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Paper Citation Record · LEDGER

OpenFGL: A Comprehensive Benchmark for Federated Graph Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2408.16288.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2408.16288 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T00:38:04.381449Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T23:57:29.084640Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c5baa592-289e-4582-8859-7aa03b6ada9c · inbound

UMEDA: Unified Multi-modal Efficient Data Fusion for Privacy-Preserving Graph Federated Learning via Spectral-Gated Attention and Diffusion-Based Operator Alignment cites this paper.

UMEDA: Unified Multi-modal Efficient Data Fusion for Privacy-Preserving Graph Federated Learning via Spectral-Gated Attention and Diffusion-Based Operator Alignment OpenFGL: A Comprehensive Benchmark for Federated Graph Learning

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-05-12T02:51:18.042880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-12T02:47:38.972072Z digest=sha256:5af87e4f7696c6643d134407e1821efa99570357df1c6e4eee50bfdc50963edf

Observation 2efe516c-9dd2-47a9-b460-33871a601197 · inbound

PRISM: Topology-Aware Cross-Modal Imputation for Modality-Deficient Federated Graph Learning cites this paper.

PRISM: Topology-Aware Cross-Modal Imputation for Modality-Deficient Federated Graph Learning OpenFGL: A Comprehensive Benchmark for Federated Graph Learning

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-02T23:57:29.086037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T17:34:54.567394Z digest=sha256:6a07413de2c7c7ea8ff88d3c8d67a1819aa33bc5804c8e098177102334b9a199

Observation 6d9a48ef-4f43-4243-b11e-97a1a19ce373 · inbound

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning cites this paper.

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning OpenFGL: A Comprehensive Benchmark for Federated Graph Learning

Reference 238

Resolution
verified exact
arxiv_id, observed 2026-07-01T09:45:40.632182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-01T06:10:26.634933Z digest=sha256:4a5b0f368c16c667da5e3f1b35f2a3ffc98a2655199bcbf47a792ba627e42e99

Observation 1367540f-f217-469c-a4bf-248c97f7e023 · inbound

FedOGL: Combating Catastrophic Forgetting in Federated Open-World Multimodal Graph Learning cites this paper.

FedOGL: Combating Catastrophic Forgetting in Federated Open-World Multimodal Graph Learning OpenFGL: A Comprehensive Benchmark for Federated Graph Learning

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-01T03:46:15.967524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T03:46:15.967524Z digest=sha256:7e8abbbc6b8ba37132e760540a816f3c54c3b1159bc49904a1da55e815364541

Observation 3e3a8c2f-1805-4dae-b289-d4b40936e987 · inbound

Towards Effective Federated Multimodal Graph Learning via Navigating Multifaceted Heterogeneity cites this paper.

Towards Effective Federated Multimodal Graph Learning via Navigating Multifaceted Heterogeneity OpenFGL: A Comprehensive Benchmark for Federated Graph Learning

Reference 81

Resolution
unresolved
no resolver link, observed 2026-08-05T00:38:04.381449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T00:38:04.381449Z digest=sha256:a409b35d461bdccde289029670e5bef62c4828c3586a06be9ec6e01ad17cf1e0