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MosaiChunk: Compositing Spatio-Temporal Memory for Autoregressive Video Generation

Paper recorded by Signals 4 on 2026-10-01 in cs.CV. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-01 on arXiv · recorded by Signals 4 on 2026-10-02

Category: cs.CV · 计算机视觉 · first seen 2026-10-02

Abstract

Long-horizon autoregressive video generation is limited by a finite context window. When an object or scene falls out of context, its fine-grained visual details may be lost and difficult to recover upon reappearance. To retain access to such visual details, we introduce MosaiChunk, a spatio-temporal memory mechanism that composes a mosaic of selected historical key-value (KV) entries across space

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#9 most recent of 380 cs.CV papers we have recorded · ↑ newer: 4Director: Controlling Video World Models with Rigid 3D Geometry · ↓ older: Omni-Embed-Mini: Binding Modalities Without Forgetting via Dense Disti
Cite this page: MosaiChunk: Compositing Spatio-Temporal Memory for Autoregressive Video Generation: the #9 most recent of 380 cs.CV papers we have recorded (as of 2026-10-01). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/mosaichunk-compositing-spatio-temporal-memory-for-autoregressive-video-generatio.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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