SimDist pretrains world models in simulation and adapts them to real-world robots by updating only the latent dynamics model, enabling rapid improvement on contact-rich tasks where prior methods fail.
Adapting world models with latent-state dynamics residuals
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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AdaJEPA performs closed-loop test-time adaptation of latent world models during MPC by executing an action chunk, observing the transition, and taking one gradient step on the model before replanning, yielding higher goal-reaching success.
citing papers explorer
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Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation
SimDist pretrains world models in simulation and adapts them to real-world robots by updating only the latent dynamics model, enabling rapid improvement on contact-rich tasks where prior methods fail.
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AdaJEPA: An Adaptive Latent World Model
AdaJEPA performs closed-loop test-time adaptation of latent world models during MPC by executing an action chunk, observing the transition, and taking one gradient step on the model before replanning, yielding higher goal-reaching success.