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Paper Citation Record · LEDGER

UVCG: Leveraging Temporal Consistency for Universal Video Protection

As of 18 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:2411.17746.

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

pith.paper-citation-record.v1
2411.17746 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:30:24.636180Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

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.

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

37 of 37 outbound references displayed

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  • verified fuzzy17
  • unresolved19
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 54eb0ef6-9e67-4662-ac09-7c1acacfe065 · outbound

This paper cites iedit: Lo- calised text-guided image editing with weak supervision.

UVCG: Leveraging Temporal Consistency for Universal Video Protection iedit: Lo- calised text-guided image editing with weak supervision

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 3e6edb32-ee22-46dc-8f18-21c960620e4e · outbound

This paper cites In- structpix2pix: Learning to follow image editing instructions.

UVCG: Leveraging Temporal Consistency for Universal Video Protection In- structpix2pix: Learning to follow image editing instructions

Reference 2

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 8632fa81-9a77-4672-9f0f-7ad83c42e723 · outbound

This paper cites In- structpix2pix: Learning to follow image editing instructions.

UVCG: Leveraging Temporal Consistency for Universal Video Protection In- structpix2pix: Learning to follow image editing instructions

Reference 3

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation dad12d61-2743-451d-9306-4cae2c5c760c · outbound

This paper cites Structure 8 and content-guided video synthesis with diffusion models.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Structure 8 and content-guided video synthesis with diffusion models

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 52748955-f8e5-4790-8cb6-407133f113e8 · outbound

This paper cites TokenFlow: Consistent Diffusion Features for Consistent Video Editing.

UVCG: Leveraging Temporal Consistency for Universal Video Protection TokenFlow: Consistent Diffusion Features for Consistent Video Editing

Reference 5

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source=pdf_text observed=2026-08-12T13:30:24.266942Z digest=sha256:90e78285b45ae156432c9a490c73ee3c9c858a610d7b6d5926d3886056a45b71

Observation b31b2dac-a7fd-4cc4-8332-0e3e375da043 · outbound

This paper cites Generative adversarial nets.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Generative adversarial nets

Reference 6

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source=pdf_text observed=2026-08-12T13:30:24.285105Z digest=sha256:ea1dd31df8c0223efa675afb9b9e4907b02f9405fdc01551cd4dd2ec108ab200

Observation 8335c92c-c942-4417-88f7-834277ccd817 · outbound

This paper cites Explaining and Harnessing Adversarial Examples.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Explaining and Harnessing Adversarial Examples

Reference 7

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source=pdf_text observed=2026-08-12T13:30:24.293841Z digest=sha256:929b1e806549301c043badffdcb69bafd4255a60eab03396bc2b5c986cd3c612

Observation 2cf2c84c-a42e-4f52-90cb-243bb14817f2 · outbound

This paper cites A Survey on Responsible Generative AI: What to Generate and What Not.

UVCG: Leveraging Temporal Consistency for Universal Video Protection A Survey on Responsible Generative AI: What to Generate and What Not

Reference 8

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source=pdf_text observed=2026-08-12T13:30:24.299778Z digest=sha256:da3bb1ee986d187402b9b722c62781c7e15bbe7ee11bab3a991659d888bf5bf8

Observation 986f5140-7455-4e3c-96b3-b0808b260783 · outbound

This paper cites Diff-privacy: Diffusion-based face privacy pro- tection.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Diff-privacy: Diffusion-based face privacy pro- tection

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.313096Z digest=sha256:13ab0a9a5449ef9bc0c46b140612ce77739a4ffef5266368289659174d535d5f

Observation 325c807a-6768-42c1-9b75-586711178cc7 · outbound

This paper cites Denoising dif- fusion probabilistic models.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Denoising dif- fusion probabilistic models

Reference 10

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source=pdf_text observed=2026-08-12T13:30:24.324099Z digest=sha256:c8c53f7d9b843b2b0176a625052b0dbc628d2d0315182119d2ec9d172e8b807a

Observation ede97725-de2a-495e-8756-c3eeca17fda6 · outbound

This paper cites Diffattack: Eva- sion attacks against diffusion-based adversarial purification.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Diffattack: Eva- sion attacks against diffusion-based adversarial purification

Reference 11

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.329570Z digest=sha256:81d3b64c3ef2ac4748ea7113b8768a2f5100bd041a65d75af3399894c6db1529

Observation 2c2395d9-c6ee-4099-8c8b-89d04b59b171 · outbound

This paper cites Text2video-zero: Text- to-image diffusion models are zero-shot video generators.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Text2video-zero: Text- to-image diffusion models are zero-shot video generators

