Database Paper Browser

Back to papers

OpenFGL: A Comprehensive Benchmark for Federated Graph Learning

Summary: OpenFGL: a unified benchmark for federated graph learning (Graph-FL and Subgraph-FL) with 42 datasets across 18 domains, 8 federation simulation strategies, 5 tasks, and a user-friendly API. Integrates 18 SOTA FGL methods for reproducible evaluation of accuracy, robustness, and efficiency, revealing practical limitations and enabling cross-disciplinary data-systems research. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13799
Venue
VLDB
Year
2025
Pagerank
4.1945683e-05
Overall Rank
10,545 | 26.65%
DOI
10.14778/3718057.3718061

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 11 of 11 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Previous Page 1 / 1 Next

Semantically Similar Papers