Liang Chen

ORCID

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 111

Top Venues

Publications

Fenfang Xie, Angyu Zheng, Liang Chen, Zibin Zheng, Mingdong Tang
Weighted meta-graph based mobile application recommendation through matrix factorisation and neural networks. Connect. Sci. 36 (1) (2024)
Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng
The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. WSDM (2024)
Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. KDD (2024)
Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. KDD (2024)
Xinzhou Jin, Jintang Li, Liang Chen, Chenyun Yu, Yuanzhen Xie, Tao Xie, Chengxiang Zhuo, Zang Li, Zibin Zheng
CL: Embarrassingly Simple Layer-to-Layer Contrastive Learning for Graph Collaborative Filtering. CoRR (2024)
Yuanzhen Xie, Xinzhou Jin, Tao Xie, Matrixmxlin Matrixmxlin, Liang Chen, Chenyun Yu, Cheng Lei, Chengxiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm. ACL (Findings) (2024)
Huizhe Zhang, Jintang Li, Liang Chen, Zibin Zheng
SGHormer: An Energy-Saving Graph Transformer Driven by Spikes. CoRR (2024)
Yunfei Liu, Jintang Li, Yuehe Chen, Ruofan Wu, Ericbk Wang, Jing Zhou, Sheng Tian, Shuheng Shen, Xing Fu, Changhua Meng, Weiqiang Wang, Liang Chen
Revisiting Modularity Maximization for Graph Clustering: A Contrastive Learning Perspective. CoRR (2024)
Zezhong Wang, Fangkai Yang, Lu Wang, Pu Zhao, Hongru Wang, Liang Chen, Qingwei Lin, Kam-Fai Wong
SELF-GUARD: Empower the LLM to Safeguard Itself. NAACL-HLT (2024)
Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen
Fair Graph Representation Learning via Sensitive Attribute Disentanglement. WWW (2024)
Liang Chen, Yatao Bian, Yang Deng, Deng Cai, Shuaiyi Li, Peilin Zhao, Kam-Fai Wong
WatME: Towards Lossless Watermarking Through Lexical Redundancy. ACL (1) (2024)
Yuchang Zhu, Jintang Li, Yatao Bian, Zibin Zheng, Liang Chen
One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. CoRR (2024)
Jintang Li, Huizhe Zhang, Ruofan Wu, Zulun Zhu, Baokun Wang, Changhua Meng, Zibin Zheng, Liang Chen
A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks. ICLR (2024)
Yuchang Zhu, Jintang Li, Zibin Zheng, Liang Chen
Fair Graph Representation Learning via Sensitive Attribute Disentanglement. CoRR (2024)
Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
Rethinking and Simplifying Bootstrapped Graph Latents. WSDM (2024)
Yuanzhen Xie, Xinzhou Jin, Tao Xie, Mingxiong Lin, Liang Chen, Chenyun Yu, Lei Cheng, Chengxiang Zhuo, Bo Hu, Zang Li
Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigm. CoRR (2024)
Zishan Gu, Ke Zhang, Guangji Bai, Liang Chen, Liang Zhao, Carl Yang
Dynamic Activation of Clients and Parameters for Federated Learning over Heterogeneous Graphs. ICDE (2023)
Jintang Li, Jiaying Peng, Liang Chen, Zibin Zheng, Tingting Liang, Qing Ling
Spectral Adversarial Training for Robust Graph Neural Network. IEEE Trans. Knowl. Data Eng. 35 (9) (2023)
Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng
Adversarial Attack on Large Scale Graph. IEEE Trans. Knowl. Data Eng. 35 (1) (2023)
Xinzhou Jin, Jintang Li, Yuanzhen Xie, Liang Chen, Beibei Kong, Lei Cheng, Bo Hu, Zang Li, Zibin Zheng
Enhancing Graph Collaborative Filtering via Neighborhood Structure Embedding. ICDM (2023)
Yuxin Zhang, Ruoting Wu, Jie Liao, Liang Chen
