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Paper Citation Record · LEDGER

A Bias-Free Training Paradigm for More General AI-generated Image Detection

As of 19 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 4 inbound Pith citation observations for arXiv:2412.17671.

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

pith.paper-citation-record.v1
2412.17671 v2

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T05:23:40.197045Z

measured 62 of 62 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:53:43.972690Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T11:21:00.848903Z

Reference resolution

58 of 58 outbound references displayed

  • verified exact0
  • verified fuzzy46
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 168dc670-b37d-4186-907d-4ba95f357e87 · outbound

This paper cites Parents and Children: Distinguishing Multimodal Deep- Fakes from Natural Images.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Parents and Children: Distinguishing Multimodal Deep- Fakes from Natural Images

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 9e79f3fa-1939-4f79-97ac-9a546252dd60 · outbound

This paper cites Synthbuster: Towards detection of diffu- sion model generated images.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Synthbuster: Towards detection of diffu- sion model generated images

Reference 2

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Source-reported events for the cited work

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Observation 7302417d-b7e0-43c2-be19-8a2087d2f42b · outbound

This paper cites Contrasting Deepfakes Diffusion via Contrastive Learning and Global-Local Similarities.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Contrasting Deepfakes Diffusion via Contrastive Learning and Global-Local Similarities

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 353df5c7-4837-479d-ab80-0536a573ef7b · outbound

This paper cites Identi- fying and Mitigating the Security Risks of Generative AI.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Identi- fying and Mitigating the Security Risks of Generative AI

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0846a9c3-5096-4752-81b3-b7979fc4a8f6 · outbound

This paper cites A possible pit- fall in the experimental analysis of tampering detection algo- rithms.

A Bias-Free Training Paradigm for More General AI-generated Image Detection A possible pit- fall in the experimental analysis of tampering detection algo- rithms

Reference 5

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Source-reported events for the cited work

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Observation e235856a-4560-4bb2-ae6c-873cc7b9415d · outbound

This paper cites Real-Time Deepfake Detection in the Real-World.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Real-Time Deepfake Detection in the Real-World

Reference 6

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Source-reported events for the cited work

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Observation 2b242778-d01a-4400-9c57-8d584307880e · outbound

This paper cites FakeInversion: Learning to Detect Images from Un- seen Text-to-Image Models by Inverting Stable Diffusion.

A Bias-Free Training Paradigm for More General AI-generated Image Detection FakeInversion: Learning to Detect Images from Un- seen Text-to-Image Models by Inverting Stable Diffusion

Reference 7

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Source-reported events for the cited work

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Observation cecdc5e3-cd79-4e18-b81f-0adb0902bbd5 · outbound

This paper cites AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image Detectors.

A Bias-Free Training Paradigm for More General AI-generated Image Detection AntifakePrompt: Prompt-Tuned Vision-Language Models are Fake Image Detectors

Reference 8

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Source-reported events for the cited work

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Observation 06e7bd4f-63d8-473d-8402-f796bbf0283a · outbound

This paper cites Intriguing properties of syn- thetic images: from generative adversarial networks to dif- fusion models.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Intriguing properties of syn- thetic images: from generative adversarial networks to dif- fusion models

Reference 9

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Source-reported events for the cited work

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Observation f5e494f4-3fa6-4e04-80bc-9aa25cc47ad3 · outbound

This paper cites On the de- tection of synthetic images generated by diffusion models.

A Bias-Free Training Paradigm for More General AI-generated Image Detection On the de- tection of synthetic images generated by diffusion models

Reference 10

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Source-reported events for the cited work

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Observation b64a67b5-ccaf-4b5b-ac48-60a0e98d8980 · outbound

This paper cites Raising the Bar of AI-generated Image Detection with CLIP.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Raising the Bar of AI-generated Image Detection with CLIP

Reference 11

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Source-reported events for the cited work

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Observation 7102b601-ac34-41bb-bc93-1300547d5883 · outbound

This paper cites RAISE: a raw images dataset for dig- ital image forensics.

A Bias-Free Training Paradigm for More General AI-generated Image Detection RAISE: a raw images dataset for dig- ital image forensics

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 0e966f9f-c9c0-4e08-ab3d-e99e49f2fe07 · outbound

This paper cites Vision Transformers Need Registers.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Vision Transformers Need Registers

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation fae6b9c0-2e6b-42e2-b950-c6084866149a · outbound

This paper cites CASIA Image Tam- pering Detection Evaluation Database.

