Paper Citation Record · LEDGER

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes

As of 15 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 2 inbound Pith citation observations for arXiv:2501.12020.

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

pith.paper-citation-record.v1
2501.12020 v2

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:41:10.283520Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T12:38:43.041140Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T18:16:16.850658Z

Reference resolution

56 of 56 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5f663fdb-00a7-4f67-9541-0390eea70989 · outbound

This paper cites Are face recognition systems accurate? Depends on your race,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Are face recognition systems accurate? Depends on your race,

Reference 1

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Observation 495af78d-6a5e-4192-ab40-205faca2dbb0 · outbound

This paper cites Facial recognition is accurate, if you’re a white guy,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Facial recognition is accurate, if you’re a white guy,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.538464Z

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Observation af24885b-a621-4ed3-848e-20482c08a125 · outbound

This paper cites Racist and sexist’facial recognition cam- eras could lead to false arrests,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Racist and sexist’facial recognition cam- eras could lead to false arrests,

Reference 3

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Observation c3046e47-8e2b-42df-bbbe-aeb9e5b2865d · outbound

This paper cites Is facial recognition too biased to be let loose?.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Is facial recognition too biased to be let loose?

Reference 4

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Observation 7159b0d8-613e-40e9-a236-23093ebbd007 · outbound

This paper cites Emerging from ai utopia,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Emerging from ai utopia,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.440558Z

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Observation d5ac0d2f-39a5-449e-80dc-79f5c6975af9 · outbound

This paper cites Face Recognition Performance: Role of Demographic Information,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Face Recognition Performance: Role of Demographic Information,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.413560Z

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Observation 84cc5182-2d3f-43a8-9879-079caf374e73 · outbound

This paper cites An other-race effect for face recognition algorithms,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes An other-race effect for face recognition algorithms,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.390659Z

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Observation 5c78999a-d2b5-4aa1-8a94-d893679f6e99 · outbound

This paper cites Grother, M.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Grother, M

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.369685Z

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Observation b5ac9ac2-3aea-4e35-8f18-228bb1c7c48d · outbound

This paper cites The gender gap in face recognition accuracy is a hairy problem,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes The gender gap in face recognition accuracy is a hairy problem,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.349528Z

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Observation b4e0e3cd-727e-4047-976a-a84c9e73666f · outbound

This paper cites A Com- prehensive Study on Face Recognition Biases Beyond Demographics,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes A Com- prehensive Study on Face Recognition Biases Beyond Demographics,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.328835Z

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Observation bb4ed436-6918-4b7d-a4cf-2f0dba200986 · outbound

This paper cites Comparison-Level Mitigation of Ethnic Bias in Face Recognition,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Comparison-Level Mitigation of Ethnic Bias in Face Recognition,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.310635Z

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Observation 1bb5119c-34df-4480-ae08-243e28135a2f · outbound

This paper cites Demographic bias in biometric systems: Current research and applicable standards,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Demographic bias in biometric systems: Current research and applicable standards,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.289431Z

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Observation 6a5da296-7042-4920-9da2-5c76b75a19c4 · outbound

This paper cites Analysis of Gender Inequality In Face Recognition Accuracy,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Analysis of Gender Inequality In Face Recognition Accuracy,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.272003Z

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Observation ae0a3c88-1367-4d14-830d-f0ea090e18de · outbound

This paper cites How Does Gender Balance In Training Data Affect Face Recog- nition Accuracy?.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes How Does Gender Balance In Training Data Affect Face Recog- nition Accuracy?

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.254747Z

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Observation 2aebeae1-cf05-45ee-ae22-c3bcd4415312 · outbound

This paper cites Logical consistency and greater descriptive power for facial hair attribute learning,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Logical consistency and greater descriptive power for facial hair attribute learning,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.235709Z

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Observation 2fecb306-d4a6-42ee-a155-12f531122e4d · outbound

This paper cites Facial Hair area in face recognition across demographics: Small size, big Effect,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Facial Hair area in face recognition across demographics: Small size, big Effect,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.213305Z

Source-reported events for the cited work

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Observation c6c801ef-8946-48b9-930e-4a86a276faf7 · outbound

This paper cites Gendered differences in face recognition accuracy ex- plained by hairstyles, makeup, and facial morphology,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Gendered differences in face recognition accuracy ex- plained by hairstyles, makeup, and facial morphology,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.188418Z

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Observation bbf5c3bd-c03f-4db1-a419-64c3bc2d91d2 · outbound

This paper cites Face recognition accuracy across demographics: Shining a light into the problem,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Face recognition accuracy across demographics: Shining a light into the problem,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.159826Z

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Observation 615f6d97-5544-414c-b758-f34464d51928 · outbound

This paper cites Is Face Recognition Sexist? No, Gendered Hairstyles and Biology Are,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Is Face Recognition Sexist? No, Gendered Hairstyles and Biology Are,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.131515Z

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Observation f1628f97-e819-44fe-9ad8-565ad04361ef · outbound

This paper cites On soft-biometric information stored in biometric face embeddings,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes On soft-biometric information stored in biometric face embeddings,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.106183Z

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Observation f9dbb997-d8ac-4c28-9199-62dc94647bc0 · outbound

This paper cites Beyond identity: What information is stored in biometric face templates?.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Beyond identity: What information is stored in biometric face templates?

