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.
and Hofmann, Dennis M
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.DB 3years
2026 3roles
background 1polarities
background 1representative citing papers
Krone-viz provides an interactive interface for hierarchical log decomposition, modular anomaly detection, and human-in-the-loop LLM explanation on system logs.
GRACE dynamically constructs and updates coresets for LLM training using representation diversity, gradient-based importance, and k-NN graph propagation to improve efficiency and performance.
citing papers explorer
-
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.
-
Detect, Localize, and Explain: Interactive Hierarchical Log Anomaly Analytics with LLM Augmentation
Krone-viz provides an interactive interface for hierarchical log decomposition, modular anomaly detection, and human-in-the-loop LLM explanation on system logs.
-
GRACE: A Dynamic Coreset Selection Framework for Large Language Model Optimization
GRACE dynamically constructs and updates coresets for LLM training using representation diversity, gradient-based importance, and k-NN graph propagation to improve efficiency and performance.