🚀 Excited to share that a survey paper from our RCLN team has been accepted at IJCAI 2026! This work has been done in collaboration with CentraleSupélec. "Graph
A survey paper on graph rewiring techniques for Graph Neural Networks (GNNs) has been accepted at IJCAI 2026. The paper addresses the challenges of over-squashing and over-smoothing in GNNs, which hinder information flow and performance. It proposes graph rewiring as a method to improve GNNs by modifying their topology and opens a discussion on the necessity and attribution of improvements from such interventions. AI
IMPACT This survey provides a structured overview of graph rewiring techniques, potentially guiding future research and development in GNNs for complex data structures.