AI RESEARCH
Dependence Fidelity and Downstream Inference Stability in Generative Models
arXiv CS.LG
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ArXi:2603.17041v1 Announce Type: cross Recent advances in generative AI have led to increasingly realistic synthetic data, yet evaluation criteria remain focused on marginal distribution matching. While these diagnostics assess local realism, they provide limited insight into whether a generative model preserves the multivariate dependence structures governing downstream inference. We