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Paper Citation Record · LEDGER

Effective Synthetic Image Detection via Noise Residual Clustering

As of 18 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2607.10695.

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2607.10695 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-14T09:57:11.905725Z

measured 37 of 37 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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

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Reference resolution

37 of 37 outbound references displayed

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Outbound references

Observation e3e83a6d-773f-4cf1-8b5a-7aef1e208567 · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering Progressive growing of GANs for improved quality, stability, and variation,

Reference 1

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Observation 67e13317-8fe8-40ce-abd5-5dd66cc24ba6 · outbound

This paper cites A style-based generator architecture for generative adversarial networks,.

Effective Synthetic Image Detection via Noise Residual Clustering A style-based generator architecture for generative adversarial networks,

Reference 2

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Observation d5f1733f-795a-46ce-9539-8615c436e9ec · outbound

This paper cites StarGAN: Unified generative adversarial networks for multi-domain image-to- image translation,.

Effective Synthetic Image Detection via Noise Residual Clustering StarGAN: Unified generative adversarial networks for multi-domain image-to- image translation,

Reference 3

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Observation 39b67edb-c3df-442f-a963-6ce5920af47c · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering High-resolution image synthesis with latent diffusion models,

Reference 4

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Observation a469280e-3337-4598-a3c9-2545be46cc8c · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 5

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Observation 4439520f-b1ed-47af-9c2b-f502034a565e · outbound

This paper cites Midjourney,.

Effective Synthetic Image Detection via Noise Residual Clustering Midjourney,

Reference 6

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Observation 6fde4acb-dade-4ae2-a879-227e7229594a · outbound

This paper cites Detection of GAN-generated fake images over social networks,.

Effective Synthetic Image Detection via Noise Residual Clustering Detection of GAN-generated fake images over social networks,

Reference 7

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Observation 066a4aa8-14a9-4b8e-8ca0-93644dbd3cc3 · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering Are GAN generated images easy to detect? A critical analysis of the state-of-the-art,

Reference 8

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Observation d57c1e41-548c-4323-850f-45ac523bcb50 · outbound

This paper cites Watch your up-convolution: CNN based generative deep neural networks are failing to reproduce spectral distributions,.

Effective Synthetic Image Detection via Noise Residual Clustering Watch your up-convolution: CNN based generative deep neural networks are failing to reproduce spectral distributions,

Reference 9

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Observation 75e3c05a-5f39-4e85-b0b8-16a146e14cbd · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering Leveraging frequency analysis for deep fake image recognition,

Reference 10

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Observation d458aa03-179c-46c5-b12a-ec33caac1b8b · outbound

This paper cites On the detection of synthetic images generated by diffusion models,.

Effective Synthetic Image Detection via Noise Residual Clustering On the detection of synthetic images generated by diffusion models,

Reference 11

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Observation 769d5206-f52c-471e-a0a3-98902833d8c3 · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering CNN-generated images are surprisingly easy to spot... for now,

Reference 12

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Observation fa36e8a8-2ad0-492c-a6ab-b35b02d73465 · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering Towards universal fake imag e detectors that generalize across generative models,

Reference 13

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Observation a25437cf-1591-49a2-9d86-661c3a6bca3f · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering Learning transferable visual models from natural language supervision,

Reference 14

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Observation e7f404e3-edfc-4845-9e6c-ce67a51f13eb · outbound

This paper cites Raising the ba r of AI-generated image de tection with CLIP,.

Effective Synthetic Image Detection via Noise Residual Clustering Raising the ba r of AI-generated image de tection with CLIP,

Reference 15

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Observation d9370d7b-0c52-4249-adf8-2f43c9baf31b · outbound

This paper cites C2P-CLIP: Injecting category common prompt in CLIP to enhance generalization in deepfake detection,.

Effective Synthetic Image Detection via Noise Residual Clustering C2P-CLIP: Injecting category common prompt in CLIP to enhance generalization in deepfake detection,

Reference 16

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Observation acd4ea27-7224-49ba-9ee9-919efdcaaaf3 · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering DIRE for diffusion-generated image detection,

Reference 17

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Observation 5fd96624-2277-49b8-ac97-bbbaa4bb3b2e · outbound

This paper cites DRCT: Diffusion reconstruction contrastive training towards universal detection of diffusion generated images,.

Effective Synthetic Image Detection via Noise Residual Clustering DRCT: Diffusion reconstruction contrastive training towards universal detection of diffusion generated images,

Reference 18

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Observation 2ac5163a-0335-43d1-8d84-1c8963daef17 · outbound

This paper cites Learning on gradients: Generalized artifacts repr esentation for GAN-generated images detection,.

