Add pipeline tag and link to code

README.md

@@ -1,15 +1,21 @@
 ---
 base_model:
 - xinlai/LISA-7B-v1
+pipeline_tag: image-text-to-text
 ---
 
 # ROSALIA-7B-v1
 
-**ROSALIA** is a vision-language model (VLM) designed for precise lesion segmentation in chest X-rays (CXRs).
+**ROSALIA** is a vision-language model (VLM) designed for precise lesion segmentation in chest X-rays (CXRs). It is a LISA model fine-tuned on the **MIMIC-ILS** dataset, a large-scale instruction-answer dataset for CXR lesion segmentation.
+
+ROSALIA is capable of **Instruction-Guided Lesion Segmentation (ILS)**, a medical-domain adaptation of referring image segmentation (RIS), allowing it to segment diverse lesions and provide textual explanations in response to simple, user-friendly instructions.
 
 This model is the core checkpoint of the paper:  
 **[Instruction-Guided Lesion Segmentation for Chest X-rays with Automatically Generated Large-Scale Dataset](https://arxiv.org/abs/2511.15186)**, accepted to **CVPR 2026**.
 
+- **Code:** [https://github.com/checkoneee/ROSALIA](https://github.com/checkoneee/ROSALIA)
+- **Paper:** [arXiv:2511.15186](https://arxiv.org/abs/2511.15186)
+
 ## 📖 Citation
 
 If you find this model or the related research useful, please cite our work:
@@ -20,4 +26,5 @@ If you find this model or the related research useful, please cite our work:
   author={Choi, Geon and Yoon, Hangyul and Shin, Hyunju and Park, Hyunki and Seo, Sang Hoon and Yang, Eunho and Choi, Edward},
   journal={arXiv preprint arXiv:2511.15186},
   year={2025}
-}
+}
+```