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Paper Citation Record · LEDGER

Graph Generative Model for Benchmarking Graph Neural Networks

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2207.04396.

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

pith.paper-citation-record.v1
2207.04396 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T11:40:55.616086Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T16:00:39.836450Z

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 9c22eff8-d3ad-42c6-9849-21c60485a048 · inbound

Data Mining in Transportation Networks with Graph Neural Networks: A Review and Outlook cites this paper.

Data Mining in Transportation Networks with Graph Neural Networks: A Review and Outlook Graph Generative Model for Benchmarking Graph Neural Networks

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T11:40:55.616086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T11:40:55.616086Z digest=sha256:67926e7eec2410acde6c26cee3450a106f3b4ec0bc2938bb9cd9356430bfa0d8

Observation d143469e-9939-45cd-a7c8-cb0106342c88 · inbound

SynCircuit: Automated Generation of New Synthetic RTL Circuits Can Enable Big Data in Circuits cites this paper.

SynCircuit: Automated Generation of New Synthetic RTL Circuits Can Enable Big Data in Circuits Graph Generative Model for Benchmarking Graph Neural Networks

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-05T16:00:39.845347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-05T16:00:39.525327Z digest=sha256:18600e72de55ed430c7a9dbe0cb361a184b6f9a1aa9b7659ac02bda829ca247e