Effective Synthetic Image Detection via Noise Residual Clustering Learning on gradients: Generalized artifacts repr esentation for GAN-generated images detection,

Reference 19

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Observation c54f3240-e756-471b-8099-bb739cc8c32b · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering A sanity check for AI-generated image detection,

Reference 20

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Observation 9f99e05f-0a3d-4d08-a834-7706e02f9d80 · outbound

This paper cites Improving synthetic image detection towards generalization: An image transformation perspective,.

Effective Synthetic Image Detection via Noise Residual Clustering Improving synthetic image detection towards generalization: An image transformation perspective,

Reference 21

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Observation 527fb0b2-dddb-4aea-a21b-43ab8f81d9b2 · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering AEROBLADE: Training-free detection of latent diffusion images using autoencoder reconstruction error,

Reference 22

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Observation 82875b46-03fa-4d5b-8a16-60340ad090b3 · outbound

This paper cites RIGID: A Training-free and Model-Agnostic Framework for Robust AI-Generated Image Detection.

Effective Synthetic Image Detection via Noise Residual Clustering RIGID: A Training-free and Model-Agnostic Framework for Robust AI-Generated Image Detection

Reference 23

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Observation 6230e953-457d-4c89-a0d9-1c80866c1e53 · outbound

This paper cites Leveraging failed sa mples: A few-shot and training-free framework for generalized deepfake detection,.

Effective Synthetic Image Detection via Noise Residual Clustering Leveraging failed sa mples: A few-shot and training-free framework for generalized deepfake detection,

Reference 24

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Observation fd98f683-c920-4a53-b2ff-b8ec667151ce · outbound

This paper cites AI-generated video detection via spatial-temporal anomaly learning,.

Effective Synthetic Image Detection via Noise Residual Clustering AI-generated video detection via spatial-temporal anomaly learning,

Reference 25

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Observation e01e8d91-4a5f-4578-96b4-de9869be9d9e · outbound

This paper cites TruFor: Leveraging all-round clues for trustworthy image forgery detection and localization,.

Effective Synthetic Image Detection via Noise Residual Clustering TruFor: Leveraging all-round clues for trustworthy image forgery detection and localization,

Reference 26

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Observation b5c06301-31b5-4c5e-9ee2-0d545193cc3d · outbound

This paper cites Trusted video inpainting localization via deep attentive noise learning,.

Effective Synthetic Image Detection via Noise Residual Clustering Trusted video inpainting localization via deep attentive noise learning,

Reference 27

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Observation a6fbd745-ea54-4711-aea6-228d05b05188 · outbound

This paper cites Effective image tampering lo calization via enhanced transformer and co-attention fusion,.

Effective Synthetic Image Detection via Noise Residual Clustering Effective image tampering lo calization via enhanced transformer and co-attention fusion,

Reference 28

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Observation 50059638-b980-4f65-b32a-4da631b3430a · outbound

This paper cites Hybrid transformer-CNN for real image denoising,.

Effective Synthetic Image Detection via Noise Residual Clustering Hybrid transformer-CNN for real image denoising,

Reference 29

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Observation ff78f883-ffdb-476d-a83f-4963cdcf3a86 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Effective Synthetic Image Detection via Noise Residual Clustering An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 30

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Observation 19bbb5af-1144-4e28-bdfa-2754f19dac10 · outbound

This paper cites Exploring multi-view pixel contrast for general and robust image forgery localization,.

Effective Synthetic Image Detection via Noise Residual Clustering Exploring multi-view pixel contrast for general and robust image forgery localization,

Reference 31

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Observation dc583a1d-46de-4501-866e-e94275e91f3f · outbound

This paper cites G enImage: A million-scale benchmark for detecting AI-generated image,.

Effective Synthetic Image Detection via Noise Residual Clustering G enImage: A million-scale benchmark for detecting AI-generated image,

Reference 32

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Observation 5762469f-986d-4316-82d9-d04d988ce36a · outbound

This paper cites Synthbuster: Towards detection of diffusion model generated images,.

Effective Synthetic Image Detection via Noise Residual Clustering Synthbuster: Towards detection of diffusion model generated images,

Reference 33

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Observation 62271dad-43ed-4f95-b8b0-e3331cc5347c · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering PatchCraft: Exploring Texture Patch for Efficient AI-generated Image Detection

Reference 34

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Observation 99588c73-8eab-4e59-943b-3edec28bf3b4 · outbound

This paper cites Analyzing and improving the image quality of stylegan.

Effective Synthetic Image Detection via Noise Residual Clustering Analyzing and improving the image quality of stylegan

Reference 35

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Observation d3ba08df-7711-420a-bced-72c86c862555 · outbound

This paper cites Large Scale GAN Training for High Fidelity Natural Image Synthesis.

Effective Synthetic Image Detection via Noise Residual Clustering Large Scale GAN Training for High Fidelity Natural Image Synthesis

Reference 36

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Observation c78cd5b9-66ac-4633-9d11-f84364959682 · outbound

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

Effective Synthetic Image Detection via Noise Residual Clustering Detecting and simulating artifacts in gan fake images

Reference 37

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