m-a-p/CMMMU

Dataset

CMMMU

31

30 commits

1 linked in READMEs

updated Sep 5, 2024

See the code

README

CMMMU

๐ŸŒ Homepage | ๐Ÿค— Paper | ๐Ÿ“– arXiv | ๐Ÿค— Dataset | GitHub

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.

Alt text

๐Ÿ† Mini-Leaderboard

ModelVal (900)Test (11K)
GPT-4V(ision) (Playground)42.543.7
Qwen-VL-PLUS*39.536.8
Yi-VL-34B36.236.5
Yi-VL-6B35.835.0
InternVL-Chat-V1.1*34.734.0
Qwen-VL-7B-Chat30.731.3
SPHINX-MoE*29.329.5
InternVL-Chat-ViT-6B-Vicuna-7B26.426.7
InternVL-Chat-ViT-6B-Vicuna-13B27.426.1
CogAgent-Chat24.623.6
Emu2-Chat23.824.5
Chinese-LLaVA25.523.4
VisCPM25.222.7
mPLUG-OWL220.822.2
Frequent Choice24.126.0
Random Choice21.621.6

*: 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

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},
      }

Contributors

dododododo

25 commits

XI
XinrunDu

3 commits

davanstrien

1 commits

zhangysk

1 commits

m-a-p/CMMMU

Dataset

CMMMU

31

30 commits

1 linked in READMEs

updated Sep 5, 2024

See the code

README

CMMMU

๐ŸŒ Homepage | ๐Ÿค— Paper | ๐Ÿ“– arXiv | ๐Ÿค— Dataset | GitHub

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.

Alt text

๐Ÿ† Mini-Leaderboard

ModelVal (900)Test (11K)
GPT-4V(ision) (Playground)42.543.7
Qwen-VL-PLUS*39.536.8
Yi-VL-34B36.236.5
Yi-VL-6B35.835.0
InternVL-Chat-V1.1*34.734.0
Qwen-VL-7B-Chat30.731.3
SPHINX-MoE*29.329.5
InternVL-Chat-ViT-6B-Vicuna-7B26.426.7
InternVL-Chat-ViT-6B-Vicuna-13B27.426.1
CogAgent-Chat24.623.6
Emu2-Chat23.824.5
Chinese-LLaVA25.523.4
VisCPM25.222.7
mPLUG-OWL220.822.2
Frequent Choice24.126.0
Random Choice21.621.6

*: 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

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},
      }

Contributors

dododododo

25 commits

XI
XinrunDu

3 commits

davanstrien

1 commits

zhangysk

1 commits