2 papers
cs.LG2026
SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation
Yexiong Lin, Jia Shi, Shanshan Ye +3
Flow matching has emerged as a powerful generative framework, with recent few-step methods achieving remarkable inference acceleration. However, we identify a critical yet overlook…
cs.CV2025
Beyond Optimal Transport: Model-Aligned Coupling for Flow Matching
Yexiong Lin, Yu Yao, Tongliang Liu
Flow Matching (FM) is an effective framework for training a model to learn a vector field that transports samples from a source distribution to a target distribution. To train the…