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Paper Citation Record · LEDGER

TextureCrop: Enhancing Synthetic Image Detection through Texture-based Cropping

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.15500.

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

pith.paper-citation-record.v1
2407.15500 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:17:41.474026Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-01T14:25:47.209711Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 97b50a94-a707-4ff2-bbe7-e5954032e451 · inbound

Any-Resolution AI-Generated Image Detection by Spectral Learning cites this paper.

Any-Resolution AI-Generated Image Detection by Spectral Learning TextureCrop: Enhancing Synthetic Image Detection through Texture-based Cropping

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-12T10:17:41.474026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T10:17:41.474026Z digest=sha256:5889072ff9f3a965d44557915e28d9dec93ae5940cd6f05b9a33a12df472f6aa

Observation 94d2241a-c9a0-4670-b243-b0af36f17333 · inbound

Navigating the Challenges of AI-Generated Image Detection in the Wild: What Truly Matters? cites this paper.

Navigating the Challenges of AI-Generated Image Detection in the Wild: What Truly Matters? TextureCrop: Enhancing Synthetic Image Detection through Texture-based Cropping

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-21T23:34:26.566173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-21T23:31:40.691896Z digest=sha256:c6c820b6f91a0867d711539017a3b90ffb11aef460724acfcdb62b1c7039addb

Observation a2cd0a8e-9271-42e7-a6b5-3480998a654e · inbound

Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation cites this paper.

Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation TextureCrop: Enhancing Synthetic Image Detection through Texture-based Cropping

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-07-01T14:25:47.212508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-30T21:17:16.489486Z digest=sha256:62bd846bd00f726610688afe051ebe1073fae961c26fbec3b28ec40526951ac6