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Paper Citation Record · LEDGER

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion

As of 27 July 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2606.18250.

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

pith.paper-citation-record.v1
2606.18250 v1

Coverage vector

measured 39 of 39 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-27T01:14:19.195054Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-27T06:30:09.085275+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

39 of 39 outbound references displayed

  • verified exact6
  • verified fuzzy0
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c5db684-8043-4783-920a-cef8d4086309 · outbound

This paper cites Cosmos World Foundation Model Platform for Physical AI.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Cosmos World Foundation Model Platform for Physical AI

Reference 1

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local_arxiv, observed 2026-07-03T20:38:55.745935Z

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Observation c07cf121-1c4a-42a8-8068-55d7b3522e2e · outbound

This paper cites Back to the Features: DINO as a Foundation for Video World Models.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Back to the Features: DINO as a Foundation for Video World Models

Reference 2

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arxiv_id, observed 2026-07-03T20:38:55.748766Z

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Observation bef8a9e7-e933-4d18-834b-74c7c6d754e0 · outbound

This paper cites Revisiting feature prediction for learning visual representations from video.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Revisiting feature prediction for learning visual representations from video

Reference 3

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Observation 26f5df37-fc4a-46d4-a9ae-2b2a6586164f · outbound

This paper cites A Pytorch Reproduction of Masked Generative Image Transformer.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion A Pytorch Reproduction of Masked Generative Image Transformer

Reference 4

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arxiv_id, observed 2026-07-03T20:38:55.743510Z

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:18d97adcdc34cf878ff493742096ed5a6bf80b51ecc6a049754fa093cdf36b8f

Observation 3c519dff-7c10-4afd-8a5a-fdfc50b2cd68 · outbound

This paper cites Vfmf: World modeling by forecasting vision foundation model features.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Vfmf: World modeling by forecasting vision foundation model features

Reference 5

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arxiv_id, observed 2026-07-03T20:38:55.756656Z

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Observation 416de8c2-1151-42df-84ec-6a60f095807e · outbound

This paper cites Video generation models as world simulators, 2024.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Video generation models as world simulators, 2024

Reference 6

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Observation 0abad7b3-5288-41fd-8d0e-a5bcfe76063f · outbound

This paper cites D., Edwards, A., Parker-Holder, J., Shi, Y., Hughes, E., Lai, M., Mavalankar, A., Steigerwald, R., Apps, C., et al.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion D., Edwards, A., Parker-Holder, J., Shi, Y., Hughes, E., Lai, M., Mavalankar, A., Steigerwald, R., Apps, C., et al

Reference 7

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:bb08187255ff6401e81568dd84f623e69d7a991c97fd58816e1712aefc60d396

Observation 5306fcb6-d06e-4bfe-918f-39413e76060f · outbound

This paper cites H., Vora, S., Liong, V.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion H., Vora, S., Liong, V

Reference 8

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:76316d48aa2ab9e7d75cfd92a61eec417230d53583c638fdda924eb17e419b74

Observation 2177f04f-464d-46d5-8c3e-2372038318f9 · outbound

This paper cites Wildrayzer: Self-supervised large view synthesis in dynamic environments.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Wildrayzer: Self-supervised large view synthesis in dynamic environments

Reference 9

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:ea64b9b0d915d04abbf5efb199d6e33e255e19d6e20c616ce344d3028d040913

Observation 991faff7-01e5-4d5c-a9c4-6da6e676c823 · outbound

This paper cites and LeCun, Y.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion and LeCun, Y

Reference 10

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:c8c7cbd47a1256e5c285b75e5663586c37fc501a4d25effc9eda6e5bbaf5f787

Observation 2685bb2d-de89-4997-904a-b475e4b42366 · outbound

This paper cites and Koltun, V.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion and Koltun, V

Reference 11

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Observation d8e226fe-9fa7-44fb-b253-f68ebec52986 · outbound

This paper cites Vista: A generalizable driving world model with high fidelity and versatile controllability.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Vista: A generalizable driving world model with high fidelity and versatile controllability

Reference 12

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:f2dbc64cddb46ef0e10414bebe4922b7fa269dc2535070a4bfcc66e53019ae17

Observation 0f52d059-8dfa-4366-baeb-839eaae80fa9 · outbound

This paper cites Vision meets robotics: The kitti dataset.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Vision meets robotics: The kitti dataset