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.335664Z digest=sha256:73491ee12e18f2831cc3c06e5c1430cb1ae2b4c0ea4415df1fe13019a0bf8a37

Observation 21b8b52e-54ff-49fd-acd1-5c7d5508f6a4 · outbound

This paper cites Auto-Encoding Variational Bayes.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Auto-Encoding Variational Bayes

Reference 13

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-12T13:30:24.344609Z digest=sha256:fc30728bba1018c32144b50ef3c85b99cb08a025b087096f6018abcd95e27077

Observation e5610bb4-d23b-4a3c-a422-8d3bbaae414b · outbound

This paper cites PRIME: Protect Your Videos From Malicious Editing.

UVCG: Leveraging Temporal Consistency for Universal Video Protection PRIME: Protect Your Videos From Malicious Editing

Reference 14

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source=pdf_text observed=2026-08-12T13:30:24.351747Z digest=sha256:396ffc5b428e593e5bc47fd9a26ee809ddf3467a82e22da5f92cf8dbb080a36f

Observation 791e28a8-f5c8-4485-be19-680ea229ec5b · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.371411Z digest=sha256:b72dad36ad11383a53cf3d4d29119b976b59d92b25624c63a1c4e0dc157e3564

Observation 1f544ff6-1f31-4a53-8710-3b07758b7595 · outbound

This paper cites Mist: Towards Improved Adversarial Examples for Diffusion Models.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Mist: Towards Improved Adversarial Examples for Diffusion Models

Reference 16

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source=pdf_text observed=2026-08-12T13:30:24.379682Z digest=sha256:0a1812405adaa8fd311931751da95641be894be26927a944bdf5ac9978872ac4

Observation 63e5e468-6505-43be-a730-50b79a1265e8 · outbound

This paper cites Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples

Reference 17

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source=pdf_text observed=2026-08-12T13:30:24.394470Z digest=sha256:5543d3a453311ac97f74b31434300a9a5fa720f75ca0aef06252592146793f76

Observation 1331800f-f885-4b43-9aa5-e93788fc38de · outbound

This paper cites Inter-frame Accelerate Attack against Video Interpolation Models.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Inter-frame Accelerate Attack against Video Interpolation Models

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 545add3d-a145-4232-9a6c-f1b174af4007 · outbound

This paper cites Video-p2p: Video editing with cross-attention control.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Video-p2p: Video editing with cross-attention control

Reference 19

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source=pdf_text observed=2026-08-12T13:30:24.413385Z digest=sha256:5acb67ff98ceed72cc13b4a5cf0c7ac373b02ebba918e60babf109ef40e62798

Observation 08903cef-eb2b-4adf-902d-7877c10c8c0a · outbound

This paper cites Delving into Transferable Adversarial Examples and Black-box Attacks.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Delving into Transferable Adversarial Examples and Black-box Attacks

Reference 20

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source=pdf_text observed=2026-08-12T13:30:24.418142Z digest=sha256:2e8e516a45f83459bd23ddc0ef0542e7ba23555bf0104a1739902d7f6207788b

Observation f75808f1-d4a5-4cab-8c93-ae8e57e16bb1 · outbound

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

UVCG: Leveraging Temporal Consistency for Universal Video Protection Towards Deep Learning Models Resistant to Adversarial Attacks

Reference 21

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source=pdf_text observed=2026-08-12T13:30:24.425318Z digest=sha256:9cbb67f8d6371385ae9667e5143669aafee614e067a3cb40cbd72fc3dd480220

Observation 171001c7-8294-4fa4-9007-81222bab0fac · outbound

This paper cites Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

Reference 22

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source=pdf_text observed=2026-08-12T13:30:24.432778Z digest=sha256:efc92f6a324b8db04b6549d6566bd669efb0b44e00082746ac0aee2f5972f615

Observation 5b90865e-7417-4698-8b7c-3104254b9330 · outbound

This paper cites The 2017 DAVIS Challenge on Video Object Segmentation.

