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Paper Citation Record · LEDGER

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches

As of 13 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2412.01440.

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

pith.paper-citation-record.v1
2412.01440 v5

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T04:26:55.190633Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T04:35:51.583460Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

64 of 64 outbound references displayed

  • verified exact0
  • verified fuzzy34
  • unresolved30
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 03844ddd-c38d-4872-882e-259b371ea618 · outbound

This paper cites GPT-4 Technical Report.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches GPT-4 Technical Report

Reference 1

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no resolver link, observed 2026-08-12T04:26:54.901459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.901459Z digest=sha256:f9acf98df9e5d234dc5b6f33d1a3d692b12bd8ebdbddf3075428b96c3664befe

Observation 64134a61-afff-4672-a611-6904b15b3554 · outbound

This paper cites 2d human pose estimation: New benchmark and state of the art analysis.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches 2d human pose estimation: New benchmark and state of the art analysis

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.254689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.906732Z digest=sha256:48285012a687d82b38a2d41171a51bd5376a74c50995011d6d583c6c993265c5

Observation 8927b149-7a1e-49e9-8821-c83424d1afea · outbound

This paper cites Synthesizing robust adversarial examples.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Synthesizing robust adversarial examples

Reference 3

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raw_fallback, observed 2026-08-12T04:26:56.240616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.911251Z digest=sha256:80891224f496ed055ecb80aad8596361bd9508ea1b912d046c920fae23db9720

Observation 7d1f9013-00d5-4feb-a910-fb55f249febd · outbound

This paper cites Blended diffusion for text-driven editing of natural images.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Blended diffusion for text-driven editing of natural images

Reference 4

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no resolver link, observed 2026-08-12T04:26:54.915984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.915984Z digest=sha256:4f99a460757065b29bfa28ed935b8eae6b2182b2e23e4cc1580530074b79ac93

Observation 06acdf48-beb0-4a86-9ef4-e8cd77fcbfa4 · outbound

This paper cites YOLOv4: Optimal Speed and Accuracy of Object Detection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches YOLOv4: Optimal Speed and Accuracy of Object Detection

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-12T04:26:54.920519Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.920519Z digest=sha256:f33cada1afed36cb4fd0bf1d2e240a546cd8f5f4f22f4061f63238bb92e8b6b8

Observation b4b4b6a1-16db-4753-b34c-09ea133c326f · outbound

This paper cites Adversarial Patch.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Adversarial Patch

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T04:26:54.925430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.925430Z digest=sha256:d2cf5890ef4d02f0a281788497a38dfec0d8b7876410074c8c934750ce2dc01c

Observation 42bebf5a-5c0e-4a79-bce8-169931536f61 · outbound

This paper cites End- to-end object detection with transformers.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches End- to-end object detection with transformers

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.215600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.930236Z digest=sha256:e273ceeba3ab97bae45c93c9227c399c8e16a04e2741ec3520ad0cb9afff6364

Observation 75d8df91-c694-4d5d-88a2-9b84b62e8c7e · outbound

This paper cites Towards evaluating the robustness of neural networks.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Towards evaluating the robustness of neural networks

Reference 8

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no resolver link, observed 2026-08-12T04:26:54.934698Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.934698Z digest=sha256:ec0c3c494702a33741c22e7c795cfe5d68e1b98c43a630d701ea5c3444bcff31

Observation 19d93927-db4f-452f-80c8-b708bffe54db · outbound

This paper cites Deepdriving: Learning affordance for direct percep- tion in autonomous driving.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Deepdriving: Learning affordance for direct percep- tion in autonomous driving

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.191540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.939482Z digest=sha256:8ed1bfe61f094910d160d5df780129561245cd166a310d09908de22f8cdc4025

Observation 3d6d99fb-a6fa-40f2-a458-d7f43e2060a3 · outbound

This paper cites Natural Adversarial Patch Generation Method Based on Latent Diffusion Model.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Natural Adversarial Patch Generation Method Based on Latent Diffusion Model

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-12T04:26:54.943744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.943744Z digest=sha256:d87c8bcd1ae3d2fc68122b3bedb6ba11716f5bb73c4dbd52e31ad2edfe5fbf7f

Observation 567632d0-14e7-4e3f-86b8-250e5e1beac4 · outbound

This paper cites Content-based unrestricted ad- versarial attack.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Content-based unrestricted ad- versarial attack

