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Paper Citation Record · LEDGER

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos

As of 8 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 5 inbound Pith citation observations for arXiv:2505.18650.

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

pith.paper-citation-record.v1
2505.18650 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:31:32.112739Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

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

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:47:00.052139Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T06:31:01.231508Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact0
  • verified fuzzy18
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ff8ec79e-c646-4faf-979c-b329c95cdaec · outbound

This paper cites Lumiere: A Space-Time Diffusion Model for Video Generation.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Lumiere: A Space-Time Diffusion Model for Video Generation

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:27.636803Z digest=sha256:4c4dbe3a2e84c0901aced049bdf8552044a7e8263eedbb26165a5d9b94cb8a14

Observation 595c10fa-b923-4a7b-a05e-9ab37d1921e0 · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasets

Reference 2

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source=pdf_text observed=2026-08-07T14:31:27.731461Z digest=sha256:e0fa239a3283b95015ff2bfb392a5350a364b50bdc7b6ea7284a7cf406a77bc5

Observation b1cb5979-f30c-4366-958e-c6eee20ed85b · outbound

This paper cites Align your latents: High-resolution video synthesis with la- tent diffusion models.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Align your latents: High-resolution video synthesis with la- tent diffusion models

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:36.293562Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:27.818864Z digest=sha256:203928119eb6ce3625c1b5ffe4c52f64d1427b0a9bce9a5b46684720b8a0793d

Observation f291e126-7b66-4bd2-af4d-f53f0ab69881 · outbound

This paper cites Ge- nie: Generative interactive environments.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Ge- nie: Generative interactive environments

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-07T14:31:36.048631Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:27.928724Z digest=sha256:c5e4dd3e50276b0deb3618c883510d0e3e645f626fe13c0ec4c46445b0ba4c04

Observation 9b2f1c90-5f5d-4938-82fc-d9a26b6af05d · outbound

This paper cites Training sequence visualization.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Training sequence visualization

Reference 5

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raw_fallback, observed 2026-08-07T14:31:35.770076Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:28.032985Z digest=sha256:77bb10cc7d6da3dc606a7c74f9ed7129a4e87113c479d2323a9c47781ab99271

Observation afc40e1e-38e6-4110-8b3f-fcbc2a61c217 · outbound

This paper cites Carla: An open urban driv- ing simulator.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Carla: An open urban driv- ing simulator

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:35.556636Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:28.161630Z digest=sha256:316b859dd48f7c6f59de4ec306aa6a8df6f35c283f07132579f78d8c9d58e976

Observation ee68233b-2757-4186-a9e1-56c4c2c33876 · outbound

This paper cites Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:28.281391Z digest=sha256:d2a22454b35a518698c5bbdb82fb623402134e2fbd858b5420d413e2b6d916f0

Observation a6501d58-ff69-490f-a201-063f62befe34 · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Vista: A Generalizable Driving World Model with High Fidelity and Versatile Controllability

Reference 8

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source=pdf_text observed=2026-08-07T14:31:28.361091Z digest=sha256:321a1509dc811bccacbbb0a93ca3d2bcd8467b99fdb12f049cd24ba331d7f05f

Observation 88228d0e-3477-4199-b0c1-919ec931778b · outbound

This paper cites Recurrent world models facilitate policy evolution.NIPS, 31, 2018.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Recurrent world models facilitate policy evolution.NIPS, 31, 2018

Reference 9

Resolution
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raw_fallback, observed 2026-08-07T14:31:35.438726Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:28.504646Z digest=sha256:ee9a62cea365c2dbf30a294d2331db333ece8256043256958470f95ab14c541c

Observation b17a4f3b-aaa7-4159-b203-f5a249d9fc9f · outbound

This paper cites World Models.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos World Models

Reference 10

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source=pdf_text observed=2026-08-07T14:31:28.598644Z digest=sha256:979827e0fac2566f046dd19820cc397934b716a08f8cd18ed0b557e426e2fbae

Observation d57bfd1e-79b6-46d9-b430-3dc84dfaa1bb · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Dream to Control: Learning Behaviors by Latent Imagination

Reference 11

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source=pdf_text observed=2026-08-07T14:31:28.709586Z digest=sha256:e7615eefe700d3692cc5504cffd9c25f36fecfa267b438a11e215b329607867a

Observation 2750b81b-0c48-4d3d-a591-eac56eb836d3 · outbound

This paper cites Mastering Atari with Discrete World Models.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Mastering Atari with Discrete World Models

Reference 12

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:28.844099Z digest=sha256:260fb1b9d6c3c246cbfa3f5d0ee7d80d9c6b4ffc11c565bc98085991241b7d3d

