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Paper Citation Record · LEDGER

Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2203.08392.

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

pith.paper-citation-record.v1
2203.08392 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T23:45:36.066294Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T05:47:41.595018Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 950a93cb-72ac-485c-a251-e354c6b4d18d · inbound

Adversarial Robustness for Deep Learning-based Wildfire Prediction Models cites this paper.

Adversarial Robustness for Deep Learning-based Wildfire Prediction Models Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-10T23:45:36.066294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T23:45:36.066294Z digest=sha256:b9ac5121d20f811eb0f29c5a4f425a5f6b3c55e269f1932e36d03409db2366de

Observation 0c40af13-8193-4d13-af12-7f909b157f6e · inbound

Mechanistic Understandings of Representation Vulnerabilities and Engineering Robust Vision Transformers cites this paper.

Mechanistic Understandings of Representation Vulnerabilities and Engineering Robust Vision Transformers Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-08T21:55:56.852148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:55:56.852148Z digest=sha256:c6c8bf633b0421da504e8c3ac7f5d200dffed853ef456969950b8d9b60c04cb7

Observation 59772677-491a-4b2e-8d53-72b1106ba510 · inbound

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study cites this paper.

Preventing Adversarial AI Attacks Against Autonomous Situational Awareness: A Maritime Case Study Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T13:32:59.262639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:32:59.262639Z digest=sha256:28b33373d507a86fd73a2f35f9f8999f0d035336d40da0cafde624cb8416e5be

Observation 5f77670b-aeb1-450d-814a-3b8be080d24f · inbound

Attacking Attention of Foundation Models Disrupts Downstream Tasks cites this paper.

Attacking Attention of Foundation Models Disrupts Downstream Tasks Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T11:09:06.657206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:09:06.657206Z digest=sha256:3e7fe390a42d1f34ba7f6b5e359c75cb21857893fff007e5bd086c77940ef0ca

Observation 3ba92546-c879-455d-9639-76bf47d3c14a · inbound

Vision Transformer with Adversarial Indicator Token against Adversarial Attacks in Radio Signal Classifications cites this paper.

Vision Transformer with Adversarial Indicator Token against Adversarial Attacks in Radio Signal Classifications Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T01:09:14.398038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:09:14.398038Z digest=sha256:c29d4c4c81b6b3f6fda661ba05dd3e785264bc0908a3e7f3a92b70c5dad8c1c0

Observation 7d9550c1-6e8d-41d7-bc57-f3aba39b4f97 · inbound

Guaranteed Jailbreaking Defense via Disrupt-and-Rectify Smoothing cites this paper.

Guaranteed Jailbreaking Defense via Disrupt-and-Rectify Smoothing Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:51:27.553214Z

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=2026-05-12T04:50:08.866969Z digest=sha256:7b5cbab091455f7edc0a83ce500c6a193516f7b2d7852f933ddb90975f076e33

Observation f0c230d6-72cb-4178-b19c-960c504ce165 · inbound

Test-time Adversarial Takeover: A Real-time Hijacking Interface against Robotic Diffusion Policies cites this paper.

Test-time Adversarial Takeover: A Real-time Hijacking Interface against Robotic Diffusion Policies Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Reference 35

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T05:47:41.596605Z

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=2026-06-27T13:04:32.423616Z digest=sha256:7f28305067eaa9d14927cfcd4b41228815fb5a51e86a98a63d7bb9fa8e2a60e6

Observation 89c56a5b-918b-40c6-b59f-b49749706a81 · inbound

Corrupting Attention: Evasion-Based Adversarial Attacks on Encoder Attention in Detection Transformers cites this paper.

Corrupting Attention: Evasion-Based Adversarial Attacks on Encoder Attention in Detection Transformers Patch-Fool: Are Vision Transformers Always Robust Against Adversarial Perturbations?

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T22:46:06.832506Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:46:06.832506Z digest=sha256:a7c76cc0bf7e817c22343c1a045842e1c51a4723c579d134be4985c0cc0d67b9