2610.02916 Decoupled Entropic-Geometric Planning (DEGP): Verified Conditioning and a Measured Contact-Prediction Boundary in Latent World Models
Gradient-based latent space planning faces a fundamental trade-off: maintaining high-entropy representations for robust perception under domain shift often yields ill-conditioned manifolds that destabilize trajectory optimization. DEGP introduces a framework designed to isolate gradient interference between representation learning and control dynamics via strict architectural separation.