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An event-aware evaluation protocol that separately measures post-trigger editing quality, pre-trigger preservation, and false-trigger robustness is introduced.
ContextFlow is introduced, a conditional flow-matching model that learns continuous action distributions for in-context imitation learning and adapts perceiver-style multimodal context compressors that distill visual, proprioceptive, and action sequences into compact, task-relevant latent representations.
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