Interactive world models generate visual content conditioned on user actions, yet maintaining spatial consistency over long-horizon exploration in real time remains challenging. Existing approaches re
L3G-World uses a compact latent 3D Gaussian memory and alternating autoregressive updates with a video diffusion transformer to generate spatially consistent interactive worlds in real time.
Interactive world models generate visual content conditioned on user actions, yet maintaining spatial consistency over long-horizon exploration in real time remains challenging. Existing approaches rely on either temporal context or explicit 3D memory, both of which scale poorly because memory grows with the length of the generated stream. Moreover, explicit 3D memories condition latent video generators by re-encoding RGB renderings, which precludes real-time generation. In this paper, we introduce a Latent 3D Gaussian Memory (L3G) that combines the efficiency of feed-forward reconstruction with a compact, rapidly renderable scene representation. Building on this memory, we propose…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
L3G-World: Real-Time Infinite World Generation with Latent 3D Gaussian Memory was first seen on Hugging Face · Daily papers on Oct 30, 2026. Since then it has appeared in 14 checks on 2 different days. Its best position was #5 of 30, reached on Oct 30, 17:28 UTC. It is #7 right now, holding steady at #7 over the last 6 checks.
Position on Hugging Face · Daily papers at every check (lower is better).
Best rank per day (UTC).
▲ as reported by Hugging Face.
Yes. As of Oct 31, 09:28 UTC it is #7, holding steady at #7 over the last 6 checks.
#5 on Hugging Face · Daily papers, on Oct 30, 17:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Oct 30, 2026 and has been on the list on 2 days (14 checks) since.