Bibliometrics can be found in Google Scholar
- 2-in-1 Phishing Detection via Large LM Distillation and Small LM Perturbation [Student Abstract]
Calvin Greenewald, Bradley Ashmore, Chien-Sing Poon, and Lingwei Chen
AAAI Conference on Artificial Intelligence (AAAI), 2025. - Leveraging Homophily-Augmented Energy Propagation for Bot Detection on Graphs
Bradley Ashmore, and Lingwei Chen
International Conference on Database Systems for Advanced Applications (DASFAA), 2024. - Clustering-Augmented Fraud Detection on Graphs Using Label-Aware Feature Aggregation
Shixiong Jing, Lingwei Chen, and Dinghao Wu
Asian Conference on Machine Learning (ACML), 2024. - DRILL: Dual-Reasoning Large Language Models for Phishing Email Detection with Limited Data
Calvin Greenewald, Bradley Ashmore, Chien-Sing Poon, and Lingwei Chen
International Conference on Neural Information Processing (ICONIP), 2024. - Enhancing Graph Neural Networks with Limited Labeled Data by Actively Distilling Knowledge from Large Language Models
Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, and Suhang Wang
IEEE International Conference on Big Data (IEEE BigData), 2024. - H2GNN: Graph Neural Networks with Homophilic and Heterophilic Feature Aggregations
Shixiong Jing, Lingwei Chen, Quan Li, and Dinghao Wu
International Conference on Database Systems for Advanced Applications (DASFAA), 2024. - HardVD: High-Capacity Cross-Modal Adversarial Reprogramming for Data-Efficient Vulnerability Detection [J]
Zhenzhou Tian, Haojiang Li, Hanlin Sun, Yanping Chen, and Lingwei Chen
Information Sciences, 2024. - DOS-GNN: Dual-Feature Aggregations with Over-Sampling for Class-Imbalanced Fraud Detection on Graphs
Shixiong Jing, Lingwei Chen, Quan Li, and Dinghao Wu
International Joint Conference on Neural Networks (IJCNN), 2024. - An Empirical Study on the Divergence of Differently-Sourced LLVM IRs [J]
Zhenzhou Tian, Yuchen Gong, Chenhao Chang, Jiaze Sun, Yanping Chen, and Lingwei Chen
Journal of Computer Languages, 2024. - Differential Testing Solidity Compiler through Deep Contract Manipulation and Mutation [J]
Zhenzhou Tian, Fanfan Wang, Yanping Chen, and Lingwei Chen
Software Quality Journal, 2024. - Advancing Chest X-Ray Diagnostics via Multi-Modal Neural Networks with Attention
Douglas Townsell, Tanvi Banerjee, Lingwei Chen, and Michael Raymer
International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), 2024. - HyperCell: Advancing Cell Type Classification with Hyperdimensional Computing
Hossein Mohammadi, Maziar Baranpouyan, Krishnaprasad Thirunarayan, and Lingwei Chen
International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS), 2024. - Vul-Mixer: Efficient and Effective Machine Learning–Assisted Software Vulnerability Detection [J]
Daniel Grahn, Lingwei Chen, and Junjie Zhang
Electronics, 2024. - "Are Your Explanations Reliable?" Investigating the Stability of LIME in Explaining Text Classifiers by Marrying XAI and Adversarial Attack
Christopher Burger, Lingwei Chen, and Thai Le
The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2023. - HOVER: Homophilic Oversampling via Edge Removal for Class-Imbalanced Bot Detection on Graphs
Bradley Ashmore, and Lingwei Chen
ACM International Conference on Information and Knowledge Management (CIKM), 2023. - Pseudo-Labeling with Graph Active Learning for Few-shot Node Classification
Quan Li, Lingwei Chen*, Shixiong Jing, and Dinghao Wu*
IEEE International Conference on Data Mining (ICDM), 2023. - Adversary for Social Good: Leveraging Adversarial Attacks to Protect Personal Attribute Privacy [J]
Xiaoting Li, Lingwei Chen, and Dinghao Wu
ACM Transactions on Knowledge Discovery from Data (TKDD), 2023. - Leveraging Comment Retrieval for Code Summarization
