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

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

25 May 2022arXiv:2205.12628archive 2025-07-28

Jie Huang, Hanyin Shao, Kevin Chen-Chuan Chang

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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get_local_domain jeffhj/lm_personalinfoleak/analysis.py official repository unverified Apache-2.0 (permissive) · 19ed7410c1facefc · report
get_pattern_type jeffhj/lm_personalinfoleak/analysis.py official repository unverified Apache-2.0 (permissive) · e19e13ff1dfd9ac7 · report
load_csv jeffhj/lm_personalinfoleak/pred.py official repository unverified Apache-2.0 (permissive) · 16b6899a69cd97b7 · report
load_pickle jeffhj/lm_personalinfoleak/analysis.py official repository unverified Apache-2.0 (permissive) · 392f87e3a95b49fd · report

Tasks

Language ModellingMemorization

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LM Email Address Leakage

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