papers

Publications (6)

cs.CL2023

Table-GPT: Table-tuned GPT for Diverse Table Tasks

Peng Li, Yeye He, Dror Yashar +6

Language models, such as GPT-3.5 and ChatGPT, demonstrate remarkable abilities to follow diverse human instructions and perform a wide range of tasks. However, when probing languag…

cs.DB2023

Auto-Validate by-History: Auto-Program Data Quality Constraints to Validate Recurring Data Pipelines

Dezhan Tu, Yeye He, Weiwei Cui +5

Data pipelines are widely employed in modern enterprises to power a variety of Machine-Learning (ML) and Business-Intelligence (BI) applications. Crucially, these pipelines are \em…

cs.LG2020

A Federated Learning Framework for Healthcare IoT devices

Binhang Yuan, Song Ge, Wenhui Xing

The Internet of Things (IoT) revolution has shown potential to give rise to many medical applications with access to large volumes of healthcare data collected by IoT devices. Howe…

cs.DB2026

Auto-Relate: A Unified Approach to Discovering Reliable Functional Relationships Leveraging Statistical Tests

Ziyan Han, Yeye He, Shuyuan Kang +8

Tables in spreadsheets, computational notebooks, and databases often contain rich inter-column relationships. Yet these relationships are typically implicit and are often lost when…

cs.DB2025

Auto-Test: Learning Semantic-Domain Constraints for Unsupervised Error Detection in Tables

Qixu Chen, Yeye He, Raymond Chi-Wing Wong +5

Data cleaning is a long-standing challenge in data management. While powerful logic and statistical algorithms have been developed to detect and repair data errors in tables, exist…

cs.DB2024

Auto-Formula: Recommend Formulas in Spreadsheets using Contrastive Learning for Table Representations

Sibei Chen, Yeye He, Weiwei Cui +5

Spreadsheets are widely recognized as the most popular end-user programming tools, which blend the power of formula-based computation, with an intuitive table-based interface. Toda…