Researchers have found a problem with some AI-powered systems used to detect anomalies in computer logs. These systems often give too much confidence to incorrect predictions, which can lead to false alarms and system downtime. A new method called LoRD aims to address this issue by recalibrating the confidence of these predictions. LoRD works by learning from correctly classified examples and estimating the reliability of each prediction. In experiments, LoRD improved the reliability of anomaly detection systems without sacrificing their ability to detect anomalies. --- Why it matters: This matters because reliable log anomaly detection is crucial for maintaining large-scale computing systems. Engineers can use this method to improve the accuracy of their systems and reduce downtime caused by false alarms. Source: https://arxiv.org/abs/2608.17965