Too Sure to Be Safe: Model Calibration for Reliable Log Anomaly Detection.

arXiv:2608.17965v4 Announce Type: replace-cross Abstract: Online log anomaly detection is critical for maintaining the reliability of large-scale computing systems. Although recent language model-based log anomaly detectors achieve strong detection performance