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Paper Citation Record · LEDGER

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection

As of 6 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 0 inbound Pith citation observations for arXiv:2605.24306.

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

pith.paper-citation-record.v1
2605.24306 v1

Coverage vector

measured 57 of 57 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T14:23:39.468471Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

57 of 57 outbound references displayed

  • verified exact7
  • verified fuzzy48
  • unresolved1
  • parse uncertain0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2e918727-0c7d-49bb-8d2e-c30d53ca9a43 · outbound

This paper cites An- alyzing and improving the image quality of StyleGAN,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection An- alyzing and improving the image quality of StyleGAN,

Reference 1

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Observation a326e8b8-7209-464f-b950-c00a4323530b · outbound

This paper cites Denoising diffusion probabilistic models.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Denoising diffusion probabilistic models

Reference 2

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Observation fd60ac6a-2e39-42a5-83d4-9dfb70c65867 · outbound

This paper cites SDXL: Improving latent diffusion models for high-resolution image synthesis,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection SDXL: Improving latent diffusion models for high-resolution image synthesis,

Reference 3

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Observation 98bdf7cb-edb2-4d29-85f4-9ef94a8c170d · outbound

This paper cites Zero-shot text-to-image generation,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Zero-shot text-to-image generation,

Reference 4

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Source-reported events for the cited work

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Observation 766c35f1-bdf9-4541-8e13-4c16ea42f2ce · outbound

This paper cites Scaling autoregressive models for content-rich text-to-image generation,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Scaling autoregressive models for content-rich text-to-image generation,

Reference 5

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Source-reported events for the cited work

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Observation d3f7dfd7-bd44-4c92-9eef-358f5953a9a7 · outbound

This paper cites CNN- generated images are surprisingly easy to spot... for now,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection CNN- generated images are surprisingly easy to spot... for now,

Reference 6

Resolution
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Observation 409ef0a4-5817-4a74-a32e-721abc9df3a7 · outbound

This paper cites Detecting GAN-generated fake images using co-occurrence matrices,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Detecting GAN-generated fake images using co-occurrence matrices,

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation c2620085-e6c0-4e12-bc09-d8778352a6b6 · outbound

This paper cites Deepfake detection by analyzing convolutional traces,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Deepfake detection by analyzing convolutional traces,

Reference 8

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Source-reported events for the cited work

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Observation c71180e4-2935-4d46-8c92-ea9049a3a213 · outbound

This paper cites Responsible disclosure of generative models using scalable fingerprinting,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Responsible disclosure of generative models using scalable fingerprinting,

Reference 9

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Source-reported events for the cited work

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Observation 624e0d98-8022-447a-a1ca-53ac3903b8f8 · outbound

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

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Leveraging frequency analysis for deep fake image recognition,

Reference 10

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 6b264ea0-bcb4-4685-90b3-d0ab6f72ec13 · outbound

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

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Frequency-aware deepfake detection: Improving generalizability through frequency space domain learning,

Reference 11

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 20df0696-24e6-46e4-a4fa-973b5770c38e · outbound

This paper cites Media forensics and deepfakes: An overview,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Media forensics and deepfakes: An overview,

Reference 12

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 655c1e4f-79ed-443a-87ac-f34b46212c18 · outbound

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

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Towards universal fake image detectors that generalize across generative models,

Reference 13

Resolution
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Source-reported events for the cited work

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Observation 25b3dc9d-080a-4c39-9635-157c922ae7d3 · outbound

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

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Forgery-aware adaptive transformer for generalizable synthetic image detection,

Reference 14

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 725f7cff-188d-4c51-88c0-15d7709dca1a · outbound

This paper cites A sanity check for AI-generated image detection,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection A sanity check for AI-generated image detection,

Reference 15

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Source-reported events for the cited work

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Observation 9b15a5e0-43ab-4deb-912f-e6fad61207c8 · outbound

This paper cites AIGI-Holmes: Towards explainable and generalizable AI- generated image detection via multimodal large language models,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection AIGI-Holmes: Towards explainable and generalizable AI- generated image detection via multimodal large language models,

Reference 16

Resolution
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Source-reported events for the cited work

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Observation 43bcd139-77e7-4c4f-b539-69556bf3b28d · outbound

