Efficient Log Anomaly Detection via Dual-Domain State Space Modeling
Log anomaly detection requires models that capture long-range event dependencies without the quadratic sequence-length cost of self-attention. We present LogMamba, a reconstruction-based model that combines a bidirectional selective state-space branch with a Multi-Scale Frequency Learner (MSFL). The sequence branch mod...