In-Context Forcing: Uncovering Context Effects in Autoregressive Video Diffusion
In-Context Forcing is introduced, a progressive autoregressive paradigm that utilizes contexts with decreasing noise levels that enables cross-frame parallel denoising, achieving substantial inference acceleration without sacrificing performance.