Link DistillPath paper on arXiv

README.md

@@ -17,7 +17,7 @@ A 22M ViT-S/16 pathology tile encoder distilled from [H-optimus-0](https://huggi
 
 This is the ImageNet-initialized variant. For the stronger kaiko-initialized variant, see [DistillPath-KS16-HOpt0](https://huggingface.co/RamonK/DistillPath-KS16-HOpt0).
 
-**Paper:** [DistillPath: An Efficient 22M Distilled Pathology Encoder Approaching Large Foundation Model Performance](https://github.com/RamonKaspar/DistillPath)
+**Paper:** [DistillPath: An Efficient 22M Distilled Pathology Encoder Approaching Large Foundation Model Performance](https://arxiv.org/abs/2608.17872)
 Ramon Kaspar, Andrey Ignatov, Valentina Boeva. ETH Zurich.
 Published at the ECCV 2026 Workshop on Medical Foundation Models and Benchmarks (MedFM-Bench).