NPCs going about their routines, factions clashing, wildlife prancing about... Even if you stand still, life goes on in these ...

Abstract: Open-source information is characterized by openness, transparency, sharing, and free usability. While these attributes promote knowledge dissemination and technological advancement, they ...

Graph Neural Networks (GNNs) and GraphRAG don’t “reason”—they navigate complex, open-world financial graphs with traceable, multi-hop evidence. Here’s why BFSI leaders should embrace graph-native AI ...

Google now considers og:title for search result titles. Open Graph tags gain broader significance beyond social media. Best practices for title creation remain unchanged. Google adds og:title to ...

The capacity to quickly store and analyze highly related data has led to graph databases’ meteoric popularity in the past few years. Applications like social networks, recommendation engines, and ...

Abstract: Graph Neural Networks (GNNs) have achieved great success in semi-supervised node classification. These methods usually assume the closed-set setting and classify unlabeled nodes to known ...

Repository of the tutorial "Leveraging Graph Neural Networks for User Profiling: Recent Advances and Open Challenges", held as part of the 32nd ACM International Conference on Information and ...

Capturing and encoding information about a visual scene, typically in the context of computer vision, artificial intelligence, or graphics, is called Scene representation. It involves creating a ...