This paper cites A visual leap in clip compositionality reasoning through generation of counterfactual sets,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection A visual leap in clip compositionality reasoning through generation of counterfactual sets,

Reference 17

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Source-reported events for the cited work

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Observation 3fe791d9-98c9-452e-9053-7f82ffdf4c5d · outbound

This paper cites Too vivid to be real? benchmarking and calibrating generative color fidelity,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Too vivid to be real? benchmarking and calibrating generative color fidelity,

Reference 18

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Observation 0421e49d-9733-427d-be12-7fd60ab32b87 · outbound

This paper cites Styledecoupler: Generalizable artistic style disentanglement,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Styledecoupler: Generalizable artistic style disentanglement,

Reference 19

Resolution
verified exact
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Source-reported events for the cited work

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Observation bfed1edf-79eb-4eb2-a7e6-f3cd94a58cee · outbound

This paper cites Intrinsic images by entropy minimization,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Intrinsic images by entropy minimization,

Reference 20

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Source-reported events for the cited work

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Observation bcec6de0-149c-4077-8ac8-91a63720d13c · outbound

This paper cites Color correction using principal components,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Color correction using principal components,

Reference 21

Resolution
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Source-reported events for the cited work

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Observation 6beb697a-b122-46b7-b94a-9611371f6389 · outbound

This paper cites an unresolved cited work.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Unresolved cited work

Reference 22

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Source-reported events for the cited work

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Observation 23dd9085-66bf-4f43-a034-55537f1b4c97 · outbound

This paper cites Attributing fake images to GANs: Learning and analyzing GAN fingerprints,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Attributing fake images to GANs: Learning and analyzing GAN fingerprints,

Reference 23

Resolution
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Source-reported events for the cited work

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Observation c86e94e5-7f5e-41e9-8037-40c77af6a939 · outbound

This paper cites Faceforensics++: Learning to detect manipulated facial images,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Faceforensics++: Learning to detect manipulated facial images,

Reference 24

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation 143c3e89-cd57-4f30-8d56-073c7183ddf6 · outbound

This paper cites Thinking in frequency: Face forgery detection by mining frequency-aware clues,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Thinking in frequency: Face forgery detection by mining frequency-aware clues,

Reference 25

Resolution
verified fuzzy
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Source-reported events for the cited work

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Observation fa54302c-f943-4fee-895c-de96aededb98 · outbound

This paper cites BiHPF: Bilateral high-pass filters for robust deepfake detection,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection BiHPF: Bilateral high-pass filters for robust deepfake detection,

Reference 26

Resolution
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Source-reported events for the cited work

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Observation 1d3919ec-781d-4395-9112-f04a47153ce7 · outbound

This paper cites Unveiling universal forensics of diffusion models with adversarial perturbations,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Unveiling universal forensics of diffusion models with adversarial perturbations,

Reference 27

Resolution
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Source-reported events for the cited work

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Observation 377979d1-6e39-48e2-8f05-2fc7c55f0325 · outbound

This paper cites arXiv preprint arXiv:2603.08064 (2026).

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection arXiv preprint arXiv:2603.08064 (2026)

Reference 28

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arxiv_id, observed 2026-06-30T14:24:44.833536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation bc9a2c3a-bc18-48db-84cd-30eec421b919 · outbound

This paper cites DIRE for diffusion- generated image detection,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection DIRE for diffusion- generated 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 2026-08-06T06:34:29.942622+00:00.

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Observation 34fe8657-2588-4b19-beb4-62df98466b99 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Learning transferable visual models from natural language supervi- sion,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 10e57bb7-ecd8-4718-bda5-4c6e7b96df70 · outbound

This paper cites Forensics adapter: Adapting CLIP for generalizable face forgery detection,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Forensics adapter: Adapting CLIP for generalizable face forgery detection,

Reference 31

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 350a09a6-c515-4394-905d-876e11e6f169 · outbound

This paper cites Multimodal Conditional Information Bottleneck for Generalizable AI-Generated Image Detection.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Multimodal Conditional Information Bottleneck for Generalizable AI-Generated Image Detection

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-06-30T14:24:44.819386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 46e1e6ea-925c-43fc-9ce5-7f81bdbd7473 · outbound

This paper cites Large scale GAN training for high fidelity natural image synthesis,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Large scale GAN training for high fidelity natural image synthesis,

