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Paper Citation Record · LEDGER

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers

As of 8 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2509.03006.

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

pith.paper-citation-record.v1
2509.03006 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T11:19:19.718926Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

45 of 45 outbound references displayed

  • verified exact1
  • verified fuzzy44
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 778d5977-8266-42a3-add6-d8934bd632bc · outbound

This paper cites Necst: Neural joint source-channel coding.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Necst: Neural joint source-channel coding

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.234189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.592517Z digest=sha256:94beb4f74b04047a5399c2f0a91c1f177ca8a3fb768e9abf7e938ccb76f9823f

Observation b2f8eebf-667d-4816-b045-525701604a64 · outbound

This paper cites Distortion agnostic deep watermarking,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Distortion agnostic deep watermarking,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.225943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.596066Z digest=sha256:51c33ac88082b30c2b96666c8b1ba7a61f62e8314bca2088899786a9e7705c94

Observation 70643b64-dec8-44c6-86c1-0f59e88ca242 · outbound

This paper cites Analyzing and Improving the Image Quality of StyleGAN,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Analyzing and Improving the Image Quality of StyleGAN,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.216991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.599043Z digest=sha256:f27d039dc3a98e774c4dd2df8289ec6e24faed6e6582ffda127d93c8dea98af7

Observation 582ab08d-989f-478d-adef-8b0e344eab2d · outbound

This paper cites Alias-Free Generative Adversarial Networks,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Alias-Free Generative Adversarial Networks,

Reference 4

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.208905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.602001Z digest=sha256:0aa51d9ee21e4b866dfa4db0e7f4ed4a8c0929b06e2ef5235844d27f4bd353eb

Observation 5930ca45-387c-4c4a-b03c-a5bf35f37083 · outbound

This paper cites Dual Contrastive Loss and Attention for GANs,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Dual Contrastive Loss and Attention for GANs,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.200667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.605060Z digest=sha256:340b31dfa16a65b4d82574687d5287c856324534086af8d39dfe3af67e10744b

Observation a9004ec9-4a43-46df-87c5-35d2b0f7ae0d · outbound

This paper cites Inclusive GAN: Improving Data and Minority Coverage in Generative Models,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Inclusive GAN: Improving Data and Minority Coverage in Generative Models,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.192131Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.608062Z digest=sha256:cb02722c9ea26ca10ab105b29e954c91674f684d55d94ca1ca3c5f7f0ed1441e

Observation 01e7b0ac-7ff3-430e-9f71-4403caeef681 · outbound

This paper cites DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesis,

Reference 7

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.183499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.611710Z digest=sha256:5c756ed3530765483306ebdbea32ef7a70d536c68133332f687a18b097ce93c5

Observation 358f7aed-6c33-4be4-895b-7ec9baa050a8 · outbound

This paper cites LAFITE: Towards Language-Free Training for Text-to-Image Generation,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers LAFITE: Towards Language-Free Training for Text-to-Image Generation,

Reference 8

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.174331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.614351Z digest=sha256:833d23766af79345bee8f742086adc4f693fbfaf2b9502460658906d6b202919

Observation 8ca18898-2739-480c-8832-20789f0f7681 · outbound

This paper cites Scaling up GANs for Text-to-Image Synthesis,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Scaling up GANs for Text-to-Image Synthesis,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.165534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.616970Z digest=sha256:9f9f7792bbbf57133985682874a78ac34d2059f0b66d2f2a5964c50e791b7027

Observation bb3628c9-319e-48ab-a604-fe43fb1c53b9 · outbound

This paper cites Interpreting the Latent Space of GANs for Semantic Face Editing,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Interpreting the Latent Space of GANs for Semantic Face Editing,

Reference 10

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.157377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.619923Z digest=sha256:7455601d48501874e7e38d3967b4e95618897bda265f377c21cd582fe4f58ca4

Observation 2e76005c-1db7-459b-9648-1d5d7df4fe0b · outbound

This paper cites StyleRes: Transforming the Residuals for Real Image Editing with StyleGAN,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers StyleRes: Transforming the Residuals for Real Image Editing with StyleGAN,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.148986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.622682Z digest=sha256:cd0e7871366f9eb8b395b16fd92fd2bda4e9a8dd194c48629d0c09fc4a576da0

Observation 5d6d3da2-6c5b-4350-9ed5-499a6b097b9f · outbound

This paper cites E4S: Fine-grained Face Swapping via Editing With Regional GAN Inversion,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers E4S: Fine-grained Face Swapping via Editing With Regional GAN Inversion,

