Decision-Metric Alignment in Latent World Models for MPC Planning
simple-world-lab · hf · 2026-08-20
This study proposes action-conditioned objectives to enhance decision-metric alignment in latent world models. The method improves the latent geometry for Euclidean-cost model-predictive control (MPC), thereby elevating the decision quality of planning.
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