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Paper Citation Record · LEDGER

A Comprehensive Survey on Graph Neural Networks

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1901.00596.

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

pith.paper-citation-record.v1
1901.00596 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T13:19:11.499175Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T14:23:30.949812Z

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 f9188c6d-d194-49a3-98f0-80709ef466e8 · inbound

Fast Training of Sparse Graph Neural Networks on Dense Hardware cites this paper.

Fast Training of Sparse Graph Neural Networks on Dense Hardware A Comprehensive Survey on Graph Neural Networks

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-25T14:20:55.405127Z

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.

source=pdf_text observed=2026-05-25T14:19:33.774814Z digest=sha256:50bbea32dcbc734216f796af8cceaa3bab40ea3c79ef5463086bfd59e8903eb7

Observation 28e90306-be41-4b0c-a3cf-9d7293da4e0d · inbound

Tracking Temporal Evolution of Graphs using Non-Timestamped Data cites this paper.

Tracking Temporal Evolution of Graphs using Non-Timestamped Data A Comprehensive Survey on Graph Neural Networks

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:55:33.021138Z

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.

source=pdf_text observed=2026-05-25T08:53:00.590168Z digest=sha256:1b601061e42742ff1aa5bf2b6ef148593e9fce6a3c0cbf0dd2a55a32ecd23078

Observation 466ad478-53dc-4931-9879-5b59088d605c · inbound

Semi-Supervised Graph Embedding for Multi-Label Graph Node Classification cites this paper.

Semi-Supervised Graph Embedding for Multi-Label Graph Node Classification A Comprehensive Survey on Graph Neural Networks

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-24T22:20:00.897730Z

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.

source=pdf_text observed=2026-05-24T22:18:01.066556Z digest=sha256:0830a31c26c4cb5d8b19f6d407623d9ed4fa5cb778f8ebfc655685dbbe6eb016

Observation 6548666c-62f8-4064-b030-aac4ded33482 · inbound

A Graph Neural Network Approach for Scalable Wireless Power Control cites this paper.

A Graph Neural Network Approach for Scalable Wireless Power Control A Comprehensive Survey on Graph Neural Networks

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-24T18:56:19.276575Z

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.

source=pdf_text observed=2026-05-24T18:55:32.983673Z digest=sha256:7632f0f446cb9cb5657bcfa05b5ea48bd53f32e15247cb9f5d38731c17a4ecf1

Observation 8473402f-6e6f-4325-ba10-169ea955e3da · inbound

Spectral-based Graph Convolutional Network for Directed Graphs cites this paper.

Spectral-based Graph Convolutional Network for Directed Graphs A Comprehensive Survey on Graph Neural Networks

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-24T18:39:48.976713Z

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.

source=pdf_text observed=2026-05-24T18:37:53.827824Z digest=sha256:5d75d6f604a4efec155bd2edaa3ee9a348c4669441c54e9667d7127266555698

Observation bdebe5a9-343f-4b6c-a866-f98757f27a89 · inbound

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs cites this paper.

Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs A Comprehensive Survey on Graph Neural Networks

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-05T13:19:11.499175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T13:19:11.499175Z digest=sha256:48e4e41cdd39f801db79040ad1fa56d5789407d8693faf5bc2bc883020f158d0

Observation 8311012b-8643-4873-bb1f-4a40a8f42c70 · inbound

Graph Property Inference in Small Language Models: Effects of Representation and Reasoning Strategy cites this paper.

Graph Property Inference in Small Language Models: Effects of Representation and Reasoning Strategy A Comprehensive Survey on Graph Neural Networks

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T20:10:18.537039Z

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.

source=pdf_text observed=2026-05-15T20:07:07.522017Z digest=sha256:a0eb90fa01dceb682e43123d17de498b5895319cd9f9cfbe14711ae950b59440

Observation 0708c3b7-1c54-4389-bd5f-4ff1df34fded · inbound

Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks cites this paper.

Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks A Comprehensive Survey on Graph Neural Networks

Reference 175

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T16:46:06.745527Z

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.

source=arxiv_source observed=2026-05-09T15:09:03.417040Z digest=sha256:ffbff2f91d4a211caac45dca4b1e81c2955fe8c8fe0281f65b40b8b840b8d4de

Observation 2b80ce70-4aa9-43b0-ae9a-180990274a9f · inbound

Designing Active Tether-Net Systems for Space Debris Capture with Graph-Learning-Aided Mixed-Combinatorial Optimization cites this paper.

Designing Active Tether-Net Systems for Space Debris Capture with Graph-Learning-Aided Mixed-Combinatorial Optimization A Comprehensive Survey on Graph Neural Networks

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:23:30.951778Z

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.

source=pdf_text observed=2026-06-29T14:14:58.355961Z digest=sha256:322de7d8af6518df900daad09eec7a02f5dd864e6072fd023956c11103f148fa