<ul><li>State-space modeling has emerged as a powerful paradigm for sequence analysis in various tasks.</li><li>The proposed Adaptive State-Space Mamba (ASSM) framework is designed for real-time sensor data anomaly detection.</li><li>The framework leverages sequential hidden states and introduces an adaptive gating mechanism for efficient and scalable detection.</li><li>Extensive experiments demonstrate superior performance compared to existing baselines.</li></ul>

Adaptive State-Space Mamba for Real-Time Sensor Data Anomaly Detection

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