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Paper Citation Record · LEDGER

With Great Backbones Comes Great Adversarial Transferability

As of 23 August 2026, this Paper Citation Record lists 68 of 68 outbound references and 2 inbound Pith citation observations for arXiv:2501.12275.

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

pith.paper-citation-record.v1
2501.12275 v1

Coverage vector

measured 68 of 68 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:24:21.710938Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T23:34:14.173157Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-14T19:12:50.711022Z

Reference resolution

68 of 68 outbound references displayed

  • verified exact4
  • verified fuzzy21
  • unresolved41
  • parse uncertain0
  • malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c6e53b82-0759-45da-9d1e-966b775e6c40 · outbound

This paper cites write newline.

With Great Backbones Comes Great Adversarial Transferability write newline

Reference 1

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Observation e9beda73-51a4-4ca8-b7f3-d2a5d38a0168 · outbound

This paper cites write newline.

With Great Backbones Comes Great Adversarial Transferability write newline

Reference 2

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Observation d37ea6be-5df6-4457-9c81-887c49e79c9e · outbound

This paper cites Xcit: Cross-covariance image transformers.

With Great Backbones Comes Great Adversarial Transferability Xcit: Cross-covariance image transformers

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation ec1a74fa-21a8-4d51-9c08-cac19a5df6b8 · outbound

This paper cites Square attack: A query-efficient black-box adversarial attack via random search.

With Great Backbones Comes Great Adversarial Transferability Square attack: A query-efficient black-box adversarial attack via random search

Reference 4

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Observation fd901f05-5191-47fc-9d71-3c40c2d50250 · outbound

This paper cites SiT: Self-supervised vIsion Transformer.

With Great Backbones Comes Great Adversarial Transferability SiT: Self-supervised vIsion Transformer

Reference 5

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Observation 57897ee0-9073-479c-9b9f-554d4a1f74f3 · outbound

This paper cites Are we done with ImageNet?.

With Great Backbones Comes Great Adversarial Transferability Are we done with ImageNet?

Reference 6

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Observation ed1ce24f-e299-4775-a20e-adf313a90f28 · outbound

This paper cites N., He, W., Li, B., and Song, D.

With Great Backbones Comes Great Adversarial Transferability N., He, W., Li, B., and Song, D

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 7addbcee-d4be-4289-9b63-23088f1c0322 · outbound

This paper cites A Survey of Black-Box Adversarial Attacks on Computer Vision Models.

With Great Backbones Comes Great Adversarial Transferability A Survey of Black-Box Adversarial Attacks on Computer Vision Models

Reference 8

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Observation 8e6fa522-ce78-47ee-a6b0-0bf23de32cad · outbound

This paper cites Decision-based adversarial attacks: Reliable attacks against black-box machine learning models.

With Great Backbones Comes Great Adversarial Transferability Decision-based adversarial attacks: Reliable attacks against black-box machine learning models

Reference 9

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 1ab4ef36-583e-411f-9202-bc6078132633 · outbound

This paper cites Efficient adaptive ensembling for image classification.

With Great Backbones Comes Great Adversarial Transferability Efficient adaptive ensembling for image classification

Reference 10

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation c182b5a7-6ff8-494e-a5c5-97796a2a2fb8 · outbound

This paper cites Membership inference attacks from first principles.

With Great Backbones Comes Great Adversarial Transferability Membership inference attacks from first principles

Reference 12

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Observation ff7fdbae-260a-4003-a231-bacef1b9121c · outbound

This paper cites Deep clustering for unsupervised learning of visual features.

With Great Backbones Comes Great Adversarial Transferability Deep clustering for unsupervised learning of visual features

Reference 13

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Observation da3e519e-bffa-429f-a43e-f9feda86757a · outbound

This paper cites Unsupervised learning of visual features by contrasting cluster assignments.

