Paper Citation Record · LEDGER

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model

As of 19 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 7 inbound Pith citation observations for arXiv:2507.00603.

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

pith.paper-citation-record.v1
2507.00603 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:19:32.259571Z

measured 55 of 55 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:18:25.774194Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T07:41:15.133064Z

Reference resolution

48 of 48 outbound references displayed

verified exact1
verified fuzzy32
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eaa5fb24-5ed8-48a9-bf5f-1e51a0fa7e99 · outbound

This paper cites VaViM and VaVAM: Autonomous Driving through Video Generative Modeling.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model VaViM and VaVAM: Autonomous Driving through Video Generative Modeling

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:28.485169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74ee6551-9412-4f04-9125-82fb894a30ac · outbound

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

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model nuscenes: A multi- modal dataset for autonomous driving

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.456134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 68783d80-a1f9-4d0a-9f13-411aabfcee6a · outbound

This paper cites VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model VADv2: End-to-End Vectorized Autonomous Driving via Probabilistic Planning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:28.630401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bcc522b-9329-4391-82ab-5c63a4a46ec4 · outbound

This paper cites Ppad: Iterative interactions of prediction and planning for end-to-end autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Ppad: Iterative interactions of prediction and planning for end-to-end autonomous driving

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.331104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 264d854e-769e-4216-b3f1-451208352558 · outbound

This paper cites Openscene: The largest up-to- date 3d occupancy prediction benchmark in autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Openscene: The largest up-to- date 3d occupancy prediction benchmark in autonomous driving

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.231874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7a7430b1-a84f-4c71-8a4d-8924bde0988b · outbound

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

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:28.847600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites DOME: Taming Diffusion Model into High-Fidelity Controllable Occupancy World Model.

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

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb96ad21-bb1c-4452-899e-43f308da5477 · outbound

This paper cites Deep residual learning for image recognition.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Deep residual learning for image recognition

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:37.123963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fcf4db1d-31d4-4616-a7ea-7b0ebf66ea57 · outbound

This paper cites Denoising dif- fusion probabilistic models.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Denoising dif- fusion probabilistic models

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.992525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 13c980ee-1142-4a85-abbf-f07843dea237 · outbound

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

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model GAIA-1: A Generative World Model for Autonomous Driving

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:29.168385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17d354fa-5b82-4c15-a252-bd55ba34b179 · outbound

This paper cites Metric3d v2: A versatile monocular geomet- ric foundation model for zero-shot metric depth and surface normal estimation.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Metric3d v2: A versatile monocular geomet- ric foundation model for zero-shot metric depth and surface normal estimation

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.869266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 664e0aa8-7228-4829-b6fb-0fe5b637c82e · outbound

This paper cites St-p3: End-to-end vision-based au- tonomous driving via spatial-temporal feature learning.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model St-p3: End-to-end vision-based au- tonomous driving via spatial-temporal feature learning

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.765702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation bd7bcb25-a4ab-475a-bef3-822833a5900c · outbound

This paper cites Planning-oriented autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Planning-oriented autonomous driving

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.653677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fcd41b05-1cd8-4c5d-a182-1e32e33d1bca · outbound

This paper cites NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:29.501478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d1501d27-c461-4b6e-8f4a-91a4d422fcbb · outbound

This paper cites Drivetransformer: Unified transformer for scalable end-to- end autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Drivetransformer: Unified transformer for scalable end-to- end autonomous driving

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.528619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 49874fa3-e297-4d87-a191-1ce7a4f12f29 · outbound

This paper cites Vad: Vectorized scene representation for efficient autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Vad: Vectorized scene representation for efficient autonomous driving

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.373483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cb38460e-e258-448e-aa38-ae591708b525 · outbound

This paper cites Tod3cap: Towards 3d dense captioning in out- door scenes.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Tod3cap: Towards 3d dense captioning in out- door scenes

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.242987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c3023140-b71c-4257-9cf9-609842e5a61d · outbound

This paper cites Enhancing end-to-end au- tonomous driving with latent world model.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Enhancing end-to-end au- tonomous driving with latent world model

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:36.092425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 28b2a234-28c4-4704-8599-082f118ebb27 · outbound