Structural Adversarial Attack for Code Representation Models. CollaborateCom (2) (2023)
Wei Yuan, Quoc Viet Hung Nguyen, Tieke He, Liang Chen, Hongzhi Yin
Manipulating Federated Recommender Systems: Poisoning with Synthetic Users and Its Countermeasures. SIGIR (2023)
Tingting Liang, Congying Xia, Haoran Xu, Ziqiang Zhao, Yuyu Yin, Liang Chen, Philip S. Yu
Modeling Reviews for Few-Shot Recommendation via Enhanced Prototypical Network. IEEE Trans. Knowl. Data Eng. 35 (9) (2023)
Ruoting Wu, Yuxin Zhang, Liang Chen
Improving Code Representation Learning via Multi-view Contrastive Graph Pooling for Abstract Syntax Tree. CollaborateCom (2) (2023)
Peilin Zheng, Zibin Zheng, Liang Chen
Selecting reliable blockchain peers via hybrid blockchain reliability prediction. IET Softw. 17 (4) (2023)
Jintang Li, Zheng Wei, Jiawang Dan, Jing Zhou, Yuchang Zhu, Ruofan Wu, Baokun Wang, Zhang Zhen, Changhua Meng, Hong Jin, Zibin Zheng, Liang Chen
Hetero$^2$Net: Heterophily-aware Representation Learning on Heterogenerous Graphs. CoRR (2023)
Wangbin Sun, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
Rethinking and Simplifying Bootstrapped Graph Latents. CoRR (2023)
Sheng Tian, Jihai Dong, Jintang Li, Wenlong Zhao, Xiaolong Xu, Baokun Wang, Bowen Song, Changhua Meng, Tianyi Zhang, Liang Chen
SAD: Semi-Supervised Anomaly Detection on Dynamic Graphs. IJCAI (2023)
Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang
Modelling High-Order Social Relations for Item Recommendation (Extended Abstract). ICDE (2023)
Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Zibin Zheng, Jiawang Dan, Changhua Meng, Weiqiang Wang
GUARD: Graph Universal Adversarial Defense. CIKM (2023)
Yuchang Zhu, Jintang Li, Liang Chen, Zibin Zheng
The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. CoRR (2023)
Liang Chen, Yang Deng, Yatao Bian, Zeyu Qin, Bingzhe Wu, Tat-Seng Chua, Kam-Fai Wong
Beyond Factuality: A Comprehensive Evaluation of Large Language Models as Knowledge Generators. CoRR (2023)
Jintang Li, Wangbin Sun, Ruofan Wu, Yuchang Zhu, Liang Chen, Zibin Zheng
Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning. CoRR (2023)
Jie Liao, Jintang Li, Liang Chen, Bingzhe Wu, Yatao Bian, Zibin Zheng
SAILOR: Structural Augmentation Based Tail Node Representation Learning. CIKM (2023)
Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang
What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders. KDD (2023)
Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. AAAI (2023)
Jintang Li, Jiaying Peng, Liang Chen, Zibin Zheng, Tingting Liang, Qing Ling
Spectral Adversarial Training for Robust Graph Neural Network. CoRR (2022)
Jintang Li, Jie Liao, Ruofan Wu, Liang Chen, Changhua Meng, Zibin Zheng, Weiqiang Wang
GUARD: Graph Universal Adversarial Defense. CoRR (2022)
Jintang Li, Ruofan Wu, Wangbin Sun, Liang Chen, Sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang
MaskGAE: Masked Graph Modeling Meets Graph Autoencoders. CoRR (2022)
Zishan Gu, Jintang Li, Liang Chen
Are All Edges Necessary? A Unified Framework for Graph Purification. CoRR (2022)
Bingzhe Wu, Jintang Li, Junchi Yu, Yatao Bian, Hengtong Zhang, Chaochao Chen, Chengbin Hou, Guoji Fu, Liang Chen, Tingyang Xu, Yu Rong, Xiaolin Zheng, Junzhou Huang, Ran He, Baoyuan Wu, Guangyu Sun, Peng Cui, Zibin Zheng, Zhe Liu, Peilin Zhao