Reference 13

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:fae70777a63cd29de419afb10912927978e68e3dd87aa2e2ca263c021a8fe8e5

Observation dd0ecdee-05f9-428a-b858-09f73cea26c2 · outbound

This paper cites Veo 3: A state-of-the-art video generation model.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Veo 3: A state-of-the-art video generation model

Reference 14

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:153d73bb25a7afcb319a81a61d3349ad8ec51e8799bb54b1ca4b955aade6b56a

Observation f20ddc69-49d9-4c79-abcd-52922b2ce3b0 · outbound

This paper cites Dist-4d: Disentangled spatiotemporal diffusion with metric depth for 4d driving scene generation.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Dist-4d: Disentangled spatiotemporal diffusion with metric depth for 4d driving scene generation

Reference 15

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:0d7f4182a69bca4f8cce235a2a7730cc09c6503b686d98ebcdf95d987c4cf959

Observation 475b87cc-2218-4308-bd76-30329c29d93e · outbound

This paper cites and Schmidhuber, J.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion and Schmidhuber, J

Reference 16

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:61fa38acc8fe2cc18b7207d9f8cdc5a467267d3ab9b547d1eb249b1082fc2ba9

Observation d979242f-227a-4c72-bdca-86f33196229b · outbound

This paper cites Mastering Diverse Domains through World Models.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Mastering Diverse Domains through World Models

Reference 17

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local_arxiv, observed 2026-07-03T20:38:55.751531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-27T06:30:09.085275+00:00.

source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:92cabd7358fdfbd05a6ccc643bd0504302325a1051e28042cf91ee24e0bed391

Observation ae428903-7d81-482d-b68f-a560db9448fb · outbound

This paper cites Probabilistic future prediction for video scene understanding.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Probabilistic future prediction for video scene understanding

Reference 18

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:e9004568d185051be99eccacf1c7e72196953e633292a400050656ada5a119d3

Observation 0f597568-daf1-4787-8cf9-56b723b63e6e · outbound

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

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Fiery: Future instance prediction in bird's-eye view from surround monocular cameras

Reference 19

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:a69cd3ee3a0ead9f599f9ec78cfca5d8a391212b88ec1a89ac0783b0854b2783

Observation 21d4b994-7a76-45f8-8cbe-3335cb0bed44 · outbound

This paper cites GAIA-1: A Generative World Model for Autonomous Driving.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion GAIA-1: A Generative World Model for Autonomous Driving

Reference 20

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local_arxiv, observed 2026-07-03T20:38:55.754327Z

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No event found in the named queried sources as of 2026-07-27T06:30:09.085275+00:00.

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Observation 7574a956-c986-400f-b149-9f3e133d2c7e · outbound

This paper cites Dino-foresight: Looking into the future with dino.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Dino-foresight: Looking into the future with dino

Reference 21

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Observation 34299df7-9554-4b22-b4c2-4f243e2608ab · outbound

This paper cites Advancing semantic future prediction through multimodal visual sequence transformers.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Advancing semantic future prediction through multimodal visual sequence transformers

Reference 22

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Observation cde9fe12-5f7d-465a-8495-c8ded6be9b7d · outbound

This paper cites u ller, N., Sch \.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion u ller, N., Sch \

Reference 23

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:a05d1cdffa003a3b046e85bebaff78200e51461311788ecce7e948d225309a39

Observation 8e9445b0-4dfa-4900-98cf-8634eed53cb7 · outbound

This paper cites A path towards autonomous machine intelligence, 2022.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion A path towards autonomous machine intelligence, 2022

Reference 24

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:afe2f6b00dbfea289fdac79bcf282c64ae78eb6a1a6f3e5e62c0c902a2719548

Observation 8b61b319-700c-447e-9eea-e052900f9917 · outbound

This paper cites Grounding image matching in 3d with mast3r.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Grounding image matching in 3d with mast3r

Reference 25

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:1a79c859f125681913966348b2bbe840b8eed6ea25ea6cf2844e56e5ec13aba9

Observation 853f3e0c-8cdd-40d0-bd2d-dfc78ccf4096 · outbound

This paper cites an unresolved cited work.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Unresolved cited work

Reference 26

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:43c09515344aa280cab6be85ae878506c8ba08c63e5194eb4cad0fd33679db2c