A Bias-Free Training Paradigm for More General AI-generated Image Detection CASIA Image Tam- pering Detection Evaluation Database

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 49cc26d8-bde1-4039-a399-dffcde493d10 · outbound

This paper cites Watch your up-convolution: CNN based Generative Deep Neural Networks are failing to reproduce spectral distributions.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Watch your up-convolution: CNN based Generative Deep Neural Networks are failing to reproduce spectral distributions

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 5c362eb4-7b48-478a-88e1-d738946686e7 · outbound

This paper cites Fourier spectrum discrepancies in deep network generated images.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Fourier spectrum discrepancies in deep network generated images

Reference 16

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Source-reported events for the cited work

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Observation 6213da8f-b8a1-4247-9445-24597f00929d · outbound

This paper cites Art and the science of generative AI.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Art and the science of generative AI

Reference 17

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Source-reported events for the cited work

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Observation ab9aacaa-290d-47f1-a335-63517243ab49 · outbound

This paper cites Are GAN generated images easy to detect? A critical analysis of the state-of-the- art.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Are GAN generated images easy to detect? A critical analysis of the state-of-the- art

Reference 18

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Source-reported events for the cited work

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Observation 310af797-9bc0-478b-8755-85ef4347e7c3 · outbound

This paper cites Fake or JPEG? Revealing Common Biases in Generated Image Detection Datasets.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Fake or JPEG? Revealing Common Biases in Generated Image Detection Datasets

Reference 19

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 51f15730-f556-471a-9d76-45909946751c · outbound

This paper cites FingerprintNet: Synthesized Fin- gerprints for Generated Image Detection.

A Bias-Free Training Paradigm for More General AI-generated Image Detection FingerprintNet: Synthesized Fin- gerprints for Generated Image Detection

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 3a2b83cc-040f-45e7-aba0-a7d2a4807634 · outbound

This paper cites Evolution of Detection Performance throughout the Online Lifespan of Synthetic Images.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Evolution of Detection Performance throughout the Online Lifespan of Synthetic Images

Reference 21

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Observation 58c9853c-4380-42d9-983d-7fb8dc320656 · outbound

This paper cites Leveraging Representations from Intermediate Encoder-blocks for Syn- thetic Image Detection.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Leveraging Representations from Intermediate Encoder-blocks for Syn- thetic Image Detection

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 45358065-c242-47d7-91bd-1f08a2a86a68 · outbound

This paper cites Faster Than Lies: Real-time Deepfake Detection using Binary Neural Networks.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Faster Than Lies: Real-time Deepfake Detection using Binary Neural Networks

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 59877ff0-02db-4868-b744-ea673510a0aa · outbound

This paper cites Autoregressive Image Generation without Vec- tor Quantization.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Autoregressive Image Generation without Vec- tor Quantization

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a2e47794-e1d1-410d-8009-97f4c084be31 · outbound

This paper cites MaskSim: Detection of Syn- thetic Images by Masked Spectrum Similarity Analysis.

A Bias-Free Training Paradigm for More General AI-generated Image Detection MaskSim: Detection of Syn- thetic Images by Masked Spectrum Similarity Analysis

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation aeccd8df-902b-4d43-ac48-c17305986356 · outbound

This paper cites FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Models.

A Bias-Free Training Paradigm for More General AI-generated Image Detection FakeBench: Probing Explainable Fake Image Detection via Large Multimodal Models

Reference 26

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Source-reported events for the cited work

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Observation 82b6ec83-fced-4a13-a943-90142758b6be · outbound

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

A Bias-Free Training Paradigm for More General AI-generated Image Detection Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 27

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no resolver link, observed 2026-08-11T05:23:39.505154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 994e7407-7815-4b0d-8f6b-d5d715c49165 · outbound

This paper cites Lawrence Zitnick.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Lawrence Zitnick

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:23:39.599577Z digest=sha256:cd52b81621171ce06fdaa29f9a2775fbde6471785c9e8379a9317714cbdf5a51

Observation 6f0a9800-5032-4136-b468-449d83c736ef · outbound

This paper cites Forgery-aware Adaptive Transformer for Generalizable Synthetic Image Detection.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Forgery-aware Adaptive Transformer for Generalizable Synthetic Image Detection

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation a2de3f2a-0832-4e5e-b3fd-ec7261049170 · outbound

This paper cites A Decade’s Battle on Dataset Bias: Are We There Yet? In ICLR, 2025.

