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Chapter and Conference Paper
Discovering Multimodal Hierarchical Structures with Graph Neural Networks for Multi-modal and Multi-hop Question Answering
Multimodal reasoning is a challenging task that requires understanding and integrating information from different modalities, such as text and image. Existing methods for multimodal reasoning often fail to cap...
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Chapter and Conference Paper
Fine-Grained Urban Flow Inferring via Conditional Generative Adversarial Networks
Urban flow super-resolution (UFSR) can deduce fine-grained urban flow heatmap (UFH) based on coarse-grained observations and plays an essential role in urban planning (traffic prediction, public facility deplo...