RESEARCH PAPER
Persistent Robot World Models: Stabilizing Multi-Step Rollouts via Reinforcement Learning
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Category review. PersistWorld post-trains Ctrl-World to improve action-conditioned multi-view video rollouts using ground-truth fidelity rewards. Actions come from recorded trajectories or separate policies; the model remains an observation simulator. Its simulator-specific post-training does not make it a canonical component. Reading evidence
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