# Resources

Licensing and credits for the MedVision benchmark and the `medvision_bm` codebase. See the [front page](index.md) for the citation and the canonical project links.

:::{tip}
For a reproducible environment, pull the published Docker image rather than resolving pinned dependencies by hand. See [Installation](getting-started/installation.md) for the setup path.
:::

## License

The `medvision_bm` package is distributed under **Creative Commons Attribution 4.0 (CC-BY 4.0)** — see the license metadata in `pyproject.toml` and <https://creativecommons.org/licenses/by/4.0/>. The MedVision annotations themselves are released under the same **CC-BY 4.0** license, which permits reuse and adaptation for academic and commercial work provided you give appropriate credit.

:::{warning}
MedVision is a **meta-dataset**: it layers new annotations on top of many independently published source datasets. The CC-BY 4.0 grant covers only MedVision's own annotations — it does **not** relicense the underlying imaging data. Any use of a given case must also honour the original license and usage terms of the dataset that case was drawn from. Confirming compliance for every constituent source is the user's responsibility.
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## Acknowledgements

This work was supported by UK Research and Innovation (grant **EP/S02431X/1**), through the UKRI Centre for Doctoral Training in Biomedical AI at the University of Edinburgh, School of Informatics.

MedVision builds directly on several open-source projects:

- **[lmms-eval](https://github.com/EvolvingLMMs-Lab/lmms-eval)** — the VLM evaluation framework underpinning the benchmark harness.
- **[lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness)** — LLM evaluation framework.
- **[vLLM](https://github.com/vllm-project/vllm)** — high-throughput LLM/VLM inference backend.
- **[verl](https://github.com/volcengine/verl)** — reinforcement learning for LLMs, used for RFT (via the [medvision-rl fork](https://github.com/YongchengYAO/verl/tree/medvision-rl)).
- **[TRL](https://github.com/huggingface/trl)** — supervised and preference post-training utilities.