Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2404.16154.
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 2026-07-12T03:11:45.903819Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T10:54:47.594511Z
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 1c0195ef-053c-4b67-93fd-b7b0ddb3f924 · inbound
A hardware efficient quantum residual neural network without post-selection cites this paper.
A hardware efficient quantum residual neural network without post-selection A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T05:36:03.370328Z
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 e1650dbd-6bca-4971-ba55-8f7f569d74fd · inbound
A hardware efficient quantum residual neural network without post-selection cites this paper.
A hardware efficient quantum residual neural network without post-selection A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T10:54:47.598433Z
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 4783ee27-d4a4-4d89-95fc-aa9c8ca32f19 · inbound
An End-to-End Multi-Stage Kill-Chain Attack on Quantum Neural Networks: Demonstration on Trapped-Ion Hardware cites this paper.
An End-to-End Multi-Stage Kill-Chain Attack on Quantum Neural Networks: Demonstration on Trapped-Ion Hardware A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T03:11:45.903819Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.