Pre-training Graph Model Phase. In the pre-training phase, we employ link prediction as the self-supervised task for pre-training the graph model. Producer Phase. In the Producer phase, we employ LLM ...
Abstract: Graph matching aims to establish node correspondences between graphs, which is a classic combinatorial optimization problem. In recent years, (deep) learning-based methods have emerged as a ...
Abstract: Heterogeneous graph neural networks (HGNNs) have demonstrated promising capabilities in addressing various problems defined on heterogeneous graphs containing multiple types of nodes or ...
To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated. MIT Technology Review Explains: Let our writers untangle the complex, messy ...
Simplify the development of your next GenAI application with GraphRAG-SDK, a specialized toolkit for building Graph Retrieval-Augmented Generation (GraphRAG) systems. It integrates knowledge graphs, ...
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