Introduces a training-free inference-time method for aesthetic refinement in unconditional diffusion models using degradation concept vectors, bottleneck patching, and classifier-free guidance to steer away from degraded outputs.
Layeredit: Disentangled multi-object editing via conflict- aware multi-layer learning.arXiv preprint arXiv:2511.08251,
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Guidance for Low-Level Perceptual Editing in Unconditional Diffusion Models
Introduces a training-free inference-time method for aesthetic refinement in unconditional diffusion models using degradation concept vectors, bottleneck patching, and classifier-free guidance to steer away from degraded outputs.