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Paper Citation Record · LEDGER

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone

As of 9 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2505.20637.

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

pith.paper-citation-record.v1
2505.20637 v1

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:55:18.651093Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

49 of 49 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4d3d066c-499e-4eca-ba01-d62f9c854882 · outbound

This paper cites Demographic Bias in Biometrics: A Survey on an Emerging Chal- lenge,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Demographic Bias in Biometrics: A Survey on an Emerging Chal- lenge,

Reference 1

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Observation c9e907e0-337c-49e2-8a8c-78e624215eff · outbound

This paper cites The Impact of Racial Distribution in Training Data on Face Recognition Bias: A Closer Look,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone The Impact of Racial Distribution in Training Data on Face Recognition Bias: A Closer Look,

Reference 2

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Source-reported events for the cited work

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Observation e1e7c60a-149a-44ee-99ac-ccfec967e973 · outbound

This paper cites NIST special publication 1270. Towards a standard for identifying and managing bias in AI,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone NIST special publication 1270. Towards a standard for identifying and managing bias in AI,

Reference 3

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Observation c48af150-3dd6-4ce8-915f-3cccd48e512c · outbound

This paper cites Not in My Face: Challenges and Ethical Considerations in Automatic Face Emotion Recognition Technology,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Not in My Face: Challenges and Ethical Considerations in Automatic Face Emotion Recognition Technology,

Reference 4

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Source-reported events for the cited work

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Observation 2f9b32bc-9caa-4dd3-92a1-3b34ab38d144 · outbound

This paper cites Investigating Bias and Fairness in Facial Expression Recognition,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Investigating Bias and Fairness in Facial Expression Recognition,

Reference 5

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Source-reported events for the cited work

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Observation aadbb939-ab62-4559-a278-3a8e72eb93a5 · outbound

This paper cites Balancing the Scales: Enhanc- ing Fairness in Facial Emotion Recognition with Latent Alignment,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Balancing the Scales: Enhanc- ing Fairness in Facial Emotion Recognition with Latent Alignment,

Reference 6

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Source-reported events for the cited work

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Observation 2358da7e-39ea-4d2f-94eb-e24f311e8d70 · outbound

This paper cites Faces of Fairness: Examining Bias in Facial Expression Recognition Datasets and Mod- els,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Faces of Fairness: Examining Bias in Facial Expression Recognition Datasets and Mod- els,

Reference 7

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Source-reported events for the cited work

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Observation 5517e61b-3bb7-4833-9311-762715124e2a · outbound

This paper cites Notes from the AI frontier : Tackling bias in AI ( and in humans ),.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Notes from the AI frontier : Tackling bias in AI ( and in humans ),

Reference 8

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Source-reported events for the cited work

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Observation 7472be39-8a3a-4163-9ce6-8cdd34fa70e4 · outbound

This paper cites Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification,

Reference 9

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Source-reported events for the cited work

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Observation 14458bf2-c311-4381-a645-8f5c4feb122c · outbound

This paper cites How We’ve Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone How We’ve Taught Algorithms to See Identity: Constructing Race and Gender in Image Databases for Facial Analysis,

Reference 10

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Source-reported events for the cited work

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Observation 34704024-f5c0-4c85-9784-a46db26497b9 · outbound

This paper cites One label, one billion faces: Usage and consistency of racial categories in computer vision,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone One label, one billion faces: Usage and consistency of racial categories in computer vision,

Reference 11

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Source-reported events for the cited work

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Observation c58ddb5f-984f-4363-839f-d3cc483d28b8 · outbound

This paper cites Consensus and Subjectivity of Skin Tone Annotation for ML Fairness,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Consensus and Subjectivity of Skin Tone Annotation for ML Fairness,

Reference 12

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Source-reported events for the cited work

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Observation 67a34aba-73ee-4b96-964b-2e3c25176ead · outbound

This paper cites Which Skin Tone Measures Are the Most Inclusive? An Investigation of Skin Tone Measures for Artificial Intelligence,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Which Skin Tone Measures Are the Most Inclusive? An Investigation of Skin Tone Measures for Artificial Intelligence,

Reference 13

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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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Observation 01eb5092-6aed-43e9-9415-91de3a18c4c9 · outbound

This paper cites The validity and practicality of sun-reactive skin types I through VI.,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone The validity and practicality of sun-reactive skin types I through VI.,

