Evaluation of LLM based Text-to-SQL models
The episode explores the use of large language models (LLMs) for the Text-to-SQL task, focusing on prompt engineering. It compares different strategies, proposes a new integrated solution called DAIL-SQL, explores the potential of open-source LLMs, and emphasizes token efficiency. The study provides insights into question representation, in-context learning, and supervised fine-tuning for LLM-based Text-to-SQL solutions, ultimately achieving a new high accuracy on the leaderboard. The work contributes to a deeper understanding of Text-to-SQL with LLMs and inspires further research in the field.