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Paper Citation Record · LEDGER

Memorization in Graph Neural Networks

As of 14 August 2026, this Paper Citation Record lists 77 of 77 outbound references and 0 inbound Pith citation observations for arXiv:2508.19352.

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

pith.paper-citation-record.v1
2508.19352 v3

Coverage vector

measured 77 of 77 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T15:53:59.520306Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

77 of 77 outbound references displayed

  • verified exact4
  • verified fuzzy43
  • unresolved27
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation db833f6e-5c70-4292-b1a1-d71d996f1cba · outbound

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

Memorization in Graph Neural Networks MixHop: Higher-order graph convolutional architectures via sparsified neighborhood mixing

Reference 1

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Observation 1581e0a8-7c6f-4911-82d8-ea6280fd2b76 · outbound

This paper cites On the bottleneck of graph neural networks and its practical implications.

Memorization in Graph Neural Networks On the bottleneck of graph neural networks and its practical implications

Reference 2

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Observation 6c500caf-1e56-4d2a-83ef-f470921caaf2 · outbound

This paper cites Generalization Error of Graph Neural Networks in the Mean-field Regime.

Memorization in Graph Neural Networks Generalization Error of Graph Neural Networks in the Mean-field Regime

Reference 3

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Observation c87952d9-f8f2-4efe-a2e3-35f1f1ae49eb · outbound

This paper cites Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks.

Memorization in Graph Neural Networks Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks

Reference 4

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Observation 23765f1e-eb2c-449f-81c8-cc86150c8b38 · outbound

This paper cites A closer look at memorization in deep networks.

Memorization in Graph Neural Networks A closer look at memorization in deep networks

Reference 5

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Observation c68541a4-010f-4df2-a8cb-e5b29051f331 · outbound

This paper cites Deep learning through the lens of example difficulty.

Memorization in Graph Neural Networks Deep learning through the lens of example difficulty

Reference 6

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Observation 3bd39413-f573-402d-a29d-c15551cdc4d2 · outbound

This paper cites Emergence of scaling in random networks.

Memorization in Graph Neural Networks Emergence of scaling in random networks

Reference 7

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Observation 851bddba-058b-4594-91b5-daee5bdf8d7c · outbound

This paper cites The Pitfalls of Memorization: When Memorization Hurts Generalization.

Memorization in Graph Neural Networks The Pitfalls of Memorization: When Memorization Hurts Generalization

Reference 8

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Observation c317b482-a0f7-4a9d-9596-f097b951e26e · outbound

This paper cites Graph neural networks use graphs when they shouldn’t, 2024.

Memorization in Graph Neural Networks Graph neural networks use graphs when they shouldn’t, 2024

Reference 9

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Observation e4083dd0-715c-4c03-9a6b-e831673574e4 · outbound

This paper cites Make heterophily graphs better fit gnn: A graph rewiring approach, 2022.

Memorization in Graph Neural Networks Make heterophily graphs better fit gnn: A graph rewiring approach, 2022

Reference 10

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Observation cba4570e-78ac-4e08-800f-8086d5e5568b · outbound

This paper cites Memorization and optimization in deep neural networks with minimum over-parameterization.

Memorization in Graph Neural Networks Memorization and optimization in deep neural networks with minimum over-parameterization

Reference 11

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Observation e8bd7345-1136-4852-b9df-f9328d9a75ac · outbound

This paper cites Biognn: How graph neural networks can solve biological problems.

Memorization in Graph Neural Networks Biognn: How graph neural networks can solve biological problems

Reference 12

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Observation 28af3de1-8988-4ec1-9b19-e99d7f53bf05 · outbound

This paper cites How attentive are graph attention networks? In International Conference on Learning Representations, 2022.

Memorization in Graph Neural Networks How attentive are graph attention networks? In International Conference on Learning Representations, 2022

Reference 13

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Observation 69e6de8f-f90d-48ef-9c7a-4004e04674e8 · outbound

This paper cites Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges.