Reference 12

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.140614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.625530Z digest=sha256:0e16f5ce617046df34be2770551ee1c5ba3a05af62970b001276680b3c72c275

Observation 578f3e0c-984c-43fe-8e33-b0f741ce7299 · outbound

This paper cites Elucidating the De- sign Space of Diffusion-Based Generative Models,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Elucidating the De- sign Space of Diffusion-Based Generative Models,

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.132145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.628341Z digest=sha256:5ac1807d0213c5e74e1c1816f965545c1ef313a79d9227fcc93d3af71687d8ec

Observation abdff1b7-f84c-4709-849a-95c1b9a8c966 · outbound

This paper cites InstructPix2Pix: Learn- ing to Follow Image Editing Instructions,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers InstructPix2Pix: Learn- ing to Follow Image Editing Instructions,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.123821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.631747Z digest=sha256:d50fd4537a1e5f8ab412521a9601a2b30778afc96f8fecbf2df37df5876b2694

Observation d383b648-72ad-474b-a1bf-c036e4bb3f38 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models,

Reference 15

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.115793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.634943Z digest=sha256:39f1b6cf387213e3a3aa82273e8924240fdab07da84487cb084aa9401d50588f

Observation 5e8dfd01-a57d-48ac-8f95-e53c42cf1098 · outbound

This paper cites Adding Conditional Control to Text-to-Image Diffusion Models,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Adding Conditional Control to Text-to-Image Diffusion Models,

Reference 16

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raw_fallback, observed 2026-08-05T11:19:20.107111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.637898Z digest=sha256:8a9591f8fba1fe49bd56466c0f605f2ad0983a020a7e3b27d00bdb95863f5c46

Observation b5530a11-1fc7-4c32-bbe1-c4bff70f837c · outbound

This paper cites Hidden: Hiding data with deep networks,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Hidden: Hiding data with deep networks,

Reference 17

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.098795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.640899Z digest=sha256:1f08cb18cdb210c0d36c38d0bd069be09ef9a7285eea82da35a6d4eb18d9ff0f

Observation 24455210-c564-4084-8560-c91ff0e3fedc · outbound

This paper cites WAVES: Benchmarking the Robustness of Image Watermarks,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers WAVES: Benchmarking the Robustness of Image Watermarks,

Reference 18

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.090769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.643621Z digest=sha256:07ec6917ae030f0eba9d84a3826a4ffa4f5579069e32a6a345d0e05184e68730

Observation 5ceb5153-e5ad-4d1f-a978-fdef22622696 · outbound

This paper cites StegaStamp: Invisible Hyperlinks in Physical Photographs,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers StegaStamp: Invisible Hyperlinks in Physical Photographs,

Reference 19

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.082421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.646534Z digest=sha256:42aeae15d03a6e951f22794fb0551bda224068085400155b4e497380d0aea9f8

Observation 8f62f5ac-dc08-4bcc-8fea-6d871d6a15d5 · outbound

This paper cites The Stable Signature: Rooting Watermarks in Latent Diffusion Models,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers The Stable Signature: Rooting Watermarks in Latent Diffusion Models,

Reference 20

Resolution
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raw_fallback, observed 2026-08-05T11:19:20.074006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.649221Z digest=sha256:a8c3578589066541be801386f05a9c94c46a22a67e93a295e391cecbb5576792

Observation bd39c39f-c4a9-44e7-b417-428b761eec14 · outbound

This paper cites Wavelet-Based CNN for Robust and High-Capacity Image Watermarking,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Wavelet-Based CNN for Robust and High-Capacity Image Watermarking,

Reference 21

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raw_fallback, observed 2026-08-05T11:19:20.066120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.652114Z digest=sha256:a04ad9ff09e18a066d74df7055e17f4648dbbcb808a36e3a6b3f9521b9ebc3b3

Observation f28bf269-5f25-497b-be19-20252a663f44 · outbound

This paper cites Artificial Fin- gerprinting for Generative Models: Rooting Deepfake Attribution in Training Data,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Artificial Fin- gerprinting for Generative Models: Rooting Deepfake Attribution in Training Data,

Reference 22

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raw_fallback, observed 2026-08-05T11:19:20.057795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.655031Z digest=sha256:e6ced27f0d84033f39602571fcf5ecd9672248ee65a93cdd4043efbf2cc3a44b

