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Paper Citation Record · LEDGER

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective

As of 17 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2505.22604.

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

pith.paper-citation-record.v1
2505.22604 v2

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:10:14.378269Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:27:56.828271Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T20:00:17.558848Z

Reference resolution

55 of 55 outbound references displayed

  • verified exact1
  • verified fuzzy33
  • unresolved21
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f50f0ae6-6c41-4045-a004-778c3138c565 · outbound

This paper cites Cnn- generated images are surprisingly easy to spot.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Cnn- generated images are surprisingly easy to spot

Reference 1

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Source-reported events for the cited work

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

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Observation 94301217-db85-4511-8ea4-052174df6f1f · outbound

This paper cites Global texture enhancement for fake face detection in the wild.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Global texture enhancement for fake face detection in the wild

Reference 2

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Observation 674055ed-0cdd-45c0-b5b4-e2af58ade9ad · outbound

This paper cites Detecting and simulating artifacts in gan fake images.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Detecting and simulating artifacts in gan fake images

Reference 3

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Observation f944b6bd-8bcb-4bd3-81a2-056cfff012e8 · outbound

This paper cites Leveraging frequency analysis for deep fake image recognition.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Leveraging frequency analysis for deep fake image recognition

Reference 4

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T13:10:06.231473Z digest=sha256:c177c3cad946ba4b107db6c066770c6c4cca995373dfe99a1df9bb7eff8e8d4f

Observation 25f1be97-4e10-490b-8267-9b3490a11da9 · outbound

This paper cites Diffusion noise feature: Accurate and fast generated image detection.arXiv preprint arXiv:2312.02625, 2023.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Diffusion noise feature: Accurate and fast generated image detection.arXiv preprint arXiv:2312.02625, 2023

Reference 5

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Observation 13791789-b4a9-44ce-aa08-d85b8acb783c · outbound

This paper cites Aeroblade: Training-free detection of latent diffusion images using autoencoder reconstruction error.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Aeroblade: Training-free detection of latent diffusion images using autoencoder reconstruction error

Reference 6

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Observation a4e9a240-457b-4fbb-a2a4-5664e6c51d6e · outbound

This paper cites Learning on gradients: Generalized artifacts representation for gan-generated images detection.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Learning on gradients: Generalized artifacts representation for gan-generated images detection

Reference 7

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Source-reported events for the cited work

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

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Observation 4413698a-3d0e-4a8b-963a-15dedf9f6906 · outbound

This paper cites Rethink- ing the up-sampling operations in cnn-based generative network for generalizable deepfake detection.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Rethink- ing the up-sampling operations in cnn-based generative network for generalizable deepfake detection

Reference 8

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Observation 798d8375-2900-4ab7-a96d-177800d04b4f · outbound

This paper cites Detecting generated images by real images.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Detecting generated images by real images

Reference 9

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Source-reported events for the cited work

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

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Observation 6f0eb1d8-5860-43a9-8502-f2ff1e8ba7ce · outbound

This paper cites PatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective PatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection

Reference 10

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Observation 7a4d905c-dbd8-496a-a87a-bb7099b88401 · outbound

This paper cites Vulnerabilities in ai-generated image detection: The challenge of adversarial attacks.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Vulnerabilities in ai-generated image detection: The challenge of adversarial attacks

Reference 11

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Observation d14d9340-5c6a-412f-aea4-9ca4f0216b86 · outbound

This paper cites Exploring the adversarial robustness of clip for ai-generated image detection.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Exploring the adversarial robustness of clip for ai-generated image detection

Reference 12

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Source-reported events for the cited work

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

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Observation 903af63f-2550-47a9-a319-95c8d4784b5f · outbound

This paper cites Adversarial Robustness of AI-Generated Image Detectors in the Real World.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Adversarial Robustness of AI-Generated Image Detectors in the Real World

Reference 13

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Observation e30d2622-3836-4bb3-a67e-dd65ce297fb4 · outbound

