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Self-evolving trainin--where models iteratively learn from their own outputs--has emerged as a key approach for complex reasoning tasks, addressing the scarcity of high-quality chain-of-thought data.
A diagram is worth a dozen images
Kembhavi, A., Salvato, M., Kolve, E., Seo, M., Hajishirzi, H., and Farhadi, A · 2016
Earlier work this paper cites.
Proximal policy optimization algorithms
Schulman, J., Wolski, F., Dhariwal, P., Radford, A., and Klimov, O · 2017
Earlier work this paper cites.
Learning transferable visual models from natural language supervision
Radford, A., Kim, J. W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al · 2021
Earlier work this paper cites.
Incoder: A generative model for code infilling and synthesis
Fried, D., Aghajanyan, A., Lin, J., Wang, S., Wallace, E., Shi, F., Zhong, R., Yih, S., Zettlemoyer, L., and Lewis, M · 2022
Earlier work this paper cites.
Large language models can self-improve
Huang, J., Gu, S. S., Hou, L., Wu, Y., Wang, X., Yu, H., and Han, J · 2022
Earlier work this paper cites.
ChartQA: A benchmark for question answering about charts with visual and logical reasoning
Masry, A., Do, X. L., Tan, J. Q., Joty, S., and Hoque, E · 2022
Earlier work this paper cites.
Star: Bootstrapping reasoning with reasoning
Zelikman, E., Wu, Y., Mu, J., and Goodman, N · 2022
Earlier work this paper cites.
Qwen-vl: A versatile vision-language model for understanding, localization, text reading, and beyond
Bai, J., Bai, S., Yang, S., Wang, S., Tan, S., Wang, P., Lin, J., Zhou, C., and Zhou, J · 2023
Earlier work this paper cites.
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
Earlier work this paper cites.
G-llava: Solving geometric problem with multi-modal large language model
Gao, J., Pi, R., Zhang, J., Ye, J., Zhong, W., Wang, Y., Hong, L., Han, J., Xu, H., Li, Z., et al · 2023
Earlier work this paper cites.
Reinforced self-training (rest) for language modeling
Gulcehre, C., Paine, T. L., Srinivasan, S., Konyushkova, K., Weerts, L., Sharma, A., Siddhant, A., Ahern, A., Wang, M., Gu, C., et al · 2023
Earlier work this paper cites.
Manipllm: Embodied multimodal large language model for object-centric robotic manipulation, 2023
Li, X., Zhang, M., Geng, Y., Geng, H., Long, Y., Shen, Y., Zhang, R., Liu, J., and Dong, H · 2023
Earlier work this paper cites.
Lightman, H., Kosaraju, V., Burda, Y., Edwards, H., Baker, B., Lee, T., Leike, J., Schulman, J., Sutskever, I., and Cobbe, K · 2023
Earlier work this paper cites.
Visual instruction tuning
Liu, H., Li, C., Wu, Q., and Lee, Y. J · 2023
Earlier work this paper cites.
Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts
Lu, P., Bansal, H., Xia, T., Liu, J., Li, C., Hajishirzi, H., Cheng, H., Chang, K.-W., Galley, M., and Gao, J · 2023
Cited alongside, same era.
Beyond human data: Scaling self-training for problem-solving with language models
Singh, A., Co-Reyes, J. D., Agarwal, R., Anand, A., Patil, P., Liu, P. J., Harrison, J., Lee, J., Xu, K., Parisi, A., et al · 2023
Cited alongside, same era.
Lidar-llm: Exploring the potential of large language models for 3d lidar understanding, 2023
Yang, S., Liu, J., Zhang, R., Pan, M., Guo, Z., Li, X., Chen, Z., Gao, P., Guo, Y., and Zhang, S · 2023
Cited alongside, same era.
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
Cited alongside, same era.