Shifu Hou, Lingwei Chen, Mingxuan Ju, and Yanfang Ye
European Conference on Information Retrieval (ECIR), 2023. - Hierarchical Graph Neural Network for Patient Treatment Preference Prediction with External Knowledge
Quan Li, Lingwei Chen, Yong Cai, and Dinghao Wu
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2023. - Knowledge Distillation on Cross-Modal Adversarial Reprogramming for Data-Limited Attribute Inference [P]
Quan Li, Lingwei Chen, Shixiong Jing, and Dinghao Wu
The Web Conference (WWW), 2023. - Enhancing Vulnerability Detection via AST Decomposition and Neural Sub-tree Encoding [J]
Zhenzhou Tian, Binhui Tian, Jiajun Lv, Yanping Chen, and Lingwei Chen
Expert Systems with Applications (ESWA), 2023. - Mining Themes in Clinical Notes to Identify Phenotypes and to Predict Length of Stay in Patients admitted with Heart Failure
Ankita Agarwal, Tanvi Banerjee, William L. Romine, Krishnaprasad Thirunarayan, Lingwei Chen, and Mia Cajita
IEEE International Conference on Digital Health (ICDH), 2023. - Learning and Fusing Multi-View Code Representations for Function Vulnerability Detection [J]
Zhenzhou Tian, Binhui Tian, Jiajun Lv, and Lingwei Chen
Electronics, 2023. - Enhancing Rare Cell Type Identification in Single-Cell Data: An Innovative Gene Filtering Approach using Bipartite Cell-Gene Relation Graph
Maziar Baranpouyan, Hossein Mohammadi, Hojjat Torabi Goudarzi, Krishnaprasad Thirunarayan, and Lingwei Chen
IEEE International Conference on Biomedical and Health Informatics (BHI), 2023. - Code Execution Capability as a Metric for Machine Learning-Assisted Software Vulnerability Detection Models [S]
Daniel Grahn, Lingwei Chen, and Junjie Zhang
IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), 2023. - Function-Level Code Obfuscation Detection Through Self-Attention Guided Multi-Representation Fusion [J]
Zhenzhou Tian, Ruikang He, Hongliang Zhao, and Lingwei Chen
International Journal of Software Engineering and Knowledge Engineering (IJSEKE), 2023. - CVII: Enhancing Interpretability in Intelligent Sensor Systems via Computer Vision Interpretability Index [J]
Hossein Mohammadi, Krishnaprasad Thirunarayan, and Lingwei Chen
Sensors, 2023. - Distilling Knowledge on Text Graph for Social Media Attribute Inference
Quan Li, Xiaoting Li, Lingwei Chen*, and Dinghao Wu*
International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2022. - Adversarially Reprogramming Pretrained Neural Networks for Data-limited and Cost-efficient Malware Detection
Lingwei Chen, Xiaoting Li, and Dinghao Wu
SIAM International Conference on Data Mining (SDM), 2022. - Summarizing Source Code from Structure and Context
Shifu Hou, Lingwei Chen, and Yanfang Ye
International Joint Conference on Neural Networks (IJCNN), 2022. - Adversary for Social Good: Leveraging Attribute-Obfuscating Attack to Protect User Privacy on Social Networks
Xiaoting Li*, Lingwei Chen*, and Dinghao Wu
EAI International Conference on Security and Privacy in Communication Networks (SecureComm), 2022. - ALPHAPROG: Reinforcement Generation of Valid Programs for Compiler Fuzzing
Xiaoting Li, Xiao Liu, Lingwei Chen, Rupesh Prajapati, and Dinghao Wu
The Thirty-Fourth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI), 2022. - Ethereum Smart Contract Representation Learning for Robust Bytecode-Level Similarity Detection
Zhenzhou Tian*, Yaqian Huang, Jie Tian, Zhongmin Wang, Yanping Chen, and Lingwei Chen*
International Conference on Software Engineering and Knowledge Engineering (SEKE), 2022. - FuzzBoost: Reinforcement Compiler Fuzzing
Xiaoting Li, Xiao Liu, Lingwei Chen, Rupesh Prajapati, and Dinghao Wu
