ARC-Bench: Closed-Loop Replanning Masks Broken Action Ranking in Frozen JEPA World Models

ARC‑Bench is a new benchmark that tests whether frozen JEPA‑style latent world models can correctly rank candidate actions by latent distance. The study finds that the assumption of latent rankability fails dramatically in both navigation and manipulation tasks, with the top‑scored actions often being suboptimal. Closed‑loop replanning masks this defect, but reducing replanning frequency reveals the underlying ranking failures.

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• rag
• diffusion
• robotics