Papers with Multi-modal Concept Alignment Pre-training

1 papers
Multi-modal Concept Alignment Pre-training for Generative Medical Visual Question Answering (2024.findings-acl)

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Challenge: Medical Visual Question Answering (Med-VQA) aims to provide accurate answers to questions regarding medical images, a task particularly challenging for open-ended questions.
Approach: They propose a multi-modal concept alignment pre-training approach for generative Med-VQA that leverages a knowledge graph sourced from medical image-caption datasets and the Unified Medical Language System.
Outcome: The proposed approach significantly outperforms existing methods on a set of benchmark datasets and shows high efficiency and knowledge-image alignment capability.

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