Generative AI for Synthetic Data Generation: Methods, Challenges and the Future

arXiv:2403.04190v1 Announce Type: new
Abstract: The recent surge in research focused on generating synthetic data from large language models (LLMs), especially for scenarios with limited data availability, marks a notable shift in Generative Artificial Intelligence (AI). Their ability to perform comparably to real-world data positions this approach as a compelling solution to low-resource challenges. This paper delves into advanced technologies that leverage these gigantic LLMs for the generation of task-specific training data. We outline methodologies, evaluation techniques, and practical applications, …

abstract artificial artificial intelligence arxiv availability challenges cs.ai cs.cl cs.lg data future generative generative artificial intelligence intelligence language language models large language large language models llms marks research shift synthetic synthetic data type world