1 code implementation • 29 Sep 2023 • Qian Wu, Si Yong Yeo, Yufei Chen, Jun Liu
Accurate localization of cephalometric landmarks holds great importance in the fields of orthodontics and orthognathics due to its potential for automating key point labeling.
1 code implementation • 1 Nov 2022 • Yufei Chen, Chao Shen, Yun Shen, Cong Wang, Yang Zhang
In this paper, we investigate the third type of exploitation of data poisoning - increasing the risks of privacy leakage of benign training samples.
1 code implementation • 6 Jun 2023 • Sen Peng, Yufei Chen, Cong Wang, Xiaohua Jia
This paper introduces WDM, a novel watermarking solution for diffusion models without imprinting the watermark during task generation.
2 code implementations • 23 Jun 2021 • Yufei Chen, Chao Shen, Cong Wang, Yang Zhang
To this end, we propose a teacher model fingerprinting attack to infer the origin of a student model, i. e., the teacher model it transfers from.
1 code implementation • 26 Jun 2020 • Kaidi Jin, Tianwei Zhang, Chao Shen, Yufei Chen, Ming Fan, Chenhao Lin, Ting Liu
It is unknown whether there are any connections and common characteristics between the defenses against these two attacks.
1 code implementation • 6 Apr 2022 • Xuanqi Gao, Juan Zhai, Shiqing Ma, Chao Shen, Yufei Chen, Qian Wang
To solve this issue, there has been a number of work trying to improve model fairness by using an adversarial game in model level.
1 code implementation • 15 Nov 2021 • Junhao Zhou, Yufei Chen, Chao Shen, Yang Zhang
In addition, we show that our attacks can be used to enhance the performance of membership inference against GANs.
1 code implementation • CONLL 2018 • Yufei Chen, Sheng Huang, Fang Wang, Junjie Cao, Weiwei Sun, Xiaojun Wan
We present experiments for cross-domain semantic dependency analysis with a neural Maximum Subgraph parser.
no code implementations • ACL 2018 • Yufei Chen, Weiwei Sun, Xiaojun Wan
We demonstrate that an SHRG-based parser can produce semantic graphs much more accurately than previously shown, by relating synchronous production rules to the syntacto-semantic composition process.
no code implementations • ACL 2018 • Yufei Chen, Yuan-Yuan Zhao, Weiwei Sun, Xiaojun Wan
Motivated by the positive impact of empty category on syntactic parsing, we study neural models for pre- and in-parsing detection of empty category, which has not previously been investigated.
no code implementations • CVPR 2016 • Gang Wang, Zhicheng Wang, Yufei Chen, Qiangqiang Zhou, Weidong Zhao
Point set registration (PSR) is a fundamental problem in computer vision and pattern recognition, and it has been successfully applied to many applications.
no code implementations • CL 2019 • Weiwei Sun, Yufei Chen, Xiaojun Wan, Meichun Liu
In this work, we propose to represent grammatical information using general directed dependency graphs.
no code implementations • CONLL 2019 • Yufei Chen, Yajie Ye, Weiwei Sun
We design, implement and evaluate two semantic parsers, which represent factorization- and composition-based approaches respectively, for Elementary Dependency Structures (EDS) at the CoNLL 2019 Shared Task on Cross-Framework Meaning Representation Parsing.
no code implementations • ACL 2020 • Yufei Chen, Weiwei Sun
We propose variable-in-situ logico-semantic graphs to bridge the gap between semantic graph and logical form parsing.
no code implementations • USENIX Security Symposium 2019 • Qixue Xiao, Yufei Chen, Chao Shen, Yu Chen, Kang Li
We also present an algorithm that can successfully enable attacks against famous cloud-based image services (such as those from Microsoft Azure, Aliyun, Baidu, and Tencent) and cause obvious misclassification effects, even when the details of image processing (such as the exact scaling algorithm and scale dimension parameters) are hidden in the cloud.
no code implementations • 27 Apr 2022 • Xiao Dong, Yufei Chen, Xunzhao Yin, Cheng Zhuo
Worst-case dynamic PDN noise analysis is an essential step in PDN sign-off to ensure the performance and reliability of chips.
no code implementations • 9 Apr 2023 • Xuanqi Gao, Juan Zhai, Shiqing Ma, Chao Shen, Yufei Chen, Shiwei Wang
The common practice leverages incremental learning (IL), e. g., Class-based Incremental Learning (CIL) that updates output labels, to update the model with new data and a limited number of old data.