Paper Citation Record · LEDGER

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

As of 21 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 32 inbound Pith citation observations for arXiv:2412.19505.

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

pith.paper-citation-record.v1
2412.19505 v2

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T00:21:49.227847Z

measured 84 of 84 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:54:07.752159Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:46:57.095080Z

Reference resolution

52 of 52 outbound references displayed

verified exact0
verified fuzzy23
unresolved28
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 992cf9e4-efa8-4255-b75c-ddaa1a364e19 · outbound

This paper cites Model-Based Offline Planning.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Model-Based Offline Planning

Reference 1

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Source-reported events for the cited work

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Observation 5ef92d33-62fc-40cb-ae00-cc8a1633112b · outbound

This paper cites Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:48.872608Z

Source-reported events for the cited work

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Observation 5e2d042e-35ff-48ed-9fbe-5effc3a6053a · outbound

This paper cites Language Models are Few-Shot Learners.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Language Models are Few-Shot Learners

Reference 3

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Source-reported events for the cited work

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Observation 7f6c6b40-c619-41ee-a230-40ab15309a8c · outbound

This paper cites nuscenes: A multi- modal dataset for autonomous driving.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT nuscenes: A multi- modal dataset for autonomous driving

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:50.294271Z

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Observation 56125511-3d54-4d01-a35c-ee61dcd8f350 · outbound

This paper cites NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT NuPlan: A closed-loop ML-based planning benchmark for autonomous vehicles

Reference 5

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Observation f84c48d1-dd00-426a-8600-923881c8408d · outbound

This paper cites UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT UMBRELLA: Uncertainty-Aware Model-Based Offline Reinforcement Learning Leveraging Planning

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:48.920295Z

Source-reported events for the cited work

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Observation 5b727d2d-5693-4a1d-b599-5065ae919f25 · outbound

This paper cites Uncertainty-aware model-based offline reinforcement learning for automated driving.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Uncertainty-aware model-based offline reinforcement learning for automated driving

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:50.272580Z

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Observation 60b72b98-76cb-4212-9fe7-4542f11bd8b8 · outbound

This paper cites Taming transformers for high-resolution image synthesis.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Taming transformers for high-resolution image synthesis

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:50.253430Z

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Observation 4347f416-1b71-4c11-ad51-97f1d229fca8 · outbound

This paper cites Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Reference 9

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Source-reported events for the cited work

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Observation 5b5eaa11-74a3-4209-a7a1-809a6a59c8fe · outbound

This paper cites World models for autonomous driving: An initial survey.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT World models for autonomous driving: An initial survey

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:50.235250Z

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Observation fb62c909-4854-4e03-9d28-c94ccdd7b717 · outbound

This paper cites Dream to Control: Learning Behaviors by Latent Imagination.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Dream to Control: Learning Behaviors by Latent Imagination

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:48.960535Z

Source-reported events for the cited work

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Observation 3b129139-b1e6-4793-8022-cd87baa51d96 · outbound

This paper cites Mastering Atari with Discrete World Models.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Mastering Atari with Discrete World Models

Reference 12

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Source-reported events for the cited work

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Observation 47cb3455-5fae-47df-87a5-c5cf99c30e47 · outbound

This paper cites Mastering Diverse Domains through World Models.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Mastering Diverse Domains through World Models

Reference 13

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Source-reported events for the cited work

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Observation 4f597b95-f6cd-4f37-a728-ac2544093686 · outbound

This paper cites Show me what and tell me how: Video synthesis via multimodal conditioning.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Show me what and tell me how: Video synthesis via multimodal conditioning

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:50.218513Z

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Observation af2682c2-60df-4882-a81e-e464c58594dc · outbound

This paper cites Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Model-Predictive Policy Learning with Uncertainty Regularization for Driving in Dense Traffic

Reference 15

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Source-reported events for the cited work

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Observation fdc8f408-ed22-440d-b429-40bccd627f93 · outbound

This paper cites Query-Key Normalization for Transformers.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Query-Key Normalization for Transformers

Reference 16

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Source-reported events for the cited work

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Observation f2f0a016-8d43-46a0-a247-a30dfe0ec8c8 · outbound

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

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT GAIA-1: A Generative World Model for Autonomous Driving

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:49.001732Z

Source-reported events for the cited work

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Observation 9c164218-d3bf-464f-8bd1-e5af50137c5b · outbound

This paper cites Image-to-image translation with conditional adversarial net- works.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Image-to-image translation with conditional adversarial net- works

Reference 18

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Source-reported events for the cited work

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Observation f3e2005e-9778-4319-a4de-7751335f7636 · outbound

