Add link to paper

This PR adds a direct link to the paper [LUTSeg: A Longitudinal Multi-Expert Dataset for Ulcer Tissue Segmentation](https://huggingface.co/papers/2608.25866) in the model card's content. The existing YAML metadata already correctly captures the dataset, license, pipeline tag, and relevant tags, so no metadata changes are needed.

README.md

@@ -1,19 +1,21 @@
 ---
+datasets:
+- ksanchez84/LUTSeg
 library_name: pytorch
-pipeline_tag: image-segmentation
 license: apache-2.0
-datasets:
-  - ksanchez84/LUTSeg
+pipeline_tag: image-segmentation
 tags:
-  - medical
-  - semantic-segmentation
-  - semi-supervised-learning
-  - dinov2
-  - medsiglip
+- medical
+- semantic-segmentation
+- semi-supervised-learning
+- dinov2
+- medsiglip
 ---
 
 # TiSage Segmentation Checkpoints
 
+This model is associated with the paper [LUTSeg: A Longitudinal Multi-Expert Dataset for Ulcer Tissue Segmentation](https://huggingface.co/papers/2608.25866).
+
 Trained checkpoints associated with the paper settings for **TiSage: Tissue
 Segmentation with Multi-Scale Semantic Guidance**, released with the code and reproducibility material at
 [carlosh93/TiSage](https://github.com/carlosh93/TiSage). The paper was selected
@@ -112,4 +114,4 @@ the complete attribution and scope.
 
 Please cite *LUTSeg: A Longitudinal Multi-Expert Dataset for Ulcer Tissue
 Segmentation*, Eleventh ISIC Skin Image Analysis Workshop @ MICCAI 2026. Final
-proceedings metadata will be added when the bibliographic record is public.
+proceedings metadata will be added when the bibliographic record is public.