MULTIBENCH++ is a new large-scale benchmark integrating over 30 datasets across 15 modalities and 20 tasks, accompanied by an open-source automated evaluation pipeline that establishes new performance baselines for multimodal fusion.
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RSEA-MVGNN estimates view uncertainty with subjective logic to enable diverse feature enhancement through de-correlation and quality-aware aggregation in GNNs, outperforming prior methods on five datasets.
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MULTIBENCH++: A Unified and Comprehensive Multimodal Fusion Benchmarking Across Specialized Domains
MULTIBENCH++ is a new large-scale benchmark integrating over 30 datasets across 15 modalities and 20 tasks, accompanied by an open-source automated evaluation pipeline that establishes new performance baselines for multimodal fusion.
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RSEA-MVGNN: Multi-View Graph Neural Network with Reliable Structural Enhancement and Aggregation
RSEA-MVGNN estimates view uncertainty with subjective logic to enable diverse feature enhancement through de-correlation and quality-aware aggregation in GNNs, outperforming prior methods on five datasets.