11 citations · 30 across the 8 of their papers we have counts for
8 papers
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…
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…
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…
Cost-Effective In-Context Learning for Entity Resolution: A Design Space Exploration
Meihao Fan, Xiaoyue Han, Ju Fan +4
Entity resolution (ER) is an important data integration task with a wide spectrum of applications. The state-of-the-art solutions on ER rely on pre-trained language models (PLMs),…
SEED: Domain-Specific Data Curation With Large Language Models
Zui Chen, Lei Cao, Sam Madden +7
Data curation tasks that prepare data for analytics are critical for turning data into actionable insights. However, due to the diverse requirements of applications in different do…
VerifAI: Verified Generative AI
Nan Tang, Chenyu Yang, Ju Fan +3
Generative AI has made significant strides, yet concerns about the accuracy and reliability of its outputs continue to grow. Such inaccuracies can have serious consequences such as…
Interleaving Pre-Trained Language Models and Large Language Models for Zero-Shot NL2SQL Generation
Zihui Gu, Ju Fan, Nan Tang +7
Zero-shot NL2SQL is crucial in achieving natural language to SQL that is adaptive to new environments (e.g., new databases, new linguistic phenomena or SQL structures) with zero an…
ChatPipe: Orchestrating Data Preparation Program by Optimizing Human-ChatGPT Interactions
Sibei Chen, Hanbing Liu, Weiting Jin +5
Orchestrating a high-quality data preparation program is essential for successful machine learning (ML), but it is known to be time and effort consuming. Despite the impressive cap…