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Paper Citation Record · LEDGER

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

As of 14 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 2026-08-14T06:32:32.682623+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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.592517Z digest=sha256:200410de1b45f2fb6363915cc246d5d30c188575a7f81a63ec74991a70bed1f6

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.596066Z digest=sha256:b1774e16fb2fec54aea251e34fe891c6f00f7838ae7f04cb4d14488a6dddaebc

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
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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.599043Z digest=sha256:569b52bf9ef87973d3b69671372ab66156c46a0022833514f44a6d43f13e2567

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.602001Z digest=sha256:7dbf1a2d10a11600b2bb83f5c5142c533bd9e5f2a59b5cf1b2d3d8c02681c989

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
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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.605060Z digest=sha256:fd38454ce5fbf46bc5026b475ea4de37b9215a6653f36e57cff089f560715a19

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.608062Z digest=sha256:cc30803115d6870aa9ef0550f336347854b7610dffb62d2be72114d1c88ab264

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.611710Z digest=sha256:0baacfaeb46941ef7e0625a720281991d344ecdc3ea1e70ebda5dcabd76866ce

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.614351Z digest=sha256:052088a0bc0ef958cda9ff808110e38e2fe5649293bf7da2617edf5a7d5d645b

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
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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.616970Z digest=sha256:5d51e4b31645bd73a0b06d41f3517f75f5bffd355ea6992d97347da1b3520d2f

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
verified fuzzy
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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.619923Z digest=sha256:b5aeb4c0bc6c6f6191b38d2513f410c724ac6544d7eda09e466d3f35529a0209

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
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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.622682Z digest=sha256:3bc8c224b7eb7767b51dd209bf6ccec051418a8fd0748a25b4b30c8db5a394d8

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.625530Z digest=sha256:ad2b391ffbdeb2fbc61b745efafe5163e8d79dbca37be48f76e749f6def5cc4c

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.628341Z digest=sha256:ff8129a820aaf9352779d05b25765d375ada3175834fa00aad2335738b4f4a0f

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
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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.631747Z digest=sha256:3d409916feaaf3c968090f3b84183078613900276a8134de2b475726ca0181a0

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.634943Z digest=sha256:6e0e266eb637eb4da0ccc00001cc114dece7ca3197ed89deb1159b04de5d3494

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.637898Z digest=sha256:ad8d0c0dea9e5827b2db5c3d446c57e225ab35b83a98c74985fed68ce87684f7

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.640899Z digest=sha256:686b9e94c6b5bb7c8981c81e7f82f8514dd4d31a6eee70800676bc44a1d21668

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.643621Z digest=sha256:71461fa41167eba7ccc69962f9a4bc740ae32093f1448f4af80580b1265c98d6

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.646534Z digest=sha256:3507368b26a19118acf84ce66c24faac1138b7dd7a59afff2072d0987cae1044

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.649221Z digest=sha256:1f34b265e1ca56623a0289cb94df3fc5133012a87df710fcc50f028461f727a7

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.652114Z digest=sha256:590e557deeb689d061dc7fcb6c42518f5f5aa3bde0ef4d8eadd2c4f7ef05ddb1

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.655031Z digest=sha256:9c277e8f6db9bc75061b4fb189a790129ae921476c1fe3b24f75c8195c45cdff

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.658400Z digest=sha256:4800c34f64cadf16ef9706a8755588e4b08dc8500ac8ea789d289e0c5f2f4a16

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
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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.661200Z digest=sha256:8847341e81f26ab2ab491319970f2f7b163064e230e409600006c7218c3b4745

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.663889Z digest=sha256:23ffbeba1a4c34b7a27e2b9805d272982608bf8ee44fc401be0dcd30c404bf43

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.666851Z digest=sha256:af12fe28227aa7d5c222cf7f0a78d6213df2146dfc5d32c7836441e5f58e6df7

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.669482Z digest=sha256:1d105e381f91e247669798d9c6bde0f00c4078a0afa5529c235c9951b1e4f0df

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.672327Z digest=sha256:957fde8b63103ac35915ad5e8d99518ab4614a61ce55f3670dad6eac1a8c0f0a

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.675175Z digest=sha256:9725da23eba340cc02a4e89572c1fc89a218945ffbc4df240cf317d19c6ffd17

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.677924Z digest=sha256:62599a87e46a2f134ee6e1c4ba7626772b753b51c2d2c8e6d36dd982da75cfcd

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.680538Z digest=sha256:c61f045b0806a3e6bd4bb970201a4478b443b5fd98c2470ce5dc3b2ae4861a50

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

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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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.683184Z digest=sha256:702485e72c57d08827ff7c9b5ea12cf956d6319b82316fc05a7a9fb4b2052b55

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.685844Z digest=sha256:2e9dc3df6729536480a529774f1df14264ea900f4931edddf55a47c854534999

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.688800Z digest=sha256:efe71d7180a6b672b09871cca0d468be33c70fe7fe613062ae7fe05ca08da451

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.691420Z digest=sha256:a768e8abb9e531972a65a21f624a6abe453a7370c9eeecd7e1070cb7621c2c4d

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.694066Z digest=sha256:5272ea2459a22673f20ec124c93b157eaef2a951bb0e3841d744ed5fe70a82b9

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.696923Z digest=sha256:03cab50176e44302de36f3ad4391bfa1ea0bb532a31bd0f7a9e0cce8331cd668

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.699697Z digest=sha256:d1255be6f5c28194fa17203b4750ca250ef4c089b49c9b72dd5e1af69ba0f10a

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.702370Z digest=sha256:682518895b1035dbf378f4d49e3cbd9c7d04e1e37f44af91a7e68dcd38edcf49

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.704949Z digest=sha256:34e9c4257252d3c3cfd32f9357e763e88398d755f2d434507af3d6dbe757f4a6

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.707503Z digest=sha256:b62b8a786253cea033c54eab86d420951331b5144b6ae338f87ae965bc15b669

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.710167Z digest=sha256:3cc48007a81807bdc8fea2ef0e1d36e521cf43916181b70b213357d58d5e058e

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.713069Z digest=sha256:a34674232d0ff3f3658120829f659e3e87e526e1964ff08c90b40d49a21ea92c

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.716280Z digest=sha256:c71cb7f1221fe873f6476b03e808e6b79f96e82235ac3855192a09aa706340af

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-05T11:19:19.718926Z digest=sha256:5cfdf4eaf68e9df6d00c605eac0a33baef635b505ba2db10a6288e113db6d8c5

Pith citing papers

No inbound Pith citation observations are available.