Reference 14

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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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Observation 1c94d1a9-6de0-4102-aaf9-71d0fc126710 · outbound

This paper cites Fitz- patrick Skin Type, Individual Typology Angle, and Melanin Index in an African Population: Steps Toward Universally Applicable Skin Photosensitivity Assessments.,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Fitz- patrick Skin Type, Individual Typology Angle, and Melanin Index in an African Population: Steps Toward Universally Applicable Skin Photosensitivity Assessments.,

Reference 15

Resolution
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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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Observation 3fdc41ae-31ff-4d1a-b206-f72879d53139 · outbound

This paper cites Diversity in Faces,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Diversity in Faces,

Reference 16

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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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Observation b11911ba-b368-4881-bae0-464b4f43b3e0 · outbound

This paper cites FairFace: Face attribute dataset for balanced race, gender, and age for bias measurement and mitigation,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone FairFace: Face attribute dataset for balanced race, gender, and age for bias measurement and mitigation,

Reference 17

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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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Observation 1c8175ca-838f-4f44-a18a-c2ba69190ddd · outbound

This paper cites Beyond Skin Tone: A Multidi- mensional Measure of Apparent Skin Color,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Beyond Skin Tone: A Multidi- mensional Measure of Apparent Skin Color,

Reference 18

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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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Observation 171ee31a-a8e9-45d3-969a-c30d73647f1c · outbound

This paper cites Racial Bias within Face Recognition : A Survey,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Racial Bias within Face Recognition : A Survey,

Reference 19

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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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Observation cc69857b-02cc-4786-a2c3-1dfd642f2ad7 · outbound

This paper cites Evaluating Group Fairness in News Recommendations : A Comparative Study of Algorithms and Metrics,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Evaluating Group Fairness in News Recommendations : A Comparative Study of Algorithms and Metrics,

Reference 20

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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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Observation cae5131a-af9b-4059-a51e-16e08ed7cefa · outbound

This paper cites Meta Balanced Network for Fair Face Recognition,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Meta Balanced Network for Fair Face Recognition,

Reference 21

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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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Observation 9789c7f7-a339-402f-8ed9-c988ded03fa6 · outbound

This paper cites Towards Measuring Fairness in AI: The Casual Conversations Dataset,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Towards Measuring Fairness in AI: The Casual Conversations Dataset,

Reference 22

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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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Observation 8a9c3a23-9885-4d46-add0-450ee38e19bc · outbound

This paper cites Racial Influence on Automated Perceptions of Emotions,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Racial Influence on Automated Perceptions of Emotions,

Reference 23

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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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Observation 686dba76-dd33-45fc-888d-dd92cbaaf2f4 · outbound

This paper cites Addressing Racial Bias in Facial Emotion Recognition,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Addressing Racial Bias in Facial Emotion Recognition,

Reference 24

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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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Observation 054b7634-e6a9-4928-9194-0a0d77f1ef98 · outbound

This paper cites Understanding perception of algorithmic decisions: Fair- ness, trust, and emotion in response to algorithmic management,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Understanding perception of algorithmic decisions: Fair- ness, trust, and emotion in response to algorithmic management,

Reference 25

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Source-reported events for the cited work

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Observation ef836f57-aadc-4a87-aa7e-33a0ecddd681 · outbound

This paper cites Counterfactual fairness for facial expression recognition,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Counterfactual fairness for facial expression recognition,

Reference 26

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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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Observation 51dba7ae-2946-4179-b41a-1f1c8593079a · outbound

This paper cites Bias and Fairness on Multimodal Emotion Detection Algorithms.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Bias and Fairness on Multimodal Emotion Detection Algorithms

Reference 27

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Source-reported events for the cited work

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Observation 7ea2274e-4c96-4c4b-b717-dd9b4e908ca0 · outbound

This paper cites Domain adaptation for bias mitigation in affective computing: use cases for facial emotion recognition and sentiment analysis systems,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Domain adaptation for bias mitigation in affective computing: use cases for facial emotion recognition and sentiment analysis systems,

Reference 28

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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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Observation ddfea415-23f8-4a43-9c34-68079fcb8d63 · outbound

This paper cites Be- yond Accuracy: Fairness, Scalability, and Uncertainty Considerations in Facial Emotion Recognition,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Be- yond Accuracy: Fairness, Scalability, and Uncertainty Considerations in Facial Emotion Recognition,

