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Are Large Pre-Trained Language Models Leaking Your Personal Information?

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arxiv 2205.12628 v2 pith:32WBTGPT submitted 2022-05-25 cs.CL cs.AIcs.CR

classification cs.CLcs.AIcs.CR
keywords informationpersonalplmsmodelslanguageleakingpre-trainedemail
verification ladder T0 review T1 audit T2 compute T3 formal
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Are Large Pre-Trained Language Models Leaking Your Personal Information? In this paper, we analyze whether Pre-Trained Language Models (PLMs) are prone to leaking personal information. Specifically, we query PLMs for email addresses with contexts of the email address or prompts containing the owner's name. We find that PLMs do leak personal information due to memorization. However, since the models are weak at association, the risk of specific personal information being extracted by attackers is low. We hope this work could help the community to better understand the privacy risk of PLMs and bring new insights to make PLMs safe.

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Cited by 14 Pith papers

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