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• MaLSF shifts multimodal verification from passive fusion to an active, bidirectional verification process.method 95%
• MaLSF utilizes mask-label pairs as semantic anchors to bridge pixels and words.method 95%
• The Bidirectional Cross-modal Verification (BCV) module uses parallel query streams (Text-as-Query and Image-as-Query) to pinpoint conflicts.method 95%
• The Hierarchical Semantic Aggregation (HSA) module aggregates multi-granularity conflict signals for task-specific reasoning.method 95%
• MaLSF achieves state-of-the-art performance on both the DGM4 and multimodal fake news detection tasks.result 95%
• MaLSF successfully identifies subtle conflicts, such as the 'champagne-vs-failed' conflict, that elude traditional methods.result 90%
• Current multimodal verification methods struggle with sophisticated misinformation due to passive holistic fusion and feature dilution.limitation 90%
• MaLSF shifts multimodal verification from passive fusion to an active, bidirectional verification process.method 95%
• MaLSF utilizes mask-label pairs as semantic anchors to bridge pixels and words.method 95%
• The Bidirectional Cross-modal Verification (BCV) module uses parallel query streams (Text-as-Query and Image-as-Query) to pinpoint conflicts.method 95%
• The Hierarchical Semantic Aggregation (HSA) module aggregates multi-granularity conflict signals for task-specific reasoning.method 95%
• MaLSF achieves state-of-the-art performance on both the DGM4 and multimodal fake news detection tasks.result 95%

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