4 papers
Kelp: A Streaming Safeguard for Large Models via Latent Dynamics-Guided Risk Detection
Xiaodan Li, Mengjie Wu, Yao Zhu +5
Large models (LMs) are powerful content generators, yet their open-ended nature can also introduce potential risks, such as generating harmful or biased content. Existing guardrail…
Towards the Resistance of Neural Network Watermarking to Fine-tuning
Ling Tang, Yuefeng Chen, Hui Xue +1
This paper proves a new watermarking method to embed the ownership information into a deep neural network (DNN), which is robust to fine-tuning. Specifically, we prove that when th…
S-Eval: Towards Automated and Comprehensive Safety Evaluation for Large Language Models
Xiaohan Yuan, Jinfeng Li, Dongxia Wang +9
Generative large language models (LLMs) have revolutionized natural language processing with their transformative and emergent capabilities. However, recent evidence indicates that…
EasyRobust: A Comprehensive and Easy-to-use Toolkit for Robust and Generalized Vision
Xiaofeng Mao, Yuefeng Chen, Rong Zhang +3
Deep neural networks (DNNs) has shown great promise in computer vision tasks. However, machine vision achieved by DNNs cannot be as robust as human perception. Adversarial attacks…