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Paper Citation Record · LEDGER

GNM: A General Navigation Model to Drive Any Robot

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 18 inbound Pith citation observations for arXiv:2210.03370.

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

pith.paper-citation-record.v1
2210.03370 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 18 of 18 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T00:13:32.859030Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T16:29:56.769376Z

Reference resolution

0 of 0 outbound references displayed

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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 6946913f-2507-4a7c-b321-7cc5175d31b1 · inbound

Dream to Fly: Model-Based Reinforcement Learning for Vision-Based Drone Flight cites this paper.

Dream to Fly: Model-Based Reinforcement Learning for Vision-Based Drone Flight GNM: A General Navigation Model to Drive Any Robot

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:55:25.153557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-23T04:53:33.503100Z digest=sha256:7f2a355b764e16e402c14ce3703d16fe15554608713ddc8144f8daf5482b37fb

Observation 3fb86e18-1eb8-43db-9832-d547ecaacde1 · inbound

Spatially-Enhanced Recurrent Memory for Long-Range Mapless Navigation via End-to-End Reinforcement Learning cites this paper.

Spatially-Enhanced Recurrent Memory for Long-Range Mapless Navigation via End-to-End Reinforcement Learning GNM: A General Navigation Model to Drive Any Robot

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T06:08:17.010941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T06:08:17.010941Z digest=sha256:dc558cc980070e61af4cd1d956cdc11fadb509da318eb9b93f589c9cc52d38ca

Observation 79f8712b-2090-4abe-96c7-b10ac9e603c1 · inbound

Narrate2Nav: Real-Time Visual Navigation with Implicit Language Reasoning in Human-Centric Environments cites this paper.

Narrate2Nav: Real-Time Visual Navigation with Implicit Language Reasoning in Human-Centric Environments GNM: A General Navigation Model to Drive Any Robot

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T00:25:04.966781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:25:04.966781Z digest=sha256:f55017c83c9b00ede4efffb0dcf3d63480e1f436087258afed3459764647b371

Observation 93bb0214-a7f1-4c3f-907d-51488a49780f · inbound

PixelNav: Towards Model-based Vision-Only Navigation with Topological Graphs cites this paper.

PixelNav: Towards Model-based Vision-Only Navigation with Topological Graphs GNM: A General Navigation Model to Drive Any Robot

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T13:14:26.099607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:14:26.099607Z digest=sha256:515dadbb9b0b5c82115cf6f9a7409f951e85ae1a4be15b7f3bb65a20e7d79bbf

Observation 0f48047a-018f-44b5-afa3-a5df9193dee3 · inbound

CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models cites this paper.

CAST: Counterfactual Labels Improve Instruction Following in Vision-Language-Action Models GNM: A General Navigation Model to Drive Any Robot

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-05T19:06:29.926483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:06:29.926483Z digest=sha256:2bf0edbc9d7a75c34bc84009125f1cf742453f1a4f2b7f2b8e6dba8de2320d23

Observation 38390953-4597-4713-af93-9be7c386ff01 · inbound

Approximate Imitation Learning for Event-based Quadrotor Flight in Cluttered Environments cites this paper.

Approximate Imitation Learning for Event-based Quadrotor Flight in Cluttered Environments GNM: A General Navigation Model to Drive Any Robot

Reference 36

Resolution
unresolved
no resolver link, observed 2026-07-15T13:10:42.531155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T13:10:42.531155Z digest=sha256:96a2684fabbf527eed94c53848f42dd9d511f422aacc96a5bb7e8729a2333d4c

Observation 3918b774-e376-4067-838e-fe7b425551ed · inbound

MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving cites this paper.

MVAdapt: Zero-Shot Multi-Vehicle Adaptation for End-to-End Autonomous Driving GNM: A General Navigation Model to Drive Any Robot

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:46:03.036980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-10T15:51:12.116796Z digest=sha256:bac31632dea949a4dcd56b1ff0ed4673592abc69ab1ec492218a2a4808af919f

Observation c1efbf6b-b8ec-4d3b-afc5-b722e2df160f · inbound

NavOL: Navigation Policy with Online Imitation Learning cites this paper.

NavOL: Navigation Policy with Online Imitation Learning GNM: A General Navigation Model to Drive Any Robot

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:52:21.935799Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-13T05:51:53.848800Z digest=sha256:d2f1c76bda05591bdad43f8d25aadee7e874c273baca2701248529cd189ae646

Observation ff52d562-1518-47db-a244-4c78b50e0eb6 · inbound

Improved Baselines with Representation Autoencoders cites this paper.

