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MedUAG sets a new standard in medical multimodal models, achieving strong performance across diverse understanding and generation tasks with the largest dataset yet.
MedUP reveals that integrating visual perception and language understanding in a single token space can dramatically enhance performance in medical vision-language tasks.
A single distilled model can outperform larger heterogeneous teachers by effectively integrating their strengths without interference.
Bridging disparate model families, Any-OPD achieves a 4.5% increase in performance while reducing model size by 80%.
Overcome the "forgetting" problem in source-free domain adaptation by explicitly preserving confident predictions, leading to state-of-the-art fundus image diagnosis.
