Yun Tang

Orcid: 0000-0002-6000-6848

Affiliations:
  • Nanyang Technological University, Alibaba-NTU Singapore Joint Research Institute, Singapore, Singapore


According to our database1, Yun Tang authored at least 13 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2023
Specification-Based Autonomous Driving System Testing.
IEEE Trans. Software Eng., June, 2023

Domain Knowledge Distillation from Large Language Model: An Empirical Study in the Autonomous Driving Domain.
CoRR, 2023

A Novel Scenario-Based Testing Approach for Cooperative-Automated Driving Systems.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2023

Domain Knowledge Distillation from Large Language Model: An Empirical Study in the Autonomous Driving Domain.
Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2023

FLYOVER: A Model-Driven Method to Generate Diverse Highway Interchanges for Autonomous Vehicle Testing.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

2022
A map-based model-driven testing framework for automated driving systems
PhD thesis, 2022

Automatic Map Generation for Autonomous Driving System Testing.
CoRR, 2022

2021
A Survey on Scenario-Based Testing for Automated Driving Systems in High-Fidelity Simulation.
CoRR, 2021

Systematic Testing of Autonomous Driving Systems Using Map Topology-Based Scenario Classification.
Proceedings of the 36th IEEE/ACM International Conference on Automated Software Engineering, 2021

Collision Avoidance Testing for Autonomous Driving Systems on Complete Maps.
Proceedings of the IEEE Intelligent Vehicles Symposium, 2021

Route Coverage Testing for Autonomous Vehicles via Map Modeling.
Proceedings of the IEEE International Conference on Robotics and Automation, 2021

2020
CANeleon: Protecting CAN Bus With Frame ID Chameleon.
IEEE Trans. Veh. Technol., 2020

2017
Deep Learning Method for Sleep Stage Classification.
Proceedings of the Neural Information Processing - 24th International Conference, 2017


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