Link paper and project page to model card

README.md

@@ -1,8 +1,8 @@
 ---
-license: cc-by-nc-sa-4.0
 language:
 - en
 library_name: sam2
+license: cc-by-nc-sa-4.0
 pipeline_tag: image-segmentation
 tags:
 - whole-slide-imaging
@@ -13,7 +13,11 @@ tags:
 
 # AtlasPatch: Whole-Slide Image Tissue Segmentation
 
-Segmentation model for whole-slide image (WSI) thumbnails, built on **Segment Anything 2 (SAM2) Tiny** and finetuned only on the normalization layers. The model takes a **power-based WSI thumbnail at 1.25x magnification level (resized to 1024×1024)** and predicts a binary tissue mask. Training used segmented thumbnails. AtlasPatch codebase (WSI preprocessing & tooling): https://github.com/AtlasAnalyticsLab/AtlasPatch
+[Paper](https://huggingface.co/papers/2602.03998) | [Project Page](https://atlasanalyticslab.github.io/AtlasPatch/) | [GitHub](https://github.com/AtlasAnalyticsLab/AtlasPatch)
+
+Segmentation model for whole-slide image (WSI) thumbnails, introduced in the paper [AtlasPatch: An Efficient and Scalable Tool for Whole Slide Image Preprocessing in Computational Pathology](https://huggingface.co/papers/2602.03998). 
+
+The model is built on **Segment Anything 2 (SAM2) Tiny** and finetuned only on the normalization layers. The model takes a **power-based WSI thumbnail at 1.25x magnification level (resized to 1024×1024)** and predicts a binary tissue mask. Training used segmented thumbnails. 
 
 ## Quickstart
 
@@ -89,8 +93,8 @@ If you use this model, please cite our paper:
 @article{atlaspatch2025,
   title   = {AtlasPatch: An Efficient and Scalable Tool for Whole Slide Image Preprocessing in Computational Pathology},
   author  = {Alagha, Ahmed and Leclerc, Christopher and Kotp, Yousef and Abdelwahed, Omar and Moras, Calvin and Rentopoulos, Peter and Rostami, Rose and Nguyen, Bich Ngoc and Baig, Jumanah and Khellaf, Abdelhakim and Trinh, Vincent Quoc-Huy and Mizouni, Rabeb and Otrok, Hadi and Bentahar, Jamal and Hosseini, Mahdi S.},
-  journal = {arXiv},
+  journal = {arXiv preprint arXiv:2602.03998},
   year    = {2025},
-  url     = {TODO: coming soon}
+  url     = {https://huggingface.co/papers/2602.03998}
 }
-```
+```