Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing | Paper Citation Record

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This paper cites Privacy and artificial intelligence,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Privacy and artificial intelligence,

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This paper cites An overview of artificial intelligence ethics,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing An overview of artificial intelligence ethics,

Reference 2

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This paper cites The right to be forgotten,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing The right to be forgotten,

Reference 3

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This paper cites 2018 reform of eu data protection rules,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing 2018 reform of eu data protection rules,

Reference 4

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This paper cites California consumer privacy act (ccpa),.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing California consumer privacy act (ccpa),

Reference 5

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This paper cites Artificial intelligence across europe: A study on awareness, attitude and trust,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Artificial intelligence across europe: A study on awareness, attitude and trust,

Reference 6

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This paper cites Inductive rep- resentation learning on large graphs,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Inductive rep- resentation learning on large graphs,

Reference 7

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This paper cites Scalable graph condensation with evolving capabilities,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Scalable graph condensation with evolving capabilities,

Reference 8

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This paper cites Graph convolutional neural networks for web-scale recommender systems,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Graph convolutional neural networks for web-scale recommender systems,

Reference 9

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This paper cites Molecular generative graph neural networks for drug discovery,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Molecular generative graph neural networks for drug discovery,

Reference 10

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This paper cites A review of graph neural networks in epidemic modeling,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing A review of graph neural networks in epidemic modeling,

Reference 11

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This paper cites Graph unlearning,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Graph unlearning,

Reference 12

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Observation 1a993085-4811-4f78-9ad0-fe014928f97f · outbound

This paper cites GNNDelete: A General Strategy for Unlearning in Graph Neural Networks.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing GNNDelete: A General Strategy for Unlearning in Graph Neural Networks

Reference 13

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This paper cites Grapheditor: An efficient graph representation learning and unlearning approach,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Grapheditor: An efficient graph representation learning and unlearning approach,

Reference 14

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This paper cites Com- bining neural networks with personalized pagerank for classification on graphs,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Com- bining neural networks with personalized pagerank for classification on graphs,

Reference 15

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This paper cites A survey on bias and fairness in machine learning,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing A survey on bias and fairness in machine learning,

Reference 16

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This paper cites Fairness through awareness,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fairness through awareness,

Reference 17

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This paper cites White admitted by stanford, black got rejections: Exploring racial stereotypes in text-to-image generation from a college admissions lens,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing White admitted by stanford, black got rejections: Exploring racial stereotypes in text-to-image generation from a college admissions lens,

Reference 18

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This paper cites Fairness in machine learning for health- care,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fairness in machine learning for health- care,

Reference 19

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This paper cites Why is my classifier discriminatory?.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Why is my classifier discriminatory?

Reference 20

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This paper cites Fairness in credit scoring: Assessment, implementation and profit implications,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fairness in credit scoring: Assessment, implementation and profit implications,

Reference 21

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This paper cites Fairness in criminal justice risk assessments: The state of the art,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fairness in criminal justice risk assessments: The state of the art,

Reference 22

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

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Gif: A general graph unlearning strategy via influence function,

Reference 23

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This paper cites Fairgraph: Automated graph debiasing with gradient matching,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fairgraph: Automated graph debiasing with gradient matching,

Reference 24

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This paper cites Equality of oppor- tunity in supervised learning,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Equality of oppor- tunity in supervised learning,

Reference 25

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This paper cites Fed- eraser: Enabling efficient client-level data removal from federated learning models,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fed- eraser: Enabling efficient client-level data removal from federated learning models,

Reference 26

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This paper cites Federated Unlearning with Knowledge Distillation.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Federated Unlearning with Knowledge Distillation

Reference 27

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This paper cites Inductive graph unlearning,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Inductive graph unlearning,

Reference 28

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This paper cites Machine unlearning,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Machine unlearning,

Reference 29

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This paper cites SAFE: Machine Unlearning With Shard Graphs.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing SAFE: Machine Unlearning With Shard Graphs

Reference 30

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This paper cites Fairness beyond disparate treatment & dis- parate impact: Learning classification without disparate mistreatment,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fairness beyond disparate treatment & dis- parate impact: Learning classification without disparate mistreatment,

Reference 31

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This paper cites Certifying and removing disparate impact,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Certifying and removing disparate impact,

Reference 32

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

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fair machine unlearning: Data removal while mitigating disparities,

Reference 33

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This paper cites FMP: Toward Fair Graph Message Passing against Topology Bias.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing FMP: Toward Fair Graph Message Passing against Topology Bias

Reference 34

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This paper cites Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark

Reference 35

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This paper cites Efficient model updates for approximate unlearning of graph-structured data,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Efficient model updates for approximate unlearning of graph-structured data,

Reference 36

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This paper cites Pri- vacy risk in machine learning: Analyzing the connection to overfitting,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Pri- vacy risk in machine learning: Analyzing the connection to overfitting,

Reference 37

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This paper cites Machine unlearning: A survey,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Machine unlearning: A survey,

Reference 38

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This paper cites Kernel Dependence Regularizers and Gaussian Processes with Applications to Algorithmic Fairness.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Kernel Dependence Regularizers and Gaussian Processes with Applications to Algorithmic Fairness