This paper cites Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Hydra-MDP: End-to-end Multimodal Planning with Multi-target Hydra-Distillation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:29.947637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 990e4bee-8798-4ad1-8b09-0c60b67f1f1b · outbound

This paper cites Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Bevformer: learning bird’s-eye-view representation from lidar-camera via spatiotemporal transformers

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.912066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ac2e1a1c-f24f-4da5-92ad-730aa7f7acc7 · outbound

This paper cites Is ego status all you need for open- loop end-to-end autonomous driving? In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Is ego status all you need for open- loop end-to-end autonomous driving? In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.779898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d236a067-cfa1-41e8-99d6-0ce07717d53d · outbound

This paper cites MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model MapTR: Structured Modeling and Learning for Online Vectorized HD Map Construction

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:30.149583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca8ec8b8-6327-477e-b9f0-9745141ef45d · outbound

This paper cites Diffusiondrive: Trun- cated diffusion model for end-to-end autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Diffusiondrive: Trun- cated diffusion model for end-to-end autonomous driving

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.650618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 76534d3f-2bfd-4c15-b5aa-f7dac4250ec9 · outbound

This paper cites Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusion.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Sparse4D: Multi-view 3D Object Detection with Sparse Spatial-Temporal Fusion

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:30.259711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d195bb2a-8347-4b10-8281-9ed835417b9e · outbound

This paper cites Petr: Position embedding transformation for multi-view 3d object detection.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Petr: Position embedding transformation for multi-view 3d object detection

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.492270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2a5cb714-f320-4f94-98ba-e79b06a9255b · outbound

This paper cites Swin transformer: Hierarchical vision transformer using shifted windows.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Swin transformer: Hierarchical vision transformer using shifted windows

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.355100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9b909651-8fea-40b4-ae17-ce48b2ae8421 · outbound

This paper cites Lingoqa: Visual question answering for autonomous driv- ing.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Lingoqa: Visual question answering for autonomous driv- ing

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.203112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7e8df97c-4e79-49fd-904d-cf8a60102460 · outbound

This paper cites Driveworld: 4d pre-trained scene understanding via world models for autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Driveworld: 4d pre-trained scene understanding via world models for autonomous driving

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:35.023310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation df0e6bfc-023b-4598-b321-e56357d95d2a · outbound

This paper cites Vlp: Vision language planning for autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Vlp: Vision language planning for autonomous driving

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.859327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 47f24059-ce9a-4017-9994-a50d4b2fba34 · outbound

This paper cites Multi-modal fusion transformer for end-to-end autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Multi-modal fusion transformer for end-to-end autonomous driving

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.702738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c1f00341-6da6-49fc-83aa-d770a8d92902 · outbound

This paper cites Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:30.752490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd73dddc-0de6-49e2-bb4a-e2d7d8e3b70a · outbound

This paper cites Drivelm: Driving with graph visual question answering.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Drivelm: Driving with graph visual question answering

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.505505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 26ddc1ba-a5d9-43ea-9be1-873a8c795287 · outbound

This paper cites SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model SparseDrive: End-to-End Autonomous Driving via Sparse Scene Representation

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:30.874272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b3e99cc9-d179-489f-bba1-2a693627bbfe · outbound

This paper cites Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Tokenize the World into Object-level Knowledge to Address Long-tail Events in Autonomous Driving

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:30.946025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 711c9425-4f87-455c-ac2f-31d5525982a5 · outbound

This paper cites DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:31.032780Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97a3dfbb-e648-41b4-8c9b-f6b0057bca99 · outbound

This paper cites Scene as occupancy.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Scene as occupancy

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.352992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f165220a-96a0-4b45-9591-19ba24858a8a · outbound

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

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Drivedreamer: Towards real-world- drive world models for autonomous driving

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.177795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dc92a3fb-997c-48d5-ad4b-6b52b408ed8b · outbound

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

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Driving into the future: Multiview visual forecasting and planning with world model for au- tonomous driving

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:34.013476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 34f69d0e-47f3-4ba7-8bea-ae6d279c1fad · outbound

This paper cites Para-drive: Parallelized architecture for real- time autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Para-drive: Parallelized architecture for real- time autonomous driving

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:33.851837Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2d06c762-09a1-422d-ad14-62bd66fe4f96 · outbound

