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SAVER is introduced, a transition-centered framework in which Substrate locates reusable influence, Adaptation captures how it changes, Violation identifies compromised safety attributes, Exposure marks where failures become observable, and Response assesses containment, repair, or revocation.
Multivariate time-series anomaly detection is central to modern cyber-physical and cloud monitoring systems. While most detectors rely solely on sensor or telemetry streams, operational anomalies are often accompanied by textual evidence such as logs. This paper presents a conditional multimodal framework for time-seri...
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