With Great Backbones Comes Great Adversarial Transferability Unsupervised learning of visual features by contrasting cluster assignments

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 429975e4-cc88-4dc3-8f2f-ad7cc46142a3 · outbound

This paper cites Emerging properties in self-supervised vision transformers.

With Great Backbones Comes Great Adversarial Transferability Emerging properties in self-supervised vision transformers

Reference 15

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Observation e1df9f33-742f-4945-bcff-aff8b5ca83dc · outbound

This paper cites ZOO: zeroth order optimization based black-box attacks to deep neural networks without training substitute models.

With Great Backbones Comes Great Adversarial Transferability ZOO: zeroth order optimization based black-box attacks to deep neural networks without training substitute models

Reference 16

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Observation 71955b0a-690d-41dd-abae-4963f9f93ed3 · outbound

This paper cites an unresolved cited work.

With Great Backbones Comes Great Adversarial Transferability Unresolved cited work

Reference 17

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 26539956-0870-4023-8b0c-ea54a5791f8d · outbound

This paper cites an unresolved cited work.

With Great Backbones Comes Great Adversarial Transferability Unresolved cited work

Reference 18

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Source-reported events for the cited work

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Observation 79c1ef65-81b2-48af-be1d-667376e69336 · outbound

This paper cites Boosting decision-based black-box adversarial attacks with random sign flip.

With Great Backbones Comes Great Adversarial Transferability Boosting decision-based black-box adversarial attacks with random sign flip

Reference 19

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Observation 5e2369d5-3aaf-4334-a4fb-5cf6e062edbf · outbound

This paper cites Imagenet: A large-scale hierarchical image database.

With Great Backbones Comes Great Adversarial Transferability Imagenet: A large-scale hierarchical image database

Reference 20

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Observation 0b0ba88b-a6c8-4680-a68a-95f584207d9a · outbound

This paper cites Boosting adversarial attacks with momentum.

With Great Backbones Comes Great Adversarial Transferability Boosting adversarial attacks with momentum

Reference 21

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Observation 3889fcb1-6fb9-40e1-a08a-92d636bfc3c1 · outbound

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

With Great Backbones Comes Great Adversarial Transferability An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 22

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Observation 949d025c-c5ed-442a-a177-3dbd1f60d9a7 · outbound

This paper cites An image is worth 16x16 words: Transformers for image recognition at scale.

With Great Backbones Comes Great Adversarial Transferability An image is worth 16x16 words: Transformers for image recognition at scale

Reference 23

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Observation a3cc243c-954f-4674-a339-ac4725efa650 · outbound

This paper cites Backbones-Review: Feature Extraction Networks for Deep Learning and Deep Reinforcement Learning Approaches.

With Great Backbones Comes Great Adversarial Transferability Backbones-Review: Feature Extraction Networks for Deep Learning and Deep Reinforcement Learning Approaches

Reference 24

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Observation e63872a4-69d8-405c-80b0-3b5d047fecd5 · outbound

This paper cites Sharpness-Aware Minimization for Efficiently Improving Generalization.

With Great Backbones Comes Great Adversarial Transferability Sharpness-Aware Minimization for Efficiently Improving Generalization

Reference 25

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Observation d464fa0a-5279-4b79-b5f5-94a3afd8855a · outbound

This paper cites Unsupervised representation learning by predicting image rotations.

With Great Backbones Comes Great Adversarial Transferability Unsupervised representation learning by predicting image rotations

Reference 26

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 26182f44-c3c7-47bf-891d-90992710c58b · outbound

This paper cites G., and Goldstein, T.

With Great Backbones Comes Great Adversarial Transferability G., and Goldstein, T

Reference 27

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation a880b347-4ced-40e4-841c-038c0f86cc11 · outbound

This paper cites Battle of the backbones: A large-scale comparison of pretrained models across computer vision tasks.

With Great Backbones Comes Great Adversarial Transferability Battle of the backbones: A large-scale comparison of pretrained models across computer vision tasks

Reference 28

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation b91254eb-4a38-4404-8769-8ce884a1b2df · outbound

This paper cites Generative Adversarial Networks.