International Conference on Information and Communications Security (ICICS), 2022. - Turning Attacks into Protection: Social Media Privacy Protection Using Adversarial Attacks
Xiaoting Li, Lingwei Chen, and Dinghao Wu
SIAM International Conference on Data Mining (SDM), 2021. - Fine-Grained Compiler Identification with Sequence-oriented Neural Modeling [J]
Zhenzhou Tian, Yaqian Huang, Borun Xie, Yanping Chen, Lingwei Chen, and Dinghao Wu
IEEE Access, 2021. - Watermarking-based Defense against Adversarial Attacks on Deep Neural Networks
Xiaoting Li, Lingwei Chen, Jingquan Zhang, James Larus, and Dinghao Wu
International Joint Conference on Neural Networks (IJCNN), 2021. - Adversarial Reprogramming of Pretrained Neural Networks for Fraud Detection
Lingwei Chen, Yujie Fan, and Yanfang Ye
ACM International Conference on Information and Knowledge Management (CIKM), 2021. - Landscape Estimation of Solidity Version Usage on Ethereum via Version Identification [J]
Zhenzhou Tian, Jie Tian, Zhongmin Wang, Yanping Chen, Hong Xia, and Lingwei Chen
International Journal of Intelligent Systems (IJIS), 2021. - Attributed Heterogeneous Information Network Embedding for Code Retrieval
Lingwei Chen, Shifu Hou, Yanfang Ye, and Shouhuai Xu
KDD Workshop on Heterogeneous Information Network Analysis and Applications (KDD-HENA), 2021. - Enhancing Robustness of Graph Convolutional Networks via Dropping Graph Connections
Lingwei Chen, Xiaoting Li, and Dinghao Wu
European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2020. - Plagiarism Detection of Multi-threaded Programs using Frequent Behavioral Pattern Mining
Qing Wang, Zhenzhou Tian, Cong Gao, and Lingwei Chen
International Conference on Software Engineering and Knowledge Engineering (SEKE), 2020. (Best Paper Award) - Towards Fine-Grained Compiler Identification with Neural Modeling
Borun Xie, Zhenzhou Tian, Cong Gao, and Lingwei Chen
International Conference on Software Engineering and Knowledge Engineering (SEKE), 2020. - Plagiarism Detection of Multi-threaded Programs via Siamese Neural Networks [J]
Zhenzhou Tian, Qing Wang, Cong Gao, Lingwei Chen, and Dinghao Wu
IEEE Access, 2020. - Binary Code Authorship Identification with Neural Representation Learning
Zhongmin Wang, Zhen Feng, Zhenzhou Tian, and Lingwei Chen
International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), 2020. - Plagiarism Detection of Multi-threaded Programs using Frequent Behavioral Pattern Mining [J]
Zhenzhou Tian, Qing Wang, Cong Gao, Lingwei Chen, and Dinghao Wu
International Journal of Software Engineering and Knowledge Engineering (IJSEKE), 2020. (Extended version of the SEKE'2020 paper) - Out-of-sample Node Representation Learning for Heterogeneous Graph in Real-time Android Malware Detection
Yanfang Ye, Shifu Hou, Lingwei Chen, Jingwei Lei, Wenqiang Wan, Jiabin Wang, Qi Xiong, and Fudong Shao
International Joint Conference on Artificial Intelligence (IJCAI), 2019. - iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow
Yujie Fan, Yiming Zhang, Shifu Hou, Lingwei Chen, Yanfang Ye, Chuan Shi, Liang Zhao, and Shouhuai Xu
International Joint Conference on Artificial Intelligence (IJCAI), 2019. - iTrustSO: An Intelligent System for Automatic Detection of Insecure Code Snippets in Stack Overflow
Lingwei Chen, Shifu Hou, Yanfang Ye, Thirimachos Bourlai, Shouhuai Xu, and Liang Zhao
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2019. - Higher-order Weighted Graph Convolutional Networks
Songtao Liu, Lingwei Chen, Hanze Dong, Zihao Wang, Dinghao Wu, and Zengfeng Huang
arXiv:1911.04129, 2019. - DroidEye: Fortifying Security of Learning-based Classifier against Adversarial Android Malware Attacks
