3 papers
cs.DB2026
Towards Practical Benchmarking of Data Cleaning Techniques: On Generating Authentic Errors via Large Language Models
Xinyuan Liu, Jiahui Chen, Bocheng Hu +4
Data quality remains an important challenge in data-driven systems, as errors in tabular data can severely compromise downstream analytics and machine learning performance. Althoug…
cs.DB2025
Sync Without Guesswork: Incomplete Time Series Alignment
Ding Jia, Jingyu Zhu, Yu Sun +4
Multivariate time series alignment is critical for ensuring coherent analysis across variables, but missing values and timestamp inconsistencies make this task highly challenging.…
cs.DS2025
Learning Dependency Models for Subset Repair
Haoda Li, Jiahui Chen, Yu Sun +3
Inconsistent values are commonly encountered in real-world applications, which can negatively impact data analysis and decision-making. While existing research primarily focuses on…