An Axiomatic Approach to Model-Agnostic Concept Explanations

• URL: http://arxiv.org/abs/2401.06890v1
• Date: Fri, 12 Jan 2024 20:53:35 GMT
• Title: An Axiomatic Approach to Model-Agnostic Concept Explanations
• Authors: Zhili Feng, Michal Moshkovitz, Dotan Di Castro, J. Zico Kolter
• Abstract summary: We propose an approach to concept explanations that satisfy three natural axioms: linearity, recursivity, and similarity. We then establish connections with previous concept explanation methods, offering insight into their varying semantic meanings.
• Score: 67.84000759813435
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Concept explanation is a popular approach for examining how human-interpretable concepts impact the predictions of a model. However, most existing methods for concept explanations are tailored to specific models. To address this issue, this paper focuses on model-agnostic measures. Specifically, we propose an approach to concept explanations that satisfy three natural axioms: linearity, recursivity, and similarity. We then establish connections with previous concept explanation methods, offering insight into their varying semantic meanings. Experimentally, we demonstrate the utility of the new method by applying it in different scenarios: for model selection, optimizer selection, and model improvement using a kind of prompt editing for zero-shot vision language models.

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