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Multimodal Reward Models (MRMs) play a crucial role in enhancing the performance of Multimodal Large Language Models (MLLMs).
Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov · 2017
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Kun Shao, Zhentao Tang, Yuanheng Zhu, Nannan Li, and Dongbin Zhao · 2019
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Zhe Chen, Jiannan Wu, Wenhai Wang, Weijie Su, Guo Chen, Sen Xing, Muyan Zhong, Qinglong Zhang, Xizhou Zhu, Lewei Lu, Bin Li, Ping Luo, Tong Lu, Yu Qiao, and Jifeng Dai · 2023
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Lei Li, Zhihui Xie, Mukai Li, Shunian Chen, Peiyi Wang, Liang Chen, Yazheng Yang, Benyou Wang, and Lingpeng Kong · 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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Aligning large multimodal models with factually augmented rlhf
Zhiqing Sun, Sheng Shen, Shengcao Cao, Haotian Liu, Chunyuan Li, Yikang Shen, Chuang Gan, Liang-Yan Gui, Yu-Xiong Wang, Yiming Yang, Kurt Keutzer, and Trevor Darrell · 2023
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Pixtral 12b
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Mllm-as-a-judge: Assessing multimodal llm-as-a-judge with vision-language benchmark
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Nvlm: Open frontier-class multimodal llms
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Molmo and pixmo: Open weights and open data for state-of-the-art multimodal models
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Vita: Towards open-source interactive omni multimodal llm
Chaoyou Fu, Haojia Lin, Zuwei Long, Yunhang Shen, Meng Zhao, Yifan Zhang, Shaoqi Dong, Xiong Wang, Di Yin, Long Ma, et al · 2024
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Mme-survey: A comprehensive survey on evaluation of multimodal llms
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Openrlhf: An easy-to-use, scalable and high-performance rlhf framework
Jian Hu, Xibin Wu, Zilin Zhu, Xianyu, Weixun Wang, Dehao Zhang, and Yu Cao · 2024
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Llava-onevision: Easy visual task transfer
Bo Li, Yuanhan Zhang, Dong Guo, Renrui Zhang, Feng Li, Hao Zhang, Kaichen Zhang, Peiyuan Zhang, Yanwei Li, Ziwei Liu, et al · 2024
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Vlrewardbench: A challenging benchmark for vision-language generative reward models
Lei Li, Yuancheng Wei, Zhihui Xie, Xuqing Yang, Yifan Song, Peiyi Wang, Chenxin An, Tianyu Liu, Sujian Li, Bill Yuchen Lin, Lingpeng Kong, and Qi Liu · 2024
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Skywork-reward: Bag of tricks for reward modeling in llms
Chris Yuhao Liu, Liang Zeng, Jiacai Liu, Rui Yan, Jujie He, Chaojie Wang, Shuicheng Yan, Yang Liu, and Yahui Zhou · 2024
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Uncertainty-aware reward model: Teaching reward models to know what is unknown
Xingzhou Lou, Dong Yan, Wei Shen, Yuzi Yan, Jian Xie, and Junge Zhang · 2024
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Wildvision: Evaluating vision-language models in the wild with human preferences
Yujie Lu, Dongfu Jiang, Wenhu Chen, William Yang Wang, Yejin Choi, and Bill Yuchen Lin · 2024
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Inf-orm-llama3.1-70b, 2024
Xiaoyu Tan Minghao Yang, Chao Qu · 2024
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Introducing openai o1-preview
OpenAI · 2024
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Deepseekmath: Pushing the limits of mathematical reasoning in open language models
Zhihong Shao, Peiyi Wang, Qihao Zhu, Runxin Xu, Junxiao Song, Xiao Bi, Haowei Zhang, Mingchuan Zhang, Y. K. Li, Y. Wu, and Daya Guo · 2024
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Qwen2-vl: Enhancing vision-language model’s perception of the world at any resolution
Peng Wang, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, et al · 2024
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Helpsteer2: Open-source dataset for training top-performing reward models, 2024
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Aonian Li, Bangwei Gong, Bo Yang, Boji Shan, Chang Liu, Cheng Zhu, Chunhao Zhang, Congchao Guo, Da Chen, Dong Li, et al · 2025
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Inference-time scaling for generalist reward modeling
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Dama: Data- and model-aware alignment of multi-modal llms
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Zhilin Wang, Yi Dong, Olivier Delalleau, Jiaqi Zeng, Gerald Shen, Daniel Egert, Jimmy J. Zhang, Makesh Narsimhan Sreedhar, and Oleksii Kuchaiev · 2024
