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Paper Citation Record · LEDGER

A survey of dynamic graph neural networks

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2404.18211.

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

pith.paper-citation-record.v1
2404.18211 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:18:42.395182Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 24304d45-1834-4771-95e3-a1c05f01d0d6 · inbound

Future Link Prediction Without Memory or Aggregation cites this paper.

Future Link Prediction Without Memory or Aggregation A survey of dynamic graph neural networks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T14:18:42.395182Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:18:42.395182Z digest=sha256:ae00c6871f0d98053b449a26d2ab12d9a46ec4c86d488c51fc2d790aaf3a88b7

Observation 2ad9140d-2a5c-45fc-9943-8eb1ef4e3df6 · inbound

TIDFormer: Exploiting Temporal and Interactive Dynamics Makes A Great Dynamic Graph Transformer cites this paper.

TIDFormer: Exploiting Temporal and Interactive Dynamics Makes A Great Dynamic Graph Transformer A survey of dynamic graph neural networks

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T12:10:34.813721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:10:34.813721Z digest=sha256:d4ff9c9040a9bf0b9811f55cbb16fce62d1c8b2dfc1ff3af910e6f615d29a2bb

Observation d2e9d9bf-7497-43f0-82ae-4d5e53a49b28 · inbound

Mechanical Field Networks: Structured Neural Dynamics for Multivariate Systems cites this paper.

Mechanical Field Networks: Structured Neural Dynamics for Multivariate Systems A survey of dynamic graph neural networks

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-06-27T17:21:06.740355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T17:17:22.959696Z digest=sha256:105f54767b766476c36829fe5d6e12ab83400a0eab6a5bea1611a578272dcd7b