Reference 11

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raw_fallback, observed 2026-08-12T04:26:56.176485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.948609Z digest=sha256:39eecf94dc1537c23eb1ad762f92d86c4171d509de19f4ba0f01d74f75f21b57

Observation b1d09a65-8735-46c4-a302-2dafbdeba471 · outbound

This paper cites Histograms of oriented gra- dients for human detection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Histograms of oriented gra- dients for human detection

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.161610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.953229Z digest=sha256:ed98b4ea3a143671d7c19c13ec8fc6c912f8d7cfc3ca1f180d3279fac3fd4121

Observation 939f4e08-b4e2-4736-ad45-368aaefdd56d · outbound

This paper cites Diffusion mod- els beat gans on image synthesis.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Diffusion mod- els beat gans on image synthesis

Reference 13

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no resolver link, observed 2026-08-12T04:26:54.957914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.957914Z digest=sha256:34d44bdf166a2b2213f0045d533d58a03d02d708d620b5087ed8dfc3aeb5a2fc

Observation 9f875f74-1367-4d97-8b9a-4743ee840461 · outbound

This paper cites Tnt attacks! universal naturalis- tic adversarial patches against deep neural network systems.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Tnt attacks! universal naturalis- tic adversarial patches against deep neural network systems

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.136864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.962471Z digest=sha256:34a4125b8b25137c5bfa769c1d6de4330f8608d603343aea39dc79983e9dc407

Observation 6aa83886-430e-4315-a4f4-352da66ab4c7 · outbound

This paper cites Robust Physical-World Attacks on Deep Learning Models.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Robust Physical-World Attacks on Deep Learning Models

Reference 15

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unresolved
no resolver link, observed 2026-08-12T04:26:54.966717Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.966717Z digest=sha256:190b258397f29ba3884f048e9434272560fcbb411c42cff0e6a824ef7696be3b

Observation d04f10d5-40bd-4001-92e6-3fd68461e4c7 · outbound

This paper cites Robust physical-world attacks on deep learning visual classification.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Robust physical-world attacks on deep learning visual classification

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.120774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.972367Z digest=sha256:217de9119138d74274a06f51b0660d0978b3bfee17a8704f081444f077a8c2d4

Observation 316f14e8-97b7-45cb-afcb-a4363da1d7dd · outbound

This paper cites Generative adversarial nets.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Generative adversarial nets

Reference 17

Resolution
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no resolver link, observed 2026-08-12T04:26:54.976660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.976660Z digest=sha256:b51114fee92cf3862c39a311af7f21f19ba54d9591822b6984019ba0ff71753d

Observation 27c5bf9b-e235-4cfe-b12f-cb425a8cc8b4 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Explaining and Harnessing Adversarial Examples

Reference 18

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no resolver link, observed 2026-08-12T04:26:54.981001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.981001Z digest=sha256:b9397842023f22f87250d78eecab8af9c6c717949bedb7ec4c197ed9f1c3878d

Observation d6ff5bac-14ed-40b2-a0c8-03827155f627 · outbound

This paper cites Advart: Adversarial art for camouflaged object detection attacks.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Advart: Adversarial art for camouflaged object detection attacks

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.095419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.986525Z digest=sha256:3607658496e3e3d9a6c14dba525ff3d39efef6336b9078b765c5ef8ff1c57a51

Observation 2df801be-d906-410e-bbf7-42cd6e8b5e5e · outbound

This paper cites Dap: A dynamic adversarial patch for evading person detectors.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Dap: A dynamic adversarial patch for evading person detectors

Reference 20

Resolution
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raw_fallback, observed 2026-08-12T04:26:56.080880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:54.991052Z digest=sha256:0cc78fdb9b045d4036227f6bd1805ac2c096dab34b3b3b3388cc49c69e787839

Observation 469dcb4b-2226-4110-afb7-4bd0ac0c0794 · outbound

This paper cites Prompt-to-Prompt Image Editing with Cross Attention Control.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 21

Resolution
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no resolver link, observed 2026-08-12T04:26:54.995173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.995173Z digest=sha256:48377f9f7b6f836d95f8237162085faf825ac9a4b4464ea7078194cc0212aa2a

Observation e779a124-6c2e-42fb-902a-32dd9ab659bb · outbound

This paper cites Classifier-Free Diffusion Guidance.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Classifier-Free Diffusion Guidance

