StructSynth: Dependency Graphs as Generation Plans for Low-Data Tabular Synthesis with Language Models

Tabular data derives its value from inter-feature dependencies, yet preserving them during synthesis is fragile when samples are scarce. Existing approaches either learn dependencies implicitly through distribution fitting, rely on statistical graph learning that becomes unstable with few samples, o