Unlearning Algorithmic Biases over Graphs | Paper Citation Record

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This paper cites Uk biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age,.

Unlearning Algorithmic Biases over Graphs Uk biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age,

Reference 1

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This paper cites Making AI forget you: Data deletion in machine learning,.

Unlearning Algorithmic Biases over Graphs Making AI forget you: Data deletion in machine learning,

Reference 2

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This paper cites What is GDPR, the EU’s new data protecion law?.

Unlearning Algorithmic Biases over Graphs What is GDPR, the EU’s new data protecion law?

Reference 3

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This paper cites Remember what you want to forget: Algorithms for machine unlearning,.

Unlearning Algorithmic Biases over Graphs Remember what you want to forget: Algorithms for machine unlearning,

Reference 4

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This paper cites Certified data removal from machine learning models,.

Unlearning Algorithmic Biases over Graphs Certified data removal from machine learning models,

Reference 5

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This paper cites Machine unlearning,.

Unlearning Algorithmic Biases over Graphs Machine unlearning,

Reference 6

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This paper cites Approximate data deletion from machine learning models,.

Unlearning Algorithmic Biases over Graphs Approximate data deletion from machine learning models,

Reference 7

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This paper cites Descent-to-delete: Gradient-based methods for machine unlearning,.

Unlearning Algorithmic Biases over Graphs Descent-to-delete: Gradient-based methods for machine unlearning,

Reference 8

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This paper cites Graph representation learning,.

Unlearning Algorithmic Biases over Graphs Graph representation learning,

Reference 9

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This paper cites GIF: A general graph unlearning strategy via influence function,.

Unlearning Algorithmic Biases over Graphs GIF: A general graph unlearning strategy via influence function,

Reference 10

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This paper cites Certified graph unlearning,.

Unlearning Algorithmic Biases over Graphs Certified graph unlearning,

Reference 11

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This paper cites Certified edge unlearning for graph neural networks,.

Unlearning Algorithmic Biases over Graphs Certified edge unlearning for graph neural networks,

Reference 12

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This paper cites IDEA: A flexible framework of certified unlearning for graph neural networks,.

Unlearning Algorithmic Biases over Graphs IDEA: A flexible framework of certified unlearning for graph neural networks,

Reference 13

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Observation e501634f-a9a3-4573-b9e9-3f4c8f4efb7a · outbound

This paper cites Unlearning graph classifiers with limited data resources,.

Unlearning Algorithmic Biases over Graphs Unlearning graph classifiers with limited data resources,

Reference 14

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This paper cites Say no to the discrimination: Learning fair graph neural networks with limited sensitive attribute information,.

Unlearning Algorithmic Biases over Graphs Say no to the discrimination: Learning fair graph neural networks with limited sensitive attribute information,

Reference 15

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This paper cites Fairness in graph mining: A survey,.

Unlearning Algorithmic Biases over Graphs Fairness in graph mining: A survey,

Reference 16

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Observation 53c2f018-c84a-46f9-921a-3a0f8f38ce61 · outbound

This paper cites Fast model debias with machine unlearning,.

Unlearning Algorithmic Biases over Graphs Fast model debias with machine unlearning,

Reference 17

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Observation 00d1b7fe-0b17-4c07-87c3-5453ef46290f · outbound

This paper cites Debayes: A Bayesian method for debiasing network embeddings,.

Unlearning Algorithmic Biases over Graphs Debayes: A Bayesian method for debiasing network embeddings,

Reference 18

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Observation 753b47ed-d2cd-4b20-95bc-4c37a0b38c33 · outbound

This paper cites Compositional fairness constraints for graph embeddings,.

Unlearning Algorithmic Biases over Graphs Compositional fairness constraints for graph embeddings,

Reference 19

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Observation 09282eb9-65af-410a-933d-97000e86f36a · outbound

This paper cites Towards a unified framework for fair and stable graph representation learning,.

