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: Graph theory is a powerful tool for addressing problems involving discrete structures, such as determining the shortest length of connected river networks or the shortest distance between ...
Welcome to the artifact repository of OSDI'25 accepted paper: Achieving Low-Latency Graph-Based Vector Search via Aligning Best-First Search Algorithm with SSD! This repository contains the ...
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