Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-30T14:23:39.468471Z
Paper Citation Record · LEDGER
CoDA: Color Distribution Probing for Efficient and Generalizable AI-Generated Image Detection
As of 18 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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
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
- malformed identifier0
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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
- Resolution
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Source-reported events for the cited work
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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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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
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Source-reported events for the cited work
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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
- Resolution
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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
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
- Resolution
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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
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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
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
- Resolution
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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
- Resolution
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Source-reported events for the cited work
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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
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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
- Resolution
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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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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
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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
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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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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
- Resolution
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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
- Resolution
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Source-reported events for the cited work
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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
- Resolution
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Source-reported events for the cited work
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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
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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
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Source-reported events for the cited work
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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
- Resolution
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
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Source-reported events for the cited work
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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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
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
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- 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 2026-08-17T06:30:58.91139+00:00.
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 2026-08-17T06:30:58.91139+00:00.
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 2026-08-17T06:30:58.91139+00:00.
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 2026-08-17T06:30:58.91139+00:00.
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 2026-08-17T06:30:58.91139+00:00.
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 2026-08-17T06:30:58.91139+00:00.
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 2026-08-17T06:30:58.91139+00:00.
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 2026-08-17T06:30:58.91139+00:00.
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 2026-08-17T06:30:58.91139+00:00.
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 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
No inbound Pith citation observations are available.