With Great Backbones Comes Great Adversarial Transferability Generative Adversarial Networks

Reference 29

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Observation bf2d6db2-a808-4fe4-b743-6341aa3cc7f4 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

With Great Backbones Comes Great Adversarial Transferability Explaining and Harnessing Adversarial Examples

Reference 30

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Observation 999382db-68b4-4e43-b178-62937d739532 · outbound

This paper cites Self-supervised Pretraining of Visual Features in the Wild.

With Great Backbones Comes Great Adversarial Transferability Self-supervised Pretraining of Visual Features in the Wild

Reference 31

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Observation a8a31ba8-6e7f-4cbd-a420-e9309f3c4874 · outbound

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With Great Backbones Comes Great Adversarial Transferability Unresolved cited work

Reference 32

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation d929c7cc-1770-49cc-ad5d-cc1ac2dad7a1 · outbound

This paper cites A survey on vision transformer.

With Great Backbones Comes Great Adversarial Transferability A survey on vision transformer

Reference 33

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Observation cea8b1f7-96c8-4523-94d8-2b6b10a61b10 · outbound

This paper cites Deep residual learning for image recognition.

With Great Backbones Comes Great Adversarial Transferability Deep residual learning for image recognition

Reference 34

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Observation 595d2db7-5ea9-40bb-83e0-afa426bb9214 · outbound

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

With Great Backbones Comes Great Adversarial Transferability Black-box adversarial attacks with limited queries and information

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 60544e0b-3332-4341-a678-4cbdba46e805 · outbound

This paper cites and Tian, Y.

With Great Backbones Comes Great Adversarial Transferability and Tian, Y

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation c4b1728b-e638-4f5b-9d77-9f0ecce6bdf5 · outbound

This paper cites and Tian, Y.

With Great Backbones Comes Great Adversarial Transferability and Tian, Y

Reference 37

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Observation c95b47b0-7138-43a0-b0cd-86e4b8bba808 · outbound

This paper cites Who's Afraid of Adversarial Transferability?.

With Great Backbones Comes Great Adversarial Transferability Who's Afraid of Adversarial Transferability?

Reference 38

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local_arxiv, observed 2026-08-10T17:24:22.338751Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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Observation 3fc6d4cc-1b9a-4682-994c-f367362dbed5 · outbound

This paper cites Big transfer (bit): General visual representation learning.

With Great Backbones Comes Great Adversarial Transferability Big transfer (bit): General visual representation learning

Reference 39

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raw_fallback, observed 2026-08-10T17:24:23.123009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.601602Z digest=sha256:c097eac7c88c85a1724da07af63cdacf5a1d85989b7865e58cdca88ddc0de2b1

Observation ea94eccc-60df-4db8-86a4-e4ca083a7064 · outbound

This paper cites Learning multiple layers of features from tiny images.

With Great Backbones Comes Great Adversarial Transferability Learning multiple layers of features from tiny images

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.605332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.605332Z digest=sha256:3d7786f8ecd961b80367968844638eab27b24204b3678829ad97db43d7d5210a

Observation d01053f8-6144-49e5-bf13-90345b3f8225 · outbound

This paper cites an unresolved cited work.

With Great Backbones Comes Great Adversarial Transferability Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-10T17:24:23.099996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.608877Z digest=sha256:e68031013c37d19bb5c304b2f7499da947336b607a4cb88bf7f00fec1c55aca3

Observation 9369e1ce-0ce6-4e90-8a97-0aef226e03ea · outbound

This paper cites J., and Bengio, S.

With Great Backbones Comes Great Adversarial Transferability J., and Bengio, S

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:23.087005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.612609Z digest=sha256:9e3a3b9a2e7218782fe2b2812081015fdaae0c8b974c2587a92b5a08271b8ec1

Observation a2985f2c-055c-4e78-9780-88fbdc8a0423 · outbound

This paper cites NATTACK: learning the distributions of adversarial examples for an improved black-box attack on deep neural networks.

