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#membership-inference

2 curated events
papersSEP 11 04:00 UTC

Adaptive Diffusion Freezing proposed against membership inference attacks

A new arXiv preprint introduces a technique called Adaptive Diffusion Freezing that aims to make diffusion models more resistant to membership inference attacks, which try to determine whether a specific sample was part of the training data. The method adapts how parts of the model are frozen during training to limit the privacy leakage that standard diffusion training can expose.

privacy/diffusion-models/membership-inference/research
papersSEP 11 04:00 UTC

arXiv Paper Proposes Black-Box Membership Inference via Word-Level Probabilities

A new arXiv preprint introduces a membership inference method that estimates word-level probabilities to detect whether text appeared in a language model's training data. The approach targets black-box settings, where attackers lack direct access to model internals. It aims to improve privacy auditing of large language models.

privacy/membership-inference/llm/safety