{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/panda-expanded-width-aware-message-passing","title":"PANDA: Expanded Width-Aware Message Passing Beyond Rewiring","arxiv_id":"2406.03671","date":"2024-06-06","proceeding":null,"authors":["Jeongwhan Choi","Sumin Park","Hyowon Wi","Sung-Bae Cho","Noseong Park"],"abstract":"Recent research in the field of graph neural network (GNN) has identified a critical issue known as \"over-squashing,\" resulting from the bottleneck phenomenon in graph structures, which impedes the propagation of long-range information. Prior works have proposed a variety of graph rewiring concepts that aim at optimizing the spatial or spectral properties of graphs to promote the signal propagation. However, such approaches inevitably deteriorate the original graph topology, which may lead to a distortion of information flow. To address this, we introduce an expanded width-aware (PANDA) message passing, a new message passing paradigm where nodes with high centrality, a potential source of over-squashing, are selectively expanded in width to encapsulate the growing influx of signals from distant nodes. 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