AINeutralarXiv – CS AI · 8h ago6/10
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World Action Verifier: Self-Improving World Models via Forward-Inverse Asymmetry
Researchers introduce World Action Verifier (WAV), a framework that enables world models to self-correct prediction errors by decomposing action-conditioned predictions into verifiable components: state plausibility and action reachability. The approach achieves 2x higher sample efficiency and 22% policy performance improvements across robotic control tasks by leveraging asymmetries in data availability and feature dimensionality.