Princeton's AIM cuts world model training data needs by up to 85x via action influence
shahdhruv_ · x · 2026-10-24
Princeton researchers introduce AIM (Action Influence Maximization), a CoRL 2026 method showing that expert demonstrations alone set a low ceiling on world-model controllability. By actively collecting exploration data targeting missing action consequences, adding just 500 episodes to 3k demonstrations matches a model trained on 300k expert episodes — an 85x data efficiency gain.
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