Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2309.02218.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:54:08.711080Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T09:11:00.508741Z
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 cbb2a882-489c-49d2-9fd0-5bb50aa2d540 · inbound
ExpertGen: Training-Free Expert Guidance for Controllable Text-to-Face Generation cites this paper.
ExpertGen: Training-Free Expert Guidance for Controllable Text-to-Face Generation Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:54:08.711080Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7b33a313-2913-45a2-8404-26fa1d6c2453 · inbound
SEED: A Benchmark Dataset for Sequential Facial Attribute Editing with Diffusion Models cites this paper.
SEED: A Benchmark Dataset for Sequential Facial Attribute Editing with Diffusion Models Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:06:39.358102Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation caa6b193-0ace-46d4-b12b-32f04f2e6a77 · inbound
SEED: A Large-Scale Benchmark for Provenance Tracing in Sequential Deepfake Facial Edits cites this paper.
SEED: A Large-Scale Benchmark for Provenance Tracing in Sequential Deepfake Facial Edits Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T09:11:00.511878Z
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.
Observation 12588bb1-fb9a-49f9-84de-10ff53d97740 · inbound
Deepfake Detection Generalization with Diffusion Noise cites this paper.
Deepfake Detection Generalization with Diffusion Noise Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T11:25:19.537838Z
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.
Observation e24ab813-f025-49b0-9c47-2a4829a38fd7 · inbound
DVAR: Adversarial Multi-Agent Debate for Video Authenticity Detection cites this paper.
DVAR: Adversarial Multi-Agent Debate for Video Authenticity Detection Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T07:52:13.676387Z
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.
Observation 21948af9-8a08-44cf-897a-8f589d936044 · inbound
Position: AI/ML Deepfake Research is Misaligned with AI-Generated Non-Consensual Intimate Imagery (AIG-NCII) cites this paper.
Position: AI/ML Deepfake Research is Misaligned with AI-Generated Non-Consensual Intimate Imagery (AIG-NCII) Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models
Reference 98
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T13:50:48.065133Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0c14b60e-cd87-4348-9deb-d3d0426715a8 · inbound
AdaForensics: Learning A Characteristic-aware Adaptive Deepfake Detector cites this paper.
AdaForensics: Learning A Characteristic-aware Adaptive Deepfake Detector Robustness and Generalizability of Deepfake Detection: A Study with Diffusion Models
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:32:48.408078Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.