Fetching the paper…
Reading the bibliography…
Recent breakthroughs in reasoning language models have significantly advanced text-based reasoning.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Earlier work this paper cites.
From images to textual prompts: Zero-shot VQA with frozen large language models
Jiaxian Guo, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Boyang Li, Dacheng Tao, and Steven CH Hoi · 2022
Earlier work this paper cites.
PromptCap: Prompt-guided task-aware image captioning
Yushi Hu, Hang Hua, Zhengyuan Yang, Weijia Shi, Noah A Smith, and Jiebo Luo · 2022
Earlier work this paper cites.
BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven Hoi · 2022
Earlier work this paper cites.
Plug-and-play VQA: Zero-shot VQA by conjoining large pretrained models with zero training
Anthony Meng Huat Tiong, Junnan Li, Boyang Li, Silvio Savarese, and Steven CH Hoi · 2022
Earlier work this paper cites.
CoCa: Contrastive captioners are image-text foundation models
Jiahui Yu, Zirui Wang, Vijay Vasudevan, Legg Yeung, Mojtaba Seyedhosseini, and Yonghui Wu · 2022
Earlier work this paper cites.
Gaining Wisdom from Setbacks: Aligning large language models via mistake analysis
Kai Chen, Chunwei Wang, Kuo Yang, Jianhua Han, Lanqing Hong, Fei Mi, Hang Xu, Zhengying Liu, Wenyong Huang, Zhenguo Li, Dit-Yan Yeung, Lifeng Shang, Xin Jiang, and Qun Liu · 2023
Earlier work this paper cites.
Mixture of cluster-conditional lora experts for vision-language instruction tuning
Yunhao Gou, Zhili Liu, Kai Chen, Lanqing Hong, Hang Xu, Aoxue Li, Dit-Yan Yeung, James T Kwok, and Yu Zhang · 2023
Earlier work this paper cites.
SEED-Bench: Benchmarking multimodal llms with generative comprehension
Bohao Li, Rui Wang, Guangzhi Wang, Yuying Ge, Yixiao Ge, and Ying Shan · 2023
Earlier work this paper cites.
MM-Vet: Evaluating large multimodal models for integrated capabilities
Weihao Yu, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Zicheng Liu, Xinchao Wang, and Lijuan Wang · 2023
Earlier work this paper cites.
Judging LLM-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al · 2023
Earlier work this paper cites.
AIME problems and solutions, 2024
AIME · 2024
Earlier work this paper cites.
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
Earlier work this paper cites.
VLMEvalKit: An open-source toolkit for evaluating large multi-modality models
Haodong Duan, Junming Yang, Yuxuan Qiao, Xinyu Fang, Lin Chen, Yuan Liu, Xiaoyi Dong, Yuhang Zang, Pan Zhang, Jiaqi Wang, et al · 2024
Earlier work this paper cites.
Eyes Closed, Safety On: Protecting multimodal LLMs via image-to-text transformation
Yunhao Gou, Kai Chen, Zhili Liu, Lanqing Hong, Hang Xu, Zhenguo Li, Dit-Yan Yeung, James T Kwok, and Yu Zhang · 2024
Earlier work this paper cites.
Aaron Hurst, Adam Lerer, Adam P Goucher, Adam Perelman, Aditya Ramesh, Aidan Clark, AJ Ostrow, Akila Welihinda, Alan Hayes, Alec Radford, et al · 2024
Earlier work this paper cites.
Aaron Jaech, Adam Kalai, Adam Lerer, Adam Richardson, Ahmed El-Kishky, Aiden Low, Alec Helyar, Aleksander Madry, Alex Beutel, Alex Carney, et al · 2024
Cited alongside, same era.
OpenAI · 2024
Cited alongside, same era.
We-Math: Does your large multimodal model achieve human-like mathematical reasoning?
Runqi Qiao, Qiuna Tan, Guanting Dong, Minhui Wu, Chong Sun, Xiaoshuai Song, Zhuoma GongQue, Shanglin Lei, Zhe Wei, Miaoxuan Zhang, et al · 2024
Cited alongside, same era.
QVQ: To see the world with wisdom
Qwen · 2024
Cited alongside, same era.
GPQA: A graduate-level google-proof Q&A benchmark
David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R Bowman · 2024
Cited alongside, same era.