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. CoRR (2022)
Bingzhe Wu, Yatao Bian, Hengtong Zhang, Jintang Li, Junchi Yu, Liang Chen, Chaochao Chen, Junzhou Huang
Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection. KDD (2022)
Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo
Spiking Graph Convolutional Networks. IJCAI (2022)
Zulun Zhu, Jiaying Peng, Jintang Li, Liang Chen, Qi Yu, Siqiang Luo
Spiking Graph Convolutional Networks. CoRR (2022)
Fenfang Xie, Yangjun Xu, Angyu Zheng, Liang Chen, Zibin Zheng
Service recommendation through graph attention network in heterogeneous information networks. Int. J. Comput. Sci. Eng. 25 (6) (2022)
Zhouxin Yu, Jintang Li, Liang Chen, Zibin Zheng
Unifying multi-associations through hypergraph for bundle recommendation. Knowl. Based Syst. 255 (2022)
Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang
Modelling High-Order Social Relations for Item Recommendation. IEEE Trans. Knowl. Data Eng. 34 (9) (2022)
Liang Chen, Tao Xie, Jintang Li, Zibin Zheng
Graph Enhanced Neural Interaction Model for recommendation. Knowl. Based Syst. 246 (2022)
Jintang Li, Zhouxin Yu, Zulun Zhu, Liang Chen, Qi Yu, Zibin Zheng, Sheng Tian, Ruofan Wu, Changhua Meng
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks. CoRR (2022)
Liang Chen, Jiaying Peng, Yang Liu, Jintang Li, Fenfang Xie, Zibin Zheng
Phishing Scams Detection in Ethereum Transaction Network. ACM Trans. Internet Techn. 21 (1) (2021)
Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie
Self-supervised Graph Learning for Recommendation. SIGIR (2021)
Fenfang Xie, Angyu Zheng, Liang Chen, Zibin Zheng
Attentive Meta-graph Embedding for item Recommendation in heterogeneous information networks. Knowl. Based Syst. 211 (2021)
Tao Xie, Yangjun Xu, Liang Chen, Yang Liu, Zibin Zheng
Sequential Recommendation on Dynamic Heterogeneous Information Network. ICDE (2021)
Jintang Li, Kun Xu, Liang Chen, Zibin Zheng, Xiao Liu
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software. ICSE (Companion Volume) (2021)
Jintang Li, Kun Xu, Liang Chen, Zibin Zheng, Xiao Liu
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software. CoRR (2021)
Liang Chen, Yangjun Xu, Fenfang Xie, Min Huang, Zibin Zheng
Data poisoning attacks on neighborhood-based recommender systems. Trans. Emerg. Telecommun. Technol. 32 (6) (2021)
Yuanzhen Xie, Zijing Ou, Liang Chen, Yang Liu, Kun Xu, Carl Yang, Zibin Zheng
Learning and Updating Node Embedding on Dynamic Heterogeneous Information Network. WSDM (2021)
Fenfang Xie, Zengxu Cao, Yangjun Xu, Liang Chen, Zibin Zheng
Graph Neural Network and Multi-view Learning Based Mobile Application Recommendation in Heterogeneous Graphs. SCC (2020)
Jieming Zhu, Jinyang Liu, Weiqi Li, Jincai Lai, Xiuqiang He, Liang Chen, Zibin Zheng
Ensembled CTR Prediction via Knowledge Distillation. CIKM (2020)
Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng
Adversarial Attack on Large Scale Graph. CoRR (2020)
Bin Wu, Xiangnan He, Zhongchuan Sun, Liang Chen, Yangdong Ye
ATM: An Attentive Translation Model for Next-Item Recommendation. IEEE Trans. Ind. Informatics 16 (3) (2020)
Liang Chen, Yongjian Ye, Angyu Zheng, Fenfang Xie, Zibin Zheng, Michael R. Lyu
Incorporating geographical location for team formation in social coding sites. World Wide Web 23 (1) (2020)
