Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery | Paper Citation Record

Observation a4ad2cc1-ba27-4769-8d68-ae8e39454283 · outbound

This paper cites A comprehensive survey on graph neural networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery A comprehensive survey on graph neural networks,

Reference 1

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Observation e4177392-18f1-49f0-ac9f-5d483e0181b1 · outbound

This paper cites Geometric deep learning: Going beyond Euclidean data,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Geometric deep learning: Going beyond Euclidean data,

Reference 2

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Observation e6ae38be-e396-45f6-877d-4a12af22be93 · outbound

This paper cites A survey of convolutional neural networks: Analysis, applications, and prospects,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery A survey of convolutional neural networks: Analysis, applications, and prospects,

Reference 3

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Observation 27397574-6cb7-470c-9388-8e47c66414b0 · outbound

This paper cites Exploiting the structure of two graphs with graph neural networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Exploiting the structure of two graphs with graph neural networks,

Reference 4

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Observation 08000e2c-74eb-40da-bc63-fd39908559a9 · outbound

This paper cites Beyond homophily in graph neural networks: Current limitations and effective designs,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Beyond homophily in graph neural networks: Current limitations and effective designs,

Reference 5

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Observation af5aab7c-8017-4850-bd25-239d91aedbe1 · outbound

This paper cites Is homophily a necessity for graph neural networks?.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Is homophily a necessity for graph neural networks?

Reference 6

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Observation e6249492-d8c3-4cc7-9384-16803e0d8b0d · outbound

This paper cites Geom- GCN: Geometric graph convolutional networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Geom- GCN: Geometric graph convolutional networks,

Reference 7

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Observation 6a7f8a93-cf54-4759-99f8-c009b8b2167c · outbound

This paper cites Revisiting graph neural networks: Graph filtering perspective,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Revisiting graph neural networks: Graph filtering perspective,

Reference 8

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Observation 9f268daf-72d9-4a66-a35c-b88667005128 · outbound

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

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery MixHop: Higher-order graph convolutional architectures via sparsified neighborhood mixing,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:44.948316Z

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Observation c03477aa-2dbe-4f32-9b79-432cf3e7dd7a · outbound

This paper cites Beyond low-frequency infor- mation in graph convolutional networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Beyond low-frequency infor- mation in graph convolutional networks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:44.549981Z

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Observation 01e5683a-934c-40e5-9ee2-ffb58f0d9c91 · outbound

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

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Large scale learning on non-homophilous graphs: new benchmarks and strong simple methods,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:44.232673Z

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Observation dbb6e2db-6d9e-4191-8879-82de1383f338 · outbound

This paper cites Adaptive universal generalized PageRank graph neural network,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Adaptive universal generalized PageRank graph neural network,

Reference 12

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Observation 7653e451-7a5b-4d35-b933-941ea5d1dbf4 · outbound

This paper cites Simple and deep graph convolutional networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Simple and deep graph convolutional networks,

Reference 13

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Observation f7dc2250-f2e6-4a86-a58c-89648a70457e · outbound

This paper cites Diffusion improves graph learning,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Diffusion improves graph learning,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:43.665865Z

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Observation feb6ada5-08af-4a76-8b7a-391d4dc7b086 · outbound

This paper cites Predict then propagate: Graph neural networks meet personalized PageRank,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Predict then propagate: Graph neural networks meet personalized PageRank,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:43.518595Z

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Observation e123a4e1-1764-4666-811e-031b808db66d · outbound

This paper cites Graph neural networks: Architec- tures, stability, and transferability,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Graph neural networks: Architec- tures, stability, and transferability,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:43.343576Z

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Observation c2b63a42-4e31-4cbf-b84c-a7020f0e68b6 · outbound

This paper cites Stability properties of graph neural networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Stability properties of graph neural networks,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:43.164579Z

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Observation 98b034bd-5e36-459a-a128-4b4520738aed · outbound

This paper cites an unresolved cited work.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Unresolved cited work

Reference 18

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Observation 5a45c4d4-30fc-475a-acea-91f82c86002d · outbound

This paper cites Breaking the limit of graph neural networks by improving the assortativity of graphs with local mixing patterns,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Breaking the limit of graph neural networks by improving the assortativity of graphs with local mixing patterns,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:42.783759Z

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Observation a14838e7-84b4-43ff-a767-d42f19e45124 · outbound

This paper cites Beyond homophily and homogeneity assumption: Relation-based frequency adaptive graph neural networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Beyond homophily and homogeneity assumption: Relation-based frequency adaptive graph neural networks,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:42.587721Z

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Observation 243234bb-cbd7-4914-bef6-c66c67078291 · outbound

This paper cites Structure-guided input graph for GNNs facing heterophily,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Structure-guided input graph for GNNs facing heterophily,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:42.406106Z

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Observation f69da0ef-80c5-4e90-ac4d-d06ca147ebda · outbound

This paper cites Role-oriented graph auto-encoder guided by structural information,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Role-oriented graph auto-encoder guided by structural information,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:42.215963Z

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Observation 633cdb4a-820d-433b-8fab-f7db5525a42d · outbound

This paper cites Recovering missing node features with local structure-based embeddings,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Recovering missing node features with local structure-based embeddings,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:42.007331Z

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Observation 530285f0-ab48-4820-9b3e-e0871949cc3f · outbound

This paper cites Newman,Networks.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Newman,Networks