This paper cites Goalflow: Goal- driven flow matching for multimodal trajectories generation in end-to-end autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Goalflow: Goal- driven flow matching for multimodal trajectories generation in end-to-end autonomous driving

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:33.665806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 35669cf3-2d43-4330-841d-1f6e76883f22 · outbound

This paper cites Bevformer v2: Adapting modern image backbones to bird’s-eye-view recognition via perspective su- pervision.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Bevformer v2: Adapting modern image backbones to bird’s-eye-view recognition via perspective su- pervision

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:33.433842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 2a31b648-c68f-4137-baae-effdc302a7f1 · outbound

This paper cites Uncad: Towards safe end-to-end au- tonomous driving via online map uncertainty.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Uncad: Towards safe end-to-end au- tonomous driving via online map uncertainty

Reference 42

Resolution: verified exact; raw_fallback, observed 2026-08-06T21:19:32.558442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d1bdf9e9-930a-47f3-91ea-ebb57e5ca801 · outbound

This paper cites Metric3d: Towards zero-shot metric 3d prediction from a single image.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Metric3d: Towards zero-shot metric 3d prediction from a single image

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:33.252720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f07abe13-4478-45da-bd94-694769daa85e · outbound

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

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Copilot4d: Learning unsupervised world models for autonomous driving via discrete diffusion

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:33.108275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 36b5becb-0b33-49fc-acc1-b7f78f4ee496 · outbound

This paper cites DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:31.953866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd9c9df6-5671-45f1-9011-fa11786930dd · outbound

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

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Occworld: Learning a 3d occupancy world model for autonomous driving

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:32.961648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fa9dc8c2-17e4-4a8c-b72b-526e02cc11bf · outbound

This paper cites Genad: Generative end-to-end au- tonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Genad: Generative end-to-end au- tonomous driving

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T21:19:32.824617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7f4e1ff1-c050-4b85-b4dd-8e7de229baa0 · outbound

This paper cites Preliminary investigation into data scaling laws for imitation learning-based end-to-end autonomous driving.

World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model Preliminary investigation into data scaling laws for imitation learning-based end-to-end autonomous driving

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-06T21:19:32.259571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 85990901-eb2a-46ef-ae95-b0b67864392a · 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 World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T04:18:25.774194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bad7dc3-c9fd-4f6f-95c5-e457e6acf8c8 · inbound

OmniNWM: Omniscient Driving Navigation World Models cites this paper.

OmniNWM: Omniscient Driving Navigation World Models World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model

Reference 114

Resolution: unresolved; no resolver link, observed 2026-08-04T08:57:19.282237Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d74bd310-6264-4902-b8a1-542f03462abe · inbound

MultiWorld: Scalable Multi-Agent Multi-View Video World Models cites this paper.

MultiWorld: Scalable Multi-Agent Multi-View Video World Models World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model

Reference 72

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T10:09:08.267982Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fb12a3b3-edb1-4212-b1f5-8d1ba74e5a4e · inbound

HEAT: Heterogeneous End-to-End Autonomous Driving via Trajectory-Guided World Models cites this paper.

HEAT: Heterogeneous End-to-End Autonomous Driving via Trajectory-Guided World Models World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-20T04:58:05.378019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation fbd15da8-b747-470f-ab19-c2770d77a4d6 · inbound

LVDrive: Latent Visual Representation Enhanced Vision-Language-Action Autonomous Driving Model cites this paper.

LVDrive: Latent Visual Representation Enhanced Vision-Language-Action Autonomous Driving Model World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-22T07:41:15.136172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dafd4fd8-97c0-458b-bb51-2e0855007bc7 · inbound

Steins;Gate Drive: Semantic Safety Arbitration over Structured Futures for Latency-Decoupled LLM Planning cites this paper.

Steins;Gate Drive: Semantic Safety Arbitration over Structured Futures for Latency-Decoupled LLM Planning World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-22T05:41:08.304980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 494a20fd-e69d-45db-9f83-7cc66dacf5fa · inbound

Depth-Regularized JEPA World Models Learn More Transferable Representations from Real Outdoor Robot Data cites this paper.

Depth-Regularized JEPA World Models Learn More Transferable Representations from Real Outdoor Robot Data World4Drive: End-to-End Autonomous Driving via Intention-aware Physical Latent World Model

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T05:26:07.155612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.