Improved Baselines with Representation Autoencoders GNM: A General Navigation Model to Drive Any Robot

Reference 44

Resolution
verified exact
arxiv_id, observed 2026-05-20T11:43:15.233938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-20T11:40:14.358108Z digest=sha256:3e6f03255ab18083d546e643733be13334c66bdffa5c91f6f538eee9d59dcfa4

Observation c41c103e-eb64-469e-8b4d-75219be27922 · inbound

AR Forcing: Towards Long-Horizon Robot Navigation World Model cites this paper.

AR Forcing: Towards Long-Horizon Robot Navigation World Model GNM: A General Navigation Model to Drive Any Robot

Reference 36

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T19:56:10.943070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-28T21:56:04.190024Z digest=sha256:5fb1d81bdc8ca16203c9b30737e74425d1d76c315e2f9f987f9d8ab339a7f9ac

Observation 601864a5-cea9-465f-8847-484db3f34d8e · inbound

Act on What You See: Unlocking Safe Social Navigation in Vision-Language-Action Models cites this paper.

Act on What You See: Unlocking Safe Social Navigation in Vision-Language-Action Models GNM: A General Navigation Model to Drive Any Robot

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-03T06:07:41.712520Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T12:52:38.764427Z digest=sha256:4df1eda41126430f2b9ae269a67cae2332dcf09e0d49af6dc4fa58a8874d1c05

Observation 41a8b311-8913-4958-b89a-0ea8f1785bbe · inbound

From Imitation to Alignment: Human-Preference Flow Policies for Long-Horizon Sidewalk Navigation cites this paper.

From Imitation to Alignment: Human-Preference Flow Policies for Long-Horizon Sidewalk Navigation GNM: A General Navigation Model to Drive Any Robot

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-07-03T11:38:04.657918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T09:29:43.030058Z digest=sha256:63512ab8fc5eca5a536d84857e8f9a8cdea5378e0f32fe68ab854dce7514a679

Observation 9b770fc6-b514-4f4a-9e3d-64f8792f14b0 · inbound

NavWAM: A Navigation World Action Model for Goal-Conditioned Visual Navigation cites this paper.

NavWAM: A Navigation World Action Model for Goal-Conditioned Visual Navigation GNM: A General Navigation Model to Drive Any Robot

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-03T15:28:34.024832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-27T06:30:17.719105Z digest=sha256:c375e66eb99dbfb1f5824a016ea99b4ca15e0e5df48301a49fdf4495f7d134a0

Observation 0726750a-445d-4678-97e3-ab0d0b518a3c · inbound

NavWM: A Unified Navigation World Model for Foresight-Driven Planning cites this paper.

NavWM: A Unified Navigation World Model for Foresight-Driven Planning GNM: A General Navigation Model to Drive Any Robot

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-04T16:29:56.770888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T00:42:30.237545Z digest=sha256:cb1a4128e19f02755250d3bb9d73f321308e4da24475c2109d0d38e1db2b6ca6

Observation 6cf8f4c2-5689-4552-b34b-2a617f956c31 · inbound

Learning to Navigate Efficiently with Only 0.58M Trainable Parameters cites this paper.

Learning to Navigate Efficiently with Only 0.58M Trainable Parameters GNM: A General Navigation Model to Drive Any Robot

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-14T07:33:00.386358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T07:33:00.386358Z digest=sha256:fb54545fa5b76d196332dd2dc186f171aaf60cce6cddec7fd0a7aac7956c7072

Observation 8c72f8d8-2785-4219-9a4e-44b20f1d53bd · inbound

Learning to Navigate Efficiently with Only 0.58M Trainable Parameters cites this paper.

Learning to Navigate Efficiently with Only 0.58M Trainable Parameters GNM: A General Navigation Model to Drive Any Robot

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-02T07:09:14.794966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:09:14.794966Z digest=sha256:99db0d098d8f948edd9d6f5594b4b2845e4bfe9bb919f98192c6a66b4efe8eec

Observation 2444674e-4326-4001-970d-f8978616653d · inbound

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills cites this paper.

Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills GNM: A General Navigation Model to Drive Any Robot

Reference 225

Resolution
unresolved
no resolver link, observed 2026-08-04T19:45:35.203645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:45:35.203645Z digest=sha256:308e21dc8eb0ccf63d628d6b229899a5c03832a87223e2db8d4c50fe4d4e2b76

Observation 73ea7ade-b87b-4cf4-9119-3bda59df104e · inbound

Latent World Models with Monotone Planning Costs for Image-Goal Navigation cites this paper.

Latent World Models with Monotone Planning Costs for Image-Goal Navigation GNM: A General Navigation Model to Drive Any Robot

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-12T00:13:32.859030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T00:13:32.859030Z digest=sha256:4cf7a6afa4e9431951162a8aab7bf35d82426f01afd3e0ee9f3326e3c08ede9d