Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-08T20:26:15.688235Z
Paper Citation Record · LEDGER
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation
As of 16 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 2 inbound Pith citation observations for arXiv:2502.05069.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:17:43.824269Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T12:24:04.282245Z
Reference resolution
55 of 55 outbound references displayed
- verified exact5
- verified fuzzy43
- unresolved7
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation e5361161-2bde-443d-a00e-9bca90047428 · outbound
This paper cites Long-distance geomagnetic navigation: Imitations of animal migration based on a new assumption,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Long-distance geomagnetic navigation: Imitations of animal migration based on a new assumption,
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.264434Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0d5547c2-e87b-4e30-83bf-95c50a885d34 · outbound
This paper cites Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation.
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 1db5d146-df6e-49a0-be2f-a29fa3ae99e7 · outbound
This paper cites Geographic true navigation based on real-time measurements of geomagnetic fields,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Geographic true navigation based on real-time measurements of geomagnetic fields,
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.250042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 16c375a4-dc8b-4049-816b-e836b3af8d12 · outbound
This paper cites Geomagnetic vector pattern recognition navigation method based on probabilistic neural network,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Geomagnetic vector pattern recognition navigation method based on probabilistic neural network,
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.235864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation cbf3e914-9859-4964-94b4-83efb808471b · outbound
This paper cites Geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Geomagnetic gradient-assisted evolutionary algorithm for long-range underwater navigation,
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.222064Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4b6e3fe4-29a7-4031-96b4-4b1093a91ed3 · outbound
This paper cites Magnetic navigation on an F-16 aircraft using online calibration,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Magnetic navigation on an F-16 aircraft using online calibration,
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.207919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d9edf84a-6c1c-415c-804d-4daaab458bdd · outbound
This paper cites Promising aircraft navigation systems with use of physical fields: Stationary magnetic field gradient, gravity gradient, alternating magnetic field,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Promising aircraft navigation systems with use of physical fields: Stationary magnetic field gradient, gravity gradient, alternating magnetic field,
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.193708Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f8c08332-7cce-45b5-a3e4-d24e3f72f213 · outbound
This paper cites A Bionic Data-driven Approach for Long-distance Underwater Navigation with Anomaly Resistance.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation A Bionic Data-driven Approach for Long-distance Underwater Navigation with Anomaly Resistance
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-08-08T20:26:16.631308Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a67229c7-ddab-48c5-bb5c-c0fac29405d0 · outbound
This paper cites Adaptive robust tracking control with active learning for linear systems with ellipsoidal bounded uncertainties,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Adaptive robust tracking control with active learning for linear systems with ellipsoidal bounded uncertainties,
Reference 9
- Resolution
- verified exact
- arxiv_id_nonexistent, observed 2026-08-08T20:26:16.610687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 15575531-e016-4913-918e-17b34517b50f · outbound
This paper cites Adaptive dual control with online outlier detection for uncertain systems,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Adaptive dual control with online outlier detection for uncertain systems,
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.178934Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5d6147c0-5bac-4bb9-9957-c0638474419e · outbound
This paper cites Dual control for stochastic systems with multiple uncertainties,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Dual control for stochastic systems with multiple uncertainties,
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.163894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2c974ad3-cfb1-4bd2-90b5-d99549d00a85 · outbound
This paper cites Robust quadratic optimal control of linear systems with ellipsoid-set learning,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Robust quadratic optimal control of linear systems with ellipsoid-set learning,
Reference 12
- Resolution
- verified exact
- arxiv_id_nonexistent, observed 2026-08-08T20:26:16.419947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6f967fda-1b7c-4cbf-b78b-19cf9579428c · outbound
This paper cites An outlier detection scheme for dynamical sequential datasets,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation An outlier detection scheme for dynamical sequential datasets,
Reference 13
- Resolution
- verified exact
- arxiv_id_nonexistent, observed 2026-08-08T20:26:16.245296Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 607b0dac-afd8-4f3d-82b8-bd3dd871663b · outbound
This paper cites Sequential outlier criterion for sparsification of online adaptive filtering,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Sequential outlier criterion for sparsification of online adaptive filtering,
Reference 14
- Resolution
- verified exact
- arxiv_id_nonexistent, observed 2026-08-08T20:26:16.013044Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation b45cf312-3c44-49c9-a8d7-ff4d2280c1c5 · outbound
This paper cites Natural orthogonal component analysis of international geomagnetic reference field models and its application to historical geomagnetic models,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Natural orthogonal component analysis of international geomagnetic reference field models and its application to historical geomagnetic models,
