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Paper Citation Record · LEDGER

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing

As of 13 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2506.05934.

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

pith.paper-citation-record.v1
2506.05934 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:19:08.184540Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

39 of 39 outbound references displayed

  • verified exact1
  • verified fuzzy19
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation db692c20-a3c8-4852-9deb-37af60d62c3f · outbound

This paper cites Blended diffusion for text-driven editing of natural images.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Blended diffusion for text-driven editing of natural images

Reference 1

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source=pdf_text observed=2026-08-07T10:19:03.478920Z digest=sha256:57d2af0bbce172a637fcd1b77fed908fd2141c6d014bfa429dc7c2ffcc149a23

Observation 832a6ef4-b1f8-436b-9b7c-8c0540a3a82d · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2

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source=pdf_text observed=2026-08-07T10:19:03.643392Z digest=sha256:41d31cc3c7f718b1632e9341a19ec825bf780a90e78a2bf0c30b52c76dd00e84

Observation e8ed28c1-cc6d-416e-9053-1ac65b93a051 · outbound

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

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing In- structpix2pix: Learning to follow image editing instructions

Reference 3

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:03.855180Z digest=sha256:2301a513c016318ca19c165481c5c9908db37cb85f13e544556d596d20cc1c98

Observation 1c99b18f-c93a-4fc2-a372-240b67f1a025 · outbound

This paper cites Video generation models as world simu- lators.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Video generation models as world simu- lators

Reference 4

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:04.029028Z digest=sha256:28f9372651ed9e27b301367e8251d793bc7a7c4168e0d7dbcd00cd8dbd896324

Observation bf34d4f6-dba7-4ab0-b8d8-ee609ba01233 · outbound

This paper cites Masactrl: Tuning-free mu- tual self-attention control for consistent image synthesis and editing.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Masactrl: Tuning-free mu- tual self-attention control for consistent image synthesis and editing

Reference 5

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:04.180450Z digest=sha256:e49cb7d23a565b03a35c3639c18229f44f4f9843f14d5937485c338143ca1ef3

Observation 5232c960-e01e-4fa2-af64-2d7e254d1e09 · outbound

This paper cites Diffusion mod- els beat gans on image synthesis.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Diffusion mod- els beat gans on image synthesis

Reference 6

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source=pdf_text observed=2026-08-07T10:19:04.368543Z digest=sha256:d976692084062d579fd4a0eca9065c65e1d283485d657919a7376a7261789581

Observation 496630e3-991c-49ed-923a-aab74dce2da1 · outbound

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

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing TokenFlow: Consistent Diffusion Features for Consistent Video Editing

Reference 7

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source=pdf_text observed=2026-08-07T10:19:04.506663Z digest=sha256:d617e5bdc2d72f480349121d564e1714bdf3ff867ff33b956a66e528c317cc2c

Observation 6b853151-fbfe-4104-9911-6b12fa6eab31 · outbound

This paper cites Prompt-to-Prompt Image Editing with Cross Attention Control.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 8

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source=pdf_text observed=2026-08-07T10:19:04.637891Z digest=sha256:307507068c1985851c803b8b08852873f57e1cc206f57b4fdb6e72bc6c00ca21

Observation ed7b6033-a2ee-48e8-b8ea-1319dc9cad69 · outbound

This paper cites Denoising diffu- sion probabilistic models.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Denoising diffu- sion probabilistic models

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:04.790362Z digest=sha256:8af0476afbf0149215523550523dcdef057fe011624fd58f097ee7a4d56be9df

Observation 92184380-9a3e-43b7-9b83-91f6786f9bde · outbound

This paper cites Imagen Video: High Definition Video Generation with Diffusion Models.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Imagen Video: High Definition Video Generation with Diffusion Models

Reference 10

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source=pdf_text observed=2026-08-07T10:19:04.949846Z digest=sha256:867b26f1f80103754672dd21a0fe8eb583d547ec6a4ea67e8ca7887d53fdce81

Observation 91f1a1dc-e477-4bf3-8a1e-ae32cce936ee · outbound

This paper cites Video dif- fusion models.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Video dif- fusion models

Reference 11

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source=pdf_text observed=2026-08-07T10:19:05.049316Z digest=sha256:73a9a1ed799e92180f2638fe795d81f06491878145282264338b84d6385c5352

Observation 951529a9-b87d-438a-8509-17cfd083a5cd · outbound

This paper cites Video dif- fusion models.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Video dif- fusion models

Reference 12

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source=pdf_text observed=2026-08-07T10:19:05.236022Z digest=sha256:c01a64bbc7b2df39ffc40d96dc2f1cbfc5bfaa4cf4014f69265f31dfaf692d0f

Observation 2c9a2b91-8962-44be-8842-63183fa8d461 · outbound

This paper cites Imagic: Text-based real image editing with diffusion models.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Imagic: Text-based real image editing with diffusion models

Reference 13

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source=pdf_text observed=2026-08-07T10:19:05.356618Z digest=sha256:a3d3a8c9c33a1a534f0925d4cfd6ab8d76a712850f363dc12ead9b240f86d798

