By fixing CLIP-derived language similarity maps as the coefficient matrix in non-negative matrix factorization, this method produces named, faithful concept explanations for frozen image classifiers.
Show and tell: Visually explainable deep neural nets via spatially-aware concept bot- tleneck models
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Naming the Concepts Classifiers Rely On: Language-Anchored Decomposition for Faithful Explanation
By fixing CLIP-derived language similarity maps as the coefficient matrix in non-negative matrix factorization, this method produces named, faithful concept explanations for frozen image classifiers.