Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2401.09769.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T15:43:12.531700Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T08:39:42.421001Z
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 0e188a22-b3cc-4ab2-a292-eedb32a023cd · inbound
Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening cites this paper.
Partition-wise Graph Filtering: A Unified Perspective Through the Lens of Graph Coarsening A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:43:12.531700Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation df6ad198-2fe1-4360-a5a0-6017d18448f0 · inbound
Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks cites this paper.
Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T16:00:51.569270Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4225f3ea-168a-4d4f-b6d6-0dd2b9593eec · inbound
FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanism cites this paper.
FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanism A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T08:39:42.422650Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation c6ec29dc-c49e-4c19-a0c9-fa19e6aeb255 · inbound
FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanism cites this paper.
FeLoG: Scalable and Efficient Distributed Graph Embedding with Feedback Loop Mechanism A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T21:57:25.486735Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.
Observation 40037a1a-69f8-4399-b7a1-ee854666abce · inbound
Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement cites this paper.
Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T06:31:21.258312Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.