Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1901.03583.
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 2026-08-10T04:30:48.432278Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-05-16T12:12:51.235343Z
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 a6b13f4f-6908-412e-96fd-bfb2f40711b9 · inbound
Uncovering and Understanding FPR Manipulation Attack in Industrial IoT Networks cites this paper.
Uncovering and Understanding FPR Manipulation Attack in Industrial IoT Networks Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries
Reference 82
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T12:12:51.237480Z
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 23a7734b-8f37-4119-bb87-c3b709103fd3 · inbound
Empirical Analysis of Evasion and Poisoning Against Malware Data Drift Detection cites this paper.
Empirical Analysis of Evasion and Poisoning Against Malware Data Drift Detection Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:25:29.719558Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 185da30d-342b-480c-ac49-1b116852520b · inbound
Empirical Analysis of Evasion and Poisoning Against Malware Data Drift Detection cites this paper.
Empirical Analysis of Evasion and Poisoning Against Malware Data Drift Detection Explaining Vulnerabilities of Deep Learning to Adversarial Malware Binaries
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T04:30:48.432278Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.