Scalable GNN Explanations with Distributed Shapley Values
Summary: DistShap distributes Shapley-based GNN explanations across GPUs, parallelizing subgraph sampling, inference, and least-squares attribution. It achieves strong accuracy while scaling explanations to million-edge GNNs on 128 GPUs. (summarized by gpt-5.6-luna on Jul 09 2026)
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Authors
- 1. Selahattin Akkas (Indiana University)
- 2. Aditya Devarakonda (Wake Forest University)
- 3. Ariful Azad (Texas A&M University)
BibTeX Citation
@article{akkas_vldb26,
title = {{Scalable GNN Explanations with Distributed Shapley Values}},
author = {Akkas, Selahattin and Devarakonda, Aditya and Azad, Ariful},
journal = {PVLDB},
series = {{VLDB} '26},
volume = {19},
number = {8},
pages = {1731--1739},
doi = {10.14778/3811243.3811247},
url = {https://doi.org/10.14778/3811243.3811247},
year = {2026}
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