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Joshua Cheung

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#machine learning Preprint Oct 2026

One-Step Prediction Fidelity Is a Poor Proxy for Planning Performance in JEPA World Models

Latent world models are routinely selected, checkpointed and ablated on one-step prediction loss, on the assumption that a model which predicts the next latent better is a better model. In model-based RL this assumption is known to be unreliable; we ask whether it also fails for latent world models, where the training...

Joshua Cheung, Zhang He · 0 citations

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