Observation 73f93c72-b4a2-4c5d-827e-4f9c306fdf1f · outbound

This paper cites A Recipe for Watermarking Diffusion Models,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers A Recipe for Watermarking Diffusion Models,

Reference 23

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raw_fallback, observed 2026-08-05T11:19:20.049622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.658400Z digest=sha256:bd69fcb242bf4bb8595a47ff80e15b03aa06c75d9dc77f10e419f3e7da978ab8

Observation c9bb182e-0d1c-419e-ab56-33536d648e2d · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers High-Resolution Image Synthesis with Latent Diffusion Models,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.041329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.661200Z digest=sha256:ab70b05b7d4d667d5eb943765bf88b79a2c88e8ec198c98862cbd6122462e49a

Observation d7077eac-1f1b-40cc-b933-91caecf50ac5 · outbound

This paper cites Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.033085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.663889Z digest=sha256:842aaf68ca7535b44763e62692a95f910660134807b2682ed2165ad18c38ee64

Observation bfc44d45-fbf8-44bc-bd12-10411b3bfdfd · outbound

This paper cites WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to- Image Diffusion Models,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to- Image Diffusion Models,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.025362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.666851Z digest=sha256:2c8e1147c0f7fc698a4bb8f2d293ab8ef2e1e1b34f45b4eef98c216a14807a9c

Observation d7727267-6f19-4a70-844f-bb83d944a19b · outbound

This paper cites PTW: Pivotal Tuning Watermarking for Pre- Trained Image Generators,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers PTW: Pivotal Tuning Watermarking for Pre- Trained Image Generators,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:20.015380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.669482Z digest=sha256:ddd2aeca803fb43cb7375c65be69d81a8b6eeac367c225bfe1cc3ef2b7cbabcd

Observation 1b1e08ff-f71b-4c6b-94cb-492d176e5bb1 · outbound

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

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale,

Reference 28

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raw_fallback, observed 2026-08-05T11:19:20.007059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.672327Z digest=sha256:a401b39be921da26b5d4fc0171d7a489d2ec93ca0ada38d1c6270658e0fcbe9d

Observation 653c373d-225c-4270-acc6-72c4b50c33f6 · outbound

This paper cites Do Vision Transformers See Like Convolutional Neural Networks?,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Do Vision Transformers See Like Convolutional Neural Networks?,

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.998553Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.675175Z digest=sha256:9d61002e0f57218f7988a6f49b2864858b703656ea1bec262d96e3b401de59f0

Observation 61a8093d-2800-468a-bc9d-da3c96be74be · outbound

This paper cites Deep Learning Face Attributes in the Wild,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Deep Learning Face Attributes in the Wild,

Reference 30

Resolution
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raw_fallback, observed 2026-08-05T11:19:19.990047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.677924Z digest=sha256:197b18fad52563efd357b295dff12d18255b2e8aa4101e91909751d024f48a1e

Observation 23811f59-cce5-4f2d-b233-0bfecc9a3cb2 · outbound

This paper cites Microsoft COCO: Common Objects in Context,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Microsoft COCO: Common Objects in Context,

Reference 31

Resolution
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raw_fallback, observed 2026-08-05T11:19:19.981698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.680538Z digest=sha256:3dfbde5a3b173cbcdc46eea5fa21d7ef11b8c193f9e58409b08ca5e2f5a791a8

Observation 121a8775-8caf-45ac-9586-42c3aa5d3feb · outbound

This paper cites Encoded Feature Enhancement in Watermarking Network for Distortion in Real Scenes,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Encoded Feature Enhancement in Watermarking Network for Distortion in Real Scenes,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.973504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.683184Z digest=sha256:7f7e82424dc1af7f995eb2b958f6381553f5078c850fd81d35f00cf1ea19bc4e

Observation 637482e2-89c6-4664-a34d-f15192ee06e2 · outbound

This paper cites Print-Camera Resistant Image Watermarking With Deep Noise Simulation and Constrained Learning,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Print-Camera Resistant Image Watermarking With Deep Noise Simulation and Constrained Learning,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.964566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.685844Z digest=sha256:3ecf12b91e891d338e6c1a53b72e74a8aac185ca2cbd13b3c879c71862d815f1

Observation 88a846e9-db9c-4fad-a15d-d4ec62a24fcc · outbound

This paper cites Towards Deep Learning Models Resistant to Adversarial Attacks,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Towards Deep Learning Models Resistant to Adversarial Attacks,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.955566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.688800Z digest=sha256:f6af30b244b4ebdf1523b66efef30f8eab0d459453a4039e4a1742620c4a8f9b

