permutation distributions

New Diffusion Model Learns Permutation Distributions with Softer, More Tractable Trajectories

Researchers propose Soft-Rank Diffusion, a discrete diffusion framework that learns probability distributions over permutations more effectively than prior shuffle-based methods. By replacing abrupt shuffle corruption with a structured soft-rank forward process and introducing contextualized generalized Plackett-Luce denoisers, the method achieves consistent gains on sorting and combinatorial optimization tasks, especially for long sequences.