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Recent studies generally enhance MLLMs' reasoning capabilities via supervised fine-tuning on high-quality chain-of-thought reasoning data, which often leads models to merely imitate successful reasoning paths without understanding what the wrong reasoning paths are.
Reinforcement learning: A survey
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Improving language understanding by generative pre-training
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Language models are few-shot learners
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Trl: Transformer reinforcement learning
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al · 2022
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Chartqa: A benchmark for question answering about charts with visual and logical reasoning
Ahmed Masry, Do Xuan Long, Jia Qing Tan, Shafiq Joty, and Enamul Hoque · 2022
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Mme: A comprehensive evaluation benchmark for multimodal large language models
Chaoyou Fu, Peixian Chen, Yunhang Shen, Yulei Qin, Mengdan Zhang, Xu Lin, Jinrui Yang, Xiawu Zheng, Ke Li, Xing Sun, et al · 2023
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Tianrui Guan, Fuxiao Liu, Xiyang Wu, Ruiqi Xian, Zongxia Li, Xiaoyu Liu, Xijun Wang, Lichang Chen, Furong Huang, Yaser Yacoob, et al · 2023
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Llava-med: Training a large language-and-vision assistant for biomedicine in one day
Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, and Jianfeng Gao · 2023
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Mathvista: Evaluating mathematical reasoning of foundation models in visual contexts
Pan Lu, Hritik Bansal, Tony Xia, Jiacheng Liu, Chunyuan Li, Hannaneh Hajishirzi, Hao Cheng, Kai-Wei Chang, Michel Galley, and Jianfeng Gao · 2023
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Macaw-llm: Multi-modal language modeling with image, audio, video, and text integration
Chenyang Lyu, Minghao Wu, Longyue Wang, Xinting Huang, Bingshuai Liu, Zefeng Du, Shuming Shi, and Zhaopeng Tu · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2023
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Next-gpt: Any-to-any multimodal llm
Shengqiong Wu, Hao Fei, Leigang Qu, Wei Ji, and Tat-Seng Chua · 2023
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mplug-docowl: Modularized multimodal large language model for document understanding
Jiabo Ye, Anwen Hu, Haiyang Xu, Qinghao Ye, Ming Yan, Yuhao Dan, Chenlin Zhao, Guohai Xu, Chenliang Li, Junfeng Tian, et al · 2023
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Pmc-vqa: Visual instruction tuning for medical visual question answering
Xiaoman Zhang, Chaoyi Wu, Ziheng Zhao, Weixiong Lin, Ya Zhang, Yanfeng Wang, and Weidi Xie · 2023
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Claude 3.5 sonnet, 2024
Anthropic · 2024
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Step-level value preference optimization for mathematical reasoning
Guoxin Chen, Minpeng Liao, Chengxi Li, and Kai Fan · 2024
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Are we on the right way for evaluating large vision-language models?
Lin Chen, Jinsong Li, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Zehui Chen, Haodong Duan, Jiaqi Wang, Yu Qiao, Dahua Lin, et al · 2024
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Self-play fine-tuning converts weak language models to strong language models
Zixiang Chen, Yihe Deng, Huizhuo Yuan, Kaixuan Ji, and Quanquan Gu · 2024
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How far are we to gpt-4v? closing the gap to commercial multimodal models with open-source suites
Zhe Chen, Weiyun Wang, Hao Tian, Shenglong Ye, Zhangwei Gao, Erfei Cui, Wenwen Tong, Kongzhi Hu, Jiapeng Luo, Zheng Ma, et al · 2024
Cited alongside, same era.
Videollama 2: Advancing spatial-temporal modeling and audio understanding in video-llms
Zesen Cheng, Sicong Leng, Hang Zhang, Yifei Xin, Xin Li, Guanzheng Chen, Yongxin Zhu, Wenqi Zhang, Ziyang Luo, Deli Zhao, et al · 2024
Cited alongside, same era.
Minicpm-v: A gpt-4v level mllm on your phone
Yuan Yao, Tianyu Yu, Ao Zhang, Chongyi Wang, Junbo Cui, Hongji Zhu, Tianchi Cai, Haoyu Li, Weilin Zhao, Zhihui He, et al · 2024
Later among the works it cites.
Rest-mcts*: Llm self-training via process reward guided tree search
Dan Zhang, Sining Zhoubian, Ziniu Hu, Yisong Yue, Yuxiao Dong, and Jie Tang · 2024
Later among the works it cites.
Mm1. 5: Methods, analysis & insights from multimodal llm fine-tuning
Haotian Zhang, Mingfei Gao, Zhe Gan, Philipp Dufter, Nina Wenzel, Forrest Huang, Dhruti Shah, Xianzhi Du, Bowen Zhang, Yanghao Li, et al · 2024
Later among the works it cites.
Vision-language models for vision tasks: A survey
Jingyi Zhang, Jiaxing Huang, Sheng Jin, and Shijian Lu · 2024
Later among the works it cites.
