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BAG: Budget-Aware Gating for Diffusion Caching
Tong Zhao, Mingkun Lei, Yucheng Han +1
Diffusion caching is a lightweight strategy that accelerates Diffusion Transformers (DiTs) by reusing intermediate features across denoising steps, but existing paradigms face a fu…
Budget-Constrained Step-Level Diffusion Caching
Mingkun Lei, Tong Zhao, Liangyu Yuan +1
Step-level caching accelerates diffusion models by exploiting temporal redundancy across denoising steps. Existing methods make per-step cache decisions using threshold-based heuri…
Improving Diffusion Generalization with Weak-to-Strong Segmented Guidance
Liangyu Yuan, Yufei Huang, Mingkun Lei +5
Diffusion models generate synthetic images through an iterative refinement process. However, the misalignment between the simulation-free objective and the iterative process often…
Few-Step Diffusion Sampling Through Instance-Aware Discretizations
Liangyu Yuan, Ruoyu Wang, Tong Zhao +4
Diffusion and flow matching models generate high-fidelity data by simulating paths defined by Ordinary or Stochastic Differential Equations (ODEs/SDEs), starting from a tractable p…
DyWeight: Dynamic Gradient Weighting for Few-Step Diffusion Sampling
Tong Zhao, Mingkun Lei, Liangyu Yuan +5
Diffusion Models (DMs) have achieved state-of-the-art generative performance across multiple modalities, yet their sampling process remains prohibitively slow due to the need for h…
Fast3Dcache: Training-free 3D Geometry Synthesis Acceleration
Mengyu Yang, Yanming Yang, Chenyi Xu +5
Diffusion models have achieved impressive generative quality across modalities like 2D images, videos, and 3D shapes, but their inference remains computationally expensive due to t…
Distilling Parallel Gradients for Fast ODE Solvers of Diffusion Models
Beier Zhu, Ruoyu Wang, Tong Zhao +2
Diffusion models (DMs) have achieved state-of-the-art generative performance but suffer from high sampling latency due to their sequential denoising nature. Existing solver-based a…