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.149335Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 412541cb-5dd6-45ba-bb3d-a69e91a89279 · outbound
This paper cites Deep reinforcement learning based mobile robot navigation: A review,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Deep reinforcement learning based mobile robot navigation: A review,
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.134946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 2c7af293-4f89-43d7-8176-0ef224c0078c · outbound
This paper cites Simulation of single element geomagnetic matching navigation based on intensified mad,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Simulation of single element geomagnetic matching navigation based on intensified mad,
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.120576Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0b6bd3f1-0563-47ff-9c05-d0015f94112c · outbound
This paper cites A fast algorithm of the geomagnetic correlation matching based on msd,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation A fast algorithm of the geomagnetic correlation matching based on msd,
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.105979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 6a9b4665-5482-46d1-ac66-1b07f9123458 · outbound
This paper cites A new geomagnetic matching navigation method based on multidimensional vector elements of earth’s magnetic field,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation A new geomagnetic matching navigation method based on multidimensional vector elements of earth’s magnetic field,
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.090870Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 50cb284d-0be0-44a1-bda6-6c977dc79ed4 · outbound
This paper cites An innovative PSO-ICCP matching algorithm for geomagnetic navigation,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation An innovative PSO-ICCP matching algorithm for geomagnetic navigation,
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.076549Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7bfb71b2-88b6-40b8-9e92-23b0439b7f05 · outbound
This paper cites Magnetoreception in birds: two receptors for two different tasks,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Magnetoreception in birds: two receptors for two different tasks,
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.061802Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation eef9443a-5c34-4262-b325-ef01c7b5a000 · outbound
This paper cites Orientation and open-sea navigation in sea turtles,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Orientation and open-sea navigation in sea turtles,
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.047664Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 53a8c7af-1b84-4cd3-abcf-055b5cd716d8 · outbound
This paper cites Inherited magnetic maps in salmon and the role of geomagnetic change,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Inherited magnetic maps in salmon and the role of geomagnetic change,
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.033772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e1616d8f-ee0b-4aec-806e-3933a1d38302 · outbound
This paper cites True navigation and magnetic maps in spiny lobsters,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation True navigation and magnetic maps in spiny lobsters,
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.019660Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 05b6b8c6-6e27-4f85-bde9-929fcde51880 · outbound
This paper cites Bio-inspired navigation based on geomagnetic,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Bio-inspired navigation based on geomagnetic,
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:17.005452Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f96984fb-86ba-473c-8698-66a2f0494c65 · outbound
This paper cites Bio-inspired geomagnetic navigation method for autonomous underwater vehicle,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Bio-inspired geomagnetic navigation method for autonomous underwater vehicle,
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.991466Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0968eb95-4306-4e65-b5f9-d86ec881b574 · outbound
This paper cites Bionic geomagnetic navigation method for auv based on differential evolution algorithm,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Bionic geomagnetic navigation method for auv based on differential evolution algorithm,
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.977137Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ab5796c6-5920-42ad-a0c4-b355f49f7f43 · outbound
This paper cites Artificial intelligence-assisted geomagnetic navigation framework,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Artificial intelligence-assisted geomagnetic navigation framework,
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.963286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation ee8a43f3-40f2-4206-91f5-762d279dba7d · outbound
This paper cites Geomagnetic navigation for AUV based on deep reinforcement learning algorithm,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Geomagnetic navigation for AUV based on deep reinforcement learning algorithm,
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.948984Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation a6072815-7692-4eec-a497-718578bcd9b8 · outbound
This paper cites Q-learning based linear quadratic regulator with balanced exploration and exploitation for unknown systems,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Q-learning based linear quadratic regulator with balanced exploration and exploitation for unknown systems,
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.935455Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation edbeb926-a1e1-4187-a10b-f6b5bd61b11e · outbound
This paper cites Geomagnetic navigation with adaptive search space for AUV based on deep double-Q-network,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Geomagnetic navigation with adaptive search space for AUV based on deep double-Q-network,
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.921749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c56f9600-4a66-47c2-8923-583f8b1978a1 · outbound
This paper cites Long-distance Geomagnetic Navigation in GNSS-denied Environments with Deep Reinforcement Learning.
