{"schemaVersion":1,"target":{"type":"reading","id":"916d2c768b95a5b6a9dd8859fdd1142bfb00e0de8d3918e58c06732a9c58ffc0","revision":"2c81b4d1-c957-40ec-8b5a-1bb0877a5a76","revisionKind":"publication-id","title":"arXiv cs.AI paper: LogCDM aims to make log anomaly detection compact and interpretable","url":"https://escapemeridian.com/readings/arxiv-cs-ai-paper-logcdm-aims-to-make-log-anomaly-detection-916d2c76"},"source":{"type":"source","id":"https://arxiv.org/abs/2611.12775","revision":"43c15b827fcbbedefc15beeba7b1c55ff412a98e555259cc81ac3c58d30e4035","revisionKind":"sha256-source-text","title":"LogCDM: Interpretable Log Anomaly Detection via Behavioral Graph Drift and Adaptive Signal Fusion","url":"https://arxiv.org/abs/2611.12775"},"status":"available","items":[],"next":null,"scope":"Explicit citations in public readings and public file attachments to this reading. Shared topics are not citations. Other artifact types need an explicit reference adapter."}