[Submitted on 31 Oct 2026]
Abstract:Autoregressive video diffusion models produce large KV caches during multi-round video generation. Keeping all these KV chunks would consume substantial memory, while rebuilding discarded caches would significantly delay video chunk generation. This paper presents ReelCache, a KV cache compression system for efficient multi-round, long video generation. ReelCache combines an intra-chunk compressor with an inter-chunk cache manager. The compressor applies low-rank decomposition across channels and video coding to the resulting coefficients, predicting the decomposition rank per transformer layer online to meet retained-energy targets. The cache manager shares basis directions across consecutive chunks and organizes chunk states in a tree, allowing generation branches to share historical state while supporting restoration for resume, rewind, and fork. Experiments across five video generation models show that ReelCache reduces KV storage by 14.46-21.13x relative to baselines and accelerates next-chunk generation by 1.25-3.36x, with less than 1% drop in six representative VBench metrics. GitHub: this https URL
Submission history
From: Tianyu Wang [view email]
[v1] Sat, 31 Oct 2026 02:36:10 UTC (5,137 KB)
