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Paper Citation Record · LEDGER

R-GCN: The R Could Stand for Random

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2203.02424.

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

pith.paper-citation-record.v1
2203.02424 v2

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T13:01:46.831444Z

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

5
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 75ab331c-c6b3-4659-a72f-71005d5ee7ae · inbound

Half a Link can Be Enough to Predict a Whole Link: Understanding Generalization in Knowledge Graph Foundation Models cites this paper.

Half a Link can Be Enough to Predict a Whole Link: Understanding Generalization in Knowledge Graph Foundation Models R-GCN: The R Could Stand for Random

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-06-27T02:00:22.137564Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T01:51:18.585359Z digest=sha256:d3a70a652d965f3d1bd463c42965e5f777c428c26006d07d4f9d6a5f66a429fc

Observation 993dc6e0-6f9b-4850-82d7-5bb227eb7ae1 · inbound

Sequential Learner Modeling Using Multi-Relational Graph Convolutional Networks cites this paper.

Sequential Learner Modeling Using Multi-Relational Graph Convolutional Networks R-GCN: The R Could Stand for Random

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-01T13:01:46.831444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T13:01:46.831444Z digest=sha256:4fef000171e20fa57b732013a77f7c89a77fa0e690dc86f4f6fec0c528157d56