This paper cites ADriver-I: A General World Model for Autonomous Driving.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT ADriver-I: A General World Model for Autonomous Driving

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T00:21:49.011945Z

Source-reported events for the cited work

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Observation 94589463-b9cc-4b15-a39d-b98587ee2f30 · outbound

This paper cites Drivegan: Towards a controllable high-quality neural simulation.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Drivegan: Towards a controllable high-quality neural simulation

Reference 20

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Observation 0dd486fe-edca-41be-b031-b7417d8a22e4 · outbound

This paper cites Adam: A method for stochastic optimization.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Adam: A method for stochastic optimization

Reference 21

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Observation eb052aa0-1ab7-44bb-8395-385fc26a2b3f · outbound

This paper cites The open im- ages dataset v4: Unified image classification, object detection, and visual relationship detection at scale.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT The open im- ages dataset v4: Unified image classification, object detection, and visual relationship detection at scale

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:50.151917Z

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Observation 0203f2ee-0557-4ca3-a464-a9e94489fbe7 · outbound

This paper cites Fast and accurate image super-resolution with deep laplacian pyramid networks.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Fast and accurate image super-resolution with deep laplacian pyramid networks

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:50.132811Z

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Observation e70f41e2-101b-4fa9-8ade-c5c4feecafbc · outbound

This paper cites A path towards autonomous machine intelli- gence version 0.9.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT A path towards autonomous machine intelli- gence version 0.9

Reference 24

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Observation d7f4f25e-64b5-42e8-8667-a858c733d8fc · outbound

This paper cites Microsoft coco: Common objects in context.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Microsoft coco: Common objects in context

Reference 25

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Observation b872b970-e03f-48ea-89c4-be0692140a87 · outbound

This paper cites Decoupled Weight Decay Regularization.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Decoupled Weight Decay Regularization

Reference 26

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Observation 97c13c3f-72e9-4ca0-aff5-7f3e74e8eb5c · outbound

This paper cites WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT WoVoGen: World Volume-aware Diffusion for Controllable Multi-camera Driving Scene Generation

Reference 27

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Observation f6acfe43-03fe-419f-8fc6-d8550ea53f1b · outbound

This paper cites Improving language understanding by genera- tive pre-training.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Improving language understanding by genera- tive pre-training

Reference 28

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Observation 245b9cb9-d6be-4a48-821e-3647adc481eb · outbound

This paper cites Language models are unsuper- vised multitask learners.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Language models are unsuper- vised multitask learners

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:50.057463Z

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Observation 0d410798-ec2a-4296-b5dd-a849c578c43a · outbound

This paper cites Learning a Driving Simulator.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Learning a Driving Simulator

Reference 30

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Observation 5813e40e-caf5-4355-9cf2-b440bdb9dbe5 · outbound

This paper cites Stylegan-v: A continuous video generator with the price, image quality and perks of stylegan2.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Stylegan-v: A continuous video generator with the price, image quality and perks of stylegan2

Reference 31

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Observation 2c9ee85b-d917-4ed7-b298-236e1382c618 · outbound

This paper cites Roformer: Enhanced transformer with rotary position embedding.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Roformer: Enhanced transformer with rotary position embedding

Reference 32

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Observation af69369a-118b-42f5-a1ee-7ba031ac8e4c · outbound

This paper cites Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation

Reference 33

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Observation 441621c2-8bf1-4738-869a-8cfc14e27081 · outbound

This paper cites Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction

Reference 34

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Observation 7392c75f-c6b8-447b-8ece-d7b0f381cfb1 · outbound

This paper cites A Good Image Generator Is What You Need for High-Resolution Video Synthesis.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT A Good Image Generator Is What You Need for High-Resolution Video Synthesis

Reference 35

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This paper cites Neural discrete representation learning.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Neural discrete representation learning

Reference 36

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Observation 05547562-d343-4383-9d3b-f677ca994290 · outbound

This paper cites DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving

Reference 37

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Observation 5fd2c5a9-005a-47dd-8634-0aa9cfbc59d6 · outbound

This paper cites Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Au- tonomous Driving.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Au- tonomous Driving

Reference 38

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Observation 82deb782-5ead-4184-aaed-f3c1598552e7 · outbound

This paper cites Driving into the future: Multiview visual forecasting and planning with world model for au- tonomous driving.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Driving into the future: Multiview visual forecasting and planning with world model for au- tonomous driving

Reference 39

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This paper cites Daydreamer: World models for physical robot learning.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Daydreamer: World models for physical robot learning