With Great Backbones Comes Great Adversarial Transferability NATTACK: learning the distributions of adversarial examples for an improved black-box attack on deep neural networks

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:23.073945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.616441Z digest=sha256:e4e4644e0c855d3e5584dad0b5b228bf263bb19e7f32b9c46d81a72f09b56e95

Observation 00485618-781f-48af-8104-f480568964e3 · outbound

This paper cites A., M \" u ller, R., and Bertinetto, L.

With Great Backbones Comes Great Adversarial Transferability A., M \" u ller, R., and Bertinetto, L

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:23.062739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.620019Z digest=sha256:3b4c734f4f5d1daab7268164cb9abb5494522f0528bbabf0cc4339271b5d1da3

Observation 10f2ad50-4aa0-4966-8d86-4085c066a919 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

With Great Backbones Comes Great Adversarial Transferability Towards deep learning models resistant to adversarial attacks

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:23.050447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.623798Z digest=sha256:d2f2985625dca3a71636d19b9567e1dcbed6e0a855fbbc03e9ad9af2eecd35ad

Observation 12cb910f-4fce-402f-8fe1-89d652044c43 · outbound

This paper cites L., Pardo, J., Pardo, L., and Pardo, M.

With Great Backbones Comes Great Adversarial Transferability L., Pardo, J., Pardo, L., and Pardo, M

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:23.036587Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.627745Z digest=sha256:7ae47fa5abe0bd352e83ccbee79b7d7a48afb845b2e00deec6bb8dd25a9cdff3

Observation 97216994-19f9-4c6e-b794-ecda2b5488d1 · outbound

This paper cites and van der Maaten, L.

With Great Backbones Comes Great Adversarial Transferability and van der Maaten, L

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.631842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.631842Z digest=sha256:91a00aa615e47d0830f7561190f0aa8efa59a1706e38158d377ace264dd870b4

Observation 18b4366b-e9f6-4f47-937f-757387f2f9d3 · outbound

This paper cites an unresolved cited work.

With Great Backbones Comes Great Adversarial Transferability Unresolved cited work

Reference 48

Resolution
unresolved
raw_fallback, observed 2026-08-10T17:24:23.021407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.635732Z digest=sha256:a22691e1d754c4dbcc6a497ab3e78e2e74a74774aa727420fb6bb89b000ae2a1

Observation ba926c3a-fe53-4bd8-99d0-46694e1de80f · outbound

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

With Great Backbones Comes Great Adversarial Transferability Deepfool: A simple and accurate method to fool deep neural networks

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.639446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.639446Z digest=sha256:828680d83574b827e295122fcb55feac4dc24f253fc3c792ebf85f6bf136c492

Observation eab0860d-8cfb-4ede-bd9a-426e1dd42b58 · outbound

This paper cites Simple Black-Box Adversarial Perturbations for Deep Networks.

With Great Backbones Comes Great Adversarial Transferability Simple Black-Box Adversarial Perturbations for Deep Networks

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.643069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.643069Z digest=sha256:f67125303ca2222a38a6260d26f5e0bb6013d879de1ca919d98ec35de27a3e65

Observation 949756a3-041a-4578-bb0c-953a371a12ca · outbound

This paper cites S., and Porikli, F.

With Great Backbones Comes Great Adversarial Transferability S., and Porikli, F

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:23.006557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.646997Z digest=sha256:155c41dcd291ad481e1b9f457543349f17a7a7292afa8033c4038f215422853d

Observation 65216333-d346-4b8c-8563-e20be76e852f · outbound

This paper cites and Deng, J.

With Great Backbones Comes Great Adversarial Transferability and Deng, J

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:22.993666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.650445Z digest=sha256:9b28487b4b460674046d5a515f5dec7acb6959393df82232af0dbecd46072cf3

Observation a1ee2367-0820-4641-9e01-d62646c60ab4 · outbound

This paper cites and Zisserman, A.

