GAMED: Knowledge Adaptive Multi-Experts Decoupling for Multimodal Fake News Detection

TL;DR

GAMED introduces a novel multimodal fake news detection method that decouples modal features, uses expert networks, and adaptively combines modalities to improve accuracy and explainability.

Contribution

The paper presents GAMED, a new approach that decouples modal features and employs expert networks for enhanced multimodal fake news detection.

Findings

Outperforms state-of-the-art models on Fakeddit and Yang datasets

Improves detection accuracy through modal decoupling and expert networks

Enhances explainability of multimodal fake news detection

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.