Author

Chen-Qian Yan

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Preprint Sep 2026

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.

Ting-Yan Wen, Chen-Qian Yan, Xu-Rui Peng et al. · 0 citations

#artificial intelligence Preprint Aug 2026

Accelerating Unified Multimodal Models with Core-Expansion Routing and Unified Computation Scheduling

CE-Router is proposed, which uses a task-shared core scorer and progress-conditioned generation expansions, optimized through generation decomposition and cross-task core alignment, and retains 98.03% of dense understanding performance with a 1.93-to-end inference speedup.

Wengyi Zhan, Chen-Qian Yan, Songwei Liu et al. · 0 citations