Datasets:
Release MedMM-ExpertRubric evaluation dataset
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- README.md +61 -0
- SHA256SUMS +541 -0
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README.md
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---
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language:
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- en
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task_categories:
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- visual-question-answering
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size_categories:
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- n<1K
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tags:
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- medical
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- multimodal
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- evaluation
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- rubric
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- huatuogpt-vision-2
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configs:
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- config_name: default
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data_files:
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- split: test
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path: medmm_expert_rubric.json
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---
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<div align="center">
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<h1>MedMM-ExpertRubric</h1>
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<a href="https://openreview.net/pdf?id=0BXKsjKlFJ">📄 Paper</a> |
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<a href="https://github.com/FreedomIntelligence/HuatuoGPT-Vision-2">💻 GitHub</a>
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</div>
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## ⚡ Introduction
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**MedMM-ExpertRubric** is the open-ended medical multimodal benchmark released with **HuatuoGPT-Vision-2**, containing **500 questions, 538 images, and 11,088 weighted rubric items**.
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- **Diverse medical images.** Covers radiology, pathology, ultrasound, endoscopy, and other modalities, including 32 multi-image questions.
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- **Fine-grained evaluation.** Positive rubric items reward correct findings. Negative items penalize specified errors.
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## 🚀 Usage
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Load the downloaded data:
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```python
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import json
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from pathlib import Path
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from PIL import Image
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root = Path("/path/to/MedMM-ExpertRubric")
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dataset = json.loads((root / "medmm_expert_rubric.json").read_text())
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case = dataset[0]
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images = [Image.open(root / path) for path in case["images"]]
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print(case["question"])
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```
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Provide the question and images in order to the model. Use the rubrics for evaluation only. Do not include the caption in model input.
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## 📖 Citation
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```bibtex
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@inproceedings{chen2026incentivizing,
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title={Incentivizing Medical Vision Capabilities from Large-Scale Multimodal Pre-training},
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author={Chen, Junying and Cai, Zhenyang and Yang, Yunjin and Cai, Kunyuan and Wang, Rongsheng and Wang, Xidong and Yu, Geyang and Feng, Xiangyi and Wang, Benyou},
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booktitle={The Fortieth Annual Conference on Neural Information Processing Systems},
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year={2026}
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}
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```
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| 1 |
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0cc844a041a46ce9c396577086b7ceacc3dd89c523109a27de19de5b9a3f287c README.md
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| 2 |
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fe12abc29f85c6bf76694a5835440fd5318d4bedf76b63f1c7f06cb368b2b01c images/000_figure1.jpg
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64225b91741a5e7a1e503cd6f6e064a793e406b8c1bd3741ae70933fecb527eb images/001_figure1.jpg
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bb2f92feff415e8b6e22d4e337023dfc1ab0beb26069b4597c6500980b09feb9 images/002_figure1.jpg
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12af57bc7c70e517ea5417a5d5af8d3e33f62bd41d6545959ad37a58f6d900b5 images/003_figure1.jpg
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6e76bdbe36542cb235d66c9d54298d69397df9ef90035a9dd0deb7293b4489e9 images/003_figure2.jpg
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9ec91e71398cf18eaf3f74da4f5ebf4dc2e7cdd31c86d971c8531a259bec4e46 images/004_figure1.jpg
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3f43fa7dd6b56537cda5660a4ce5a7591068965f5eab0c0d07e8a1aa38eac179 images/005_figure1.jpg
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18d2febc5776e81eb13ce3848d0be1fdad2849b7a035c8e14321527d94f8799c images/006_figure1.jpg
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21329c8eb43a7e9bc7950f9be088c6ac7616a1b5378a3f590e748568018bb6b2 images/007_figure1.jpg
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Git LFS Details
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images/040_figure1.jpg
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Git LFS Details
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images/041_figure1.jpg
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Git LFS Details
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images/042_figure1.jpg
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Git LFS Details
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images/043_figure1.jpg
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Git LFS Details
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Git LFS Details
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Git LFS Details
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images/046_figure1.jpg
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Git LFS Details
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