Reference 40

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Observation fa749b3e-ccb2-47aa-8860-449b51f9b65a · outbound

This paper cites VideoGPT: Video Generation using VQ-VAE and Transformers.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT VideoGPT: Video Generation using VQ-VAE and Transformers

Reference 41

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This paper cites Generalized Predictive Model for Autonomous Driving.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Generalized Predictive Model for Autonomous Driving

Reference 42

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This paper cites Vector-quantized Image Modeling with Improved VQGAN.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Vector-quantized Image Modeling with Improved VQGAN

Reference 43

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This paper cites Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks

Reference 44

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This paper cites Learning to drive by watching youtube videos: Action-conditioned contrastive policy pretraining.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Learning to drive by watching youtube videos: Action-conditioned contrastive policy pretraining

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:49.923303Z

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Observation 26c8db5e-159f-4ec0-9d42-a0b041bb72bc · outbound

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DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT The unreasonable effectiveness of deep features as a perceptual metric

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:49.905925Z

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This paper cites Movq: Modulating quantized vectors for high-fidelity image generation.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Movq: Modulating quantized vectors for high-fidelity image generation

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:49.888778Z

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This paper cites The authors believe that this work has small potential negative impacts.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT The authors believe that this work has small potential negative impacts

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:49.866768Z

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This paper cites Due to limited GPU memory, each image is restricted to a resolution of 256 × 512.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT Due to limited GPU memory, each image is restricted to a resolution of 256 × 512

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:49.844782Z

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Observation d4d847be-07b0-4687-90bb-977aef0c73ec · outbound

This paper cites This dataset is automatically annotated using a state-of-the-art offline perception system.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT This dataset is automatically annotated using a state-of-the-art offline perception system

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:49.825507Z

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DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT The images are with size of 256 × 512 and tokenized into 512 tokens

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T00:21:49.806904Z

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Observation 6f9985d5-488a-4f52-885a-7de8d1069b53 · outbound

This paper cites w/o AR” and “Ours.

DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT w/o AR” and “Ours

Reference 52

Resolution: malformed identifier; raw_fallback, observed 2026-08-11T00:21:49.784312Z

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Pith citing papers

Observation 9acad089-1f21-497d-9a75-b60439efa4ba · inbound

ARCON: Advancing Auto-Regressive Continuation for Driving Videos cites this paper.

ARCON: Advancing Auto-Regressive Continuation for Driving Videos DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T22:11:52.549073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f7ba31e-8639-496b-8631-e77f823c5b90 · inbound

DriveGPT: Scaling Autoregressive Behavior Models for Driving cites this paper.

DriveGPT: Scaling Autoregressive Behavior Models for Driving DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T12:18:48.098811Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4727ccc5-6884-4c1b-97e9-7ea6f12e52d5 · inbound

A Survey of World Models for Autonomous Driving cites this paper.

A Survey of World Models for Autonomous Driving DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-10T18:31:52.474058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0db9d819-b5bb-41d5-8218-c317dea44932 · 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 DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cd00c96b-81ea-4696-8e55-4298f1af5821 · inbound

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving cites this paper.

ARTEMIS: Autoregressive End-to-End Trajectory Planning with Mixture of Experts for Autonomous Driving DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T05:54:07.752159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3c39100-9998-42e8-96aa-a59ba53efb26 · inbound

PosePilot: Steering Camera Pose for Generative World Models with Self-supervised Depth cites this paper.

PosePilot: Steering Camera Pose for Generative World Models with Self-supervised Depth DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T04:18:26.096340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b78d4b06-e9f4-4de9-acbc-71041aa5bb28 · 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 DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T13:13:43.254703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82e4a2a7-0850-40ef-9200-49d35d6dd197 · inbound

Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Model cites this paper.

Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Model DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T05:03:12.935432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bb55e9a0-0669-4394-a68e-ee0fb00a8013 · inbound

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

Epona: Autoregressive Diffusion World Model for Autonomous Driving DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T21:29:49.144575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65b2649b-0e03-4020-8598-f513f30aee3d · inbound

Depth Anything at Any Condition cites this paper.

Depth Anything at Any Condition DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T20:52:02.480908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2409850-6265-41af-87aa-044ac4955e59 · 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 DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-06T18:32:54.718781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4fa05f2-f4f2-4f68-b7ba-c6ffff482753 · inbound

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

3D and 4D World Modeling: A Survey DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-05T06:04:15.535672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db6ed7d7-8fec-4f55-87cc-dcd438111853 · inbound

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

A Comprehensive Survey on World Models for Embodied AI DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 133

Resolution: unresolved; no resolver link, observed 2026-08-04T09:12:45.347912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4be31751-4d72-4bd0-8886-6c587a079584 · inbound

OmniNWM: Omniscient Driving Navigation World Models cites this paper.