Observation 7fb3b985-1ab7-4181-9cd8-2099ea8c77d5 · outbound

This paper cites Mastering Diverse Domains through World Models.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Mastering Diverse Domains through World Models

Reference 13

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:31:28.933557Z digest=sha256:a4b1b8e903e6981ddf2d089732b8f9d6d35ca507895de0d8d08b99d57f33bbed

Observation da58873e-0253-4ecd-8333-c22e084f68e1 · outbound

This paper cites The prediction results from different low-level control actions.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos The prediction results from different low-level control actions

Reference 14

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raw_fallback, observed 2026-08-07T14:31:35.319817Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:29.023177Z digest=sha256:bb9d64d3715a9e9eeb63f2f2ce4911192191d3ed023907de8096a993d5460d7e

Observation bf87d30a-c5f9-4b2d-8cb2-addf54b105c6 · outbound

This paper cites Denoising diffu- sion probabilistic models.NIPS, 33:6840–6851, 2020.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Denoising diffu- sion probabilistic models.NIPS, 33:6840–6851, 2020

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:35.176142Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:29.147275Z digest=sha256:93c4693e60f4438220886687a1bdd692612db4f990eafb22d4ac9554390e80eb

Observation eaea6781-c006-4778-b324-b67a80728f98 · outbound

This paper cites Model-based imitation learning for urban driving.NIPS, 35:20703–20716, 2022.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Model-based imitation learning for urban driving.NIPS, 35:20703–20716, 2022

Reference 16

Resolution
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raw_fallback, observed 2026-08-07T14:31:35.061672Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:29.236966Z digest=sha256:b29f5d0f8ccfabf23d857c641e5b2af0785b58d7aa5820b861f7959870cbc92a

Observation 8e8b9fb7-c703-442f-8b06-47225aad1d61 · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos GAIA-1: A Generative World Model for Autonomous Driving

Reference 17

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source=pdf_text observed=2026-08-07T14:31:29.353475Z digest=sha256:248dfb2c466e5e41b02bd9119f7a3de0ecc8ef86d4a2b973cec6af880e42a6a2

Observation fb12fabc-62be-4408-9d9a-775a072f9176 · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos ADriver-I: A General World Model for Autonomous Driving

Reference 18

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source=pdf_text observed=2026-08-07T14:31:29.483235Z digest=sha256:f91d6ac26e0d100413ca460d9ba5a4ff263bf7101e3ef5fa1a4e4d8b89278f31

Observation d989e58a-1399-4977-9c87-6193fbb84803 · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Drivegan: Towards a controllable high-quality neural simulation

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:34.940330Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:29.565638Z digest=sha256:d6c77a82903959831b85211d9c5ffb1d08f760d948fc69e7dd39e063aa6158f7

Observation 087b60be-5bed-4cbf-a627-fb659b04780c · outbound

This paper cites VideoPoet: A Large Language Model for Zero-Shot Video Generation.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos VideoPoet: A Large Language Model for Zero-Shot Video Generation

Reference 20

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:31:29.713433Z digest=sha256:f2bf29da36cd3aa4b6d700b951de5f75c264a21cd415337d57ab3e0e13468268

Observation 556d7ddb-42c7-40b7-adfe-b2899e168558 · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos A path towards autonomous machine intelli- gence version 0.9

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:34.811873Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:29.836070Z digest=sha256:1dc736b1b6de847e0c8cdf71bc134799e41c916efa3aaa82578471904c28c3cf

Observation 13b9d563-4728-4671-9fc4-c481f10cafad · outbound

This paper cites DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos DrivingDiffusion: Layout-Guided multi-view driving scene video generation with latent diffusion model

Reference 22

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source=pdf_text observed=2026-08-07T14:31:29.939418Z digest=sha256:450fc68350a98f03fa09497ad614a8081333b7c211e39fa2cc3c67a7515707e0

Observation c3f29ed5-9f45-4641-99c7-76420f52ef65 · outbound

This paper cites Learning to model the world with language.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Learning to model the world with language

Reference 23

Resolution
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raw_fallback, observed 2026-08-07T14:31:34.654359Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:30.042717Z digest=sha256:bf47c1ba4cec342ee5e2339411bcbbb0c97a872c7a8c4c612a66f8072b6b10d8

Observation 63cf608a-af9f-4d6d-949c-310b5852c5f1 · outbound

This paper cites Learning to model the world with language.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Learning to model the world with language

