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Paper Citation Record · LEDGER

DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:1907.10903.

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

pith.paper-citation-record.v1
1907.10903 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T19:05:45.910225Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T01:17:30.938472Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c57110d0-75f0-4dae-8a31-fed224b0cf65 · inbound

xAI-Drop: Don't Use What You Cannot Explain cites this paper.

xAI-Drop: Don't Use What You Cannot Explain DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 28

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arxiv_id, observed 2026-05-23T23:03:34.661106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 16ef597f-a03c-43cd-82d1-ccfbefd9f1f5 · 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 DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 31

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T19:05:45.910225Z digest=sha256:446f96f68a929fbaea4829870350708689484281aeef49df3c889340efac10da

Observation f86149dd-e3ce-40cc-99f3-1287e168e7d6 · inbound

Khan-GCL: Kolmogorov-Arnold Network Based Graph Contrastive Learning with Hard Negatives cites this paper.

Khan-GCL: Kolmogorov-Arnold Network Based Graph Contrastive Learning with Hard Negatives DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 37

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no resolver link, observed 2026-08-07T15:29:49.547039Z

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Observation 4a7bce00-ecb2-4c27-baa4-dee6bb36769c · inbound

Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization cites this paper.

Pruning Spurious Subgraphs for Graph Out-of-Distribution Generalization DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 42

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no resolver link, observed 2026-08-07T10:19:30.640457Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:19:30.640457Z digest=sha256:d52771985e1f9260d6784ac2a7b3f789a8377cfe31c8f00374f623e02503779a

Observation 183e04f1-01ec-487c-b71e-f7e7d3039cb5 · 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 DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 52

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no resolver link, observed 2026-08-07T00:55:54.817854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:55:54.817854Z digest=sha256:76ce1af9f2c57bfc83806714d672ab772ee4404ba5c76a4a73e85b97f6c10de0

Observation ccd2e350-51d7-4e9d-80f2-c670fd2c928f · inbound

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning cites this paper.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 23

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no resolver link, observed 2026-08-06T23:34:51.966546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 34f5209e-afa6-45f6-85b4-afa3e027106d · inbound

Graph-Based Deep Learning for Component Segmentation of Maize Plants cites this paper.

Graph-Based Deep Learning for Component Segmentation of Maize Plants DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 29

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no resolver link, observed 2026-08-06T21:25:52.232712Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:25:52.232712Z digest=sha256:da18f49b579dc1057b073ff49c968b51d0d258732cd183e5f688a07dd8b4100f

Observation a2317651-03eb-4ccd-85e7-357142e9c707 · inbound

Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization cites this paper.

Rethinking Over-Smoothing in Graph Neural Networks: A Perspective from Anderson Localization DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 25

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no resolver link, observed 2026-08-06T23:35:48.574839Z

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source=pdf_text observed=2026-08-06T23:35:48.574839Z digest=sha256:9406fc83754861473546df3113fdc3bcafe94c1baf0ed933750d4e1061a47627

Observation 9b5c6070-61d9-4bd3-a702-22c4a26c07e4 · inbound

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks cites this paper.

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 23

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no resolver link, observed 2026-08-04T23:12:23.445107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a9cacac8-c0fd-46ba-bf35-56ff472757c4 · inbound

AEGIS: Authentic Edge Growth In Sparsity for Link Prediction in Edge-Sparse Bipartite Knowledge Graphs cites this paper.

AEGIS: Authentic Edge Growth In Sparsity for Link Prediction in Edge-Sparse Bipartite Knowledge Graphs DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 16

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arxiv_id, observed 2026-05-18T13:52:39.071093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1a99107f-9cce-4ba0-9303-7213a2b06e83 · inbound

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning cites this paper.

From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 8

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no resolver link, observed 2026-08-04T12:13:08.410634Z

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Unavailable: canonical work link unavailable.

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Observation c65404e3-0fcc-4ec9-9c5e-602c255cbc08 · inbound

Robustness of Graph Self-Supervised Learning to Real-World Noise: A Case Study on Text-Driven Biomedical Graphs cites this paper.

Robustness of Graph Self-Supervised Learning to Real-World Noise: A Case Study on Text-Driven Biomedical Graphs DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 43

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arxiv_id, observed 2026-05-11T17:46:08.147801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 47cc5170-934a-46e4-a7a5-4b70237dca6c · inbound

A Unified Benchmark for Evaluating Knowledge Graph Construction Methods and Graph Neural Networks cites this paper.

A Unified Benchmark for Evaluating Knowledge Graph Construction Methods and Graph Neural Networks DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 124

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arxiv_id, observed 2026-05-11T17:46:13.516179Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0ad8762c-c63a-4ff8-8678-16b889f04cae · inbound

Learning over Positive and Negative Edges with Contrastive Message Passing cites this paper.

Learning over Positive and Negative Edges with Contrastive Message Passing DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 22

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arxiv_id, observed 2026-05-20T12:33:16.857717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 73f7b33c-9610-4d01-8b8f-2662ddbaeb26 · inbound

EUPHORIA: Efficient Universal Planning via Hybrid Optimization for Robust Industrial Robotic Assembly cites this paper.

EUPHORIA: Efficient Universal Planning via Hybrid Optimization for Robust Industrial Robotic Assembly DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 42

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verified exact
arxiv_id, observed 2026-05-20T20:03:43.336853Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7bf31139-2009-4420-9cdc-c6eae4b7d26a · inbound

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

Graph Transductive Sharpening: Leveraging Unlabeled Predictions in Node Classification DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 36

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verified exact
arxiv_id, observed 2026-05-21T08:34:05.430893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 74de1410-9f88-4e84-be94-0ee4cc6feb5a · inbound

Topology-Aware Gaussian Graph Repair for Robust Graph Neural Networks cites this paper.

Topology-Aware Gaussian Graph Repair for Robust Graph Neural Networks DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 29

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verified exact
arxiv_id, observed 2026-07-02T01:46:26.741573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-28T11:33:57.079373Z digest=sha256:d8bd9e0e4853c3356f3ca2f5f281eb8e618b56835ab4e372068e1e35ce8987b0

Observation 825f8170-31d1-4276-b14b-24383a3ffbba · inbound

From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction cites this paper.

From Coarse to Fine: Managing Temporal Granularity in Spatio-Temporal Data for Fine-Grained Traffic Prediction DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 41

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arxiv_id, observed 2026-07-03T01:17:30.939991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a7a3a992-a296-4132-b578-b445e46df096 · inbound

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning cites this paper.

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 223

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arxiv_id, observed 2026-07-01T09:45:40.714825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-07-01T06:10:26.634933Z digest=sha256:9e8149a66deda4dbf4802671d0760e2882abe7cf8b48b5a6d7296f8ae19df52c

Observation d29e18a9-9eb4-43f0-aa23-caae38afb422 · inbound

From Diffusion to Reaction-Diffusion: A Dynamical-Systems View of Oversmoothing in Hypergraph Neural Networks cites this paper.

From Diffusion to Reaction-Diffusion: A Dynamical-Systems View of Oversmoothing in Hypergraph Neural Networks DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 12

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Unavailable: canonical work link unavailable.

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Observation aea5c00a-d9af-4b5d-a496-151bb8f572af · inbound

LAEF: A Lead-Agnostic ECG Foundation Model Towards Point-of-Care Diagnostics cites this paper.

LAEF: A Lead-Agnostic ECG Foundation Model Towards Point-of-Care Diagnostics DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 178

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