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insight - Medical Visual Question Answering
Latent Prompt Assist Model for Enhancing Medical Visual Question Answering Performance
The Latent Prompt Assist (LaPA) model leverages latent prompts to filter and extract clinically relevant information from uni-modal and multi-modal features, enabling improved performance in medical visual question answering tasks.
A Comprehensive Medical Visual Question Answering Benchmark for Evaluating Large Vision-Language Models
OmniMedVQA is a large-scale and diverse medical visual question answering dataset that can comprehensively evaluate the capabilities of large vision-language models in the medical domain.
Fusion of Domain-Adapted Vision and Language Models for Improved Medical Visual Question Answering
A novel vision-language model that integrates a radiology domain-adapted language model and a biomedical vision encoder to achieve state-of-the-art performance on medical visual question answering benchmarks.
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