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Paper Citation Record · LEDGER

Towards a satellite image manipulation and deepfake localization benchmark dataset

As of 9 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2608.04840.

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

pith.paper-citation-record.v1
2608.04840 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:19:45.381455Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+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

12 of 12 outbound references displayed

  • verified exact3
  • verified fuzzy6
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation edd70de3-6391-41e9-8cf1-e059f370f8dd · outbound

This paper cites RSFAKE-1M: A Large-Scale Dataset for Detecting Diffusion-Generated Remote Sensing Forgeries.

Towards a satellite image manipulation and deepfake localization benchmark dataset RSFAKE-1M: A Large-Scale Dataset for Detecting Diffusion-Generated Remote Sensing Forgeries

Reference 1

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:19:45.442484Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:19:45.340339Z digest=sha256:02ebc048e3024ab558f16d0fe4e5de65aacb5caa4261775757750097ad75dae1

Observation 2696b781-5970-426c-8e60-ad3e04749a32 · outbound

This paper cites Fldcf: A collaborative framework for forgery localization and detection in satellite imagery,.

Towards a satellite image manipulation and deepfake localization benchmark dataset Fldcf: A collaborative framework for forgery localization and detection in satellite imagery,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:45.521527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:19:45.344728Z digest=sha256:fa761c2c15bfaf842b94eb6beb05c29c07204406661f81076acaf491dd6362a3

Observation bd001403-fbbd-4810-bbdb-8bc90575279c · outbound

This paper cites DM-AER-DeepFake-V1 dataset,.

Towards a satellite image manipulation and deepfake localization benchmark dataset DM-AER-DeepFake-V1 dataset,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:45.511978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:19:45.348212Z digest=sha256:a94b56cc5b22ab65fc758e13de551bf7452ff8b1fe1fcdf253dcd6b081c65805

Observation f1201127-fcd7-45cb-9a66-f33690d6c5a4 · outbound

This paper cites Deep fake ge- ography? when geospatial data encounter artificial intelligence,.

Towards a satellite image manipulation and deepfake localization benchmark dataset Deep fake ge- ography? when geospatial data encounter artificial intelligence,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:45.502196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:19:45.352217Z digest=sha256:3300820516b216cae75bba6d4f59ad9aab1d31143fcdeaa5220773806f9f1e71

Observation e11393a6-7850-4cc5-a299-4ecac51e7fef · outbound

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

Towards a satellite image manipulation and deepfake localization benchmark dataset A sanity check for AI-generated image detection,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:45.491263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:19:45.355681Z digest=sha256:628f503b5e1bae70a670cdfc4a46f8425bca0b7180a042adfe45b7e6f2f8eff8

Observation d451b918-291f-4577-93d6-db1f9f936ed5 · outbound

This paper cites Satellite Image Forgery Detection and Localization Using GAN and One-Class Classifier.

Towards a satellite image manipulation and deepfake localization benchmark dataset Satellite Image Forgery Detection and Localization Using GAN and One-Class Classifier

Reference 6

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:19:45.429445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:19:45.359666Z digest=sha256:07504bdb365a469aa74cff3c2584eafc7a260c1161812f01809b4cfeaf310869

Observation 057c7577-efb1-49ac-abfa-7db72bed5bca · outbound

This paper cites Func- tional map of the world,.

Towards a satellite image manipulation and deepfake localization benchmark dataset Func- tional map of the world,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:45.481621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:19:45.363768Z digest=sha256:95b9a7db8a83030ac9e13f7d7e8616febab90b06137c36b72eb5f3858b836091

Observation 52a6c0b2-05f8-4496-878c-bf5e5b60e0f7 · outbound

This paper cites Segment anything,.

Towards a satellite image manipulation and deepfake localization benchmark dataset Segment anything,

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:45.367109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:45.367109Z digest=sha256:19ca22978b53672bb1b9b272aa26b601a1e880a7dfa97249ebeb1e17b31b10c9

Observation 50674a48-f8da-450b-8fef-08d94ffdb3f2 · outbound

This paper cites Paint by example: Exemplar-based image editing with diffusion models,.

Towards a satellite image manipulation and deepfake localization benchmark dataset Paint by example: Exemplar-based image editing with diffusion models,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T15:19:45.466674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:19:45.370818Z digest=sha256:ba71bfb3acff0f2dfb81db9249e2880948786bb3ff75596453df44b056e7db79

Observation 6ec65aa4-a4d6-4a24-a5f3-f818f608960a · outbound

This paper cites Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model.

Towards a satellite image manipulation and deepfake localization benchmark dataset Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:19:45.415036Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T15:19:45.373781Z digest=sha256:cb32b7d331dd454ac9bd7a1d46ff0805e5d1acd54f944050fe35bbfa09a81aff

Observation 991fb1cb-dbb4-4f0b-a3fa-19f5125908a9 · outbound

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

Towards a satellite image manipulation and deepfake localization benchmark dataset High-resolution image synthesis with latent diffusion models,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:45.377967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:45.377967Z digest=sha256:f8d9ef0bab04283091a3722de5fcc103039c3973bc7c1859e29cce8ba5c8b1f9

Observation 027a3585-638d-40c1-95df-e75a1ed03714 · outbound

This paper cites Samrs: Scaling-up remote sensing segmentation dataset with segment anything model,.

Towards a satellite image manipulation and deepfake localization benchmark dataset Samrs: Scaling-up remote sensing segmentation dataset with segment anything model,

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T15:19:45.381455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:19:45.381455Z digest=sha256:87a2cd403afc343863b1fe3ce7cf73a9a7ea66788ffa335ae90515e1aace327a

Pith citing papers

No inbound Pith citation observations are available.