This paper cites Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks

Reference 14

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Observation 1cf5d30d-44ba-4c48-a18a-689e586878f5 · outbound

This paper cites Think twice before detecting gan-generated fake images from their spectral domain imprints.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Think twice before detecting gan-generated fake images from their spectral domain imprints

Reference 15

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Source-reported events for the cited work

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

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Observation 464dc641-44be-440e-b3da-2d836198ab56 · outbound

This paper cites Evading deepfake detectors via adversarial statistical consistency.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Evading deepfake detectors via adversarial statistical consistency

Reference 16

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Source-reported events for the cited work

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

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Observation 4337e481-ec46-46c9-887e-9996b2038695 · outbound

This paper cites Exploring frequency adversarial attacks for face forgery detection.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Exploring frequency adversarial attacks for face forgery detection

Reference 17

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Source-reported events for the cited work

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

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Observation ac12986d-d257-4320-bc4c-a8aa03986be9 · outbound

This paper cites Stealthd- iffusion: Towards evading diffusion forensic detection through diffusion model.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Stealthd- iffusion: Towards evading diffusion forensic detection through diffusion model

Reference 18

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Source-reported events for the cited work

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

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Observation 87177b1f-e37f-4eb0-9e22-8bc6eb4f9736 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks, 2019.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Towards deep learning models resistant to adversarial attacks, 2019

Reference 19

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

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Observation 1746dacf-a297-40cb-91f4-b251896c166d · outbound

This paper cites Xing, Laurent El Ghaoui, and Michael I.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Xing, Laurent El Ghaoui, and Michael I

Reference 20

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Source-reported events for the cited work

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

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Observation ff7c89be-f9af-4a08-b7d0-21a9f1c9cf0e · outbound

This paper cites Pereira, and William Bialek.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Pereira, and William Bialek

Reference 21

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Source-reported events for the cited work

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

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Observation 223d470a-5592-4ca0-8ef8-110f74be4bd8 · outbound

This paper cites Robustbench: a standardized adversarial robustness benchmark.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Robustbench: a standardized adversarial robustness benchmark

Reference 22

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

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Observation 84d3ad8b-ae79-46a7-b248-5b255c3ad2e9 · outbound

This paper cites Genimage: A million-scale benchmark for detecting ai-generated image.Advances in Neural Information Processing Systems, 36:77771–77782, 2023.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Genimage: A million-scale benchmark for detecting ai-generated image.Advances in Neural Information Processing Systems, 36:77771–77782, 2023

Reference 23

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Source-reported events for the cited work

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

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Observation fa559cef-0d15-4c94-8a19-9815b278e12d · outbound

This paper cites Towards universal fake image detectors that generalize across generative models, 2024.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Towards universal fake image detectors that generalize across generative models, 2024

Reference 24

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:09.348111Z digest=sha256:c19fe0bd69eae8359bab244fdb30419a06aa28950351f20d93147faea0415c24

Observation 314f7015-0164-47fc-b02c-392281ba6a81 · outbound

This paper cites Emergence of invariance and disentanglement in deep representations.Journal of Machine Learning Research, 19(50):1–34, 2018.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Emergence of invariance and disentanglement in deep representations.Journal of Machine Learning Research, 19(50):1–34, 2018

Reference 25

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source=pdf_text observed=2026-08-07T13:10:09.577782Z digest=sha256:5f52d1234fdf051e031b7d2524470dbf957617dd4f2b4190d643e3f9691c9e18

Observation 6e2ac375-1aad-4693-b040-3b0f3417ae58 · outbound

This paper cites Information dropout: Learning optimal representations through noisy computation.IEEE transactions on pattern analysis and machine intelligence, 40(12):2897–2905, 2018.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Information dropout: Learning optimal representations through noisy computation.IEEE transactions on pattern analysis and machine intelligence, 40(12):2897–2905, 2018

Reference 26

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

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Observation 5cd9928e-1691-4331-aa2a-836cff809b39 · outbound

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Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Unresolved cited work

Reference 27

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Source-reported events for the cited work

