5 papers · 1 filter
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…
Parallel Diffusion Solver via Residual Dirichlet Policy Optimization
Ruoyu Wang, Ziyu Li, Beier Zhu +5
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…
Adaptive Stochastic Coefficients for Accelerating Diffusion Sampling
Ruoyu Wang, Beier Zhu, Junzhi Li +2
Diffusion-based generative processes, formulated as differential equation solving, frequently balance computational speed with sample quality. Our theoretical investigation of ODE-…
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…