ICON Decomposition : Multivariate Concept-Level Explanations of Deep Representations for Model Auditing
Roshan Prakash, Marco Simnacher, Manuel Pfeuffer et al.
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Safety Signals to Verify NetOps Agents with Action-Level Granularity
Agentic Network Operations (NetOps) are an emerging paradigm promising to enable workload-aware, self-adjustable, and reliable autonomous networks. While agents have proven their value in incident summarization and telemetry signal extraction, their effectiveness as autonomous control-loop engines heavily relies on the...
T. Labarta, Frederik Pahde, Novak Boškov et al.
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ICON Decomposition: Auditing Deep Neural Networks with Multivariate Variance-based Concept-level Explanations
CON decomposition is introduced, which quantifies how much of a layer's variance each concept explains given all other concepts and the outcome, and how much none of them explains, yielding layer-comparable, calibrated scores that suppress false positives.
R. Rane, Marco Simnacher, Manuel Pfeuffer et al.
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