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

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Observation d99328bc-e583-4f85-9d6e-d29ecb703272 · outbound

This paper cites an unresolved cited work.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Unresolved cited work

Reference 28

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Source-reported events for the cited work

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Observation 35ae5811-c3f3-42a7-a1cf-ac679765e91d · outbound

This paper cites Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks, 2020.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks, 2020

Reference 29

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Source-reported events for the cited work

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Observation 470a077f-eec5-4e77-8b79-11f492b79742 · outbound

This paper cites Pixle: a fast and effective black-box attack based on rearranging pixels.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Pixle: a fast and effective black-box attack based on rearranging pixels

Reference 30

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T13:10:10.367428Z digest=sha256:ea2d6463a346a68e5c2a9ba7fd58b4e3022b8be7e4553bad85a50160f287f14a

Observation 770057a1-5819-47ee-a700-10bf50101294 · outbound

This paper cites Square attack: a query-efficient black-box adversarial attack via random search, 2020.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Square attack: a query-efficient black-box adversarial attack via random search, 2020

Reference 31

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:10.441821Z digest=sha256:73aa55d4313c74b2031449dcedbdd2c978bcccb02cd27b10d25f1386a56c986e

Observation 45b4f8f8-f0ef-4ada-a4d9-002c2b97f8d7 · outbound

This paper cites On adaptive attacks to adversarial example defenses, 2020.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective On adaptive attacks to adversarial example defenses, 2020

Reference 32

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:10.615051Z digest=sha256:0dab7310680a8ce665b2ecb8c3a0b84fe1912ed366bfea666238113d209bfb37

Observation 45dcfcd6-4027-410d-b92a-53d0b2234618 · outbound

This paper cites Adversarial examples are not easily detected: Bypassing ten detection methods, 2017.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Adversarial examples are not easily detected: Bypassing ten detection methods, 2017

Reference 33

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Source-reported events for the cited work

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Observation deed95b4-0b40-400e-8a59-6d8edde5a4cb · outbound

This paper cites High-resolution image synthesis with latent diffusion models, 2022.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective High-resolution image synthesis with latent diffusion models, 2022

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:10.986550Z digest=sha256:53d1be98462f91d6c53aff712b62d1204a95f1c7d0337a40fa9c7529228b0439

Observation 2714d8bf-667e-4fab-ba6b-0409586f2894 · outbound

This paper cites Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-07T13:10:19.568011Z

Source-reported events for the cited work

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

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Observation bd355a24-a57f-4897-85cd-78e4f5d18253 · outbound

This paper cites Progressive growing of gans for im- proved quality, stability, and variation.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Progressive growing of gans for im- proved quality, stability, and variation

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-07T13:10:19.247880Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:11.348839Z digest=sha256:86a43031e26e6bd0791aa6c2a16b68540ac60d260bac9443af5b8c2f5619b1e0

Observation 341afacd-826d-40aa-9f96-47f6161cba6c · outbound

This paper cites Frequency-aware deepfake detection: Improving generalizability through frequency space learning, 2024.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Frequency-aware deepfake detection: Improving generalizability through frequency space learning, 2024

Reference 37

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no resolver link, observed 2026-08-07T13:10:11.501004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:11.501004Z digest=sha256:ba79c6d1ec42354493ffb84cfc1502e7a695983f0ae659048bf47cf7336be000

Observation cd78852e-e4bc-4f3d-849a-1888dfc4be9a · outbound

This paper cites Towards evaluating the robustness of neural networks, 2017.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Towards evaluating the robustness of neural networks, 2017

Reference 38

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verified fuzzy
raw_fallback, observed 2026-08-07T13:10:18.930916Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:11.665116Z digest=sha256:0357fb7bfca5ce22189d32a1b37767132ea39297cd561ff20e8af4e0f10d4969

Observation c5f53db8-6aae-4fcd-9e47-f6601e433bdb · outbound

This paper cites Minimally distorted adversarial examples with a fast adaptive boundary attack, 2020.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Minimally distorted adversarial examples with a fast adaptive boundary attack, 2020

