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Paper Citation Record · LEDGER

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers

As of 16 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2508.12384.

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

pith.paper-citation-record.v1
2508.12384 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T17:27:45.506800Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

48 of 48 outbound references displayed

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  • verified fuzzy29
  • unresolved19
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3897efc5-47bf-421c-8851-753048e94689 · outbound

This paper cites An adaptive model ensemble adversarial attack for boosting adversarial transferability.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers An adaptive model ensemble adversarial attack for boosting adversarial transferability

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7f245155-22d0-408a-ad58-d85426bae3b2 · outbound

This paper cites Visformer: The vision-friendly transformer.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Visformer: The vision-friendly transformer

Reference 2

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Observation e9571995-e3e9-4437-97ac-53a0a890eda2 · outbound

This paper cites Boosting adversarial at- tacks with momentum.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Boosting adversarial at- tacks with momentum

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation b83cb56a-16d3-4758-adad-de6e01ddb661 · outbound

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

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Evading defenses to transferable adversarial examples by translation-invariant attacks

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 70417bee-98db-45a0-beac-0fa55ea5afaa · outbound

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

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 9a7aaf27-883d-421d-8282-472f43ba923b · outbound

This paper cites Convit: Improv- ing vision transformers with soft convolutional inductive bi- ases.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Convit: Improv- ing vision transformers with soft convolutional inductive bi- ases

Reference 6

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 817e9c58-fbdc-45d7-a008-7a8bf9125ebe · outbound

This paper cites Fda: Feature disruptive attack.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Fda: Feature disruptive attack

Reference 7

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raw_fallback, observed 2026-08-15T17:27:46.013148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.337186Z digest=sha256:0065931c52ef289ad4b2cdfa5defc00ebd3e0355444b1f49a3d1599449f7a3bc

Observation 058b639f-c246-4186-a20c-3fd1be0f45c8 · outbound

This paper cites Boosting Adversarial Transferability by Achieving Flat Local Maxima.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Boosting Adversarial Transferability by Achieving Flat Local Maxima

Reference 8

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raw_fallback, observed 2026-08-15T17:27:46.000591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 14af46bd-075f-4f61-b153-a7d7901a1d26 · outbound

This paper cites Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Improving the Transferability of Adversarial Examples with Arbitrary Style Transfer

Reference 9

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raw_fallback, observed 2026-08-15T17:27:45.988814Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.345239Z digest=sha256:5286b03da84ac336d66bb0e0ef649521bda91a6b372ba5cdc314e18c58da0d21

Observation 06b8dafe-c974-4c19-b8a0-57e84aa7a352 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Explaining and Harnessing Adversarial Examples

Reference 10

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 00b41356-e820-4778-9f9d-d8826d63eeb1 · outbound

This paper cites Levit: a vision transformer in convnet’s clothing for faster inference.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Levit: a vision transformer in convnet’s clothing for faster inference

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 79845059-adb8-41ab-a2c9-e9316a869730 · outbound

This paper cites Countering Adversarial Images using Input Transformations.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Countering Adversarial Images using Input Transformations

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 97e90a96-1e3f-46c5-bfd8-f59ff1921840 · outbound

This paper cites Transformer in transformer.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Transformer in transformer

Reference 13

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 933c09ba-44af-461a-b1c2-a8dc670157fa · outbound

This paper cites Deep residual learning for image recognition.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Deep residual learning for image recognition

Reference 14

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:27:45.368022Z digest=sha256:130ccaf2d43fa2c96314a8122b99a373af2d75e73fdda4873e8af89862456e77

Observation da5fe8c1-93a0-4150-81dd-5629c527fc42 · outbound

This paper cites Rethinking spa- tial dimensions of vision transformers.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Rethinking spa- tial dimensions of vision transformers

Reference 15

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:27:45.372387Z digest=sha256:0fb27036190fc8b83aff39fb965fdce0def3773a865a1e280bdf22d11e4048a9

Observation 9e219378-9c51-4d99-b868-a426830f2fd6 · outbound

This paper cites Accelerating stochastic gradi- ent descent using predictive variance reduction.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Accelerating stochastic gradi- ent descent using predictive variance reduction

Reference 16

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raw_fallback, observed 2026-08-15T17:27:45.947920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation dd0a7cfa-db26-44c0-aaf3-6f2fdc171bdd · outbound

This paper cites Ad- versarial examples in the physical world.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Ad- versarial examples in the physical world

Reference 17

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raw_fallback, observed 2026-08-15T17:27:45.936173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.381089Z digest=sha256:1eac072b553d00ae162d8348592219899097252a4a89ab5a3623a24241c27a71

Observation 7c5f8666-5162-41cb-87c0-9b6c7c90938a · outbound

This paper cites Improving adversarial transferability via intermediate-level perturbation decay.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Improving adversarial transferability via intermediate-level perturbation decay

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation ddd01164-d654-42ac-9eb8-0b64bb5734ce · outbound

