Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On the detection of synthetic images generated by diffusion models
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2211.00680.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-12T08:02:37.135363Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T23:59:07.398766Z
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 5d20b508-6eec-4574-ad5c-2894c488f0de · 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? On the detection of synthetic images generated by diffusion models
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T23:34:26.592621Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation fe64f637-d2b8-4e9c-819b-562fae8a4a0e · inbound
Deepfake Detection Generalization with Diffusion Noise cites this paper.
Deepfake Detection Generalization with Diffusion Noise On the detection of synthetic images generated by diffusion models
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T11:25:19.607868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 8254fae0-9fc6-444b-a52b-ee497040da72 · inbound
The CIFAR Synthetic Evidence Corpus for Detecting AI-Generated Evidence cites this paper.
The CIFAR Synthetic Evidence Corpus for Detecting AI-Generated Evidence On the detection of synthetic images generated by diffusion models
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T20:47:22.757504Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation fc06718e-2411-47cd-a025-090f775153c8 · inbound
Forged Calamity: Benchmark for Cross-Domain Synthetic Disaster Detection in the Age of Diffusion cites this paper.
Forged Calamity: Benchmark for Cross-Domain Synthetic Disaster Detection in the Age of Diffusion On the detection of synthetic images generated by diffusion models
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T23:59:07.403772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 934a6340-cfe8-4003-b59b-bce6c5beea40 · inbound
BiSLW: Bi-Spectral Latent Watermarking for Generative Diffusion Models cites this paper.
BiSLW: Bi-Spectral Latent Watermarking for Generative Diffusion Models On the detection of synthetic images generated by diffusion models
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T08:02:37.135363Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.