Yangjun Xu, Liang Chen, Fenfang Xie, Weibo Hu, Jieming Zhu, Chuan Chen, Zibin Zheng
Directional Adversarial Training for Recommender Systems. ECAI (2020)
Wenqiang Lei, Gangyi Zhang, Xiangnan He, Yisong Miao, Xiang Wang, Liang Chen, Tat-Seng Chua
Interactive Path Reasoning on Graph for Conversational Recommendation. KDD (2020)
Wenqiang Lei, Gangyi Zhang, Xiangnan He, Yisong Miao, Xiang Wang, Liang Chen, Tat-Seng Chua
Interactive Path Reasoning on Graph for Conversational Recommendation. CoRR (2020)
Liang Chen, Yuanzhen Xie, Zibin Zheng, Huayou Zheng, Jingdun Xie
Friend Recommendation Based on Multi-Social Graph Convolutional Network. IEEE Access 8 (2020)
Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang
Modelling High-Order Social Relations for Item Recommendation. CoRR (2020)
Liang Chen, Jintang Li, Jiaying Peng, Tao Xie, Zengxu Cao, Kun Xu, Xiangnan He, Zibin Zheng
A Survey of Adversarial Learning on Graphs. CoRR (2020)
Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie
Self-supervised Graph Learning for Recommendation. CoRR (2020)
Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Haochao Ying, Philip S. Yu, Jian Wu
CAMAR: a broad learning based context-aware recommender for mobile applications. Knowl. Inf. Syst. 62 (8) (2020)
Yang Liu, Xianzhuo Xia, Liang Chen, Xiangnan He, Carl Yang, Zibin Zheng
Certifiable Robustness to Discrete Adversarial Perturbations for Factorization Machines. SIGIR (2020)
Jieming Zhu, Jinyang Liu, Weiqi Li, Jincai Lai, Xiuqiang He, Liang Chen, Zibin Zheng
Ensembled CTR Prediction via Knowledge Distillation. CoRR (2020)
Angyu Zheng, Liang Chen, Fenfang Xie, Jianrong Tao, Changjie Fan, Zibin Zheng
Keep You from Leaving: Churn Prediction in Online Games. DASFAA (2) (2020)
Huakun Huang, Shuxue Ding, Lingjun Zhao, Huawei Huang, Liang Chen, Honghao Gao, Syed Hassan Ahmed
Real-Time Fault Detection for IIoT Facilities Using GBRBM-Based DNN. IEEE Internet Things J. 7 (7) (2020)
Tingting Liang, Lei Zheng, Liang Chen, Yao Wan, Philip S. Yu, Jian Wu
Multi-view factorization machines for mobile app recommendation based on hierarchical attention. Knowl. Based Syst. 187 (2020)
Jintang Li, Zishan Gu, Qibiao Peng, Kun Xu, Liang Chen, Zibin Zheng
Deep Insights into Graph Adversarial Learning: An Empirical Study Perspective. HBAI@IJCAI (2020)
Yang Liu, Jiaying Peng, Liang Chen, Zibin Zheng
Abstract Interpretation Based Robustness Certification for Graph Convolutional Networks. ECAI (2020)
Fenfang Xie, Shenghui Li, Liang Chen, Yangjun Xu, Zibin Zheng
Generative Adversarial Network Based Service Recommendation in Heterogeneous Information Networks. ICWS (2019)
Liang Chen, Fenfang Xie, Zibin Zheng, Yaoming Wu
Predicting Quality of Service via Leveraging Location Information. Complex. 2019 (2019)
Liang Chen, Yang Liu, Xiangnan He, Lianli Gao, Zibin Zheng
Matching User with Item Set: Collaborative Bundle Recommendation with Deep Attention Network. IJCAI (2019)
Peilin Zheng, Zibin Zheng, Liang Chen
Selecting Reliable Blockchain Peers via Hybrid Blockchain Reliability Prediction. CoRR (2019)
Yinglan Feng, Liang Chen, Angyu Zheng, Cuiyun Gao, Zibin Zheng
AC-Net: Assessing the Consistency of Description and Permission in Android Apps. IEEE Access 7 (2019)
Tingting Liang, Liang Chen, Jian Wu, Guandong Xu, Zhaohui Wu
