An online KS-statistic monitor detects shifts in deployed safety classifiers with 86.6% valid detection rate, exposes conformal prediction collapse in high-dimensional embeddings, and derives a confidence-gated security boundary against adaptive attackers.
Reactive soft prototype computing for concept drift streams
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Profile Drift Detection measures changes in partial dependence profiles with new metrics to detect concept drift while providing explanations and supporting efficient MLOps monitoring.
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Online Shift Detection and Conformal Adaptation for Deployed Safety Classifiers
An online KS-statistic monitor detects shifts in deployed safety classifiers with 86.6% valid detection rate, exposes conformal prediction collapse in high-dimensional embeddings, and derives a confidence-gated security boundary against adaptive attackers.