Sign inGet started
Paper · arXiv

LOCI: Spatial Linear Memory for Streaming World Models

When a camera revisits a previously observed region, a video world model should reproduce what was there before. This requires both remembering past observations and retrieving the right one for the current viewpoint. Key-value caches preserve visual detail but grow with video length; recurrent memory is compact but compresses history into a fixed-size state, so individual past observations are no longer directly accessible. We introduce LOCI, a hybrid spatial-memory architecture that keeps both representations. In half of the transformer blocks, main attention keeps a key-value cache of past observations; in the other half, it is restricted to the current chunk and complemented by a recu...

AuthorsJi Xia, Tingting Liao, Xuezhi Liang et al.
Primary categorycs.CV
Published30 September 2026
Last updated at source30 September 2026
cs.CV
Embed this entry
<iframe src="https://silytics.si/embed/item/c47b3220-429f-4eaa-a93a-ced42f60bc26" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Connected in the knowledge graph

Explore this entry in the graph

Models and datasets referencing this paper

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.