Memorization in Graph Neural Networks Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 14

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Observation 042ad211-b56d-4f76-a80f-b23fffa1c35b · outbound

This paper cites Extracting training data from large language models.

Memorization in Graph Neural Networks Extracting training data from large language models

Reference 15

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Observation 32cd0d3a-c088-44d5-ac0b-85ec18bbb275 · outbound

This paper cites Membership inference attacks from first principles.

Memorization in Graph Neural Networks Membership inference attacks from first principles

Reference 16

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Observation 399fee7b-768c-4398-acd0-07091048e874 · outbound

This paper cites The privacy onion effect: Memorization is relative.

Memorization in Graph Neural Networks The privacy onion effect: Memorization is relative

Reference 17

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Observation 7bc7ee87-4ba5-429e-9e47-35418b5f713b · outbound

This paper cites Quantifying Memorization Across Neural Language Models.

Memorization in Graph Neural Networks Quantifying Memorization Across Neural Language Models

Reference 18

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Observation 5fb7586e-a252-4aa4-8b88-079d27d1408a · outbound

This paper cites On kernel-target alignment.

Memorization in Graph Neural Networks On kernel-target alignment

Reference 19

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Observation 6d44fffb-5237-46cf-9926-2d08c371ddd3 · outbound

This paper cites Attentive walk-aggregating graph neural networks.

Memorization in Graph Neural Networks Attentive walk-aggregating graph neural networks

Reference 20

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Observation f26413f2-2011-4a1f-a6e0-c509ced76552 · outbound

This paper cites Does learning require memorization? a short tale about a long tail.

Memorization in Graph Neural Networks Does learning require memorization? a short tale about a long tail

Reference 21

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Observation 592d7fe9-e375-4626-a94b-8565972f91a0 · outbound

This paper cites How powerful are k-hop message passing graph neural networks.

Memorization in Graph Neural Networks How powerful are k-hop message passing graph neural networks

Reference 22

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Observation 418b9f37-accf-4781-bd33-e193fb60d16a · outbound

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Memorization in Graph Neural Networks Unresolved cited work

Reference 23

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Observation 9a5f47e2-5384-4f6d-8d4f-c9fb6c29dfc9 · outbound

This paper cites Schoenholz, Patrick F.

Memorization in Graph Neural Networks Schoenholz, Patrick F

Reference 24

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Observation eda04afc-ef09-4233-8fce-d38c817942a1 · outbound

This paper cites Giraldo, Konstantinos Skianis, Thierry Bouwmans, and Fragkiskos D.

Memorization in Graph Neural Networks Giraldo, Konstantinos Skianis, Thierry Bouwmans, and Fragkiskos D

Reference 25

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Observation a0dbb547-9856-4755-bd7f-ec7ae784fddc · outbound

This paper cites Understanding the difficulty of training deep feedforward neural networks.

Memorization in Graph Neural Networks Understanding the difficulty of training deep feedforward neural networks

Reference 26

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Observation d2ee4238-2beb-4aa1-93ba-a4b6144618a9 · outbound

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Memorization in Graph Neural Networks Unresolved cited work

Reference 27

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Observation 43716b5e-600d-4159-baa4-684f864abb49 · outbound

This paper cites Hamilton, Rex Ying, and Jure Leskovec.

Memorization in Graph Neural Networks Hamilton, Rex Ying, and Jure Leskovec

Reference 28

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Observation 44039cf1-bc86-4c56-8505-a1267e638287 · outbound

This paper cites Hamilton, Zhitao Ying, and Jure Leskovec.

Memorization in Graph Neural Networks Hamilton, Zhitao Ying, and Jure Leskovec

Reference 29

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Observation 61baf7f2-f2ab-4736-b375-469c944253b7 · outbound

This paper cites Open Graph Benchmark: Datasets for Machine Learning on Graphs.

