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Paper Citation Record · LEDGER

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples

As of 19 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2505.03383.

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

pith.paper-citation-record.v1
2505.03383 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:57:04.580640Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

31 of 31 outbound references displayed

  • verified exact0
  • verified fuzzy23
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a43bba9e-6360-449d-af09-2fea4c55c4a9 · outbound

This paper cites Black-box adversarial attacks with limited queries and information,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Black-box adversarial attacks with limited queries and information,

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-15T23:57:05.066087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.436295Z digest=sha256:f81573097da75bcb021170d858b599f08e8b9b987362354ced59b4822ed040aa

Observation b4781bf3-cf69-4a11-b41d-707e563b1b31 · outbound

This paper cites Query- efficient black-box adversarial attacks guided by a transfer- based prior,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Query- efficient black-box adversarial attacks guided by a transfer- based prior,

Reference 2

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raw_fallback, observed 2026-08-15T23:57:05.050195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.441824Z digest=sha256:1c9ac35fc4a085913a5c7046ed0ca604b93ec40781403362c589a64d61d773ff

Observation c4385f81-f2ef-44d0-8892-a2cf4f231d35 · outbound

This paper cites Query- efficient black-box adversarial attack with customized iteration and sampling,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Query- efficient black-box adversarial attack with customized iteration and sampling,

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-15T23:57:05.035129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.446950Z digest=sha256:c2becc97c3e8d9e5b9c886eef769b1386ffe9fd58759ae4c3f61461c11ba1ff8

Observation 0a09b4b7-24a2-4685-914b-934417b01197 · outbound

This paper cites Boosting query efficiency of meta attack with dynamic fine-tuning,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Boosting query efficiency of meta attack with dynamic fine-tuning,

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-15T23:57:05.020028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.452208Z digest=sha256:6275da2a811e7c2a639983e85559b46db9b1f1813dc1e570c3b565f63a7a630a

Observation b5d1dc5e-cfcb-4855-b2ed-aaf922c14224 · outbound

This paper cites Substitute meta-learning for black-box adversarial attack,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Substitute meta-learning for black-box adversarial attack,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:05.004139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.457014Z digest=sha256:7bd5650d2ed0600ca82ccc51190a8edf8692917d8c1ccb9efb8c14407830c5c0

Observation 7b143d01-5049-4e1b-8534-6b07017d70d5 · outbound

This paper cites Improving transferability of adversarial examples with input diversity,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Improving transferability of adversarial examples with input diversity,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.986949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.461870Z digest=sha256:8ef5d722ff67a072421d58fdb9ccbee48fc77d35159b9e17a9168a4eafcbfae9

Observation 7c96d5b4-b5c3-4aab-b393-2d47108bbdb7 · outbound

This paper cites Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks

Reference 7

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unresolved
no resolver link, observed 2026-08-15T23:57:04.467221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:57:04.467221Z digest=sha256:004dac012e58874db77c336f15a8681a310dfe8f3b9b48d10baabd5f3189d378

Observation d6df4444-97d9-45e4-8a1a-4b4d0acf8ea0 · outbound

This paper cites Feature importance-aware transferable adversarial attacks,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Feature importance-aware transferable adversarial attacks,

Reference 8

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verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.969447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.472293Z digest=sha256:c44434c7fec2e6f5a743d98ba1fd5dae88a7fcc1544b68fe39c60805d7d56ff6

Observation 5391009e-c1e3-4024-b2a6-d4dbe4e32580 · outbound

This paper cites Improving adversarial transferability via neuron attribution-based attacks,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Improving adversarial transferability via neuron attribution-based attacks,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.953572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.476808Z digest=sha256:3d70c9fe380523f3a9019c293300689bb05f5bf713b1136386f624995cb8b66e

Observation e0bc57c8-ceea-4ae6-aaf4-0f127826a9f2 · outbound

This paper cites RobFR: Benchmarking Adversarial Robustness on Face Recognition.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples RobFR: Benchmarking Adversarial Robustness on Face Recognition

Reference 10

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unresolved
no resolver link, observed 2026-08-15T23:57:04.481879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:57:04.481879Z digest=sha256:6e1cce06d2ed520f4250b96f39fe5c59b6efe78b1146352f58ff9ecb9d5cb7b8

