Min Kim

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2024

pdf bib
TEAM MIPAL at MEDIQA-M3G 2024: Large VQA Models for Dermatological Diagnosis
Hyeonjin Kim | Min Kim | Jae Jang | KiYoon Yoo | Nojun Kwak
Proceedings of the 6th Clinical Natural Language Processing Workshop

This paper describes the methods used for the NAACL 2024 workshop MEDIQA-M3G shared task for generating medical answers from image and query data for skin diseases. MedVInT-Decoder, LLaVA, and LLaVA-Med are chosen as base models. Finetuned with the task dataset on the dermatological domain, MedVInT-Decoder achieved a BLEU score of 3.82 during competition, while LLaVA and LLaVA-Med reached 6.98 and 4.62 afterward, respectively.
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