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.
Tracking the risk of a deployed model and detecting harmful distri- bution shifts
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Simple thresholding on an external verifier signal, calibrated by risk control, performs competitively with sequential hypothesis testing monitors on math reasoning and red-teaming datasets.
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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.
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A Gentle Introduction to Conformal Prediction and Distribution-Free Uncertainty Quantification
Pith review generated a malformed one-line summary.
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Online Safety Monitoring for LLMs
Simple thresholding on an external verifier signal, calibrated by risk control, performs competitively with sequential hypothesis testing monitors on math reasoning and red-teaming datasets.