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Paper Citation Record · LEDGER

DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2410.10429.

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

pith.paper-citation-record.v1
2410.10429 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:13:42.754803Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:29:29.474307Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9b125c01-8d02-4d49-a876-30b171bb7c18 · inbound

DriVerse: Navigation World Model for Driving Simulation via Multimodal Trajectory Prompting and Motion Alignment cites this paper.

DriVerse: Navigation World Model for Driving Simulation via Multimodal Trajectory Prompting and Motion Alignment DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 17

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verified exact
arxiv_id, observed 2026-05-22T17:51:54.724798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T17:50:59.797593Z digest=sha256:f1abf971c329c9c891e43b2824d627bb8a940bea36406adc8ad10ff7e812ae4f

Observation f49e13b1-88ab-43ef-a031-117538ab56b0 · inbound

GeoDrive: 3D Geometry-Informed Driving World Model with Precise Action Control cites this paper.

GeoDrive: 3D Geometry-Informed Driving World Model with Precise Action Control DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 15

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no resolver link, observed 2026-08-07T13:13:42.754803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:13:42.754803Z digest=sha256:67f302de812915cf5bab71b34dd6b729c5a1388bcc975ec20dc6beeebf9d745e

Observation 5026a570-a1fa-4589-98e4-01b1c8fd1085 · inbound

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model cites this paper.

COME: Adding Scene-Centric Forecasting Control to Occupancy World Model DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 4

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no resolver link, observed 2026-08-07T00:41:29.912088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:29.912088Z digest=sha256:217331e640a102a7b6b1d697a3b1215b1946a667b72b7a2618b5ca57b66d3424

Observation 6d2260a1-6b29-479b-a684-08871cc56c55 · inbound

Epona: Autoregressive Diffusion World Model for Autonomous Driving cites this paper.

Epona: Autoregressive Diffusion World Model for Autonomous Driving DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 18

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no resolver link, observed 2026-08-06T21:29:48.761264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:29:48.761264Z digest=sha256:4f837f677e1fb6f7a299211012eb7e469451a3f36608b5a36c2c97891102ea7c

Observation 7e9a3492-fd7b-4a7f-a38c-7bb133eceb70 · inbound

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model cites this paper.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 7

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unresolved
no resolver link, observed 2026-08-06T21:19:28.914725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:19:28.914725Z digest=sha256:d3507839275bd97181d75d09665c4d9903aa94413ebd768dfc6631723a68f52f

Observation 69d03620-ebd1-4159-ac54-d37d909ee7d4 · inbound

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models cites this paper.

A Survey: Learning Embodied Intelligence from Physical Simulators and World Models DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 297

Resolution
unresolved
no resolver link, observed 2026-08-06T21:09:19.089679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:09:19.089679Z digest=sha256:244c4bbec4a019aa42395020eca0ca3d0426a2368e9e69eafc8de8271d42e92a

Observation e7e61a31-cdb8-44f3-9958-9a1053b31b4c · inbound

MGVQ: Could VQ-VAE Beat VAE? A Generalizable Tokenizer with Multi-group Quantization cites this paper.

MGVQ: Could VQ-VAE Beat VAE? A Generalizable Tokenizer with Multi-group Quantization DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 14

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no resolver link, observed 2026-08-06T18:32:54.709837Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:32:54.709837Z digest=sha256:8beff7cb0a1897ecee1bdac208e2e8426821032720c1ecbb1fae93f5f4d27cc0

Observation 69b499b6-93b8-40fa-9686-373f74471843 · inbound

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting cites this paper.

$I^{2}$-World: Intra-Inter Tokenization for Efficient Dynamic 4D Scene Forecasting DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 11

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no resolver link, observed 2026-08-06T18:08:50.127134Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:08:50.127134Z digest=sha256:aa53bb515f060d82d5457ee05044defe6baef430c13b7cd74a8a557e39b065ed

Observation 6a874407-46ff-4eea-a746-df7bccddb128 · inbound

3D and 4D World Modeling: A Survey cites this paper.

3D and 4D World Modeling: A Survey DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 72

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unresolved
no resolver link, observed 2026-08-05T06:04:12.844748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T06:04:12.844748Z digest=sha256:3520709730273ed771a67bc9d6e0c208c5e74eb87a31c0266dc33f86be10f86a

Observation 30d83273-0ed2-49ce-85ed-275b34313bcd · inbound

A Comprehensive Survey on World Models for Embodied AI cites this paper.

A Comprehensive Survey on World Models for Embodied AI DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 94

Resolution
unresolved
no resolver link, observed 2026-08-04T09:12:40.271035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:12:40.271035Z digest=sha256:488391662a641195bb440c77462e2e968cf8d13994ff899ec9b426b31f7bcf32

Observation 11d51470-4ba8-4605-9fdf-a835fcfb213c · inbound

SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model cites this paper.

