Ninghao Liu

ORCID

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 147

Top Venues

Publications

Yucheng Shi, Qiaoyu Tan, Xuansheng Wu, Shaochen Zhong, Kaixiong Zhou, Ninghao Liu
Retrieval-Enhanced Knowledge Editing for Multi-Hop Question Answering in Language Models. CoRR (2024)
Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai, Wenlin Yao, Jundong Li, Mengnan Du, Ninghao Liu
Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era. CoRR (2024)
Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du
Explainability for Large Language Models: A Survey. ACM Trans. Intell. Syst. Technol. 15 (2) (2024)
Xuansheng Wu, Huachi Zhou, Yucheng Shi, Wenlin Yao, Xiao Huang, Ninghao Liu
Could Small Language Models Serve as Recommenders? Towards Data-centric Cold-start Recommendation. WWW (2024)
John A. Miller, Mohammed Aldosari, Farah Saeed, Nasid Habib Barna, Subas Rana, Ismailcem Budak Arpinar, Ninghao Liu
A Survey of Deep Learning and Foundation Models for Time Series Forecasting. CoRR (2024)
Zirui He, Huiqi Deng, Haiyan Zhao, Ninghao Liu, Mengnan Du
Mitigating Shortcuts in Language Models with Soft Label Encoding. LREC/COLING (2024)
Xuansheng Wu, Padmaja Pravin Saraf, Gyeong-Geon Lee, Ehsan Latif, Ninghao Liu, Xiaoming Zhai
Unveiling Scoring Processes: Dissecting the Differences between LLMs and Human Graders in Automatic Scoring. CoRR (2024)
Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang
PokeMQA: Programmable knowledge editing for Multi-hop Question Answering. ACL (1) (2024)
Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang
Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models. CoRR (2024)
Huachi Zhou, Shuang Zhou, Hao Chen, Ninghao Liu, Fan Yang, Xiao Huang
Enhancing Explainable Rating Prediction through Annotated Macro Concepts. ACL (1) (2024)
Shuang Zhou, Xiao Huang, Ninghao Liu, Wen Zhang, Yuan-Ting Zhang, Fu-Lai Chung
Open-world electrocardiogram classification via domain knowledge-driven contrastive learning. Neural Networks 179 (2024)
Yi Fang, Dongzhe Fan, Sirui Ding, Ninghao Liu, Qiaoyu Tan
UniGLM: Training One Unified Language Model for Text-Attributed Graphs. CoRR (2024)
Gengchen Mai, Weiming Huang, Jin Sun, Suhang Song, Deepak Mishra, Ninghao Liu, Song Gao, Tianming Liu, Gao Cong, Yingjie Hu, Chris Cundy, Ziyuan Li, Rui Zhu, Ni Lao
On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper). ACM Trans. Spatial Algorithms Syst. 10 (2) (2024)
Rui Miao, Kaixiong Zhou, Yili Wang, Ninghao Liu, Ying Wang, Xin Wang
Rethinking Independent Cross-Entropy Loss For Graph-Structured Data. CoRR (2024)
Xuansheng Wu, Wenlin Yao, Jianshu Chen, Xiaoman Pan, Xiaoyang Wang, Ninghao Liu, Dong Yu
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning. NAACL-HLT (2024)
Zihao Li, Yucheng Shi, Zirui Liu, Fan Yang, Ninghao Liu, Mengnan Du
Quantifying Multilingual Performance of Large Language Models Across Languages. CoRR (2024)
Hédi Razgallah, Michalis Vlachos, Ahmad Ajalloeian, Ninghao Liu, Johannes Schneider, Alexis Steinmann
Using Neural and Graph Neural Recommender Systems to Overcome Choice Overload: Evidence From a Music Education Platform. ACM Trans. Inf. Syst. 42 (4) (2024)
Chenxu Zhao, Wei Qian, Yucheng Shi, Mengdi Huai, Ninghao Liu
Automated Natural Language Explanation of Deep Visual Neurons with Large Models (Student Abstract). AAAI (2024)
Yili Wang, Kaixiong Zhou, Ninghao Liu, Ying Wang, Xin Wang
Efficient Sharpness-Aware Minimization for Molecular Graph Transformer Models. ICLR (2024)
