SOURCE-LINKED INTELLIGENCE

Frequency-Conditioned Flow Matching for Vision-Language-Action Models

arXiv · AI, language, vision and robotics · article · Sep 9, 2026 · UTC

Robot actions are temporally correlated trajectories whose frequency components encode motion at different scales with highly non-uniform energy distributions. Yet Flow Matching--based vision-language-action (VLA) models typically generate actions in temporal coordinates, without explicitly modeling or systematically leveraging this frequency heterogeneity. We introduce \emph{FreqFM}, a frequency-conditioned Flow Matching framework for VLA models. It raises action frequency from an implicit trajectory property to an explicit conditioning dimension that spans the entire generation pipeline. Con

Read original source ↗ Open in workspace

recordType

paper

region

Global