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--- |
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license: apache-2.0 |
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base_model: |
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- liuhaotian/llava-v1.5-7b |
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base_model_relation: finetune |
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pipeline_tag: image-text-to-text |
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tags: |
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- RRG |
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- Radiology Report Generation |
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- Chest X-ray |
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- Multimodal Large Language Models |
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library_name: transformers |
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datasets: |
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- StanfordAIMI/rrg24-shared-task-bionlp |
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--- |
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# **Med-CXRGen-I Model Card** |
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**Task**: Radiology Report Generation – Impression section (RRG Shared Task) |
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## Paper and Resources |
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For details on Med-CXRGen-I, including its architecture, training strategy, and evaluation—please refer to the following resources: |
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- 📘 **Paper:** [Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report Generation](https://aclanthology.org/2024.bionlp-1.54/) |
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- 💻 Code Repository: [GitHub: Med-CXRGen](https://github.com/X-iZhang/RRG-BioNLP-ACL2024) |
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--- |
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## How to Cite ✒️ |
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If you use this model in academic or research contexts, please cite: |
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```bibtex |
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@inproceedings{zhang-etal-2024-gla, |
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title = "Gla-{AI}4{B}io{M}ed at {RRG}24: Visual Instruction-tuned Adaptation for Radiology Report Generation", |
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author = "Zhang, Xi and |
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Meng, Zaiqiao and |
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Lever, Jake and |
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Ho, Edmond S.L.", |
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editor = "Demner-Fushman, Dina and |
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Ananiadou, Sophia and |
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Miwa, Makoto and |
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Roberts, Kirk and |
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Tsujii, Junichi", |
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booktitle = "Proceedings of the 23rd Workshop on Biomedical Natural Language Processing", |
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month = aug, |
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year = "2024", |
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address = "Bangkok, Thailand", |
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publisher = "Association for Computational Linguistics", |
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url = "https://aclanthology.org/2024.bionlp-1.54/", |
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doi = "10.18653/v1/2024.bionlp-1.54", |
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pages = "624--634", |
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} |
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``` |
