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cs.CV2024
Visual Evaluative AI: A Hypothesis-Driven Tool with Concept-Based Explanations and Weight of Evidence
Thao Le, Tim Miller, Ruihan Zhang +2
This paper presents Visual Evaluative AI, a decision aid that provides positive and negative evidence from image data for a given hypothesis. This tool finds high-level human conce…
cs.CV2020★ 1 cited
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors
Ruihan Zhang, Prashan Madumal, Tim Miller +2
Convolutional neural network (CNN) models for computer vision are powerful but lack explainability in their most basic form. This deficiency remains a key challenge when applying C…