SOURCE-LINKED INTELLIGENCE
Spatially Aware World Action Model via Geometric Latent Diffusion
World Action Models (WAMs) leverage the capabilities of large-scale pretrained video diffusion models to jointly predict future observations and actions, inheriting rich visual and physical priors from internet-scale video. This has made them a promising paradigm for robot policy learning, yet the prevailing models operate exclusively on RGB observations and do not leverage 3D information. To bridge this gap, we introduce a Spatially Aware World Action Model (SA-WAM), which repurposes a pretrained video model for joint action, RGB, and depth prediction, enabling 3D-aware world modeling and act
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-02T12:42:37.000Z
First collected: 2026-09-21T05:32:15.665Z. This is not the publication date.