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Paper Citation Record · LEDGER

Towards a satellite image manipulation and deepfake localization benchmark dataset

As of 8 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 2026-08-08T06:32:00.761636+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

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:45.340339Z digest=sha256:d8434d422ad5b41bb914a5f5fd83a0dec91ec2b564e899df06bfb527988086ad

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:45.344728Z digest=sha256:bd8c640af8de476763bad11b7f1b90fa911b6ed19c73a2c441f8ef9def5bca0c

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:45.348212Z digest=sha256:e7016f57f44a21497cb4faf2d9705b2e079c0f2d6b57d7817749ddf2f1d3577d

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:45.352217Z digest=sha256:846a95e813506b7a9f84dc4a60151328d51afd55da0bf66add250a6c74799ac5

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:45.355681Z digest=sha256:8e726e7c7b410d1d8aff573e8c169e29992fa12379339b2393dc4ff9b77262fe

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:45.359666Z digest=sha256:c5611ece0c4ce57202d399a4e6559a38c256f0c7c781f8a3287144d202e5b842

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:45.363768Z digest=sha256:577d03614da32a47598d63c0cc2964f5957d6ff655f560261081c1d5383e8ba8

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=sha256:088aa8c3da90d5969f676e446d663b6b02e6a27c6964811c5e7a5b162a104cc9

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:45.370818Z digest=sha256:06c817b86451cd849a574feb0ff850920318a845fa62894b964dadecd92f9a3e

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T15:19:45.373781Z digest=sha256:5b88264dff2619957797a29b1347c10b070cf2f4805f19ae92e74dd56ab1c0ca

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=sha256:001db22a8e6dd9857e50236dbf045b51f253b95d3a3f23e0c0e4ba797dd37267

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:b47dc97fbe3db24188d9b317d57d3af35fbda328bed79c4a12762762eb969f84

Pith citing papers

No inbound Pith citation observations are available.