Papers with LLM-based generation framework

1 papers
SAGE: Sparse Adaptive Guidance for Dependency-Aware Tabular Data Generation (2026.acl-long)

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Challenge: Recent approaches to generate tabular data are limited by their static dependences and lack of fidelity.
Approach: They propose a novel LLM-based generation framework that enforces sparse and dynamic dependency guidance.
Outcome: The proposed framework boosts F1 scores by 10% and reduces policy violations by one point.

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