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Updated: Jan 7, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
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Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

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可解释的多语言和多模式假新闻检测:朝着强大的和值得信赖的人工智能来打击错误信息

Rohini Jadhav1, Vishal Meshram2, Amol Bhosle3

  • 1Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune, India.

Frontiers in artificial intelligence
|December 26, 2025
PubMed
概括

一种新的混合可解释多式变压器假冒 (HEMT-Fake) 模型增强了跨多种语言和模式的假新闻检测. 这种方法提供了更好的准确性和可解释性,这对于打击复杂的虚假信息活动至关重要.

关键词:
竞争力强度 竞争力强度可解释的人工智能假新闻检测 假新闻检测混合深度学习架构 混合深度学习架构错误的信息和错误的信息是错误的信息.多语言数据集.社交媒体分析

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