Historical test-time prompt tuning for vision foundation models
Jingyi Zhang, Jiaxing Huang, Xiaoqin Zhang, Ling Shao, and Shijian Lu · 2024
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Insight-v: Exploring long-chain visual reasoning with multimodal large language models
Yuhao Dong, Zuyan Liu, Hai-Long Sun, Jingkang Yang, Winston Hu, Yongming Rao, and Ziwei Liu · 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
Cited alongside, same era.
Building and better understanding vision-language models: insights and future directions
Hugo Laurençon, Andrés Marafioti, Victor Sanh, and Léo Tronchon · 2024
Cited alongside, same era.
Llava-next: Improved reasoning, ocr, and world knowledge, January 2024
Haotian Liu, Chunyuan Li, Yuheng Li, Bo Li, Yuanhan Zhang, Sheng Shen, and Yong Jae Lee · 2024
Cited alongside, same era.
Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2024
Cited alongside, same era.
Textmonkey: An ocr-free large multimodal model for understanding document
Yuliang Liu, Biao Yang, Qiang Liu, Zhang Li, Zhiyin Ma, Shuo Zhang, and Xiang Bai · 2024
Cited alongside, same era.
Reft: Reasoning with reinforced fine-tuning
Trung Quoc Luong, Xinbo Zhang, Zhanming Jie, Peng Sun, Xiaoran Jin, and Hang Li · 2024
Cited alongside, same era.
Introducing openai o1, 2024
OpenAI · 2024
Cited alongside, same era.
Later among the works it cites.
Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems?
Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin, Ziyu Guo, Pengshuo Qiu, Aojun Zhou, Pan Lu, Kai-Wei Chang, Yu Qiao, et al · 2024
Later among the works it cites.
Improve vision language model chain-of-thought reasoning
Ruohong Zhang, Bowen Zhang, Yanghao Li, Haotian Zhang, Zhiqing Sun, Zhe Gan, Yinfei Yang, Ruoming Pang, and Yiming Yang · 2024
Later among the works it cites.
Chengke Zou, Xingang Guo, Rui Yang, Junyu Zhang, Bin Hu, and Huan Zhang · 2024
Later among the works it cites.
Shuai Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Sibo Song, Kai Dang, Peng Wang, Shijie Wang, Jun Tang, et al · 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
Closest in time.
Vision-r1: Incentivizing reasoning capability in multimodal large language models
Wenxuan Huang, Bohan Jia, Zijie Zhai, Shaosheng Cao, Zheyu Ye, Fei Zhao, Zhe Xu, Yao Hu, and Shaohui Lin · 2025
Closest in time.
Gem: Empowering mllm for grounded ecg understanding with time series and images
Xiang Lan, Feng Wu, Kai He, Qinghao Zhao, Shenda Hong, and Mengling Feng · 2025
Closest in time.
Mm-eureka: Exploring the frontiers of multimodal reasoning with rule-based reinforcement learning
Fanqing Meng, Lingxiao Du, Zongkai Liu, Zhixiang Zhou, Quanfeng Lu, Daocheng Fu, Tiancheng Han, Botian Shi, Wenhai Wang, Junjun He, et al · 2025
Closest in time.
Lmm-r1: Empowering 3b lmms with strong reasoning abilities through two-stage rule-based rl
Yingzhe Peng, Gongrui Zhang, Miaosen Zhang, Zhiyuan You, Jie Liu, Qipeng Zhu, Kai Yang, Xingzhong Xu, Xin Geng, and Xu Yang · 2025
Closest in time.
Kimi k1. 5: Scaling reinforcement learning with llms
Kimi Team, Angang Du, Bofei Gao, Bowei Xing, Changjiu Jiang, Cheng Chen, Cheng Li, Chenjun Xiao, Chenzhuang Du, Chonghua Liao, et al · 2025
Closest in time.
Llamav-o1: Rethinking step-by-step visual reasoning in llms
Omkar Thawakar, Dinura Dissanayake, Ketan More, Ritesh Thawkar, Ahmed Heakl, Noor Ahsan, Yuhao Li, Mohammed Zumri, Jean Lahoud, Rao Muhammad Anwer, et al · 2025
Closest in time.
Measuring multimodal mathematical reasoning with math-vision dataset
Ke Wang, Junting Pan, Weikang Shi, Zimu Lu, Houxing Ren, Aojun Zhou, Mingjie Zhan, and Hongsheng Li · 2025
Closest in time.
Mmreason: An open-ended multi-modal multi-step reasoning benchmark for mllms toward agi
Huanjin Yao, Jiaxing Huang, Yawen Qiu, Michael K Chen, Wenzheng Liu, Wei Zhang, Wenjie Zeng, Xikun Zhang, Jingyi Zhang, Yuxin Song, et al · 2025
Closest in time.
R1-sharevl: Incentivizing reasoning capability of multimodal large language models via share-grpo
Huanjin Yao, Qixiang Yin, Jingyi Zhang, Min Yang, Yibo Wang, Wenhao Wu, Fei Su, Li Shen, Minghui Qiu, Dacheng Tao, et al · 2025
Closest in time.