Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:1606.04435.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
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 2026-08-14T11:19:34.150832Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T18:20:00.247364Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation ababaec7-0ecf-4525-b51d-2e57b490885e · inbound
advPattern: Physical-World Attacks on Deep Person Re-Identification via Adversarially Transformable Patterns Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 34bc01ba-83ca-42b1-9c32-818242e79163 · inbound
Adversarial Filtering Based Evasion and Backdoor Attacks to EEG-Based Brain-Computer Interfaces Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Reference 22
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 323236d1-5aeb-440b-9220-d252c233243e · inbound
Comprehensive Survey on Adversarial Examples in Cybersecurity: Impacts, Challenges, and Mitigation Strategies Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Reference 41
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24fa556a-ffab-4257-8012-a067acd2afc8 · inbound
ADAPT: A Pseudo-labeling Approach to Combat Concept Drift in Malware Detection Adversarial Perturbations Against Deep Neural Networks for Malware Classification
Reference 37
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.