Update README.md

README.md

@@ -13,7 +13,7 @@ library_name: pytorch
 
 # GrapHist: Graph Self-Supervised Learning for Histopathology
 
-This repository contains the pre-trained model from [GrapHist](https://github.com/ogutsevda/graphist). Pre-trained on the [graph-tcga-brca](https://huggingface.co/datasets/ogutsevda/graph-tcga-brca) dataset, it employs an **ACM-GIN** (Adaptive Channel Mixing Graph Isomorphism Network) encoder-decoder architecture with a masked node attribute prediction objective.
+This repository contains the pre-trained model from [GrapHist](https://github.com/ogutsevda/graphist). Pre-trained on the [graph-tcga-brca](https://huggingface.co/datasets/ogutsevda/graph-tcga-brca) dataset, it employs an **ACM-GIN** (Adaptive Channel Mixing Graph Isomorphism Network) encoder-decoder architecture with a masked node attribute prediction objective. Please check the associated [preprint](https://arxiv.org/pdf/2603.00143) for details.
 
 <p align="center">
   <img src="graphist.png" alt="GrapHist architecture" width="100%">
@@ -107,10 +107,11 @@ The model architecture adapts code from [GraphMAE](https://github.com/THUDM/Grap
 ## Citation
 
 ```bibtex
-@article{graphist2025,
-  title     = {GrapHist: Graph Self-Supervised Learning for Histopathology},
-  author    = {TODO},
-  journal   = {TODO},
-  year      = {2025},
+@misc{ogut2026graphist,
+    title={GrapHist: Graph Self-Supervised Learning for Histopathology}, 
+    author={Sevda Öğüt and Cédric Vincent-Cuaz and Natalia Dubljevic and Carlos Hurtado and Vaishnavi Subramanian and Pascal Frossard and Dorina Thanou},
+    year={2026},
+    eprint={2603.00143},
+    url={https://arxiv.org/abs/2603.00143}, 
 }
 ```