Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On Large Language Models in National Security Applications
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.03453.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T04:12:57.720091Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
1
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 464074f8-5fee-4563-a630-b93ed80bb0b0 · inbound
Sovereign Large Language Models: Advantages, Strategy and Regulations cites this paper.
Sovereign Large Language Models: Advantages, Strategy and Regulations On Large Language Models in National Security Applications
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T04:12:57.720091Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a373add2-c0b8-44e1-b0c5-49ae5cc8eb54 · inbound
Semantic Scheduling for LLM Inference cites this paper.
Semantic Scheduling for LLM Inference On Large Language Models in National Security Applications
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T01:09:20.517251Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53e3bca5-074f-498e-a318-d298172f6122 · inbound
Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data cites this paper.
Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data On Large Language Models in National Security Applications
Reference 152
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T05:57:21.828025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.