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Paper Citation Record · LEDGER

Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:1801.07606.

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

pith.paper-citation-record.v1
1801.07606 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T00:33:17.975036Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-04T13:39:51.022374Z

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 d6041861-4fef-4893-b82d-12a7d2281603 · 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 Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

Reference 156

Resolution
verified exact
arxiv_id, observed 2026-05-11T16:46:06.617047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-09T15:09:03.417040Z digest=sha256:1427043dcfeb983ed1ca4c0f29615676a8601d3d920fceeccddc5dcc8bb2b32e

Observation 6f9fc35d-5c00-4e7e-978e-16d223947fb5 · inbound

Six Open Questions in Machine-Learned Interatomic Potential Foundation Models cites this paper.

Six Open Questions in Machine-Learned Interatomic Potential Foundation Models Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

Reference 117

Resolution
verified exact
local_arxiv, observed 2026-07-02T19:37:19.132831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-27T21:27:50.941166Z digest=sha256:f6843fd68dbeab1e4ee27eacdbea5488cce23796e11019c31373db81bacf45ce

Observation 5f5b9be4-251f-4784-83c0-9508c1aa0abe · inbound

SubdivAR: Autoregressive Next-Scale Prediction for Neural Mesh Subdivision cites this paper.

SubdivAR: Autoregressive Next-Scale Prediction for Neural Mesh Subdivision Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

Reference 18

Resolution
metadata mismatch
local_arxiv, observed 2026-07-04T13:39:51.023661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T05:01:44.347859Z digest=sha256:09e1366c72749d19d6589ec50ed3cf0d6fa9e4a8d4af3d398084c26cd14f753a

Observation fa64f255-c770-4a47-805b-7cfd3ff1f80d · inbound

SubdivAR: Autoregressive Next-Scale Prediction for Neural Mesh Subdivision cites this paper.

SubdivAR: Autoregressive Next-Scale Prediction for Neural Mesh Subdivision Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-02T10:07:04.183165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:07:04.183165Z digest=sha256:7b488d7ece6a64125dea8587fe0006c9214e7b33ed6eba851c8b4b58558c9b4c

Observation b5f568c6-942a-46b7-b9a3-389a18881094 · inbound

Perspectives on Tsallis Statistics for Artificial Intelligence cites this paper.

Perspectives on Tsallis Statistics for Artificial Intelligence Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T00:33:17.975036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T00:33:17.975036Z digest=sha256:83e981d9e73ef29a9928444a2866ec1830585843cd2ed1b8b6e2e265fd8f1526