CountsDiff: A Diffusion Model on the Natural Numbers for Generation and Imputation of Count-Based Data

arXiv:2604.03779v1 Announce Type: cross Abstract: Diffusion models have excelled at generative tasks for both continuous and token-based domains, but their application to discrete ordinal data remains underdeveloped. We present CountsDiff, a diffusion framework designed to natively model distributions on the natural numbers. CountsDiff extends the Blackout diffusion framework by simplifying its formulation through a direct parameterization in terms of a survival probability schedule and an expli