Paper Citation Record · LEDGER

UniWorld: Autonomous Driving Pre-training via World Models

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2308.07234.

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

pith.paper-citation-record.v1
2308.07234 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

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

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:31:52.710442Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:09:13.953642Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3f7ec0fa-6932-49b8-b470-3e3093c65919 · inbound

Physically Interpretable World Models via Weakly Supervised Representation Learning cites this paper.

Physically Interpretable World Models via Weakly Supervised Representation Learning UniWorld: Autonomous Driving Pre-training via World Models

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-23T07:02:41.378560Z

Source-reported events for the cited work

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

Observation c45350d6-7427-4468-837f-7f8668750473 · inbound

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

A Survey of World Models for Autonomous Driving UniWorld: Autonomous Driving Pre-training via World Models

Reference 148

Resolution: unresolved; no resolver link, observed 2026-08-10T18:31:52.710442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd17e3b0-11f6-4ea3-b8f8-922c02c07528 · inbound

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

3D and 4D World Modeling: A Survey UniWorld: Autonomous Driving Pre-training via World Models

Reference 170

Resolution: unresolved; no resolver link, observed 2026-08-05T06:04:29.024741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10a1318b-6404-44ce-bc94-b2f334d909ac · inbound

Foundation Models for Autonomous Driving Perception: A Survey Through Core Capabilities cites this paper.

Foundation Models for Autonomous Driving Perception: A Survey Through Core Capabilities UniWorld: Autonomous Driving Pre-training via World Models

Reference 107

Resolution: unresolved; no resolver link, observed 2026-08-04T20:52:06.597119Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5960807-99b1-4a6c-b1b6-e452f6a92fbf · inbound

AutoWorld: Learning Multi-Agent Traffic Simulation with Self-Supervised World Models cites this paper.

AutoWorld: Learning Multi-Agent Traffic Simulation with Self-Supervised World Models UniWorld: Autonomous Driving Pre-training via World Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T17:10:12.026783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c2795f1-93d4-41e7-bc4f-e765f2477d73 · inbound

ExploreVLA: Dense World Modeling and Exploration for End-to-End Autonomous Driving cites this paper.

ExploreVLA: Dense World Modeling and Exploration for End-to-End Autonomous Driving UniWorld: Autonomous Driving Pre-training via World Models

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:53:15.528633Z

Source-reported events for the cited work

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

Observation bc778fa4-99ab-4006-9a38-ddd4448ca28c · inbound

SparseWorld: Enhancing End-to-End Autonomous Driving via World Models with Sparse Scene Representation cites this paper.

SparseWorld: Enhancing End-to-End Autonomous Driving via World Models with Sparse Scene Representation UniWorld: Autonomous Driving Pre-training via World Models

Reference 27

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T14:14:45.841460Z

Source-reported events for the cited work

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

Observation f7572d0e-74e0-4ec1-8fb0-bc44e5c07bcb · inbound

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications cites this paper.

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications UniWorld: Autonomous Driving Pre-training via World Models

Reference 285

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:43:15.650981Z

Source-reported events for the cited work

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

Observation 655d7da8-27f4-4a8b-86df-7ec6a4df3591 · inbound

Taming I2V models for Image HOI Editing: A Cognitive Benchmark and Agentic Self-Correcting Framework cites this paper.

Taming I2V models for Image HOI Editing: A Cognitive Benchmark and Agentic Self-Correcting Framework UniWorld: Autonomous Driving Pre-training via World Models

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:09:13.957350Z

Source-reported events for the cited work

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

Observation db276bf3-a01a-4839-a03c-3a972a2ae897 · inbound

CRISP: A Spatiotemporal Camera-Radar Backbone for Driving via Forecasting-Based World-Model Pretraining cites this paper.

CRISP: A Spatiotemporal Camera-Radar Backbone for Driving via Forecasting-Based World-Model Pretraining UniWorld: Autonomous Driving Pre-training via World Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-11T17:41:06.399906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.