Source-Lifted Flow Matching for Intervenable Multimodal Imitation
Source-Lifted Flow Matching (SL-FM) creates a new flow-matching policy for multimodal imitation learning. It allows users to directly choose between different valid continuations from the same state by treating source randomness as an actionable intervention variable. This enables precise control over behavior without conditioning the velocity field on which mode is selected.