Scalable and Adaptive Log-based Anomaly Detection: A Synergistic Approach
Jinyang Liu, Junjie Huang, Zhihan Jiang et al.
· 0 citations
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Jul 2026
LogNLQ: Natural-Language Log Querying with Parser-Induced and Semantically Grounded Schemas
LogNLQ is a framework that formulates natural-language log querying as executable SQL generation over parser-induced and semantically grounded schemas, and demonstrates that LogNLQ consistently outperforms all representative baselines by wide margins, with especially pronounced gains on analytically complex scenario queries.
Jue Wang, Jinyang Liu, Zhuang-Bin Chen et al.
· arXiv.org · 0 citations