Xiaole Wen

AMANDA: Agentic Medical Knowledge Augmentation for Data-Efficient Medical Visual Question Answering

Medical Multimodal Large Language Models (Med-MLLMs) have shown great promise in medical visual question answering (Med-VQA). However, when deployed in low-resource settings where abundant labeled data are unavailable, existing Med-MLLMs commonly fail due to their medical reasoning capability bottle