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CAS: A Causal Attribution Score for Local and Global Explainable Artificial Intelligence

Abstract

arXiv:2608.12555v1 Announce Type: new Abstract: Predictive explanation methods attribute a model output; they do not, by themselves, attribute an intervention effect on the real-world outcome. We introduce the Causal Attribution Score (CAS), a compact score architecture for causal explanation. CAS starts from an identified interventional coalition game, allocates the joint intervention contrast with causal Shapley contributions, and converts those raw outcome-scale effects into Local CAS, Signed

Transparencia: Este análisis ha sido generado con asistencia de inteligencia artificial bajo supervisión editorial de SAPIENSDATAAI.

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