data augmentation 1large language models 1multi-turn dialogue 1question answering 1sql generation 1text-to-sql 1
From the 1 of 2 linked papers with an AI index.
2 citations · 2 across the 1 of their papers we have counts for
2 papers
cs.AI2026★ 2 cited
QDA-SQL: Questions Enhanced Dialogue Augmentation for Multi-Turn Text-to-SQL
Yinggang Sun, Ziming Guo, Haining Yu +5
The paper introduces QDA-SQL, a data augmentation technique that uses large language models to generate and validate multi‑turn question‑answer pairs, improving fine‑tuned models'…
cs.CL2025
Evaluating and Enhancing LLMs for Multi-turn Text-to-SQL with Multiple Question Types
Ziming Guo, Chao Ma, Yinggang Sun +3
Recent advancements in large language models (LLMs) have significantly advanced text-to-SQL systems. However, most LLM-based methods often narrowly focus on SQL generation, neglect…