Reference 33

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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Observation 4206af56-4e5f-4355-aacd-7d675086dc95 · outbound

This paper cites Classifier-Free Diffusion Guidance.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Classifier-Free Diffusion Guidance

Reference 34

Resolution
verified exact
local_arxiv, observed 2026-06-30T14:24:44.825028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:076f3169470b031239dd5241f16c921ed8148ff21e3b603ee239e9abd73716ea

Observation 6bb8be0a-8e37-45d8-bf9b-4bcf17bbca92 · outbound

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

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Photorealistic text-to- image diffusion models with deep language understanding,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.986454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:19cc694d29481b569c0a0aaed9bb4b4e464780d7aa7c1c3166a403cbb49d96de

Observation f5679b48-b9df-4d80-9eaf-4c38cff3ed85 · outbound

This paper cites Angle domain guidance: Latent diffusion requires rotation rather than extrapolation,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Angle domain guidance: Latent diffusion requires rotation rather than extrapolation,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.990893Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:b527cdca0d0935623e7c8c4c9aa9238362d5f2a082bec1d9f8dca586ba8c64d9

Observation c6564c4e-05db-4ab7-9175-3a34169ae58f · outbound

This paper cites Eliminating oversaturation and artifacts of high guidance scales in diffusion models,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Eliminating oversaturation and artifacts of high guidance scales in diffusion models,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.994488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:decaa18b5eef52647cec3e3ed9d98b8f73cf3f66dc703d92502d636a90fd77b5

Observation 315e6ee2-7072-4296-8914-8f9c73152c8d · outbound

This paper cites Common diffusion noise schedules and sample steps are flawed,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Common diffusion noise schedules and sample steps are flawed,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:45.000366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:883b8ca018188db431a08522a77cb66a9b4470564d1f9556c195e4e5a1303c38

Observation 64aca328-bab7-411d-aae4-f5cde537ac6f · outbound

This paper cites Neural discrete representation learning,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Neural discrete representation learning,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.978028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:f5d9b6854250465d505d1f690092fc504ca06c7f03133ff25151f679e3653b6e

Observation ea8c7811-08e3-4428-9996-5a42a5fcace5 · outbound

This paper cites Sequence level training with recurrent neural networks,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Sequence level training with recurrent neural networks,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.976026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:0ca520b45269f93cbfc67fbb94e3495e588b77ed85517159c6b2d83e6402ab52

Observation d48ee2b4-e7d8-4ced-9368-b5ea03c496b9 · outbound

This paper cites Visual autoregressive modeling: Scalable image generation via next-scale prediction,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Visual autoregressive modeling: Scalable image generation via next-scale prediction,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.980775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:409802528dd6ec7ed78ea00b3042c20c02caf034a1a901496faafd45169df90a

Observation 03bc32b5-d40b-4849-bb4c-bcf08e537992 · outbound

This paper cites Infinity: Scaling bitwise autoregressive modeling for high-resolution image synthesis,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Infinity: Scaling bitwise autoregressive modeling for high-resolution image synthesis,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.982954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:e414e61a7a810a767e6caf653cb92f5d976d80d650288323a22480c7ae481fee

Observation af3d38c4-1013-49e2-a620-a68fb075a33c · outbound

This paper cites HART: Efficient visual generation with hybrid autoregressive transformer,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection HART: Efficient visual generation with hybrid autoregressive transformer,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.984720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:3e2ec16313aed5945b481c6b58a6bad3f45146b1b7972fcb1d5482a6d4422f7a

Observation 52b7d6b4-bae7-41c5-8b59-7cc7cdd935ab · outbound

This paper cites Hierarchical masked autoregressive models with low-resolution token pivots,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Hierarchical masked autoregressive models with low-resolution token pivots,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.996840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:40e95e62809e1b897438ced7c0bfd940721c0392441d89d6968f7d33f1e05c09

Observation 4f66b661-3b1d-4d4d-8a9a-bffa72e5da13 · outbound

This paper cites D 3QE: Learning discrete distribution discrepancy-aware quantization error for autoregressive-generated image detection,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection D 3QE: Learning discrete distribution discrepancy-aware quantization error for autoregressive-generated image detection,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:45.014923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:aa2f3c97f77a55b1d6393873a006b2bd18f62a4390eead52aaed392b7041b25b

