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Paper Citation Record · LEDGER

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

As of 20 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 2026-08-20T06:33:59.587034+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 2026-08-20T06:33:59.587034+00:00.

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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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verified fuzzy
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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.441824Z digest=sha256:018fe0014542da097667b802c77922571250bd6e2a3b8a28ceb3c3e1bf4cb92c

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.446950Z digest=sha256:bc94fec138ef841d56c87385dbb1777ad63c655879ebbda046b8b96278185e0f

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

Resolution
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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.452208Z digest=sha256:98c1e44a36397181437028b2325c6bb2730aca8f61d865d21d067af28f2b9b34

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

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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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.457014Z digest=sha256:a22a2b7821462c9704654ecda2c6c860d05c3e9cc2555fa7167b86d8038550fa

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.461870Z digest=sha256:617740e642730aba725664d997a72bfa558ba32642c83cb5f0c037a1b2666186

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:d8dc1cbda2e444374d9215c0c22d6cf5d6b72b60539a391cfa96eab1c20d1c46

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

Resolution
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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.472293Z digest=sha256:12e139e174189fa12c40c54581cb9af1d9ae45bc4e94bbabf753f0fe6d1258e2

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.476808Z digest=sha256:ceccc74b7495e680733c8d387b9f5948d3f6acb158798c0f7e0637c42936d383

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=sha256:225028c57ee273b2f908afc59e3f8d5ceed31038e5b68a3912e42d2b6c185f3f

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.487128Z digest=sha256:cc0f27c2d3642198d08fb7a406326bbba7f3ffa88033fcad6b97f28379923123

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.491486Z digest=sha256:6d78594b50a936d19e97181ee82cb60175ce54a12cf729f3d4998985d1744430

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.496357Z digest=sha256:5bf7cfadb3853d6e37d5af3a3ad8059fe22d9b68923ba62f7569ab6c64e02790

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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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:a34677116c667c8da83a6ae2f9ea0326d6b0823306c35a46beabe44513bcf492

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

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unresolved
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=sha256:2a84cac19558094128ba82823aeeee5cbb2b3ce2d7491b350cd1a049401d5765

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.510868Z digest=sha256:7fd400604fa85b83de5f383d066501e6a59fee8fc1b48e8447cc816d1c05a4ea

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.515686Z digest=sha256:58424c42770ded8c98c92e811026ea6a55dd058801dcc1e1525ee67997a4a3c3

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

Resolution
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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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.520675Z digest=sha256:dc265dd11521b14865f14037e5fb0b7c1066b988805f297cde19839996788ce5

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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verified fuzzy
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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.525237Z digest=sha256:050df3ec4b9415f4e7bb41a6fa2a84b93a07698dcf9570c86047a3cc5a510adf

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.529710Z digest=sha256:ba0f8bfa182148cc0f8b41d0cbdfcaf74e42180e9038727528125886800a8f7a

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=sha256:4310cc2d8ede50b9c2a3773a5d9e3289a78eca4fad5883e619060bd422e8b77f

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

Resolution
unresolved
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:ec15be99f26153bc309516cf977db84add5f483d851a0753d8323710af53a7c4

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.544059Z digest=sha256:ce76eebe784147c74163628d0a9e4cb3922bc56f112f902ce82d3c306aa01300

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.548695Z digest=sha256:af054175db2a96ecca014a5c27ae9110bd0ed1a219fa5b45266be7ff08232ff4

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.553246Z digest=sha256:f3e00765369d1098716fbceae718da9886d430f6f831fb8868690ceb86b7c47e

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.557709Z digest=sha256:25c614d563bb281c9793071fc9f9e255b454d8990ba545e91ca109dccb65a046

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.562177Z digest=sha256:ad408c10e678ea20db6ae5e91c17eb27b2ee4844308f4d61054712c8ee0ac7e9

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.566671Z digest=sha256:79e4e5f92ca6a9312189277cea3e2bc7a86edaa0b084dc32f1d18006a0c2b33f

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 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-15T23:57:04.571468Z digest=sha256:ecc30d689b2a8b122f95e85014bded4e7ac20089b656b2535e415fa0acdf459e

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=sha256:137ed9a3f625b0f901061857d2359c2842de4ba581ad8e8df1ed895b0e7f9d75

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=sha256:57e21f5219178dd5fcfcd53ba705b828ecdc776d116c117f23110712da9c9af4

Pith citing papers

No inbound Pith citation observations are available.