Gyeong-Geon Lee, Ehsan Latif, Xuansheng Wu, Ninghao Liu, Xiaoming Zhai
Applying large language models and chain-of-thought for automatic scoring. Comput. Educ. Artif. Intell. 6 (2024)
Zihan Guan, Mengxuan Hu, Zhongliang Zhou, Jielu Zhang, Sheng Li, Ninghao Liu
BadSAM: Exploring Security Vulnerabilities of SAM via Backdoor Attacks (Student Abstract). AAAI (2024)
Huaqin Zhao, Zhengliang Liu, Zihao Wu, Yiwei Li, Tianze Yang, Peng Shu, Shaochen Xu, Haixing Dai, Lin Zhao, Gengchen Mai, Ninghao Liu, Tianming Liu
Revolutionizing Finance with LLMs: An Overview of Applications and Insights. CoRR (2024)
Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Jin Sun, Ninghao Liu
Black-box Backdoor Defense via Zero-shot Image Purification. NeurIPS (2023)
Xuansheng Wu, Kaixiong Zhou, Mingchen Sun, Xin Wang, Ninghao Liu
A Survey of Graph Prompting Methods: Techniques, Applications, and Challenges. CoRR (2023)
Yucheng Shi, Mengnan Du, Xuansheng Wu, Zihan Guan, Ninghao Liu
Black-box Backdoor Defense via Zero-shot Image Purification. CoRR (2023)
Ehsan Latif, Gengchen Mai, Matthew Nyaaba, Xuansheng Wu, Ninghao Liu, Guoyu Lu, Sheng Li, Tianming Liu, Xiaoming Zhai
Artificial General Intelligence (AGI) for Education. CoRR (2023)
Zhengliang Liu, Yiwei Li, Qian Cao, Junwen Chen, Tianze Yang, Zihao Wu, John Hale, John Gibbs, Khaled Rasheed, Ninghao Liu, Gengchen Mai, Tianming Liu
Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities. CoRR (2023)
Zihan Guan, Mengnan Du, Ninghao Liu
XGBD: Explanation-Guided Graph Backdoor Detection. ECAI (2023)
Xuansheng Wu, Huachi Zhou, Wenlin Yao, Xiao Huang, Ninghao Liu
Towards Personalized Cold-Start Recommendation with Prompts. CoRR (2023)
Zihan Guan, Lichao Sun, Mengnan Du, Ninghao Liu
Attacking Neural Networks with Neural Networks: Towards Deep Synchronization for Backdoor Attacks. CIKM (2023)
Qiaoyu Tan, Ninghao Liu, Xiao Huang, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu
S2GAE: Self-Supervised Graph Autoencoders are Generalizable Learners with Graph Masking. WSDM (2023)
Gengchen Mai, Weiming Huang, Jin Sun, Suhang Song, Deepak Mishra, Ninghao Liu, Song Gao, Tianming Liu, Gao Cong, Yingjie Hu, Chris Cundy, Ziyuan Li, Rui Zhu, Ni Lao
On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence. CoRR (2023)
Zihan Guan, Zihao Wu, Zhengliang Liu, Dufan Wu, Hui Ren, Quanzheng Li, Xiang Li, Ninghao Liu
CohortGPT: An Enhanced GPT for Participant Recruitment in Clinical Study. CoRR (2023)
Qing Li, Xiao Huang, Ninghao Liu, Yuxiao Dong, Guansong Pang
International Workshop on Learning with Knowledge Graphs: Construction, Embedding, and Reasoning. WSDM (2023)
Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu
DEGREE: Decomposition Based Explanation For Graph Neural Networks. CoRR (2023)
Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang
SEAT: Stable and Explainable Attention. AAAI (2023)
Gyeong-Geon Lee, Ehsan Latif, Xuansheng Wu, Ninghao Liu, Xiaoming Zhai
Applying Large Language Models and Chain-of-Thought for Automatic Scoring. CoRR (2023)
Yao Rong, Guanchu Wang, Qizhang Feng, Ninghao Liu, Zirui Liu, Enkelejda Kasneci, Xia Hu
Efficient GNN Explanation via Learning Removal-based Attribution. CoRR (2023)
Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang, Xia Hu
Did You Train on My Dataset? Towards Public Dataset Protection with CleanLabel Backdoor Watermarking. SIGKDD Explor. 25 (1) (2023)
Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu
GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction. CoRR (2023)
Shuang Zhou, Xiao Huang, Ninghao Liu, Huachi Zhou, Fu-Lai Chung, Long-Kai Huang
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation. IEEE Trans. Knowl. Data Eng. 35 (12) (2023)
Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang
Improving Faithfulness for Vision Transformers. CoRR (2023)
Yucheng Shi, Kaixiong Zhou, Ninghao Liu
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning. ECML/PKDD (3) (2023)
Guoyu Lu, Sheng Li, Gengchen Mai, Jin Sun, Dajiang Zhu, Lilong Chai, Haijian Sun, Xianqiao Wang, Haixing Dai, Ninghao Liu, Rui Xu, Daniel Petti, Changying Li, Tianming Liu, Changying Li
AGI for Agriculture. CoRR (2023)
Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Zihao Wu, Lin Zhao, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, Hongmin Cai, Quanzheng Li, Dinggang Shen, Tianming Liu, Xiang Li
ChatAug: Leveraging ChatGPT for Text Data Augmentation. CoRR (2023)
Mingyang Wan, Daochen Zha, Ninghao Liu, Na Zou
In-Processing Modeling Techniques for Machine Learning Fairness: A Survey. ACM Trans. Knowl. Discov. Data 17 (3) (2023)
Hengrui Gu, Kaixiong Zhou, Xiaotian Han, Ninghao Liu, Ruobing Wang, Xin Wang
PokeMQA: Programmable knowledge editing for Multi-hop Question Answering. CoRR (2023)
Kaixiong Zhou, Soo-Hyun Choi, Zirui Liu, Ninghao Liu, Fan Yang, Rui Chen, Li Li, Xia Hu
Adaptive Label Smoothing To Regularize Large-Scale Graph Training. SDM (2023)
Zihan Guan, Mengnan Du, Ninghao Liu
XGBD: Explanation-Guided Graph Backdoor Detection. CoRR (2023)
Zhengliang Liu, Peilong Wang, Yiwei Li, Jason Holmes, Peng Shu, Lian Zhang, Chenbin Liu, Ninghao Liu, Dajiang Zhu, Xiang Li, Quanzheng Li, Samir H. Patel, Terence T. Sio, Tianming Liu, Wei Liu
RadOnc-GPT: A Large Language Model for Radiation Oncology. CoRR (2023)
Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Ben Hu
Mitigating Algorithmic Bias with Limited Annotations. ECML/PKDD (2) (2023)
Xuansheng Wu, Xinyu He, Tianming Liu, Ninghao Liu, Xiaoming Zhai
Matching Exemplar as Next Sentence Prediction (MeNSP): Zero-Shot Prompt Learning for Automatic Scoring in Science Education. AIED (2023)
Guanchu Wang, Zirui Liu, Zhimeng Jiang, Ninghao Liu, Na Zou, Xia Hu
DIVISION: Memory Efficient Training via Dual Activation Precision. ICML (2023)
Qiaoyu Tan, Daochen Zha, Ninghao Liu, Soo-Hyun Choi, Li Li, Rui Chen, Xia Hu
Double Wins: Boosting Accuracy and Efficiency of Graph Neural Networks by Reliable Knowledge Distillation. ICDM (2023)
John A. Miller, Nasid Habib Barna, Subas Rana, Ismailcem Budak Arpinar, Ninghao Liu
Knowledge Enhanced Deep Learning: Application to Pandemic Prediction. CIC (2023)
Chenjiao Tan, Qian Cao, Yiwei Li, Jielu Zhang, Xiao Yang, Huaqin Zhao, Zihao Wu, Zhengliang Liu, Hao Yang, Nemin Wu, Tao Tang, Xinyue Ye, Lilong Chai, Ninghao Liu, Changying Li, Lan Mu, Tianming Liu, Gengchen Mai
On the Promises and Challenges of Multimodal Foundation Models for Geographical, Environmental, Agricultural, and Urban Planning Applications. CoRR (2023)
Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection. WSDM (2023)
Ruixiang Tang, Qizhang Feng, Ninghao Liu, Fan Yang, Xia Hu
Did You Train on My Dataset? Towards Public Dataset Protection with Clean-Label Backdoor Watermarking. CoRR (2023)
Wenxiong Liao, Zhengliang Liu, Yiyang Zhang, Xiaoke Huang, Fei Qi, Siqi Ding, Hui Ren, Zihao Wu, Haixing Dai, Sheng Li, Lingfei Wu, Ninghao Liu, Quanzheng Li, Tianming Liu, Xiang Li, Hongmin Cai
