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WLA$^3$ (World Latent Action Modeling for Semantics, Dynamics, and Kinematics), a unified generalist policy model framework built around representations learned by a World Latent Action Model (WLAM), is introduced.
Neural image compression can finally rival classic formats in raw throughput, achieving 2000 FPS decoding and practical 20 FPS encoding while matching JPEG's rate-distortion performance.
Simply adding multi-view videos to latent action models doesn't guarantee 3D awareness; LAWM-3D reveals the critical design choices needed for success.
Hierarchical post-training can significantly enhance robotic manipulation by enabling agents to better navigate complex tasks through effective subgoal decomposition.