SMS: A Framework for Service Discovery by Incorporating Social Media Information. IEEE Trans. Serv. Comput. 12 (3) (2019)
Liang Chen, Yangjun Xu, Fenfang Xie, Min Huang, Zibin Zheng
Data Poisoning Attacks on Neighborhood-based Recommender Systems. CoRR (2019)
Fenfang Xie, Liang Chen, Dongding Lin, Zibin Zheng, Xiaola Lin
Personalized Service Recommendation With Mashup Group Preference in Heterogeneous Information Network. IEEE Access 7 (2019)
Yao Wan, Liang Chen, Guandong Xu, Zhou Zhao, Jie Tang, Jian Wu
SCSMiner: mining social coding sites for software developer recommendation with relevance propagation. World Wide Web 21 (6) (2018)
Shaoan Xie, Zibin Zheng, Liang Chen, Chuan Chen
Learning Semantic Representations for Unsupervised Domain Adaptation. ICML (2018)
Fenfang Xie, Liang Chen, Yongjian Ye, Zibin Zheng, Xiaola Lin
Factorization Machine Based Service Recommendation on Heterogeneous Information Networks. ICWS (2018)
Liang Chen, Angyu Zheng, Yinglan Feng, Fenfang Xie, Zibin Zheng
Software Service Recommendation Base on Collaborative Filtering Neural Network Model. ICSOC (2018)
Fenfang Xie, Liang Chen, Dongding Lin, Chuan Chen, Zibin Zheng, Xiaola Lin
Group preference based API recommendation via heterogeneous information network. ICSE (Companion Volume) (2018)
Liang Chen, Yang Liu, Zibin Zheng, Philip S. Yu
Heterogeneous Neural Attentive Factorization Machine for Rating Prediction. CIKM (2018)
Yao Wan, Guandong Xu, Liang Chen, Zhou Zhao, Jian Wu
Exploiting cross-source knowledge for warming up community question answering services. Neurocomputing 320 (2018)
Fenfang Xie, Liang Chen, Yongjian Ye, Yang Liu, Zibin Zheng, Xiaola Lin
A Weighted Meta-graph Based Approach for Mobile Application Recommendation on Heterogeneous Information Networks. ICSOC (2018)
Athman Bouguettaya, Munindar P. Singh, Michael N. Huhns, Quan Z. Sheng, Hai Dong, Qi Yu, Azadeh Ghari Neiat, Sajib Mistry, Boualem Benatallah, Brahim Medjahed, Mourad Ouzzani, Fabio Casati, Xumin Liu, Hongbing Wang, Dimitrios Georgakopoulos, Liang Chen, Surya Nepal, Zaki Malik, Abdelkarim Erradi, Yan Wang, M. Brian Blake, Schahram Dustdar, Frank Leymann, Michael P. Papazoglou
A service computing manifesto: the next 10 years. Commun. ACM 60 (4) (2017)
Yaoming Wu, Fenfang Xie, Liang Chen, Chuan Chen, Zibin Zheng
An Embedding Based Factorization Machine Approach for Web Service QoS Prediction. ICSOC (2017)
Yuqiang Han, Yao Wan, Liang Chen, Guandong Xu, Jian Wu
Exploiting Geographical Location for Team Formation in Social Coding Sites. PAKDD (1) (2017)
Tingting Liang, Liang Chen, Xingde Ying, Philip S. Yu, Jian Wu, Zibin Zheng
Mobile Application Rating Prediction via Feature-Oriented Matrix Factorization. ICWS (2017)
Li Kuang, Gaofeng Cao, Liang Chen
Extracting Core Users Based on Features of Users and Their Relationships in Recommender Systems. Int. J. Web Serv. Res. 14 (2) (2017)
Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Philip S. Yu, Jian Wu
A Broad Learning Approach for Context-Aware Mobile Application Recommendation. CoRR (2017)
Tingting Liang, Lifang He, Chun-Ta Lu, Liang Chen, Philip S. Yu, Jian Wu
A Broad Learning Approach for Context-Aware Mobile Application Recommendation. ICDM (2017)

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Publication Activity (10 Years)

Top Topics

Top Venues

Liang Chen