Reference 29

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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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Observation ca33025a-e153-497c-9f7c-f3e1b0d7df03 · outbound

This paper cites Com- putational methods for pigmented skin lesion classification in images: review and future trends,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Com- putational methods for pigmented skin lesion classification in images: review and future trends,

Reference 30

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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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Observation 65896dd9-8e02-427e-b7eb-e607304f7ab6 · outbound

This paper cites Human Skin Detection Using RGB, HSV and YCbCr Color Models,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Human Skin Detection Using RGB, HSV and YCbCr Color Models,

Reference 31

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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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Observation 57e7abaa-324f-43b8-a573-9da848d3edfa · outbound

This paper cites Colorimetric skin tone scale for improved accuracy of human skin tone annotations.,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Colorimetric skin tone scale for improved accuracy of human skin tone annotations.,

Reference 32

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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.

source=pdf_text observed=2026-08-07T13:55:17.224916Z digest=sha256:97e9b174c50b06784a5f066e264fd3952fb755ab46995d08f9de1e3b76a191fe

Observation a610aac8-804f-4690-b859-0df5d9552799 · outbound

This paper cites Fairness and Bias Mitigation in Computer Vision: A Survey,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Fairness and Bias Mitigation in Computer Vision: A Survey,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:21.525221Z

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.

source=pdf_text observed=2026-08-07T13:55:17.271407Z digest=sha256:0d1d59d9fce498e426c1f01a7a9a28f50215f5d7a9efce4317ea89670cc1af27

Observation f6c8cfb8-bb7e-498d-b82f-b4b7b2b7be4a · outbound

This paper cites AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:21.388639Z

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.

source=pdf_text observed=2026-08-07T13:55:17.351509Z digest=sha256:9bffb119b9c854db6819bbb2e52c68080f46ed8a1ecca01854983adb5bb60fa9

Observation b4b308c1-a4b2-4016-aa5c-8f06f821a88f · outbound

This paper cites Exploring strategies to generate Fitz- patrick skin type metadata for dermoscopic images using individual ty- pology angle techniques,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Exploring strategies to generate Fitz- patrick skin type metadata for dermoscopic images using individual ty- pology angle techniques,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:21.301929Z

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.

source=pdf_text observed=2026-08-07T13:55:17.427452Z digest=sha256:1d6865b871287013769e062f579280459b0285a4320cb37cc7bf52297ed2417b

Observation 35de5651-a697-4d23-ac80-37adbac6e8bb · outbound

This paper cites Variations in skin colour and the biological consequences of ultraviolet radiation exposure,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Variations in skin colour and the biological consequences of ultraviolet radiation exposure,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:21.096065Z

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.

source=pdf_text observed=2026-08-07T13:55:17.513284Z digest=sha256:ba034e8f82e657217b82e04e91c9224cb81755230527eac36c37de2ac7a29d5e

Observation 8de003a9-e811-4e60-8d66-b9fc894d14e6 · outbound

This paper cites Achieve fairness without demographics for dermatological disease diagnosis,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Achieve fairness without demographics for dermatological disease diagnosis,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:20.947266Z

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.

source=pdf_text observed=2026-08-07T13:55:17.570445Z digest=sha256:68e7d13ea249eab3d36a962ae7ee79447ee87f72b26c4f037a9d1a9f3ce500f8

Observation 6f608100-828c-43c0-be70-7c66383d7590 · outbound

This paper cites Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Estimating Skin Tone and Effects on Classification Performance in Dermatology Datasets,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:21.189382Z

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.

source=pdf_text observed=2026-08-07T13:55:17.643681Z digest=sha256:84bc7e878ec41ab712c4c722f8873e028fa9c28b1d9c1331b9088af7ebce9556

Observation 2ede6da6-6874-4eb0-9eed-45b70f31aa3d · outbound

This paper cites Towards Fairness in AI for Melanoma Detection: Systemic Review and Recommenda- tions,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Towards Fairness in AI for Melanoma Detection: Systemic Review and Recommenda- tions,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:20.838237Z

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.

source=pdf_text observed=2026-08-07T13:55:17.700245Z digest=sha256:5dcbc5d15cd067c50ea9b7e9d027b943ab7455dc4bdfa1a087796402d82574a1

Observation 61c729a1-a9fe-41bb-9a32-8f9b7f9cb332 · outbound

This paper cites AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:20.738491Z

