and Liu, J. (2023) · 2023
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Direct preference optimization: Your language model is secretly a reward model
Rafailov, R., Sharma, A., Mitchell, E., Ermon, S., Manning, C. D., and Finn, C. (2023) · 2023
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Llama 2: Open foundation and fine-tuned chat models
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., et al. (2023) · 2023
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Iterative preference learning from human feedback: Bridging theory and practice for rlhf under kl-constraint
Xiong, W., Dong, H., Ye, C., Wang, Z., Zhong, H., Ji, H., Jiang, N., and Zhang, T. (2023) · 2023
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Some things are more cringe than others: Preference optimization with the pairwise cringe loss
Xu, J., Lee, A., Sukhbaatar, S., and Weston, J. (2023) · 2023
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Metamath: Bootstrap your own mathematical questions for large language models
Yu, L., Jiang, W., Shi, H., Yu, J., Liu, Z., Zhang, Y., Kwok, J. T., Li, Z., Weller, A., and Liu, W. (2023) · 2023
Cited alongside, same era.
Deepseekmath: Pushing the limits of mathematical reasoning in open language models
Shao, Z., Wang, P., Zhu, Q., Xu, R., Song, J., Zhang, M., Li, Y., Wu, Y., and Guo, D. (2024) · 2024
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Policy filtration in rlhf to fine-tune llm for code generation
Shen, W. and Zhang, C. (2024) · 2024
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Hybridflow: A flexible and efficient rlhf framework
Sheng, G., Zhang, C., Ye, Z., Wu, X., Zhang, W., Zhang, R., Peng, Y., Lin, H., and Wu, C. (2024) · 2024
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Openmathinstruct-1: A 1.8 million math instruction tuning dataset
Toshniwal, S., Moshkov, I., Narenthiran, S., Gitman, D., Jia, F., and Gitman, I. (2024) · 2024
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Yuan, Z., Yuan, H., Li, C., Dong, G., Tan, C., and Zhou, C. (2023) · 2023
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Mammoth: Building math generalist models through hybrid instruction tuning
Yue, X., Xingwei Qu, G. Z., Fu, Y., Huang, W., Sun, H., Su, Y., and Chen, W. (2023) · 2023
Cited alongside, same era.
Slic-hf: Sequence likelihood calibration with human feedback
Zhao, Y., Joshi, R., Liu, T., Khalman, M., Saleh, M., and Liu, P. J. (2023) · 2023
Cited alongside, same era.
Back to basics: Revisiting reinforce style optimization for learning from human feedback in llms
Ahmadian, A., Cremer, C., Gallé, M., Fadaee, M., Kreutzer, J., Pietquin, O., Üstün, A., and Hooker, S. (2024) · 2024
Cited alongside, same era.
Numinamath 7b cot
Beeching, E., Huang, S. C., Jiang, A., Li, J., Lipkin, B., Qina, Z., Rasul, K., Shen, Z., Soletskyi, R., and Tunstall, L. (2024) · 2024
Cited alongside, same era.
Rlhf workflow: From reward modeling to online rlhf
Dong, H., Xiong, W., Pang, B., Wang, H., Zhao, H., Zhou, Y., Jiang, N., Sahoo, D., Xiong, C., and Zhang, T. (2024) · 2024
Cited alongside, same era.
Grattafiori, A., Dubey, A., Jauhri, A., Pandey, A., Kadian, A., Al-Dahle, A., Letman, A., Mathur, A., Schelten, A., Vaughan, A., et al. (2024) · 2024
Cited alongside, same era.
He, C., Luo, R., Bai, Y., Hu, S., Thai, Z. L., Shen, J., Hu, J., Han, X., Huang, Y., Zhang, Y., et al. (2024) · 2024
Cited alongside, same era.