With Great Backbones Comes Great Adversarial Transferability and Zisserman, A

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:22.980949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.653958Z digest=sha256:10fd0c4db48c5110722eb38ac574d12cd3fd039f6c70d856c8b81cb4a8447caf

Observation 5350b706-b5de-4d4f-8e43-a7c8243d0857 · outbound

This paper cites and Favaro, P.

With Great Backbones Comes Great Adversarial Transferability and Favaro, P

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.657521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.657521Z digest=sha256:e09cfd3b1379f8bca7759c7032ae2056c42c43121e8a92f07622d28a72f0c34e

Observation 4c3e995f-a9c9-4ec4-b29c-41709a6ac8cd · outbound

This paper cites D., Goodfellow, I.

With Great Backbones Comes Great Adversarial Transferability D., Goodfellow, I

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.661853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.661853Z digest=sha256:fab17f347b73c4479831df478e385d6425fdb6fd80bb11caa1a2675785fcb42c

Observation da74f90e-0dd6-4f5e-bc89-b696854d4bed · outbound

This paper cites M., Vedaldi, A., Zisserman, A., and Jawahar, C.

With Great Backbones Comes Great Adversarial Transferability M., Vedaldi, A., Zisserman, A., and Jawahar, C

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.665535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.665535Z digest=sha256:1246b9f1363397dbbef9aaf397382f2cc8868253d98655140389f85ad492518f

Observation b47ade0e-e061-4d20-9955-c85a3b6e3782 · outbound

This paper cites S., and Manikandan, V.

With Great Backbones Comes Great Adversarial Transferability S., and Manikandan, V

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:22.961100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.668983Z digest=sha256:6f93ffd30abd5befd9672637643f7bef36d9c6d420c8c773c4408653c0016e40

Observation e0f6322e-5dd4-483b-9a94-8059b13fc2b8 · outbound

This paper cites an unresolved cited work.

With Great Backbones Comes Great Adversarial Transferability Unresolved cited work

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.672631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.672631Z digest=sha256:3edcf96fb5eb400becf5236e1c8487567a6581f23e067bb210dd8381df4a5d1c

Observation af5e29fe-81ef-471d-b1aa-5efe10cabf9a · outbound

This paper cites Training meta-surrogate model for transferable adversarial attack.

With Great Backbones Comes Great Adversarial Transferability Training meta-surrogate model for transferable adversarial attack

Reference 59

Resolution
malformed identifier
no resolver link, observed 2026-08-10T17:24:21.676801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.676801Z digest=sha256:cead2c2ee1f7910a00e515f8c07c6106eee95d2888a4cd612af0e03fa6b3526f

Observation 26d8dbaa-bc95-483a-ae74-e9ccba6b0f33 · outbound

This paper cites Analysis of variance (anova).

With Great Backbones Comes Great Adversarial Transferability Analysis of variance (anova)

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:22.949275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.680123Z digest=sha256:9e7c96dc73bbfdb659d68efc9dbe62f85f038f53c1b685773c93afc4b294d8ce

Observation 8c48bca7-6bf5-4642-a731-15a9570a06e2 · outbound

This paper cites Intriguing properties of neural networks.

With Great Backbones Comes Great Adversarial Transferability Intriguing properties of neural networks

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.683421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.683421Z digest=sha256:bb8d59d245c0f144a22c7b825887b2fec538611551cdc66cfb283f897d3f3b19

Observation 78124b96-1730-4aab-a69d-746c007bc289 · outbound

This paper cites A., Friedland, G., Elizalde, B., Ni, K., Poland, D., Borth, D., and Li, L.