Memorization in Graph Neural Networks Open Graph Benchmark: Datasets for Machine Learning on Graphs

Reference 30

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Observation eb1ee335-1069-4d00-9056-6adc4fdb0e38 · outbound

This paper cites Neural tangent kernel: Convergence and generalization in neural networks.

Memorization in Graph Neural Networks Neural tangent kernel: Convergence and generalization in neural networks

Reference 31

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Observation 1225bdcf-24d7-4318-83b1-dcb2296be331 · outbound

This paper cites Spectral graph pruning against over-squashing and over-smoothing.

Memorization in Graph Neural Networks Spectral graph pruning against over-squashing and over-smoothing

Reference 32

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Observation e5166a8b-6823-4a7a-a47b-751e6d5eaf22 · outbound

This paper cites Banerjee, and Guido Montufar.

Memorization in Graph Neural Networks Banerjee, and Guido Montufar

Reference 33

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Observation 40012159-d636-4321-b225-8beaad422dcc · outbound

This paper cites Homophily influences ranking of minorities in social networks.

Memorization in Graph Neural Networks Homophily influences ranking of minorities in social networks

Reference 34

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Observation 0df95029-86fb-4698-bf9d-c9c900188647 · outbound

This paper cites Not too little, not too much: a theoretical analysis of graph (over)smoothing.

Memorization in Graph Neural Networks Not too little, not too much: a theoretical analysis of graph (over)smoothing

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:53.364689Z digest=sha256:7c294b097eff6c0dc131b39d55f2287d8b081a9db059df5b3f4c7c8f8832361e

Observation 13fd615d-cb1e-4f53-9f96-132233add437 · outbound

This paper cites Convergence and Stability of Graph Convolutional Networks on Large Random Graphs.

Memorization in Graph Neural Networks Convergence and Stability of Graph Convolutional Networks on Large Random Graphs

Reference 36

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local_arxiv, observed 2026-08-05T15:54:00.656704Z

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No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:53.528985Z digest=sha256:902a597fcb1dc2a5f08e0a87fb3e7bb2f811652c6dd2db300736f6073a7df3ca

Observation 283f999e-b217-488e-aeee-01b0fafce216 · outbound

This paper cites Kipf and Max Welling.

Memorization in Graph Neural Networks Kipf and Max Welling

Reference 37

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raw_fallback, observed 2026-08-05T15:54:10.524633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:53.720397Z digest=sha256:d6a30abda59f6c118815d622c946c1bbaa5c48cb9016446fea024fde653afc97

Observation 5cc8453d-7084-4837-ba77-3d783ddf0fe3 · outbound

This paper cites Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond.

Memorization in Graph Neural Networks Trustworthy Machine Learning via Memorization and the Granular Long-Tail: A Survey on Interactions, Tradeoffs, and Beyond

Reference 38

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no resolver link, observed 2026-08-05T15:53:53.901347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:53.901347Z digest=sha256:624ae304180202771adb7c67f44e7ad4ea409f56912d22b8eb2561106212a33d

Observation f1b371d0-c53f-40a9-b021-a2e916881856 · outbound

This paper cites Towards bridging generalization and expressivity of graph neural networks, 2024.

Memorization in Graph Neural Networks Towards bridging generalization and expressivity of graph neural networks, 2024

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:10.094950Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:54.041266Z digest=sha256:21571f2ae94bf829324618a3e64d692bc4ff19939fbdd3b7620ef33af0e72774

Observation dcac8884-8a25-412c-9418-120dac162732 · outbound

This paper cites Can Neural Network Memorization Be Localized?.

Memorization in Graph Neural Networks Can Neural Network Memorization Be Localized?