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.

source=pdf_text observed=2026-08-07T13:55:17.790035Z digest=sha256:afed8dd21a9d2c7f2f5b3021ffd6a5b01ff7cac753aa2284709584fb03dcf349

Observation 2ad08935-1bb5-4c0e-8d7a-422b80c4f31f · outbound

This paper cites FACET: Fairness in Computer Vision Evalua- tion Benchmark,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone FACET: Fairness in Computer Vision Evalua- tion Benchmark,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:20.557333Z

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.

source=pdf_text observed=2026-08-07T13:55:17.853541Z digest=sha256:e2cb6a49d0f5dc0c04979e3957e2b9faceedb7a91bb66f2e14367e93c54614ac

Observation 5da115dd-de89-476e-9df5-4802ea7c6160 · outbound

This paper cites Equality of opportunity in super- vised learning,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Equality of opportunity in super- vised learning,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:20.398268Z

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.

source=pdf_text observed=2026-08-07T13:55:17.942396Z digest=sha256:d2e227145e270a8f504f7df5d7409009bb51552823422f157a771ba1b3804fb5

Observation ee67ed6f-3446-42a4-8124-1ff4e26dcc87 · outbound

This paper cites Coroama and A.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Coroama and A

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:20.194229Z

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.

source=pdf_text observed=2026-08-07T13:55:18.037128Z digest=sha256:d9f9af101f402958eb3f93e2530cfd9b1d2812591278049827360bf5f71535bc

Observation 7dec7e48-78d8-4d90-bd5a-a22346e17f5a · outbound

This paper cites Explaining Face Recognition Through SHAP-Based Pixel-Level Face Image Quality Assessment,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Explaining Face Recognition Through SHAP-Based Pixel-Level Face Image Quality Assessment,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:20.014085Z

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.

source=pdf_text observed=2026-08-07T13:55:18.122522Z digest=sha256:e2c5050a1316ad93305c4761aa766dcaba2abaf26ab0d9639f7f2c41a486d966

Observation 9901f53b-71ca-4da4-b9e4-49a120326e5d · outbound

This paper cites On Black-Box Explanation for Face Ver- ification,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone On Black-Box Explanation for Face Ver- ification,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:19.760044Z

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.

source=pdf_text observed=2026-08-07T13:55:18.256978Z digest=sha256:0823f1a0722278497840560282ec98694d11b2ba5a56c28dc512225f49417c58

Observation 37cecc1d-f8f5-4e85-a0c6-4c86165ff06a · outbound

This paper cites True Black-Box Explanation in Facial Analysis,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone True Black-Box Explanation in Facial Analysis,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:19.471885Z

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.

source=pdf_text observed=2026-08-07T13:55:18.367531Z digest=sha256:fd998ba223f835132ea69afb22af4214a7d796f24e72d49524e41a1d687e0664

Observation 9b5c6ede-f007-41d7-abf2-865e4f05f7bf · outbound

This paper cites Grad-cam: Why did you say that? visual explanations from deep networks via gradient-based localization,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Grad-cam: Why did you say that? visual explanations from deep networks via gradient-based localization,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:19.196818Z

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.

source=pdf_text observed=2026-08-07T13:55:18.438326Z digest=sha256:432aeae4afb87cb25cdca7a5ecaf7ad5df438a40259b6181ec23c579a034de74

Observation 03f0f073-e8fb-4fbf-be22-3302071273b7 · outbound

This paper cites On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:19.072569Z

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.

source=pdf_text observed=2026-08-07T13:55:18.559842Z digest=sha256:9a5ad85ee641479478ba5853efeede057f60face4a2fa25958d6b5d89c64c469

Observation 7a7e5a61-9429-48b7-a7c1-b5013b6817e5 · outbound

This paper cites Focused LRP: Explainable AI for Face Morphing Attack Detection,.

TrustSkin: A Fairness Pipeline for Trustworthy Facial Affect Analysis Across Skin Tone Focused LRP: Explainable AI for Face Morphing Attack Detection,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:55:18.905881Z

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.

source=pdf_text observed=2026-08-07T13:55:18.651093Z digest=sha256:6a5d9c481513e966ff76a45fc97d0518e1fef466ab9b90c820c8e8afe96cfa46

Pith citing papers

No inbound Pith citation observations are available.