AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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A hard pseudo-anomaly generation module to construct pseudo-anomalous tokens, simulating the subtle anomalies obscured by semantic smoothing, and a probabilistic boundary loss is developed to standardize anomaly scores into statistical distances, effectively enforcing anomalous instances to deviate significantly from t...
CORE introduces a decorrelated feature alignment module to directly align heterogeneous features into a unified representation space, which retains their semantic information, and formulates unified TAD as an in-context reconstruction problem, eliminating the need for labeled or synthesized anomalies.
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