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:18.612409Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:11.797039Z digest=sha256:38ef328b023648d690cfb07b6a05bb7e1ecbc31889dc5d64f8d2d883eee26925

Observation 9115cb62-8c2d-40da-bb84-21d72c34127f · outbound

This paper cites Learning transferable visual models from natural language supervision, 2021.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Learning transferable visual models from natural language supervision, 2021

Reference 40

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no resolver link, observed 2026-08-07T13:10:11.949869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:11.949869Z digest=sha256:d00577b0fba8470101c643642685dbd28d9d74bd3c46496bb1d19a930e6eed0c

Observation 929fed8f-ec08-4cc5-bf38-b6b438fca8d9 · outbound

This paper cites Randomized adversarial training via taylor expansion, 2023.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Randomized adversarial training via taylor expansion, 2023

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:18.256682Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:12.138840Z digest=sha256:95f59331fe776dc65ef4b8658050a4432291db6b6a86f3af4effa26b7ad01ec6

Observation a7f74d66-e6f3-4f50-b13d-92eed0b21f02 · outbound

This paper cites Feature squeezing: Detecting adversarial examples in deep neural networks.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Feature squeezing: Detecting adversarial examples in deep neural networks

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:17.917539Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:12.329687Z digest=sha256:0792419787fe4abb44b3a34ca035082406f962eec2abcffa7706cee3768285a5

Observation 14ffbe0f-389e-453e-aded-f1b896a030b6 · outbound

This paper cites Diffusion models for adversarial purification, 2022.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Diffusion models for adversarial purification, 2022

Reference 43

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no resolver link, observed 2026-08-07T13:10:12.492086Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:12.492086Z digest=sha256:6fba15e1f54377648c673f6623c51782cfe79fe175b6d33287bd627a818910f5

Observation 75de3bd9-fd4e-400a-9c0e-4b100d8bebaa · outbound

This paper cites Robust overfitting does matter: Test-time adversarial purification with fgsm.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Robust overfitting does matter: Test-time adversarial purification with fgsm

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:17.652342Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:12.620082Z digest=sha256:8467b6ef3520a437dc124cfff815d9a3d51f668c4785c0497d3fc84bb274a6c5

Observation 81948614-33c2-41a7-b2dd-2a1174c64d8c · outbound

This paper cites Robust clip: Unsupervised adversarial fine-tuning of vision embeddings for robust large vision-language models, 2024.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Robust clip: Unsupervised adversarial fine-tuning of vision embeddings for robust large vision-language models, 2024

Reference 45

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verified fuzzy
raw_fallback, observed 2026-08-07T13:10:17.303160Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:12.806709Z digest=sha256:88ec43842e79dba89ef595cda431e3b625b27ce55fdc581e4e8722dcd9166866

Observation 5489af7c-a26a-4eab-a24e-81f396818277 · outbound

This paper cites Forgery-aware adaptive transformer for generalizable synthetic image detection, 2023.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Forgery-aware adaptive transformer for generalizable synthetic image detection, 2023

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:16.962824Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:13.018251Z digest=sha256:09f4d623df698e4fa3eeb70398eb9ee21233e834387821cc8985866335da2f1f

Observation f7c6a5b7-6571-4b47-8ac7-6b1f83e9b178 · outbound

This paper cites Forgery-aware adaptive transformer for generalizable synthetic image detection.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Forgery-aware adaptive transformer for generalizable synthetic image detection

Reference 47

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no resolver link, observed 2026-08-07T13:10:13.221953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:13.221953Z digest=sha256:c608f7e44a7343b58b37a4683c363ca803708a6fba67f90cebdefa9c3fbbf0a8

Observation 5f3fc9c5-3689-49de-8bb5-2fe3c6d5263b · outbound

This paper cites Univer- sal adversarial perturbations.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Univer- sal adversarial perturbations

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:16.642233Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:13.373431Z digest=sha256:446f6c883f46c2ea9f4893c1b2879d9f024bcb9b8312be9c2592649e000d52d1

