Paper Citation Record · LEDGER

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving

As of 18 August 2026, this Paper Citation Record lists 74 of 74 outbound references and 5 inbound Pith citation observations for arXiv:2505.19239.

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

pith.paper-citation-record.v1
2505.19239 v1

Coverage vector

measured 74 of 74 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:22:57.947371Z

measured 79 of 79 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T06:04:36.055010Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T06:55:28.862159Z

Reference resolution

74 of 74 outbound references displayed

verified exact0
verified fuzzy57
unresolved17
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6e599bb7-2c25-497c-aef8-47e198d35df7 · outbound

This paper cites Uno: Unsupervised occupancy fields for perception and forecasting.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Uno: Unsupervised occupancy fields for perception and forecasting

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:59.081281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c6dba01b-842d-415b-90b2-fc248b0b60e7 · outbound

This paper cites Diffusion for world modeling: Visual details matter in atari.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Diffusion for world modeling: Visual details matter in atari

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:59.063747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 09e84b10-f960-43e5-85ec-ee4f1a22d396 · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving nuscenes: A multi- modal dataset for autonomous driving

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:59.045308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7ca46b1c-19e2-4073-a0cc-f5617f909a04 · outbound

This paper cites GameGen-X: Interactive Open-world Game Video Generation.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving GameGen-X: Interactive Open-world Game Video Generation

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.599410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4f61fa06-14f9-4633-bca0-6d5b7f766441 · outbound

This paper cites Videocrafter2: Overcoming data limitations for high-quality video diffusion models.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Videocrafter2: Overcoming data limitations for high-quality video diffusion models

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:59.020457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 815c60db-c8d6-43b9-affe-108c46ec0050 · outbound

This paper cites Transfuser: Imitation with transformer-based sensor fusion for autonomous driv- ing.TPAMI, 2022.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Transfuser: Imitation with transformer-based sensor fusion for autonomous driv- ing.TPAMI, 2022

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:59.006606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 58b4d4d6-557f-4aee-bc59-6e915ecaefb5 · outbound

This paper cites Openscene: The largest up-to- date 3d occupancy prediction benchmark in autonomous driving.https://github.com/OpenDriveLab/ OpenScene, 2023.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Openscene: The largest up-to- date 3d occupancy prediction benchmark in autonomous driving.https://github.com/OpenDriveLab/ OpenScene, 2023

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.990834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e3fb539e-3ac0-4cb3-a0ed-3190b431ff42 · outbound

This paper cites Navsim: Data-driven non- reactive autonomous vehicle simulation and benchmarking.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Navsim: Data-driven non- reactive autonomous vehicle simulation and benchmarking

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.974999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c810d635-8e2c-4a70-a988-8b6f4e2c7258 · outbound

This paper cites MagicDrive: Street View Generation with Diverse 3D Geometry Control.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving MagicDrive: Street View Generation with Diverse 3D Geometry Control

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.624818Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b927677-9bed-415b-a590-64b46c99d926 · outbound

This paper cites MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.630262Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a94cb5e6-eb89-4eaa-b3cb-d838f00b2855 · outbound

This paper cites Vista: A generalizable driving world model with high fidelity and versatile controllability.NeurIPS, 2024.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Vista: A generalizable driving world model with high fidelity and versatile controllability.NeurIPS, 2024

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.957877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 266ac965-fd2b-4175-afbf-62438b2b475e · outbound

This paper cites End-to-End Autonomous Driving without Costly Modularization and 3D Manual Annotation.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving End-to-End Autonomous Driving without Costly Modularization and 3D Manual Annotation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.639057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b98d6e86-bdf3-484b-bddf-41e19bc4f67d · outbound

This paper cites Recurrent world models facilitate policy evolution.NeurIPS, 2018.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Recurrent world models facilitate policy evolution.NeurIPS, 2018

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.943132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 334dd10b-453e-42c8-a593-4889bea6c4a5 · outbound

This paper cites Dream to control: Learning behaviors by la- tent imagination.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Dream to control: Learning behaviors by la- tent imagination

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.920956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 461652f9-c4b7-4d36-862a-d0c69d6a77ee · outbound

This paper cites Mastering atari with discrete world models.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Mastering atari with discrete world models

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.901699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation faa8da38-485e-49cd-a988-c7b2b7163d1e · outbound

This paper cites Mastering Diverse Domains through World Models.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Mastering Diverse Domains through World Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.659310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35deb4de-baf0-4646-baea-56b06e2f6096 · outbound

This paper cites Flexible diffusion modeling of long videos.NeurIPS, 2022.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Flexible diffusion modeling of long videos.NeurIPS, 2022

