9 citations · 20 across the 13 of their papers we have counts for
4 papers · 1 filter
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…
Smoke and Mirrors: Jailbreaking LLM-based Code Generation via Implicit Malicious Prompts
Sheng Ouyang, Yihao Qin, Bo Lin +3
The proliferation of Large Language Models (LLMs) has revolutionized natural language processing and significantly impacted code generation tasks, enhancing software development ef…
Large Language Models-Aided Program Debloating
Bo Lin, Shangwen Wang, Yihao Qin +2
As software grows in complexity to accommodate diverse features and platforms, software bloating has emerged as a significant challenge, adversely affecting performance and securit…
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…