Selective Amnesia using Contrastive Subnet Erasure for Class Level Unlearning in Vision Models

The research question

How can a model forget a class while preserving its other knowledge?

Research summary

This work investigates selective class-level forgetting in vision models. Contrastive subnet erasure connects the identification of relevant model components with targeted machine unlearning.