Observation ceb0b82c-334d-4329-828c-99b44376bb2f · outbound

This paper cites Microsoft COCO: Common objects in context,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Microsoft COCO: Common objects in context,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.972465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:5fe571fab5259117b7f81bc547cf2c73ab91773a2cb0c48fbc8e5bc135d3170e

Observation 42a3daba-52aa-4ce4-80db-e43292e146ce · outbound

This paper cites ImageNet large scale visual recognition challenge,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection ImageNet large scale visual recognition challenge,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.974247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:dfc776bc759fff04853c2083b8e78d838a2bf4cfdff5ebfe6dc37d4142aa948f

Observation cfff2dcc-7c8a-489a-aa93-bde52dee160a · outbound

This paper cites LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection LSUN: Construction of a Large-scale Image Dataset using Deep Learning with Humans in the Loop

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-06-30T14:24:44.828308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:36731b45fc5406a290371e3b0deb2840449129bcfbb8def8b3fc92b8d72ef608

Observation 5cf744f6-acf9-448d-885e-057659d51198 · outbound

This paper cites Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis

Reference 49

Resolution
verified exact
local_arxiv, observed 2026-06-30T14:24:44.835933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:e137953af841f2203cb0035bfa898faecf84c75cc338a4a088843fae4c6c3aa8

Observation 6368782d-229f-4f8d-9c15-ba6d72c5b224 · outbound

This paper cites Progressive growing of GANs for improved quality, stability, and variation,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Progressive growing of GANs for improved quality, stability, and variation,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:45.012958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:3a21e94a4b922ea08d45ae2882f199b0aec65bf08bb03c2480d28b7bd7a7ba96

Observation 1f487c1f-1c92-414c-9d30-ddf1f4b1e0c0 · outbound

This paper cites GenImage: A million-scale benchmark for detecting AI-generated images,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection GenImage: A million-scale benchmark for detecting AI-generated images,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:45.034248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:c24e07b2659b16f04c346bfb59f09013685235e9c6e4abd2b7599ab111120824

Observation bf6c1d07-5e3d-434f-bd2a-439cbd05711b · outbound

This paper cites Learning on gradi- ents: Generalized artifacts representation for GAN-generated images detection,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Learning on gradi- ents: Generalized artifacts representation for GAN-generated images detection,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.966551Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:e80b9dcdd5440ba4522cc05e3e8464f62465f7c28475faa5b1087d51f275b9ce

Observation 55ded087-a0fe-4c67-9321-f007a5403016 · outbound

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

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection PatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection

Reference 53

Resolution
verified exact
arxiv_id, observed 2026-06-30T14:24:44.822270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:cce5dd27334f81d573cdc2183d7cf147265662891f610333a881066fb27d26a1

Observation 9a3c58c3-f590-45ca-857d-5896fb79e05b · outbound

This paper cites Rethinking the up- sampling operations in CNN-based generative network for generalizable deepfake detection,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Rethinking the up- sampling operations in CNN-based generative network for generalizable deepfake detection,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.964719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:5385df62937b2dcd3299df70a250ad8759174a01bca8153cc78f3798a89fca1e

Observation 3e15ab47-8c32-46cb-ae57-a932ad25c867 · outbound

This paper cites Improving synthetic image detection towards generalization: An image transformation per- spective,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Improving synthetic image detection towards generalization: An image transformation per- spective,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.962909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:4519cabbdb69f55f4a829fb9b5f570b02fccae31b8b0f203a9f2cfe0b1f4e3ed

Observation ccbf0871-cefe-4796-92c6-ff0df94f6a8b · outbound

This paper cites Secret lies in color: Enhancing AI-generated image detection with color distribution analysis,.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection Secret lies in color: Enhancing AI-generated image detection with color distribution analysis,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:44.970566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:6e8dbc97346cf5b590015d086593481b3a22f7f031b3bed591b2401100d2616b

Observation 3cd27a86-dcea-4d7f-92a8-1d3a19d131df · outbound

This paper cites His research interests include machine learning and multimodal models.

CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection His research interests include machine learning and multimodal models

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-07-08T23:15:45.038599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=pdf_text observed=2026-06-30T14:23:39.468471Z digest=sha256:89aaf8ba474aaa4a026da48b1271c2cd95c201f5f9bae34c1d61ce7a5d51f870

Pith citing papers

No inbound Pith citation observations are available.