Paper Citation Record · LEDGER

Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2505.00972.

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

pith.paper-citation-record.v1
2505.00972 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:28:31.532098Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-09T05:46:01.467877Z

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 b422b420-b1f7-42c4-a5bd-179d8b3c7232 · inbound

Simulating the Unseen: Crash Prediction Must Learn from What Did Not Happen cites this paper.

Simulating the Unseen: Crash Prediction Must Learn from What Did Not Happen Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models

Reference 111

Resolution: unresolved; no resolver link, observed 2026-08-07T13:28:31.532098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dabd44af-e515-4680-bd52-8bf4838405eb · inbound

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

Generative AI for Testing of Autonomous Driving Systems: A Survey Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models

Reference 148

Resolution: unresolved; no resolver link, observed 2026-08-05T15:24:15.911418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff35c4a7-a63a-4448-9b18-674bf99cfe5f · inbound

Steerable Adversarial Scenario Generation through Test-Time Preference Alignment cites this paper.

Steerable Adversarial Scenario Generation through Test-Time Preference Alignment Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-18T14:16:27.881808Z

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.

Observation 75faa04b-f419-4be8-b585-0cf3786be4f8 · inbound

CARLA-GS: Decoupling Representation, Reasoning, and Physics Simulation for Autonomous Driving Corner-Case Synthesis cites this paper.

CARLA-GS: Decoupling Representation, Reasoning, and Physics Simulation for Autonomous Driving Corner-Case Synthesis Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-07-09T05:46:01.471867Z

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.

Observation 719bf5f3-72d4-411b-b528-9bb5245922ff · inbound

NSF-HRPT: Neural Semantic Field meets Hierarchical Risk Perception Tree for Safety-Critical Scenario Assessment cites this paper.

NSF-HRPT: Neural Semantic Field meets Hierarchical Risk Perception Tree for Safety-Critical Scenario Assessment Seeking to Collide: Online Safety-Critical Scenario Generation for Autonomous Driving with Retrieval Augmented Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T17:00:14.076023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.