8 citations · 8 across the 5 of their papers we have counts for
5 papers
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…
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…
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…
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…
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…