Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:41:31.481271Z
Paper Citation Record · LEDGER
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models
As of 9 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2506.16699.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
21 of 21 outbound references displayed
- verified exact3
- verified fuzzy12
- unresolved6
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 4cb40f7c-1695-4a7f-ac3b-0d239c431d02 · outbound
This paper cites En- hancing road safety and cybersecurity in traffic manage- ment systems: Leveraging the potential of reinforcement learning.IEEE Access, 12:9963–9975, 2024.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models En- hancing road safety and cybersecurity in traffic manage- ment systems: Leveraging the potential of reinforcement learning.IEEE Access, 12:9963–9975, 2024
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:32.074172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 5ccc3575-27d2-4ac4-b3fb-843340734620 · outbound
This paper cites Information fusion-based cybersecu- rity threat detection for intelligent transportation system.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Information fusion-based cybersecu- rity threat detection for intelligent transportation system
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:32.057240Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 87cbe2f1-a65c-4836-bb41-be05076f737d · outbound
This paper cites On the cybersecurity of traffic signal control system with connected vehicles.IEEE Transactions on Intelligent Transportation Systems, 23(9):16267–16279, 2022.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models On the cybersecurity of traffic signal control system with connected vehicles.IEEE Transactions on Intelligent Transportation Systems, 23(9):16267–16279, 2022
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:32.040038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 453e35c2-55c0-4bc2-9a78-d64a39204173 · outbound
This paper cites Implications of traffic signal cybersecurity on potential deliberate traffic disruptions.Transportation research part A: policy and practice, 120:58–70, 2019.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Implications of traffic signal cybersecurity on potential deliberate traffic disruptions.Transportation research part A: policy and practice, 120:58–70, 2019
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:32.021063Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation ceeb1441-d05f-4b24-a1c9-60943921e8ed · outbound
This paper cites An innovative attack modeling and attack detection approach for a waiting time-based adaptive traffic signal controller.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models An innovative attack modeling and attack detection approach for a waiting time-based adaptive traffic signal controller
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:32.002346Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 18f2a163-a8b3-4981-8b1b-7462a33c9940 · outbound
This paper cites Assessing cybersecurity risks and traffic impact in connected autonomous vehicles.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Assessing cybersecurity risks and traffic impact in connected autonomous vehicles
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:41:31.401811Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 852a7d33-9470-49ee-9310-8e9121cb36b9 · outbound
This paper cites Reinforcement learning-driven attack on road traffic signal controllers.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Reinforcement learning-driven attack on road traffic signal controllers
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:31.972612Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 406e64c5-aed0-4c87-b64e-0d2f8faf3688 · outbound
This paper cites Cybersecurity-focused anomaly detection in connected autonomous vehicles using machine learning.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Cybersecurity-focused anomaly detection in connected autonomous vehicles using machine learning
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:31.955401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a86a6020-01ea-4649-b82f-3411a769273d · outbound
This paper cites Evaluating cybersecurity risks of cooperative ramp merging in mixed traffic environ- ments.IEEE Intelligent Transportation Systems Maga- zine, 14(6):52–65, 2022.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Evaluating cybersecurity risks of cooperative ramp merging in mixed traffic environ- ments.IEEE Intelligent Transportation Systems Maga- zine, 14(6):52–65, 2022
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:31.938777Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 579d725c-5cad-4a68-a978-d70a1c45ca12 · outbound
This paper cites an unresolved cited work.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-08-06T23:41:31.921772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 426af8dd-95e7-49af-a644-c23a3b315997 · outbound
This paper cites Mistralbsm: Leveraging mistral-7b for vehicular networks misbehav- ior detection.arXiv preprint arXiv:2407.18462, 2024.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Mistralbsm: Leveraging mistral-7b for vehicular networks misbehav- ior detection.arXiv preprint arXiv:2407.18462, 2024
Reference 11
- Resolution
- verified exact
- raw_fallback, observed 2026-08-06T23:41:31.822566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation e4f52e90-ebe3-41c7-a839-4fd43682481e · outbound
This paper cites LASER: Script Execution by Autonomous Agents for On-demand Traffic Simulation.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models LASER: Script Execution by Autonomous Agents for On-demand Traffic Simulation
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T23:41:31.734677Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation d48973cf-a504-40d1-98c0-c022ef3939f0 · outbound
This paper cites Realistic Corner Case Generation for Autonomous Vehicles with Multimodal Large Language Model.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Realistic Corner Case Generation for Autonomous Vehicles with Multimodal Large Language Model
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:41:31.437528Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd11d92f-887e-4a1d-8993-14f77924d762 · outbound
This paper cites iLLM-TSC: Integration reinforcement learning and large language model for traffic signal control policy improvement.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models iLLM-TSC: Integration reinforcement learning and large language model for traffic signal control policy improvement
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:41:31.442791Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a695fa7-e1dd-4296-8305-b6866e088b9c · outbound
This paper cites From sands to mansions: Enabling au- tomatic full-life-cycle cyberattack construction with llm.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models From sands to mansions: Enabling au- tomatic full-life-cycle cyberattack construction with llm
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:41:31.448034Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dcb113cf-fe13-4347-874a-9b694c7b3c69 · outbound
This paper cites VulnBot: Autonomous Penetration Testing for A Multi-Agent Collaborative Framework.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models VulnBot: Autonomous Penetration Testing for A Multi-Agent Collaborative Framework
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:41:31.453447Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5d50a7db-a6ec-4114-be7d-5f5fb23cf02c · outbound
This paper cites Leveraging large language models for dynamic scenario building targeting enhanced cyber-threat detection and security training.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Leveraging large language models for dynamic scenario building targeting enhanced cyber-threat detection and security training
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:31.900683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation fa8b6872-b28e-4704-ba76-b17ea24b9a2a · outbound
This paper cites Pentest-ai, an llm-powered multi-agents framework for penetration testing automation leveraging mitre attack.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Pentest-ai, an llm-powered multi-agents framework for penetration testing automation leveraging mitre attack
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:31.879088Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 0f393b0e-bb66-49a7-8f6c-d73e5a44fba3 · outbound
This paper cites Multimodal Road Network Generation Based on Large Language Model.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Multimodal Road Network Generation Based on Large Language Model
Reference 19
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T23:41:31.534186Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 84e6a124-58c0-4eef-a8ac-bd7bc9d7ca12 · outbound
This paper cites Chatsumo: Large language model for automating traffic scenario generation in simulation of urban mobility.IEEE Trans- actions on Intelligent Vehicles, 2024.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Chatsumo: Large language model for automating traffic scenario generation in simulation of urban mobility.IEEE Trans- actions on Intelligent Vehicles, 2024
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:31.861865Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 34dea8c7-8943-47f4-95b3-eaffa216bfed · outbound
This paper cites Large language model-assisted arterial traffic signal control.
Exploring Traffic Simulation and Cybersecurity Strategies Using Large Language Models Large language model-assisted arterial traffic signal control
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-06T23:41:31.842107Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Pith citing papers
No inbound Pith citation observations are available.