Paper Citation Record · LEDGER

DeepGCNs: Can GCNs Go as Deep as CNNs?

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1904.03751.

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

pith.paper-citation-record.v1
1904.03751 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 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:51:16.201976Z

measured 1 of 1 external citation measurements

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

Source: pith, 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

107
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 83709793-6896-4cff-9d3b-1d0a40a0e15c · inbound

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks cites this paper.

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks DeepGCNs: Can GCNs Go as Deep as CNNs?

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-11T10:51:16.201976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3091f10-9246-4af9-bea5-28cc717fa7e2 · inbound

A Probabilistic Model for Node Classification in Directed Graphs cites this paper.

A Probabilistic Model for Node Classification in Directed Graphs DeepGCNs: Can GCNs Go as Deep as CNNs?

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T22:30:02.059327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 792144a5-07d8-4188-a73e-1e5e2a44cdf8 · inbound

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement cites this paper.

Generating Highly Structured Test Inputs Leveraging Constraint-Guided Graph Refinement DeepGCNs: Can GCNs Go as Deep as CNNs?

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T12:59:46.985294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 64791012-9a76-46e6-a786-4c9e73e8d592 · inbound

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning cites this paper.

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning DeepGCNs: Can GCNs Go as Deep as CNNs?

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-07-31T18:35:53.483324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.