KRONE derives semantic execution hierarchies from flat logs to enable modular multi-level anomaly detection with hybrid local and nested-aware detectors plus limited LLM use, delivering 10% F1 gains and over 100x data efficiency on benchmarks and industrial data.
Spell: Streaming parsing of system event logs
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2representative citing papers
FAME achieves F1 of 98.16 on BGL and 99.95 on Thunderbird for message-level log anomaly detection using at most K=100 labels per template, reducing annotation effort by 76x while detecting anomalies from unseen EventIDs.
citing papers explorer
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KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction
KRONE derives semantic execution hierarchies from flat logs to enable modular multi-level anomaly detection with hybrid local and nested-aware detectors plus limited LLM use, delivering 10% F1 gains and over 100x data efficiency on benchmarks and industrial data.
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FAME: Failure-Aware Mixture-of-Experts for Message-Level Log Anomaly Detection
FAME achieves F1 of 98.16 on BGL and 99.95 on Thunderbird for message-level log anomaly detection using at most K=100 labels per template, reducing annotation effort by 76x while detecting anomalies from unseen EventIDs.