---
id: 20260313-T0-26
title: "高效混合深度学习方法检测网络虐待性语言"
title_en: "Efficient Hybrid Deep Learning Approach for Online Abuse Detection"
url: https://ai.daily.yangsir.net/daily/20260313-T0-26
issue_date: 2026-03-13
publish_date: 2026-03-12T04:00:00.000Z
source_name: "arXiv cs.CL (NLP)"
source_url: https://arxiv.org/abs/2603.09984
---

# 高效混合深度学习方法检测网络虐待性语言

研究人员提出高效混合深度学习方法，结合CNN和注意力机制检测网络暴力语言。模型在多语言数据集上测试，对仇恨言论和有毒评论的识别准确率达91%，处理速度比传统方法快3倍。

## English Version

**Efficient Hybrid Deep Learning Approach for Online Abuse Detection**

Researchers developed an efficient hybrid deep learning method combining CNN and attention mechanisms to detect online abusive language. Tested on multilingual datasets, the model achieves 91% accuracy in identifying hate speech and toxic comments, processing 3x faster than traditional methods.

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**来源**：[arXiv cs.CL (NLP)](https://arxiv.org/abs/2603.09984)

**详情页**：https://ai.daily.yangsir.net/daily/20260313-T0-26

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