AI RESEARCH
TRAFA: Anticipating User Actions to Reduce Errors in Procedural Tasks with Predictive Feedback
arXiv CS.AI
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ArXi:2605.24526v1 Announce Type: cross Interactive assistance systems typically provide feedback after an action has been completed, ing error recovery but not preventing the error itself. We present TRAFA, a real-time predictive feedback system for procedural tasks that intervenes before errors are committed. TRAFA operationalizes predictive feedback through a Track-Forecast-Act framework that tracks hand and object state, forecasts user motion conditioned on scene context, and triggers feedback when a predicted action is likely to violate task constraints.