A Bias-Free Training Paradigm for More General AI-generated Image Detection A Decade’s Battle on Dataset Bias: Are We There Yet? In ICLR, 2025

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation acb6d877-436e-433a-a82a-657c40ba18fd · outbound

This paper cites When Synthetic Traces Hide Real Content: Analysis of Stable Dif- fusion Image Laundering.

A Bias-Free Training Paradigm for More General AI-generated Image Detection When Synthetic Traces Hide Real Content: Analysis of Stable Dif- fusion Image Laundering

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 983b2d9e-9567-4552-97bd-eda3d09d356c · outbound

This paper cites Do GANs Leave Artificial Fingerprints? In MIPR, pages 506–511, 2019.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Do GANs Leave Artificial Fingerprints? In MIPR, pages 506–511, 2019

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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Observation 6a9c4782-e06b-41ab-b60e-e660c438340c · outbound

This paper cites Towards uni- versal fake image detectors that generalize across generative models.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Towards uni- versal fake image detectors that generalize across generative models

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.811769Z digest=sha256:96fb200b38c2b4a369934c6f0303e1da91468f73f8b7deb0a34efd284545788d

Observation 9507f210-7694-4a25-9149-e7d2a56bc1bd · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervi- sion.

A Bias-Free Training Paradigm for More General AI-generated Image Detection DINOv2: Learning Robust Visual Features without Supervi- sion

Reference 34

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raw_fallback, observed 2026-08-11T05:23:41.038459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.815942Z digest=sha256:dd7bc05e9a1af25f58a0fefa43b81e3b9484bdece7ae615d6d5f63aa97f25421

Observation a2cbbf4d-219a-4190-9fe5-140e9da2436c · outbound

This paper cites Obtaining Well Calibrated Probabilities Using Bayesian Binning.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Obtaining Well Calibrated Probabilities Using Bayesian Binning

Reference 35

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verified fuzzy
raw_fallback, observed 2026-08-11T05:23:41.025131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.819623Z digest=sha256:d102292dd00d3f39867eb6d4961499e43eb9ec6f9442eb5962644fbb95be71eb

Observation ae8da6ec-73f6-456c-9839-22acd8c3f3b2 · outbound

This paper cites Evaluating Predictive Uncertainty Challenge.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Evaluating Predictive Uncertainty Challenge

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:41.011395Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.823001Z digest=sha256:959f743a2d1745bff3d379ce092de58cfd418c293ac68024e11deb0d84d98e14

Observation 15f06695-224c-4fd7-bbde-01cf2a9c45d4 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Super- vision.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Learning Transferable Visual Models From Natural Language Super- vision

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.987167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.826882Z digest=sha256:dba3f64631f1dd799b8446af0b4af289bab248ac3105f077dda4f1892657ecf4

Observation dce6098a-1d87-4dc6-bce4-df0095c44bff · outbound

This paper cites Aligned Datasets Improve Detection of Latent Diffusion-Generated Images.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Aligned Datasets Improve Detection of Latent Diffusion-Generated Images

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-11T05:23:39.830597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:23:39.830597Z digest=sha256:3dd187b8aad515af1607a0c1dc057dea4e01cb62f111952ab758190d0c74dcad

Observation fe20e0dc-47a1-4ed7-b940-e127879fee55 · outbound

This paper cites Stable Diffu- sion.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Stable Diffu- sion

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.972825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.835381Z digest=sha256:91fa070fa8c16943f2213b87344fcc2b4d433038bbfa5e9a68629d2682162b60

Observation 87600c04-c3b4-4757-b2f1-78308926f649 · outbound

This paper cites DE- FAKE: Detection and Attribution of Fake Images Gener- ated by Text-to-Image Generation Models.

A Bias-Free Training Paradigm for More General AI-generated Image Detection DE- FAKE: Detection and Attribution of Fake Images Gener- ated by Text-to-Image Generation Models

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.958699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.839119Z digest=sha256:f62c34d640e5c2dfc808e03c399dea2a870f8d135318823155d9d1f20dd273bd

Observation 610268ae-253e-43db-bdce-9e131d8df863 · outbound

This paper cites Learning on Gradients: Generalized Arti- facts Representation for GAN-Generated Images Detection.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Learning on Gradients: Generalized Arti- facts Representation for GAN-Generated Images Detection

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.946493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.843305Z digest=sha256:8171d0c11ebec05944413741d32a7a3945bfb0ad3e1c8b5d03d52612e3892f32

Observation 2618025b-41af-4f2e-b937-30f59ba6320c · outbound

This paper cites Rethinking the Up-Sampling Operations in CNN-based Generative Network for Generalizable Deepfake Detection.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Rethinking the Up-Sampling Operations in CNN-based Generative Network for Generalizable Deepfake Detection

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.811783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.848265Z digest=sha256:670e69293ad67e8ebdcc7e349e87d95733942ee46210b30abc08dfdb52eb978c

Observation 06bc4048-4029-4c2c-9cac-647eca99752f · outbound

This paper cites C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detection.

