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---
task_categories:
- multiple-choice
- question-answering
- visual-question-answering
language:
- en
size_categories:
- 1K<n<10K
configs:
- config_name: testmini
data_files:
- split: testmini
path: testmini.parquet
dataset_info:
- config_name: testmini
features:
- name: sample_index
dtype: string
- name: problem_index
dtype: string
- name: problem_version
dtype: string
- name: question
dtype: string
- name: image
dtype: image
- name: answer
dtype: string
- name: question_type
dtype: string
- name: metadata
struct:
- name: split
dtype: string
- name: source
dtype: string
- name: subject
dtype: string
- name: subfield
dtype: string
- name: query_wo
dtype: string
- name: query_cot
dtype: string
- name: question_for_eval
dtype: string
- name: passrate_for_qwen2.5_vl_7b
dtype: float64
- name: difficulty_level_for_qwen2.5_vl_7b
dtype: int64
splits:
- name: testmini
num_bytes: 166789963
num_examples: 3940
license: mit
---
# MathVerse with difficulty level tags
This dataset extends the 🤗 [MathVerse testmini](https://huggingface.co/datasets/AI4Math/MathVerse) benchmark by introducing two additional tags: **passrate_for_qwen2.5_vl_7b** and **difficulty_level_for_qwen2.5_vl_7b**. Further details are available in our paper [The Synergy Dilemma of Long-CoT SFT and RL: Investigating Post-Training Techniques for Reasoning VLMs](https://www.arxiv.org/pdf/2507.07562).
## 🚀 Data Usage
```python
from datasets import load_dataset
dataset = load_dataset("JierunChen/MathVerse_with_difficulty_level")
print(dataset)
```
## 📑 Citation
If you find this benchmark useful in your research, please consider citing this BibTex:
```latex
@inproceedings{zhang2024mathverse,
title={MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?},
author={Renrui Zhang, Dongzhi Jiang, Yichi Zhang, Haokun Lin, Ziyu Guo, Pengshuo Qiu, Aojun Zhou, Pan Lu, Kai-Wei Chang, Peng Gao, Hongsheng Li},
booktitle={arXiv},
year={2024}
}
@misc{chen2025synergydilemmalongcotsft,
title={The Synergy Dilemma of Long-CoT SFT and RL: Investigating Post-Training Techniques for Reasoning VLMs},
author={Jierun Chen and Tiezheng Yu and Haoli Bai and Lewei Yao and Jiannan Wu and Kaican Li and Fei Mi and Chaofan Tao and Lei Zhu and Manyi Zhang and Xiaohui Li and Lu Hou and Lifeng Shang and Qun Liu},
year={2025},
eprint={2507.07562},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2507.07562},
}
``` |