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.078250Z

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Observation da75ba81-1a60-4c2c-85da-928ddacf9504 · outbound

This paper cites Face recognition vendor test 2002,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Face recognition vendor test 2002,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.053346Z

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Observation 710dbb50-374b-45c7-b23b-e9d70fdf0cf0 · outbound

This paper cites Overview of the face recognition grand challenge,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Overview of the face recognition grand challenge,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:11.017793Z

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Observation d8335bed-aed6-4b3a-9f3c-7849858bd874 · outbound

This paper cites Factors that influence algorithm performance in the face recognition grand challenge,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Factors that influence algorithm performance in the face recognition grand challenge,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.991213Z

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Observation f2eb21cc-ae5a-4b78-88b3-f98de59cc807 · outbound

This paper cites A meta-analysis of face recognition covariates,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes A meta-analysis of face recognition covariates,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.974561Z

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Observation 2498e719-6357-45c9-bdc0-d58e3c4c7461 · outbound

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On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Unresolved cited work

Reference 26

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Observation 07ac3500-cb0d-4758-bb60-4537c2a03d7b · outbound

This paper cites Face recognition performance: Role of demographic information,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Face recognition performance: Role of demographic information,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.943306Z

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Observation 9c21db71-666c-466b-835c-d219686aa618 · outbound

This paper cites Labeled faces in the wild: A database forstudy- ing face recognition in unconstrained environments,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Labeled faces in the wild: A database forstudy- ing face recognition in unconstrained environments,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.925191Z

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This paper cites A longitudinal study of automatic face recognition,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes A longitudinal study of automatic face recognition,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.904436Z

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Observation b9b0b3fb-6051-40b0-81b7-b74f06468089 · outbound

This paper cites Longitudinal study of automatic face recognition,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Longitudinal study of automatic face recognition,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.884489Z

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This paper cites What should be balanced in a.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes What should be balanced in a

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.867761Z

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Observation a6fb7e17-447e-47aa-a50f-14c4c3ae2057 · outbound

This paper cites Influence of make-up on facial recognition,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Influence of make-up on facial recognition,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.851304Z

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Observation 39decdfc-68b9-48c2-93e5-258b40bfe879 · outbound

This paper cites Can facial cos- metics affect the matching accuracy of face recognition systems?.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Can facial cos- metics affect the matching accuracy of face recognition systems?

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.834589Z

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Observation f7a1db40-e6ac-4033-a80d-d2dab2a67fd5 · outbound

This paper cites Face authentication with makeup changes,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Face authentication with makeup changes,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.817300Z

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Observation d165eacd-7176-4e62-980b-990296b18793 · outbound

This paper cites Beard Segmentation and Recognition Bias.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Beard Segmentation and Recognition Bias

Reference 35

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Observation 4b9f546c-d840-4bb8-92ae-81f597b585f4 · outbound

This paper cites Post-comparison mitigation of demo- graphic bias in face recognition using fair score normal- ization,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Post-comparison mitigation of demo- graphic bias in face recognition using fair score normal- ization,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.796341Z

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Observation 7f84e6fa-2086-4fc3-b548-9e897017d842 · outbound

This paper cites Jointly de-biasing face recognition and demographic attribute estimation,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Jointly de-biasing face recognition and demographic attribute estimation,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.777051Z

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Observation 53ceb7f3-105c-4b80-8252-817a5db9a90f · outbound

This paper cites Learning disentangled representation for fair facial attribute clas- sification via fairness-aware information alignment,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Learning disentangled representation for fair facial attribute clas- sification via fairness-aware information alignment,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.758468Z

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Observation 21306d16-7061-420b-9373-25308358cd61 · outbound

This paper cites Distill and De-bias: Mitigating Bias in Face Verification using Knowledge Distillation.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Distill and De-bias: Mitigating Bias in Face Verification using Knowledge Distillation

Reference 39

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Observation 3087ca43-6443-428b-86a0-777e2d016851 · outbound

This paper cites PASS: protected attribute suppression system for mitigating bias in face recognition,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes PASS: protected attribute suppression system for mitigating bias in face recognition,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.741307Z

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Observation 9b4c07ca-5a96-4d2c-89fa-5134f70a3c86 · outbound

This paper cites Fairness in Bio- metrics: A Figure of Merit to Assess Biometric Ver- ification Systems,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Fairness in Bio- metrics: A Figure of Merit to Assess Biometric Ver- ification Systems,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.723800Z

