Paper Citation Record · LEDGER

Geom-GCN: Geometric Graph Convolutional Networks

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 29 inbound Pith citation observations for arXiv:2002.05287.

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

pith.paper-citation-record.v1
2002.05287 v2

Coverage vector

measured 0 of 0 reference resolution

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Source: paper_references, paper_reference_links

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 29 of 29 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:25:40.748982Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:27:37.371060Z

Reference resolution

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External citation measurements

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Outbound references

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Pith citing papers

Observation cf41b542-a70e-4734-8730-aa6690ee28f6 · inbound

COMBINEX: A Unified Counterfactual Explainer for Graph Neural Networks via Node Feature and Structural Perturbations cites this paper.

COMBINEX: A Unified Counterfactual Explainer for Graph Neural Networks via Node Feature and Structural Perturbations Geom-GCN: Geometric Graph Convolutional Networks

Reference 2020

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Observation 3b324403-6865-41be-b645-64919925bdca · inbound

SGS-GNN: A Supervised Graph Sparsification method for Graph Neural Networks cites this paper.

SGS-GNN: A Supervised Graph Sparsification method for Graph Neural Networks Geom-GCN: Geometric Graph Convolutional Networks

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T19:05:45.898813Z

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Observation 581ed39f-7ad8-445c-8a80-f54b69911c2e · inbound

Learn Beneficial Noise as Graph Augmentation cites this paper.

Learn Beneficial Noise as Graph Augmentation Geom-GCN: Geometric Graph Convolutional Networks

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:28:34.696094Z

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Observation cd62a6aa-1925-4eae-a86e-118b185b0e22 · inbound

Aggregation Buffer: Revisiting DropEdge with a New Parameter Block cites this paper.

Aggregation Buffer: Revisiting DropEdge with a New Parameter Block Geom-GCN: Geometric Graph Convolutional Networks

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T13:51:45.633953Z

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Observation d7ed0f09-b999-4dab-9362-5cf47e715d90 · inbound

Graph Positional Autoencoders as Self-supervised Learners cites this paper.

Graph Positional Autoencoders as Self-supervised Learners Geom-GCN: Geometric Graph Convolutional Networks

Reference 2020

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Observation ced7cb21-77fc-4bba-9fee-11cc63f313bf · inbound

Sheaves Reloaded: A Directional Awakening cites this paper.

Sheaves Reloaded: A Directional Awakening Geom-GCN: Geometric Graph Convolutional Networks

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T11:24:01.187324Z

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Observation de28c197-f021-497d-b087-939cfd17db6f · inbound

The Oversmoothing Fallacy: A Misguided Narrative in GNN Research cites this paper.

The Oversmoothing Fallacy: A Misguided Narrative in GNN Research Geom-GCN: Geometric Graph Convolutional Networks

Reference 26

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Observation a11b5338-59db-4175-8f88-2020bbbabb38 · inbound

OpenGT: A Comprehensive Benchmark For Graph Transformers cites this paper.

OpenGT: A Comprehensive Benchmark For Graph Transformers Geom-GCN: Geometric Graph Convolutional Networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T10:37:17.846436Z

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Observation a07b7555-13e3-45cc-af4d-05f3fc07a25d · inbound

How do Probabilistic Graphical Models and Graph Neural Networks Look at Network Data? cites this paper.

How do Probabilistic Graphical Models and Graph Neural Networks Look at Network Data? Geom-GCN: Geometric Graph Convolutional Networks

Reference 50

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Observation 27a1c442-8ba0-4d1a-9744-f231d07a928a · inbound

Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark cites this paper.

Delving into Instance-Dependent Label Noise in Graph Data: A Comprehensive Study and Benchmark Geom-GCN: Geometric Graph Convolutional Networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-07T00:55:54.806901Z

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Observation 08156981-c23e-4cab-9799-f5e1eece2a40 · inbound

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams cites this paper.

A Batch-Insensitive Dynamic GNN Approach to Address Temporal Discontinuity in Graph Streams Geom-GCN: Geometric Graph Convolutional Networks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T23:12:03.113234Z

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Observation 56ee54c7-f61a-4738-9d99-19bbd3aa6702 · inbound

Enhancing Power Flow Estimation with Topology-Aware Gated Graph Neural Networks cites this paper.

Enhancing Power Flow Estimation with Topology-Aware Gated Graph Neural Networks Geom-GCN: Geometric Graph Convolutional Networks

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T20:42:58.731287Z

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Observation 05bc02ed-5791-4cd1-98b8-d3982e109dbe · inbound

PLACE: Prompt Learning for Attributed Community Search in Large Graphs cites this paper.

PLACE: Prompt Learning for Attributed Community Search in Large Graphs Geom-GCN: Geometric Graph Convolutional Networks

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-25T07:50:29.432844Z

Source-reported events for the cited work

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Observation ae005426-ca29-46a6-85ea-f77c91843d52 · inbound

Dual-Center Graph Clustering with Neighbor Distribution cites this paper.

Dual-Center Graph Clustering with Neighbor Distribution Geom-GCN: Geometric Graph Convolutional Networks

Reference 20

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Observation 62768154-f16e-4841-80e7-623a2547b228 · inbound

Unifying Adversarial Perturbation for Graph Neural Networks cites this paper.

