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20232026
most citedSoVAR: Building Generalizable Scenarios from Accident Reports for Autonomous Driving Testing

16 citations · 34 across the 11 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.SE2024★ 16 cited

SoVAR: Building Generalizable Scenarios from Accident Reports for Autonomous Driving Testing

An Guo, Yuan Zhou, Haoxiang Tian +7

Autonomous driving systems (ADSs) have undergone remarkable development and are increasingly employed in safety-critical applications. However, recently reported data on fatal acci…

cs.SE2024★ 6 cited

CooTest: An Automated Testing Approach for V2X Communication Systems

An Guo, Xinyu Gao, Zhenyu Chen +5

Perceiving the complex driving environment precisely is crucial to the safe operation of autonomous vehicles. With the tremendous advancement of deep learning and communication tec…

cs.CR2024★ 1 cited

Eliminating Backdoors in Neural Code Models for Secure Code Understanding

Weisong Sun, Yuchen Chen, Chunrong Fang +7

Neural code models (NCMs) have been widely used to address various code understanding tasks, such as defect detection. However, numerous recent studies reveal that such models are…

cs.SE2024★ 2 cited

LMM-enhanced Safety-Critical Scenario Generation for Autonomous Driving System Testing From Non-Accident Traffic Videos

Haoxiang Tian, Xingshuo Han, Yuan Zhou +6

Safety testing serves as the fundamental pillar for the development of autonomous driving systems (ADSs). To ensure the safety of ADSs, it is paramount to generate a diverse range…

cs.SE2024★ 1 cited

Pre-trained Model-based Actionable Warning Identification: A Feasibility Study

Xiuting Ge, Chunrong Fang, Quanjun Zhang +8

Actionable Warning Identification (AWI) plays a pivotal role in improving the usability of static code analyzers. Currently, Machine Learning (ML)-based AWI approaches, which mainl…