Papers with LLM-based tabular synthesis

1 papers
Explain the Synth: Interpretable Evaluation of LLM Data Synthesis (2026.acl-long)

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Challenge: Large language models (LLMs) are increasingly used to generate tabular data.
Approach: They propose a framework that uses a rule-based model as a shared explanatory language to examine the explanation of real versus synthetic data.
Outcome: The proposed framework compares the explanatory structure induced by real versus synthetic data.

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