Overview of black-box forgetting (IMAGE)

Tokyo University of Science

Overview of black-box forgetting

Caption

Selective forgetting aims to reduce the classification accuracy for classes to be forgotten while maintaining the accuracy for the classes to be remembered. The proposed method, which targets the image classifier model CLIP, achieves selective forgetting by optimizing the input text prompt, since the model itself is a ‘black box.’

Credit

Go Irie from Tokyo University of Science

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