Observation 343c1462-f542-48ab-a8b4-992900d1f20d · outbound

This paper cites Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation

Reference 14

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:05.476134Z digest=sha256:d49725313f8b9052b0ff621b01fb0d29b3251ead6e4048bec8bc9a59a4e6b31e

Observation 9c13f280-c937-467e-b9f7-28fe2b187b1e · outbound

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

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Video-p2p: Video editing with cross-attention control

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:05.622236Z digest=sha256:e2567d415194a8d52b3210b1fa5db5e482afd66cf37bf65239869b26505a010a

Observation a76149a9-8926-448b-9a87-8880257ea169 · outbound

This paper cites Latte: Latent Diffusion Transformer for Video Generation.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Latte: Latent Diffusion Transformer for Video Generation

Reference 16

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source=pdf_text observed=2026-08-07T10:19:05.798152Z digest=sha256:f30e18dd43d87315ea748f8b33236766ae60f342c3e5deb0ef3c87a6ab4f3eee

Observation 0e1c0273-7406-420d-beef-7a67493a5b1e · outbound

This paper cites Sdedit: Guided image synthesis and editing with stochastic differential equa- tions.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Sdedit: Guided image synthesis and editing with stochastic differential equa- tions

Reference 17

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source=pdf_text observed=2026-08-07T10:19:05.946367Z digest=sha256:d0055ee47475ecebba506f6bf648c6108c7f6b1d2697e5a8251b712890cf65dc

Observation 134e72a0-fd6b-49d2-9905-1031ebadd6e1 · outbound

This paper cites Null-text inversion for editing real images using guided diffusion models.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Null-text inversion for editing real images using guided diffusion models

Reference 18

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source=pdf_text observed=2026-08-07T10:19:06.054702Z digest=sha256:143f1aedb69915e23f6cba6f69f13959a3a70a0f989a1af0e6f8a9c523d92586

Observation 580e706b-153f-44e9-a01b-e5d81297e334 · outbound

This paper cites Dreamix: Video Diffusion Models are General Video Editors.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Dreamix: Video Diffusion Models are General Video Editors

Reference 19

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source=pdf_text observed=2026-08-07T10:19:06.151039Z digest=sha256:630c1ca5e083632fa3c1832817cda1bc7035b21af41859f9844cfac925ee4a41

Observation 5f2b93ed-92f1-45f6-9742-4daaa3750809 · outbound

This paper cites Zero-shot image-to-image translation.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Zero-shot image-to-image translation

Reference 20

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:06.257761Z digest=sha256:74255e2609fffcf4aaeb25173f59b9ec0275a522cbb3743e7b779c1315cd5d40

Observation c54bbec5-e7f6-4c3d-a340-74ea357175c1 · outbound

This paper cites Scalable diffusion models with transformers.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Scalable diffusion models with transformers

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:06.377616Z digest=sha256:21c98368c5cf1c72e43f3a3a81c5ea4d900f85e7e67b08a34f9211f9c3b316ad

Observation 46bf6358-31b4-4db6-9d55-61b0a42d908b · outbound

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

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing The 2017 DAVIS Challenge on Video Object Segmentation

Reference 22

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source=pdf_text observed=2026-08-07T10:19:06.504730Z digest=sha256:7b5653dbbb840ac9bab5fb697e7f9f1f6632d666f508e3b30617a92629996788

Observation b12d2c16-ac26-4d31-9549-e0029e48b6a4 · outbound

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

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Fatezero: Fus- ing attentions for zero-shot text-based video editing

Reference 23

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:06.588722Z digest=sha256:809c8cbd7108440aa5eea0237af89baa6c5f67d84f2651ed0aea48d55c283b69

Observation d26d0e87-8c74-436f-9770-f07054680081 · outbound

This paper cites Learn- ing transferable visual models from natural language super- vision.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Learn- ing transferable visual models from natural language super- vision

Reference 24

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:06.683218Z digest=sha256:4f28a8130e41506966e5c64191cba456657e701c0d7e71381a9a4424c8376399

Observation 7b2ed3be-d619-4506-8e21-380b0f6e197c · outbound

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

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing High-resolution image syn- thesis with latent diffusion models

Reference 25

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source=pdf_text observed=2026-08-07T10:19:06.769852Z digest=sha256:8e5f0b456bc9d9e5fffce3f7718afe29c0431c58adea963d33a838e437240dff

Observation 5a0c3715-3de1-4a30-8b63-aff7f867382b · outbound

This paper cites U-net: Convolutional networks for biomedical image segmentation.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing U-net: Convolutional networks for biomedical image segmentation

Reference 26

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:06.869319Z digest=sha256:34599cfe91221ed9219237a9c72922715dce8aab14366f5b15eeb844ee992e7b

Observation 1d28bcca-6a64-4db8-8967-056959b88607 · outbound

This paper cites Edit-a-video: Single video editing with object-aware consistency.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Edit-a-video: Single video editing with object-aware consistency

