3 papers
cs.CL2026
FAITH: Factuality Alignment through Integrating Trustworthiness and Honestness
Xiaoning Dong, Chengyan Wu, Yajie Wen +5
Large Language Models (LLMs) can generate factually inaccurate content even if they have corresponding knowledge, which critically undermines their reliability. Existing approaches…
cs.CR2025
SATA: A Paradigm for LLM Jailbreak via Simple Assistive Task Linkage
Xiaoning Dong, Wenbo Hu, Wei Xu +1
Large language models (LLMs) have made significant advancements across various tasks, but their safety alignment remain a major concern. Exploring jailbreak prompts can expose LLMs…
cs.CR2025
SPDZCoder: Combining Expert Knowledge with LLMs for Generating Privacy-Computing Code
Xiaoning Dong, Peilin Xin, Jia Li +1
Privacy computing receives increasing attention but writing privacy computing code remains challenging for developers due to limited library functions, necessitating function imple…