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Paper Citation Record · LEDGER

Long-distance Geomagnetic Navigation in GNSS-denied Environments with Deep Reinforcement Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2410.15837.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2410.15837 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:26:15.587854Z

measured 0 of 1 external citation measurements

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 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.

source=pdf_text observed=2026-08-08T20:26:15.587854Z digest=sha256:e99951436bd421125156d763a85cc678774341838c8ba8394fd84db4d450d24e

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T12:24:01.378953Z digest=sha256:18a22a9ba1bd72005fb707fac182a216d78d18827e5cca3b6e47d85a2516b9e4