TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection

Summary: TSB-AutoAD: taxonomy plus benchmark (20 methods, 70 variants) for automated time-series anomaly detection across nine domains, organizing approaches into selection, ensembling, and generation. Extensive evaluation shows many methods fail to beat random; naive ensembling is accurate but costly, dataset-driven methods break OOD; proposes selective ensembling to balance accuracy and efficiency. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: h9fbb9c1c34e96a0a
Venue: VLDB
Year: 2025
Pagerank: 5.168414e-05
Overall Rank: 9,493 | 36.20%
DOI: 10.14778/3749646.3749699
PDF: Download (CC BY-NC-ND 4.0)

Incoming Non-self Citations Over Time

Authors

1. Qinghua Liu (Ohio State University)
2. Seunghak Lee (Meta)
3. John Paparrizos (Ohio State University)

BibTeX Citation

@article{liu_vldb25,
        title = {{TSB-AutoAD: Towards Automated Solutions for Time-Series Anomaly Detection}},
        author = {Liu, Qinghua and Lee, Seunghak and Paparrizos, John},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {11},
        pages = {4364--4379},
        doi = {10.14778/3749646.3749699},
        url = {https://doi.org/10.14778/3749646.3749699},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
9,494	Beyond Compression: A Comprehensive Evaluation of Lossless Floating-Point Compression	2025	VLDB	5.168414e-05
10,480	HYDRA: A Multi-Level Hierarchy-Driven Approach for Robust Anomaly Detection in Time Series	2026	SIGMOD	4.9769913e-05
10,494	MUFASA: Fast and Accurate Multivariate Time-Series Clustering	2026	SIGMOD	4.9769913e-05
10,521	The Power of Anomaly Detection in Predictive Maintenance: [Experiments & Analysis]	2026	SIGMOD	4.9769913e-05
10,770	KDSelector: A Framework of Knowledge-Enhanced and Data-Efficient Selector Learning for Anomaly Detection Model Selection in Time Series	2026	VLDB	4.9769913e-05
11,355	BURST: Rendering Clustering Techniques Suitable for Evolving Streams	2025	VLDB	4.9769913e-05
11,425	EasyAD: A Demonstration of Automated Solutions for Time-Series Anomaly Detection	2025	VLDB	4.9769913e-05

Outgoing Citations (Sorted by Pagerank)

Showing 22 of 22 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
142	LOF: Identifying Density-Based Local Outliers	2000	SIGMOD	0.00029189529
583	Efficient Algorithms for Mining Outliers from Large Data Sets	2000	SIGMOD	0.00015952617
1,005	Anomaly Detection in Time Series: A Comprehensive Evaluation	2022	VLDB	0.00012584107
1,579	k-Shape: Efficient and Accurate Clustering of Time Series	2015	SIGMOD	0.00010182038
1,629	SAND: Streaming Subsequence Anomaly Detection	2021	VLDB	0.0001003165
1,938	TSB-UAD: An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection	2022	VLDB	9.334286e-05
1,974	Decomposed Bounded Floats for Fast Compression and Queries	2021	VLDB	9.2806652e-05
2,376	Series2Graph: Graph-based Subsequence Anomaly Detection for Time Series	2020	VLDB	8.5517908e-05
3,299	Volume Under the Surface: A New Accuracy Evaluation Measure for Time-Series Anomaly Detection	2022	VLDB	7.441222e-05
4,105	AutoOD: Automatic Outlier Detection	2023	SIGMOD	6.8033852e-05
4,317	GRAIL: Efficient Time-Series Representation Learning	2019	VLDB	6.6651881e-05
4,705	Debunking Four Long-Standing Misconceptions of Time-Series Distance Measures	2020	SIGMOD	6.4591377e-05
5,477	Good to the Last Bit: Data-Driven Encoding with CodecDB	2021	SIGMOD	6.1152706e-05
6,075	AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series Data	2024	VLDB	5.8925161e-05
6,192	VergeDB: A Database for IoT Analytics on Edge Devices	2021	CIDR	5.8540507e-05
7,096	Time-Series Clustering: A Comprehensive Study of Data Mining, Machine Learning, and Deep Learning Methods	2025	VLDB	5.5991152e-05
7,647	A Structured Study of Multivariate Time-Series Distance Measures	2025	SIGMOD	5.4746904e-05
8,166	PIDS: Attribute Decomposition for Improved Compression and Query Performance in Columnar Storage	2020	VLDB	5.3846089e-05
9,633	Theseus: Navigating the Labyrinth of Time-Series Anomaly Detection	2022	VLDB	5.1459383e-05
9,665	Odyssey: An Engine Enabling The Time-Series Clustering Journey	2023	VLDB	5.142891e-05
11,425	EasyAD: A Demonstration of Automated Solutions for Time-Series Anomaly Detection	2025	VLDB	4.9769913e-05
11,755	Accelerating Similarity Search for Elastic Measures: A Study and New Generalization of Lower Bounding Distances	2023	VLDB	4.9769913e-05

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1	5,118	TimeEval: A Benchmarking Toolkit for Time Series Anomaly Detection Algorithms	2022	VLDB
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