ProRLearn: boosting prompt tuning-based vulnerability detection by reinforcement learning

Zilong Ren; Xiaolin Ju; Xiang Chen; Hao Shen

doi:10.1007/s10515-024-00438-9

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ProRLearn: boosting prompt tuning-based vulnerability detection by reinforcement learning

Zilong Ren Xiaolin Ju Xiang Chen Hao Shen

Year: 2024 Journal: Automated Software Engineering Vol: 31 (2) Publisher: Springer Science+Business Media

DOI: 10.1007/s10515-024-00438-9

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Keywords:

Boosting (machine learning) Reinforcement learning Reinforcement Computer science Vulnerability (computing) Artificial intelligence Machine learning Psychology Computer security Social psychology

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Topics

Advanced Malware Detection Techniques

Physical Sciences → Computer Science → Signal Processing

Network Security and Intrusion Detection

Physical Sciences → Computer Science → Computer Networks and Communications

Software Testing and Debugging Techniques

Physical Sciences → Computer Science → Software

ProRLearn: boosting prompt tuning-based vulnerability detection by reinforcement learning

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Citation History

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