Toward an Auto-Synthesizer: Stress-Aware Selection and Recommendation of Deep Tabular Generative Models

Deep generative models for tabular data — GANs, variational autoencoders, diffusion models, and LLM-based generators — exhibit highly non-uniform behavior across datasets: the best-performing family depends on distributional stressors such as long-tailed marginals, high-cardinality categoricals, Zip