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Paper Citation Record · LEDGER

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph

As of 18 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2505.12411.

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

pith.paper-citation-record.v1
2505.12411 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:42:59.298147Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

34 of 34 outbound references displayed

  • verified exact0
  • verified fuzzy12
  • unresolved22
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bd04d86b-e891-4348-99af-50ce3dee4da9 · outbound

This paper cites Braingnn: Interpretable brain graph neural network for fmri analysis.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Braingnn: Interpretable brain graph neural network for fmri analysis

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1d1ab6d6-47ca-4222-8a5e-71eeed891478 · outbound

This paper cites Learning effective road network representation with hierarchical graph neural networks.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Learning effective road network representation with hierarchical graph neural networks

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 4967be75-db9b-4778-9cdb-eaae54fd84ab · outbound

This paper cites Fast and flexible protein design using deep graph neural networks.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Fast and flexible protein design using deep graph neural networks

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 42c40794-674d-4071-9d9e-27ff8c841f14 · outbound

This paper cites Birds of a feather: Homophily in social networks.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Birds of a feather: Homophily in social networks

Reference 4

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no resolver link, observed 2026-08-15T20:42:59.206221Z

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Unavailable: canonical work link unavailable.

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Observation 6037b694-1ba9-43f9-83f3-06014697ff7c · outbound

This paper cites Graph Neural Networks for Graphs with Heterophily: A Survey.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Graph Neural Networks for Graphs with Heterophily: A Survey

Reference 5

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Unavailable: canonical work link unavailable.

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Observation 32c8fd94-e300-48ff-b0f6-80b91c0f3f72 · outbound

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

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Be- yond homophily in graph neural networks: Current limitations and effective designs

Reference 6

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation a313716b-159a-4623-9d47-1c8eeb2fe660 · outbound

This paper cites Two sides of the same coin: Heterophily and oversmoothing in graph convolutional neural networks.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Two sides of the same coin: Heterophily and oversmoothing in graph convolutional neural networks

Reference 7

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation c0b6e94a-5c98-4c24-80c0-b41d8a47bda9 · outbound

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

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation e5ac6e05-cc9f-49d4-8edb-3da384d40b0d · outbound

This paper cites Adaptive Universal Generalized PageRank Graph Neural Network.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Adaptive Universal Generalized PageRank Graph Neural Network

Reference 9

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Observation cd30af4d-6b25-4d77-819f-db5751e31479 · outbound

This paper cites Exploiting neighbor effect: Conv-agnostic gnn framework for graphs with heterophily.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Exploiting neighbor effect: Conv-agnostic gnn framework for graphs with heterophily

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3e9944bf-2e1d-4eff-b106-4d76305c13b3 · outbound

This paper cites Graph Rewiring in GNNs to Mitigate Over-Squashing and Over-Smoothing: A Survey.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Graph Rewiring in GNNs to Mitigate Over-Squashing and Over-Smoothing: A Survey

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 31c8d260-80f0-462d-90cb-46789b7f87ab · outbound

This paper cites Deeper insights into graph convolutional networks for semi-supervised learning.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Deeper insights into graph convolutional networks for semi-supervised learning

Reference 12

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Observation 699420a5-266e-49e7-8df1-e0f6ab42307a · outbound

This paper cites On the Bottleneck of Graph Neural Networks and its Practical Implications.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph On the Bottleneck of Graph Neural Networks and its Practical Implications

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d0ab0083-988f-4cb3-98e0-f514d68e4d03 · outbound

This paper cites Supervised and semi-supervised diffusion maps with label-driven diffusion.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Supervised and semi-supervised diffusion maps with label-driven diffusion

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 9b0cf7d7-e261-4e37-addf-0563a507f085 · outbound

This paper cites Diffusion maps.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Diffusion maps

Reference 15

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Unavailable: canonical work link unavailable.

