Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2010.05788.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T16:10:53.501544Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-20T13:43:19.549203Z
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 ca3d2d52-e734-4328-b106-bb31e1e148af · inbound
VISION: Robust and Interpretable Code Vulnerability Detection Leveraging Counterfactual Augmentation cites this paper.
VISION: Robust and Interpretable Code Vulnerability Detection Leveraging Counterfactual Augmentation PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T16:10:53.501544Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d4e2264-5717-4bc3-a41a-0b8317de142d · inbound
UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models cites this paper.
UNR-Explainer: Counterfactual Explanations for Unsupervised Node Representation Learning Models PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T13:43:19.550637Z
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.