Paper recorded by Signals 4 on 2026-10-13 in cs.LG. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-13 on arXiv · recorded by Signals 4 on 2026-10-14
Category: cs.LG · 机器学习 · first seen 2026-10-14
A central challenge in scaling flow models is maintaining stability in training and integration. In flow matching, this stability depends critically on how source samples are paired with data. Independent random pairing introduces substantial stochasticity, motivating minibatch optimal transport (OT) to construct online source-target couplings that reduce this randomness (Tong et al., 2024). Howev