UVCG: Leveraging Temporal Consistency for Universal Video Protection The 2017 DAVIS Challenge on Video Object Segmentation

Reference 23

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source=pdf_text observed=2026-08-12T13:30:24.442827Z digest=sha256:f9949fba538063d3bd9c66edd2bc5669d80c275be8ccf2f0c37821f8a183ba9e

Observation 2888a429-a9df-4ad7-bff3-fc18a67b46e2 · outbound

This paper cites Fatezero: Fus- ing attentions for zero-shot text-based video editing.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Fatezero: Fus- ing attentions for zero-shot text-based video editing

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 54ae7841-1e6f-4b09-9d22-d998b5d5636f · outbound

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

UVCG: Leveraging Temporal Consistency for Universal Video Protection Learning transferable visual models from natural language supervi- sion

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 7038d4d7-d7b2-461c-b332-d84da9a8ee31 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

UVCG: Leveraging Temporal Consistency for Universal Video Protection High-resolution image syn- thesis with latent diffusion models

Reference 26

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Observation 983d9055-8361-420a-9cf4-333f39cb1580 · outbound

This paper cites Raising the Cost of Malicious AI-Powered Image Editing.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Raising the Cost of Malicious AI-Powered Image Editing

Reference 27

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:30:24.498279Z digest=sha256:9ce70ec3765276c22dc7fad950c7aef20a20a7a2ae9797087e0336abf2b995dd

Observation 35b2fb38-8d6c-4e7b-95a6-560d210710da · outbound

This paper cites Glaze: Protecting artists from style mimicry by{Text-to-Image} models.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Glaze: Protecting artists from style mimicry by{Text-to-Image} models

Reference 28

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

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Observation 635c7bf5-83ae-4a32-9a1d-7b2e525951f0 · outbound

This paper cites Image information and visual quality.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Image information and visual quality

Reference 29

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raw_fallback, observed 2026-08-12T13:30:25.644857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.515742Z digest=sha256:ae258b8bb7d4cba51d003e5527ed53dbeeac2877587b1e358f0416e21542d9d6

Observation b51c9ffe-067c-4660-8bba-139edcbec1d4 · outbound

This paper cites Image quality assessment: from error visibility to structural similarity.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Image quality assessment: from error visibility to structural similarity

Reference 30

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raw_fallback, observed 2026-08-12T13:30:25.624860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.523551Z digest=sha256:a79bb2c03d75fee6c7bf697df579c9dad2fdec3e9472c987da4faa4155fe4916

Observation 597d66c7-8730-4ba6-ba28-106a1f1528dc · outbound

This paper cites Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.531607Z digest=sha256:c7ddea3db9a163f579e41acdcb0f6ad672a7ee7c6b702c3c951940b99b18d988

Observation 564cae59-91df-4544-95dd-115c3e713994 · outbound

This paper cites Cross: Diffusion model makes controllable, robust and se- cure image steganography.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Cross: Diffusion model makes controllable, robust and se- cure image steganography

Reference 32

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raw_fallback, observed 2026-08-12T13:30:25.585944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.551806Z digest=sha256:f875edd4eb6410af19acac9950cb613965d7cfafda89732c2ee33d475e2f6945

Observation 2a4d7e6f-9ae3-4cf6-a978-e5a8a4178000 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

UVCG: Leveraging Temporal Consistency for Universal Video Protection The unreasonable effectiveness of deep features as a perceptual metric

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation c110c7e5-4918-4660-bc61-f98bbed5fc88 · outbound

This paper cites Sine: Single image editing with text-to-image diffusion models.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Sine: Single image editing with text-to-image diffusion models

Reference 34

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raw_fallback, observed 2026-08-12T13:30:25.561006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.583958Z digest=sha256:29b27d58e3f3f4a9148d3b440998418aeb6fb4867e31e76346a775e66a9cbc0e

Observation 5dd429da-ec93-4c47-8eab-f7c46758a06c · outbound

This paper cites Understanding and improving adversarial attacks on latent diffusion model.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Understanding and improving adversarial attacks on latent diffusion model

Reference 35

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:30:24.604166Z digest=sha256:6018a23eb57d9bfd37ed43b09c40efe3d4d3f4091a063609f5f355f5cae171e3

Observation 66641ced-0804-4018-aaa2-7c660b00133e · outbound

This paper cites an unresolved cited work.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Unresolved cited work

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.618187Z digest=sha256:251862fb3f5a93bffde3c3a7b07688b9c3a5d2cff1c0cbcd907205820d0c0573

Observation f1611bc8-c6b8-4e64-9563-ed0261ea640f · outbound

This paper cites Figure 9, figure 10 and figure 11 showcase video protection results using our method on Fatezero.

UVCG: Leveraging Temporal Consistency for Universal Video Protection Figure 9, figure 10 and figure 11 showcase video protection results using our method on Fatezero

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:30:25.497767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-12T13:30:24.636180Z digest=sha256:b1232f292da2dc68e3728efb5c231abbbd5e03149e1fb4b8b62d96e3d913ed0b

Pith citing papers

No inbound Pith citation observations are available.