TCAV (Testing with Concept Activation Vectors)

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Trains a linear classifier separating activations of concept examples from random ones, then measures how far the model's output moves along the resulting normal vector.

Findings

• TM-002The mean-difference concept vector scores higher than trained classifiers under cosine similarity [builds-on]