7 citations · 14 across the 6 of their papers we have counts for
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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.DB2023★ 7 cited
Demonstration of InsightPilot: An LLM-Empowered Automated Data Exploration System
Pingchuan Ma, Rui Ding, Shuai Wang +2
Exploring data is crucial in data analysis, as it helps users understand and interpret the data more effectively. However, performing effective data exploration requires in-depth k…
cs.DB2022
AnaMeta: A Table Understanding Dataset of Field Metadata Knowledge Shared by Multi-dimensional Data Analysis Tasks
Xinyi He, Mengyu Zhou, Mingjie Zhou +7
Tabular data analysis is performed every day across various domains. It requires an accurate understanding of field semantics to correctly operate on table fields and find common p…