INSIGHT: INference-time Sequence Introspection for Generating Help Triggers in Vision-Language-Action Models 事件

INSIGHT: INference-time Sequence Introspection for Generating Help Triggers in Vision-Language-Action Models arXiv:2510.01389v2 Announce Type: replace-cross Abstract: Recent Vision-Language-Action (VLA) models show strong generalization capabilities, yet they lack introspective mechanisms for anticipating failures and requesting help from a human supervisor. We present \textbf{INSIGHT}, a learning framework for leveraging token-level uncertainty signals to predict when a VLA should request help