3 papers
cs.CL2025
AutoPrep: Natural Language Question-Aware Data Preparation with a Multi-Agent Framework
Meihao Fan, Ju Fan, Nan Tang +3
Answering natural language (NL) questions about tables, known as Tabular Question Answering (TQA), is crucial because it allows users to quickly and efficiently extract meaningful…
cs.DB2025
A Unified Model for Cardinality Estimation by Learning from Data and Queries via Sum-Product Networks
Jiawei Liu, Ju Fan, Tongyu Liu +5
Cardinality estimation is a fundamental component in database systems, crucial for generating efficient execution plans. Despite advancements in learning-based cardinality estimati…
cs.DB2025
Automatic Database Configuration Debugging using Retrieval-Augmented Language Models
Sibei Chen, Ju Fan, Bin Wu +8
Database management system (DBMS) configuration debugging, e.g., diagnosing poorly configured DBMS knobs and generating troubleshooting recommendations, is crucial in optimizing DB…