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Paper Citation Record · LEDGER

BadPatch: Diffusion-Based Generation of Physical Adversarial Patches

As of 17 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 2026-08-17T06:30:58.91139+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

Resolution
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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=sha256:7e781610d4c8f57e663c4ebca1b153bb4df7e2adce2e45d6baf6035be99c6a20

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.906732Z digest=sha256:04d46758327a1ac5a2e467375edc26cc23cea1ff91f66953db4ef372a443f90c

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

Resolution
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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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.911251Z digest=sha256:53dedb96527a9a42a5f378e8465da4f52feed10826d941d132cafbb42bf000b1

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:fd2af70af9104b63ec93f78444f5a183e32c9e83ec48c458967dcacfcd6ddc23

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=sha256:1e1f0007a286854201514a4a967885aaaeffcffea9c926d3d6e8f881d1ada3a6

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:e77535134b7ef715b28b737e51e6c60e7ed72723cb7789566d303d69d7634985

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.930236Z digest=sha256:23d4dfb92cf29d88a5521ec00da528bd7f43e55d40a6e34dcab5ba9c75a4f93b

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:aa466d205b40faa8415dc0c25260079c16224153d56528d246cef9d28737a601

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.939482Z digest=sha256:0715ec5437a6aae1d35a5df5ebb85077ad0641c22bb4c6ff15d5a3be3555c0da

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=sha256:59ba4605afd97b436f67e6b68bc413c70c6203eb4468815423c2f79e4c22134e

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.948609Z digest=sha256:c9f0f7eda4bde36d86e1d52453d1ce15ea5d0a6079e83b12dfb854b613384f9d

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.953229Z digest=sha256:e0d01f3153539adba76716f3a59db8c04e63a270cfde5ac8dee0c79d09d0e185

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

Resolution
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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=sha256:03e6ad0363f24cd992d5f0151ae78b3957084d0ef4cd9bec4bc838c09a7c7c7f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.962471Z digest=sha256:bdf0833679c6f6aaa0ebc04b37a5bf6bd8a89fe45cfabe44b4701c736641c3b5

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

Resolution
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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:ccfc52603d45a8f0647a67affdea1e67325c07cbe85f4b4a1aa96bb77866d8cd

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.972367Z digest=sha256:cb7424e53f4e2f8021cc1e9647ae4b434ec595f8a04a2bd1d07474bb41fd79cb

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=sha256:424e5dad58f6ae2f7e8b7b5d43565c0d090152a0c4ba014edea790cb7e8c78aa

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=sha256:5918e9902e6066d8dcf52d10085614ba368b6ae62a3e09b988baf1601194757c

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.986525Z digest=sha256:d46723cfa3777408bbac1c3783a6704c45d682c65603b2816dc1e19ab871f8fb

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:54.991052Z digest=sha256:b9577b59d888fb55790166d1ad7b48b33364584ef572ab98f90e0e37949d39bb

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=sha256:71721970d20ceb25664307441651beac9379b5776ce272ed5f0f6e2840547600

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

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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=sha256:11120b8930cf77151ff971f90671a43a547de98875c64a6343f43037972d8c44

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

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

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.004103Z digest=sha256:2477a8a49a571605bff6d9d486bf5cada46fe6a12c049bd15a650cb9c755f630

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.008395Z digest=sha256:a1e64d3f3307c8dab7651474ae55ae42af19ffb3af386c8a2fe7f86023ea6cdd

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.012684Z digest=sha256:42c14b2788d79d2bbdec9d071b6c9243df31478591a18b21bf8c35a65dff1e12

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.016808Z digest=sha256:2ef83dd5be702c77f04ac4d12a80b1846d2cf20d31a8425e4313cf54cf8b7ac6

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
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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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.021140Z digest=sha256:5a9af59f779e5fdffab24d4a58e068a3dd4aa233ad495a3ffabf1699a5249adc

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.025606Z digest=sha256:9500db1d1ffebd3f2ba0ee20c8363ada84015e7d87c444b3762b3162d30f8032

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

Resolution
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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:b7334f0f9333c833c37c94496966d74c1db12b63f5bff2a9e753ce9b45da4647

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.034371Z digest=sha256:a22b12e6707a303c6f7716816f49bdfcd2a7d7e6a0fad79c8835a009867dc8c0

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:aa731d5a02c556c6bfda263bb29d12be86c9c83cfa2044314dd6c1835a550954

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=sha256:0fd02643b1e412978216890454fbc9ab4643986cd3946bba31cc905b2d40f728

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.048078Z digest=sha256:274389acdb69a55687250151ebf5aba01132379ac14b2e586941fcdb1f463afc

