Skip to content
星际流动

LLM-Enhanced Log Anomaly Detection: A Comprehensive Benchmark of Large Language Models for Automated System Diagnostics

发布
采集
学术前沿 3.2 分 — Moderate AI relevance +practical(1)
原文: cs.LG updates on arXiv.org

评分 3.2 · 来源:cs.LG updates on arXiv.org · 发布于 2026-04-15

评分依据:Moderate AI relevance +practical(1)

arXiv:2604.12218v1 Announce Type: new Abstract: System log anomaly detection is critical for maintaining the reliability of large-scale software systems, yet traditional methods struggle with the heterogeneous and evolving nature of modern log data. Recent advances in Large Language Models (LLMs) offer promising new approaches to log understanding, but a systematic comparison of LLM-based methods against established techniques remains lacking. In this paper, we present a comprehensive benchmark…