Paper Citation Record · LEDGER

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks

As of 11 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2606.18510.

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

pith.paper-citation-record.v1
2606.18510 v1

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T00:45:33.196262Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+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

23 of 23 outbound references displayed

verified exact12
verified fuzzy0
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 21297f84-b524-497d-81cc-7af751a73823 · outbound

This paper cites Introduction to Presentation Attack Detection in Face Biometrics and Recent Advances.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Introduction to Presentation Attack Detection in Face Biometrics and Recent Advances

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.610122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ba5c332a-66ff-40fc-b5ca-fc0e92c45d8c · outbound

This paper cites Presentation Attack Detection Methods for Face Recognition Systems: A Comprehensive Survey,.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Presentation Attack Detection Methods for Face Recognition Systems: A Comprehensive Survey,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3faa6047-df1b-4712-ae75-324b2df70b36 · outbound

This paper cites Review of Demographic Fairness in Face Recognition.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Review of Demographic Fairness in Face Recognition

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.607502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2cdd1bd0-e4ca-4508-9b39-b27baccbe39c · outbound

This paper cites Issues Related to Face Recognition Accuracy Varying Based on Race and Skin Tone,.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Issues Related to Face Recognition Accuracy Varying Based on Race and Skin Tone,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b762e76-34c9-46b2-a1ea-870ef3f379eb · outbound

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

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4b18b46d-a715-4b54-9e62-c448d73fbd2e · outbound

This paper cites Fairness-Aware Face Presentation Attack Detection Using Local Binary Patterns: Bridging Skin Tone Bias in Biometric Systems,.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Fairness-Aware Face Presentation Attack Detection Using Local Binary Patterns: Bridging Skin Tone Bias in Biometric Systems,

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1368edc-787a-4bcb-ac46-c8a77294cddc · outbound

This paper cites CASIA-SURF CeFA: A Benchmark for Multi-modal Cross-ethnicity Face Anti-spoofing.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks CASIA-SURF CeFA: A Benchmark for Multi-modal Cross-ethnicity Face Anti-spoofing

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.639289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation efb69213-94b9-4ac5-85c2-ff3bf5445da0 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-07-03T21:18:58.636486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d861370d-c0ef-4d25-aefa-00da6f255cc2 · outbound

This paper cites Training data-efficient image transformers & distillation through attention.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Training data-efficient image transformers & distillation through attention

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.622125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 21d4d12c-25ff-49c2-8a31-2028e476efd1 · outbound

This paper cites ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T21:18:58.629194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6fa2bb85-a10b-43ce-b67a-dae07f158ba4 · outbound

This paper cites Intriguing Properties of Vision Transformers.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Intriguing Properties of Vision Transformers

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.636654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 25fe8251-918e-48eb-b894-328459a9a60e · outbound

This paper cites Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Rethinking Bias Mitigation: Fairer Architectures Make for Fairer Face Recognition

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.641938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f30578d3-2be4-487b-9cf5-a6ceb13770fa · outbound

This paper cites Faces of Fairness: Examining Bias in Facial Expression Recognition Datasets and Models.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Faces of Fairness: Examining Bias in Facial Expression Recognition Datasets and Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-07-29T02:25:06.229574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 87d868c9-01ef-4786-a019-ac511ebc66af · outbound

This paper cites Face Spoofing Detection from Single Images Using Micro-Texture Analysis,.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Face Spoofing Detection from Single Images Using Micro-Texture Analysis,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93403c7b-7b34-414c-9340-063775117c69 · outbound

This paper cites Face Anti-Spoofing Detection with Multi- Modal CNN Enhanced by ResNet,.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Face Anti-Spoofing Detection with Multi- Modal CNN Enhanced by ResNet,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9865c372-0752-4d34-a590-091c16ca1813 · outbound

This paper cites Can Your Face Detector Do Anti-spoofing? Face Presentation Attack Detection with a Multi-Channel Face Detector.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Can Your Face Detector Do Anti-spoofing? Face Presentation Attack Detection with a Multi-Channel Face Detector

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.634096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fcab5c02-c99e-4520-bb53-fd1f8312a336 · outbound

This paper cites Using Infrared to Improve Face Recognition of Individuals with Highly Pigmented Skin,.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Using Infrared to Improve Face Recognition of Individuals with Highly Pigmented Skin,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21183065-aec8-477b-9d6a-2dc3eb661b28 · outbound

This paper cites Fairness in Face Presentation Attack Detection.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Fairness in Face Presentation Attack Detection

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.644448Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3f40759f-44f1-499b-8883-b29cfd1b50fd · outbound

This paper cites On the Effectiveness of Vision Transformers for Zero-Shot Face Anti-Spoofing,.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks On the Effectiveness of Vision Transformers for Zero-Shot Face Anti-Spoofing,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4885a10f-0f7f-4bd0-88a3-761465010e2b · outbound

This paper cites S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.609117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 99cfaa68-a8d6-4da6-977c-fe0e4b3903e0 · outbound

This paper cites FM-ViT: Flexible Modal Vision Transformers for Face Anti-Spoofing,.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks FM-ViT: Flexible Modal Vision Transformers for Face Anti-Spoofing,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebdb5860-c042-4cd9-be4e-422cfcadc6a5 · outbound

This paper cites Robust face anti-spoofing framework with Convolutional Vision Transformer.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks Robust face anti-spoofing framework with Convolutional Vision Transformer

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-03T21:18:58.627805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 201d14d7-faf5-4ad1-a7d1-cb099975cde1 · outbound

This paper cites The Performance Analysis of Facial Expression Recognition System Using Local Regions and Features,.

Architectural Bias in Face Presentation Attack Detection: A Comparative Study of Vision Transformers and Convolutional Neural Networks The Performance Analysis of Facial Expression Recognition System Using Local Regions and Features,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-27T00:45:33.196262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.