Reference 22

Resolution
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no resolver link, observed 2026-08-12T04:26:54.999524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:54.999524Z digest=sha256:3a2a8e8eed73f08863df6540c40e666921480faaea36ec1a996399dd5a19a8f9

Observation 73c3d641-0f46-47d6-8f8b-a047a2ef566e · outbound

This paper cites Denoising dif- fusion probabilistic models.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Denoising dif- fusion probabilistic models

Reference 23

Resolution
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no resolver link, observed 2026-08-12T04:26:55.004103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.004103Z digest=sha256:61d4b236aaec2aaf05fcd5ae3f63f7f92688943f446826b51f3af8184bd0fee7

Observation 8a0a7bbe-02f6-481e-8aea-b04d2743ac12 · outbound

This paper cites Nat- uralistic physical adversarial patch for object detectors.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Nat- uralistic physical adversarial patch for object detectors

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.055057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.008395Z digest=sha256:8e0e0f929c0f66b16e16aeb7da33c3604af3a6c91e5c819f64d15007f67e9e63

Observation 1740060e-3fc7-4f11-8f8a-d939bd7388fe · outbound

This paper cites T-sea: Transfer-based self-ensemble attack on object detection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches T-sea: Transfer-based self-ensemble attack on object detection

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.040010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.012684Z digest=sha256:ff947abdfa17611bf1222f6c4c03816282e10c8735c85b79825316122a607703

Observation e6ecfabc-0f4b-4b24-b13f-a3c5f846721a · outbound

This paper cites Universal physical camouflage attacks on object detectors.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Universal physical camouflage attacks on object detectors

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.023431Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.016808Z digest=sha256:42ef297cc5dee41c8f7a63fb7edd62c668301a342d4297ceaf344430188e7ce5

Observation c115e840-1996-44c7-a0bc-5deadcf293c2 · outbound

This paper cites Connecting the digital and phys- ical world: Improving the robustness of adversarial attacks.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Connecting the digital and phys- ical world: Improving the robustness of adversarial attacks

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:56.008326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.021140Z digest=sha256:64be8a9926c165f7a7561d69ecb06bfc40946cded2977f61f3cca2d95bfbd972

Observation 1793ff06-362f-4fce-8148-3e0f99fcfacf · outbound

This paper cites ultralytics/yolov5, 2020.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches ultralytics/yolov5, 2020

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:55.992875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.025606Z digest=sha256:31095e84c4f858be020fc821fcedf460001187fc5b21a6f07c7c068abbc57d31

Observation 79de2481-a009-44a4-8039-8dc17555f9f4 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Adam: A Method for Stochastic Optimization

Reference 29

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no resolver link, observed 2026-08-12T04:26:55.029953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.029953Z digest=sha256:b05624c1dbdcf9d47f9b2fa3adb79bcac3c6b636534838f805e7d8413bdfc49b

Observation 8f235450-8050-4c78-af5f-ab47dbe6584f · outbound

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

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Ad- versarial examples in the physical world

Reference 30

Resolution
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raw_fallback, observed 2026-08-12T04:26:55.977436Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.034371Z digest=sha256:1d84fd9596088a60c172fef037f7e5ce35ba3a9fd29ff3c318080457434c154d

Observation 0099e7ec-3a68-410f-8137-deff73c2bf2a · outbound

This paper cites Patch of invisibility: Natural- istic black-box adversarial attacks on object de-tectors.arXiv preprint arXiv:2303.04238, 2023.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Patch of invisibility: Natural- istic black-box adversarial attacks on object de-tectors.arXiv preprint arXiv:2303.04238, 2023

Reference 31

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no resolver link, observed 2026-08-12T04:26:55.038945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.038945Z digest=sha256:9ff82ce0e057b6873a3413a18a6bffea466c6d561425d2b091f4b40415b4e66a

Observation e93b978c-a26d-4c5e-abcc-f554b5521b48 · outbound

This paper cites CapGen:An Environment-Adaptive Generator of Adversarial Patches.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches CapGen:An Environment-Adaptive Generator of Adversarial Patches

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-12T04:26:55.043260Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.043260Z digest=sha256:7af7a49b24a77b2c70663184174086aae03ee934fc21eb8fda9628971f8151c8

Observation 756c1b01-41c6-4317-9790-3a6f040b7f77 · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:55.961270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.048078Z digest=sha256:0f00cc0acaa4a07ca72fe281f0eced138a87e1839c3225d06d449e3f309aea78

