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Paper Citation Record · LEDGER

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms

As of 10 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.14607.

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

pith.paper-citation-record.v1
2607.14607 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T01:41:47.188111Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

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Outbound references

Observation 2a645162-f59b-4456-9c02-f57f26179ef7 · outbound

This paper cites Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Brendan McMahan, Ilya Mironov, Kunal Talwar, and Li Zhang

Reference 1

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Observation 8e4dfac0-2099-4361-96ae-f9852bc36eb7 · outbound

This paper cites A reductions approach to fair classification.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms A reductions approach to fair classification

Reference 2

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Observation 5dffd72c-46f6-460f-a638-649ed7529926 · outbound

This paper cites Aithal and R.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Aithal and R

Reference 3

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Observation 9521c666-32c9-46b2-9a8a-81cee98cf28e · outbound

This paper cites Evaluating marketing campaigns of banking using neural networks.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Evaluating marketing campaigns of banking using neural networks

Reference 4

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Observation 3fe57218-5dfe-41bb-b08b-2d5d6cb64230 · outbound

This paper cites Differential privacy has disparate impact on model accuracy.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Differential privacy has disparate impact on model accuracy

Reference 5

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Observation 56312e5d-88eb-41d8-907d-6f2389f4b5a1 · outbound

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Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Unresolved cited work

Reference 6

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Observation e9271a22-e714-42d6-9109-0f60c2954a3b · outbound

This paper cites Evaluating the Fairness Impact of Differentially Private Synthetic Data.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Evaluating the Fairness Impact of Differentially Private Synthetic Data

Reference 7

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Observation ed86f7bc-337d-4a25-8bb0-6b6621ad5aae · outbound

This paper cites Membership inference attacks from first principles.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Membership inference attacks from first principles

Reference 8

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Observation 0adc0b74-03b7-49f8-99c1-d127bef59143 · outbound

This paper cites On the Privacy Risks of Algorithmic Fairness.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms On the Privacy Risks of Algorithmic Fairness

Reference 9

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Observation 7edf9aa8-cc6d-4b7b-9f9d-babd017d5d4f · outbound

This paper cites Chawla, Kevin W.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Chawla, Kevin W

Reference 10

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Observation 57a8027d-4ce1-47c8-8961-fe8249102841 · outbound

This paper cites Residuals and influence in regression.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Residuals and influence in regression

Reference 11

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Observation 96f0abf6-ac50-40b8-97db-ec7551c4124d · outbound

This paper cites The accuracy, fairness, and limits of predicting recidivism.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms The accuracy, fairness, and limits of predicting recidivism

Reference 12

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Observation 9895a2de-92ad-457b-b145-874c45381a54 · outbound

This paper cites Fairness via Representation Neutralization.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Fairness via Representation Neutralization

Reference 13

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Observation 04c5ec61-3eab-4099-b87c-82153dcb2828 · outbound

This paper cites Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian

Reference 14

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Observation 4bf43eea-9901-4d22-83a9-9ccee3d468db · outbound

This paper cites Does learning require memorization? a short tale about a long tail, 2021.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Does learning require memorization? a short tale about a long tail, 2021

Reference 15

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Observation e2d4cab6-86cf-4a12-800d-62fd9da41d54 · outbound

This paper cites Whatneuralnetworks memorize and why: Discovering the long tail via influence estimation.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Whatneuralnetworks memorize and why: Discovering the long tail via influence estimation

Reference 16

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Observation 376a3656-c61c-4bc4-ac44-809a58d2cd5e · outbound

This paper cites Differential privacy and fairness in deci- sions and learning tasks: A survey.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Differential privacy and fairness in deci- sions and learning tasks: A survey

Reference 17

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Observation 24747e6f-cc29-45da-abc3-cb4ce8722340 · outbound

This paper cites Decision making with differential privacy under a fairness lens, 2024.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Decision making with differential privacy under a fairness lens, 2024

Reference 18

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Observation 081d9885-fe65-4c11-9ddc-f609a5376b73 · outbound

This paper cites Why do tree-based models still outperform deep learning on typical tabular data? In Advances in Neural Information Processing Systems, volume 35, pages 507–520, 2022.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Why do tree-based models still outperform deep learning on typical tabular data? In Advances in Neural Information Processing Systems, volume 35, pages 507–520, 2022

Reference 19

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Observation fab21cf2-5e6c-48f4-9239-edda4176b22a · outbound

This paper cites Robuststatistics:theapproachbased on influence functions.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Robuststatistics:theapproachbased on influence functions

Reference 20

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Observation 02820d12-bf72-4ccd-93a8-801b2e010cfb · outbound

This paper cites The impact of differential privacy on group disparity mitigation.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms The impact of differential privacy on group disparity mitigation