Unlearning Algorithmic Biases over Graphs Towards a unified framework for fair and stable graph representation learning,

Reference 20

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This paper cites Demystifying and mitigating bias for node representation learning,.

Unlearning Algorithmic Biases over Graphs Demystifying and mitigating bias for node representation learning,

Reference 21

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This paper cites Fairdrop: Biased edge dropout for en- hancing fairness in graph representation learning,.

Unlearning Algorithmic Biases over Graphs Fairdrop: Biased edge dropout for en- hancing fairness in graph representation learning,

Reference 22

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This paper cites Graph unlearning,.

Unlearning Algorithmic Biases over Graphs Graph unlearning,

Reference 23

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This paper cites Inductive graph unlearning,.

Unlearning Algorithmic Biases over Graphs Inductive graph unlearning,

Reference 24

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Observation 0f14dfd2-1752-4a0b-8d46-b3c6d67e38d2 · outbound

This paper cites Graph unlearning with efficient partial retraining,.

Unlearning Algorithmic Biases over Graphs Graph unlearning with efficient partial retraining,

Reference 25

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Observation ec4581a9-7945-483a-ac6b-2acf1bc0d5e2 · outbound

This paper cites GNNDelete: A general strategy for unlearning in graph neural networks,.

Unlearning Algorithmic Biases over Graphs GNNDelete: A general strategy for unlearning in graph neural networks,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:06.974507Z

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This paper cites Towards effective and general graph unlearning via mutual evolution,.

Unlearning Algorithmic Biases over Graphs Towards effective and general graph unlearning via mutual evolution,

Reference 27

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Observation caf9101b-4002-48ca-947f-8b9da40fed49 · outbound

This paper cites Toward Scalable Graph Unlearning: A Node Influence Maximization based Approach.

Unlearning Algorithmic Biases over Graphs Toward Scalable Graph Unlearning: A Node Influence Maximization based Approach

Reference 28

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Observation 9f05ad0e-8bd9-4748-bf6a-fb9ed0133a31 · outbound

This paper cites Distill to Delete: Unlearning in Graph Networks with Knowledge Distillation.

Unlearning Algorithmic Biases over Graphs Distill to Delete: Unlearning in Graph Networks with Knowledge Distillation

Reference 29

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Observation 5a2c73ea-ce1b-4903-943a-dcc98827a67a · outbound

This paper cites When contrastive learning meets graph unlearning: Graph contrastive unlearning for link prediction,.

Unlearning Algorithmic Biases over Graphs When contrastive learning meets graph unlearning: Graph contrastive unlearning for link prediction,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:06.485261Z

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This paper cites Efficiently forgetting what you have learned in graph representation learning via projection,.

Unlearning Algorithmic Biases over Graphs Efficiently forgetting what you have learned in graph representation learning via projection,

Reference 31

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Observation 8b218b09-17dd-4104-bca2-d3cc8d2ef98e · outbound

This paper cites A Survey on Fairness for Machine Learning on Graphs.

Unlearning Algorithmic Biases over Graphs A Survey on Fairness for Machine Learning on Graphs

Reference 32

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Source-reported events for the cited work

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This paper cites Fairness in graph machine learning: Recent advances and future prospectives,.

Unlearning Algorithmic Biases over Graphs Fairness in graph machine learning: Recent advances and future prospectives,

Reference 33

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This paper cites Fairwalk: Towards fair graph embedding,.

Unlearning Algorithmic Biases over Graphs Fairwalk: Towards fair graph embedding,

Reference 34

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This paper cites Debiasing graph representations via metadata-orthogonal train- ing,.

Unlearning Algorithmic Biases over Graphs Debiasing graph representations via metadata-orthogonal train- ing,

Reference 35

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This paper cites Individual fairness for graph neural networks: A ranking based approach,.

Unlearning Algorithmic Biases over Graphs Individual fairness for graph neural networks: A ranking based approach,

Reference 36

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This paper cites GUIDE: Group equality informed individual fairness in graph neural networks,.