Reference 39

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

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Towards a unified framework for fair and stable graph representation learning,

Reference 40

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

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Say no to the discrimination: Learning fair graph neural networks with limited sen- sitive attribute information,

Reference 41

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

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Edits: Modeling and mitigating data bias for graph neural networks,

Reference 42

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This paper cites Stochastic methods for auc optimization subject to auc-based fairness constraints,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Stochastic methods for auc optimization subject to auc-based fairness constraints,

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This paper cites Learning fair graph representations via automated data augmenta- tions,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Learning fair graph representations via automated data augmenta- tions,

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This paper cites Mitigating unwanted biases with adversarial learning,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Mitigating unwanted biases with adversarial learning,

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This paper cites Fairness-aware classifier with prejudice remover regu- larizer,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fairness-aware classifier with prejudice remover regu- larizer,

Reference 46

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This paper cites Learn- ing adversarially fair and transferable representations,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Learn- ing adversarially fair and transferable representations,

Reference 47

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This paper cites A comprehensive survey on trustworthy graph neural networks: Privacy, robustness, fairness, and explainability. arxiv e-prints,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing A comprehensive survey on trustworthy graph neural networks: Privacy, robustness, fairness, and explainability. arxiv e-prints,

Reference 48

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

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Semi-Supervised Classification with Graph Convolutional Networks

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This paper cites TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing TinyGraph: Joint Feature and Node Condensation for Graph Neural Networks

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This paper cites Graph neural networks: A review of methods and applications,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Graph neural networks: A review of methods and applications,

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This paper cites Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Graph ODEs and Beyond: A Comprehensive Survey on Integrating Differential Equations with Graph Neural Networks

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This paper cites A review on machine unlearning,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing A review on machine unlearning,

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This paper cites A Survey of Machine Unlearning.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing A Survey of Machine Unlearning

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This paper cites Trustworthy machine learning and ar- tificial intelligence,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Trustworthy machine learning and ar- tificial intelligence,

Reference 55

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Observation 34df1771-2cd7-4f4d-843b-ad68c4663675 · outbound

This paper cites Strategic and business planning practices of fast growth family firms,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Strategic and business planning practices of fast growth family firms,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.271414Z

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This paper cites Charter of fundamental rights and general data protection regulation,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Charter of fundamental rights and general data protection regulation,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.245164Z

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Observation 13744bb8-359e-4cab-8bed-4d93d210ec79 · outbound

This paper cites On the privacy risks of al- gorithmic fairness,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing On the privacy risks of al- gorithmic fairness,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.227730Z

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This paper cites Data privacy and trustworthy machine learning,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Data privacy and trustworthy machine learning,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.210112Z

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This paper cites Fairsin: Achieving fairness in graph neural networks through sensitive in- formation neutralization,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fairsin: Achieving fairness in graph neural networks through sensitive in- formation neutralization,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.193124Z

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Observation 1b67cdf3-06d0-489a-80ba-9eaae0eaafe9 · outbound

This paper cites Link prediction techniques, applications, and performance: A survey,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Link prediction techniques, applications, and performance: A survey,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.172720Z

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This paper cites Link Prediction in Social Networks: the State-of-the-Art.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Link Prediction in Social Networks: the State-of-the-Art

Reference 62

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

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fairdrop: Biased edge dropout for enhancing fairness in graph representation learning,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.154865Z

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This paper cites Promoting fairness in link prediction with graph enhancement,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Promoting fairness in link prediction with graph enhancement,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.135358Z

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Observation a945eb40-b634-46fd-825c-1ff5507a24eb · outbound

This paper cites On dyadic fairness: Exploring and mitigating bias in graph connections,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing On dyadic fairness: Exploring and mitigating bias in graph connections,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.117679Z

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Observation 1e5a7e77-6b9c-430f-b99c-d8fa5ad9959d · outbound

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

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Towards effective and general graph unlearning via mutual evolution,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T21:31:26.095031Z

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This paper cites Automatic differentiation in pytorch,.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Automatic differentiation in pytorch,

Reference 67

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This paper cites Adam: A Method for Stochastic Optimization.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Adam: A Method for Stochastic Optimization

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-15T21:31:25.569769Z

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This paper cites Fast Graph Representation Learning with PyTorch Geometric.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Fast Graph Representation Learning with PyTorch Geometric

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-15T21:31:25.575730Z

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Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-15T21:31:26.060785Z

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Observation 6e5ce88f-245d-4284-b286-0bd90cd31475 · outbound

This paper cites TABLE VIII: The utility and fairness performances of FGU on German with sensitive attribute gender after unlearning.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing TABLE VIII: The utility and fairness performances of FGU on German with sensitive attribute gender after unlearning

Reference 71

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T21:31:26.042500Z

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Observation 05929ec7-7071-40fb-a7e6-0d6c440593b0 · outbound

This paper cites TABLE IX: The utility and fairness performances of FGU on German with sensitive attribute gender after unlearning.

Enabling Group Fairness in Graph Unlearning via Bi-level Debiasing TABLE IX: The utility and fairness performances of FGU on German with sensitive attribute gender after unlearning

Reference 72

Resolution: malformed identifier; raw_fallback, observed 2026-08-15T21:31:26.022071Z

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