OmniNWM: Omniscient Driving Navigation World Models DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-04T08:57:09.462192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d054fc5c-8512-4b6f-8410-dd03d7a4fa39 · inbound

Thinking Ahead: Foresight Intelligence in MLLMs and World Model cites this paper.

Thinking Ahead: Foresight Intelligence in MLLMs and World Model DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T20:41:57.783447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6e6cbc5b-8e79-4619-8c5a-1bd740c0b85f · inbound

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World cites this paper.

DriveLaW:Unifying Planning and Video Generation in a Latent Driving World DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fccf9409-c6f8-4df7-8646-f78bce711583 · inbound

Learning Vision-Language-Action World Models for Autonomous Driving cites this paper.

Learning Vision-Language-Action World Models for Autonomous Driving DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 88dd64db-3028-4efc-94c8-2045588a8501 · 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 DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 145

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1523f59a-96a8-4f5a-bc00-c1ea18730cce · 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 DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 23b6a125-2a6d-4deb-a730-0d96c104108d · inbound

CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving cites this paper.

CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 200f7029-45a7-4d53-903c-1e4a480634f1 · inbound

CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving cites this paper.

CoWorld-VLA: Thinking in a Multi-Expert World Model for Autonomous Driving DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 63fe9d34-9637-40c3-81c9-f3479298f508 · 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 DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 724b52d1-eaac-4d39-9e19-98173b2f592c · inbound

Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends cites this paper.

Towards Interactive Video World Modeling: Frontiers, Challenges, Benchmarks, and Future Trends DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 213

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation ef710abf-7490-4f43-9c2a-61978eb80f36 · inbound

Discrete-WAM: Unified Discrete Vision-Action Token Editing for World-Policy Learning cites this paper.

Discrete-WAM: Unified Discrete Vision-Action Token Editing for World-Policy Learning DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-08-18T01:13:47.485071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 68ca223f-0f8f-4af5-9abd-6e3415aa9a5d · inbound

UNIVERSE: Unified Video Action Models for Autonomous Driving with Flexible Mask-Modulated Modality Generation cites this paper.

UNIVERSE: Unified Video Action Models for Autonomous Driving with Flexible Mask-Modulated Modality Generation DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-11T08:19:04.131379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18800ef9-5faf-4b61-897d-cf4217d7db68 · inbound

OpenLongTail: Generative Scaling of Long-Tail Driving Data cites this paper.

OpenLongTail: Generative Scaling of Long-Tail Driving Data DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-13T01:26:27.220907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d925026-4feb-4bd7-a003-b0f70351c1f7 · inbound

Instant NuRec: Feed-Forward 3D Gaussian Reconstruction for Driving Scene Simulation cites this paper.

Instant NuRec: Feed-Forward 3D Gaussian Reconstruction for Driving Scene Simulation DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-02T02:55:46.103411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bd34162-89f3-46e2-a849-b45a45eed1cb · inbound

Orbis 2: A Hierarchical World Model for Driving cites this paper.

Orbis 2: A Hierarchical World Model for Driving DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-01T22:05:02.737118Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a95fcd14-a47f-445b-b5dc-410b0a3670d1 · inbound

Adaptive-WAM: Quality-Guided Early-Exit Planning from Intermediate Video-Diffusion Features cites this paper.

Adaptive-WAM: Quality-Guided Early-Exit Planning from Intermediate Video-Diffusion Features DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T18:25:51.323654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90a528d6-e066-47c5-a81c-0a10ad410c84 · inbound

CosmosAlign: Adapting a World Foundation Model for Generative Traffic Video Forecasting cites this paper.

CosmosAlign: Adapting a World Foundation Model for Generative Traffic Video Forecasting DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T00:28:52.210464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 848b8722-b994-4d37-80d0-8505559c48ed · inbound

How Can Driving World Models Do Counterfactual Prediction? cites this paper.

How Can Driving World Models Do Counterfactual Prediction? DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T00:40:58.427662Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 671d015b-a27f-4d65-9d33-36c446c29423 · inbound

PlayWorld: Benchmarking World Models with Agent Players over Long-Horizon Objectives cites this paper.

PlayWorld: Benchmarking World Models with Agent Players over Long-Horizon Objectives DrivingWorld: Constructing World Model for Autonomous Driving via Video GPT

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-14T04:23:02.078100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.