Unifying Adversarial Perturbation for Graph Neural Networks Geom-GCN: Geometric Graph Convolutional Networks

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T13:44:08.804616Z

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Observation 7bd31b42-e575-409f-89f7-c9983e371e42 · inbound

Are Heterogeneous Graph Neural Networks Truly Effective for Node Classification? A Causal Perspective cites this paper.

Are Heterogeneous Graph Neural Networks Truly Effective for Node Classification? A Causal Perspective Geom-GCN: Geometric Graph Convolutional Networks

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-04T11:19:48.954103Z

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Observation d023920e-d8c6-467a-b036-c6efcb69fbac · inbound

Structural Bias Beyond Homophily: A Study of Fairness in Link Prediction cites this paper.

Structural Bias Beyond Homophily: A Study of Fairness in Link Prediction Geom-GCN: Geometric Graph Convolutional Networks

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T00:05:34.671939Z

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Observation e4115ee8-3e21-424c-bc1a-0f026ec29777 · inbound

Frequency-Corrupt Based Graph Self-Supervised Learning cites this paper.

Frequency-Corrupt Based Graph Self-Supervised Learning Geom-GCN: Geometric Graph Convolutional Networks

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-10T08:32:52.059421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f06672c1-a41a-4c32-870f-e33893bf8474 · inbound

Frequency-Corrupt Based Graph Self-Supervised Learning cites this paper.

Frequency-Corrupt Based Graph Self-Supervised Learning Geom-GCN: Geometric Graph Convolutional Networks

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-02T16:10:59.751880Z

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Unavailable: canonical work link unavailable.

Observation 2635d07b-8a56-49c6-a88d-0687cdef07bc · inbound

Inductive Subgraphs as Shortcuts: Causal Disentanglement for Heterophilic Graph Learning cites this paper.

Inductive Subgraphs as Shortcuts: Causal Disentanglement for Heterophilic Graph Learning Geom-GCN: Geometric Graph Convolutional Networks

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:51:02.744366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0f03c76a-7675-48e1-8f70-28214a09de25 · inbound

RAwR: Role-Aware Rewiring via Approximate Equitable Partition cites this paper.

RAwR: Role-Aware Rewiring via Approximate Equitable Partition Geom-GCN: Geometric Graph Convolutional Networks

Reference 36

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T06:06:25.988165Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 71ad8517-faff-4d93-b940-46d669c11e35 · inbound

A complete discussion on fully reconfigurable, digital, scalable, graph and sparsity-aware near-memory accelerator for graph neural networks cites this paper.

A complete discussion on fully reconfigurable, digital, scalable, graph and sparsity-aware near-memory accelerator for graph neural networks Geom-GCN: Geometric Graph Convolutional Networks

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-20T02:22:59.188355Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a7591e97-043b-46dd-ace3-e7dd973dbf2e · inbound

A complete discussion on fully reconfigurable, digital, scalable, graph and sparsity-aware near-memory accelerator for graph neural networks cites this paper.

A complete discussion on fully reconfigurable, digital, scalable, graph and sparsity-aware near-memory accelerator for graph neural networks Geom-GCN: Geometric Graph Convolutional Networks

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:04:58.419675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8c99087a-4ab1-430c-ada9-b64da295cfb5 · inbound

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification cites this paper.

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification Geom-GCN: Geometric Graph Convolutional Networks

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T08:34:05.438903Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a439cefe-6ab9-4e8c-a8b0-0fd9abcad89a · inbound

Graph Navier Stokes Networks cites this paper.

Graph Navier Stokes Networks Geom-GCN: Geometric Graph Convolutional Networks

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:13:58.233665Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 70504e1d-f42b-4c28-a736-4792e4c2bdb3 · inbound

Graph Navier Stokes Networks cites this paper.

Graph Navier Stokes Networks Geom-GCN: Geometric Graph Convolutional Networks

Reference 63

Resolution: verified exact; arxiv_id, observed 2026-06-30T17:14:56.859596Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bee752fe-6518-497f-8aaa-7d89e39cb9ba · inbound

Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing cites this paper.

Revisiting Positive Samples in Graph Contrastive Learning: From the Perspective of Message Passing Geom-GCN: Geometric Graph Convolutional Networks

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T04:27:37.372495Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 48ff1c8c-ae13-4e16-a0c1-4b15a2a7af6c · inbound

NodeImport: Imbalanced Node Classification with Node Importance Assessment cites this paper.

NodeImport: Imbalanced Node Classification with Node Importance Assessment Geom-GCN: Geometric Graph Convolutional Networks

Reference 2020

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Observation 11f25e31-eaef-4780-af24-10cb7e058621 · inbound

HeAD-CP: Heterophily-Aware Diffused Conformal Prediction Sets for Graph Neural Networks cites this paper.

HeAD-CP: Heterophily-Aware Diffused Conformal Prediction Sets for Graph Neural Networks Geom-GCN: Geometric Graph Convolutional Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-01T02:57:52.500897Z

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Unavailable: canonical work link unavailable.