Copper-Policy Replaces Pixel Prediction With Compact Latent Representations for Robot Control
The Copper-Policy model jointly learns compact latent world representations and action policies, bypassing the heavy computational cost of pixel-level video prediction. First author Zexin Feng from The University of Hong Kong explains how this asymmetric architecture achieves robust control without extensive embodied pre-training.