With Great Backbones Comes Great Adversarial Transferability A., Friedland, G., Elizalde, B., Ni, K., Poland, D., Borth, D., and Li, L

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.686854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.686854Z digest=sha256:a5f0eb2a17978fe690640201a38f70a1b63943b98f7eeeee83777345214ca2c7

Observation c6942f6f-ee7b-47ed-8e4b-2df556862eac · outbound

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

With Great Backbones Comes Great Adversarial Transferability Training data-efficient image transformers & distillation through attention

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:22.937419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.690015Z digest=sha256:1301f91b91e1af51969eb8b5c635965b4dafb4ef43b8978de37b11f4a0f29c7d

Observation 570bb95b-80f8-4ae3-9e4d-245804cd5ca0 · outbound

This paper cites H., and Echizen, I.

With Great Backbones Comes Great Adversarial Transferability H., and Echizen, I

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.693272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.693272Z digest=sha256:32c07b3b31a3729978f59ed34f14b562c152aa5f23cdb35b77abe08325e6489f

Observation 8d6da9ba-0f12-4a8d-8d00-e48f8bf48a24 · outbound

This paper cites X., and Lin, D.

With Great Backbones Comes Great Adversarial Transferability X., and Lin, D

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.696601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.696601Z digest=sha256:5515eb68ead3da9b5687fe1ee0a9ab919165e95e3086fc4aa4a6ef81f56da7cc

Observation 89d13b4e-f072-44a9-86f4-4a14f6139d67 · outbound

This paper cites CoCa: Contrastive Captioners are Image-Text Foundation Models.

With Great Backbones Comes Great Adversarial Transferability CoCa: Contrastive Captioners are Image-Text Foundation Models

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.699709Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.699709Z digest=sha256:3a50c587994d912ac911350e2ed20e3b6dd3bca5de8ae5d1e18890e59e05c318

Observation 80b7f876-d683-4e0a-8e92-651eecf359d3 · outbound

This paper cites an unresolved cited work.

With Great Backbones Comes Great Adversarial Transferability Unresolved cited work

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-10T17:24:21.703584Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T17:24:21.703584Z digest=sha256:b4feae150cfee677988549b093c2b59e210f33ddfa24dc010d224a40d0155c23

Observation 33b3a93d-e6c6-4767-8c11-02c566662fe4 · outbound

This paper cites Toward understanding and boosting adversarial transferability from a distribution perspective.

With Great Backbones Comes Great Adversarial Transferability Toward understanding and boosting adversarial transferability from a distribution perspective

Reference 68

Resolution
metadata mismatch
raw_fallback, observed 2026-08-10T17:24:21.900423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.707286Z digest=sha256:1183455ce53bf552cf3335b14eae10b54e166eff3b4e2184b627b1ac8aa85244

Observation 7857f793-a142-4672-8678-2c898cbda89c · outbound

This paper cites and Asano, Y.

With Great Backbones Comes Great Adversarial Transferability and Asano, Y

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T17:24:22.924731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T17:24:21.710938Z digest=sha256:10d6a94b98260fc22e169fb24067130d9625b983310828201d5ccc34a2c94711

Pith citing papers

Observation 74800adf-3436-442f-927b-0c1b08d36420 · inbound

Backbone is All You Need: Assessing Vulnerabilities of Frozen Foundation Models in Synthetic Image Forensics cites this paper.

Backbone is All You Need: Assessing Vulnerabilities of Frozen Foundation Models in Synthetic Image Forensics With Great Backbones Comes Great Adversarial Transferability

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:12:50.713624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-14T19:11:32.679508Z digest=sha256:8418f8e173511b40586d4907790111f71c9fa1b54b1ec2102739b49b18d08a8c

Observation 4bf1bf2c-30ce-4030-8d39-f3b5a83479ba · inbound

Large Language Models as Unified Multimodal Learners for Clinical Prediction cites this paper.

Large Language Models as Unified Multimodal Learners for Clinical Prediction With Great Backbones Comes Great Adversarial Transferability

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-01T23:34:14.173157Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T23:34:14.173157Z digest=sha256:3c2dc462e3110e177cc6b7b522560335578f1d3308ea5c6d2657e685a6069b1d