activity
20232025
most citedReboost Large Language Model-based Text-to-SQL, Text-to-Python, and Text-to-Function -- with Real Applications in Traffic Domain

1 citations · 1 across the 5 of their papers we have counts for

collaborators

13 papers

cs.CR2025

SFIBA: Spatial-based Full-target Invisible Backdoor Attacks

Yangxu Yin, Honglong Chen, Yudong Gao +3

Multi-target backdoor attacks pose significant security threats to deep neural networks, as they can preset multiple target classes through a single backdoor injection. This allows…

cs.LG2024

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…

cs.LG2024

TraffiDent: A Dataset for Understanding the Interplay Between Traffic Dynamics and Incidents

Xiaochuan Gou, Ziyue Li, Tian Lan +6

Long-separated research has been conducted on two highly correlated tracks: traffic and incidents. Traffic track witnesses complicating deep learning models, e.g., to push the pred…

cs.DB2024

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…

stat.ME2024

MultiFun-DAG: Multivariate Functional Directed Acyclic Graph

Tian Lan, Ziyue Li, Junpeng Lin +6

Directed Acyclic Graphical (DAG) models efficiently formulate causal relationships in complex systems. Traditional DAGs assume nodes to be scalar variables, characterizing complex…

cs.CL2024

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…