4 papers · 1 filter
CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor
Zhenhua Xu, Xixiang Zhao, Xubin Yue +3
The widespread deployment of large language models (LLMs) has intensified concerns around intellectual property (IP) protection, as model theft and unauthorized redistribution beco…
SproutBench: A Benchmark for Safe and Ethical Large Language Models for Youth
Wenpeng Xing, Lanyi Wei, Haixiao Hu +5
The rapid proliferation of large language models (LLMs) in applications targeting children and adolescents necessitates a fundamental reassessment of prevailing AI safety framework…
Direct Behavior Optimization: Unlocking the Potential of Lightweight LLMs
Hongming Yang, Shi Lin, Jun Shao +4
Lightweight Large Language Models (LwLLMs) are reduced-parameter, optimized models designed to run efficiently on consumer-grade hardware, offering significant advantages in resour…
MIST: Jailbreaking Black-box Large Language Models via Iterative Semantic Tuning
Muyang Zheng, Yuanzhi Yao, Changting Lin +3
Despite efforts to align large language models (LLMs) with societal and moral values, these models remain susceptible to jailbreak attacks -- methods designed to elicit harmful res…