Observation af7f2586-df81-4b95-99c4-0f3146f2a419 · outbound

This paper cites Deep Residual Learn- ing for Image Recognition,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Deep Residual Learn- ing for Image Recognition,

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.850843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.691420Z digest=sha256:3169250886f3e95a8e14d0f2c9a8289d9db5649747d6ac2baeb6457dc195c88d

Observation 1545754c-6d76-4fa4-b70f-59a2b4802539 · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Learning Transferable Visual Models From Natural Language Supervision,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.841232Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.694066Z digest=sha256:81c6ede2157d4b8ce9a4dbcdd7a64bc8ab7dbcd573f20c21dda74e9463ef6689

Observation 78a77875-026a-49e7-be6c-79b3f1c9ef9c · outbound

This paper cites SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis,

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.829745Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.696923Z digest=sha256:6dc9781e6e990adae238b2864a71b246f5e2c4536fe58c86df7c8f8007b5d30e

Observation 87395938-28c6-4993-af45-39264f4043fb · outbound

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

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Robustness of AI-Image Detectors: Fundamental Limits and Practical Attacks,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.819628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.699697Z digest=sha256:753d5153c3236239cdccb54a864bc6895f8ba05c376c6d566c345d2939f52592

Observation 67ae7cc7-c8b9-41bd-9211-7f91841cea6c · outbound

This paper cites Two-Stage Watermark Removal Framework for Spread Spectrum Watermarking,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Two-Stage Watermark Removal Framework for Spread Spectrum Watermarking,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.809947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.702370Z digest=sha256:0eb435b8a2c6f276a1d741445607dfc230b3b9a8053f8c07fbd937e4bd0db49d

Observation 6a90171b-33fe-482c-bce4-6f9ffe1b12c5 · outbound

This paper cites Exploring Accurate Invariants on Polar Harmonic Fourier Moments in Polar Coordinates for Robust Image Watermarking,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Exploring Accurate Invariants on Polar Harmonic Fourier Moments in Polar Coordinates for Robust Image Watermarking,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.800277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.704949Z digest=sha256:eb7a29b0695a76a2163bf79935a2ce6fc9493d63dd59fc309fc56c0c25f3aad7

Observation 4b408cec-1e2a-464a-8917-3bae00044496 · outbound

This paper cites De-END: Decoder-Driven Watermarking Network,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers De-END: Decoder-Driven Watermarking Network,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.790923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.707503Z digest=sha256:06a97733c94a0346d59b7dc52cbff76823818ba793ef2b167b8e0dba1bd74823

Observation e079fb9c-02d2-47db-bdae-59da5d8ff458 · outbound

This paper cites Estimating the Secret Key of Spread Spectrum Watermarking Based on Equivalent Keys,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Estimating the Secret Key of Spread Spectrum Watermarking Based on Equivalent Keys,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.781765Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.710167Z digest=sha256:547e4bf57621fc16f31de736d3b4221bb9b9fa0798ea8ef4433d1be6cdbec9eb

Observation 8c65395d-c61c-4a09-a638-4f8c2df1e63c · outbound

This paper cites Invisible Backdoor Triggers in Image Editing Model via Deep Watermarking.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Invisible Backdoor Triggers in Image Editing Model via Deep Watermarking

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-05T11:19:19.751736Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.713069Z digest=sha256:1a9ee427a1781776b23f4b2281c718da16cc40e01a2b85f74eaee9808c174be0

Observation 51e7b212-1336-4c18-ab09-8a92db3e1631 · outbound

This paper cites Exploring Frequency Adversarial Attacks for Face Forgery Detection,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Exploring Frequency Adversarial Attacks for Face Forgery Detection,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.771484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.716280Z digest=sha256:67a7efc86ad485dd4b30b14e0e8c68b37f8638ffe2262214f57ddfceb35fca61

Observation 0371983e-94bb-4be6-a63e-694a22a46085 · outbound

This paper cites Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity,.

Enhancing Robustness in Post-Processing Watermarking: An Ensemble Attack Network Using CNNs and Transformers Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-05T11:19:19.762005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-05T11:19:19.718926Z digest=sha256:a74c67271c0845ac9ef6329075cbb29c1cd8fa351fc08189c532f25c81ecbf3b

Pith citing papers

No inbound Pith citation observations are available.