Paper Citation Record · LEDGER

LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2406.10857.

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

pith.paper-citation-record.v1
2406.10857 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 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 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T05:37:45.393540Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:21:35.695771Z

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 676b49a7-d2dc-47bc-9340-029ab6a33bce · inbound

Realistic Corner Case Generation for Autonomous Vehicles with Multimodal Large Language Model cites this paper.

Realistic Corner Case Generation for Autonomous Vehicles with Multimodal Large Language Model LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-12T05:37:45.393540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 029b416b-d2ba-4ec3-8ed9-e5d8e59e015d · inbound

Multi-modal Traffic Scenario Generation for Autonomous Driving System Testing cites this paper.

Multi-modal Traffic Scenario Generation for Autonomous Driving System Testing LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T15:33:59.492686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd71634b-52b1-4492-8a66-7feb50d08a59 · inbound

LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios cites this paper.

LiloDriver: A Lifelong Learning Framework for Closed-loop Motion Planning in Long-tail Autonomous Driving Scenarios LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:21:35.698956Z

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 b2a5a153-c794-4439-8bac-446c991ffb94 · inbound

From Failures to Fixes: LLM-Driven Scenario Repair for Self-Evolving Autonomous Driving cites this paper.

From Failures to Fixes: LLM-Driven Scenario Repair for Self-Evolving Autonomous Driving LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T13:20:27.501626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d14f56f-5017-4033-8029-42b08da41fea · inbound

Survey of GenAI for Automotive Software Development: From Requirements to Executable Code cites this paper.

Survey of GenAI for Automotive Software Development: From Requirements to Executable Code LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T15:48:45.150312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f8550cb-2001-47c7-bcb7-fe8e86f7ca9c · 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 LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-05T18:34:45.310936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5200ad1e-688f-427e-9075-d4b5ac24df05 · inbound

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

Generative AI for Testing of Autonomous Driving Systems: A Survey LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Reference 210

Resolution: unresolved; no resolver link, observed 2026-08-05T15:24:16.232285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2faa46a5-5dcc-4474-b2a1-5b458190e393 · inbound

PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment cites this paper.

PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T19:18:54.625566Z

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 0b55cf33-f0c5-4e54-8039-8f144d1869c1 · 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 LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T02:17:10.137079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.