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Paper Citation Record · LEDGER

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations

As of 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 1 inbound Pith citation observation for arXiv:2603.00167.

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

pith.paper-citation-record.v1
2603.00167 v2

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:38:19.695526Z

measured 36 of 36 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-15T12:41:56.465485Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f818a9c1-33f5-49b7-bc4f-8e617521f9e0 · outbound

This paper cites A survey on socially aware robot navigation: Taxonomy and future challenges,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations A survey on socially aware robot navigation: Taxonomy and future challenges,

Reference 1

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Observation 6870b443-cb9c-4bb9-9115-b9c52e771281 · outbound

This paper cites Survey of maps of dynamics for mobile robots,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Survey of maps of dynamics for mobile robots,

Reference 2

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Observation 84ab9b90-bdc4-40d2-8742-e1f2ebc0c647 · outbound

This paper cites Enabling flow awareness for mobile robots in partially observable environments,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Enabling flow awareness for mobile robots in partially observable environments,

Reference 3

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Observation c674d2b7-da99-4e8f-9531-e8d96ba961b5 · outbound

This paper cites Spectral analysis for long-term robotic mapping,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Spectral analysis for long-term robotic mapping,

Reference 4

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Observation a0743a36-0be3-465a-a0db-f219e6174bc3 · outbound

This paper cites Robotic exploration for learning human motion patterns,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Robotic exploration for learning human motion patterns,

Reference 5

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Observation e85ab659-0887-475e-a06d-6ba5ae6d989d · outbound

This paper cites V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning

Reference 6

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Observation 8258bbd8-dba7-4572-ac5a-3b17b4609f3e · outbound

This paper cites Fremen: Frequency map enhancement for long-term mobile robot autonomy in changing environments,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Fremen: Frequency map enhancement for long-term mobile robot autonomy in changing environments,

Reference 7

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Observation bc459464-0a6b-42c8-8a12-8bd27a45cb24 · outbound

This paper cites Time- varying pedestrian flow models for service robots,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Time- varying pedestrian flow models for service robots,

Reference 8

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Observation e37667ac-c36d-4119-9489-e7eb04c16a82 · outbound

This paper cites Learning state-space models for mapping spatial motion patterns,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Learning state-space models for mapping spatial motion patterns,

Reference 9

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Observation 5e4bae23-7465-4c14-ad77-ec34328259fd · outbound

This paper cites Learning temporal maps of dynamics for mobile robots,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Learning temporal maps of dynamics for mobile robots,

Reference 10

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Observation 2a8ce995-2b43-41db-8dc8-ec4c85a84187 · outbound

This paper cites Neural implicit flow fields for spatio-temporal motion mapping,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Neural implicit flow fields for spatio-temporal motion mapping,

Reference 11

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Observation 74c37a51-6bcd-469c-9136-ba5d3a7acd90 · outbound

This paper cites Non-parametric modeling of spatio- temporal human activity based on mobile robot observations,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Non-parametric modeling of spatio- temporal human activity based on mobile robot observations,

Reference 12

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Observation cae27523-c47f-47ac-a3c5-d914db63831f · outbound

This paper cites Bayesian floor field: Transferring people flow predictions across environments,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Bayesian floor field: Transferring people flow predictions across environments,

Reference 13

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Observation e663998f-ab54-473b-b5d4-b682345217a3 · outbound

This paper cites Stef-lstm: A hybrid framework inte- grating periodic and sequential modeling for mapping motion patterns,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Stef-lstm: A hybrid framework inte- grating periodic and sequential modeling for mapping motion patterns,

Reference 14

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Observation f0aceb7d-39df-45d0-a141-352b3a23a72f · outbound

This paper cites Event-triggered maps of dynamics: A framework for modeling spatial motion patterns in non-stationary environments,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Event-triggered maps of dynamics: A framework for modeling spatial motion patterns in non-stationary environments,

Reference 15

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Observation 7fa56d56-c22b-4457-86f7-46e3c61fe3e7 · outbound

This paper cites Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Trajectron++: Dynamically-feasible trajectory forecasting with heterogeneous data,

Reference 16

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Observation 95d241ed-399f-4fab-8752-4d0b1c40967d · outbound

This paper cites Social lstm: Human trajectory prediction in crowded spaces,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Social lstm: Human trajectory prediction in crowded spaces,

Reference 17

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Observation 522953db-8d92-4e68-8536-30f36529cfd5 · outbound

This paper cites Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Agentformer: Agent-aware transformers for socio-temporal multi-agent forecasting,

Reference 18

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Observation 3fef04cf-d5e7-4280-aa13-7ecdb050427a · outbound

