---
license: apache-2.0
base_model:
- liuhaotian/llava-v1.5-7b
base_model_relation: finetune
pipeline_tag: image-text-to-text
tags:
- RRG
- Radiology Report Generation
- Chest X-ray
- Multimodal Large Language Models
library_name: transformers
datasets:
- StanfordAIMI/rrg24-shared-task-bionlp
---
# **Med-CXRGen-I Model Card**

**Task**: Radiology Report Generation – Impression section (RRG Shared Task)

## Paper and Resources

For details on Med-CXRGen-I, including its architecture, training strategy, and evaluation—please refer to the following resources:
- 📘 **Paper:** [Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report Generation](https://aclanthology.org/2024.bionlp-1.54/)
- 💻 Code Repository: [GitHub: Med-CXRGen](https://github.com/X-iZhang/RRG-BioNLP-ACL2024)

---

## How to Cite ✒️

If you use this model in academic or research contexts, please cite:

```bibtex
@inproceedings{zhang-etal-2024-gla,
    title = "Gla-{AI}4{B}io{M}ed at {RRG}24: Visual Instruction-tuned Adaptation for Radiology Report Generation",
    author = "Zhang, Xi  and
      Meng, Zaiqiao  and
      Lever, Jake  and
      Ho, Edmond S.L.",
    editor = "Demner-Fushman, Dina  and
      Ananiadou, Sophia  and
      Miwa, Makoto  and
      Roberts, Kirk  and
      Tsujii, Junichi",
    booktitle = "Proceedings of the 23rd Workshop on Biomedical Natural Language Processing",
    month = aug,
    year = "2024",
    address = "Bangkok, Thailand",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2024.bionlp-1.54/",
    doi = "10.18653/v1/2024.bionlp-1.54",
    pages = "624--634",
}
```