Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2204.08570.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T18:12:37.062427Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T03:56:34.609000Z
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 0413c05e-fad5-4db4-af68-0aa719a3e084 · inbound
Explaining the Explainers in Graph Neural Networks: a Comparative Study cites this paper.
Explaining the Explainers in Graph Neural Networks: a Comparative Study A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T11:04:22.198473Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e58bed36-4fec-47df-baed-8ba26fce2ac1 · inbound
A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives cites this paper.
A Systematic Survey of Model Extraction Attacks and Defenses: State-of-the-Art and Perspectives A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:12:37.062427Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6528a238-da28-48ca-874f-4891d9a0d4e4 · inbound
Impact of Graph Structure on Membership-Inference Risk for Graph Neural Networks cites this paper.
Impact of Graph Structure on Membership-Inference Risk for Graph Neural Networks A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T08:30:20.212975Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aebd55b6-5080-47b3-92ec-51f08b0409c7 · inbound
Bayesian Membership Privacy for Graph Neural Networks cites this paper.
Bayesian Membership Privacy for Graph Neural Networks A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Reference 33
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T03:56:34.610626Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.