Observation c7667703-a1fb-4bba-a5d4-0a1dc74a4c85 · outbound

This paper cites Diffusion to Confusion: Naturalistic Adversarial Patch Generation Based on Diffusion Model for Object Detector.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Diffusion to Confusion: Naturalistic Adversarial Patch Generation Based on Diffusion Model for Object Detector

Reference 34

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no resolver link, observed 2026-08-12T04:26:55.052237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.052237Z digest=sha256:559e9cc73408bda89cab81406fde6ff40bcf5e591582cd3499866eb0ce04ac44

Observation 1af587ea-d783-492a-b0b4-527c9b5acc44 · outbound

This paper cites Microsoft coco: Common objects in context.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Microsoft coco: Common objects in context

Reference 35

Resolution
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no resolver link, observed 2026-08-12T04:26:55.056639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.056639Z digest=sha256:0f0ccb1e50709dc4f89eab898adb0a57966d8a6deeefd46ce78eae4a9419324a

Observation 9d4b828b-62d3-4e82-82ba-3a1091e6e605 · outbound

This paper cites Beware of road markings: A new adversarial patch attack to monocular depth estimation.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Beware of road markings: A new adversarial patch attack to monocular depth estimation

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T04:26:55.936034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.061437Z digest=sha256:25c79fe9790376dc96cc43448343244c664fcb3e656792e4bdb62530aa11f722

Observation c642ac43-1051-4cc9-9cd9-82fd1b319fa5 · outbound

This paper cites Segment and complete: Defending object detectors against adversarial patch attacks with robust patch detection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Segment and complete: Defending object detectors against adversarial patch attacks with robust patch detection

Reference 37

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.065924Z digest=sha256:61d7a62f0868d3151a640b11b4d318428f14dde647d3132ff2974fb52365898d

Observation ff16fc77-fa44-46d1-b35a-d84863296d0e · outbound

This paper cites Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety

Reference 38

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source=pdf_text observed=2026-08-12T04:26:55.070309Z digest=sha256:572d22de59098565ff75a33b721403dc1b666e8a9f8bbf088d89617797795827

Observation 855c5479-908e-4e23-942b-0c8f46b26ae1 · outbound

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

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Towards deep learning models resistant to adversarial attacks

Reference 39

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source=pdf_text observed=2026-08-12T04:26:55.074863Z digest=sha256:8da4d1b0f8da74a798777be4e67fe29c4b5269f264cb9de6a9d150eb01f0097a

Observation 42e9658c-2ca6-4f4d-a085-d756979a84b2 · outbound

This paper cites Deep learning for healthcare: review, opportunities and challenges.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Deep learning for healthcare: review, opportunities and challenges

Reference 40

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raw_fallback, observed 2026-08-12T04:26:55.896496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.079169Z digest=sha256:b292c5c7e5fc509b48ba8e56521feb74adbca331c8073096799af17b7870e693

Observation 07d106f3-439b-4444-bf1e-6cb06de62109 · outbound

This paper cites Null-text inversion for editing real images using guided diffusion models.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Null-text inversion for editing real images using guided diffusion models

Reference 41

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.083527Z digest=sha256:ac31eb5408b7a050f853e6e13f844473acb3bc515652eaa162cf146dabfe7c2a

Observation a0cc8827-6f5e-40a8-9b1e-d736124a1cc1 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Learn- ing transferable visual models from natural language super- vision

Reference 42

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.087835Z digest=sha256:a747f7efc8287234ae5444e9d76d368b44696113d29bc66f6d208e0c12653f7e

Observation 45f33e89-fad1-45d0-98b9-5a10a839b130 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 43

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.091981Z digest=sha256:4426e932d703d4fe733ea07c9b120e8450cc260326c566eb8b702988baf58896

Observation ead4b7a5-6833-4d6c-9861-6b439efc1d17 · outbound

This paper cites YOLOv3: An Incremental Improvement.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches YOLOv3: An Incremental Improvement

Reference 44

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.097007Z digest=sha256:32352c3afdf16848597d42bb598218167a7f9b8113d84ca46203e2cad1ebaca6

Observation 786c1de7-388b-4194-aa8a-91c20df78249 · outbound

This paper cites Faster r-cnn: Towards real-time object detection with region proposal networks.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Faster r-cnn: Towards real-time object detection with region proposal networks

