Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2006.11468.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T13:19:11.815903Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T08:34:05.443936Z
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 76ac5007-9920-4d57-8231-f891eadbf68c · inbound
Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs cites this paper.
Flow Matters: Directional and Expressive GNNs for Heterophilic Graphs Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T13:19:11.815903Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6770850f-78ba-4899-9766-a42d651b31ea · inbound
TRAVELFRAUDBENCH: A Configurable Evaluation Framework for GNN Fraud Ring Detection in Travel Networks cites this paper.
TRAVELFRAUDBENCH: A Configurable Evaluation Framework for GNN Fraud Ring Detection in Travel Networks Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:51:02.443417Z
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.
Observation 7bc78a8c-9e48-4cd9-a15d-4419d9000865 · inbound
Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification cites this paper.
Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T08:34:05.445971Z
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.