Paper Citation Record · LEDGER

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting

As of 18 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2509.07456.

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

pith.paper-citation-record.v1
2509.07456 v1

Coverage vector

measured 29 of 29 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T22:15:59.451137Z

measured 29 of 29 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

29 of 29 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 33eca0da-79de-4da8-bb30-b717e2f04179 · outbound

This paper cites Recognition in terra incognita.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Recognition in terra incognita

Reference 1

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Observation 8cfbc781-9377-436e-892d-7b3ee554c33a · outbound

This paper cites Machine unlearning.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Machine unlearning

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.377038Z

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Observation dcda6723-e6ea-49e0-9dd6-5394cff28c47 · outbound

This paper cites Bird species categorization using pose normalized deep convolutional nets, 2014.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Bird species categorization using pose normalized deep convolutional nets, 2014

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.368489Z

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Observation 2f6a5bc2-87c3-4c08-b25d-18c90f7a8abf · outbound

This paper cites Gender shades: Inter- sectional accuracy disparities in commercial gender classifi- cation.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Gender shades: Inter- sectional accuracy disparities in commercial gender classifi- cation

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.359616Z

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Observation b08b8088-a19b-4905-a551-038b7ab8e6ee · outbound

This paper cites Building classifiers with independency constraints.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Building classifiers with independency constraints

Reference 5

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Observation 329a758b-0d5d-4e2a-92d9-1131686c1f9a · outbound

This paper cites When machine unlearn- ing jeopardizes privacy.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting When machine unlearn- ing jeopardizes privacy

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.342282Z

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Observation 7a140da0-6b7d-44ba-a0ac-522ccad271ff · outbound

This paper cites Fast model debias with machine un- learning.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Fast model debias with machine un- learning

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.333201Z

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Observation e898d739-8f17-4ee0-9022-ed70fed806fb · outbound

This paper cites Fairness and bias mitigation in com- puter vision: A survey, 2024.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Fairness and bias mitigation in com- puter vision: A survey, 2024

Reference 8

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Source-reported events for the cited work

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Observation cef38318-59fb-458e-b24b-869e2b4b5bd2 · outbound

This paper cites Can machine unlearning reduce social bias in lan- guage models? InEMNLP, pages 954–969, 2024.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Can machine unlearning reduce social bias in lan- guage models? InEMNLP, pages 954–969, 2024

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.314149Z

Source-reported events for the cited work

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Observation 64f05146-59ea-4825-95ef-e2f4b1f5dfb9 · outbound

This paper cites Shortcut learning in deep neural networks.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Shortcut learning in deep neural networks

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.303841Z

Source-reported events for the cited work

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Observation ad798171-f488-4517-aeb1-366a3225c1a6 · outbound

This paper cites Making ai forget you: Data deletion in ma- chine learning.NeurIPS, 2019.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Making ai forget you: Data deletion in ma- chine learning.NeurIPS, 2019

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.293426Z

Source-reported events for the cited work

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Observation c6d6c4a8-44a2-4c19-8a1e-036515d665b3 · outbound

This paper cites Equality of opportunity in supervised learning.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Equality of opportunity in supervised learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.283975Z

Source-reported events for the cited work

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Observation e48c1b5d-9d41-4ee7-861c-d20bce017d7a · outbound

This paper cites Deep residual learning for image recognition, 2015.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Deep residual learning for image recognition, 2015

Reference 13

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Observation eb4f2c6b-b726-48e3-9ee6-ecf583be14a2 · outbound

This paper cites SAP: corrective machine unlearning with scaled activation projection for label noise robustness.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting SAP: corrective machine unlearning with scaled activation projection for label noise robustness

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.265372Z

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Observation 1d4fa0c3-0c13-47c0-afbc-03f3f14c8053 · outbound

This paper cites ”alexa, can you forget me?” machine unlearn- ing benchmark in spoken language understanding, 2025.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting ”alexa, can you forget me?” machine unlearn- ing benchmark in spoken language understanding, 2025

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.256630Z

Source-reported events for the cited work

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Observation 42296f8e-2510-4ab8-8290-c25b5f6e3124 · outbound

This paper cites Towards unbounded machine unlearning.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Towards unbounded machine unlearning

Reference 16

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Observation bea4fcb6-0c42-4e6a-8fab-b7ae153564f2 · outbound

This paper cites Deep learning face attributes in the wild.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Deep learning face attributes in the wild

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.240231Z

Source-reported events for the cited work

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Observation f07cd2a5-70b5-4cbf-9a20-9798c3a2d6bd · outbound

This paper cites Breaking the trilemma of privacy, utility, and efficiency via controllable machine unlearning.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Breaking the trilemma of privacy, utility, and efficiency via controllable machine unlearning

Reference 18

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Observation c4ecf572-eece-453f-86af-1395815d6ecb · outbound

This paper cites A survey on bias and fairness in machine learning.ACM computing surveys (CSUR), 54 (6):1–35, 2021.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting A survey on bias and fairness in machine learning.ACM computing surveys (CSUR), 54 (6):1–35, 2021

Reference 19

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Observation 1459218d-c89d-4eb4-be6d-5d0fa3cb28a5 · outbound

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

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Fair machine unlearning: Data removal while mitigating disparities

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.208890Z

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Observation 08220908-aa03-49cb-b63a-adff2d411491 · outbound

This paper cites Smith, and Chiyuan Zhang.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Smith, and Chiyuan Zhang

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.198420Z

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Observation e359542d-26c7-4973-a3e3-62372008699a · outbound

This paper cites Don’t judge an object by its context: learning to overcome contex- tual bias.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Don’t judge an object by its context: learning to overcome contex- tual bias

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.188621Z

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Observation 5c112e8d-fc17-4fbf-b347-839911f5295f · outbound

This paper cites Unrolling SGD: Understanding Factors Influencing Machine Unlearning.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Unrolling SGD: Understanding Factors Influencing Machine Unlearning

Reference 23

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Observation ac769f17-4298-4234-95d3-a9f91b870d31 · outbound

This paper cites Unbiased look at dataset bias.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Unbiased look at dataset bias

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.179751Z

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Observation af4b423c-65f0-4508-8275-699673b09af5 · outbound

This paper cites To- wards fairness in visual recognition: Effective strategies for bias mitigation.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting To- wards fairness in visual recognition: Effective strategies for bias mitigation

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.170468Z

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Observation ebae3657-831a-4ffd-b1c4-713a6d1d3275 · outbound

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

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Don’t forget too much: Towards machine unlearning on feature level.IEEE Trans

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.161221Z

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Observation b2442fe0-953a-4b72-bdb9-1db9b610a99f · outbound

This paper cites Facts: First amplify correlations and then slice to discover bias, 2023.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Facts: First amplify correlations and then slice to discover bias, 2023

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.151261Z

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Observation a5e203fb-20a0-444d-a7bc-1baa6cbec32e · outbound

This paper cites Mitigating unwanted biases with adversarial learning.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Mitigating unwanted biases with adversarial learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:16:00.080452Z

Source-reported events for the cited work

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Observation 7872a33c-e6f2-4935-b830-b4701a1c2402 · outbound

This paper cites Geniu: A restricted data access unlearn- ing for imbalanced data, 2024.

Bias-Aware Machine Unlearning: Towards Fairer Vision Models via Controllable Forgetting Geniu: A restricted data access unlearn- ing for imbalanced data, 2024

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-04T22:15:59.922154Z

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.

Pith citing papers

No inbound Pith citation observations are available.