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Observation dedfadda-f5c7-41c2-a76c-1a743b1f22a3 · outbound

This paper cites Geom-GCN: Geometric Graph Convolutional Networks.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Geom-GCN: Geometric Graph Convolutional Networks

Reference 16

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no resolver link, observed 2026-08-15T20:42:59.242403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 903f9696-7bf5-47bb-a881-9a7dcb0971ce · outbound

This paper cites New Benchmarks for Learning on Non-Homophilous Graphs.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph New Benchmarks for Learning on Non-Homophilous Graphs

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d51f4abe-d34b-4711-b702-b4c7e80bf061 · outbound

This paper cites Neighborhood homophily-based graph convolutional network.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Neighborhood homophily-based graph convolutional network

Reference 18

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 99487f57-e0be-46b1-8974-2d759ebb85df · outbound

This paper cites Graph neural networks with heterophily.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Graph neural networks with heterophily

Reference 19

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 65bb250e-8478-4773-a654-509649c9d573 · outbound

This paper cites Powerful graph convolutional networks with adaptive propagation mechanism for homophily and heterophily.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Powerful graph convolutional networks with adaptive propagation mechanism for homophily and heterophily

Reference 20

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7c8bf886-6c64-440e-a99c-09965c6fdc39 · outbound

This paper cites Revisiting over-smoothing and over-squashing using ollivier-ricci curvature.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Revisiting over-smoothing and over-squashing using ollivier-ricci curvature

Reference 21

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ef427f0e-cb06-443b-9fd0-5267563b69f2 · outbound

This paper cites Understanding over-squashing and bottlenecks on graphs via curvature.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Understanding over-squashing and bottlenecks on graphs via curvature

Reference 22

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Observation 280dab2a-fa46-4a3c-b47f-dc3cdc697cba · outbound

This paper cites Make heterophilic graphs better fit gnn: A graph rewiring approach.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Make heterophilic graphs better fit gnn: A graph rewiring approach

Reference 23

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 36e59c2c-5b19-49dd-81dc-24f8a74d0b14 · outbound

This paper cites Opengsl: A comprehensive benchmark for graph structure learning.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Opengsl: A comprehensive benchmark for graph structure learning

Reference 24

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 36fda3bb-a6d3-42ff-a5bf-da854a98f6e5 · outbound

This paper cites How to learn a graph from smooth signals.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph How to learn a graph from smooth signals

Reference 25

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Unavailable: canonical work link unavailable.

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Observation 936f372c-94cd-4fe7-be79-a0274ef1e21e · outbound

This paper cites Measuring and relieving the over-smoothing problem for graph neural networks from the topological view.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Measuring and relieving the over-smoothing problem for graph neural networks from the topological view

Reference 26

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 739903d7-7d6e-48eb-8f0d-4aeeef575e55 · outbound

This paper cites A fast and high quality multilevel scheme for partitioning irregular graphs.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph A fast and high quality multilevel scheme for partitioning irregular graphs

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 922472c3-e29a-49e2-87b9-3918d2925a08 · outbound

This paper cites FoSR: First-order spectral rewiring for addressing oversquashing in GNNs.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph FoSR: First-order spectral rewiring for addressing oversquashing in GNNs

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f42643d0-e170-48d3-b29b-3ff6c05f8558 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Semi-Supervised Classification with Graph Convolutional Networks

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b4248f81-33fc-4be0-9563-bb27542e4d1b · outbound

This paper cites How Attentive are Graph Attention Networks?.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph How Attentive are Graph Attention Networks?

Reference 30

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Unavailable: canonical work link unavailable.

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Observation 62623255-dc0c-4bd3-b032-6c32aef07422 · outbound

This paper cites Predict then Propagate: Graph Neural Networks meet Personalized PageRank.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Predict then Propagate: Graph Neural Networks meet Personalized PageRank

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 18771e54-1453-44cf-8bfc-82060b0763cb · outbound

This paper cites Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 3b602006-d338-45d4-9031-dfe509018104 · outbound

This paper cites Less is More: on the Over-Globalizing Problem in Graph Transformers.

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph Less is More: on the Over-Globalizing Problem in Graph Transformers

Reference 33

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Unavailable: canonical work link unavailable.

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Observation f54086ed-e992-4750-821b-02e669d35b40 · outbound

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

It Takes a Graph to Know a Graph: Rewiring for Homophily with a Reference Graph A critical look at the evaluation of GNNs under heterophily: Are we really making progress?

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.