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Paper Citation Record · LEDGER

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks

As of 18 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 1 inbound Pith citation observation for arXiv:2506.19533.

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

pith.paper-citation-record.v1
2506.19533 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:36:37.696794Z

measured 29 of 29 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:36:37.527795Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-15T18:36:37.937123Z

Reference resolution

28 of 28 outbound references displayed

  • verified exact2
  • verified fuzzy18
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ece0b69-6191-49cc-8512-737c1c1be277 · outbound

This paper cites Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks

Reference 1

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metadata mismatch
local_arxiv, observed 2026-08-15T18:36:37.943154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 459d2103-5329-4e02-b3dd-b0b8a7c503b0 · outbound

This paper cites Our task in this section is to detect whetherf is compromised, and if so, identify ∆.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Our task in this section is to detect whetherf is compromised, and if so, identify ∆

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:38.200191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 2e4d5173-71bf-4bfc-90b3-2735d0b085fc · outbound

This paper cites The net- work architecture used is DeepID [2].

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks The net- work architecture used is DeepID [2]

Reference 3

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raw_fallback, observed 2026-08-15T18:36:38.188255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation dc38cd54-5157-4217-8587-bd62332aa3e3 · outbound

This paper cites Importantly our method does not require access to any poisoned example.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Importantly our method does not require access to any poisoned example

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:38.177203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 42747046-9aff-431f-8ecc-115108f4d234 · outbound

This paper cites Deep face recognition,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Deep face recognition,

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation fff3504f-8bd6-48a5-bb45-d8bb5c91b803 · outbound

This paper cites Deep learn- ing face representation from predicting 10,000 classes,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Deep learn- ing face representation from predicting 10,000 classes,

Reference 6

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raw_fallback, observed 2026-08-15T18:36:38.152735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 223061c2-0bde-49ba-ba08-e86c26b4b787 · outbound

This paper cites BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain

Reference 7

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no resolver link, observed 2026-08-15T18:36:37.568708Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 63aacf50-5a8c-436e-8a25-f21399636f0f · outbound

This paper cites Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Targeted Backdoor Attacks on Deep Learning Systems Using Data Poisoning

Reference 8

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no resolver link, observed 2026-08-15T18:36:37.574347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation f289facd-dc3d-4d6c-b980-3a7e723684e5 · outbound

This paper cites Tro- janing attack on neural networks,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Tro- janing attack on neural networks,

Reference 9

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raw_fallback, observed 2026-08-15T18:36:38.139931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.579481Z digest=sha256:f45340b5479932106f1c3c1f076f55e0295f22bdaff760ba4764d9f5e7844854

Observation 30271493-c965-40f5-bbf3-9c7cb125f473 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Explaining and Harnessing Adversarial Examples

Reference 10

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unresolved
no resolver link, observed 2026-08-15T18:36:37.584173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:36:37.584173Z digest=sha256:9dc024351cc6fb922f513f767bfbf22f5989d99adf7f13a09e145e0e9d5f909b

Observation 5a8c28ed-26f0-4fa5-bc01-ec62a5390779 · outbound

This paper cites Deepfool: a simple and accurate method to fool deep neural networks,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Deepfool: a simple and accurate method to fool deep neural networks,

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:38.122373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 84fbc7a6-35a6-4436-82df-9f07bfa273db · outbound

This paper cites Universal adversar- ial perturbations,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Universal adversar- ial perturbations,

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:38.105479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation ad1aa9f2-2b1b-4f75-b0a4-44ba1f413ec7 · outbound

This paper cites Backdoor Attacks Against Deep Learning Systems in the Physical World.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Backdoor Attacks Against Deep Learning Systems in the Physical World

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-08-15T18:36:37.848067Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.599267Z digest=sha256:a14f38eec6ca717c695eb97e7ea5107a62f700860c90909d889de44fd9069639

Observation 9f895bd4-699c-4377-9577-54f007fc82d1 · outbound

This paper cites Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Neural cleanse: Identifying and mitigating backdoor attacks in neural networks,

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:38.091379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.604272Z digest=sha256:6f7cb5565f91799ccd93c8bdd656f5cae2b62b10c9b772ec32c8fe53fb548aa6

Observation 5cdd4ca5-99e8-4f2b-b18b-d502f6e34acd · outbound

This paper cites Defending neural backdoors via generative distribution modeling,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Defending neural backdoors via generative distribution modeling,

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:38.079967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.612823Z digest=sha256:11a30f9bb5ae493d37cc68c65c754e42f4f6b67dcedb7b06afb984485304c28a

Observation 1776c37c-184b-41f9-b434-bf422ce76689 · outbound

This paper cites Deepinspect: A black-box trojan de- tection and mitigation framework for deep neural net- works,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Deepinspect: A black-box trojan de- tection and mitigation framework for deep neural net- works,

Reference 16

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raw_fallback, observed 2026-08-15T18:36:38.067343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.618719Z digest=sha256:8c55dd15eaabcf5e22568dbc018db983d5ad5f9cc370a1c79f1969f088c86f49

