Yu-Fang Jin

Hybrid-Basis Feature Forecasting for Diffusion Sampling Acceleration

This work proposes Hybrid-Basis Feature Forecasting (HybridFF), a training-free, plug-and-play framework for accelerating diffusion sampling that demonstrates a favorable speedup--quality trade-off over representative single-basis forecasters and caching baselines.