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Unseen Anomaly Detection from System Logs

Summary: UnseenLog targets log anomaly detection under anomaly shift: test-time failures whose patterns were absent in training, common after software upgrades. Key ideas: MinMax pseudo-anomaly selection plus RISE, an iterative competitive training/data-enhancement scheme to improve robustness to novel anomalies. (summarized by gpt-5.4-mini on Apr 11 2026)

Paper ID
7530
Venue
SIGMOD
Year
2026
Pagerank
4.1945683e-05
Overall Rank
10,218 | 28.92%
DOI
10.1145/3786705

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

Rank Cited Paper Year Venue Pagerank
6,394 Pluto: Sample Selection for Robust Anomaly Detection on Polluted Log Data 2024 SIGMOD 5.0829207e-05
6,893 Adaptive and Efficient Log Parsing as a Cloud Service 2025 SIGMOD 4.8925595e-05
6,897 PreLog: A Pre-trained Model for Log Analytics 2024 SIGMOD 4.8925595e-05
9,872 Substructure-aware Log Anomaly Detection 2025 VLDB 4.2667743e-05
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