广西师范大学学报（自然科学版）2026，Vol.44Issue(1)：68-79,12.DOI:10.16088/j.issn.1001-6600.2024122004
基于注意力机制和多尺度融合的多模态虚假新闻检测模型
A Detection Model for Multimodal Fake News Based on Attention Mechanism and Multiscale Fusion
摘要
Abstract
Fake news can have serious consequences if not dealt with in a timely manner.Currently,various attention mechanisms are mainly employed in multimodal fake news detection methods to fuse unimodal features.The semantic gaps that may exist between different modal features are not taken into account,nor is the potential of multimodal pre-training models fully exploited.To this end,a new multimodal fake news detection model that performs multistage fusion of features is proposed in this paper.The pretrained multimodal model is utilized by the proposed model to extract the aligned features.Then the features are enhanced by each other through the attention mechanism,and the enhanced features are spliced to achieve early fusion.Finally,the interaction information between different modal features is captured by the multiscale fusion module,and the fusion weights are learned to realize the late fusion of features.It is shown by the experimental results that the model proposed in this paper achieves better results than similar models,and the effectiveness of the attention mechanism and the multiscale fusion module is also verified by the experimental results.关键词
多模态/虚假新闻检测/注意力机制/多尺度融合/多阶段融合Key words
multimodality/fake news detection/attention mechanism/multiscale fusion/multistage fusion分类
信息技术与安全科学引用本文复制引用
施子豪,蒙祖强,谈超洪..基于注意力机制和多尺度融合的多模态虚假新闻检测模型[J].广西师范大学学报（自然科学版）,2026,44(1):68-79,12.基金项目
国家自然科学基金(62266004) （62266004）
广西数字基础设施重点实验室开放基金(GXDINBC202401) （GXDINBC202401）