Reference 40

Resolution
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no resolver link, observed 2026-08-05T15:53:54.132399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:54.132399Z digest=sha256:d161281f700ffb916a84d9aa0e8abd6d12db1475c51aab8e4d8959679116cd46

Observation b7b5cb8a-4162-4b84-b9fb-81605edcd12f · outbound

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

Memorization in Graph Neural Networks Automat- ing the construction of internet portals with machine learning

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:54.297775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:54.297775Z digest=sha256:62930a51c8789f6464468379f45f6e31624d0973e2614e3c551984838294ccae

Observation f99f9859-6ddc-4ec2-b567-adbc0d4f94bf · outbound

This paper cites Schoenholz, Muratahan Aykol, Gowoon Cheon, and Ekin Dogus Cubuk.

Memorization in Graph Neural Networks Schoenholz, Muratahan Aykol, Gowoon Cheon, and Ekin Dogus Cubuk

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:54.451673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:54.451673Z digest=sha256:a6c17b207d3fb1c743bde7d55ed7c99b3648ec961c8b9099bf09d9b316850d3a

Observation 699c6722-b5cb-4898-88d1-77e0604a7850 · outbound

This paper cites TUDataset: A collection of benchmark datasets for learning with graphs.

Memorization in Graph Neural Networks TUDataset: A collection of benchmark datasets for learning with graphs

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:54.671282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:54.671282Z digest=sha256:c6448bf036567af4864968e9bc6a8165c0dada03d53c7a9e55dcab841a8a6d36

Observation f8a88748-6dd9-42ca-bd0c-2454feee6f87 · outbound

This paper cites Are GATs out of balance? In Thirty-seventh Conference on Neural Information Processing Systems, 2023.

Memorization in Graph Neural Networks Are GATs out of balance? In Thirty-seventh Conference on Neural Information Processing Systems, 2023

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:09.711553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:54.836744Z digest=sha256:4047e81cacb75bdfc0aab124a2760049246dab92bb543ef116901f41b9b5956b

Observation ffded4b2-efaa-4f3c-ba91-24d0e48e991a · outbound

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

Memorization in Graph Neural Networks Query-driven active surveying for collective classification

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:09.399298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:55.038309Z digest=sha256:c89720f30d79e4de8ddbd31ec5fa987be92232f1d5c4a7750e2ae0897069d1d7

Observation 3e0c7961-428e-44ca-90c4-df6c8e951015 · outbound

This paper cites Revisiting over-smoothing and over-squashing using ollivier-ricci curvature, 2023.

Memorization in Graph Neural Networks Revisiting over-smoothing and over-squashing using ollivier-ricci curvature, 2023

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:09.086150Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:55.219756Z digest=sha256:ee9fc6cf3f8b6f152d2ab1d3d817f629dcc1962861aa7dab9525715222fc6375

Observation 7c5db356-5921-49cd-a005-913b251abbae · outbound

This paper cites k-hop graph neural networks,.

Memorization in Graph Neural Networks k-hop graph neural networks,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:08.653590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:55.445264Z digest=sha256:b2e7ea429273a710aa7e8379fe95122a7b14ec672384c705582afa72cb7cae21

Observation 389f3d85-6b83-4911-b2c5-9ac7e0f5e838 · outbound

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

Memorization in Graph Neural Networks Geom-gcn: Geo- metric graph convolutional networks

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:08.343396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:55.801261Z digest=sha256:8c6daf1da2e3b554e2693b60a62b6a75580a2d3870e94f98ed3dec21e8af6376

Observation 298621f7-5650-4af2-8d2a-b7c94c15d152 · outbound

This paper cites Charac- terizing graph datasets for node classification: Homophily-heterophily dichotomy and be- yond.

Memorization in Graph Neural Networks Charac- terizing graph datasets for node classification: Homophily-heterophily dichotomy and be- yond

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:07.549789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:56.126280Z digest=sha256:85ede05a59eb50d5534047ba25a5d7f1e6eb1fb35930c8e0eff1f7eda3103104

Observation 255f522f-5aa8-4212-8b54-7d4e7e91e6df · outbound

This paper cites A critical look at evaluation of gnns under heterophily: Are we really making progress? In The Eleventh International Conference on Learning Representations, 2023.