Lingwei Chen, Shifu Hou, Yanfang Ye, and Shouhuai Xu
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018. - ICSD: An Automatic System for Insecure Code Snippet Detection in Stack Overflow over Heterogeneous Information Network
Yanfang Ye, Shifu Hou, Lingwei Chen, Xin Li, Liang Zhao, Shouhuai Xu, Jiabin Wang, and Qi Xiong
Annual Computer Security Applications Conference (ACSAC), 2018. - AiDroid: When Heterogeneous Information Network Marries Deep Neural Network for Real-time Android Malware Detection
Yanfang Ye, Shifu Hou, Lingwei Chen, Jingwei Lei, Wenqiang Wan, Jiabin Wang, Qi Xiong, and Fudong Shao
arXiv:1811.01027, 2018. - DeepAM: A Heterogeneous Deep Learning Framework for Intelligent Malware Detection [J]
Yanfang Ye, Lingwei Chen, Shifu Hou, William Hardy, and Xin Li
Knowledge and Information Systems (KAIS), 2018. - SecureDroid: Enhancing Security of Machine Learning-based Detection against Adversarial Android Malware Attacks
Lingwei Chen, Shifu Hou, and Yanfang Ye
Annual Computer Security Applications Conference (ACSAC), 2017. - Adversarial Machine Learning in Malware Detection: Arms Race between Evasion Attack and Defense
Lingwei Chen, Yanfang Ye, and Thirimachos Bourlai
European Intelligence and Security Informatics Conference (EISIC), 2017. (Best Paper Award) - SecMD: Make Machine Learning More Secure Against Adversarial Malware Attacks
Lingwei Chen, and Yanfang Ye
Australasian Joint Conference on Artificial Intelligence (AJCAI), 2017. - Deep Neural Networks for Automatic Android Malware Detection
Shifu Hou, Aaron Saas, Lingwei Chen, Yanfang Ye, and Thirimachos Bourlai
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2017. - An Adversarial Machine Learning Model Against Android Malware Evasion Attacks
Lingwei Chen, Shifu Hou, Yanfang Ye, and Lifei Chen
International Conference on Web-Age Information Management (WAIM), 2017. - Deep Analysis and Utilization of Malware’s Social Relation Network for Its Detection
Shifu Hou, Lingwei Chen, Yanfang Ye, and Lifei Chen
International Conference on Web-Age Information Management (WAIM), 2017. - DL4MD: A Deep Learning Framework for Intelligent Malware Detection
William Hardy, Lingwei Chen, Shifu Hou, Yanfang Ye, and Xin Li
International Conference on Data Science (ICDATA), 2016. - Automatic Detection of Helmet Uses for Construction Safety
Abu HM Rubaiyat, Tanjin T Toma, Masoumeh Kalantari-Khandani, Syed A Rahman, Lingwei Chen, Yanfang Ye, Christopher S Pan
IEEE/WIC/ACM International Conference on Web Intelligence Workshops (WIW), 2016. - Analyzing File-to-File Relation Network in Malware Detection
Lingwei Chen, William Hardy, Yanfang Ye, and Tao Li
International Conference onWeb Information Systems Engineering (WISE), 2015. - Intelligent Malware Detection Based on File Relation Graphs
Lingwei Chen, Tao Li, Melih Abdulhayoglu, and Yanfang Ye
IEEE International Conference on Semantic Computing (ICSC), 2015. - Blind Image Restoration using Divisional Regularization and Wavelet Technique
Lingwei Chen, Xinyu Chen, and Ping Guo
IEEE International Conference on Natural Computation (ICNC), 2008. - Blind Image Restoration based on Parzen-window Estimate and Regularization Method
Lingwei Chen, Xinyu Chen, and Ping Guo
Medical Imaging, Parallel Processing of Images, and Optimization Techniques (MIPPR), 2007. - Comparison of Parzen-Window Estimate and Recursive Filtering Method for Blind Image Restoration
Lingwei Chen, and Ping Guo
Proceeding of the Asia-PacificWorkshop on Visual Information Processing (VIP), 2006.
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
Prior to 2015
* Corresponding author(s) or authors contributed equally