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:34.536232Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:30.157804Z digest=sha256:bb880b4cc8716b91090dd880a8ea31b855804e2f581a5d466561e91402584e1b

Observation 057d6e09-d41d-4787-b7c5-f1389e6f676c · outbound

This paper cites Sora technical report.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Sora technical report

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:34.396313Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:30.283781Z digest=sha256:89d44e2535250d8d2f940634c49e3ea847497a27b1b3da632dad52078cef6299

Observation b39b2c4c-8420-4344-bfce-08ecfb75d86d · outbound

This paper cites ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos ConsistI2V: Enhancing Visual Consistency for Image-to-Video Generation

Reference 26

Resolution
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no resolver link, observed 2026-08-07T14:31:30.407849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:30.407849Z digest=sha256:b46ee5ba9f863799dd4efa0fafc10aed86223ed04407332eab25874ccae82ae0

Observation 282b65bb-b120-402a-b625-7d4d856c1b08 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos High-resolution image syn- thesis with latent diffusion models

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:34.223660Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:30.517402Z digest=sha256:6e6b8ba131b3ae59da5b44629ac4c41e09a71ed4778bf9b0c3f8395aaf2ebf0d

Observation 5ee87003-764e-47b7-ada1-de356248678d · outbound

This paper cites The optimal control of partially observable markov processes over a finite horizon.Operations research, 21(5):1071–1088, 1973.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos The optimal control of partially observable markov processes over a finite horizon.Operations research, 21(5):1071–1088, 1973

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:34.061140Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:30.643517Z digest=sha256:217f3cb91d88068a3cb5cfa9a186c1dda97bcb1acc632ca5fbe024d4dc827aca

Observation bcb686dd-6cdb-4121-9264-0038adfb985a · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Scalability in perception for autonomous driving: Waymo open dataset

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:33.886567Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:30.768370Z digest=sha256:10138ba8ad6d628fc4c0e83b77cb8cfab15ee1881f5da9c7aa631b966a7ffa97

Observation 600fe287-358e-4acc-8640-28b23aa8ec7b · outbound

This paper cites DeepMind Control Suite.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos DeepMind Control Suite

Reference 30

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:30.854731Z digest=sha256:211a34dc510c333a97a7f6d099902643d033a1bdbe5120c2bc1a8b8e699d0277

Observation e2a8cc88-d8a1-4c8d-b245-3b0af3bd0ec9 · outbound

This paper cites Towards Accurate Generative Models of Video: A New Metric & Challenges.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Towards Accurate Generative Models of Video: A New Metric & Challenges

Reference 31

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:31:30.968359Z digest=sha256:3181e06c3a94f39e2b53e16f54ae5d7fd10531b0a851248a231525ae1c1a3894

Observation 72783f9d-54a3-4aa8-bf65-9b1eacc1b508 · outbound

This paper cites MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos MagicVideo-V2: Multi-Stage High-Aesthetic Video Generation

Reference 32

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no resolver link, observed 2026-08-07T14:31:31.070285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:31.070285Z digest=sha256:d3e40d0e6dc57068cb04cdb165da22094041dbec70148a1ef419c9b1ca6c8f51

Observation b13e568a-6c3f-4813-804c-495f1e864233 · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving

Reference 33

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unresolved
no resolver link, observed 2026-08-07T14:31:31.195661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:31.195661Z digest=sha256:431b42d149df1f7cbcc3ad3cf40cb735cfc8fb775843b12cf023189ad66a2ad9

Observation a403d5d3-3523-41dc-97ee-a0e3898b796d · outbound

This paper cites WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens

Reference 34

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no resolver link, observed 2026-08-07T14:31:31.307028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:31.307028Z digest=sha256:4e90a0217caa29719d7f63d07c7827afc3ba8d2fab67f72c7c0d754f69aba657

Observation 1c101253-eb39-4a4f-b381-4443ca5cda83 · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Driving into the Future: Multiview Visual Forecasting and Planning with World Model for Autonomous Driving

Reference 35

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no resolver link, observed 2026-08-07T14:31:31.414215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:31.414215Z digest=sha256:53abde7747cb35bcfcb0d2d0324833598253ba1158b4adb9c6831dab8e76403b

Observation f88d4af6-57ee-463d-901d-b56a72e66d4b · outbound

This paper cites Panacea: Panoramic and Controllable Video Generation for Autonomous Driving.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Panacea: Panoramic and Controllable Video Generation for Autonomous Driving

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:31.506449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:31.506449Z digest=sha256:06243c43c23f08a2b3e49ca5e1e9b611b5652d41f97440f8e177a1e34f43c5cc