SparseWorld-TC: Trajectory-Conditioned Sparse Occupancy World Model DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-17T05:29:04.951833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 1c465e81-810c-4899-986d-5e4120239c27 · inbound

Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model cites this paper.

Lotus-2: Advancing Geometric Dense Prediction with Powerful Image Generative Model DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 9

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verified exact
arxiv_id, observed 2026-05-21T18:24:18.266073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T18:21:15.831853Z digest=sha256:793249bbe88541ea5ced2bad51f9ef8f5146f38e95e11009f4bec87acc5544ad

Observation 63bd158b-f5bb-48b6-b17d-6ba4a5e6ace1 · inbound

Rolling Sink: Bridging Limited-Horizon Training and Open-Ended Testing in Autoregressive Video Diffusion cites this paper.

Rolling Sink: Bridging Limited-Horizon Training and Open-Ended Testing in Autoregressive Video Diffusion DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 23

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arxiv_id, observed 2026-05-16T07:07:29.793888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 81de777f-6400-4b98-a7de-f3cb67211095 · inbound

Artificial Intelligence for Modeling and Simulation of Mixed Automated and Human Traffic cites this paper.

Artificial Intelligence for Modeling and Simulation of Mixed Automated and Human Traffic DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 149

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verified exact
arxiv_id, observed 2026-05-11T09:26:02.669057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T16:00:59.662003Z digest=sha256:0ac889f9fa69929f8399fe086d7df616e68c0b4ab19a286886595671781160cb

Observation ea56042e-b604-4f3b-b594-558797298bd8 · inbound

HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation cites this paper.

HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 40

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verified exact
arxiv_id, observed 2026-05-12T10:36:30.062034Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-07T05:31:59.676725Z digest=sha256:45aea5fdb3fe635810e01430db33c856d99fc3d3db4b8be4878fbac9fca5342f

Observation b09dd0b6-02ed-4288-9930-2346d706718b · inbound

GEM: Generating LiDAR World Model via Deformable Mamba cites this paper.

GEM: Generating LiDAR World Model via Deformable Mamba DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 9

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verified exact
arxiv_id, observed 2026-05-11T01:45:51.329343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T01:31:09.604703Z digest=sha256:bd9018044639b23be4aaab733836b559dadd5bb12277b767b04491aedcfcd3bf

Observation edaa927a-76d1-4f35-805f-dcde23ce8ea2 · inbound

GEM: Gaussian Evolution Model for Occupancy Forecasting and Motion Planning cites this paper.

GEM: Gaussian Evolution Model for Occupancy Forecasting and Motion Planning DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 36

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verified exact
arxiv_id, observed 2026-05-20T13:23:18.379452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T13:22:31.915829Z digest=sha256:c90836266430c85c69fa4a3fb92d8bedec757f2dcb4d440b2dc89bc1eb7f591f

Observation 0cf7e19e-c18e-4d58-a096-06b4910af891 · inbound

AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyond cites this paper.

AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyond DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 16

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arxiv_id, observed 2026-06-29T22:04:00.910208Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T21:15:12.465970Z digest=sha256:f395c50dcb1aa69a6d3276a2b54f2a2b934b1129be49e87ae24643a69a02a37b

Observation e6dfff39-892b-46c2-a6a9-223c2a24e304 · inbound

TPS-Drive: Task-Guided Representation Purification for VLM-based Autonomous Driving cites this paper.

TPS-Drive: Task-Guided Representation Purification for VLM-based Autonomous Driving DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 42

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verified exact
arxiv_id, observed 2026-06-29T17:43:45.765979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T17:42:49.902997Z digest=sha256:10f9506f326115325a719458a94adf6d494f7ca7987bd6192aac8390b620841f

Observation df861c6f-8cef-4160-9fca-25fe3fac6d72 · inbound

HilDA: Hierarchical Distillation with Diffusion for Advancing Self-Supervised LiDAR Pre-training cites this paper.

HilDA: Hierarchical Distillation with Diffusion for Advancing Self-Supervised LiDAR Pre-training DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 26

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metadata mismatch
arxiv_id, observed 2026-07-04T03:29:29.477514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T18:06:04.101217Z digest=sha256:8698752514c822e2367292d989c1d70b6c38d40077f82aca6797b89b6d94ead8

Observation ec0c1f05-2a6a-4602-96a2-28baf1734c59 · inbound

OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model cites this paper.

OWMDrive: Causality-Aware End-to-End Autonomous Driving via 4D Occupancy World Model DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:04:21.630838Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-30T05:59:20.898830Z digest=sha256:656a3f4b8459761fb3050f114a2b458f9f314e7f85a965441ecfa8eff80d8b81