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Observation f541d957-f145-409f-9f98-5c6f699e83bb · outbound

This paper cites Publications Office of the European Union, 2015, ISBN : 978-92- 95205-43-7.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Publications Office of the European Union, 2015, ISBN : 978-92- 95205-43-7

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.705686Z

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Observation 499ecd69-6679-4c6c-893e-6d55d965c25c · outbound

This paper cites Demographic Differentials in Face Recognition Algorithms,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Demographic Differentials in Face Recognition Algorithms,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.681845Z

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This paper cites Evaluating Proposed Fairness Models for Face Recognition Algorithms,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Evaluating Proposed Fairness Models for Face Recognition Algorithms,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.662470Z

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Observation a28142c4-5089-42f5-8279-560a5a8e02f0 · outbound

This paper cites The Small-Sample Bias of the Gini Coeffi- cient: Results and Implications for Empirical Research,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes The Small-Sample Bias of the Gini Coeffi- cient: Results and Implications for Empirical Research,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.644025Z

Source-reported events for the cited work

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Observation 9d4f8ad4-a453-4a96-a298-b413f56a74b0 · outbound

This paper cites MAAD-Face: A Mas- sively Annotated Attribute Dataset for Face Images,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes MAAD-Face: A Mas- sively Annotated Attribute Dataset for Face Images,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.625611Z

Source-reported events for the cited work

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Observation ca9fc053-1c7c-421d-9a24-f1a1e465b020 · outbound

This paper cites VGGFace2: A Dataset for Recognising Faces across Pose and Age,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes VGGFace2: A Dataset for Recognising Faces across Pose and Age,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.606106Z

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Observation d9824bde-28f6-484b-a6f0-2b249540a943 · outbound

This paper cites Using Semi-Joins to Solve Relational Queries,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Using Semi-Joins to Solve Relational Queries,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.583263Z

Source-reported events for the cited work

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Observation 16f2e2ba-3175-4fbe-b1af-e27492a4b083 · outbound

This paper cites ArcFace: Additive Angular Margin Loss for Deep Face Recog- nition,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes ArcFace: Additive Angular Margin Loss for Deep Face Recog- nition,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.566056Z

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Observation 933218eb-5a44-4020-a653-8dae5e3f9032 · outbound

This paper cites FaceNet: A unified embedding for face recognition and cluster- ing,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes FaceNet: A unified embedding for face recognition and cluster- ing,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.541173Z

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Observation 2ed7098b-4f89-46a8-97d3-bc9eb5275efb · outbound

This paper cites MS- Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes MS- Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.523727Z

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Observation c452ee7f-b589-49d5-9f85-cd73ff68326a · outbound

This paper cites Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Stacked Dense U-Nets with Dual Transformers for Robust Face Alignment,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.496640Z

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Observation d9fac941-e866-4ec0-bd71-1c25742d0c86 · outbound

This paper cites One Millisecond Face Alignment with an Ensemble of Regression Trees,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes One Millisecond Face Alignment with an Ensemble of Regression Trees,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.462780Z

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Observation bfa566a3-a94b-44e8-8012-72ecce6323bc · outbound

This paper cites Information technology — Biometric performance testing and reporting — Part 1: Principles and frame- work (ISO/IEC 19795-1),.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Information technology — Biometric performance testing and reporting — Part 1: Principles and frame- work (ISO/IEC 19795-1),

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.438081Z

Source-reported events for the cited work

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Observation dccaff78-3cb6-4e4b-969f-7e3ef104975c · outbound

This paper cites The Effect of Broad and Specific Demographic Homogene- ity on the Imposter Distributions and False Match Rates in Face Recognition Algorithm Performance,.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes The Effect of Broad and Specific Demographic Homogene- ity on the Imposter Distributions and False Match Rates in Face Recognition Algorithm Performance,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.419309Z

Source-reported events for the cited work

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Observation 61e0a5b7-fa8b-4b8c-839c-a67b1d99feba · outbound

This paper cites Responsible AI for Biometrics.

On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes Responsible AI for Biometrics

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T17:41:10.399938Z

Source-reported events for the cited work

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Pith citing papers

Observation 16b75fb0-fabd-474a-990f-f9a4d1626ad8 · inbound

Review of Demographic Fairness in Face Recognition cites this paper.

Review of Demographic Fairness in Face Recognition On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-09T12:38:43.041140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f3713e0-1c18-4f8f-ab3d-bf55d301f1bb · inbound

A Responsible Face Recognition Approach for Small and Mid-Scale Systems Through Personalized Neural Networks cites this paper.

A Responsible Face Recognition Approach for Small and Mid-Scale Systems Through Personalized Neural Networks On the Illusion of Gender Bias in Face Recognition: Explaining the Fairness Issue Through Non-demographic Attributes

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:08:22.875587Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.