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Paper Citation Record · LEDGER

Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2409.06450.

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

pith.paper-citation-record.v1
2409.06450 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 2026-08-15T06:32:42.880941+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:03:27.939171Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T07:16:27.359137Z

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 cb0e2757-184c-4bfe-b51d-c90db53e673e · inbound

Generating Out-Of-Distribution Scenarios Using Language Models cites this paper.

Generating Out-Of-Distribution Scenarios Using Language Models Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-12T13:03:27.939171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:03:27.939171Z digest=sha256:5144cfb0d1ef743bfcb2043c6ee5af32c1837dd35b057cca8c8e7908762bb62c

Observation 603ce83d-801a-4250-a6c5-affa72a8d2d9 · inbound

Exploring Critical Testing Scenarios for Decision-Making Policies: An LLM Approach cites this paper.

Exploring Critical Testing Scenarios for Decision-Making Policies: An LLM Approach Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-11T19:28:52.509460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:28:52.509460Z digest=sha256:4a8f94759377a5da889eb4ad76c0deb40c8ddf47e9c63664fd4b6e1e0b6b47ab

Observation 16cbcf5d-d614-42b4-ab3b-8a60d4936db4 · inbound

From Words to Collisions: LLM-Guided Evaluation and Adversarial Generation of Safety-Critical Driving Scenarios cites this paper.

From Words to Collisions: LLM-Guided Evaluation and Adversarial Generation of Safety-Critical Driving Scenarios Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-09T13:12:23.856099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:12:23.856099Z digest=sha256:3d17009ca8a5e2627187aac82d2d9360fedd9e704cf3503a2bea43448beff1c9

Observation a00ef34f-2299-4175-85f0-e28fbbe2a352 · inbound

CrashAgent: Crash Scenario Generation via Multi-modal Reasoning cites this paper.

CrashAgent: Crash Scenario Generation via Multi-modal Reasoning Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T14:35:40.960144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:35:40.960144Z digest=sha256:8b0c434b3e4d92dcb2d90d4c4c3f71c5d514a0a6cc2dea8ae09812c6c5d63021

Observation e3942720-4e80-4914-8d42-470c7b92c603 · inbound

LLM-based Property-based Test Generation for Guardrailing Cyber-Physical Systems cites this paper.

LLM-based Property-based Test Generation for Guardrailing Cyber-Physical Systems Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T12:48:23.308991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:48:23.308991Z digest=sha256:e675c8c3a1074b01b96442ed1aef12ebd73e43815cf4396aaa7e12f224fa58bb

Observation 016cbd1a-d3a4-4ee7-8e7b-2e2462f63294 · inbound

Adversarial Generation and Collaborative Evolution of Safety-Critical Scenarios for Autonomous Vehicles cites this paper.

Adversarial Generation and Collaborative Evolution of Safety-Critical Scenarios for Autonomous Vehicles Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-05T18:34:44.228032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T18:34:44.228032Z digest=sha256:5dac8ba8e17622182b46f562450ce84c4144b7dfad86c6a0706ac3fa70586c08

Observation 020b9a41-9529-44f4-9899-2a9c1c16e87e · inbound

Generative AI for Testing of Autonomous Driving Systems: A Survey cites this paper.

Generative AI for Testing of Autonomous Driving Systems: A Survey Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 141

Resolution
unresolved
no resolver link, observed 2026-08-05T15:24:15.882341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T15:24:15.882341Z digest=sha256:a853dad05ce6f14a1501cc70784daceb2fed3d953630e95c200904c2a18fd0a1

Observation f1e4aef2-2ded-4b11-8d24-37cf6e41e91b · inbound

AutoODD: Agentic Audits via Bayesian Red Teaming in Black-Box Models cites this paper.

AutoODD: Agentic Audits via Bayesian Red Teaming in Black-Box Models Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-04T20:19:20.211840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T20:19:20.211840Z digest=sha256:466dec5e26af526644247f57c9de10c6e7d3670459257958bbeb5c84482027b9

Observation e8614ccb-aca9-47bd-8eb2-0ea4cd8013d8 · inbound

A Survey on the Applications of Generative Artificial Intelligence in Automated Driving Systems Test Scenario Generation Methods cites this paper.

A Survey on the Applications of Generative Artificial Intelligence in Automated Driving Systems Test Scenario Generation Methods Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-03T15:54:39.739654Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T15:54:39.739654Z digest=sha256:4aac4059f7c78688d94d371b75c16e43b4ecd1ff95f8dbcbe5769c1389ec3884

Observation 7a8b17e7-e50a-4c32-b8f8-4ae23509e25c · inbound

Operating Within the Operational Design Domain: Zero-Shot Perception with Vision-Language Models cites this paper.

Operating Within the Operational Design Domain: Zero-Shot Perception with Vision-Language Models Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-11T04:15:57.122065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-11T01:52:46.303378Z digest=sha256:9d7af494593b58175e6b8b82da0df06a9f2469ae60bb2cfbde00db31a6f85462

Observation de2d067b-0ddb-4045-affb-bf7d90ce2811 · inbound

Operating Within the Operational Design Domain: Zero-Shot Perception with Vision-Language Models cites this paper.

Operating Within the Operational Design Domain: Zero-Shot Perception with Vision-Language Models Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:16:27.372236Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-12T03:35:16.193455Z digest=sha256:d715a5f882f5132ed26744b6616470a636388b56e1d6bd87db48608b81efc63a

Observation ffc5aed4-3b64-4e07-902a-b1beb5e56042 · inbound

Chat2Scenic: An Iterative RAG-Based Framework for Scenario Generation in Autonomous Driving cites this paper.

Chat2Scenic: An Iterative RAG-Based Framework for Scenario Generation in Autonomous Driving Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-02T02:17:11.688613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T02:17:11.688613Z digest=sha256:9e8dc49cf730d9210b91ce74eaad04dc35887f3a5a06a46c9ce10763bfc6f925