SOURCE-LINKED INTELLIGENCE

DensityKV: Density-Guided KV Cache Compression for Long Video Generation

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

Autoregressive video diffusion models enable streaming generation through sliding-window attention, but each generated block is conditioned on previously generated content, causing appearance and motion errors to propagate recursively over time. Historical key-value (KV) memory preserves earlier subject and scene states and helps maintain long-horizon consistency. However, retaining every generated state creates a historical archive that grows continuously with the rollout, while recurrent states repeatedly add redundant coverage. To address this problem, we propose DensityKV, a training-free

Read original source ↗ Open in workspace

recordType

paper

region

Global