This paper cites Learning transferable adversarial examples via ghost networks.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Learning transferable adversarial examples via ghost networks

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.389092Z digest=sha256:891b8a66e6e1cbbfc533a447c0290e1004ab92a09eb7fef38b1fbd6273babe30

Observation 5ea6cfdc-adde-4da6-941d-57b6e6e27ead · outbound

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

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Nesterov Accelerated Gradient and Scale Invariance for Adversarial Attacks

Reference 20

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b9f0c49d-fe81-4f59-b784-099cad795279 · outbound

This paper cites Boosting adversarial transferability across model genus by deformation-constrained warping.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Boosting adversarial transferability across model genus by deformation-constrained warping

Reference 21

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verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.901708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7b2908b4-c7f8-47f3-aab6-b3fc29e737fa · outbound

This paper cites Delving into Transferable Adversarial Examples and Black-box Attacks.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Delving into Transferable Adversarial Examples and Black-box Attacks

Reference 22

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Unavailable: canonical work link unavailable.

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Observation 780d69a4-a7a0-43d6-b9e5-ab1188eeb5fa · outbound

This paper cites Discrete Representations Strengthen Vision Transformer Robustness.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Discrete Representations Strengthen Vision Transformer Robustness

Reference 23

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Observation 93563e55-90a1-4465-90ae-961585aac8b7 · outbound

This paper cites Enhance the visual representation via discrete adversarial training.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Enhance the visual representation via discrete adversarial training

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 5cbb16d5-3f99-48e0-bddb-7f82df192a6d · outbound

This paper cites Towards robust vision transformer.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Towards robust vision transformer

Reference 25

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raw_fallback, observed 2026-08-15T17:27:45.877292Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 4ada3316-bc99-49b8-87d2-7e4cb36d23f0 · outbound

This paper cites Separable Self-attention for Mobile Vision Transformers.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Separable Self-attention for Mobile Vision Transformers

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 02dbb314-1478-431f-b3dc-d45f3cb8843e · outbound

This paper cites When adversarial training meets vision trans- formers: Recipes from training to architecture.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers When adversarial training meets vision trans- formers: Recipes from training to architecture

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 5e6299ba-da2a-4130-8dda-574fc3833911 · outbound

This paper cites A self-supervised approach for adversarial robustness.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers A self-supervised approach for adversarial robustness

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.857547Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 7d782a44-eae0-4f96-90c6-c60bf8a32528 · outbound

This paper cites Imagenet large scale visual recognition challenge.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Imagenet large scale visual recognition challenge

Reference 29

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:27:45.433583Z digest=sha256:5f126fcace83e38c04d1a093cb54b690b9e153aadf1e1d41899274c89a771313

Observation f78a665b-3502-4622-b887-5346778fe884 · outbound

This paper cites Rethinking the inception archi- tecture for computer vision.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Rethinking the inception archi- tecture for computer vision

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ab1ce8e5-7ead-46e8-9106-b2ec17aeac24 · outbound

This paper cites Inception-v4, inception-resnet and the im- pact of residual connections on learning.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Inception-v4, inception-resnet and the im- pact of residual connections on learning

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.826964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.440833Z digest=sha256:78711279d713f6c708ed39d67454056c059033585f0f98df9728b33845fe56d9

Observation 9639caf7-afdc-496d-8e93-425725816246 · outbound

This paper cites Ensemble diversity facilitates adversarial transferability.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Ensemble diversity facilitates adversarial transferability

Reference 32

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verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.815273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.444492Z digest=sha256:2b68fbbbebdf177e0bebec12fd4a54b6459ef4ef8d64307f7f5e50791d14d860

Observation a201b439-79cb-4e5a-a4fe-65c08ca2b565 · outbound

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

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Training data-efficient image transformers & distillation through at- tention

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.803187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.448629Z digest=sha256:00c311030d1c288720385ac53ded459b63b595fc3bcf75ec73cfd0a78b86cba7

Observation 87b010ca-0917-416d-bd1b-be956e588ceb · outbound

This paper cites Going deeper with im- age transformers.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Going deeper with im- age transformers

Reference 34

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verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.790512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.453009Z digest=sha256:2247bba3fed002ff08d2cd71bed7ae25890c0f3f86366281e315dfa0a1b94ce0

Observation 2b271089-51e3-4de4-9bd5-ceac577526e6 · outbound

This paper cites Ensemble Adversarial Training: Attacks and Defenses.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Ensemble Adversarial Training: Attacks and Defenses

Reference 35

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unresolved
no resolver link, observed 2026-08-15T17:27:45.456906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:27:45.456906Z digest=sha256:062db532fafcead4eaa2a81cb67fbdaa185535564ac7dc1a4cc672ee56e39849

Observation 15fe691c-ade9-4efc-bb7a-b8f5239dbc92 · outbound

This paper cites Boosting adversarial transferability by block shuffle and rotation.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Boosting adversarial transferability by block shuffle and rotation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.778048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.461299Z digest=sha256:fffa0d077018826eda5276e42585e7b665b87e93a30458d1ef5bc1021836e798

