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Digital Forgetting in Large Language Models: A Survey of Unlearning Methods
The objective of digital forgetting is, given a model with undesirable knowledge or behavior, obtain a new model where the detected issues are no longer present.
An Examination of the Alleged Privacy Threats of Confidence-Ranked Reconstruction of Census Microdata
The alleged threat of reconstruction attacks has led the U. S. Census Bureau (USCB) to replace in the Decennial Census 2020 the traditional statistical disclosure limitation based on rank swapping with one based on differential privacy (DP).
FL-Defender: Combating Targeted Attacks in Federated Learning
This makes it possible i) to train more accurate models due to learning from rich joint training data, and ii) to improve privacy by not sharing the workers' local private data with others.
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