Abstract: Graph neural networks (GNNs) are specifically designed for graph-structured data and have gained significant attention. However, training GNN on large-scale graphs remains challenging due to ...

Abstract: Retrieval-Augmented Generation (RAG) has emerged as a potent method for enhancing the capabilities of large language models (LLMs) by integrating them with external knowledge sources. While ...