Observation 19f9158e-c763-4a28-aa1b-b43bac9cc365 · outbound

This paper cites Enhancing the Transferability of Adversarial Attacks through Variance Tuning.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Enhancing the Transferability of Adversarial Attacks through Variance Tuning

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.765541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.465795Z digest=sha256:1e533f529543fec7f74e4056e0d1002b20573fc58dbfb7676a4cfc9b9f9769e6

Observation 7d338e21-ef86-4c8c-bffc-99836136a56c · outbound

This paper cites Boosting Adversarial Transferability through En- hanced Momentum.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Boosting Adversarial Transferability through En- hanced Momentum

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.753231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.470130Z digest=sha256:ccd78185657dfd8a5ebfce03858e3ddc97d7ef28fbc1040f05f781594a88affa

Observation 8f5623e5-4637-4e7c-818e-344980e81fde · outbound

This paper cites Struc- ture Invariant Transformation for better Adversarial Trans- ferability.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Struc- ture Invariant Transformation for better Adversarial Trans- ferability

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.739540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.473738Z digest=sha256:ab739e56b875e4d27f48bae3aad3ea17113b230e98ca91898365fce748b6d77f

Observation db30418b-4cb7-4624-8840-74a2d0728584 · outbound

This paper cites Better diffusion models further improve adversarial training.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Better diffusion models further improve adversarial training

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-15T17:27:45.477265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:27:45.477265Z digest=sha256:cd4ae33504b7c7f3cea9446a28635eddff139f4e694122add11ac79cddd6de30

Observation df95cbb4-0d8f-45ce-b939-f69557fc85b3 · outbound

This paper cites Towards transferable adversarial attacks on vision transformers.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Towards transferable adversarial attacks on vision transformers

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.717166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.480980Z digest=sha256:d5856f44fd85ffe82548767c7222f2c7447ec419393d54c62a922581a766da34

Observation 46b9dca7-cd41-47af-840e-25cff4c81839 · outbound

This paper cites Rethinking the backward propagation for adversarial transferability.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Rethinking the backward propagation for adversarial transferability

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.703752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.484291Z digest=sha256:eaf7936adb08568aea52090063716dfd03fcaa8ed4714cbc49fa75f2f21e0557

Observation f4b9468e-b7e6-4c5b-a03c-028c66fe9741 · outbound

This paper cites Mitigating Adversarial Effects Through Randomization.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Mitigating Adversarial Effects Through Randomization

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T17:27:45.487895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:27:45.487895Z digest=sha256:448e6be3740659d23ac4109121d95342e8bca62fdb6188ec7b05204066b20ec5

Observation b65ef6c6-abdb-494d-830f-3fdfbe8ed7da · outbound

This paper cites Improving transferabil- ity of adversarial examples with input diversity.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Improving transferabil- ity of adversarial examples with input diversity

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.691330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.491718Z digest=sha256:3563660bd9a42931b7ff9069a8aba07858133a1b21240cabc5e7a008f6e8dbfb

Observation ed46cfac-6fbf-4bb8-91c7-ddd24d1032e8 · outbound

This paper cites Stochastic variance reduced ensemble adver- sarial attack for boosting the adversarial transferability.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Stochastic variance reduced ensemble adver- sarial attack for boosting the adversarial transferability

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.679097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.495662Z digest=sha256:c8f44484462dc2926e1cd09b82195652bbf58ec5773cc52f340434e587e0080b

Observation b54d554e-a1ce-4390-84c7-74d5b6eee41e · outbound

This paper cites Improving adversarial transferability via neuron attribution-based at- tacks.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Improving adversarial transferability via neuron attribution-based at- tacks

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.666339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.499404Z digest=sha256:50e9ea9e50d12dfc9d4532998285543e03878159dcc24031a7c348fd66ea692b

Observation e50207d3-17fe-47fe-9034-4d43e99c3a9a · outbound

This paper cites an unresolved cited work.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Unresolved cited work

Reference 47

Resolution
unresolved
raw_fallback, observed 2026-08-15T17:27:45.651708Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.503208Z digest=sha256:6fe2b836fb885a0719597c75a74ef2f2df531ae23efeac68f92af2913db3063d

Observation a8d67555-5bec-41ae-9d42-579dbef413be · outbound

This paper cites Bag of Tricks to Boost Adversarial Transfer- ability.

ViT-EnsembleAttack: Augmenting Ensemble Models for Stronger Adversarial Transferability in Vision Transformers Bag of Tricks to Boost Adversarial Transfer- ability

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T17:27:45.639200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T17:27:45.506800Z digest=sha256:caee7049f1e7efcb103f755d39a94dbd57e0f034e7232c06cdcab6dd25b8fe6b

Pith citing papers

No inbound Pith citation observations are available.