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README.md
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path: data/test-*
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- split: train
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path: data/train-*
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---
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path: data/test-*
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- split: train
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path: data/train-*
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license: cc
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task_categories:
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- image-text-to-text
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language:
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- en
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tags:
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- medical
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- biology
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size_categories:
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- 10K<n<100K
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---
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# MediX-R1: Open-Ended Medical Reinforcement Learning
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<p align="center">
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<img src="https://huggingface.co/MBZUAI/MediX-R1-30B/resolve/main/assets/logo_white_no_bg.png" alt="MediX-R1" width="200">
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</p>
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<p align="center">
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<img src="https://i.imgur.com/waxVImv.png" alt="MediX-R1">
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</p>
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#### **Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI), UAE**
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[](https://medix.cvmbzuai.com)
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[](https://arxiv.org/pdf/2602.23363)
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[](https://huggingface.co/collections/MBZUAI/medix-r1)
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[](https://medix.cvmbzuai.com/leaderboard)
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---
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## Model Zoo
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| Model | HuggingFace |
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|-------|-------------|
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| MediX-R1-2B | [MBZUAI/MediX-R1-2B](https://huggingface.co/MBZUAI/MediX-R1-2B) |
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| MediX-R1-8B | [MBZUAI/MediX-R1-8B](https://huggingface.co/MBZUAI/MediX-R1-8B) |
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| MediX-R1-30B | [MBZUAI/MediX-R1-30B](https://huggingface.co/MBZUAI/MediX-R1-30B) |
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---
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## Citation
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If you use MediX-R1 in your research, please cite our work as follows:
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```bibtex
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@misc{mullappilly2026medixr1openendedmedical,
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title={MediX-R1: Open Ended Medical Reinforcement Learning},
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author={Sahal Shaji Mullappilly and Mohammed Irfan Kurpath and Omair Mohamed and Mohamed Zidan and Fahad Khan and Salman Khan and Rao Anwer and Hisham Cholakkal},
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year={2026},
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eprint={2602.23363},
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archivePrefix={arXiv},
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primaryClass={cs.CV},
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url={https://arxiv.org/abs/2602.23363},
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}
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```
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---
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## License
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This project is released for **research purposes only** under [*CC-BY-NC-SA 4.0*](https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.en) License. It is not intended for clinical or commercial use.
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Users are urged to employ MediX-R1 responsibly, especially when applying its outputs in real-world medical scenarios. It is imperative to verify the model's advice with qualified healthcare professionals and not rely on it for medical diagnoses or treatment decisions.
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---
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## Acknowledgements
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We are thankful to [EasyR1](https://github.com/hiyouga/EasyR1) (a fork of [veRL](https://github.com/volcengine/verl)) for their open-source RL training framework.
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This work was partially supported with *NVIDIA Academic Grant 2025* and *MBZUAI-IITD* Research Collaboration Seed Grant.
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We are grateful to [MBZUAI](https://mbzuai.ac.ae/) for compute and support.
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