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Found 2 papers, 1 papers with code
On the Efficacy of Differentially Private Few-shot Image Classification
There has been significant recent progress in training differentially private (DP) models which achieve accuracy that approaches the best non-private models.
Grey-box Extraction of Natural Language Models
This is true even for queries that are entirely in-distribution, making extraction attacks indistinguishable from legitimate use; (ii) with fine-tuned base layers, the effectiveness of algebraic attacks decreases with the learning rate, showing that fine-tuning is not only beneficial for accuracy but also indispensable for model confidentiality.
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