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Few-shot Hate Speech Detection Based on the MindSpore Framework

💡 原文英文，约100词，阅读约需1分钟。
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内容提要

本研究提出了MS-FSLHate框架，旨在提高社交媒体上少量样本的仇恨言论检测能力。该框架结合了可学习提示嵌入、CNN-BiLSTM网络和同义词对抗数据增强，显著提升了检测的准确性和适应性，适合资源有限的环境。实验结果表明，其在精确率、召回率和F1值上均优于现有基准。

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标签

CNN-BiLSTM framework 仇恨言论检测 少量样本 数据增强 检测准确性
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