AI RESEARCH
MixFlow: Mixed Source Distributions Improve Rectified Flows
arXiv CS.LG
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ArXi:2604.09181v1 Announce Type: cross Diffusion models and their variations, such as rectified flows, generate diverse and high-quality images, but they are still hindered by slow iterative sampling caused by the highly curved generative paths they learn. An important cause of high curvature, as shown by previous work, is independence between the source distribution (standard Gaussian) and the data distribution. In this work, we tackle this limitation by two complementary contributions. First, we attempt to break away from the standard Gaussian assumption by.