Rewind-IL adds a zero-shot failure detector based on action-chunk discrepancy plus a checkpoint-based state respawn mechanism to make imitation-learned robot policies more reliable during long tasks.
DOSE3: diffusion-based unified out-of-distribution detec- tion on $\mathbb{SE}(3)$ trajectories
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Rewind-IL: Online Failure Detection and State Respawning for Imitation Learning
Rewind-IL adds a zero-shot failure detector based on action-chunk discrepancy plus a checkpoint-based state respawn mechanism to make imitation-learned robot policies more reliable during long tasks.