Coarse-to-fine Knowledge Graph Domain Adaptation based on Distantly-supervised Iterative Training. BIBM (2023)
Xuansheng Wu, Wenlin Yao, Jianshu Chen, Xiaoman Pan, Xiaoyang Wang, Ninghao Liu, Dong Yu
From Language Modeling to Instruction Following: Understanding the Behavior Shift in LLMs after Instruction Tuning. CoRR (2023)
Feng Luo, Ling Liu, G. Geoff Wang, Vijay Kumar, Mark S. Ashton, Jacob D. Abernethy, Fatemeh Afghah, Matthew H. E. M. Browning, David Coyle, Philip M. Dames, Tom O'Halloran, James Hays, Patrick Heisl, Chenfanfu Jiang, Puskar Khanal, Venkat Narayan Krovi, Sara Kuebbing, Nianyi Li, JingJing Liang, Ninghao Liu, Steve McNulty, Christopher M. Oswalt, Neil Pederson, Demetri Terzopoulos, Christopher W. Woodall, Yongkai Wu, Jian Yang, Yin Yang, Liang Zhao
Artificial Intelligence for Climate Smart Forestry: A Forward Looking Vision. CogMI (2023)
Hua Tang, Lu Cheng, Ninghao Liu, Mengnan Du
A Theoretical Approach to Characterize the Accuracy-Fairness Trade-off Pareto Frontier. CoRR (2023)
Saed Rezayi, Zhengliang Liu, Zihao Wu, Chandra Dhakal, Bao Ge, Haixing Dai, Gengchen Mai, Ninghao Liu, Chen Zhen, Tianming Liu, Sheng Li
Exploring New Frontiers in Agricultural NLP: Investigating the Potential of Large Language Models for Food Applications. CoRR (2023)
Yucheng Shi, Kaixiong Zhou, Ninghao Liu
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning. CoRR (2023)
Chenxu Zhao, Wei Qian, Yucheng Shi, Mengdi Huai, Ninghao Liu
Automated Natural Language Explanation of Deep Visual Neurons with Large Models. CoRR (2023)
Haixing Dai, Lu Zhang, Lin Zhao, Zihao Wu, Zhengliang Liu, David Liu, Xiaowei Yu, Yanjun Lyu, Changying Li, Ninghao Liu, Tianming Liu, Dajiang Zhu
Hierarchical Semantic Tree Concept Whitening for Interpretable Image Classification. CoRR (2023)
Fei Dou, Jin Ye, Geng Yuan, Qin Lu, Wei Niu, Haijian Sun, Le Guan, Guoyu Lu, Gengchen Mai, Ninghao Liu, Jin Lu, Zhengliang Liu, Zihao Wu, Chenjiao Tan, Shaochen Xu, Xianqiao Wang, Guoming Li, Lilong Chai, Sheng Li, Jin Sun, Hongyue Sun, Yunli Shao, Changying Li, Tianming Liu, Wenzhan Song
Towards Artificial General Intelligence (AGI) in the Internet of Things (IoT): Opportunities and Challenges. CoRR (2023)
Xuansheng Wu, Xinyu He, Tianming Li, Ninghao Liu, Xiaoming Zhai
Matching Exemplar as Next Sentence Prediction (MeNSP): Zero-shot Prompt Learning for Automatic Scoring in Science Education. CoRR (2023)
Xuansheng Wu, Zhiyi Zhao, Ninghao Liu
NoPPA: Non-Parametric Pairwise Attention Random Walk Model for Sentence Representation. CoRR (2023)
Shuang Zhou, Xiao Huang, Ninghao Liu, Huachi Zhou, Fu-Lai Chung, Long-Kai Huang
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation. CoRR (2023)
Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu
GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction. CIKM (2023)
Zihan Guan, Mengxuan Hu, Zhongliang Zhou, Jielu Zhang, Sheng Li, Ninghao Liu
BadSAM: Exploring Security Vulnerabilities of SAM via Backdoor Attacks. CoRR (2023)
Ziqi Zhao, Yucheng Shi, Shushan Wu, Fan Yang, Wenzhan Song, Ninghao Liu
Interpretation of Time-Series Deep Models: A Survey. CoRR (2023)
Yucheng Shi, Shaochen Xu, Zhengliang Liu, Tianming Liu, Xiang Li, Ninghao Liu
MedEdit: Model Editing for Medical Question Answering with External Knowledge Bases. CoRR (2023)
Haiyan Zhao, Hanjie Chen, Fan Yang, Ninghao Liu, Huiqi Deng, Hengyi Cai, Shuaiqiang Wang, Dawei Yin, Mengnan Du
Explainability for Large Language Models: A Survey. CoRR (2023)