Observation bfda184d-2893-4254-8eb8-52e9373e0b90 · outbound

This paper cites an unresolved cited work.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-07T14:31:33.693050Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:31.596665Z digest=sha256:f9938b53d88ef1815ade3b20e0e9b4856f3f13aea04c29ea2b731834c5a5af8c

Observation eb6e2854-ea9c-451b-a6b2-b3f1898ee0d4 · outbound

This paper cites Generalized predictive model for autonomous driving.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Generalized predictive model for autonomous driving

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:33.537750Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:31.668692Z digest=sha256:6d3c50aa6f8efc8e0814da72dbc682b1b24e6b4d1e5c454f750bbde16f88b539

Observation 4b1b0b94-42de-46c7-af5d-88b03c1ce5f2 · outbound

This paper cites CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer

Reference 39

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unresolved
no resolver link, observed 2026-08-07T14:31:31.762639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:31.762639Z digest=sha256:5009525b74c3e0d978136add239743d470dac8f955908b4d45d1b880a564f8f9

Observation 9c532645-42f0-4310-bdaf-01193c0cffda · outbound

This paper cites NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos NUWA-XL: Diffusion over Diffusion for eXtremely Long Video Generation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:31.859867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:31.859867Z digest=sha256:f133576395c257e09cc5d98fe4b57b3c6cd7f4d9118b4f42888aba88a82b0c4a

Observation 580b6a68-9815-4458-9a55-c87326dc69d9 · outbound

This paper cites MagicTime: Time-lapse Video Generation Models as Metamorphic Simulators.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos MagicTime: Time-lapse Video Generation Models as Metamorphic Simulators

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:31.955804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:31.955804Z digest=sha256:7a7e399b8c02bbf93092c91a40d1cc03c792c84c8f55dbfeac4cc77c9eddccc7

Observation 184f5428-957a-4bc2-8a4b-965dec18d78b · outbound

This paper cites Llava- next: A strong zero-shot video understanding model, 2024.

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos Llava- next: A strong zero-shot video understanding model, 2024

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:31:33.294676Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-07T14:31:32.062676Z digest=sha256:b9ead567c9026116be726d428a859b2bd1b661efe557a297669e3e1b95bf5c10

Observation a2b76419-530c-4dbf-9aad-08a1a6726ab5 · outbound

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

ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos DriveDreamer-2: LLM-Enhanced World Models for Diverse Driving Video Generation

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T14:31:32.112739Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:31:32.112739Z digest=sha256:6ff4bfb51e5ad89caf9f8f694ab344105af2cb53fa0af0226a89139291fe3889

Pith citing papers

Observation ef6585e4-e1d8-421c-99ff-842c66a39ef9 · inbound

LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model cites this paper.

LongDWM: Cross-Granularity Distillation for Building a Long-Term Driving World Model ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T11:47:00.052139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:47:00.052139Z digest=sha256:e4a277babc04ac09e2c00a0d0f8b7474bdfa7f8ae6502f22cbec038152afcd85

Observation 9dad5e03-0889-41ef-8672-4ce4ecff1b73 · inbound

WorldLens: Full-Spectrum Evaluations of Driving World Models in Real World cites this paper.

WorldLens: Full-Spectrum Evaluations of Driving World Models in Real World ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos

Reference 103

Resolution
unresolved
no resolver link, observed 2026-08-03T17:02:40.380078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T17:02:40.380078Z digest=sha256:01c72b45954b3e2f94ed6298550acee91e83accfff817efb4477f3e441868f84

Observation 0d6055eb-a7c1-4f8e-9bfe-a2094f63188b · inbound

LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving cites this paper.

LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:31:01.234667Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-10T17:36:38.627415Z digest=sha256:4cd1069b4080fe3148e3d66c097fa4d9c7ae14c05cf3f2c4a8d4239f3d526026

Observation 27eac14a-1150-47a6-b3b3-1907e13d1ac2 · inbound

ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation cites this paper.

ScenarioControl: Vision-Language Controllable Vectorized Latent Scenario Generation ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-10T06:26:27.488305Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-10T06:23:22.058330Z digest=sha256:d95dc6c6fdafea318054f87c0f26c0d2750ce3341a6d9f9154f20bb9b1098ec8

Observation cd9f61eb-a9c5-4a07-a724-9993149039d9 · 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 ProphetDWM: A Driving World Model for Rolling Out Future Actions and Videos

Reference 18

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T08:19:04.131379Z digest=sha256:d7c949acab7631ce8bdfd2e07a3007aaf95748a1271bf601656ee41cf97035c5