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.885711Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3f472685-0f51-4bab-a5de-66e67f6af587 · outbound

This paper cites Deep residual learning for image recognition.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Deep residual learning for image recognition

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.669955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f88bf5a-9563-4a68-a9f7-5e2d10f20b5b · outbound

This paper cites Denoising diffu- sion probabilistic models.NeurIPS, 33, 2020.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Denoising diffu- sion probabilistic models.NeurIPS, 33, 2020

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.863409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b9aa55d0-a7f3-4a81-aea5-662e5fd09e09 · outbound

This paper cites Cogvideo: Large-scale pretraining for text-to-video generation via transformers.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Cogvideo: Large-scale pretraining for text-to-video generation via transformers

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.848096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 75ede378-48e5-4a3d-b69a-de2ba4e1482e · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving GAIA-1: A Generative World Model for Autonomous Driving

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.683838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8aab71b3-b8ca-47c5-980a-89f2ffa40db8 · outbound

This paper cites Planning-oriented autonomous driving.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Planning-oriented autonomous driving

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.828505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation cbb54df8-42e4-4f02-ade6-981759a412a4 · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Vad: Vectorized scene representation for efficient autonomous driving

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.692406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b447e7ac-62ae-470b-abb1-2e32b09bd107 · outbound

This paper cites Text2video-zero: Text- to-image diffusion models are zero-shot video generators.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Text2video-zero: Text- to-image diffusion models are zero-shot video generators

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.802046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b8a76472-4365-468b-b11c-f79c89d029e1 · outbound

This paper cites Differentiable raycasting for self-supervised occupancy forecasting.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Differentiable raycasting for self-supervised occupancy forecasting

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.787443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8fb9536c-5f94-49aa-afe7-0bb730ef53d0 · outbound

This paper cites Point cloud forecasting as a proxy for 4d occupancy forecasting.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Point cloud forecasting as a proxy for 4d occupancy forecasting

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.772691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 230f0eac-3a19-4759-95f5-cb0c87ccd941 · outbound

This paper cites Pointpillars: Fast encoders for object detection from point clouds.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Pointpillars: Fast encoders for object detection from point clouds

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.759260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c2ed284f-3ce8-40dc-9f6d-022efaab62aa · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving A path towards autonomous machine intelli- gence version 0.9

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.742690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3eb29d22-b430-4219-bf90-d1a176e461ae · outbound

This paper cites T2v-turbo: Breaking the quality bottleneck of video consistency model with mixed reward feedback.NeurIPS, 2024.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving T2v-turbo: Breaking the quality bottleneck of video consistency model with mixed reward feedback.NeurIPS, 2024

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.727146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 31cd8a67-c007-41c2-aef6-ce01ed576adf · outbound

This paper cites Viewformer: Exploring spatiotem- poral modeling for multi-view 3d occupancy perception via view-guided transformers.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Viewformer: Exploring spatiotem- poral modeling for multi-view 3d occupancy perception via view-guided transformers

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.714929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dbcfe383-ca2d-437f-893f-879c5a654759 · outbound

This paper cites Navigation-guided sparse scene representation for end-to-end autonomous driving.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Navigation-guided sparse scene representation for end-to-end autonomous driving

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.700212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6efc5877-e20a-498b-adbc-739ac4975b58 · outbound

This paper cites Drivingdiffusion: Layout-guided multi-view driving scenarios video genera- tion with latent diffusion model.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Drivingdiffusion: Layout-guided multi-view driving scenarios video genera- tion with latent diffusion model

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.684039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d78e69a4-49b7-4b4b-9e43-552cba6800ea · outbound

This paper cites Semi-supervised vision-centric 3d occu- pancy world model for autonomous driving.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Semi-supervised vision-centric 3d occu- pancy world model for autonomous driving

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.666317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 88b41393-5af4-46ec-b19a-8be42a300c60 · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Enhancing end-to-end autonomous driving with latent world model

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.649398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e0d860f0-81a7-4a2a-80e1-5fff5e650cf4 · outbound

This paper cites Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Bevformer: Learning bird’s-eye-view representation from multi-camera images via spatiotemporal transformers

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.629249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5803ef61-52ca-4db3-9d30-3d4cc557b1c8 · outbound

This paper cites Fb-bev: Bev representa- tion from forward-backward view transformations.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Fb-bev: Bev representa- tion from forward-backward view transformations

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.608880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 37a1ef2b-6956-45a5-9fcc-fef53f371228 · outbound

This paper cites Is ego status all you need for open- loop end-to-end autonomous driving? InCVPR, 2024.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Is ego status all you need for open- loop end-to-end autonomous driving? InCVPR, 2024

