Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Limits of Deepfake Detection: A Robust Estimation Viewpoint
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1905.03493.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T18:17:57.314006Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T04:37:06.629305Z
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 634074a0-64b1-4d4d-995a-458f9e71f6a3 · inbound
Fair-FLIP: Fair Deepfake Detection with Fairness-Oriented Final Layer Input Prioritising cites this paper.
Fair-FLIP: Fair Deepfake Detection with Fairness-Oriented Final Layer Input Prioritising Limits of Deepfake Detection: A Robust Estimation Viewpoint
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:17:57.314006Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2ac247be-e9fb-4e08-a421-8d46455e81aa · inbound
Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection cites this paper.
Seeing Through Deepfakes: A Human-Inspired Framework for Multi-Face Detection Limits of Deepfake Detection: A Robust Estimation Viewpoint
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:52:38.818462Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7561827b-15e0-4478-ae5b-371c0bc03a63 · inbound
Adversarial Attacks on Reinforcement Learning-based Medical Questionnaire Systems: Input-level Perturbation Strategies and Medical Constraint Validation cites this paper.
Adversarial Attacks on Reinforcement Learning-based Medical Questionnaire Systems: Input-level Perturbation Strategies and Medical Constraint Validation Limits of Deepfake Detection: A Robust Estimation Viewpoint
Reference 45
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T04:37:06.741360Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.