| 2026 | ACL | Compressing LLM Knowledge into Graph Representations for Text-attributed Graphs Learning. | Runhuai Chen, Dian Shen, Dandan Zhang, Kaihong Huang, Linghui Meng, Beilun Wang |
| 2026 | ACL | Structured Episodic Event Memory. | Zhengxuan Lu, Dongfang Li, Yukun Shi, Beilun Wang, Longyue Wang, Baotian Hu |
| 2026 | ACL | LiGen: Active Lipid Generation via a Molecular Language Model. | Ying Zhan, Xiuqi Tang, Yan Zhang, Xiao Tan, Dian Shen, Zhou Yu, Beilun Wang |
| 2026 | INFOCOM | NGSim: A High-Fidelity and Efficient Simulator for Optimizing Network Function Graphs. | Bin Yang, Dian Shen, Jianrui Liu, Beilun Wang |
| 2026 | WWW | Identification of Influential Node Group in Attributed Graph through Explaining Graph Neural Network. | Xiao Tan, Tongtong Su, Jiayi Wu, Yan Zhang, Binghui Xu, Dian Shen, Meng Wang, Beilun Wang |
| 2025 | DASFAA | Information-Agnostic Model Poisoning Attacks Against Byzantine-Robust Federated Learning. | Yan Zhang, Yueyao Chen, Xiao Tan, Dian Shen, Meng Wang, Beilun Wang |
| 2025 | EuroSys | eNetSTL: Towards an In-kernel Library for High-Performance eBPF-based Network Functions. | Bin Yang, Dian Shen, Junxue Zhang, Hanlin Yang, Lunqi Zhao, Beilun Wang, Guyue Liu, Kai Chen |
| 2025 | ICML | Bi-perspective Splitting Defense: Achieving Clean-Seed-Free Backdoor Security. | Yangyang Shen, Xiao Tan, Dian Shen, Meng Wang, Beilun Wang |
| 2025 | IJCAI | ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks. | Kai Sun, Peibo Duan, Levin Kuhlmann, Beilun Wang, Bin Zhang |
| 2025 | INFOCOM | HyperCom: Enabling High Performance and Composable Data Structures for Software Network Functions with eBPF. | Bin Yang, Dian Shen, Hanlin Yang, Lunqi Zhao, Jianrui Liu, Jiantao Cheng, Beilun Wang |
| 2025 | WWW | NoTeNet: Normalized Mutual Information-Driven Tuning-free Dynamic Dependence Network Inference Method for Multimodal Data. | Xiao Tan, Yangyang Shen, Yan Zhang, Jingwen Shao, Dian Shen, Meng Wang, Beilun Wang |
| 2024 | CIKM | Factor Model-Based Large Covariance Estimation from Streaming Data Using a Knowledge-Based Sketch Matrix. | Xiao Tan, Zhaoyang Wang, Hao Qian, Jun Zhou, Peibo Duan, Dian Shen, Meng Wang, Beilun Wang |
| 2024 | CSCWD | A Privacy-Preserving Method for Sequential Recommendation in Vertical Federated Learning. | Yutian Shi, Beilun Wang |
| 2024 | DAC | Hynify: A High-throughput and Unified Accelerator for Multi-Mode Nonparametric Statistics. | Kaihong Huang, Dian Shen, Zhaoyang Wang, Juntao Yang, Beilun Wang |
| 2024 | DASFAA | Large Covariance Estimation from Streaming Data with Knowledge-Based Sketch Matrix. | Xiao Tan, Zhaoyang Wang, Meng Wang, Dian Shen, Weitong Chen, Beilun Wang |
| 2024 | ICML | Adaptive Group Personalization for Federated Mutual Transfer Learning. | Haoqing Xu, Dian Shen, Meng Wang, Beilun Wang |
| 2023 | CIKM | Graph Inference via the Energy-efficient Dynamic Precision Matrix Estimation with One-bit Data. | Xiao Tan, Yangyang Shen, Meng Wang, Beilun Wang |
| 2023 | CSCWD | Applying Robust Gradient Difference Compression to Federated Learning. | Yueyao Chen, Beilun Wang, Tianyi Ma, Cheng Chen |
| 2023 | CSCWD | A Robust Framework for Fixing The Vulnerability of Compressed Distributed Learning. | Yueyao Chen, Beilun Wang, Yan Zhang, Jingyu Kuang |
| 2023 | CSCWD | A Framework Using Absolute Compression Hard-Threshold for Improving The Robustness of Federated Learning Model. | Yuzhang Wu, Beilun Wang |
| 2023 | ICDM | Take CARE: Improving Inherent Robustness of Spiking Neural Networks with Channel-wise Activation Recalibration Module. | Yan Zhang, Cheng Chen, Dian Shen, Meng Wang, Beilun Wang |
| 2023 | SMC | Collaborative Estimating Multiple Gaussian Graphical Models on Resource Constrained Devices in IoT Networks. | Ying Zhan, Beilun Wang |
| 2023 | WWW | Label Information Enhanced Fraud Detection against Low Homophily in Graphs. | Yuchen Wang, Jinghui Zhang, Zhengjie Huang, Weibin Li, Shikun Feng, Ziheng Ma, Yu Sun, Dianhai Yu, Fang Dong, Jiahui Jin, Beilun Wang, Junzhou Luo |
| 2022 | ICML | A Difference Standardization Method for Mutual Transfer Learning. | Haoqing Xu, Meng Wang, Beilun Wang |
| 2020 | IJCAI | Quadratic Sparse Gaussian Graphical Model Estimation Method for Massive Variables. | Jiaqi Zhang, Meng Wang, Qinchi Li, Sen Wang, Xiaojun Chang, Beilun Wang |
| 2018 | AISTATS | Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure. | Beilun Wang, Arshdeep Sekhon, Yanjun Qi |
| 2018 | ICML | A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models. | Beilun Wang, Arshdeep Sekhon, Yanjun Qi |
| 2017 | AISTATS | A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models. | Beilun Wang, Ji Gao, Yanjun Qi |
| 2017 | ICLR | DeepCloak: Masking Deep Neural Network Models for Robustness Against Adversarial Samples. | Ji Gao, Beilun Wang, Zeming Lin, Weilin Xu, Yanjun Qi |
| 2017 | ICLR | A Theoretical Framework for Robustness of (Deep) Classifiers against Adversarial Samples. | Beilun Wang, Ji Gao, Yanjun Qi |
| 2017 | PSB | Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks. | Jack Lanchantin, Ritambhara Singh, Beilun Wang, Yanjun Qi |