Memorization in Graph Neural Networks A critical look at evaluation of gnns under heterophily: Are we really making progress? In The Eleventh International Conference on Learning Representations, 2023

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:07.194125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:56.256820Z digest=sha256:96a05a8e826a734dd307dc27b2f11f70b91556dc635b84944d9ed30f1b030ce6

Observation 71bdcd82-dee2-417a-b92b-343e7cdcc764 · outbound

This paper cites Recipe for a General, Powerful, Scalable Graph Transformer.

Memorization in Graph Neural Networks Recipe for a General, Powerful, Scalable Graph Transformer

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:06.769275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:56.388986Z digest=sha256:f9b16f919a233a66a254cdccbef2913fe6c5c849d073651a1f6016b792bb183e

Observation 96345e88-9695-47d6-89de-741ad81afd7e · outbound

This paper cites Graph neural networks for materials science and chemistry.

Memorization in Graph Neural Networks Graph neural networks for materials science and chemistry

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:56.493215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:56.493215Z digest=sha256:b4a6e147f4565740e0ac72a0420cf045d5ad9adf03c075203fef5993d8eedccd

Observation 96157cbc-b8d2-4e66-a014-2a9fea372085 · outbound

This paper cites an unresolved cited work.

Memorization in Graph Neural Networks Unresolved cited work

Reference 53

Resolution
unresolved
raw_fallback, observed 2026-08-05T15:54:07.953432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:55.979967Z digest=sha256:68d633c04cae5ac8bd84aaf90449d4cd2a660cd35ef2eaf57d71425dc320252a

Observation 6fd88c90-f208-412f-bd6e-004f8715756a · outbound

This paper cites GNNs getting comfy: Com- munity and feature similarity guided rewiring.

Memorization in Graph Neural Networks GNNs getting comfy: Com- munity and feature similarity guided rewiring

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:06.416221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:56.709105Z digest=sha256:dd8db8cd9b701c46ba48e5443adb8c9ecfcc90b64a709ff1be497c2f0d30dd56

Observation 31ad7bd0-f81e-43dd-a65f-92f558cff1d1 · outbound

This paper cites The graph neural network model.

Memorization in Graph Neural Networks The graph neural network model

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:56.825872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:56.825872Z digest=sha256:a33e4cfd3c648777a9cf73daa3e7197f6c31c848995cacacfed84044ffdca9aa

Observation 07f606d3-e1ac-44a5-b63d-4f3b22d78d82 · outbound

This paper cites Collective classification in network data.

Memorization in Graph Neural Networks Collective classification in network data

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:56.916261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:56.916261Z digest=sha256:d681e08bc30debf682f5c41f7ba84823e4785a0a2d3d5b8f0789d42d7ea0cd69

Observation aed1751b-b935-4f22-86ff-0f6fcf7a9e49 · outbound

This paper cites Pitfalls of graph neural network evaluation, 2019.

Memorization in Graph Neural Networks Pitfalls of graph neural network evaluation, 2019

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:57.035916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:57.035916Z digest=sha256:0cc2789078ed2e21c63199a40ed619e6a9d6447d25e843c8082a6405e5177e0a

Observation 1b8f7a16-6c1a-4ff8-817c-93f83dbdd0a9 · outbound

This paper cites Multi-scale Attributed Node Embedding.

Memorization in Graph Neural Networks Multi-scale Attributed Node Embedding

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:56.575424Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:56.575424Z digest=sha256:784137054e0604001e724d8d752cc1a1155ea0fe8955ffca71c32c3db82bacb1

Observation 0e5b8678-65a7-492e-9fb8-74ad0f2c2f1c · outbound

This paper cites Membership inference attacks against machine learning models.

Memorization in Graph Neural Networks Membership inference attacks against machine learning models

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:57.272780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:57.272780Z digest=sha256:027c9b288e10e2d678108c4311dfefcfeeb8e0a1b3b4edc5ac83a9e94bead65a

Observation 4ad4f228-bd30-4970-aa6f-406ff446aa63 · outbound

This paper cites Towards understanding generalization of graph neural networks.

