Commute-Time-Optimised Graphs for GNNs

AmazUtah_NLP at SemEval-2024 Task 9: A MultiChoice Question Answering System for Commonsense Defying Reasoning


View a PDF of the paper titled Commute-Time-Optimised Graphs for GNNs, by Igor Sterner and 2 other authors

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Abstract:We explore graph rewiring methods that optimise commute time. Recent graph rewiring approaches facilitate long-range interactions in sparse graphs, making such rewirings commute-time-optimal on average. However, when an expert prior exists on which node pairs should or should not interact, a superior rewiring would favour short commute times between these privileged node pairs. We construct two synthetic datasets with known priors reflecting realistic settings, and use these to motivate two bespoke rewiring methods that incorporate the known prior. We investigate the regimes where our rewiring improves test performance on the synthetic datasets. Finally, we perform a case study on a real-world citation graph to investigate the practical implications of our work.

Submission history

From: Shiye Su [view email]
[v1]
Tue, 9 Jul 2024 19:31:49 UTC (307 KB)
[v2]
Fri, 19 Jul 2024 02:36:08 UTC (291 KB)
[v3]
Thu, 5 Sep 2024 11:35:35 UTC (88 KB)



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