Reference 27

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:06.966198Z digest=sha256:763bbe1441e174b0cd5c13ce169a15a59b66a55c29682b42c1a4c775d4939948

Observation 85521acf-c599-40fd-895b-232d0898e7ba · outbound

This paper cites Make-A-Video: Text-to-Video Generation without Text-Video Data.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Make-A-Video: Text-to-Video Generation without Text-Video Data

Reference 28

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source=pdf_text observed=2026-08-07T10:19:07.077392Z digest=sha256:f130caf5e6191300141ddfb67dba1a0904162e74b2c779d3b0c69309f4345f12

Observation 93d29866-473f-437d-aaa7-719da92ed9d5 · outbound

This paper cites Denois- ing diffusion implicit models.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Denois- ing diffusion implicit models

Reference 29

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raw_fallback, observed 2026-08-07T10:19:09.795744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:07.140497Z digest=sha256:62a404385bc3d8accf6c5f269b35788d511d001018a5c0bca4e51757357fc81d

Observation f9698051-03a2-4865-ae22-fd4e0eff5a3d · outbound

This paper cites Guide-and-Rescale: Self-Guidance Mechanism for Effective Tuning-Free Real Image Editing.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Guide-and-Rescale: Self-Guidance Mechanism for Effective Tuning-Free Real Image Editing

Reference 30

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local_arxiv, observed 2026-08-07T10:19:08.463865Z

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No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:07.247237Z digest=sha256:8e8de8f689dc5718b322024faaadbf42e100260f8f079066e6bd50bb7ccf9d39

Observation c1237889-b656-4685-a507-6bb920794a2b · outbound

This paper cites Plug-and-play diffusion features for text-driven image-to-image translation.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Plug-and-play diffusion features for text-driven image-to-image translation

Reference 31

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source=pdf_text observed=2026-08-07T10:19:07.351249Z digest=sha256:06708fc956851f704a1147cf7dd2b6a899a113bb402fa815b137266b31974b54

Observation 0493e568-c121-479d-86ea-12339d3461f1 · outbound

This paper cites Phenaki: Variable length video generation from open domain textual descriptions.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Phenaki: Variable length video generation from open domain textual descriptions

Reference 32

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raw_fallback, observed 2026-08-07T10:19:09.612868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:07.464678Z digest=sha256:95b3f84138596714c4898a9befa1ded46eb3072228477128f4fbabfdcb9fce2a

Observation 8020d1fc-c6dd-46ea-97b5-a46faefbec06 · outbound

This paper cites Zero-Shot Video Editing Using Off-The-Shelf Image Diffusion Models.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Zero-Shot Video Editing Using Off-The-Shelf Image Diffusion Models

Reference 33

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source=pdf_text observed=2026-08-07T10:19:07.565705Z digest=sha256:7fe73306815cb6e5e5bb83304f1205b5e092a931441d623f44ddaeffd159facb

Observation ee46637e-616d-4ba3-8947-8e9f8dee71fe · outbound

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

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Tune-a-video: One-shot tuning of image diffusion models for text-to-video generation

Reference 34

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:07.663134Z digest=sha256:b4664402b31295e1f5c90b2a23c7e8a034ee753ce2b8c1390ba9549c63f9df65

Observation 0f40527c-d616-455c-bb7e-283c77d3f925 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 35

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source=pdf_text observed=2026-08-07T10:19:07.787108Z digest=sha256:de11d2905a3464fec13da8012b5963ba5bf7953483139f02e7beaae63ba77362

Observation 2b12b871-0d75-4c28-85ee-ca45797e5152 · outbound

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

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing The unreasonable effectiveness of deep features as a perceptual metric

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:19:07.881118Z digest=sha256:692a8e7be3b6f76509a85fbd323f3ee53749cb4b47deb7ac63b5885526f42342

Observation 40d88a7c-bedf-4f33-bd9c-e3482708fe9f · outbound

This paper cites Open-sora: Democratizing efficient video production for all.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Open-sora: Democratizing efficient video production for all

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:19:09.191248Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:07.960797Z digest=sha256:c188b6a4848ffda8434985730cefdc1fc6244368d4b7b3652b9bcd3c1e63f76c

Observation 338153ab-2662-4847-ab01-51a95173f9b1 · outbound

This paper cites Detecting twenty-thousand classes using image-level supervision.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing Detecting twenty-thousand classes using image-level supervision

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:19:08.996401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:08.097733Z digest=sha256:c58ccc222a4f79f3a05dc579b282603d08a6b64e29f10c9f0b0cabf1a6307e8c

Observation 85a95c9a-9186-4d28-ac40-a7aee9e33d20 · outbound

This paper cites taxi”+“autumn.

FADE: Frequency-Aware Diffusion Model Factorization for Video Editing taxi”+“autumn

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:19:08.721804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-08-07T10:19:08.184540Z digest=sha256:283484d5765d88a2c9e2cba721c060c7c02ff65bd92cc56fcbf30109d52f009e

Pith citing papers

No inbound Pith citation observations are available.