Evidence-Constrained Log Anomaly Detection and LLM-Ready Failure Narrative Generation with Selective Refusal on LogEval 2024

Victor Cui DOI: 10.5281/zenodo.21623891 GAS Journal of Engineering and Technology (GASJET) This paper presents ECLA, an evidence-constrained, LLM-ready pipeline for LogEval 2024-style log intelligence on the HDFS-2k corpus. The study links four tasks: log parsing, window-level anomaly detection, root-cause ranking, Read More …