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Paper Citation Record · LEDGER

Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2204.07321.

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

pith.paper-citation-record.v1
2204.07321 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:34:54.947250Z

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

9
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 7dad1ba9-8595-4ef8-a68d-cf204b57c04c · inbound

Mitigating Context Bias in Domain Adaptation for Object Detection using Mask Pooling cites this paper.

Mitigating Context Bias in Domain Adaptation for Object Detection using Mask Pooling Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T14:34:54.947250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:34:54.947250Z digest=sha256:523afe7b8b78b6fd96f38b7801793ba7aded946dba18834b790b68dad6b52bc7

Observation 446d0384-f6bd-4aa9-b5bb-d9d26233d2a2 · inbound

Context Pooling: Query-specific Graph Pooling for Generic Inductive Link Prediction in Knowledge Graphs cites this paper.

Context Pooling: Query-specific Graph Pooling for Generic Inductive Link Prediction in Knowledge Graphs Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T18:45:17.258114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:45:17.258114Z digest=sha256:30b39b66a761901d55e348acabbf6bb5b2aa877caeb9a0cdd82c883adc6c6e33

Observation 71a714c3-0b7e-4fff-97a5-f9e9691e36f0 · inbound

BioBlobs: Unsupervised Discovery of Functional Substructures for Protein Function Prediction cites this paper.

BioBlobs: Unsupervised Discovery of Functional Substructures for Protein Function Prediction Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:16:19.154506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T11:13:33.458480Z digest=sha256:c75c019817894d6844083232b7952d8e8af50f1807b5d4ef7a1b7a4facf35e60

Observation 7302a9a8-489a-4b71-bc70-82275a0c5625 · inbound

BioBlobs: Unsupervised Discovery of Functional Substructures for Protein Function Prediction cites this paper.

BioBlobs: Unsupervised Discovery of Functional Substructures for Protein Function Prediction Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-21T22:04:24.149704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T22:02:20.544141Z digest=sha256:7884608213889be28af5509eb71cc26b81fef3d074f67f1f044c176af8465059

Observation a9a7ad1c-6905-4ff9-b0d9-8da531e9edd2 · inbound

Learning from Historical Activations in Graph Neural Networks cites this paper.

Learning from Historical Activations in Graph Neural Networks Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T17:15:25.420915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T17:14:52.859473Z digest=sha256:f88b2c186629347715f9feddd1548a7e1742cd561b7bc1df2cf84e30e630c8af

Observation e3c838e7-95a9-4969-a124-ba7962f4efaf · inbound

GraphVec: Cross-Domain Graph Vectorization for Graph-Level Representation Learning cites this paper.

GraphVec: Cross-Domain Graph Vectorization for Graph-Level Representation Learning Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-16T07:27:31.617481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-16T07:25:35.324582Z digest=sha256:77b097223fa1acc017c09d81d834009e2074236ef4beb94f13bcd76eded58586

Observation a2df4b5b-9944-44ed-ab0f-911caf29c1e0 · inbound

Treatment Effect Estimation with Differentiated Networked Effect on Graph Data cites this paper.

Treatment Effect Estimation with Differentiated Networked Effect on Graph Data Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Reference 50

Resolution
verified exact
arxiv_id, observed 2026-06-30T15:04:46.217651Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T15:02:48.630964Z digest=sha256:a7b4ae444db803d8818f66f8869dcef6b2eba74eb61e785f3449161b4e26dde9

Observation 3bc0f0ff-db6c-4047-8d19-c5f795e3a217 · inbound

GMN4AD: Graph Matching Network for Alzheimer's Disease Diagnosis with Test-Time Domain Adaptation using Multi-centered Structure Magnetic Resonance Imaging cites this paper.

GMN4AD: Graph Matching Network for Alzheimer's Disease Diagnosis with Test-Time Domain Adaptation using Multi-centered Structure Magnetic Resonance Imaging Graph Pooling for Graph Neural Networks: Progress, Challenges, and Opportunities

Reference 65

Resolution
verified exact
arxiv_id, observed 2026-06-27T05:20:35.449296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T05:11:13.768584Z digest=sha256:cfe65f5ea5e85fdc1cac750c55117bc8c1c1d1a1c390f8d82a702265016f0824