Search Results for author: Xiangyu Liu

Found 14 papers, 8 papers with code

SemAttack: Natural Textual Attacks via Different Semantic Spaces

1 code implementation3 May 2022 Boxin Wang, Chejian Xu, Xiangyu Liu, Yu Cheng, Bo Li

In particular, SemAttack optimizes the generated perturbations constrained on generic semantic spaces, including typo space, knowledge space (e. g., WordNet), contextualized semantic space (e. g., the embedding space of BERT clusterings), or the combination of these spaces.

Adversarial Text

Towards Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games

1 code implementation NeurIPS 2021 Xiangyu Liu, Hangtian Jia, Ying Wen, Yaodong Yang, Yujing Hu, Yingfeng Chen, Changjie Fan, Zhipeng Hu

With this unified diversity measure, we design the corresponding diversity-promoting objective and population effectivity when seeking the best responses in open-ended learning.

Unifying Behavioral and Response Diversity for Open-ended Learning in Zero-sum Games

no code implementations9 Jun 2021 Xiangyu Liu, Hangtian Jia, Ying Wen, Yaodong Yang, Yujing Hu, Yingfeng Chen, Changjie Fan, Zhipeng Hu

With this unified diversity measure, we design the corresponding diversity-promoting objective and population effectivity when seeking the best responses in open-ended learning.

Neural Auction: End-to-End Learning of Auction Mechanisms for E-Commerce Advertising

no code implementations7 Jun 2021 Xiangyu Liu, Chuan Yu, Zhilin Zhang, Zhenzhe Zheng, Yu Rong, Hongtao Lv, Da Huo, YiQing Wang, Dagui Chen, Jian Xu, Fan Wu, Guihai Chen, Xiaoqiang Zhu

In e-commerce advertising, it is crucial to jointly consider various performance metrics, e. g., user experience, advertiser utility, and platform revenue.

Enhancing Model Robustness By Incorporating Adversarial Knowledge Into Semantic Representation

no code implementations23 Feb 2021 Jinfeng Li, Tianyu Du, Xiangyu Liu, Rong Zhang, Hui Xue, Shouling Ji

Extensive experiments on two real-world tasks show that AdvGraph exhibits better performance compared with previous work: (i) effective - it significantly strengthens the model robustness even under the adaptive attacks setting without negative impact on model performance over legitimate input; (ii) generic - its key component, i. e., the representation of connotative adversarial knowledge is task-agnostic, which can be reused in any Chinese-based NLP models without retraining; and (iii) efficient - it is a light-weight defense with sub-linear computational complexity, which can guarantee the efficiency required in practical scenarios.

Natural Language Processing

Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising

no code implementations5 Dec 2020 Zhilin Zhang, Xiangyu Liu, Zhenzhe Zheng, Chenrui Zhang, Miao Xu, Junwei Pan, Chuan Yu, Fan Wu, Jian Xu, Kun Gai

In e-commerce advertising, the ad platform usually relies on auction mechanisms to optimize different performance metrics, such as user experience, advertiser utility, and platform revenue.

From SCAN to Real Data: Systematic Generalization via Meaningful Learning

1 code implementation14 Mar 2020 Ning Shi, Boxin Wang, Wei Wang, Xiangyu Liu, Rong Zhang, Hui Xue, Xinbing Wang, Zhouhan Lin

In this paper, we revisit systematic generalization from the perspective of meaningful learning, an exceptional capability of humans to learn new concepts by connecting them with other previously known knowledge.

Data Augmentation Semantic Parsing +1

PSGAN: A Generative Adversarial Network for Remote Sensing Image Pan-Sharpening

1 code implementation9 May 2018 Qingjie Liu, Huanyu Zhou, Qizhi Xu, Xiangyu Liu, Yunhong Wang

This paper addresses the problem of remote sensing image pan-sharpening from the perspective of generative adversarial learning.

Invisible Mask: Practical Attacks on Face Recognition with Infrared

no code implementations13 Mar 2018 Zhe Zhou, Di Tang, Xiao-Feng Wang, Weili Han, Xiangyu Liu, Kehuan Zhang

We propose a kind of brand new attack against face recognition systems, which is realized by illuminating the subject using infrared according to the adversarial examples worked out by our algorithm, thus face recognition systems can be bypassed or misled while simultaneously the infrared perturbations cannot be observed by raw eyes.

Cryptography and Security

Understanding Android Obfuscation Techniques: A Large-Scale Investigation in the Wild

no code implementations5 Jan 2018 Shuaike Dong, Menghao Li, Wenrui Diao, Xiangyu Liu, Jian Liu, Zhou Li, Fenghao Xu, Kai Chen, Xiao-Feng Wang, Kehuan Zhang

In this paper, we seek to better understand Android obfuscation and depict a holistic view of the usage of obfuscation through a large-scale investigation in the wild.

Cryptography and Security

Remote Sensing Image Fusion Based on Two-stream Fusion Network

1 code implementation7 Nov 2017 Xiangyu Liu, Qingjie Liu, Yunhong Wang

Unlike previous CNN based methods that consider pan-sharpening as a super resolution problem and perform pan-sharpening in pixel level, the proposed TFNet aims to fuse PAN and MS images in feature level and reconstruct the pan-sharpened image from the fused features.

Computer Vision Image Reconstruction +1

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