QDA-SQL: Questions Enhanced Dialogue Augmentation for Multi-Turn Text-to-SQL
Published in CAAI International Conference on Artificial Intelligence (CICAI), 2026
Fine-tuning LLMs for Text-to-SQL tasks is effective, but they often struggle with multi-turn queries due to ambiguity. QDA-SQL, a data augmentation method that generates diverse multi-turn Q&A pairs using LLMs. Fine-tuning with QDA-SQL improves SQL statement accuracy and enhances the models' ability to manage challenging, unanswerable questions. The generation script and test set are released at Github.