| license: cc-by-nc-4.0 | |
| dataset_info: | |
| features: | |
| - name: ID | |
| dtype: string | |
| - name: split | |
| dtype: string | |
| - name: knowledge concept | |
| dtype: string | |
| - name: question | |
| dtype: string | |
| - name: option | |
| dtype: string | |
| - name: answer | |
| dtype: string | |
| - name: image_path | |
| dtype: image | |
| - name: key | |
| dtype: string | |
| - name: question number | |
| dtype: int64 | |
| - name: knowledge concept description | |
| dtype: string | |
| splits: | |
| - name: testmini | |
| num_bytes: 44509869 | |
| num_examples: 1740 | |
| download_size: 23075805 | |
| dataset_size: 44509869 | |
| task_categories: | |
| - question-answering | |
| - text-generation | |
| language: | |
| - en | |
| tags: | |
| - LLM | |
| - NLP | |
| - CV | |
| size_categories: | |
| - 1K<n<10K | |
| # Dataset Card for WE-MATH (ACL 2025) | |
| [GitHub](https://github.com/We-Math/We-Math) | [Paper](https://arxiv.org/pdf/2407.01284) | [Website](https://we-math.github.io/) | |
| Inspired by human-like mathematical reasoning, we introduce We-Math, the first benchmark specifically designed to explore the problem-solving principles beyond the end-to-end performance. We meticulously collect and categorize 6.5K visual math problems, spanning 67 hierarchical knowledge concepts and 5 layers of knowledge granularity. | |
| ## Citation | |
| If you find the content of this project helpful, please cite our paper as follows: | |
| ``` | |
| @article{qiao2024we, | |
| title={We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?}, | |
| author={Qiao, Runqi and Tan, Qiuna and Dong, Guanting and Wu, Minhui and Sun, Chong and Song, Xiaoshuai and GongQue, Zhuoma and Lei, Shanglin and Wei, Zhe and Zhang, Miaoxuan and others}, | |
| journal={arXiv preprint arXiv:2407.01284}, | |
| year={2024} | |
| } | |
| ``` |