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TabSODA: Tabular Diffusion based Imputation with Skip Pattern Detection and Ordinal Awareness
arXiv:2606.05361v1 Announce Type: cross Abstract: Missing data imputation in large-scale surveys faces two challenges that are not well handled by current tabular diffusion methods. First, \emph{structural skips}, cells made inapplicable by questionnaire design, should not be imputed but are often conflated with item nonresponse. Second, \emph{ordinal} responses encode ordered categories, yet most pipelines treat them as nominal levels through one-hot or analog-bit encodings.