Observation cc6962ac-edfb-4115-a87a-d21f3351a269 · outbound

This paper cites an unresolved cited work.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Unresolved cited work

Reference 27

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Observation 85fb9e79-038e-4e33-bb63-848019d0fe87 · outbound

This paper cites L., Zheng, E., Pollefeys, M., and Frahm, J.-M.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion L., Zheng, E., Pollefeys, M., and Frahm, J.-M

Reference 28

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Observation 282d1674-b2e4-4be0-9b97-0e43fa46ba36 · outbound

This paper cites Scalability in perception for autonomous driving: Waymo open dataset.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Scalability in perception for autonomous driving: Waymo open dataset

Reference 29

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Observation bb8dc08a-88d7-4205-a12c-28c70930007b · outbound

This paper cites and Agapito, L.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion and Agapito, L

Reference 30

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Observation c9b70388-4866-4601-a988-4235afd2be34 · outbound

This paper cites Vggt: Visual geometry grounded transformer.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Vggt: Visual geometry grounded transformer

Reference 31

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Observation 0f672f7a-0720-4292-bc54-7050c4505ad3 · outbound

This paper cites A., and Kanazawa, A.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion A., and Kanazawa, A

Reference 32

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:ba6ad136faa5e7a80bbf2906cf61babe2716ec26fa629339be7fe8b3c321fa94

Observation 18291ffd-036d-4607-93d3-b387ddcf3211 · outbound

This paper cites Dust3r: Geometric 3d vision made easy.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Dust3r: Geometric 3d vision made easy

Reference 33

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:7322ea552e69b301352691ee70c9130aeb7f0e6c1b9c9680ce44cbeb8cea5aaa

Observation a3133b27-5a26-4a39-93d1-b46eb32cd76b · outbound

This paper cites DriveDreamer : Towards real-world-drive world models for autonomous driving.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion DriveDreamer : Towards real-world-drive world models for autonomous driving

Reference 34

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:d585a80d6160cfc79d99bf4e33215749236b7b2d4d78e4c45c4788f6e151732d

Observation c2409329-35ce-4e50-8d3a-7ecbf7a33d94 · outbound

This paper cites Spatialtracker: Tracking any 2d pixels in 3d space.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Spatialtracker: Tracking any 2d pixels in 3d space

Reference 35

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:7c6879dd8e398be1b8178aeee9554e32e25f5695f260b5c4a26641c66a212698

Observation 67351bb8-cb2a-4af4-b377-67b5efaf4e11 · outbound

This paper cites Driving in the occupancy world: Vision-centric 4d occupancy forecasting and planning via world models for autonomous driving.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Driving in the occupancy world: Vision-centric 4d occupancy forecasting and planning via world models for autonomous driving

Reference 36

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:38350eb4dd0215884b0d4e9621b3178db01b322c731eebfbeded3b50cb1da7b6

Observation b09c93b6-d6bd-421a-813c-4300ab4f0c0b · outbound

This paper cites Copilot4d: Learning unsupervised world models for autonomous driving via discrete diffusion.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Copilot4d: Learning unsupervised world models for autonomous driving via discrete diffusion

Reference 37

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:61251eb2ef7c2a854fdd38c53e68fd04d05b98a50ec815190114c161da7f6b37

Observation 2578fe41-402f-44fd-bda1-adde7e397d6b · outbound

This paper cites OccWorld : Learning a 3d occupancy world model for autonomous driving.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion OccWorld : Learning a 3d occupancy world model for autonomous driving

Reference 38

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no resolver link, observed 2026-06-27T01:14:19.195054Z

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:206b922fb12a72d1fe269baf5acd2bbc729d0ec8a7a8940557af2859099fc35a

Observation ee19cee6-6d38-405e-b9d2-605c3c2dc0cb · outbound

This paper cites Dino-wm: World models on pre-trained visual features enable zero-shot planning.

Future Dynamic 3D Reconstruction: A 3D World Model with Disentangled Ego-Motion Dino-wm: World models on pre-trained visual features enable zero-shot planning

Reference 39

Resolution
unresolved
no resolver link, observed 2026-06-27T01:14:19.195054Z

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source=arxiv_source observed=2026-06-27T01:14:19.195054Z digest=sha256:3c42c650ec62beb514626dc4acfa118a4d1f60e48eb2a3256999fd2cbcd04d99

Pith citing papers

No inbound Pith citation observations are available.