Unlearning Algorithmic Biases over Graphs GUIDE: Group equality informed individual fairness in graph neural networks,

Reference 37

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This paper cites Learning fair node representations with graph counterfactual fairness,.

Unlearning Algorithmic Biases over Graphs Learning fair node representations with graph counterfactual fairness,

Reference 38

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This paper cites Towards fair graph neural networks via graph counterfactual,.

Unlearning Algorithmic Biases over Graphs Towards fair graph neural networks via graph counterfactual,

Reference 39

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This paper cites EDITS: Modeling and mitigating data bias for graph neural networks,.

Unlearning Algorithmic Biases over Graphs EDITS: Modeling and mitigating data bias for graph neural networks,

Reference 40

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This paper cites Fair contrastive learning on graphs,.

Unlearning Algorithmic Biases over Graphs Fair contrastive learning on graphs,

Reference 41

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This paper cites Debiasing knowledge graph embeddings,.

Unlearning Algorithmic Biases over Graphs Debiasing knowledge graph embeddings,

Reference 42

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Observation 60310e84-2779-4e9f-8d6c-0d1634fda650 · outbound

This paper cites Learning fair representations via distance correlation minimization,.

Unlearning Algorithmic Biases over Graphs Learning fair representations via distance correlation minimization,

Reference 43

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Observation c663351c-eb54-4f8e-9bc0-b27b5658b053 · outbound

This paper cites Endowing pre-trained graph models with provable fairness,.

Unlearning Algorithmic Biases over Graphs Endowing pre-trained graph models with provable fairness,

Reference 44

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This paper cites Bursting the filter bubble: Fairness-aware network link prediction,.

Unlearning Algorithmic Biases over Graphs Bursting the filter bubble: Fairness-aware network link prediction,

Reference 45

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This paper cites Inform: Individual fairness on graph mining,.

Unlearning Algorithmic Biases over Graphs Inform: Individual fairness on graph mining,

Reference 46

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This paper cites Machine unlearning: Taxonomy, metrics, applications, challenges, and prospects,.

Unlearning Algorithmic Biases over Graphs Machine unlearning: Taxonomy, metrics, applications, challenges, and prospects,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:02.367073Z

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Observation e91be522-4937-4e21-993b-c698fa3b7e4b · outbound

This paper cites Fair machine unlearning: Data removal while mitigating disparities,.

Unlearning Algorithmic Biases over Graphs Fair machine unlearning: Data removal while mitigating disparities,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:02.124305Z

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Observation e550ef8a-cebf-4ff2-8639-fc6ca4db2771 · outbound

This paper cites To be forgotten or to be fair: Unveiling fairness implications of machine unlearning methods,.

Unlearning Algorithmic Biases over Graphs To be forgotten or to be fair: Unveiling fairness implications of machine unlearning methods,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:01.887054Z

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Observation fabf32c6-c2cb-4396-813f-4bf23fb407d8 · outbound

This paper cites Exploring Fairness in Educational Data Mining in the Context of the Right to be Forgotten.

Unlearning Algorithmic Biases over Graphs Exploring Fairness in Educational Data Mining in the Context of the Right to be Forgotten

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-08-07T15:33:57.781246Z

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This paper cites Can machine unlearning reduce social bias in language models?.

Unlearning Algorithmic Biases over Graphs Can machine unlearning reduce social bias in language models?

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:01.636938Z

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Observation 8471c040-e761-4e6d-9dd1-ea32666d63a3 · outbound

This paper cites FROG: Fair removal on graphs,.

Unlearning Algorithmic Biases over Graphs FROG: Fair removal on graphs,

Reference 52

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Source-reported events for the cited work

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This paper cites Simplifying graph convolutional networks,.

Unlearning Algorithmic Biases over Graphs Simplifying graph convolutional networks,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:01.344755Z

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Observation 62c5aacc-1766-4e2e-b0cc-ee1c394c735e · outbound

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

Unlearning Algorithmic Biases over Graphs Semi-supervised classification with graph convolutional networks,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:01.079192Z

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Observation 11b732e2-750f-43b1-a6b6-477a7df1cb26 · outbound

This paper cites Improving fairness in graph neural networks via mitigating sensitive attribute leakage,.