Zirui He, Huiqi Deng, Haiyan Zhao, Ninghao Liu, Mengnan Du
Mitigating Shortcuts in Language Models with Soft Label Encoding. CoRR (2023)
Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution. AAAI (2023)
Guanchu Wang, Ninghao Liu, Daochen Zha, Xia Hu
Interactive System-wise Anomaly Detection. CoRR (2023)
Qiaoyu Tan, Xin Zhang, Ninghao Liu, Daochen Zha, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
Bring Your Own View: Graph Neural Networks for Link Prediction with Personalized Subgraph Selection. CoRR (2022)
Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu
Geometric Graph Representation Learning via Maximizing Rate Reduction. CoRR (2022)
Lijie Hu, Yixin Liu, Ninghao Liu, Mengdi Huai, Lichao Sun, Di Wang
SEAT: Stable and Explainable Attention. CoRR (2022)
Yili Wang, Kaixiong Zhou, Rui Miao, Ninghao Liu, Xin Wang
AdaGCL: Adaptive Subgraph Contrastive Learning to Generalize Large-scale Graph Training. CIKM (2022)
Shoujin Wang, Ninghao Liu, Xiuzhen Zhang, Yan Wang, Francesco Ricci, Bamshad Mobasher
Data Science and Artificial Intelligence for Responsible Recommendations. KDD (2022)
Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution. CoRR (2022)
Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu
G-Mixup: Graph Data Augmentation for Graph Classification. ICML (2022)
Qiaoyu Tan, Ninghao Liu, Xiao Huang, Rui Chen, Soo-Hyun Choi, Xia Hu
MGAE: Masked Autoencoders for Self-Supervised Learning on Graphs. CoRR (2022)
Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Xia Hu
G-Mixup: Graph Data Augmentation for Graph Classification. CoRR (2022)
Guanchu Wang, Zirui Liu, Zhimeng Jiang, Ninghao Liu, Na Zou, Xia Hu
Towards Memory Efficient Training via Dual Activation Precision. CoRR (2022)
Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu
Geometric Graph Representation Learning via Maximizing Rate Reduction. WWW (2022)
Shuang Zhou, Xiao Huang, Ninghao Liu, Qiaoyu Tan, Fu-Lai Chung
Unseen Anomaly Detection on Networks via Multi-Hypersphere Learning. SDM (2022)
Ruixiang Tang, Ninghao Liu, Fan Yang, Na Zou, Xia Hu
Defense Against Explanation Manipulation. Frontiers Big Data 5 (2022)
Shuang Zhou, Xiao Huang, Ninghao Liu, Fu-Lai Chung, Long-Kai Huang
Improving Generalizability of Graph Anomaly Detection Models via Data Augmentation. CoRR (2022)
Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks. WWW (2022)
Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li
GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks. KDD (2022)
Zhou Yang, Ninghao Liu, Xia Ben Hu, Fang Jin
Tutorial on Deep Learning Interpretation: A Data Perspective. CIKM (2022)
Qizhang Feng, Ninghao Liu, Fan Yang, Ruixiang Tang, Mengnan Du, Xia Hu
DEGREE: Decomposition Based Explanation for Graph Neural Networks. ICLR (2022)
Guanchu Wang, Mengnan Du, Ninghao Liu, Na Zou, Xia Hu
Mitigating Algorithmic Bias with Limited Annotations. CoRR (2022)
Weijie Fu, Meng Wang, Mengnan Du, Ninghao Liu, Shijie Hao, Xia Hu
Differentiated Explanation of Deep Neural Networks With Skewed Distributions. IEEE Trans. Pattern Anal. Mach. Intell. 44 (6) (2022)
Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu, Xia Hu
Adversarial Attacks and Defenses: An Interpretation Perspective. SIGKDD Explor. 23 (1) (2021)
Raj Vardhan, Ninghao Liu, Phakpoom Chinprutthiwong, Weijie Fu, Zhenyu Hu, Xia Ben Hu, Guofei Gu
ExAD: An Ensemble Approach for Explanation-based Adversarial Detection. CoRR (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Ninghao Liu