面向大型语言模型的日语预训练语料中的敏感个人信息检测 / Detecting Sensitive Personal Information in Japanese Pre-Training Corpora for Large Language Models
1️⃣ 一句话总结
本研究针对日语大语言模型预训练数据中可能出现的敏感个人信息,利用大模型自动标注数据并训练分类器,首次实现了对日本《个人信息保护法》所定义的特殊需注意个人信息的有效检测,为隐私合规提供了自动化解决方案。
Sensitive personal information can appear in large-scale pre-training corpora for large language models (LLMs). Detecting and filtering such information is therefore essential to ensure compliance with privacy regulations and prevent unintended information leakage. However, in contrast to English and other languages, research into sensitive personal information has been limited in the Japanese language. In this study, we focus on sensitive personal data defined as special care-required personal information (SCPI) under Japan's Act on the Protection of Personal Information (APPI). We construct an SCPI dataset using LLM-based annotation and train machine learning models to rapidly detect SCPI in text. As a result, our SCPI classifier can effectively identify information related to SCPI. This study is the first to explore SCPI detection in Japanese text corpora, highlighting the challenges of accurate detection.
面向大型语言模型的日语预训练语料中的敏感个人信息检测 / Detecting Sensitive Personal Information in Japanese Pre-Training Corpora for Large Language Models
本研究针对日语大语言模型预训练数据中可能出现的敏感个人信息,利用大模型自动标注数据并训练分类器,首次实现了对日本《个人信息保护法》所定义的特殊需注意个人信息的有效检测,为隐私合规提供了自动化解决方案。
源自 arXiv: 2606.12114