Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Survey of Adversarial Defenses in Vision-based Systems: Categorization, Methods and Challenges
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2503.00384.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T14:21:41.852561Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-15T18:16:14.067578Z
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 0d5260d1-8def-4835-869f-f18f05ebae5c · inbound
On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models cites this paper.
On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models A Survey of Adversarial Defenses in Vision-based Systems: Categorization, Methods and Challenges
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T14:23:34.803627Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.