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Nanjing University
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A latent world model slashes navigation planning costs by 128x while boosting real-robot success rates from 43% to 83% in unseen environments.
Task knowledge can be efficiently reused across heterogeneous agents, slashing tracking errors by up to 99.79% while using significantly less data.