CompDiff enables fair and zero shot medical image generation across demographic intersections through compositional diffusion.

arXiv:2603.16551v4 Announce Type: replace-cross Abstract: Medical image generators trained on imbalanced data can fail at demographic intersections absent from training. We introduce CompDiff, which encodes age, sex and race separately and composes supervised