Observation b5bcae91-3958-40bb-a88a-9d74357afa67 · outbound

This paper cites Scalable Backdoor Detection in Neural Networks.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Scalable Backdoor Detection in Neural Networks

Reference 17

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local_arxiv, observed 2026-08-15T18:36:37.822743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.624384Z digest=sha256:f2b4b2412f7bebd6a4486b7a9cdc02f13c4376c2a816cc534bd43997948023a5

Observation c6c9e4d7-f1ab-49b0-ac33-6715ca2f9d57 · outbound

This paper cites TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks TABOR: A Highly Accurate Approach to Inspecting and Restoring Trojan Backdoors in AI Systems

Reference 18

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no resolver link, observed 2026-08-15T18:36:37.629818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:36:37.629818Z digest=sha256:148549eb1f838c5475abd8713fe30f6f0961e63d6c1800f1fdfb1160d391c9df

Observation 8755a5ae-8719-4716-8221-3d41d1d74864 · outbound

This paper cites Disguised faces in the wild,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Disguised faces in the wild,

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:38.052893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.642104Z digest=sha256:aad5893a07d3cf500f4805825396f31c0dde9d42309ede41850451bd3fa28c60

Observation 2d4a79a7-7f48-4134-9355-f21ced0697f3 · outbound

This paper cites Spec- tral signatures in backdoor attacks,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Spec- tral signatures in backdoor attacks,

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:38.040105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 5f1cffd9-d951-461b-9b89-2dff710100a6 · outbound

This paper cites Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

Reference 21

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no resolver link, observed 2026-08-15T18:36:37.656183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:36:37.656183Z digest=sha256:1e3a6b2a85e523a6bee9d203e4162ef4a12cd2b87ed0513300f04f82c69a08b6

Observation c3075c9f-07d9-42fb-bce5-c9738ca5ca95 · outbound

This paper cites STRIP: A Defence Against Trojan Attacks on Deep Neural Networks.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks STRIP: A Defence Against Trojan Attacks on Deep Neural Networks

Reference 22

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no resolver link, observed 2026-08-15T18:36:37.663824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:36:37.663824Z digest=sha256:278f54335ff6b896683f3a9a9db3ae9504826bb85368b09aa0cc9dab00beb503

Observation e23bd7ef-9cf0-449c-959a-91afe659bb18 · outbound

This paper cites Detection of trojaning attack on neural networks via cost of sample classification,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Detection of trojaning attack on neural networks via cost of sample classification,

Reference 23

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raw_fallback, observed 2026-08-15T18:36:38.026196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.671547Z digest=sha256:8ebc936c7c161f31edcefe8eadec9e4453d85461c76e8489d13aca244571e7b5

Observation 5c5c885d-65d4-4078-83d1-900656c89cb8 · outbound

This paper cites Neu- ral trojans,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Neu- ral trojans,

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:38.011508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 3a4a3050-6f61-4677-bb8b-73346d3e120c · outbound

This paper cites an unresolved cited work.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Unresolved cited work

Reference 25

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unresolved
raw_fallback, observed 2026-08-15T18:36:37.995857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 5689f6ef-81b3-425e-a3bd-bf1e2f116421 · outbound

This paper cites Face recogni- tion in unconstrained videos with matched background similarity,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Face recogni- tion in unconstrained videos with matched background similarity,

Reference 26

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:37.985212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.686861Z digest=sha256:44b0baedf063579c34245a9561c3169b2b5eb1f5d6cae1440d95a9ed3e3f4c03

Observation 47069550-68c7-4ae6-bdf8-b517650fc3fd · outbound

This paper cites One-shot learning of object categories,.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks One-shot learning of object categories,

Reference 27

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verified fuzzy
raw_fallback, observed 2026-08-15T18:36:37.971011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.690908Z digest=sha256:afd6027bb5d4cd8a1cca80cc236232e5c36848503b053c78f1e6f95636d2ebf0

Observation e0a030db-cb1e-40f1-bed6-6f2655ac2a18 · outbound

This paper cites Each mini-batch of 32 images consists of 12 clean images, 10 images containing both the triggers (e.g.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Each mini-batch of 32 images consists of 12 clean images, 10 images containing both the triggers (e.g

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:36:37.957528Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.696794Z digest=sha256:adb24fe21d8a041fca6c9ddb9184400935c0391232478ce0bdc1e785c2c6818d

Pith citing papers

Observation 1ece0b69-6191-49cc-8512-737c1c1be277 · inbound

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks cites this paper.

Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks Identifying Physically Realizable Triggers for Backdoored Face Recognition Networks

Reference 1

Resolution
metadata mismatch
local_arxiv, observed 2026-08-15T18:36:37.943154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-15T18:36:37.527795Z digest=sha256:05f7f8dd8e4e970b534c608f0f29a1987c8983abe5ec0b0901ce2d6f45827199