MALLM-GAN uses multi-agent LLMs to emulate GAN architecture for generating higher-quality synthetic tabular data from small samples than prior models, while preserving privacy.
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MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data
MALLM-GAN uses multi-agent LLMs to emulate GAN architecture for generating higher-quality synthetic tabular data from small samples than prior models, while preserving privacy.