Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Verification of Non-Linear Specifications for Neural Networks
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1902.09592.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T13:26:18.616560Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T21:32:59.054115Z
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 be2b6735-7dc1-4719-ba29-50f9ef12dc54 · inbound
A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics cites this paper.
A Survey of Recent Scalability Improvements for Semidefinite Programming with Applications in Machine Learning, Control, and Robotics Verification of Non-Linear Specifications for Neural Networks
Reference 95
- Resolution
- unresolved
- no resolver link, observed 2026-08-14T13:26:18.616560Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 38c55ea9-2c0e-4ef1-ae66-f67415e7995c · inbound
A Scalable Approach for Safe and Robust Learning via Lipschitz-Constrained Networks cites this paper.
A Scalable Approach for Safe and Robust Learning via Lipschitz-Constrained Networks Verification of Non-Linear Specifications for Neural Networks
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T21:32:59.060301Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.