JEDI minimizes Jensen-Shannon divergence between subject attention maps during diffusion sampling, reducing attribute mixing in generated images.
Scaling rectified flow transformers for high-resolution image synthesis
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JEDI: The Force of Jensen-Shannon Divergence in Disentangling Diffusion Models
JEDI minimizes Jensen-Shannon divergence between subject attention maps during diffusion sampling, reducing attribute mixing in generated images.