Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2412.11882.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T20:26:15.450318Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T12:24:04.119310Z
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 0d5547c2-e87b-4e30-83bf-95c50a885d34 · inbound
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation cites this paper.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T20:26:15.445211Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fa0f2772-1501-4fe7-a3a6-ca66b8bed4db · inbound
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation cites this paper.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T20:26:15.450318Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8e760e7b-3073-4c89-8d59-fae46190e158 · inbound
Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning cites this paper.
Fine-tuning for Data-enabled Predictive Control of Noisy Systems by Reinforcement Learning Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T12:24:04.189511Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.