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Found 2 papers, 2 papers with code
TMI! Finetuned Models Leak Private Information from their Pretraining Data
In this work we propose a new membership-inference threat model where the adversary only has access to the finetuned model and would like to infer the membership of the pretraining data.
SNAP: Efficient Extraction of Private Properties with Poisoning
Property inference attacks allow an adversary to extract global properties of the training dataset from a machine learning model.
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