Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 1 inbound Pith citation observation for arXiv:2007.03724.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T18:06:12.986007Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T18:06:13.641272Z
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 f4032e61-7ca7-487b-aba8-8bb5251027ec · inbound
How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? cites this paper.
How Does the Smoothness Approximation Method Facilitate Generalization for Federated Adversarial Learning? Learning while Respecting Privacy and Robustness to Distributional Uncertainties and Adversarial Data
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T18:06:13.650941Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.