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The Generated World Remembers Places, Not Frames
A latent 3D Gaussian memory grew with explored scene extent and rendered into a video model at a reported 9 frames per second.
Summary
A latent 3D Gaussian memory grew with explored scene extent and rendered into a video model at a reported 9 frames per second.
Long interactive video streams make temporal memory grow without bound. L3G-World instead stores a compact 3D Gaussian scene memory, adding geometry when a new region appears and refining what it already knows. Each Gaussian carries a latent feature that can feed the diffusion transformer without re-encoding an RGB render. Against the paper's most efficient prior 3D-memory baselines for each metric, the method used up to 38.6 times fewer primitives, updated memory 3.2 times faster and rendered it 359 times faster, enabling reported generation at 9 frames per second. These are benchmarked generation results, not proof of physical simulation accuracy.
Why it matters
A latent 3D Gaussian memory grew with explored scene extent and rendered into a video model at a reported 9 frames per second.
Limits and context
- These are benchmarked generation results, not proof of physical simulation accuracy.
Key claims
A latent 3D Gaussian memory grew with explored scene extent and rendered into a video model at a reported 9 frames per second.
Qualification: These are benchmarked generation results, not proof of physical simulation accuracy.
Evidence: source-2026-11-01-008
Sources
- arXiv preprint 2610.40614, original v1arXiv · primary research
Corrections
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