9 citations · 9 across the 1 of their papers we have counts for
7 papers
SQLBench: A Comprehensive Evaluation for Text-to-SQL Capabilities of Large Language Models
Bin Zhang, Yuxiao Ye, Guoqing Du +8
Large Language Models (LLMs) have emerged as a powerful tool in advancing the Text-to-SQL task, significantly outperforming traditional methods.Nevertheless, as a nascent research…
KITS: Inductive Spatio-Temporal Kriging with Increment Training Strategy
Qianxiong Xu, Cheng Long, Ziyue Li +3
Sensors are commonly deployed to perceive the environment. However, due to the high cost, sensors are usually sparsely deployed. Kriging is the tailored task to infer the unobserve…
Transformer-based Drum-level Prediction in a Boiler Plant with Delayed Relations among Multivariates
Gang Su, Sun Yang, Zhishuai Li
The steam drum water level is a critical parameter that directly impacts the safety and efficiency of power plant operations. However, predicting the drum water level in boilers is…
Spatial-Temporal Large Language Model for Traffic Prediction
Chenxi Liu, Sun Yang, Qianxiong Xu +4
Traffic prediction, an essential component for intelligent transportation systems, endeavours to use historical data to foresee future traffic features at specific locations. Altho…
PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistency
Zhishuai Li, Xiang Wang, Jingjing Zhao +8
Recent advancements in Text-to-SQL (Text2SQL) emphasize stimulating the large language models (LLM) on in-context learning, achieving significant results. Nevertheless, they face c…
SQL-to-Schema Enhances Schema Linking in Text-to-SQL
Sun Yang, Qiong Su, Zhishuai Li +4
In sophisticated existing Text-to-SQL methods exhibit errors in various proportions, including schema-linking errors (incorrect columns, tables, or extra columns), join errors, nes…