From the 1 of 4 linked papers with an AI index.
2 citations · 2 across the 1 of their papers we have counts for
4 papers
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'…
Breaking the Context Bottleneck on Long Time Series Forecasting
Chao Ma, Yikai Hou, Xiang Li +4
Long-term time-series forecasting is essential for planning and decision-making in economics, energy, and transportation, where long foresight is required. To obtain such long fore…
Long Input Sequence Network for Long Time Series Forecasting
Chao Ma, Yikai Hou, Xiang Li +2
Short fixed-length inputs are the main bottleneck of deep learning methods in long time-series forecasting tasks. Prolonging input length causes overfitting, rapidly deteriorating…
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…