Observation 28c5857e-0101-499c-af1f-b6e06c715977 · outbound

This paper cites Cue saliency in faces as assessed by the ‘photofit’technique,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Cue saliency in faces as assessed by the ‘photofit’technique,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.938246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.487128Z digest=sha256:ca9b3fead3cdcab091c9c48e7dd9fe5bd7090d6601827d570380e46b03128658

Observation b3490d28-344d-489f-a2a8-ff36fc0b9710 · outbound

This paper cites Evading defenses to transferable adversarial examples by translation-invariant attacks,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Evading defenses to transferable adversarial examples by translation-invariant attacks,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.922132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.491486Z digest=sha256:84d966d4db80b8d0d54a2da1de4184f779ef2255689e1697c53c6ac137e6d0f3

Observation 7adcdb20-7f22-4ba1-b214-ee11343aa4ed · outbound

This paper cites Boosting adversarial attacks with momentum,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Boosting adversarial attacks with momentum,

Reference 13

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raw_fallback, observed 2026-08-15T23:57:04.906631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.496357Z digest=sha256:166e26545cf6df113741e61ccc86cc2beb28cdf41e54bd6ce2c981b04d9a83b6

Observation e0efca12-ffc7-44cc-ba29-467d7567e8c1 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Explaining and Harnessing Adversarial Examples

Reference 14

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unresolved
no resolver link, observed 2026-08-15T23:57:04.500881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:57:04.500881Z digest=sha256:f64cc14cfacb3ed378150eee5b2c120e32f2e57fc3e6ce7beb3b74c9fb749905

Observation 92d6a0de-6171-4cd2-a043-5798b55ee6ab · outbound

This paper cites Adversarial examples in the physical world,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Adversarial examples in the physical world,

Reference 15

Resolution
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no resolver link, observed 2026-08-15T23:57:04.505749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:57:04.505749Z digest=sha256:ebb15f33cddb16d8df795d9d4a34f9b9b451c3f970dac323a96efc6d2766c01e

Observation c38b825e-b148-4a3d-9ffb-7c1107c13095 · outbound

This paper cites Boosting adversarial transferability by achieving flat local maxima,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Boosting adversarial transferability by achieving flat local maxima,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.879080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.510868Z digest=sha256:42544c94db35db94ab50224cb60e9ed4faf2d8732ac8b447e8f95284b90ba950

Observation 2c1877e9-a0e6-4c86-a236-489c3e652714 · outbound

This paper cites Improving the transferability of adversarial examples with arbitrary style transfer,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Improving the transferability of adversarial examples with arbitrary style transfer,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.862911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.515686Z digest=sha256:9fde2a75b86c8fda52ec79e3b55c90b9b64b0c369f72e6f5854e46c12cea9f71

Observation 3000eafd-af68-4451-b011-8a30c3793572 · outbound

This paper cites Adversarial attack on object detection via object feature- wise attention and perturbation extraction,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Adversarial attack on object detection via object feature- wise attention and perturbation extraction,

Reference 18

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raw_fallback, observed 2026-08-15T23:57:04.847324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.520675Z digest=sha256:76888b9b7bb2ac4868f238c229fcaaa145cb5d5f404bbff4f04cd75bbec01fa1

Observation e86c0f40-699f-4186-859e-ecf0ab841394 · outbound

This paper cites Learning transferable adversarial perturbations,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Learning transferable adversarial perturbations,

Reference 19

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raw_fallback, observed 2026-08-15T23:57:04.832038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.525237Z digest=sha256:fe883bb466a75d357121f65c1ecaabd2fe053ea0eb4b33ddccf25167780cd61e

Observation 15fa438c-86a5-425f-a90e-49dc3e19ff94 · outbound

This paper cites Human face perception and identification,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Human face perception and identification,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.816977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.529710Z digest=sha256:9ef688dd16afbfaee29f2456bb69dd14c4b68e478a12045bb126f4cc0b1b5a30

Observation e6645d23-6b1b-4b1d-a944-4368344ea8c8 · outbound

This paper cites Identity mappings in deep residual networks,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Identity mappings in deep residual networks,

