s. In this paper, we present a perspective about the chal-lenges and opportunities associated with developing large graph models1. First, we introduce large graph models and outline four key …

First, we introduce large graph models and outline four key desired characteristics, including graph models with scaling laws, graph foundation model, in-context graph understanding and …

This repository contains a paper list related to Large Graph Models. Similar to Large Language Models (LLMs) for natural languages, we believe large graph models will revolutionaize graph …

First, we discuss the desired characteristics of large graph models. Then, we present detailed discussions from three key perspectives: representation basis, graph data, and graph models.

Aug 28, 2023 · First, we discuss the desired characteristics of large graph models. Then, we present detailed discussions from three key perspectives: representation basis, graph data, …

This work provides a comprehensive review of GNN models in recent financial context, and summarizes the GNN methodology for each graph type, application in each area, and …

Jun 12, 2024 · Researchers from Vanderbilt University, the University of Michigan, Adobe Research, and Intel Labs have introduced LARGE GRAPH GENERATIVE MODEL (LGGM), a …

May 13, 2024 · This tutorial offers an overview of incorporating large language models into the graph domain, accompanied by practical examples. The methods are categorized into three …

Aug 28, 2023 · First, we discuss the desired characteristics of large graph models. Then, we present detailed discussions from three key perspectives: representation basis, graph data, …

As shown in Figure 1, the integration of graphs and LLMs demonstrates success in various downstream tasks across a myriad of graph domains. Integrating LLMs with tra-ditional GNNs …