Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T13:03:27.939171Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-12T07:16:27.359137Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation cb0e2757-184c-4bfe-b51d-c90db53e673e · inbound
Generating Out-Of-Distribution Scenarios Using Language Models Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles
Reference 40
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 603ce83d-801a-4250-a6c5-affa72a8d2d9 · inbound
Exploring Critical Testing Scenarios for Decision-Making Policies: An LLM Approach Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles
Reference 61
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 16cbcf5d-d614-42b4-ab3b-8a60d4936db4 · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a00ef34f-2299-4175-85f0-e28fbbe2a352 · inbound
CrashAgent: Crash Scenario Generation via Multi-modal Reasoning Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles
Reference 30
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3942720-4e80-4914-8d42-470c7b92c603 · inbound
LLM-based Property-based Test Generation for Guardrailing Cyber-Physical Systems Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 016cbd1a-d3a4-4ee7-8e7b-2e2462f63294 · inbound
Adversarial Generation and Collaborative Evolution of Safety-Critical Scenarios for Autonomous Vehicles Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles
Reference 36
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 020b9a41-9529-44f4-9899-2a9c1c16e87e · inbound
Generative AI for Testing of Autonomous Driving Systems: A Survey Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles
Reference 141
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f1e4aef2-2ded-4b11-8d24-37cf6e41e91b · inbound
AutoODD: Agentic Audits via Bayesian Red Teaming in Black-Box Models Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles
Reference 20
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e8614ccb-aca9-47bd-8eb2-0ea4cd8013d8 · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a8b17e7-e50a-4c32-b8f8-4ae23509e25c · inbound
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
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 de2d067b-0ddb-4045-affb-bf7d90ce2811 · inbound
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
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 ffc5aed4-3b64-4e07-902a-b1beb5e56042 · inbound
Chat2Scenic: An Iterative RAG-Based Framework for Scenario Generation in Autonomous Driving Multimodal Large Language Model Driven Scenario Testing for Autonomous Vehicles
Reference 19
Source-reported events for the cited work
Unavailable: canonical work link unavailable.