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.588538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8ae24905-9dc3-4518-94be-db254ff16944 · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Diffusiondrive: Truncated diffusion model for end-to-end autonomous driving

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.572980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0ae61854-31d0-4e62-a4f5-cd06c2194655 · outbound

This paper cites Feature pyramid networks for object detection.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Feature pyramid networks for object detection

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.554218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5b5c994a-29c2-4957-9756-621557c66e89 · outbound

This paper cites Decoupled weight decay regularization.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Decoupled weight decay regularization

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.528300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 152c1b1c-e22f-4298-beb6-026fba953e70 · outbound

This paper cites Detzero: Rethinking offboard 3d object detection with long-term sequential point clouds.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Detzero: Rethinking offboard 3d object detection with long-term sequential point clouds

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.512892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 87d7f0ec-e4c6-46ef-bed2-f5f253232168 · outbound

This paper cites Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Self-supervised point cloud prediction using 3d spatio-temporal convolutional networks

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.497324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ab8cb483-47c2-412e-8474-57019a57a551 · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Driveworld: 4d pre-trained scene understanding via world models for au- tonomous driving

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.483466Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 96a8909c-1dfe-4542-8d5b-e78d8fd572b3 · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Driveworld: 4d pre-trained scene understanding via world models for autonomous driving

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.469263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 567ba7e8-9b69-41bd-b68b-db3a2c109ee9 · outbound

This paper cites Renderocc: Vision-centric 3d occupancy prediction with 2d rendering supervision.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Renderocc: Vision-centric 3d occupancy prediction with 2d rendering supervision

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.453627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 256b45ba-0897-4f89-8f8f-6f072ab9de5c · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Grounded SAM: Assembling Open-World Models for Diverse Visual Tasks

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.820138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f5b179f-b6b7-4872-be36-d317ef3f7469 · outbound

This paper cites Planning to explore via self-supervised world models.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Planning to explore via self-supervised world models

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.438483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e3441a3e-66cb-4336-9bd9-feb8517ab71f · outbound

This paper cites Pv- rcnn++: Point-voxel feature set abstraction with local vector representation for 3d object detection.IJCV, 2023.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Pv- rcnn++: Point-voxel feature set abstraction with local vector representation for 3d object detection.IJCV, 2023

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.425671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e688bc1c-dbad-4a3f-9d4e-bfc848d4c2cf · outbound

This paper cites Denois- ing diffusion implicit models.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Denois- ing diffusion implicit models

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.833077Z

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Observation 81999f72-498b-46c5-9db3-49db36681fc5 · outbound

This paper cites Diffusion Models Are Real-Time Game Engines.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Diffusion Models Are Real-Time Game Engines

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.837416Z

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Observation 327d2a96-e298-4f83-bc0b-fdbf0c773b89 · outbound

This paper cites Exploring object-centric temporal modeling 10 for efficient multi-view 3d object detection.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Exploring object-centric temporal modeling 10 for efficient multi-view 3d object detection

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.404499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 68410192-8cac-4b1d-b5ae-94365704251a · outbound

This paper cites OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving OmniDrive: A Holistic Vision-Language Dataset for Autonomous Driving with Counterfactual Reasoning

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.845826Z

Source-reported events for the cited work

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Observation f4d036b8-4f67-4989-bccb-1fd38df74c52 · outbound

This paper cites Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Internimage: Exploring large-scale vi- sion foundation models with deformable convolutions

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.390007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c4e852a4-b8a9-437d-94bc-3d0e9d853368 · outbound

This paper cites Videocomposer: Compositional video synthesis with motion controllability.NeurIPS, 2024.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Videocomposer: Compositional video synthesis with motion controllability.NeurIPS, 2024

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.374789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 84c62559-e05b-4dcd-9519-4f6bce168c3c · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Drivedreamer: Towards real-world- driven world models for autonomous driving

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.360807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 16079ace-524f-4f6e-8c6a-66b8567625cd · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Driving into the future: Multiview visual forecasting and planning with world model for au- tonomous driving

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.347616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 884e959c-3a1d-49b6-a02c-0988fb394689 · outbound

This paper cites Inverting the pose forecasting pipeline with spf2: Sequential pointcloud forecasting for se- quential pose forecasting.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Inverting the pose forecasting pipeline with spf2: Sequential pointcloud forecasting for se- quential pose forecasting

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.332224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e07a6774-400f-470b-ac29-61d4b41a35df · outbound

This paper cites S2net: Stochastic sequential pointcloud forecasting.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving S2net: Stochastic sequential pointcloud forecasting

