Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2206.12227.
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 2026-07-31T23:40:00.743668Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation aa94c9bb-4101-4b3d-ae16-8b4153784f5e · inbound
Probabilistic Verification of Neural Networks via Efficient Probabilistic Hull Generation cites this paper.
Probabilistic Verification of Neural Networks via Efficient Probabilistic Hull Generation Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T14:41:38.105619Z
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.
Observation e91bb73d-ee4e-49e7-831a-d1bea1cf1371 · inbound
SoK: A Comprehensive Analysis of the Current Status of Neural Tangent Generalization Attacks with Research Directions cites this paper.
SoK: A Comprehensive Analysis of the Current Status of Neural Tangent Generalization Attacks with Research Directions Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
Reference 64
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T20:42:56.146257Z
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.
Observation a3164fe8-059b-4497-9792-85b4a68e6365 · inbound
On AI Safety and Security Technical Debt in Engineering AI-Enabled Systems cites this paper.
On AI Safety and Security Technical Debt in Engineering AI-Enabled Systems Adversarial Robustness of Deep Neural Networks: A Survey from a Formal Verification Perspective
Reference 137
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T23:40:00.743668Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.