Claude 3.7 Sonnet System Card
Anthropic · 2025
Closest in time.
Shuai Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Sibo Song, Kai Dang, Peng Wang, Shijie Wang, Jun Tang, Humen Zhong, Yuanzhi Zhu, Mingkun Yang, Zhaohai Li, Jianqiang Wan, Pengfei Wang, Wei Ding, Zheren Fu, Yiheng Xu, Jiabo Ye, Xi Zhang, Tianbao Xie, Zesen Cheng, Hang Zhang, Zhibo Yang, Haiyang Xu, and Junyang Lin · 2025
Closest in time.
Gemini 2.0 Flash
Google DeepMind · 2025
Closest in time.
Corrupted but Not Broken: Rethinking the impact of corrupted data in visual instruction tuning
Yunhao Gou, Hansi Yang, Zhili Liu, Kai Chen, Yihan Zeng, Lanqing Hong, Zhenguo Li, Qun Liu, James T Kwok, and Yu Zhang · 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
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
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, YK Li, Y Wu, et al · 2024
Cited alongside, same era.
Grok, 2024
xAI · 2024
Cited alongside, same era.
LogicVista: Multimodal LLM logical reasoning benchmark in visual contexts
Yijia Xiao, Edward Sun, Tianyu Liu, and Wei Wang · 2024
Cited alongside, same era.
An Yang, Baosong Yang, Beichen Zhang, Binyuan Hui, Bo Zheng, Bowen Yu, Chengyuan Li, Dayiheng Liu, Fei Huang, Haoran Wei, et al · 2024
Cited alongside, same era.
Kaining Ying, Fanqing Meng, Jin Wang, Zhiqian Li, Han Lin, Yue Yang, Hao Zhang, Wenbo Zhang, Yuqi Lin, Shuo Liu, et al · 2024
Cited alongside, same era.
MMMU: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, et al · 2024
Cited alongside, same era.
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
Cited alongside, same era.
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.
OmniCaptioner: One captioner to rule them all
Yiting Lu, Jiakang Yuan, Zhen Li, Shitian Zhao, Qi Qin, Xinyue Li, Le Zhuo, Licheng Wen, Dongyang Liu, Yuewen Cao, et al · 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.
HybridFlow: A flexible and efficient rlhf framework
Guangming Sheng, Chi Zhang, Zilingfeng Ye, Xibin Wu, Wang Zhang, Ru Zhang, Yanghua Peng, Haibin Lin, and Chuan Wu · 2025
Closest in time.
Openthinkimg: Learning to think with images via visual tool reinforcement learning
Zhaochen Su, Linjie Li, Mingyang Song, Yunzhuo Hao, Zhengyuan Yang, Jun Zhang, Guanjie Chen, Jiawei Gu, Juntao Li, Xiaoye Qu, et al · 2025
Closest in time.
Countqa: How well do mllms count in the wild?
Jayant Sravan Tamarapalli, Rynaa Grover, Nilay Pande, and Sahiti Yerramilli · 2025
Closest in time.
SRPO: Enhancing multimodal LLM reasoning via reflection-aware reinforcement learning
Zhongwei Wan, Zhihao Dou, Che Liu, Yu Zhang, Dongfei Cui, Qinjian Zhao, Hui Shen, Jing Xiong, Yi Xin, Yifan Jiang, et al · 2025
Closest in time.
DAPO: An open-source LLM reinforcement learning system at scale
Qiying Yu, Zheng Zhang, Ruofei Zhu, Yufeng Yuan, Xiaochen Zuo, Yu Yue, Weinan Dai, Tiantian Fan, Gaohong Liu, Lingjun Liu, et al · 2025
Closest in time.
Deepeyes: Incentivizing" thinking with images" via reinforcement learning
Ziwei Zheng, Michael Yang, Jack Hong, Chenxiao Zhao, Guohai Xu, Le Yang, Chao Shen, and Xing Yu · 2025
Closest in time.
Reinforced visual perception with tools
Zetong Zhou, Dongping Chen, Zixian Ma, Zhihan Hu, Mingyang Fu, Sinan Wang, Yao Wan, Zhou Zhao, and Ranjay Krishna · 2025
Closest in time.
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
Closest in time.