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Pre-load auditing of Agent Skills can achieve >97% accuracy in detecting malicious intent, even against semantics-preserving rewrites, by combining role-aware evidence extraction with semantic verification.
Overcome the limitations of existing information-theoretic methods by using structural entropy to learn high-order feature correlations, leading to improved feature selection in multi-view multi-label learning.