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Discrete diffusion, with carefully designed transition matrices for commands and parameters, unlocks superior CAD generation compared to continuous diffusion baselines.
By explicitly disentangling shared and view-specific features across multi-view fundus images, MVGFDR achieves superior diabetic retinopathy grading compared to methods that directly fuse visual features.
