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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=sha256:50f1ad5b2843a138ad96a32ae9164d7ba1aa2960321859bb9802f32ff416dc03

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:f8d7911ffeacfad68125b8c7ad7906f094fe369d5888b745f179e1c59ae0797c

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:d303393da62ddaba5cf85a38972c04ef5f6ece75b1f50d80f08c32b187663585

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=sha256:8c2ccb2375b7fa8cbaf62bbaa1b0900647421ed7cacf87ac96d9f93bb3f1f3c7

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:b6f77cc1bf01afceabdccf2da131b1c86be57dac971cbc3c5faff6125831722f

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:ed996f54b5d97406de8a3ef178e7611e1487f1439d222a054c5ca3c5d4113d98

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:b279159b8abb3a5e08a6f71c6c5e00febdf027eaa81cdfb4b179b8c1169bcfc9

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=sha256:1c16648257ab15785f46535e9249a977349523fa5f671111db17bfcd4b96b762

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=sha256:03df18797d68c7ae67eaf75bf52e4f44a5c7285735fcdd93e226c857f6fcf82c

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:a673735308e66bde416da8e06c98d2ab13f4a5cc505f12ac3d214fb4bc455274

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=sha256:2be2c0bd3c5a2ea61848f175fbc34111772bf7b0fc6261f1d16b38b174250a7e

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:ec2e28451fa92ef76e4943d1438e54b0d1ac11692ac8852ef88e890eb74f5dc7

Pith citing papers

No inbound Pith citation observations are available.