AINeutralarXiv – CS AI · May 96/10
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Concept-Based Abductive and Contrastive Explanations for Behaviors of Vision Models
Researchers propose concept-based abductive and contrastive explanations that identify minimal sets of high-level concepts causally relevant to vision model predictions. The approach combines human-interpretable concept-based explanations with formal causal reasoning, enabling better understanding of both individual predictions and common model behaviors across image collections.