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Paper Citation Record · LEDGER

Embodied Understanding of Driving Scenarios

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 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 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:06:43.313538Z

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T07:59:32.638758Z digest=sha256:6ddf02400978af2705b337584128734707a06c6422799475050f2632ae743899

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-15T15:24:23.756052Z digest=sha256:2d8f334e02321873d8d3f3199ba9eccd2510d81e1e55d33b9b40a684962e7635

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.

source=pdf_text observed=2026-08-11T18:39:43.097129Z digest=sha256:58e8398e9aeb5e26387144c7a0812a320ce10551f6d59c629b14b5332f73010b

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.

source=pdf_text observed=2026-08-11T16:35:17.480171Z digest=sha256:6bc645066d82c1b70bb4ef6fcb40b945c23b3031be9c0ec33eee7220bcc95a66

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.

source=pdf_text observed=2026-08-10T20:34:11.805443Z digest=sha256:caf3a60670fa17347027a2fee9ae30ce836fdad1726470bb81ae1fd9d773fff6

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.

source=pdf_text observed=2026-08-10T20:15:04.539684Z digest=sha256:2e8649daebbe7728c671478a0a2944f5e999d36ac2423e6a537465b34dba4af0

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.

source=pdf_text observed=2026-08-09T12:11:50.572804Z digest=sha256:2f7a588d7fc450497f6ccfa858401e7c1f5bd3c3dee2c640700e1b1a68d7d6b9

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T20:06:27.136345Z digest=sha256:7deea4e2a6f4a86b99a1d5de79d6cd59ee88f3657f23ab59396baf10055b2843

Observation 8bc21a7d-369d-494c-8e87-075f236b92fe · inbound

TinyMA-IEI-PPO: Exploration Incentive-Driven Multi-Agent DRL with Self-Adaptive Pruning for Vehicular Embodied AI Agent Twins Migration cites this paper.

TinyMA-IEI-PPO: Exploration Incentive-Driven Multi-Agent DRL with Self-Adaptive Pruning for Vehicular Embodied AI Agent Twins Migration Embodied Understanding of Driving Scenarios

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-16T05:06:43.313538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:06:43.313538Z digest=sha256:e34b289c7da89179973e1ef1a6b93615835d4135007f09bc7a7156c33ed5730f

Observation 29852160-84df-4536-8fc6-b738e43c86cb · inbound

Embodied Intelligence: The Key to Unblocking Generalized Artificial Intelligence cites this paper.

Embodied Intelligence: The Key to Unblocking Generalized Artificial Intelligence Embodied Understanding of Driving Scenarios

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T22:33:49.101328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:33:49.101328Z digest=sha256:b6d97894acad62110d9fc647f32f9a048841d77fdf627c897b45e45abaac3a47

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.

source=pdf_text observed=2026-08-07T12:43:58.997932Z digest=sha256:9bb4404430888c34afe1bb8279d477cc963f3b2c4cb0faa141632d712b4ca693

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-07-02T12:20:05.133204Z digest=sha256:384e42c1b4cf351de84bb5e5fe04fa7c7e2606987b39414b96bb2b2ac6d012dd