Unlearning Algorithmic Biases over Graphs Improving fairness in graph neural networks via mitigating sensitive attribute leakage,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:00.773574Z

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 2f495262-edee-4af1-a5d2-f7aaf0f68dc1 · outbound

This paper cites Machine Unlearning of Features and Labels.

Unlearning Algorithmic Biases over Graphs Machine Unlearning of Features and Labels

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-07T15:33:56.283886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c1cac917-6af3-4e25-9c58-e9dde1558057 · outbound

This paper cites Don’t forget too much: Towards machine unlearning on feature level,.

Unlearning Algorithmic Biases over Graphs Don’t forget too much: Towards machine unlearning on feature level,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:00.551842Z

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 d47ad4d2-4164-4c1c-8c4b-4cac0369d377 · outbound

This paper cites Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations.

Unlearning Algorithmic Biases over Graphs Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-07T15:33:56.510740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fb24845-dc9a-4b9c-bd99-d18a15d51bf6 · outbound

This paper cites Post-training attribute unlearning in recommender systems,.

Unlearning Algorithmic Biases over Graphs Post-training attribute unlearning in recommender systems,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:34:00.324961Z

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 fd43898f-0f1b-4ad7-91fb-2b66e5a9d2a8 · outbound

This paper cites Towards fair classifiers without sensitive attributes: Exploring biases in related features,.

Unlearning Algorithmic Biases over Graphs Towards fair classifiers without sensitive attributes: Exploring biases in related features,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:33:59.982160Z

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 ce4bc929-7ea4-40f0-8166-0455b483ef5c · outbound

This paper cites Fairness through awareness,.

Unlearning Algorithmic Biases over Graphs Fairness through awareness,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:33:59.740184Z

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 6d9067fc-da0c-4ac3-ba0b-ca59cf282526 · outbound

This paper cites Thirteen ways to look at the correlation coefficient,.

Unlearning Algorithmic Biases over Graphs Thirteen ways to look at the correlation coefficient,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:33:59.539818Z

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 35513a2a-8bea-4e57-8e30-d376528a5e9e · outbound

This paper cites On Convergence and Stability of GANs.

Unlearning Algorithmic Biases over Graphs On Convergence and Stability of GANs

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T15:33:57.042194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da9f7466-45a4-4280-aa98-0cb9d1333132 · outbound

This paper cites Towards a unified framework for fair and stable graph representation learning,.

Unlearning Algorithmic Biases over Graphs Towards a unified framework for fair and stable graph representation learning,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:33:59.280771Z

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 e38b0fb5-410b-48b6-b6d3-4e35db16cfa6 · outbound

This paper cites GNNExplainer: Generating explanations for graph neural networks,.

Unlearning Algorithmic Biases over Graphs GNNExplainer: Generating explanations for graph neural networks,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:33:59.052981Z

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 efa9a5c0-69ce-4381-92af-cf86af718ce4 · outbound

This paper cites On the limited memory BFGS method for large scale optimization,.

Unlearning Algorithmic Biases over Graphs On the limited memory BFGS method for large scale optimization,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:33:58.844042Z

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 4a38c2d8-92f9-47a5-8349-e2d931f824fd · outbound

This paper cites ℓ′ ˜z⊤ i w∗, yi [ ¯Al]ij dl i #2 σ2 ≤ ol ≤ 5 L + 1 vuuut X vi∈Vtr X vj ∈Nl(vi).

Unlearning Algorithmic Biases over Graphs ℓ′ ˜z⊤ i w∗, yi [ ¯Al]ij dl i #2 σ2 ≤ ol ≤ 5 L + 1 vuuut X vi∈Vtr X vj ∈Nl(vi)

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T15:33:58.554983Z

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.

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