DyMRL: Dynamic Multispace Representation Learning for Multimodal Event Forecasting in Knowledge Graph

ArXi:2603.24636v1 Announce Type: cross Accurate representation of multimodal knowledge is crucial for event forecasting in real-world scenarios. However, existing studies have largely focused on static settings, overlooking the dynamic acquisition and fusion of multimodal knowledge. 1) At the knowledge acquisition level, how to learn time-sensitive information of different modalities, especially the dynamic structural modality.