Reference 21

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Observation 2a404d6d-2cb3-4b2a-a179-a099b285ce3e · outbound

This paper cites Diffprivlib: The IBM Differential Privacy Library.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Diffprivlib: The IBM Differential Privacy Library

Reference 22

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Observation 44469d99-a8f8-45f3-b171-714e059ab731 · outbound

This paper cites Differentially private fair learning.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Differentially private fair learning

Reference 23

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Observation 5b6c2f5b-6b1f-4565-a36e-c78291a30b2b · outbound

This paper cites Datapreprocessingtech- niques for classification without discrimination.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Datapreprocessingtech- niques for classification without discrimination

Reference 24

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Observation a83e6ca8-8a35-4374-9328-967aef063488 · outbound

This paper cites Understanding black- box predictions via influence functions.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Understanding black- box predictions via influence functions

Reference 25

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Observation 61888f5c-4863-49b3-b948-5ddd0502b5bb · outbound

This paper cites Disparate vulnerability to membership inference attacks.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Disparate vulnerability to membership inference attacks

Reference 26

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Observation 448356cb-0c8b-4812-b4b1-1c285ab03bde · outbound

This paper cites Arcolezi, and Catuscia Palamidessi.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Arcolezi, and Catuscia Palamidessi

Reference 27

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Observation e41c4d78-70ec-476e-ab0f-963e530bb33b · outbound

This paper cites Differential privacy has bounded impact on fairness in classification, 2023.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Differential privacy has bounded impact on fairness in classification, 2023

Reference 28

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Observation ecd1ff98-2e9b-41f3-9730-1ff843bf2942 · outbound

This paper cites ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms ML Privacy Meter: Aiding Regulatory Compliance by Quantifying the Privacy Risks of Machine Learning

Reference 29

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Observation 0136a617-be9e-4b44-ac5a-e49942883f4a · outbound

This paper cites Increasing the views and reducing the depth in random forest.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Increasing the views and reducing the depth in random forest

Reference 30

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Observation f6393eeb-7d44-4826-befc-ac6a9047f417 · outbound

This paper cites A comprehensive sustainable framework for machine learning and artificial intelligence, 2024.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms A comprehensive sustainable framework for machine learning and artificial intelligence, 2024

Reference 31

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Observation 0a50ebf8-d591-44e6-b6ac-39aaa27234db · outbound

This paper cites Weinberger.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Weinberger

Reference 32

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Observation 18429d41-7a43-4a7a-8f6e-5630df5a3fb1 · outbound

This paper cites Understanding MachineLearning:FromTheorytoAlgorithms.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Understanding MachineLearning:FromTheorytoAlgorithms

Reference 33

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Observation 7ef5218d-41be-46c1-a972-f7819ccce87b · outbound

This paper cites When fairness meets pri- vacy: Exploring privacy threats in fair binary classifiers via membership inference attacks.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms When fairness meets pri- vacy: Exploring privacy threats in fair binary classifiers via membership inference attacks

Reference 34

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Observation df87a2a1-503b-423c-9ba1-c206e5e04be4 · outbound

This paper cites Dinh, and Ferdinando Fioretto.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Dinh, and Ferdinando Fioretto

Reference 35

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Observation e514350c-6c8d-4262-b309-674080710ca8 · outbound

This paper cites Effectsofdifferentialprivacyanddataskewness on membership inference vulnerability.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Effectsofdifferentialprivacyanddataskewness on membership inference vulnerability

Reference 36

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Observation 2505cd46-c9bc-4dfc-a75b-77daf1f31b2a · outbound

This paper cites Disparate Vulnerability to Membership Inference Attacks.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Disparate Vulnerability to Membership Inference Attacks

Reference 37

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Observation f998a0fa-13fc-40b8-b8dc-af9caebf2e5d · outbound

This paper cites Privacy risk in machine learning: Analyzing the connection to overfitting.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Privacy risk in machine learning: Analyzing the connection to overfitting

Reference 38

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Observation 19d4da5f-0b2d-4529-a4c9-d58a63af72cf · outbound

This paper cites Understanding disparate effects of membership inference attacks and their countermeasures.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Understanding disparate effects of membership inference attacks and their countermeasures

Reference 39

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Observation f0070d5c-e82a-425a-822c-a773080ab165 · outbound

This paper cites On Improving Fairness of AI Models with Synthetic Minority Oversampling Techniques, pages 874–882.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms On Improving Fairness of AI Models with Synthetic Minority Oversampling Techniques, pages 874–882

Reference 40

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Observation 4f4f9422-e7fb-4578-abd5-06952390e9d5 · outbound

This paper cites an unresolved cited work.

Auditing Fairness-Privacy Trade-offs: Subpopulation-Level Effects of Fairness-Enhancing Algorithms Unresolved cited work

Reference 2891

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