Concordia aligns synthetic table generation with federated validation utility via client-side utility scorers and group-relative policy optimization to improve LLM adaptation on non-IID tabular tasks.
Challenges and opportunities of generative models on tabular data.Applied Soft Computing, page 112223, 2024a
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LLM-TabLogic extracts inter-column logical constraints using LLMs and conditions a score-based latent diffusion model on them to generate synthetic tabular data that preserves those relationships.
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Concordia: Self-Improving Synthetic Tables for Federated LLMs
Concordia aligns synthetic table generation with federated validation utility via client-side utility scorers and group-relative policy optimization to improve LLM adaptation on non-IID tabular tasks.
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LLM-TabLogic: Preserving Inter-Column Logical Relationships in Synthetic Tabular Data via Prompt-Guided Latent Diffusion
LLM-TabLogic extracts inter-column logical constraints using LLMs and conditions a score-based latent diffusion model on them to generate synthetic tabular data that preserves those relationships.