CMMMU

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Introduction

CMMMU includes 12k manually collected multimodal questions from college exams, quizzes, and textbooks, covering six core disciplines: Art & Design, Business, Science, Health & Medicine, Humanities & Social Science, and Tech & Engineering, like its companion, MMMU. These questions span 30 subjects and comprise 39 highly heterogeneous image types, such as charts, diagrams, maps, tables, music sheets, and chemical structures.

🏆 Mini-Leaderboard

Model	Val (900)	Test (11K)
GPT-4V(ision) (Playground)	42.5	43.7
Qwen-VL-PLUS*	39.5	36.8
Yi-VL-34B	36.2	36.5
Yi-VL-6B	35.8	35.0
InternVL-Chat-V1.1*	34.7	34.0
Qwen-VL-7B-Chat	30.7	31.3
SPHINX-MoE*	29.3	29.5
InternVL-Chat-ViT-6B-Vicuna-7B	26.4	26.7
InternVL-Chat-ViT-6B-Vicuna-13B	27.4	26.1
CogAgent-Chat	24.6	23.6
Emu2-Chat	23.8	24.5
Chinese-LLaVA	25.5	23.4
VisCPM	25.2	22.7
mPLUG-OWL2	20.8	22.2
Frequent Choice	24.1	26.0
Random Choice	21.6	21.6

*: results provided by the authors.

Disclaimers

The guidelines for the annotators emphasized strict compliance with copyright and licensing rules from the initial data source, specifically avoiding materials from websites that forbid copying and redistribution. Should you encounter any data samples potentially breaching the copyright or licensing regulations of any site, we encourage you to contact us. Upon verification, such samples will be promptly removed.

Contact

• Ge Zhang: zhangge@01.ai
• Wenhao Huang: huangwenhao@01.ai
• Xinrun Du: duxinrun@01.ai
• Bei Chen: chenbei@01.ai
• Jie Fu: jiefu@ust.hk

Citation

BibTeX:

@article{zhang2024cmmmu,
        title={CMMMU: A Chinese Massive Multi-discipline Multimodal Understanding Benchmark},
        author={Ge, Zhang and Xinrun, Du and Bei, Chen and Yiming, Liang and Tongxu, Luo and Tianyu, Zheng and Kang, Zhu and Yuyang, Cheng and Chunpu, Xu and Shuyue, Guo and Haoran, Zhang and Xingwei, Qu and Junjie, Wang and Ruibin, Yuan and Yizhi, Li and Zekun, Wang and Yudong, Liu and Yu-Hsuan, Tsai and Fengji, Zhang and Chenghua, Lin and Wenhao, Huang and Jie, Fu},
        journal={arXiv preprint arXiv:2401.20847},
        year={2024},
      }