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cs.LG2023★ 13 cited
In-Context Unlearning: Language Models as Few Shot Unlearners
Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju
Machine unlearning, the study of efficiently removing the impact of specific training instances on a model, has garnered increased attention in recent years due to regulatory guide…
cs.LG2023
Gaussian Membership Inference Privacy
Tobias Leemann, Martin Pawelczyk, Gjergji Kasneci
We propose a novel and practical privacy notion called -Membership Inference Privacy (-MIP), which explicitly considers the capabilities of realistic adversaries under the me…