Paper Citation Record · LEDGER

TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2305.06018.

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

pith.paper-citation-record.v1
2305.06018 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:33:53.868842Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T19:18:54.620774Z

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 9766a1b8-4c56-4baa-9382-df2c6564b03f · inbound

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

Multi-modal Traffic Scenario Generation for Autonomous Driving System Testing TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T15:33:53.868842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea38baee-b5dc-4b8c-923d-6c46bdd44611 · 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 TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T13:20:24.662017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53869046-5832-4f75-a1f7-405b46a56fc2 · inbound

Causality-aware Safety Testing for Autonomous Driving Systems cites this paper.

Causality-aware Safety Testing for Autonomous Driving Systems TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T05:10:59.316696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 079aa970-b9a0-47f2-a687-f7f5e1921b34 · 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 TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T15:48:44.993593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 851fc81e-847d-45e7-8355-52124043473b · 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 TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T20:19:19.733339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 981a18cb-1e48-47be-a2ac-bc4f63fd7635 · inbound

From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing cites this paper.

From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:26:03.522142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 224a11b9-e7dd-44c6-a089-3145f7cc4ddf · inbound

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

PCASim: Promptable Closed-loop Adversarial Simulation for Urban Traffic Environment TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-20T19:18:54.622403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f9ab30c5-f4eb-4301-893c-b61767fa0142 · 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 TARGET: Automated Scenario Generation from Traffic Rules for Testing Autonomous Vehicles via Validated LLM-Guided Knowledge Extraction

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-02T02:17:09.812000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.