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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
7346
Venue
SIGMOD
Year
2025
Pagerank
5.093636e-05
Overall Rank
10,785 | 26.01%
DOI
10.1145/3725396

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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}
}

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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
112 HoloClean: Holistic Data Repairs with Probabilistic Inference 2017 VLDB 0.00032801121
142 LOF: Identifying Density-Based Local Outliers 2000 SIGMOD 0.0002962566
317 Annotating and Searching Web Tables Using Entities, Types and Relationships 2010 VLDB 0.00021402049
420 Can Foundation Models Wrangle Your Data? 2023 VLDB 0.00018789852
661 Don’t be SCAREd: Use SCalable Automatic REpairing with Maximal Likelihood and Bounded Changes 2013 SIGMOD 0.0001519162
693 Algorithms for Mining Distance-Based Outliers in Large Datasets 1998 VLDB 0.00014918477
1,476 Baran: Effective Error Correction via a Unified Context Representation and Transfer Learning 2020 VLDB 0.00010659277
1,923 Annotating Columns with Pre-trained Language Models 2022 SIGMOD 9.4789109e-05
2,099 Table-GPT: Table Fine-tuned GPT for Diverse Table Tasks 2024 SIGMOD 9.1682353e-05
2,123 Discovery of Genuine Functional Dependencies from Relational Data with Missing Values 2018 VLDB 9.1372798e-05
2,297 Raha: A Configuration-Free Error Detection System 2019 SIGMOD 8.7897221e-05
2,398 BigDansing: A System for Big Data Cleansing 2015 SIGMOD 8.631172e-05
3,147 Auto-Detect: Data-Driven Error Detection in Tables 2018 SIGMOD 7.7077175e-05
4,515 ArcheType: A Novel Framework for Open-Source Column Type Annotation using Large Language Models 2024 VLDB 6.6492389e-05
5,620 DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python 2021 SIGMOD 6.1482864e-05
6,436 Synthesizing Type-Detection Logic for Rich Semantic Data Types using Open-source Code 2018 SIGMOD 5.8793793e-05
6,801 Unit Testing Data with Deequ 2019 SIGMOD 5.7690726e-05
7,690 Auto-Validate: Unsupervised Data Validation Using Data-Domain Patterns Inferred from Data Lakes 2021 SIGMOD 5.5669307e-05
8,458 RECA: Related Tables Enhanced Column Semantic Type Annotation Framework 2023 VLDB 5.4217059e-05
8,860 Watchog: A Light-weight Contrastive Learning based Framework for Column Annotation 2023 SIGMOD 5.3564029e-05
9,629 Auto-BI: Automatically Build BI-Models Leveraging Local Join Prediction and Global Schema Graph 2023 VLDB 5.2434488e-05
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