Reference 21

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no resolver link, observed 2026-08-15T23:57:04.535027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:57:04.535027Z digest=sha256:82f7ecbdbe42381b6769713efacca2cecab4d3d4e314f35be4bfeb540d19e269

Observation e4e87b52-dec3-48e9-a8d7-573f77c6b0f8 · outbound

This paper cites Mobilenetv2: Inverted residuals and linear bottlenecks,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Mobilenetv2: Inverted residuals and linear bottlenecks,

Reference 22

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no resolver link, observed 2026-08-15T23:57:04.539376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:57:04.539376Z digest=sha256:d6ad0485257a424b63836864acf03e43c38b242d638fb206d0c3314077b528fa

Observation 78f9ab75-5997-44ac-8b9a-f6e8acb52e2e · outbound

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

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Labeled faces in the wild: A database forstudying face recognition in unconstrained environments,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.782989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.544059Z digest=sha256:f3ab4531f475adf20fd8f891390e84ae7621c37084163d31fe77229aab0d7ae0

Observation 0e9e8ee4-48ce-4164-be8d-5984ae67a736 · outbound

This paper cites Facenet: A unified embedding for face recognition and clustering,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Facenet: A unified embedding for face recognition and clustering,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.767823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.548695Z digest=sha256:3187698acda1e54ccd669fed0b265551b2622d019b64e8f31b44a3a6aa23eee1

Observation f6966293-16eb-4b1b-9014-732e4cdf6f72 · outbound

This paper cites Sphereface: Deep hypersphere embedding for face recognition,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Sphereface: Deep hypersphere embedding for face recognition,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.751275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.553246Z digest=sha256:c0855c6662aa09808580633108b6de82b1cc065664580d9da355d43f0e4d816e

Observation 5609c6e7-243b-4ad2-ae98-7f6f37208834 · outbound

This paper cites Cosface: Large margin cosine loss for deep face recognition,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Cosface: Large margin cosine loss for deep face recognition,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.736558Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.557709Z digest=sha256:4a950cdca99c154f0928b86aa5f21f65f5950f6526b64ed43ada80be9e92472f

Observation c6871db5-fe71-4805-9404-badbc8538fa7 · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Arcface: Additive angular margin loss for deep face recognition,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.721013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.562177Z digest=sha256:ea469e3b06163dd607f362b40c85de620ab606399309cc1903b041626672e914

Observation 0fedd5cf-6545-45b2-b210-d5574be6e00e · outbound

This paper cites Mobilefacenets: Efficient cnns for accurate real-time face verification on mobile devices,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Mobilefacenets: Efficient cnns for accurate real-time face verification on mobile devices,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.706248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.566671Z digest=sha256:a8780362d26bfd8ddbffad3b253d07fcbd36c113517a011b5dafa84d11fb2e97

Observation adadba67-7b2f-46fb-9d51-c69b0fe6c6b0 · outbound

This paper cites Shufflenet: An extremely efficient convolutional neural network for mobile devices,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Shufflenet: An extremely efficient convolutional neural network for mobile devices,

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-15T23:57:04.690870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-15T23:57:04.571468Z digest=sha256:340dfeffbb6c48444355b325a543243cad85c074769bb50c47b529d7a48dee21

Observation 956b6bac-7998-4108-8010-13745290cdf0 · outbound

This paper cites SmoothGrad: removing noise by adding noise.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples SmoothGrad: removing noise by adding noise

Reference 30

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unresolved
no resolver link, observed 2026-08-15T23:57:04.575824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:57:04.575824Z digest=sha256:85781e04fd6ee05f9c2e30f28c24b0c6b65744918fcb3484ae0595738dde6424

Observation 74dd1a85-bacd-4eac-a86d-ac8dfa542fe4 · outbound

This paper cites Deep residual learning for image recognition,.

Attention-aggregated Attack for Boosting the Transferability of Facial Adversarial Examples Deep residual learning for image recognition,

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-15T23:57:04.580640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:57:04.580640Z digest=sha256:4c900fda7227cd145dd30caf4ec7f6ee815791894bff7229b02884996d57f0de

Pith citing papers

No inbound Pith citation observations are available.