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Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data

Summary: Pluto automatically selects a clean subset from polluted log data to train a Transformer-based anomaly detector. It uses Gaussian mixtures to identify and discard polluted embedding regions and a (1−1/e) greedy facility-location approach to purify samples, iterating training. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6969
Venue
SIGMOD
Year
2024
Pagerank
5.0829207e-05
Overall Rank
6,394 | 55.52%
DOI
10.1145/3677139

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,218 Unseen Anomaly Detection from System Logs 2026 SIGMOD 4.1945683e-05
10,713 CoLA: Model Collaboration for Log-based Anomaly Detection 2025 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank Cited Paper Year Venue Pagerank
161 LOF: Identifying Density-Based Local Outliers 2000 SIGMOD 0.00039846974
4,154 Robust and Transferable Log-based Anomaly Detection 2023 SIGMOD 6.4032498e-05
4,911 Unsupervised Contextual Anomaly Detection for Database Systems 2022 SIGMOD 5.8328593e-05
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