Are LLMs Naturally Good at Synthetic Tabular Data Generation?

arXiv:2406.14541v1 Announce Type: new
Abstract: Large language models (LLMs) have demonstrated their prowess in generating synthetic text and images; however, their potential for generating tabular data -- arguably the most common data type in business and scientific applications -- is largely underexplored. This paper demonstrates that LLMs, used as-is, or after traditional fine-tuning, are severely inadequate as synthetic table generators. Due to the autoregressive nature of LLMs, fine-tuning with random order permutation runs counter to the importance of modeling functional …

abstract applications arxiv business cs.lg data data generation good however images language language models large language large language models llms paper potential scientific synthetic tabular tabular data text type