Wang, H., Hao, S., Dong, H., Zhang, S., Bao, Y., Yang, Z., and Wu, Y. (2024) · 2024
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Building math agents with multi-turn iterative preference learning
Xiong, W., Shi, C., Shen, J., Rosenberg, A., Qin, Z., Calandriello, D., Khalman, M., Joshi, R., Piot, B., Saleh, M., et al. (2024) · 2024
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Self-rewarding language models
Yuan, W., Pang, R. Y., Cho, K., Sukhbaatar, S., Xu, J., and Weston, J. (2024) · 2024
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Automatic curriculum expert iteration for reliable llm reasoning
Zhao, Z., Dong, H., Saha, A., Xiong, C., and Sahoo, D. (2024) · 2024
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
DeepSeek-AI, Guo, D., Yang, D., Zhang, H., Song, J., Zhang, R., Xu, R., Zhu, Q., Ma, S., Wang, P., Bi, X., Zhang, X., Yu, X., Wu, Y., Wu, Z. F., Gou, Z., Shao, Z., Li, Z., Gao, Z., Liu, A., Xue, B., Wang, B., Wu, B., Feng, B., Lu, C., Zhao, C., Deng, C., Zhang, C., Ruan, C., Dai, D., Chen, D., Ji, D., Li, E., Lin, F., Dai, F., Luo, F., Hao, G., Chen, G., Li, G., Zhang, H., Bao, H., Xu, H., Wang, H., Ding, H., Xin, H., Gao, H., Qu, H., Li, H., Guo, J., Li, J., Wang, J., Chen, J., Yuan, J., Qiu, J., Li, J., Cai, J. L., Ni, J., Liang, J., Chen, J., Dong, K., Hu, K., Gao, K., Guan, K., Huang, K., Yu, K., Wang, L., Zhang, L., Zhao, L., Wang, L., Zhang, L., Xu, L., Xia, L., Zhang, M., Zhang, M., Tang, M., Li, M., Wang, M., Li, M., Tian, N., Huang, P., Zhang, P., Wang, Q., Chen, Q., Du, Q., Ge, R., Zhang, R., Pan, R., Wang, R., Chen, R. J., Jin, R. L., Chen, R., Lu, S., Zhou, S., Chen, S., Ye, S., Wang, S., Yu, S., Zhou, S., Pan, S., Li, S. S., Zhou, S., Wu, S., Ye, S., Yun, T., Pei, T., Sun, T., Wang, T., Zeng, W., Zhao, W., Liu, W., Liang, W., Gao, W., Yu, W., Zhang, W., Xiao, W. L., An, W., Liu, X., Wang, X., Chen, X., Nie, X., Cheng, X., Liu, X., Xie, X., Liu, X., Yang, X., Li, X., Su, X., Lin, X., Li, X. Q., Jin, X., Shen, X., Chen, X., Sun, X., Wang, X., Song, X., Zhou, X., Wang, X., Shan, X., Li, Y. K., Wang, Y. Q., Wei, Y. X., Zhang, Y., Xu, Y., Li, Y., Zhao, Y., Sun, Y., Wang, Y., Yu, Y., Zhang, Y., Shi, Y., Xiong, Y., He, Y., Piao, Y., Wang, Y., Tan, Y., Ma, Y., Liu, Y., Guo, Y., Ou, Y., Wang, Y., Gong, Y., Zou, Y., He, Y., Xiong, Y., Luo, Y., You, Y., Liu, Y., Zhou, Y., Zhu, Y. X., Xu, Y., Huang, Y., Li, Y., Zheng, Y., Zhu, Y., Ma, Y., Tang, Y., Zha, Y., Yan, Y., Ren, Z. Z., Ren, Z., Sha, Z., Fu, Z., Xu, Z., Xie, Z., Zhang, Z., Hao, Z., Ma, Z., Yan, Z., Wu, Z., Gu, Z., Zhu, Z., Liu, Z., Li, Z., Xie, Z., Song, Z., Pan, Z., Huang, Z., Xu, Z., Zhang, Z., and Zhang, Z. (2025) · 2025
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Reinforce++: A simple and efficient approach for aligning large language models
Hu, J. (2025) · 2025
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Search-r1: Training llms to reason and leverage search engines with reinforcement learning
Jin, B., Zeng, H., Yue, Z., Yoon, J., Arik, S., Wang, D., Zamani, H., and Han, J. (2025) · 2025
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Self-rewarding correction for mathematical reasoning
Xiong, W., Zhang, H., Ye, C., Chen, L., Jiang, N., and Zhang, T. (2025) · 2025
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Online-dpo-r1: Unlocking effective reasoning without the ppo overhead
Zhang, H., Yao, J., Ye, C., Xiong, W., and Zhang, T. (2025) · 2025
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