On Deep Learning Approaches for Single-Turn Text-to-SQL Parsing: Concepts, Methods, and Future Directions

This literature review delves into deep learning techniques for text-to-SQL parsing, exploring datasets, evaluation metrics, models, and methodologies. The study aims to provide a comprehensive overview of the field, analyzing strengths, weaknesses, accuracy, practical applications, and scalability of various approaches. By examining the current landscape and future directions, this work serves as a valuable resource for researchers, industry professionals, and enthusiasts interested in Natural Language Processing and neural semantic parsing.