AI RESEARCH
FAME: Failure-Aware Mixture-of-Experts for Message-Level Log Anomaly Detection
arXiv CS.LG
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ArXi:2605.22779v1 Announce Type: cross Production systems generate millions of log lines daily, yet most anomaly detectors operate at the session or window-level, flagging groups of lines rather than identifying the specific message responsible. This coarse granularity forces operators to inspect many routine lines per alert. Message-level detection offers finer granularity, but remains challenging. A single event template may correspond to both normal and anomalous messages, failures arise from heterogeneous subsystems, and line-level labeling at scale is impractical.