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Paper Citation Record · LEDGER

GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2107.11889.

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

pith.paper-citation-record.v1
2107.11889 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 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T15:09:24.772602Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:37:37.632965Z

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 cf868807-7cba-4021-9aa5-6739e67fdcb3 · inbound

Subgraph Concept Networks: Concept Levels in Graph Classification cites this paper.

Subgraph Concept Networks: Concept Levels in Graph Classification GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:55:21.309650Z

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=pdf_text observed=2026-05-10T04:43:04.600687Z digest=sha256:9d65afddb56a61971b103a1d3df9dd38ef4408f93ae45ec1869b7f70e6f57b1a

Observation a6ccc499-0aa2-4be8-895d-436f39d9babb · inbound

Concept Graph Convolutions: Message Passing in the Concept Space cites this paper.

Concept Graph Convolutions: Message Passing in the Concept Space GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:19:46.898015Z

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=pdf_text observed=2026-05-10T00:16:59.207965Z digest=sha256:5d41c54c4f1c538015729354677040631156b6034f7cecf8f5f4ebe1267bca88

Observation 9a5c8175-0988-4ea8-9802-753d3bff99c6 · inbound

AIMing for Standardised Explainability Evaluation in GNNs: A Framework and Case Study on Graph Kernel Networks cites this paper.

AIMing for Standardised Explainability Evaluation in GNNs: A Framework and Case Study on Graph Kernel Networks GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-19T17:27:41.277914Z

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=2026-05-19T17:26:39.809292Z digest=sha256:601e3c60fcbc7a4f3c8f78089cdc21a1a7b5ae2c8eee9f512a2237ebdb62fad1

Observation 01f77b41-9fb4-486d-bf24-68b1da0361e7 · inbound

Learning Label-Efficient Interpretable Medical Image Diagnosis via Semi-supervised Hypergraph Concept Bottleneck Model cites this paper.

Learning Label-Efficient Interpretable Medical Image Diagnosis via Semi-supervised Hypergraph Concept Bottleneck Model GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-07-01T22:36:17.933242Z

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=pdf_text observed=2026-06-28T15:09:24.772602Z digest=sha256:f7bc7071349dd371a9f5ec2717ccc42a9fcb1eee9486f7b2199bc0ee4db8870c

Observation dc75a548-95fa-4069-bc81-02ec7d3d3f58 · inbound

In Defense of Information Leakage in Concept-based Models cites this paper.

In Defense of Information Leakage in Concept-based Models GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

Reference 219

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T04:37:37.634353Z

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=2026-06-27T13:43:55.952527Z digest=sha256:9329f9fd52dc2e0665eac36d786facb1bf195307eb860d6905df9ae5960c84e0