Shunqi Mao

ReAL: Accelerating Flow Matching through Segment Advancement with Shared Lookahead

This work introduces ReAL, a training-free sampler that selects how far to advance using one shared lookahead, and shows that the discrepancy between uncorrected and lookahead-corrected endpoint proposals can be computed directly from the observed velocity mismatch and the candidate span beyond the lookahead.