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Show-o: One single transformer to unify multimodal understanding and generation
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Llava-critic: Learning to evaluate multimodal models
Tianyi Xiong, Xiyao Wang, Dong Guo, Qinghao Ye, Haoqi Fan, Quanquan Gu, Heng Huang, and Chunyuan Li · 2024
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Rlaif-v: Open-source ai feedback leads to super gpt-4v trustworthiness
Tianyu Yu, Haoye Zhang, Qiming Li, Qixin Xu, Yuan Yao, Da Chen, Xiaoman Lu, Ganqu Cui, Yunkai Dang, Taiwen He, Xiaocheng Feng, Jun Song, Bo Zheng, Zhiyuan Liu, Tat-Seng Chua, and Maosong Sun · 2024
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Self-generated critiques boost reward modeling for language models
Yue Yu, Zhengxing Chen, Aston Zhang, Liang Tan, Chenguang Zhu, Richard Yuanzhe Pang, Yundi Qian, Xuewei Wang, Suchin Gururangan, Chao Zhang, et al · 2024
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Benchmarking large multimodal models against common corruptions
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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
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Judge anything: Mllm as a judge across any modality
Shu Pu, Yaochen Wang, Dongping Chen, Yuhang Chen, Guohao Wang, Qi Qin, Zhongyi Zhang, Zhiyuan Zhang, Zetong Zhou, Shuang Gong, et al · 2025
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Tapered off-policy reinforce: Stable and efficient reinforcement learning for llms
Nicolas Le Roux, Marc G Bellemare, Jonathan Lebensold, Arnaud Bergeron, Joshua Greaves, Alex Fréchette, Carolyne Pelletier, Eric Thibodeau-Laufer, Sándor Toth, and Sam Work · 2025
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Vlm-r1: A stable and generalizable r1-style large vision-language model
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Long-vita: Scaling large multi-modal models to 1 million tokens with leading short-context accuracy, 2025
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Visualprm: An effective process reward model for multimodal reasoning, 2025
Weiyun Wang, Zhangwei Gao, Lianjie Chen, Zhe Chen, Jinguo Zhu, Xiangyu Zhao, Yangzhou Liu, Yue Cao, Shenglong Ye, Xizhou Zhu, Lewei Lu, Haodong Duan, Yu Qiao, Jifeng Dai, and Wenhai Wang · 2025
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Logic-rl: Unleashing llm reasoning with rule-based reinforcement learning
Tian Xie, Zitian Gao, Qingnan Ren, Haoming Luo, Yuqian Hong, Bryan Dai, Joey Zhou, Kai Qiu, Zhirong Wu, and Chong Luo · 2025
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Mme-unify: A comprehensive benchmark for unified multimodal understanding and generation models
Wulin Xie, Yi-Fan Zhang, Chaoyou Fu, Yang Shi, Bingyan Nie, Hongkai Chen, Zhang Zhang, Liang Wang, and Tieniu Tan · 2025
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Multimodal rewardbench: Holistic evaluation of reward models for vision language models
Michihiro Yasunaga, Luke Zettlemoyer, and Marjan Ghazvininejad · 2025
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Dapo: An open-source llm reinforcement learning system at scale
Qiying Yu, Zheng Zhang, Ruofei Zhu, Yufeng Yuan, Xiaochen Zuo, Yu Yue, Tiantian Fan, Gaohong Liu, Lingjun Liu, Xin Liu, et al · 2025
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Aligning multimodal llm with human preference: A survey
Tao Yu, Chaoyou Fu, Junkang Wu, Jinda Lu, Kun Wang, Xingyu Lu, Yunhang Shen, Guibin Zhang, Dingjie Song, Yibo Yan, et al · 2025
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Internlm-xcomposer2. 5-reward: A simple yet effective multi-modal reward model
Yuhang Zang, Xiaoyi Dong, Pan Zhang, Yuhang Cao, Ziyu Liu, Shengyuan Ding, Shenxi Wu, Yubo Ma, Haodong Duan, Wenwei Zhang, et al · 2025
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Llava-mini: Efficient image and video large multimodal models with one vision token, 2025
Shaolei Zhang, Qingkai Fang, Zhe Yang, and Yang Feng · 2025
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Mm-rlhf: The next step forward in multimodal llm alignment
Yi-Fan Zhang, Tao Yu, Haochen Tian, Chaoyou Fu, Peiyan Li, Jianshu Zeng, Wulin Xie, Yang Shi, Huanyu Zhang, Junkang Wu, et al · 2025
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R1-omni: Explainable omni-multimodal emotion recognition with reinforcing learning
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Internvl3: Exploring advanced training and test-time recipes for open-source multimodal models
Jinguo Zhu, Weiyun Wang, Zhe Chen, Zhaoyang Liu, Shenglong Ye, Lixin Gu, Yuchen Duan, Hao Tian, Weijie Su, Jie Shao, et al · 2025
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