AMANDA: Agentic Medical Knowledge Augmentation for Data-Efficient Medical Visual Question Answering (2025.findings-emnlp)
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| Challenge: | Existing Med-MLLMs fail when deployed in low-resource settings where abundant labeled data is unavailable. |
| Approach: | They propose a training-free agentic framework that performs medical knowledge augmentation via LLM agents. |
| Outcome: | The proposed framework performs medical knowledge augmentation via LLM agents. |
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Yu Sun, Xingyu Qian, Weiwen Xu, Hao Zhang, Chenghao Xiao, Long Li, Deli Zhao, Wenbing Huang, Tingyang Xu, Qifeng Bai, Yu Rong
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Medical Adaptation of Large Language and Vision-Language Models: Are We Making Progress? (2024.emnlp-main)
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| Challenge: | Several studies claim that domain-adaptive pretraining improves performance on downstream medical tasks. |
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