154 citations · 284 across the 15 of their papers we have counts for
15 papers
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…
Model Inversion Attack via Dynamic Memory Learning
Gege Qi, YueFeng Chen, Xiaofeng Mao +4
Model Inversion (MI) attacks aim to recover the private training data from the target model, which has raised security concerns about the deployment of DNNs in practice. Recent adv…
Context-Aware Robust Fine-Tuning
Xiaofeng Mao, Yuefeng Chen, Xiaojun Jia +3
Contrastive Language-Image Pre-trained (CLIP) models have zero-shot ability of classifying an image belonging to "[CLASS]" by using similarity between the image and the prompt sent…
Prompt-based Connective Prediction Method for Fine-grained Implicit Discourse Relation Recognition
Hao Zhou, Man Lan, Yuanbin Wu +2
Due to the absence of connectives, implicit discourse relation recognition (IDRR) is still a challenging and crucial task in discourse analysis. Most of the current work adopted mu…
Boosting Out-of-distribution Detection with Typical Features
Yao Zhu, YueFeng Chen, Chuanlong Xie +6
Out-of-distribution (OOD) detection is a critical task for ensuring the reliability and safety of deep neural networks in real-world scenarios. Different from most previous OOD det…
Defects of Convolutional Decoder Networks in Frequency Representation
Ling Tang, Wen Shen, Zhanpeng Zhou +2
In this paper, we prove the representation defects of a cascaded convolutional decoder network, considering the capacity of representing different frequency components of an input…