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cs.CR2025
R1-Fuzz: Specializing Language Models for Textual Fuzzing via Reinforcement Learning
Jiayi Lin, Liangcai Su, Junzhe Li +1
Fuzzing is effective for vulnerability discovery but struggles with complex targets such as compilers, interpreters, and database engines, which accept textual input that must sati…
cs.LG2025
How Far Are We from True Unlearnability?
Kai Ye, Liangcai Su, Chenxiong Qian
High-quality data plays an indispensable role in the era of large models, but the use of unauthorized data for model training greatly damages the interests of data owners. To overc…
cs.CR2025
ImportSnare: Directed "Code Manual" Hijacking in Retrieval-Augmented Code Generation
Kai Ye, Liangcai Su, Chenxiong Qian
Code generation has emerged as a pivotal capability of Large Language Models(LLMs), revolutionizing development efficiency for programmers of all skill levels. However, the complex…