A Bias-Free Training Paradigm for More General AI-generated Image Detection C2P-CLIP: Injecting Category Common Prompt in CLIP to Enhance Generalization in Deepfake Detection

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-11T05:23:39.852148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:23:39.852148Z digest=sha256:16865e23cd5899a70a87b82d6fce3fb8c9e4c3785f5ae244733406f1cd29744d

Observation a2948feb-1ec2-4e73-a79c-6c0b98997d2e · outbound

This paper cites Synthetic Image Verification in the Era of Generative AI: What Works and What Isn’t There Yet.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Synthetic Image Verification in the Era of Generative AI: What Works and What Isn’t There Yet

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.732971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.856821Z digest=sha256:9b086f4cabdec992bc8255c002218943790b2109df8d4d46a806d52d9bd0aa87

Observation d329984a-53d1-466c-a6d3-e591c4bb30dc · outbound

This paper cites an unresolved cited work.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-11T05:23:40.684811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.861126Z digest=sha256:ddcb2b403af4751ff18d370464f1bc5800a0bfb0c96abe0b296e430bd708f189

Observation 99f3775e-ac04-4d4f-a497-ad88b6f4bd15 · outbound

This paper cites CNN-generated images are sur- prisingly easy to spot.

A Bias-Free Training Paradigm for More General AI-generated Image Detection CNN-generated images are sur- prisingly easy to spot

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-11T05:23:39.902893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:23:39.902893Z digest=sha256:f2473a2d79d98b4ede43d2cd7800cb377614f3406475e1804ea3a42c82e634c0

Observation ddd7566d-f687-4868-baf2-0027c4c8d15d · outbound

This paper cites DIRE for diffusion-generated image detection.

A Bias-Free Training Paradigm for More General AI-generated Image Detection DIRE for diffusion-generated image detection

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.647725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:40.122160Z digest=sha256:945e6dc0e066a392842b265f4f1c770f198cdb843cf53922f3b38c156be209e7

Observation d7cdb038-a0f0-4bc4-b483-a0cdf5374f93 · outbound

This paper cites A Sanity Check for AI- generated Image Detection.

A Bias-Free Training Paradigm for More General AI-generated Image Detection A Sanity Check for AI- generated Image Detection

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.633551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:40.159899Z digest=sha256:6f2d8b495b96c637d09617758195c1db6eb38740ff82baceaab7da0742cb5b96

Observation 7fbcc67f-c38f-4099-a393-8fdb206add01 · outbound

This paper cites Diffusion Probabilistic Model Made Slim.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Diffusion Probabilistic Model Made Slim

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.618446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:40.163997Z digest=sha256:a9ba895ac49a8b6f46c2f50d94519414c0fb51d8d7ae2944759e9e96cab26a74

Observation 266b5a07-d079-4a4c-bbc0-2267d3a8de6f · outbound

This paper cites Attributing Fake Images to GANs: Learning and Analyzing GAN Finger- prints.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Attributing Fake Images to GANs: Learning and Analyzing GAN Finger- prints

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.604251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:40.168275Z digest=sha256:6a5ddc2be422d9ca21e09836f5df6087469846c4cc3a9aabe877a7790e5d3a24

Observation 0348c676-bd36-42fe-8304-0d5e1599704c · outbound

This paper cites Randomized Autoregressive Visual Generation.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Randomized Autoregressive Visual Generation

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-11T05:23:40.172310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:23:40.172310Z digest=sha256:40b6cad93a766c1eefbea0a0fc22f622b34675a741fba58d3a22518d91aa5329

Observation 2d3e74ce-12ce-408b-aacd-074a47e414e3 · outbound

This paper cites CutMix: Regu- larization strategy to train strong classifiers with localizable features.