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 8caa6740-e625-47e9-896b-5b8715071095 · outbound
This paper cites Research on geomagnetic perceiving navigation method based on deep reinforcement learning,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Research on geomagnetic perceiving navigation method based on deep reinforcement learning,
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.907333Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7c6b2b9a-2d30-422d-97c5-2e60e1481739 · outbound
This paper cites Magnetic anomalies as a reference for ground-speed and map-matching navigation,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Magnetic anomalies as a reference for ground-speed and map-matching navigation,
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.893319Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 1cff0211-5e16-48d1-886b-3ec26d9aebb0 · outbound
This paper cites The magnetic poles of the earth,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation The magnetic poles of the earth,
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.878926Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation f2c59493-2ce0-4568-be64-641675621532 · outbound
This paper cites Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Multi-Goal Reinforcement Learning: Challenging Robotics Environments and Request for Research
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T20:26:15.606395Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation adc1d03b-fce2-4483-91a2-cfcca5d17c73 · outbound
This paper cites Addressing function approximation error in actor-critic methods,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Addressing function approximation error in actor-critic methods,
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.864518Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 72dcf5bd-c84d-4b68-b2d7-5b413ac94471 · outbound
This paper cites Deterministic policy gradient algorithms,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Deterministic policy gradient algorithms,
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.850582Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 90f98ce0-42c0-42ad-a300-3459ef9d2040 · outbound
This paper cites Policy Distillation.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Policy Distillation
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T20:26:15.619883Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ace44f2a-999a-4077-8b07-f07420176da6 · outbound
This paper cites Multi-agent reinforcement learning: An overview,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Multi-agent reinforcement learning: An overview,
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.836680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 0eb87ceb-d056-41a0-bc13-a907d22cdb48 · outbound
This paper cites Distilling the Knowledge in a Neural Network.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Distilling the Knowledge in a Neural Network
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T20:26:15.629082Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6fade149-0f0f-4633-bd77-30af63012c85 · outbound
This paper cites Magnetic sensitivity of cryptochrome 4 from a migratory songbird,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Magnetic sensitivity of cryptochrome 4 from a migratory songbird,
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.822839Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c3069829-ba06-4d0d-89cc-a5ddae46ff05 · outbound
This paper cites Coordinated formation guidance law for fixed-wing uavs based on missile parallel approach method,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Coordinated formation guidance law for fixed-wing uavs based on missile parallel approach method,
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.808496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 5dd2225a-b3ff-4e12-b9ba-b44a1c046d0b · outbound
This paper cites International geomagnetic reference field: The 12th generation,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation International geomagnetic reference field: The 12th generation,
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.793901Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation e8c07822-f904-4e51-a4a3-121cb7c02be2 · outbound
This paper cites Optuna: A next-generation hyperparameter optimization framework,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Optuna: A next-generation hyperparameter optimization framework,
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.780165Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 30df3a32-f6ee-4d54-9e91-00f08fd5e650 · outbound
This paper cites Particle swarm optimization,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Particle swarm optimization,
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.766433Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 19af61b4-d280-442d-a0ca-6dddd6341f3f · outbound
This paper cites Fuzzy adaptive artificial fish swarm algorithm,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Fuzzy adaptive artificial fish swarm algorithm,
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.752178Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 556f990d-c69b-461f-95bd-6d1d5084497e · outbound
This paper cites Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces,
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.736868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 29542d29-ab0b-4fd7-89bf-1504d4345e31 · outbound
This paper cites Adaptation in natural and artificial systems,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Adaptation in natural and artificial systems,
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.720770Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 7e195c00-d8d3-4b62-bc37-9b34f66aec2e · outbound
This paper cites A novel neural multi-store memory network for autonomous visual navigation in unknown environment,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation A novel neural multi-store memory network for autonomous visual navigation in unknown environment,
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.706515Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 4d76c77a-6e6d-4f7b-b30a-c103429c253e · outbound
This paper cites ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation ObjectNav Revisited: On Evaluation of Embodied Agents Navigating to Objects
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T20:26:15.674289Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 471cd4f8-1360-480a-8c8b-745e4e8cba2d · outbound
This paper cites A low-cost dead reckoning navigation system for an auv using a robust AHRS: Design and experimental analysis,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation A low-cost dead reckoning navigation system for an auv using a robust AHRS: Design and experimental analysis,
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.691754Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation 9331693b-7204-4c01-9733-64de84c12fdd · outbound
This paper cites IPAPRec: A promising tool for learning high-performance mapless navigation skills with deep reinforcement learning,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation IPAPRec: A promising tool for learning high-performance mapless navigation skills with deep reinforcement learning,
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.676014Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation d3a7e150-b0ca-44f1-ae9b-59d0b1811ef9 · outbound
This paper cites Towards deviation-robust agent navigation via perturbation-aware contrastive learning,.
Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation Towards deviation-robust agent navigation via perturbation-aware contrastive learning,
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-08T20:26:16.660902Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation fa0f2772-1501-4fe7-a3a6-ca66b8bed4db · outbound
This paper cites Hardware-in-the-loop Simulation Testbed for Geomagnetic Navigation.
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.
Pith citing papers
Observation 51ae698e-93ed-4eb0-80f4-4d95010daeab · inbound
Adaptive Fault-tolerant Control of Underwater Vehicles with Thruster Failures cites this paper.
Adaptive Fault-tolerant Control of Underwater Vehicles with Thruster Failures Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:17:43.824269Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c30ea80c-b8b8-4e83-b325-4a544380a756 · 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 Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T12:24:04.399680Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.