4 citations · 4 across the 2 of their papers we have counts for
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cs.CR2025
Uncovering Pretraining Code in LLMs: A Syntax-Aware Attribution Approach
Yuanheng Li, Zhuoyang Chen, Xiaoyun Liu +5
As large language models (LLMs) become increasingly capable, concerns over the unauthorized use of copyrighted and licensed content in their training data have grown, especially in…
cs.CR2025
SilentStriker:Toward Stealthy Bit-Flip Attacks on Large Language Models
Haotian Xu, Qingsong Peng, Jie Shi +3
The rapid adoption of large language models (LLMs) in critical domains has spurred extensive research into their security issues. While input manipulation attacks (e.g., prompt inj…
cs.CR2025★ 4 cited
On Benchmarking Code LLMs for Android Malware Analysis
Yiling He, Hongyu She, Xingzhi Qian +4
Large Language Models (LLMs) have demonstrated strong capabilities in various code intelligence tasks. However, their effectiveness for Android malware analysis remains underexplor…