AI RESEARCH
Learning Unbiased Permutations via Flow Matching
arXiv CS.LG
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ArXi:2605.16755v1 Announce Type: new Learning permutations is fundamental to sorting, ranking, and matching, but existing differentiable methods based on entropy-regularized Sinkhorn produce a single softened solution and collapse under ambiguity. We present PermFlow, a conditional flow matching framework that operates directly on the affine subspace of matrices with unit row and column sums.