Memorization in Graph Neural Networks Towards understanding generalization of graph neural networks

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:06.096498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:57.376107Z digest=sha256:099038cca7afe525ffa5f53d77a90233d257a9d14b3e8d7448f80d2411a03671

Observation 51850cc4-92e8-4db4-8cc0-04afdc54bee5 · outbound

This paper cites Bronstein.

Memorization in Graph Neural Networks Bronstein

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:05.608901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:57.493234Z digest=sha256:67f55941842dc8e86d9b3d03d935c773f0eb2c73e0c8a3cd683e2e841b32d16c

Observation 2b2cea8c-f514-4242-a8ae-c2b759b8ce1b · outbound

This paper cites Graph Attention Networks.

Memorization in Graph Neural Networks Graph Attention Networks

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:05.199623Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:57.595083Z digest=sha256:719a74ac5c81b5e934f619ddb80f0283e454a2902b1b418aa1cc8f28722b2523

Observation 8b903f9f-d5b4-4ca1-b1b1-224c17a21c4a · outbound

This paper cites Graph neural networks in particle physics.

Memorization in Graph Neural Networks Graph neural networks in particle physics

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:57.140213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:57.140213Z digest=sha256:95b5d433b53131e388209c97a51318ea15e48ca72a5ab10e3b09bb28a19965e5

Observation a1a0e9b9-8abf-43b8-be62-120bb45be956 · outbound

This paper cites A Manifold Perspective on the Statistical Generalization of Graph Neural Networks.

Memorization in Graph Neural Networks A Manifold Perspective on the Statistical Generalization of Graph Neural Networks

Reference 64

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:53:59.900314Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:57.949017Z digest=sha256:9bc29c5e84a95819cd3524260f0f10fb0b983029ec1d283498651f3fc59d05ae

Observation 5647f6ca-0b5c-454a-a883-50296a25b3a6 · outbound

This paper cites Simplifying graph convolutional networks.

Memorization in Graph Neural Networks Simplifying graph convolutional networks

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:04.483379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:58.216533Z digest=sha256:2f16c2f094ab279cff29763eb1e20d8971136ace1ceb156e51462f7b4281f67a

Observation 2e83f67b-8f99-40c9-8204-6ad84e385750 · outbound

This paper cites How graph neural networks learn: Lessons from training dynamics in function space, 2024.

Memorization in Graph Neural Networks How graph neural networks learn: Lessons from training dynamics in function space, 2024

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:04.168047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:58.379399Z digest=sha256:18017cf66173b65d1753079d95f4863a8cd3a3d42a798521699d4ccfc7f8e20a

Observation 79ba0b58-b477-4ff5-968b-7fb503f086e9 · outbound

This paper cites Understanding deep learning requires rethinking generalization.

Memorization in Graph Neural Networks Understanding deep learning requires rethinking generalization

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:03.820739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:58.600810Z digest=sha256:e0fa13b41d702e25d01b87d76e3c63e9e61d46e351deb8758dc1c6f0df64bfe6

Observation a08c7bd9-0559-4894-89b5-d44820b377f8 · outbound

This paper cites Memorization in self-supervised learning improves downstream generalization.

Memorization in Graph Neural Networks Memorization in self-supervised learning improves downstream generalization

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:04.842169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:57.776819Z digest=sha256:5198ccb360fd848d038e60d288a392c7519b12eec51f28cfbbafc851ebf1ce55

Observation f42514a7-9365-41eb-86e0-322a8f0cf943 · outbound

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

Memorization in Graph Neural Networks Be- yond homophily in graph neural networks: Current limitations and effective designs

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:03.493496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:58.785264Z digest=sha256:06a7791b344ce1dbf99aa4d5149ebaaf70e953d73e209e4c99f52e4432cef2d9

Observation e577da71-9499-4ab5-adc5-f0021cdf1a1b · outbound

This paper cites an unresolved cited work.

