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A Comprehensive Benchmark on Spectral GNNs: The Impact on Efficiency, Memory, and Effectiveness
Summary: Systematic benchmark of spectral GNNs: categorizes 35 models into 27 spectral filters and implements them in a unified spectral-oriented framework that scales to million-node graphs. Cross-scale evaluations expose nontrivial efficiency/memory/effectiveness trade-offs and give practical deployment guidelines.
(summarized by gpt-5-mini on Feb 11 2026)
- Paper ID
- 7314
- Venue
- SIGMOD
- Year
- 2026
- Pagerank
- 4.1905499e-05
- Overall Rank
- 10,011 | 30.43%
- DOI
-
10.1145/3749156
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Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
Outgoing Citations (Sorted by Pagerank)
Showing 17 of 17 cited papers.
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| 271 |
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| 1,332 |
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| 7,568 |
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