ATLAS: Aligned Transport of Latent Structure for Reliable World Model Planning
Overview
ATLAS is a new method that preserves relational geometry in latent representations to improve world model planning. It uses Wasserstein embedding matching to calibrate global latent distributions.
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- 2026-10-01T03:06:44.154Z · evidence updated · source revision 2. Evidence extraction was updated; current source attributions are shown above.
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- arXiv Robotics — research abstractsATLAS: Aligned Transport of Latent Structure for Reliable World Model Planning
This research introduces ATLAS, a method that preserves relational geometry in latent representations for reliable world model planning. By calibrating the global latent distribution through Wasserstein embedding matching, ATLAS improves performance on tasks like PushT, TwoRoom, and OGBench-Cube, particularly in high-novelty scenarios. The method enhances novelty-related structure in the planning latent and reduces multi-step prediction error.
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