AI RESEARCH
Tail Annealing for Heavy-Tailed Flow Matching
arXiv CS.LG
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ArXi:2605.20068v1 Announce Type: cross Standard generative models struggle with heavy-tailed data: Lipschitz architectures cannot produce power-law tails from Gaussian noise, and interpolating between heavy-tailed data and Gaussians is ill-posed. We propose a simple fix: apply the soft-log transform $\phi(x) = \mathrm{sign}(x) \cdot \log(1 + |x|)$ coordinate-wise to data before