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Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration
Prior attempts have quantified the privacy risks of language models (LMs) via MIAs, but there is still no consensus on whether existing MIA algorithms can cause remarkable privacy leakage on practical Large Language Models (LLMs).
A Probabilistic Fluctuation based Membership Inference Attack for Diffusion Models
Membership Inference Attack (MIA) identifies whether a record exists in a machine learning model's training set by querying the model.
An Event Correlation Filtering Method for Fake News Detection
To improve the detection performance of fake news, we take advantage of the event correlations of news and propose an event correlation filtering method (ECFM) for fake news detection, mainly consisting of the news characterizer, the pseudo label annotator, the event credibility updater, and the news entropy selector.
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