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Directional Pullback Regularization for Long-Horizon Rollout of Latent World Models in Autonomous Driving
Learned world models for autonomous driving operate in unconstrained latent spaces, yet the physical systems they represent are governed by strict non-holonomic constraints: ground vehicles cannot realize instantaneous pure lateral motion. We study long-horizon latent rollout modeling for autonomous
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