Reference 24

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Observation 025a2379-6163-4148-a846-4ad1cf0432e9 · outbound

This paper cites Homophily- enhanced self-supervision for graph structure learning: Insights and directions,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Homophily- enhanced self-supervision for graph structure learning: Insights and directions,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:41.863013Z

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Observation 2b36073e-fd58-49ed-adbc-280b108fbd61 · outbound

This paper cites Graph structure learning for robust graph neural networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Graph structure learning for robust graph neural networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:41.661856Z

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Observation 2de7e4e0-2c12-4317-8a46-26e8a26e8e33 · outbound

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

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Measuring and relieving the over-smoothing problem for graph neural networks from the topological view,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:41.432670Z

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Observation ad5fb8e8-cb4f-4660-9daf-2d4547f7f050 · outbound

This paper cites Node similarity preserving graph convolutional networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Node similarity preserving graph convolutional networks,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:41.205627Z

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Observation 64082da5-b5c7-4f91-9954-62495cedf508 · outbound

This paper cites Seeking similarities while removing differences: Graph neural networks based on node correlation,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Seeking similarities while removing differences: Graph neural networks based on node correlation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:40.967305Z

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Observation 79e9d642-beae-4853-b270-b9f9b512bd4b · outbound

This paper cites Unbiased graph embedding with biased graph observations,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Unbiased graph embedding with biased graph observations,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:40.846549Z

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Observation aa332f12-23b3-4d7b-a77f-283fdce8906e · outbound

This paper cites struc2vec: Learning node representations from structural identity,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery struc2vec: Learning node representations from structural identity,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:40.658794Z

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Observation 2447f7dc-ed37-496b-a64c-111a1cd3e825 · outbound

This paper cites Semi-supervised classification with graph convolutional networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Semi-supervised classification with graph convolutional networks,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:40.399908Z

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Observation d5c26dc6-a95a-4d4e-b494-cf607798e29a · outbound

This paper cites Graph attention networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Graph attention networks,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:40.087070Z

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Observation 7bf861a4-e853-4c63-a57e-7ebc431d48cb · outbound

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

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Birds of a feather: Homophily in social networks,

Reference 34

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Observation c6d3bce7-20f9-4447-8b5b-70163c717155 · outbound

This paper cites Simplifying graph convolutional networks,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Simplifying graph convolutional networks,

Reference 35

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Observation a056cd74-dd5a-4de2-8679-2958ed1121c8 · outbound

This paper cites Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification?.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification?

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T05:08:34.482166Z

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Observation d3e39086-b965-475e-bc9a-115310d2eba2 · outbound

This paper cites Discrete signal processing on graphs: Frequency analysis,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Discrete signal processing on graphs: Frequency analysis,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:39.525932Z

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Observation 3b96b774-9fdb-49bc-a6a2-e2f66bc7329c · outbound

This paper cites RolX: structural role extraction & mining in large graphs,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery RolX: structural role extraction & mining in large graphs,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:39.241957Z

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Observation 025e1fd2-942d-4edc-bec6-d4128059645d · outbound

This paper cites A set of measures of centrality based on betweenness,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery A set of measures of centrality based on betweenness,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T05:08:34.913534Z

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Observation 85f6ed2d-be36-4390-8cbe-543b8e0267e5 · outbound

This paper cites Automat- ing the construction of internet portals with machine learning,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Automat- ing the construction of internet portals with machine learning,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:38.970423Z

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Observation 0a818049-3120-4446-9c86-7423c0f1f7f5 · outbound

This paper cites CiteSeer: An automatic citation indexing system,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery CiteSeer: An automatic citation indexing system,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:38.625275Z

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Observation 0805db1e-ce06-4c67-a4af-460f9c85b393 · outbound

This paper cites Tensor graph convolutional networks for multi-relational and robust learning,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Tensor graph convolutional networks for multi-relational and robust learning,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:38.329927Z

Source-reported events for the cited work

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Observation c3768a4b-deac-4522-a935-ed28d4414bde · outbound

This paper cites How powerful are graph neural networks?.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery How powerful are graph neural networks?

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:38.023665Z

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Observation d75b74fd-efdd-4a60-815a-827bd5170d6a · outbound

This paper cites Collective classification in network data,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Collective classification in network data,

Reference 44

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Observation 553bcceb-634c-42bf-8f29-fe22ea3eeb19 · outbound

This paper cites DeepWalk: Online learning of social representations,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery DeepWalk: Online learning of social representations,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:37.773429Z

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Observation 4c0ae4d4-0525-4c2e-b8d1-cd7f95473291 · outbound

This paper cites node2vec: Scalable feature learning for net- works,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery node2vec: Scalable feature learning for net- works,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:37.449842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2aff24f8-e115-4526-9722-dc8bd342dd92 · outbound

This paper cites Learning structural node embeddings via diffusion wavelets,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Learning structural node embeddings via diffusion wavelets,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:37.239648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8e4c8fe9-4018-407f-a19e-8fc61d8a94f3 · outbound

This paper cites Edge directionality improves learning on heterophilic graphs,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Edge directionality improves learning on heterophilic graphs,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:36.964022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b979943a-c605-4caa-a53d-714b8c67739a · outbound

This paper cites Simple spectral graph convolution,.

Adapting to Heterophilic Graph Data with Structure-Guided Neighbor Discovery Simple spectral graph convolution,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T05:08:36.733280Z

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