Reference 45

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raw_fallback, observed 2026-08-12T04:26:55.862596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.101699Z digest=sha256:ab3fc85e3a43ea69ed22afef49117d6b339e6598d9e10783d7b1118a7735ac4e

Observation 335ee805-57eb-4d64-92aa-2fcd3a49d6a3 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches High-resolution image syn- thesis with latent diffusion models

Reference 46

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raw_fallback, observed 2026-08-12T04:26:55.848725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.106093Z digest=sha256:01ba916fd0d70a45604615d46751893ab8395f09a387190269425a40a3ac4967

Observation 10669cde-d07c-4db6-9b9d-b562b4744967 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Photorealistic text-to-image diffusion models with deep language understanding

Reference 47

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.110530Z digest=sha256:aed272ab5ea95784d52b0545b8160963679806de5885df517bb5733e48ed07fb

Observation 3d84208d-d184-482e-a058-6b2a9bbc3cde · outbound

This paper cites Accessorize to a crime: Real and stealthy attacks on state-of-the-art face recognition.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Accessorize to a crime: Real and stealthy attacks on state-of-the-art face recognition

Reference 48

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raw_fallback, observed 2026-08-12T04:26:55.825712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.114802Z digest=sha256:26d34457de2816fa1530fcb8c1e31a3fa3c223bd9a7fb18a30d2bd4e31989a30

Observation 0eb85e0c-4e60-4fec-9d77-24ec06be32b3 · outbound

This paper cites A Survey of Multimodal-Guided Image Editing with Text-to-Image Diffusion Models.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches A Survey of Multimodal-Guided Image Editing with Text-to-Image Diffusion Models

Reference 49

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.119335Z digest=sha256:a41663878b977a8b19680ed17f225a45caaccacec95943160cb530e71d182e00

Observation c27dd4c3-0a3d-4432-aa96-9c7e947b0208 · outbound

This paper cites Denoising Diffusion Implicit Models.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Denoising Diffusion Implicit Models

Reference 50

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.123995Z digest=sha256:90da960d735b9fe7b8b192aeb95b9fc785f6f35031a836ca78e4a36ac0f3ac73

Observation 6884f959-7884-4d82-8c9c-545755a4f8ce · outbound

This paper cites Fool- ing automated surveillance cameras: adversarial patches to attack person detection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Fool- ing automated surveillance cameras: adversarial patches to attack person detection

Reference 51

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raw_fallback, observed 2026-08-12T04:26:55.812319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.128627Z digest=sha256:b4f21f98b573415a2675fc057f530787c1922a987985969cc96ab00ed01446b7

Observation 18fa73af-2c00-4cbd-a182-591437e84b4e · outbound

This paper cites YOLOv12: Attention-Centric Real-Time Object Detectors.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches YOLOv12: Attention-Centric Real-Time Object Detectors

Reference 52

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T04:26:55.133641Z digest=sha256:083639ee159b195e7dfc705c4168d440451e348ed488ac3c88d561e0dcf6837b

Observation 725709be-9f12-4c4a-b19c-fc24db3d3f50 · outbound

This paper cites Yolov10: Real-time end-to-end object de- tection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Yolov10: Real-time end-to-end object de- tection

Reference 53

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.138360Z digest=sha256:755920b250a4e204aad9d8c0fe8b41830246a6c43896cbab370e9b4a131b5a32

Observation 75fea814-3cea-4a16-b08f-0204fbd8b4ea · outbound

This paper cites Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Yolov7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors

Reference 54

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raw_fallback, observed 2026-08-12T04:26:55.784652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.142923Z digest=sha256:67d684d0a59937130ffd76e3e5faa7ee266a176c15e1bd44f0ebbf42a223fa38

Observation f0b58d28-5e3f-40dc-90c4-c2e05ab0f6a8 · outbound

This paper cites A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Reference 55

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T04:26:55.147561Z digest=sha256:608b00eef01b7b0f565a7bee205fc01913ebfa472294b1c2674f3a1b51e56176

Observation f1a34902-b9b7-4936-b916-fa6d81fd487a · outbound

This paper cites Revisiting adversarial patches for designing camera-agnostic attacks against person detection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Revisiting adversarial patches for designing camera-agnostic attacks against person detection

Reference 56

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.152786Z digest=sha256:24112e7d1a127d45506225c213b4cfd06911e3f423bbee6f7f016df86a196ef7

