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Paper Citation Record · LEDGER

GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.11264.

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

pith.paper-citation-record.v1
2306.11264 v1

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 2026-08-20T06:33:59.587034+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:16:13.958671Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T17:09:31.286202Z

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 f53f653a-fd54-4d8b-96ca-3b10366bbb9b · inbound

MLDGG: Meta-Learning for Domain Generalization on Graphs cites this paper.

MLDGG: Meta-Learning for Domain Generalization on Graphs GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-12T17:09:31.294963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-12T17:09:30.912742Z digest=sha256:3aab3e93dd3a3075dcbf9c1cecb7845c92f9ef0e76cb28a04ed8a6a92137e55c

Observation 637e76b2-dcbf-42fe-9589-17022802b485 · inbound

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs cites this paper.

FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks

Reference 93

Resolution
unresolved
no resolver link, observed 2026-08-16T05:16:13.958671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T05:16:13.958671Z digest=sha256:86377e6dfcfe237fc995587e88b9d3fc0b1aab377dc98c054c67d11a9bdad369