This paper cites Stochastic trajectory prediction via motion indeterminacy diffusion,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Stochastic trajectory prediction via motion indeterminacy diffusion,

Reference 19

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Observation fa6ac806-8a06-449a-915c-4125a3094351 · outbound

This paper cites Sicnav-diffusion: Safe and interactive crowd navigation with diffusion trajectory predictions,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Sicnav-diffusion: Safe and interactive crowd navigation with diffusion trajectory predictions,

Reference 20

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Observation e9988bad-0e5d-4344-a971-ca712e1c8898 · outbound

This paper cites Flowbot: Flow-based modeling for robot navigation,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Flowbot: Flow-based modeling for robot navigation,

Reference 21

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Observation 897174ec-ad2f-4ddc-b5e8-15e550f37828 · outbound

This paper cites Trajflow: Learning distributions over trajectories for human behavior prediction,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Trajflow: Learning distributions over trajectories for human behavior prediction,

Reference 22

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Observation dce456dd-4dc8-4988-889f-b952765f02ab · outbound

This paper cites Probabilistic dynamic crowd prediction for social navigation,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Probabilistic dynamic crowd prediction for social navigation,

Reference 23

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Observation 1295b459-56a7-44fc-adff-643e3e9cdb3b · outbound

This paper cites Long-term human motion prediction using spatio-temporal maps of dynamics,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Long-term human motion prediction using spatio-temporal maps of dynamics,

Reference 24

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Observation 147f1bb7-eb40-4654-a576-3a7c9ff87ea7 · outbound

This paper cites Leveraging maps of spatial motion patterns to enhance long-term adaptive trajectory prediction with diffusion models,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Leveraging maps of spatial motion patterns to enhance long-term adaptive trajectory prediction with diffusion models,

Reference 25

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Observation 8d8df7a3-3de1-48de-96f1-e59cbc1b05fd · outbound

This paper cites Allo-centric occupancy grid prediction for urban traffic scene using video prediction networks,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Allo-centric occupancy grid prediction for urban traffic scene using video prediction networks,

Reference 26

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Observation d5f2a107-0f5f-4655-a7b3-0514601f9edc · outbound

This paper cites Mapping high-level semantic regions in indoor environments without object recognition,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Mapping high-level semantic regions in indoor environments without object recognition,

Reference 27

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Observation 710438a7-60b0-4f1a-8ef8-d8b5df5dbad4 · outbound

This paper cites Monoc- ular semantic occupancy grid mapping with convolutional variational encoder–decoder networks,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Monoc- ular semantic occupancy grid mapping with convolutional variational encoder–decoder networks,

Reference 28

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Observation e8ea3a93-90df-4c55-a140-07d297e25f59 · outbound

This paper cites Predicting semantic map representations from images using pyramid occupancy networks,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Predicting semantic map representations from images using pyramid occupancy networks,

Reference 29

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Observation ab3b1386-e41a-4ed1-b0c1-dabd853a6eb6 · outbound

This paper cites Occupancy antic- ipation for efficient exploration and navigation,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Occupancy antic- ipation for efficient exploration and navigation,

Reference 30

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Observation f62ddb7a-3129-4441-98c4-8c8b859f32f1 · outbound

This paper cites Fiery: Future instance prediction in bird’s- eye view from surround monocular cameras,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Fiery: Future instance prediction in bird’s- eye view from surround monocular cameras,

Reference 31

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Observation 860aa3ea-d755-44aa-a5ea-b16dc47d926a · outbound

This paper cites Predicting occupancy distri- butions of walking humans with convolutional neural networks,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Predicting occupancy distri- butions of walking humans with convolutional neural networks,

Reference 32

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Observation dde907ec-87c9-4964-a384-685420170489 · outbound

This paper cites Person tracking in large public spaces using 3-d range sensors,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Person tracking in large public spaces using 3-d range sensors,

Reference 33

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Observation c797d237-1e97-4cc2-bb84-a7120179383c · outbound

This paper cites Towards safe navigation through crowded dynamic environments,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Towards safe navigation through crowded dynamic environments,

Reference 34

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Observation f77db051-1d12-498e-bb24-2f2645980f7d · outbound

This paper cites Ultralytics yolo11,.

EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations Ultralytics yolo11,

Reference 35

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Pith citing papers

Observation 23b201af-b4c9-42e9-860d-6048d89479c5 · inbound

Rheos: Modelling Continuous Motion Dynamics in Hierarchical 3D Scene Graphs cites this paper.

Rheos: Modelling Continuous Motion Dynamics in Hierarchical 3D Scene Graphs EgoMoD: Predicting Global Maps of Dynamics from Local Egocentric Observations

Reference 22

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