ROSALIA-7B-v1

ROSALIA is a vision-language model (VLM) designed for precise lesion segmentation in chest X-rays (CXRs).

This model is the core checkpoint of the paper:
Instruction-Guided Lesion Segmentation for Chest X-rays with an Automatically Generated Large-Scale Dataset, accepted to CVPR 2026.

πŸ“– Citation

If you find this model or the related research useful, please cite our work:

@article{choi2025instruction,
  title={Instruction-Guided Lesion Segmentation for Chest X-rays with Automatically Generated Large-Scale Dataset},
  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}
}
Downloads last month
27
Inference Providers NEW
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support

Model tree for checkone/ROSALIA-7B-v1

Base model

xinlai/LISA-7B-v1
Finetuned
(3)
this model

Paper for checkone/ROSALIA-7B-v1