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

Summary: Auto-Test learns Semantic-Domain Constraints from corpora for unsupervised error detection, removing per-table expert specification. Optimization-based distillation yields a provably reliable core that detects errors and augments cleaning; 2400-column benchmark and code released. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h776fc787a2a4684d
Venue
SIGMOD
Year
2025
Pagerank
5.2056825e-05
Overall Rank
9,229 | 37.95%
DOI
10.1145/3725396

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{chen_sigmod25,
        title = {{Auto-Test: Learning Semantic-Domain Constraints for Unsupervised Error Detection in Tables}},
        author = {Chen, Qixu and He, Yeye and Wong, Raymond Chi-Wing and Cui, Weiwei and Ge, Song and Zhang, Haidong and Zhang, Dongmei and Chaudhuri, Surajit},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3725396},
        url = {https://dl.acm.org/doi/10.1145/3725396},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

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Outgoing Citations (Sorted by Pagerank)

Showing 21 of 21 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
104 HoloClean: Holistic Data Repairs with Probabilistic Inference 2017 VLDB 0.00033690989
142 LOF: Identifying Density-Based Local Outliers 2000 SIGMOD 0.00029202746
316 Annotating and Searching Web Tables Using Entities, Types and Relationships 2010 VLDB 0.00021221602
329 Can Foundation Models Wrangle Your Data? 2023 VLDB 0.00020858443
652 Don’t be SCAREd: Use SCalable Automatic REpairing with Maximal Likelihood and Bounded Changes 2013 SIGMOD 0.00015121325
695 Algorithms for Mining Distance-Based Outliers in Large Datasets 1998 VLDB 0.00014702685
1,342 Baran: Effective Error Correction via a Unified Context Representation and Transfer Learning 2020 VLDB 0.00010968223
1,780 Annotating Columns with Pre-trained Language Models 2022 SIGMOD 9.6560923e-05
1,805 Raha: A Configuration-Free Error Detection System 2019 SIGMOD 9.59842e-05
1,978 Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks 2024 SIGMOD 9.2730152e-05
2,125 Discovery of Genuine Functional Dependencies from Relational Data with Missing Values 2018 VLDB 9.0033119e-05
2,423 BigDansing: A System for Big Data Cleansing 2015 SIGMOD 8.4877894e-05
2,960 Auto-Detect: Data-Driven Error Detection in Tables 2018 SIGMOD 7.8075103e-05
4,589 ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models 2024 VLDB 6.5144711e-05
5,640 DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python 2021 SIGMOD 6.0548401e-05
6,488 Synthesizing Type-Detection Logic for Rich Semantic Data Types using Open-source Code 2018 SIGMOD 5.76799e-05
6,898 Unit Testing Data with Deequ 2019 SIGMOD 5.6530554e-05
7,738 Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes 2021 SIGMOD 5.4623434e-05
8,594 RECA: Related Tables Enhanced Column Semantic Type Annotation Framework 2023 VLDB 5.3063445e-05
8,979 Auto-BI: Automatically Build BI-Models Leveraging Local Join Prediction and Global Schema Graph 2023 VLDB 5.2443558e-05
8,988 Watchog: A Light-weight Contrastive Learning based Framework for Column Annotation 2023 SIGMOD 5.2425067e-05
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