SelfLift: Accelerating Few-Step Diffusion via Self-Recovering Resolution Transition
SelfLift is introduced, a self-recovering progressive-resolution framework that derives both transition-repair signals and trajectory-aligned supervision from the generative model itself and reduces end-to-end latency across FLUX, establishing a stronger speed-quality frontier for few-step diffusion.