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研究提出基于BERT的冒犯性居高临下语言自动检测系统

一篇于2026年10月26日发布在arXiv(编号arXiv:2610.31808v1)的论文提出两种自动化检测“居高临下式语言”(PCL)的方法,其中基于微调BERT嵌入的模型在开发集上F1得分为0.528,显著优于基于静态词向量与CNN的方案。

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Patronizing and Condescending Language Detection in English and Mandarin

arXiv:2610.31808v1 Announce Type: new Abstract: Patronizing and condescending language (PCL) is a form of harmful language that belittles and assumes pity for vulnerable groups, reinforcing negative societal stereotypes. However, unlike overt hate speech, it is often difficult to detect, even for human judges. This paper proposes a system for the automated detection of PCL. Our first approach uses static word embeddings and a convolutional neural network for classification, while our second approach uses pre-trained BERT embeddings fine-tuned for the PCL task. Our second approach was considerably more successful, and achieved an F1 score of 0.528 over the development set.

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Patronizing and Condescending Language Detection in English and Mandarin
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