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Research questionHow can a single graph-learning model handle text-, image-, and multimodal-attributed graphs?Attributed graphs may contain textual node features, visual node features, or both, while many graph-learning models assume one fixed modality schema. Supporting these settings separately makes reuse across graphs and modality configurations difficult.
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Machine Learning
Multimodal Models
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Latest papersRecent research connected to this question, newest first.One Model, Many Graphs: Learning over Attributed Graphs across Heterogeneous Modalities with Vision-Language ModelsThe source studies a pretrained vision-language model with structure-aware graph adapters for text-attributed, image-attributed, and multimodal-attributed graphs. Its evidence covers node classification and link prediction across diverse domains, including reported generalization to unseen graphs and varying modality schemas.research paper · Sep 2, 2026
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