The rapid growth of online news consumption has intensified the spread of misinformation, underscoring the critical need for effective fake news detection methods. Despite significant advancements in this area, the scarcity and inadequacy of high-quality labeled datasets necessary for training effective ...
To address these limitations, we propose the FND-LLM Framework, which effectively combines SLMs and LLMs to enhance their complementary strengths and explore the capabilities of LLMs in multimodal fake news detection. The FND-LLM framework integrates the textual feature branch, the visual semantic ...
We begin by discussing the applications of LLMs in various computational problems in social science including sentiment analysis, hate speech detection, stance and humor detection, misinformation detection, event understanding, and social network analysis, illustrating their capacity to generate nuanced ...
FakeShield框架 如图3所示,该框架包括域标签引导的可解释伪造检测模块(Domain Tag-guided Explainable Forgery Detection Module,DTE-FDM)和多模态伪造定位模块(Multi-modal Forgery Localization Module,MFLM)两个关键部分。 DTE-FDM负责图像伪造检测与检测结果分析,利用数据域标签(domain tag)弥合不同伪造类型数据之间的...
fake news classification; fake news detection; fake news classifier; misinformation; disinformation; convolutional neural networks (CNNs); bidirectional encoder representations from transformers (BERT); generative pre-trained transformers (GPTs); natural language processing (NLP); informati...
关键词: Explainable Fake News Detection&Generative Adversarial Network 摘要:可解释的假新闻检测旨在通过带有注释解释的方式预测新闻的真实性。现如今,大型语言模型(LLMs)因其强大的自然语言理解和解释生成能力,被广泛应用于各种任务。然而,利用LLMs进行可解释的假新闻检测仍面临两大挑战。首先,虚假新闻往往看似合理,容...
Recent advancements in Large Language Models (LLMs) have enabled the creation of fake news, particularly in complex fields like healthcare. Studies highlight the gap in the deceptive power of LLM-generated fake news with and without human assistance, yet the potential of prompting techniques has ...
关键词: Fake News Detection & Hybrid Attention Mechanism & Large Language Models 摘要:本文提出了一种基于大型语言模型(LLMs)的混合注意力框架,用于假新闻检测。框架结合文本的统计特征(如标点分布、标题大写比例等)和深层语义特征,通过层次化的注意力机制捕获假新闻特征之间的复杂关系。在WELFake数据集上的实验表...
关键词:Fake News Detection&Bangla&Low-Resource Languages&LLMs&Transformer Models 摘要: 假新闻的快速传播对全球特别是低资源语言(如孟加拉语)构成了重大挑战。这些语言缺乏足够的数据集和检测工具。为了应对这一问题,本文提出了BanFakeNews-2.0,这是一个用于提升孟加拉语假新闻检测的增强数据集。该版本新增了11,70...
Consistency Regularization on Unlabeled News:在无标注数据熵使用约束信号,让全局预测结果和局部预测结果尽可能的一致性高一些。 首先,将全局表征和局部表征加权求和,得到原型表征 之后拉近原型表征和全局表征以及局部表征之间的预测logits Training Objective and Fake News Detection:总的损失是有监督交叉熵损失和无监督约...