Paper Citation Record · LEDGER

Revisiting Graph Homophily Measures

As of 19 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2412.09663.

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

pith.paper-citation-record.v1
2412.09663 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T17:15:25.690922Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact0
verified fuzzy23
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e8bd5c10-1a9f-420d-a3f5-43ea374fe0ef · outbound

This paper cites The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges.

Revisiting Graph Homophily Measures The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T17:15:25.552790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d7336f2-a5c0-49bd-8cbc-21116ed32997 · outbound

This paper cites Be- yond homophily in graph neural networks: Current limitations and effective designs.

Revisiting Graph Homophily Measures Be- yond homophily in graph neural networks: Current limitations and effective designs

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.159181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4c482dc4-52c6-4532-a109-2a4aaa836153 · outbound

This paper cites Is homophily a necessity for graph neural networks? In International Conference on Learning Representations, 2022.

Revisiting Graph Homophily Measures Is homophily a necessity for graph neural networks? In International Conference on Learning Representations, 2022

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.141643Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 943284cf-15e3-4d70-a189-5fd2db3337b6 · outbound

This paper cites Revisiting heterophily for graph neural networks.

Revisiting Graph Homophily Measures Revisiting heterophily for graph neural networks

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.126387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 267cc8a6-1f42-48d0-9343-01cfcc61edb0 · outbound

This paper cites A critical look at the evaluation of GNNs under heterophily: Are we re- ally making progress? 2023.

Revisiting Graph Homophily Measures A critical look at the evaluation of GNNs under heterophily: Are we re- ally making progress? 2023

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.111355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d43fd6da-c879-4a67-b705-f39176f77e70 · outbound

This paper cites Characteriz- ing graph datasets for node classification: Homophily-heterophily dichotomy and beyond.

Revisiting Graph Homophily Measures Characteriz- ing graph datasets for node classification: Homophily-heterophily dichotomy and beyond

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.096095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 41e231cc-dea4-43d5-b718-7d2d6ea56dc9 · outbound

This paper cites Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing.

Revisiting Graph Homophily Measures Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.080973Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9170c2f1-c8fb-432f-a5a7-f524c323c32d · outbound

This paper cites Geom-GCN: Geo- metric graph convolutional networks.

Revisiting Graph Homophily Measures Geom-GCN: Geo- metric graph convolutional networks

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.065390Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d7f9f38e-981a-4a28-9c5f-9e86fc0cdf16 · outbound

This paper cites Large scale learning on non-homophilous graphs: New benchmarks and strong simple methods.

Revisiting Graph Homophily Measures Large scale learning on non-homophilous graphs: New benchmarks and strong simple methods

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.050065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 228e3a89-444e-44d5-a58d-2bb7b693c83b · outbound

This paper cites an unresolved cited work.

Revisiting Graph Homophily Measures Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-11T17:15:26.033459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3e236507-a41b-4af1-979d-22c5f6f05667 · outbound

This paper cites What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks.

Revisiting Graph Homophily Measures What Is Missing In Homophily? Disentangling Graph Homophily For Graph Neural Networks

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T17:15:25.609744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 687af56d-fae1-4404-88d7-6c4add82cc0a · outbound

This paper cites When do graph neural networks help with node classification? In- vestigating the homophily principle on node distinguishability.

Revisiting Graph Homophily Measures When do graph neural networks help with node classification? In- vestigating the homophily principle on node distinguishability

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.016537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ffd30179-5902-4fc2-b935-3709ab68fb17 · outbound

This paper cites Graph database repository for graph based pattern recognition and machine learning.

Revisiting Graph Homophily Measures Graph database repository for graph based pattern recognition and machine learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:26.000007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 10ed2b20-b76d-41c7-b4e3-4ede081f3517 · outbound

This paper cites Good classification measures and how to find them.

Revisiting Graph Homophily Measures Good classification measures and how to find them

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.981611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 60bd8b94-3245-46a1-814a-476a250e8b82 · outbound

This paper cites Higher-order homophily on simplicial complexes.

Revisiting Graph Homophily Measures Higher-order homophily on simplicial complexes

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.965469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4e780484-663f-4db3-a062-08b797a6c28d · outbound

This paper cites On the inadequacy of nominal assortativity for assessing homophily in networks.

Revisiting Graph Homophily Measures On the inadequacy of nominal assortativity for assessing homophily in networks

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.949073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 420498bd-dff3-440e-bffe-b9903b698662 · outbound

This paper cites Lee Giles, Kurt D.

Revisiting Graph Homophily Measures Lee Giles, Kurt D

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.931865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8ae9e7b6-bfe3-4334-b2d7-be0571198dd3 · outbound

This paper cites Automating the construction of internet portals with machine learning.

Revisiting Graph Homophily Measures Automating the construction of internet portals with machine learning

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.915634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ed3eb9e4-82bb-414d-8d98-1d032ec6d35c · outbound

This paper cites Collective classification in network data.

Revisiting Graph Homophily Measures Collective classification in network data

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T17:15:25.649572Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03ea3ce7-8390-4352-8f2a-83e77d04f31c · outbound

This paper cites Query-driven active surveying for collective classification.

Revisiting Graph Homophily Measures Query-driven active surveying for collective classification

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.888612Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 340800f5-c8eb-4e39-993b-dc39b75c0661 · outbound

This paper cites Revisiting semi-supervised learning with graph embeddings.

Revisiting Graph Homophily Measures Revisiting semi-supervised learning with graph embeddings

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.872754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 24280517-b5c9-409d-a3f1-4550e376389e · outbound

This paper cites Pitfalls of graph neural network evaluation.

Revisiting Graph Homophily Measures Pitfalls of graph neural network evaluation

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.855828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8bc710eb-af72-473a-9242-cf1cdede42cb · outbound

This paper cites Characteristic functions on graphs: Birds of a feather, from statistical descriptors to parametric models.

Revisiting Graph Homophily Measures Characteristic functions on graphs: Birds of a feather, from statistical descriptors to parametric models

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.838309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b6c73b45-75d9-4661-a8b7-c1c819ef85c2 · outbound

This paper cites Multi-scale attributed node embedding.

Revisiting Graph Homophily Measures Multi-scale attributed node embedding

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.821220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a456f828-2276-4bcc-9b6a-cdf6f9d23aa9 · outbound

This paper cites Social influence analysis in large-scale networks.

Revisiting Graph Homophily Measures Social influence analysis in large-scale networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.804889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dabd8905-43d4-4dae-8560-2a25a16cd51b · outbound

This paper cites GraphSAINT: Graph sampling based inductive learning method.

Revisiting Graph Homophily Measures GraphSAINT: Graph sampling based inductive learning method

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.788231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 8243c506-5015-4a01-bece-ad59ca0551e4 · outbound

This paper cites 1 4 1 4 1 4 1 4 # , L 2 =.

Revisiting Graph Homophily Measures 1 4 1 4 1 4 1 4 # , L 2 =

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T17:15:25.768945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.