Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.18854.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T05:30:17.267430Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T05:57:22.394635Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 9da4ac16-60cd-471d-99b8-da9092a495b8 · inbound
Mixture of Experts for Node Classification What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
Reference 33
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3e236507-a41b-4af1-979d-22c5f6f05667 · inbound
Revisiting Graph Homophily Measures What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f5d6b55b-bb83-4487-acdb-ab2ac1aa2a3a · inbound
Spectrum-based Modality Representation Fusion Graph Convolutional Network for Multimodal Recommendation What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
Reference 46
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cdaa8346-e62b-4ce4-8413-6144bc9d0965 · inbound
Hierarchical Multi-Scale Graph Neural Networks: Scalable Heterophilous Learning with Oversmoothing and Oversquashing Mitigation What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks
Reference 9
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.