Paper Citation Record · LEDGER

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective

As of 18 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2502.01272.

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

pith.paper-citation-record.v1
2502.01272 v3

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:57:30.040648Z

measured 32 of 32 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

32 of 32 outbound references displayed

verified exact0
verified fuzzy14
unresolved17
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9bb11ed7-3e07-4277-bc3a-1800331d73a2 · outbound

This paper cites Outlier aware network embed- ding for attributed networks.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Outlier aware network embed- ding for attributed networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.518154Z

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.

Observation 8284a48a-b780-4486-87bf-e67b8ab0e300 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective A simple framework for contrastive learning of visual representations

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.900517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6340717-15a8-45d5-8b3f-8abd80170815 · outbound

This paper cites Generative adversarial attributed network anomaly detection.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Generative adversarial attributed network anomaly detection

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.495896Z

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.

Observation d7677fcb-c5c0-4c41-b0d6-a749c4cb4794 · outbound

This paper cites Unnoticeable backdoor attacks on graph neural networks.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Unnoticeable backdoor attacks on graph neural networks

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.909469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb21aaa7-cdd9-4adf-9b34-1bcd491ce427 · outbound

This paper cites Deep anomaly detection on attributed networks.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Deep anomaly detection on attributed networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.913944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3dd15bd-236f-495e-ba1f-19707c09d058 · outbound

This paper cites A density-based algorithm for discovering clusters in large spatial databases with noise.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective A density-based algorithm for discovering clusters in large spatial databases with noise

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.919325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bcd470f1-9d66-4661-9b07-d05efa70da63 · outbound

This paper cites Graph neural networks for social recommendation.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Graph neural networks for social recommendation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.455732Z

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.

Observation 10a50fc7-2edd-4873-86f3-12f18b193c74 · outbound

This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Fast Graph Representation Learning with PyTorch Geometric

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.929511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14292f64-831e-466f-bb14-a5a1da40f9ad · outbound

This paper cites Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284, 2020.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Bootstrap your own latent-a new approach to self-supervised learning.Advances in neural information processing systems, 33:21271–21284, 2020

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.934085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51c9ed16-06c2-4eb1-bd1d-d1e90b529487 · outbound

This paper cites Inductive representation learning on large graphs.Advances in neural information processing systems, 30, 2017.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Inductive representation learning on large graphs.Advances in neural information processing systems, 30, 2017

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.938616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation faeb95be-5035-4e3d-b62c-372a40e27aec · outbound

This paper cites Algorithm as 136: A k-means clustering algorithm.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Algorithm as 136: A k-means clustering algorithm

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.422854Z

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.

Observation 2fb37c3d-c321-49a8-b14c-bff34743c30b · outbound

This paper cites Open graph benchmark: Datasets for machine learning on graphs.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Open graph benchmark: Datasets for machine learning on graphs

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.948720Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a554e14-6a97-42b2-aaa0-4ade868225cb · outbound

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

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Semi-Supervised Classification with Graph Convolutional Networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.953132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6e95907-40a8-4059-9e17-7fff28f92e92 · outbound

This paper cites Universal litmus patterns: Revealing backdoor attacks in cnns.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Universal litmus patterns: Revealing backdoor attacks in cnns

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.400027Z

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.

Observation 1a036ffc-4b78-439d-addd-176ed2339702 · outbound

This paper cites Anti-backdoor learning: Training clean models on poisoned data.Advances in Neural Information Processing Systems, 34:14900–14912, 2021.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Anti-backdoor learning: Training clean models on poisoned data.Advances in Neural Information Processing Systems, 34:14900–14912, 2021

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.386357Z

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.

Observation 54aadd03-81db-4ca5-9984-cf8692b0a5c8 · outbound

This paper cites Are defenses for graph neural networks robust?Advances in Neural Information Processing Systems, 35:8954–8968, 2022.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Are defenses for graph neural networks robust?Advances in Neural Information Processing Systems, 35:8954–8968, 2022

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.372623Z

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.