Observation 63feb7ef-7ba7-4ff7-92cc-f066c0a58b5b · outbound

This paper cites Transferable Adversarial Attacks for Image and Video Object Detection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Transferable Adversarial Attacks for Image and Video Object Detection

Reference 57

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T04:26:55.157557Z digest=sha256:e6c000b84195523ae61f9f2bb7e1cd1a87aa2bb755cd32418251e56067e5ac5b

Observation 6efcb6c8-5de5-47c2-bced-51083c2546ac · outbound

This paper cites Making an invisibility cloak: Real world adversarial attacks on object detectors.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Making an invisibility cloak: Real world adversarial attacks on object detectors

Reference 58

Resolution
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raw_fallback, observed 2026-08-12T04:26:55.756093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.162292Z digest=sha256:76c7fd043666b0ac06f69074ebe1a610997593238888ac4dffeeb0507bda6abc

Observation f7d797b4-abb4-4eda-8ddd-d4c7877138d1 · outbound

This paper cites Adversarial examples for se- mantic segmentation and object detection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Adversarial examples for se- mantic segmentation and object detection

Reference 59

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raw_fallback, observed 2026-08-12T04:26:55.741595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.166704Z digest=sha256:e9545c20179cb40d916439c4513b507827f23d63f211dc974fbd37a393554d74

Observation 4bc21c6f-9311-42e5-966a-00f278d55240 · outbound

This paper cites Adversarial t-shirt! evading person detectors in a phys- ical world.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Adversarial t-shirt! evading person detectors in a phys- ical world

Reference 60

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raw_fallback, observed 2026-08-12T04:26:55.726438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.171222Z digest=sha256:c3b8f858fb6853b90d13684086c536f04d5de41906d155dc4287988d5e1e9d2a

Observation b6fc1715-ea2f-470c-8cf1-8e8d51d1a817 · outbound

This paper cites Diffusion-based adversarial sample generation for improved stealthiness and controllability.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Diffusion-based adversarial sample generation for improved stealthiness and controllability

Reference 61

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raw_fallback, observed 2026-08-12T04:26:55.712070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.176217Z digest=sha256:3e4cc920901bc23950fccd81c4badf09e985a6aeb75f16281db9ed6e2f21bcae

Observation 4350c5b2-f7bb-4e0b-9a35-d50dfaac3549 · outbound

This paper cites Detrs beat yolos on real-time object detection.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Detrs beat yolos on real-time object detection

Reference 62

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raw_fallback, observed 2026-08-12T04:26:55.698013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.181393Z digest=sha256:a4f40029d0a9d4524428e51bc6228eeae99370f60b9ef3a44f463baf3b561218

Observation 747d1f7d-8deb-4af5-a771-776b38a72e42 · outbound

This paper cites Shadows can be dangerous: Stealthy and effective physical-world adversarial attack by natural phe- nomenon.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Shadows can be dangerous: Stealthy and effective physical-world adversarial attack by natural phe- nomenon

Reference 63

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.186430Z digest=sha256:752a02070635055f4c2749a181725abf38112c3fafb0994b12c0bf081b5cc2e2

Observation 0391ddf9-3089-46eb-b468-519a17ed07b3 · outbound

This paper cites Fooling thermal infrared pedestrian detectors in real world using small bulbs.

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches Fooling thermal infrared pedestrian detectors in real world using small bulbs

Reference 64

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raw_fallback, observed 2026-08-12T04:26:55.667943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-12T04:26:55.190633Z digest=sha256:ee9c626ab20d81e439168503777aa67d568aa3d5a3144a4b9d119f982a048c2c

Pith citing papers

Observation c123a101-e3eb-48f2-beb5-d86e16ba3d08 · inbound

Adversarial Diffusion Across Modalities: A Fusion Survey of Attacks, Defenses, and Evaluation for Text, Vision, and Vision-Language Models cites this paper.

Adversarial Diffusion Across Modalities: A Fusion Survey of Attacks, Defenses, and Evaluation for Text, Vision, and Vision-Language Models BadPatch: Diffusion-Based Generation of Physical Adversarial Patches

Reference 70

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arxiv_id, observed 2026-06-26T04:38:59.130159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-26T04:35:51.583460Z digest=sha256:3ebfd381554cdbcd79f9b71f4135c80b55f1e4052bd33aff9ed122331d8c2021