10 citations · 26 across the 7 of their papers we have counts for
7 papers
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…
TimeCMA: Towards LLM-Empowered Multivariate Time Series Forecasting via Cross-Modality Alignment
Chenxi Liu, Qianxiong Xu, Hao Miao +5
Multivariate time series forecasting (MTSF) aims to learn temporal dynamics among variables to forecast future time series. Existing statistical and deep learning-based methods suf…
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…
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…
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…
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…
Reboost Large Language Model-based Text-to-SQL, Text-to-Python, and Text-to-Function -- with Real Applications in Traffic Domain
Guanghu Sui, Zhishuai Li, Ziyue Li +4
The previous state-of-the-art (SOTA) method achieved a remarkable execution accuracy on the Spider dataset, which is one of the largest and most diverse datasets in the Text-to-SQL…