Observation d48709fb-7ad0-495c-ab50-288d4d98820c · outbound

This paper cites Representation Learning with Contrastive Predictive Coding.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Representation Learning with Contrastive Predictive Coding

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.970977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 935bd4f1-b303-47cd-b5ef-d81e1c821a68 · outbound

This paper cites Graph neural networks for intelligent transportation systems: A survey.IEEE Transactions on Intelligent Transportation Systems, 24(8):8846–8885, 2023.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Graph neural networks for intelligent transportation systems: A survey.IEEE Transactions on Intelligent Transportation Systems, 24(8):8846–8885, 2023

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.358981Z

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.

Observation 4848404a-fbc6-4c13-bf3c-093534d7dcb6 · outbound

This paper cites Collective classification in network data.AI magazine, 29(3):93–93, 2008.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Collective classification in network data.AI magazine, 29(3):93–93, 2008

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.980099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2896b1d2-b2af-4b4c-b43b-08ffa89fa1cc · outbound

This paper cites An overview of microsoft academic service (mas) and applications.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective An overview of microsoft academic service (mas) and applications

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.336205Z

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.

Observation 8795b833-6772-4698-aa83-bf412fd88c9b · outbound

This paper cites Graph attention networks.stat, 1050(20):10–48550, 2017.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Graph attention networks.stat, 1050(20):10–48550, 2017

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.989454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f66b4cf-8b1b-45ae-84f0-42e480248f2e · outbound

This paper cites Neural cleanse: Identifying and mitigating backdoor attacks in neural networks.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Neural cleanse: Identifying and mitigating backdoor attacks in neural networks

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:29.993961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ac9c4f1-bc44-4583-bb40-7e575c044933 · outbound

This paper cites Rab: Provable robustness against backdoor attacks.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Rab: Provable robustness against backdoor attacks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.304194Z

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.

Observation 38d839f4-f18a-44ce-a6df-4c3f3024a17e · outbound

This paper cites Graph backdoor.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Graph backdoor

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:30.002792Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 622e55e2-7726-4ea7-a072-1ed5b49abcf1 · outbound

This paper cites Contrastive attributed network anomaly detection with data augmentation.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Contrastive attributed network anomaly detection with data augmentation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:30.007131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c6db122-2660-4f01-8a39-4e89f8363819 · outbound

This paper cites GraphSAINT: Graph Sampling Based Inductive Learning Method.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective GraphSAINT: Graph Sampling Based Inductive Learning Method

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:30.011561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a46fac2c-ac50-4a66-8bf4-4ca2ee172037 · outbound

This paper cites Gnnguard: Defending graph neural networks against adversarial attacks.Advances in neural information processing systems, 33:9263–9275, 2020.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Gnnguard: Defending graph neural networks against adversarial attacks.Advances in neural information processing systems, 33:9263–9275, 2020

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.273286Z

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.

Observation 9c1061dd-6db3-4783-8447-179f00ef74a6 · outbound

This paper cites Backdoor attacks to graph neural networks.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Backdoor attacks to graph neural networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.259100Z

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.

Observation f67d4fa6-84c7-4324-8a16-8342e3d7f602 · outbound

This paper cites Rethinking graph backdoor attacks: A distribution-preserving perspective.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Rethinking graph backdoor attacks: A distribution-preserving perspective

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.245093Z

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.

Observation dcd5e8d2-fc32-43c9-a297-82707052d6e1 · outbound

This paper cites Robustness Inspired Graph Backdoor Defense.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Robustness Inspired Graph Backdoor Defense

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-09T15:57:30.030370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f7b2c2e7-2edc-4d12-a63e-bd89f33f6c1a · outbound

This paper cites Robust graph convolutional networks against adversarial attacks.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective Robust graph convolutional networks against adversarial attacks

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T15:57:30.230602Z

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.

Observation baefaa19-c863-4d49-b554-8911075597b0 · outbound

This paper cites successful defense.

Boosting Graph Robustness Against Backdoor Attacks: An Over-Similarity Perspective successful defense

Reference 32

Resolution: malformed identifier; no resolver link, observed 2026-08-09T15:57:30.040648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.