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.318862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fba690ff-82a7-4dd5-a20a-c429040b1e1f · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Para-drive: Parallelized architecture for real- time autonomous driving

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.302192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 456b5048-f310-4028-a7e5-9062e2715e0e · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Daydreamer: World models for physical robot learning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.287844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 35e229ba-cf7a-4080-9635-259eedf7159a · outbound

This paper cites Pred: pre-training via semantic rendering on lidar point clouds.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Pred: pre-training via semantic rendering on lidar point clouds

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.272316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bb5e6966-97e2-437d-bc3f-e12c1de93352 · outbound

This paper cites Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Driving in the Occupancy World: Vision-Centric 4D Occupancy Forecasting and Planning via World Models for Autonomous Driving

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.892791Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55a99846-5466-43cd-ae92-85a547e2e8c2 · outbound

This paper cites Visual point cloud forecasting enables scalable autonomous driving.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Visual point cloud forecasting enables scalable autonomous driving

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.258356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 003b4631-908a-4b61-9897-c73c01e64182 · outbound

This paper cites Cogvideox: Text-to-video diffusion models with an expert transformer.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Cogvideox: Text-to-video diffusion models with an expert transformer

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.246343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f07e71aa-8f65-463e-ad4d-9a805c4af2a8 · outbound

This paper cites Cvt-occ: Cost volume temporal fusion for 3d occupancy prediction.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Cvt-occ: Cost volume temporal fusion for 3d occupancy prediction

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.231902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ee55c96f-ce6f-4a4d-9a5d-53c39340e399 · outbound

This paper cites Center- based 3d object detection and tracking.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Center- based 3d object detection and tracking

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.217636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d6d102ff-15cf-4244-b4b7-ec5a83f3ff8b · outbound

This paper cites Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Rethinking the Open-Loop Evaluation of End-to-End Autonomous Driving in nuScenes

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.915976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d6eb478-b4ab-402f-ba07-e119991949a9 · outbound

This paper cites OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environments.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving OccNeRF: Advancing 3D Occupancy Prediction in LiDAR-Free Environments

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.921287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2adf098f-657c-4448-b12d-6486d9fc888c · outbound

This paper cites A simple framework for open-vocabulary segmentation and detection.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving A simple framework for open-vocabulary segmentation and detection

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.925938Z

Source-reported events for the cited work

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Observation dfa246ca-61fd-4197-aa8e-57f162f6dccf · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Copilot4d: Learning unsupervised world models for autonomous driving via discrete diffusion

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.195845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a85a32a8-5869-4fb8-be41-65198a1a5098 · outbound

This paper cites Occformer: Dual-path transformer for vision-based 3d semantic occu- pancy prediction.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Occformer: Dual-path transformer for vision-based 3d semantic occu- pancy prediction

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.180415Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fa679fea-b9ec-42e7-8d7b-8c3e6cdaa13e · outbound

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

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Occworld: Learning a 3d occupancy world model for autonomous driving

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.164286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation eef18061-3149-42c0-91c5-71755eda4d01 · outbound

This paper cites HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and Generation.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving HERMES: A Unified Self-Driving World Model for Simultaneous 3D Scene Understanding and Generation

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T14:22:57.943453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fc4a6d9-9799-4a5f-8ef7-19bd16eff5b0 · outbound

This paper cites Deformable detr: Deformable transformers for end-to-end object detection.NeurIPS, 2020.

DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving Deformable detr: Deformable transformers for end-to-end object detection.NeurIPS, 2020

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:22:58.149332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 9aab4f91-7bff-4da4-ac98-3b5c18a20eb3 · inbound

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

3D and 4D World Modeling: A Survey DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving

Reference 203

Resolution: unresolved; no resolver link, observed 2026-08-05T06:04:36.055010Z

Source-reported events for the cited work

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Observation 86d329a4-ccaa-4059-884b-43b2cd821ff9 · inbound

OmniNWM: Omniscient Driving Navigation World Models cites this paper.

OmniNWM: Omniscient Driving Navigation World Models DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-04T08:57:13.282913Z

Source-reported events for the cited work

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Observation ffc09964-808c-4216-99b6-771d4181a9d6 · inbound

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

GEM: Generating LiDAR World Model via Deformable Mamba DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-11T01:45:51.299652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 51c2d954-f0ed-4b75-ad48-f4a46b64fcf4 · inbound

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving cites this paper.

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T06:54:21.303276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c52170c4-899c-48a5-8e19-396172c54a1d · inbound

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving cites this paper.

LWDrive: Layer-Wise World-Model-Guided Vision-Language Model Planning for Autonomous Driving DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T06:55:28.864273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.