no code implementations • 27 Dec 2023 • Jinwen He, Yujia Gong, Kai Chen, Zijin Lin, Chengan Wei, Yue Zhao
In this paper, we introduce the LLM factoscope, a novel Siamese network-based model that leverages the inner states of LLMs for factual detection.
1 code implementation • 9 Sep 2023 • Jinwen He, Kai Chen, Guozhu Meng, Jiangshan Zhang, Congyi Li
While enjoying the great achievements brought by deep learning (DL), people are also worried about the decision made by DL models, since the high degree of non-linearity of DL models makes the decision extremely difficult to understand.
no code implementations • 13 May 2021 • Yingzhe He, Guozhu Meng, Kai Chen, Jinwen He, Xingbo Hu
Compared to the method of retraining from scratch, our approach can achieve 99. 0%, 95. 0%, 91. 9%, 96. 7%, 74. 1% accuracy rates and 66. 7$\times$, 75. 0$\times$, 33. 3$\times$, 29. 4$\times$, 13. 7$\times$ speedups on the MNIST, SVHN, CIFAR-10, Purchase, and ImageNet datasets, respectively.
no code implementations • 28 Nov 2019 • Yingzhe He, Guozhu Meng, Kai Chen, Xingbo Hu, Jinwen He
In order to unveil the security weaknesses and aid in the development of a robust deep learning system, we undertake an investigation on attacks towards deep learning, and analyze these attacks to conclude some findings in multiple views.