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Enhancing Generalization in Medical Visual Question Answering Tasks via Gradient-Guided Model Perturbation
In this paper, we introduce a method that incorporates gradient-guided parameter perturbations to the visual encoder of the multimodality model during both pre-training and fine-tuning phases, to improve model generalization for downstream medical VQA tasks.
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