Observation 51ff02df-8c70-4675-848c-4b543b0c9a09 · outbound

This paper cites Adversarial example detection using latent neighborhood graph.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Adversarial example detection using latent neighborhood graph

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:16.313281Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:13.492253Z digest=sha256:fcfd41b01250a878f36f30013a7211081facc7ef0c9c35062de976bf9f928db4

Observation fb6a9ded-3626-4f10-a132-6d70972ea20e · outbound

This paper cites Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality

Reference 50

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:13.621948Z digest=sha256:13d9db6299a6568da0a51580a6c1e934df10cc92c31bd21061788ff812650942

Observation 00694277-5a5f-4366-9357-484b8414126f · outbound

This paper cites Detecting adversarial examples via reconstruction-based semantic inconsistency.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Detecting adversarial examples via reconstruction-based semantic inconsistency

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:15.974933Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:13.775128Z digest=sha256:6a021cfe39b2908daff30c33921251327e8bc8db6709b87e81bb31d35be54984

Observation 32ce206e-c471-4388-80ea-4a41f65dad3e · outbound

This paper cites The devil’s advocate: Shattering the illusion of unexploitable data using diffusion models.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective The devil’s advocate: Shattering the illusion of unexploitable data using diffusion models

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:15.689397Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:13.932430Z digest=sha256:95ce074ff1c0033e517f7870e1de7b5b850efda5aa76e9d80973c3711f4fa031

Observation 6c8633f0-b8ed-4b16-92b0-28f7d6af5643 · outbound

This paper cites Salient Conditional Diffusion for Defending Against Backdoor Attacks.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Salient Conditional Diffusion for Defending Against Backdoor Attacks

Reference 53

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verified exact
local_arxiv, observed 2026-08-07T13:10:14.688522Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:14.075220Z digest=sha256:a57b913a62b9d90bf53a2ad0edecc0ea3ddc2eda973915c674e9f0aa633510a2

Observation 5841c4ea-9b28-4a02-bd9b-0792b1dd6ffb · outbound

This paper cites Guided Diffusion Model for Adversarial Purification.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Guided Diffusion Model for Adversarial Purification

Reference 54

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unresolved
no resolver link, observed 2026-08-07T13:10:14.244190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:10:14.244190Z digest=sha256:09643f6ef869ee95360b286ee1dfdd799a291724244fbf5c836fde072af9f6c7

Observation 9465f26b-9c68-4e34-bd20-c32a88222d6a · outbound

This paper cites Improving adversarial robustness via mutual information estimation, 2022.

Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective Improving adversarial robustness via mutual information estimation, 2022

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:10:15.313829Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T13:10:14.378269Z digest=sha256:06550c873474a8801a034657517b5a7338a81f850941c01069cb01a5506580e0

Pith citing papers

Observation 28c8cbf5-bd6c-40e4-bce6-d433c6ad9bdd · inbound

MFFI: Multi-Dimensional Face Forgery Image Dataset for Real-World Scenarios cites this paper.

MFFI: Multi-Dimensional Face Forgery Image Dataset for Real-World Scenarios Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective

Reference 83

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no resolver link, observed 2026-08-15T16:27:56.828271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:27:56.828271Z digest=sha256:aeaf3f221626232d693b0bdfb57e2bb4ec7d101c2bd39f70ded665c65ad6c7e8

Observation 4e853f2f-1cac-4f0c-a6c9-6ef0388a26de · inbound

Adversarial Attacks for Good: A Survey of Proactive Protection across the Visual Content Lifecycle cites this paper.

Adversarial Attacks for Good: A Survey of Proactive Protection across the Visual Content Lifecycle Adversarially Robust AI-Generated Image Detection for Free: An Information Theoretic Perspective

Reference 179

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verified exact
local_arxiv, observed 2026-08-08T20:00:17.565652Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-08T20:00:16.640220Z digest=sha256:985ae92eb28f5718ea5f8a2295461ff31aaf8a5e0f32940585b6a5b8ae3003c5