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Unlock explainable outlier detection in foundation models with FoMo-X, a modular framework that adds negligible inference overhead while revealing interpretable risk tiers and calibrated confidence measures.
Anomaly detection gets a dose of interpretability: SYRAN learns human-readable equations that flag anomalies by violating learned invariants.
