Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses
As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1904.00979.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T12:19:05.606368Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-14T10:28:44.771432Z
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 c381f0c8-d95c-4435-b2bf-7aac6398842b · inbound
Transferring Robustness for Graph Neural Network Against Poisoning Attacks cites this paper.
Transferring Robustness for Graph Neural Network Against Poisoning Attacks Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T12:19:05.606368Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 838bf3b6-ba5b-4e06-bccb-aa8144ac2143 · inbound
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness cites this paper.
Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness Regional Homogeneity: Towards Learning Transferable Universal Adversarial Perturbations Against Defenses
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-08-14T10:28:44.805410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.