121 citations · 173 across the 25 of their papers we have counts for
4 papers · 1 filter
Exploring the Security Threats of Retriever Backdoors in Retrieval-Augmented Code Generation
Tian Li, Bo Lin, Shangwen Wang +1
Retrieval-Augmented Code Generation (RACG) is increasingly adopted to enhance Large Language Models for software development, yet its security implications remain dangerously under…
Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injection
Bo Lin, Shangwen Wang, Yihao Qin +2
Retrieval-Augmented Code Generation (RACG) leverages external knowledge to enhance Large Language Models (LLMs) in code synthesis, improving the functional correctness of the gener…
Exploring the Security Threats of Knowledge Base Poisoning in Retrieval-Augmented Code Generation
Bo Lin, Shangwen Wang, Liqian Chen +1
The integration of Large Language Models (LLMs) into software development has revolutionized the field, particularly through the use of Retrieval-Augmented Code Generation (RACG) s…
An Extensive Study on Adversarial Attack against Pre-trained Models of Code
Xiaohu Du, Ming Wen, Zichao Wei +2
Transformer-based pre-trained models of code (PTMC) have been widely utilized and have achieved state-of-the-art performance in many mission-critical applications. However, they ca…