arXiv Machine Learning July 31, 2026 By Roel Visser, Isaac Roberts, Barbara Hammer

Contrastive Concept Importance: Explaining Pairwise Class Decisions Through Automatically Extracted Concept Representations

Read the original on arXiv Machine Learning →

arXiv:2607. 27904v1 Announce Type: new Abstract: Concept-based explanations are a prevalent way to explain the decisions of complex black-box methods through semantically meaningful, human-interpretable concepts.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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