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CALM-TS is presented, a risk-controlled weak-supervision pipeline that bounds the labeling error rate while maximizing coverage, and yields auditable evidence chains and a coverage-based, label-free drift indicator.
Labeling time-series events such as anomalies and system failures is expensive and subjective, and distribution drift makes label definitions evolve over time. Large language models can generate weak labels with natural-language rationales, but their error rates are unbounded and their failure modes opaque. We present...
RunbookFX is presented, a typed functional domain-specific language that elevates incident response from natural-language suggestions to executable programs whose safety is established statically, and key insight is that incident-response safety decomposes into three interacting dimensions: risk severity, exercised cap...
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