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=sha256:04fcc3b12ff495ab7493e085d82ce7a511798f742c9b3efb95e4c4a5a9c17dbc

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

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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:ae302db1910a0db6cac8ad9cc6d64be8790a9789031b2e1e7c35190ace7931e2

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.061437Z digest=sha256:48ac68e1f1ee1e482b2f3fd3c57e07dd51d9a40fddae292083fb5c137fd3a22c

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.065924Z digest=sha256:d0d057c3f415e7b0fd7f42902a0c21cb3567d614fb0d8b064cac42d2502d19f0

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-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.070309Z digest=sha256:c817bcfbc88c6424533215fa2c12ae9baedf3a1c55553481dc89ed386673a2d3

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:ce486115d49100c3dd677269b744c5f12a1e4d3dd9ee6dffef99685845fae136

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.079169Z digest=sha256:4dc2b9d064d0eaba9ab3dd0998c66bb6f9b8d94c6b7f16d6a5209c6caf9efea1

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:d481bcf5b1b796b4ce1060ac79990207f60c6b9470be2dc888eb1e66a1ebe510

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=sha256:67f3f545084e171d1b32230dc85886a88b406a944408096f0c2ce3288134007e

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:c98f5c40127cbc4a49b056d197c6361b2f9a58c48c88365c5db58f2e1bd8c337

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.097007Z digest=sha256:296fe911daa22d824c119ad99fb3a056df154f6f686fdbfc642aa2968dc95a9f

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.101699Z digest=sha256:0a79432f72d82754ac16f5d8226abb00668ba04b7fd57c90f8e3c5957b181681

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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verified fuzzy
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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.106093Z digest=sha256:c5095d6beefc764878767b885565109f2131f1d2d9054e8d22193ec34d2a7181

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=sha256:11145188ab41fe6d20f105492b6174f3039c512492420e6aaf4095aea17ee283

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.114802Z digest=sha256:083b4fab8abf0f5eb32b67bab982446a626821e756f0e8a2b2d122f98c83150d

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=sha256:49d9c1b9d09abd12c9ae34120dfeba4ef98f5fb77b97365c12a61e53027325fb

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:a68ec7fc6ebe38ca3923a3887cacf19bd28fb2b3ce7c4eac7e77573b8731fd17

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.128627Z digest=sha256:b2baa65a08eab59aea4fb62ae4c74a86f005cde7272e69d1e03af50226465507

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:ac61b7613c40e3bca890c892e056cfd3e0b017c1f6836066a69e7d16b532201d

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.138360Z digest=sha256:6939c6a0a685e87934f43a3c042d313e0d6909b974e6426ea55fff6a4666918c

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.142923Z digest=sha256:439cf1d30e10b5b5d7b123d7de00ac3695c342bf34c758deaa1091039bc4f95c

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.147561Z digest=sha256:c2ba7960945052de54019fe9fdd3b5350fc191a220e61d1e428283b25b333ff6

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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raw_fallback, observed 2026-08-12T04:26:55.771249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.152786Z digest=sha256:e25b069736bdd3a25311c87fb9fd2dbad2e95f7432cc39968d22934eda15c687

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

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:26:55.157557Z digest=sha256:6cd1fea8570ff2121b514aa815bf390317493a5abc13ceeeb334e5a9646f3283

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

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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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.162292Z digest=sha256:cc4e1b0c18a99deeacec081bd90241e2ad92a69f5af8e6a16144fe1ca8381ec7

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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verified fuzzy
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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.166704Z digest=sha256:cb7c0742d046bbfaec7799464810897da55706bf01c5dc44e8bde03a8c30316b

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.171222Z digest=sha256:eaab92674318a98f10f59566835ae5aa1c2ef65348158035f88b28daf2edc4bc

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.176217Z digest=sha256:c97de35d87556ef25446c68c317ecbe40ae20b2cc2ec5d8d7ad26763450eaed9

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.181393Z digest=sha256:1fe71d73e49f64693e761a96a9181ebd5df9567f9a078444f020bd9e4969731c

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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raw_fallback, observed 2026-08-12T04:26:55.682670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.186430Z digest=sha256:64a4e1035b8c4c3c9bc547e53994c756d0e8b6144d90e4ed17fada306b7618f0

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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-12T04:26:55.190633Z digest=sha256:a67fe2c70af23407b3d693c5c610449a88244eb258e9b49a1f06696db9422367

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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verified exact
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 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-06-26T04:35:51.583460Z digest=sha256:55da4fc8355a73157685e92d98e1bcb7b311cfaf5590a8d8490ea6a52ae3da28