Paper Citation Record · LEDGER

Graph Neural Networks: Methods, Applications, and Opportunities

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2108.10733.

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

pith.paper-citation-record.v1
2108.10733 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:02:32.134251Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T00:12:50.258066Z

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 a56bc2f7-6b36-468a-9ff2-cbbced4ec039 · inbound

xAI-Drop: Don't Use What You Cannot Explain cites this paper.

xAI-Drop: Don't Use What You Cannot Explain Graph Neural Networks: Methods, Applications, and Opportunities

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-23T23:03:34.637304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9821ddf3-bb31-45ba-a5b0-76c1bf4e325e · inbound

GraphTheft: Quantifying Privacy Risks in Graph Prompt Learning cites this paper.

GraphTheft: Quantifying Privacy Risks in Graph Prompt Learning Graph Neural Networks: Methods, Applications, and Opportunities

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-12T15:02:32.134251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35b5fb8c-c0bf-4565-9ba7-135b3aa5499a · inbound

Logical Grammar Induction via Graph Kolmogorov Complexity: A Neuro-Symbolic Framework for Self-Healing Clinical Data Integrity cites this paper.

Logical Grammar Induction via Graph Kolmogorov Complexity: A Neuro-Symbolic Framework for Self-Healing Clinical Data Integrity Graph Neural Networks: Methods, Applications, and Opportunities

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:32:39.462096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5feee503-0438-4b88-a2e2-36163835b97d · inbound

An Efficient and Scalable Graph Condensation with Structure-Preserving cites this paper.

An Efficient and Scalable Graph Condensation with Structure-Preserving Graph Neural Networks: Methods, Applications, and Opportunities

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:12:50.259461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.