meta_data.py

# CONSTANTS-URL
URL = "http://opencompass.openxlab.space/assets/MathLB.json"
# CONSTANTS-CITATION
CITATION_BUTTON_TEXT = r"""\
@inproceedings{duan2024vlmevalkit,
  title={Vlmevalkit: An open-source toolkit for evaluating large multi-modality models},
  author={Duan, Haodong and Yang, Junming and Qiao, Yuxuan and Fang, Xinyu and Chen, Lin and Liu, Yuan and Dong, Xiaoyi and Zang, Yuhang and Zhang, Pan and Wang, Jiaqi and others},
  booktitle={Proceedings of the 32nd ACM International Conference on Multimedia},
  pages={11198--11201},
  year={2024}
}
"""
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results"
# CONSTANTS-TEXT
LEADERBORAD_INTRODUCTION = """# Open LMM Reasoning Leaderboard

This leaderboard aims at providing a comprehensive evaluation of the reasoning capabilities of LMMs. 
Currently, it is a collection of evaluation results on multiple multi-modal mathematical reasoning benchmarks. 
We obtain all evaluation results based on the [VLMEvalKit](https://github.com/open-compass/VLMEvalKit), with the corresponding dataset names: 

1. MathVista_MINI: The Test Mini split of MathVista dataset, around 1000 samples.
2. MathVision: The Full test set of MathVision, around 3000 samples.
3. MathVerse_MINI_Vision_Only: The Test Mini split of MathVerse, using the "Vision Only" mode, around 700 samples.
4. DynaMath: The Full test set of DynaMath, around 5000 samples (501 original questions x 10 variants).

To suggest new models or benchmarks for this leaderboard, please contact duanhaodong@pjlab.org.cn.
"""

# CONSTANTS-FIELDS
DATASETS_ALL = ['MathVista', 'MathVision', 'MathVerse', 'DynaMath']
DATASETS_ESS = ['MathVista', 'MathVision', 'MathVerse', 'DynaMath']
META_FIELDS = ['Method', 'Param (B)', 'Language Model', 'Vision Model', 'OpenSource', 'Verified', 'Org']
MODEL_SIZE = ['<4B', '4B-10B', '10B-20B', '20B-40B', '>40B', 'Unknown']
MODEL_TYPE = ['OpenSource', 'API']