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.CL2023★ 4 cited
Table Meets LLM: Can Large Language Models Understand Structured Table Data? A Benchmark and Empirical Study
Yuan Sui, Mengyu Zhou, Mingjie Zhou +2
Large language models (LLMs) are becoming attractive as few-shot reasoners to solve Natural Language (NL)-related tasks. However, the understanding of their capability to process s…
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…