V-star: Training verifiers for self-taught reasoners
Hosseini, A., Yuan, X., Malkin, N., Courville, A., Sordoni, A., and Agarwal, R · 2024
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Introducing meta llama 3: The most capable openly available llm to date, 2024
Meta · 2024
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Iterative reasoning preference optimization
Pang, R. Y., Yuan, W., Cho, K., He, H., Sukhbaatar, S., and Weston, J · 2024
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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
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Math-llava: Bootstrapping mathematical reasoning for multimodal large language models
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Yuan, Z., Yuan, H., Li, C., Dong, G., Lu, K., Tan, C., Zhou, C., and Zhou, J · 2023
Cited alongside, same era.
Mammoth: Building math generalist models through hybrid instruction tuning
Yue, X., Qu, X., Zhang, G., Fu, Y., Huang, W., Sun, H., Su, Y., and Chen, W · 2023
Cited alongside, same era.
Sigmoid loss for language image pre-training
Zhai, X., Mustafa, B., Kolesnikov, A., and Beyer, L · 2023
Cited alongside, same era.
Phi-3 technical report: A highly capable language model locally on your phone
Abdin, M., Aneja, J., Awadalla, H., Awadallah, A., Awan, A. A., Bach, N., Bahree, A., Bakhtiari, A., Bao, J., Behl, H., et al · 2024
Cited alongside, same era.
Cai, Z., Cao, M., Chen, H., Chen, K., Chen, K., Chen, X., Chen, X., Chen, Z., Chen, Z., Chu, P., et al · 2024
Cited alongside, same era.
M 3 CoT: A novel benchmark for multi-domain multi-step multi-modal chain-of-thought
Chen, Q., Qin, L., Zhang, J., Chen, Z., Xu, X., and Che, W · 2024
Cited alongside, same era.
Enhancing large vision language models with self-training on image comprehension
Deng, Y., Lu, P., Yin, F., Hu, Z., Shen, S., Zou, J., Chang, K.-W., and Wang, W · 2024
Cited alongside, same era.
Dubey, A., Jauhri, A., Pandey, A., Kadian, A., Al-Dahle, A., Letman, A., Mathur, A., Schelten, A., Yang, A., Fan, A., et al · 2024
Cited alongside, same era.
Shi, W., Hu, Z., Bin, Y., Liu, J., Yang, Y., Ng, S.-K., Bing, L., and Lee, R. K.-W · 2024
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Easy-to-hard generalization: Scalable alignment beyond human supervision
Sun, Z., Yu, L., Shen, Y., Liu, W., Yang, Y., Welleck, S., and Gan, C · 2024
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Math-shepherd: Verify and reinforce LLMs step-by-step without human annotations
Wang, P., Li, L., Shao, Z., Xu, R., Dai, D., Li, Y., Chen, D., Wu, Y., and Sui, Z · 2024
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Progress or regress? self-improvement reversal in post-training
Wu, T., Li, X., and Liu, P · 2024
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Minicpm-v: A gpt-4v level mllm on your phone
Yao, Y., Yu, T., Zhang, A., Wang, C., Cui, J., Zhu, H., Cai, T., Li, H., Zhao, W., He, Z., et al · 2024
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Mavis: Mathematical visual instruction tuning
Zhang, R., Wei, X., Jiang, D., Zhang, Y., Guo, Z., Tong, C., Liu, J., Zhou, A., Wei, B., Zhang, S., et al · 2024
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Web-shepherd: Advancing prms for reinforcing web agents, 2025
Chae, H., Kim, S., Cho, J., Kim, S., Moon, S., Hwangbo, G., Lim, D., Kim, M., Hwang, Y., Gwak, M., Choi, D., Kang, M., Im, G., Cho, B., Kim, H., Han, J. H., Kwon, T., Kim, M., woo Kwak, B., Kang, D., and Yeo, J · 2025
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning, 2025
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
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Mmbench: Is your multi-modal model an all-around player?
Liu, Y., Duan, H., Zhang, Y., Li, B., Zhang, S., Zhao, W., Yuan, Y., Wang, J., He, C., Liu, Z., et al · 2025
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