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GAMED: Knowledge Adaptive Multi-Experts Decoupling for Multimodal Fake News Detection
Shen, Lingzhi Long, Yunfei Cai, Xiaohao Razzak, Imran Chen, Guanming Liu, Kang Jameel, Shoaib
Shen, Lingzhi
Long, Yunfei
Cai, Xiaohao
Razzak, Imran
Chen, Guanming
Liu, Kang
Jameel, Shoaib
Supervisor
Department
Computational Biology
Embargo End Date
Type
Conference proceeding
Date
2025
License
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
Multimodal fake news detection often involves modelling heterogeneous data sources, such as vision and language. Existing detection methods typically rely on fusion effectiveness and cross-modal consistency to model the content, complicating understanding how each modality affects prediction accuracy. Additionally, these methods are primarily based on static feature modelling, making it difficult to adapt to the dynamic changes and relationships between different data modalities. This paper develops a significantly novel approach, GAMED, for multimodal modelling, which focuses on generating distinctive and discriminative features through modal decoupling to enhance cross-modal synergies, thereby optimizing overall performance in the detection process. GAMED leverages multiple parallel expert networks to refine features and pre-embed semantic knowledge to improve the experts' ability in information selection and viewpoint sharing. Subsequently, the feature distribution of each modality is adaptively adjusted based on the respective experts' opinions. GAMED also introduces a novel classification technique to dynamically manage contributions from different modalities, while improving the explainability of decisions. Experimental results on the Fakeddit and Yang datasets demonstrate that GAMED performs better than recently developed state-of-the-art models. The source code can be accessed at https://github.com/slz0925/GAMED.
Citation
L. Shen et al., “GAMED: Knowledge Adaptive Multi-Experts Decoupling for Multimodal Fake News Detection,” p. 10, Dec. 2024, doi: 10.1145/3701551.3703541
Source
WSDM '25: Proceedings of the Eighteenth ACM International Conference on Web Search and Data Mining
Conference
18th International Conference on Web Search and Data Mining-WSDM
Keywords
Fake News Detection, Multimodal Learning, Pattern Recognition, Mixture of Experts, Explainable AI
Subjects
Source
18th International Conference on Web Search and Data Mining-WSDM
Publisher
Association for Computing Machinery