A Bias-Free Training Paradigm for More General AI-generated Image Detection CutMix: Regu- larization strategy to train strong classifiers with localizable features

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.590300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:40.177092Z digest=sha256:8c833301ea5f54318f387d3ed32ae0b48b2f85862d825403c4568652b59e0e4e

Observation b15c1e94-ac54-418b-b5a6-bb8172890b79 · outbound

This paper cites Sigmoid loss for language image pre-training.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Sigmoid loss for language image pre-training

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-11T05:23:40.180729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:23:40.180729Z digest=sha256:2ee4726a346e83b6826e35038b9e3377ff0a01e1017dfdd267fa1d5d1d59f975

Observation 68a8c8cd-d2a5-4a74-ab6d-96965e7b4218 · outbound

This paper cites Multimodal Image Synthesis and Editing: The Generative AI Era.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Multimodal Image Synthesis and Editing: The Generative AI Era

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.568588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:40.184930Z digest=sha256:97913f7fdf669914b2b22a3b6cc6080261a2f081ee06551f174f607bdf3d82ba

Observation 249f12bc-4eed-41e4-8b33-32cd571a01fc · outbound

This paper cites Dauphin, and David Lopez-Paz.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Dauphin, and David Lopez-Paz

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.534829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:40.188303Z digest=sha256:3626304f439360cbfca0e54a519c02eca95b24728ebcae70ede83655b3d70493

Observation 9781916e-b102-4dbd-9dc9-0d3494483270 · outbound

This paper cites Detecting and Simulating Artifacts in GAN Fake Images.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Detecting and Simulating Artifacts in GAN Fake Images

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.345795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:40.192511Z digest=sha256:c372438aae7732187ad5f8982cff281e68d33cca2836eac893c6064895c7e303

Observation 3170256f-7341-471e-ae9e-0b42bdc22706 · outbound

This paper cites GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image.

A Bias-Free Training Paradigm for More General AI-generated Image Detection GenImage: A Million-Scale Benchmark for Detecting AI-Generated Image

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T05:23:40.330870Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:40.197045Z digest=sha256:6f87403a72afeb251bcc73e1694b72fc4b078fb94b6ee27a3694e6f5a70ed546

Observation 91b42534-5718-46f8-81f5-4955e96f33ae · outbound

This paper cites an unresolved cited work.

A Bias-Free Training Paradigm for More General AI-generated Image Detection Unresolved cited work

Reference 2020

Resolution
parse uncertain
raw_fallback, observed 2026-08-11T05:23:40.661583Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-11T05:23:39.989779Z digest=sha256:3d6e7e1b3e0068a55e0f5eecd0db34565a0159a280530abf3c5424cf548a669d

Pith citing papers

Observation f11f4e79-cba8-4b88-b417-90bf20530acd · inbound

Combating Pattern and Content Bias: Adversarial Feature Learning for Generalized AI-Generated Image Detection cites this paper.

Combating Pattern and Content Bias: Adversarial Feature Learning for Generalized AI-Generated Image Detection A Bias-Free Training Paradigm for More General AI-generated Image Detection

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-11T11:21:00.856211Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T15:01:21.206132Z digest=sha256:db804e1bc93c20e7029ef1175ba36bbcd2de8ee5030546d9006fd8c76359d3cf

Observation 778cf27f-896c-4433-81a3-fbf938295abf · inbound

Continuously Evolving Deepfake Detection: An Architecture and Public-Benchmark Evaluation of a Dynamic Detection System cites this paper.

Continuously Evolving Deepfake Detection: An Architecture and Public-Benchmark Evaluation of a Dynamic Detection System A Bias-Free Training Paradigm for More General AI-generated Image Detection

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-02T05:51:35.397247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:51:35.397247Z digest=sha256:ba579f50570b632d848dbcd1074397eeaff4b05eff526d0f0b8082ea8250dec1

Observation 704480b3-8f78-40bd-8cae-35cd2afdbc81 · inbound

V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors cites this paper.

V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors A Bias-Free Training Paradigm for More General AI-generated Image Detection

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-08T04:21:37.892889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T04:21:37.892889Z digest=sha256:d398db7ea207eed71a44faa036d44a05d7e2d24b3e205d23042141bf824d4850

Observation beb4ac0e-1dc0-4527-b396-6c15c1023b25 · inbound

Structured Local Differential Modeling for AI-Generated Image Detection cites this paper.

Structured Local Differential Modeling for AI-Generated Image Detection A Bias-Free Training Paradigm for More General AI-generated Image Detection

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-15T22:53:43.972690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:53:43.972690Z digest=sha256:3adc66296bf83fb864bc9f476b6f832f818b20867eb8c02bfcd537b866738f19