Add link to paper

README.md

@@ -1,26 +1,28 @@
 ---
 license: cc-by-nc-sa-4.0
-pretty_name: RepConTUR AbdomenAtlas Annotations
+size_categories:
+- 1K<n<10K
 task_categories:
-  - image-segmentation
-  - visual-question-answering
-  - text-generation
+- image-segmentation
+- visual-question-answering
+- text-generation
+pretty_name: RepConTUR AbdomenAtlas Annotations
 tags:
-  - medical
-  - radiology
-  - ct
-  - 3d
-  - tumor-segmentation
-  - referring-segmentation
-  - report-generation
-size_categories:
-  - 1K<n<10K
+- medical
+- radiology
+- ct
+- 3d
+- tumor-segmentation
+- referring-segmentation
+- report-generation
 ---
 
 # RepConTUR AbdomenAtlas Annotations
 
 Official annotations for "RepConTUR: A Report-Conditioned Volumetric Multimodal Model for Abdominal Tumor Segmentation".
 
+**Paper:** [RepConTUR: A Report-Conditioned Volumetric Multimodal Model for Abdominal Tumor Segmentation](https://huggingface.co/papers/2610.40094)
+
 This dataset extends [AbdomenAtlas 3.0 Mini](https://huggingface.co/datasets/AbdomenAtlas/AbdomenAtlas3.0Mini) to
 suborgan-level promptable tumor segmentation and report-derived visual question answering. It holds **annotations
 only**: the CT volumes and the original masks must be downloaded from AbdomenAtlas 3.0 Mini.
@@ -135,4 +137,4 @@ AbdomenAtlas 3.0 and RadGPT when you use this dataset, as well as:
   author = {Lee, Seunghwan and Park, Sangjoon and Lee, Jongmin and Kim, Yoon Jo and Cho, Wonyoung and Kim, Jin Sung and Chae, Han Joo},
   year   = {2026}
 }
-```
+```