Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Long-distance Geomagnetic Navigation in GNSS-denied Environments with Deep Reinforcement Learning
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.15837.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T14:33:45.744571Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T12:24:03.956745Z
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 0c1b23ce-8462-4e1a-8b95-2035b8a668d7 · inbound
Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation cites this paper.
Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation Long-distance Geomagnetic Navigation in GNSS-denied Environments with Deep Reinforcement Learning
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T14:33:45.744571Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c56f9600-4a66-47c2-8923-583f8b1978a1 · 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 Long-distance Geomagnetic Navigation in GNSS-denied Environments with Deep Reinforcement Learning
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T20:26:15.587854Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea5964f5-886f-45b2-a910-5f1869a4fa5b · 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 Long-distance Geomagnetic Navigation in GNSS-denied Environments with Deep Reinforcement Learning
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T12:24:04.041571Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.