Paper Citation Record · LEDGER

Embodied Understanding of Driving Scenarios

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2403.04593.

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

pith.paper-citation-record.v1
2403.04593 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 2026-08-14T06:32:32.682623+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T18:39:43.097129Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T12:26:56.138674Z

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 91a02f30-8fb2-4ef1-888c-c3cd3b2ce3d2 · inbound

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? cites this paper.

MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans? Embodied Understanding of Driving Scenarios

Reference 74

Resolution: verified exact; arxiv_id, observed 2026-05-16T07:59:32.759804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 81f482de-c3e6-4b57-be06-bd30fade1252 · inbound

Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving cites this paper.

Senna: Bridging Large Vision-Language Models and End-to-End Autonomous Driving Embodied Understanding of Driving Scenarios

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-15T15:24:23.855906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9a9ab1b6-5bef-4bce-b434-6c2905a3fd84 · inbound

RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving cites this paper.

RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving Embodied Understanding of Driving Scenarios

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T18:39:43.097129Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a43f6623-837b-4426-bd67-702236fdcbc4 · inbound

WiseAD: Knowledge Augmented End-to-End Autonomous Driving with Vision-Language Model cites this paper.

WiseAD: Knowledge Augmented End-to-End Autonomous Driving with Vision-Language Model Embodied Understanding of Driving Scenarios

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-11T16:35:17.480171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49190fe8-dc57-4422-a760-567b59854cbd · inbound

LeapVAD: A Leap in Autonomous Driving via Cognitive Perception and Dual-Process Thinking cites this paper.

LeapVAD: A Leap in Autonomous Driving via Cognitive Perception and Dual-Process Thinking Embodied Understanding of Driving Scenarios

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-10T20:34:11.805443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 763ff7de-1dcb-4148-9394-60d3cd0bf5ec · inbound

Embodied Scene Understanding for Vision Language Models via MetaVQA cites this paper.

Embodied Scene Understanding for Vision Language Models via MetaVQA Embodied Understanding of Driving Scenarios

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T20:15:04.539684Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28c12e57-09b4-4b1a-b4bc-c2707a8a75df · inbound

TUMTraffic-VideoQA: A Benchmark for Unified Spatio-Temporal Video Understanding in Traffic Scenes cites this paper.

TUMTraffic-VideoQA: A Benchmark for Unified Spatio-Temporal Video Understanding in Traffic Scenes Embodied Understanding of Driving Scenarios

Reference 36

Resolution: malformed identifier; no resolver link, observed 2026-08-09T12:11:50.572804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 766bc41e-f67c-42a6-90ad-7b9ce6530a3b · inbound

AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning cites this paper.

AlphaDrive: Unleashing the Power of VLMs in Autonomous Driving via Reinforcement Learning and Reasoning Embodied Understanding of Driving Scenarios

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-16T20:06:27.269089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c4cdcc59-5205-4585-b33a-c833d043cbc0 · inbound

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models cites this paper.

Impromptu VLA: Open Weights and Open Data for Driving Vision-Language-Action Models Embodied Understanding of Driving Scenarios

Reference 88

Resolution: malformed identifier; no resolver link, observed 2026-08-07T12:43:58.997932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 929e8b15-b47d-4a78-b7e5-55c0e4912f40 · inbound

What's Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models cites this paper.

What's Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models Embodied Understanding of Driving Scenarios

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-02T12:26:56.145661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.