Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:1802.04528.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T04:30:48.442583Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T19:31:10.937229Z
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 1010d64d-fdf2-44b3-b58b-1de967e714b9 · inbound
RoMA: Robust Malware Attribution via Byte-level Adversarial Training with Global Perturbations and Adversarial Consistency Regularization Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Reference 20
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2b785b30-d81f-4f96-8561-4da46a3dd038 · inbound
Tarallo: Evading Behavioral Malware Detectors in the Problem Space Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Reference 24
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ee35854a-dbb7-4567-af2f-ed82e57b64b5 · inbound
MalGuard: Towards Real-Time, Accurate, and Actionable Detection of Malicious Packages in PyPI Ecosystem Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Reference 26
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2f971dc6-004d-4541-965f-9c158fce4c89 · inbound
Adversarial Evasion in Non-Stationary Malware Detection: Minimizing Drift Signals through Similarity-Constrained Perturbations Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Reference 13
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 2c3c8d92-ddf6-458c-a477-b48d4fa68716 · inbound
Adversarial Malware Generation in Linux ELF Binaries via Semantic-Preserving Transformations Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Reference 7
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 8533bff1-f997-405f-b939-76bea3797f14 · inbound
Guarding Organizations Against Malware Risk: A Novel Graph-Based Malware Detection Method Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Reference 56
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 21a1edf8-e6fa-4103-8429-ac3c49b4c22a · inbound
Empirical Analysis of Evasion and Poisoning Against Malware Data Drift Detection Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation efa8f771-6c7d-4756-b4e3-4f136c5279fa · inbound
Empirical Analysis of Evasion and Poisoning Against Malware Data Drift Detection Deceiving End-to-End Deep Learning Malware Detectors using Adversarial Examples
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.