Memorization in Graph Neural Networks Unresolved cited work

Reference 74

Resolution
unresolved
raw_fallback, observed 2026-08-05T15:54:03.138915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:58.973355Z digest=sha256:0c4735b1229b10648b6437387197bfe720caba97e1b06d811d10803a239f0ec6

Observation c02dcdf5-beab-4cd5-bbc8-6324c46e7b02 · outbound

This paper cites an unresolved cited work.

Memorization in Graph Neural Networks Unresolved cited work

Reference 75

Resolution
unresolved
raw_fallback, observed 2026-08-05T15:54:02.760978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:59.168344Z digest=sha256:ace9c366838875aec8ea88c55982fe359f17959b474ce8d6489d716cf750d190

Observation bf839a4a-4644-4b89-b4bc-f4399689689c · outbound

This paper cites Inequality 10 states that γ must be greater than or equal to this large angle (δ − ϵ).

Memorization in Graph Neural Networks Inequality 10 states that γ must be greater than or equal to this large angle (δ − ϵ)

Reference 76

Resolution
malformed identifier
raw_fallback, observed 2026-08-05T15:54:02.387902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:59.316219Z digest=sha256:135d7eacf7231bbec2f4da294a4fe2cc6377c979773f4cfc8dbef4dd666239c8

Observation 3375b53a-6a4c-4c6e-88c0-933df55386f4 · outbound

This paper cites Our theoretical results in Section 4 demonstrate that one of the key factors influencing memorization in GNNs is the graph homophily.

Memorization in Graph Neural Networks Our theoretical results in Section 4 demonstrate that one of the key factors influencing memorization in GNNs is the graph homophily

Reference 77

Resolution
malformed identifier
raw_fallback, observed 2026-08-05T15:54:01.925640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:59.520306Z digest=sha256:4f207a41217eeaf3e609ef4192885a1a365d885a4c2e35e9894bf70e5b94b786

Observation 5f08ca9b-ceed-4c83-befe-26773f38c018 · outbound

This paper cites an unresolved cited work.

Memorization in Graph Neural Networks Unresolved cited work

Reference 2001

Resolution
unresolved
raw_fallback, observed 2026-08-05T15:54:15.853047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:50.215222Z digest=sha256:49405cfae3673f503a91e124cafba5c45d86bdd7c0f0c1c2d4157569ffd0d710

Observation d9470b05-5a76-4c75-b610-b59cde8f8470 · outbound

This paper cites URL https://proceedings.mlr.press/v9/glorot10a.html.

Memorization in Graph Neural Networks URL https://proceedings.mlr.press/v9/glorot10a.html

Reference 2010

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T15:54:13.578059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:51.800978Z digest=sha256:a25bb8a79e6127f68e33cf732e5eb67c5c86b32a426880560b446c6f13b95aa6

Observation 47f9c5ff-09b4-4383-83f2-708f6401f4d8 · outbound

This paper cites doi: 10.1038/s41598-018-29405-7.

Memorization in Graph Neural Networks doi: 10.1038/s41598-018-29405-7

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-05T15:53:53.230001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:53:53.230001Z digest=sha256:67a2b370a90e96eba18216728a81f55330d726e482425ee58b39e19f2e6e7911

Observation 44bb15bb-e1f3-41ca-8ff6-72f2b5db5ee6 · outbound

This paper cites k-hop Graph Neural Networks.

Memorization in Graph Neural Networks k-hop Graph Neural Networks

Reference 2020

Resolution
verified exact
local_arxiv, observed 2026-08-05T15:54:00.366113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-05T15:53:55.659437Z digest=sha256:451adc0ef88b2118f6f6138b69b5c5d537c4587464e8952ba3f3e4cfb6606c48

Pith citing papers

No inbound Pith citation observations are available.