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 ...

Raster-to-Graph is a novel automatic recognition framework, which achieves structural and semantic recognition of floorplans, addresses the problem of obtaining high-quality vectorized floorplans from ...

Abstract: The nature of heterophilous graphs is significantly different from that of homophilous graphs, which causes difficulties in early graph neural network (GNN) models and suggests aggregations ...

This repository contains code for Talk like a Graph: Encoding Graphs for Large Language Models and Let Your Graph Do the Talking: Encoding Structured Data for LLMs. @inproceedigs{fatemi2024talk, ...