| 2026 | AAAI | Anti-adversarial Learning: Desensitizing Prompts for Large Language Model. | Xuan Li, Zhe Yin, Xiaodong Gu, Beijun Shen |
| 2026 | ACL | SWE-QA: Can Language Models Answer Repository-level Code Questions? | Weihan Peng, Yuling Shi, Yuhang Wang, Xinyun Zhang, Beijun Shen, Xiaodong Gu |
| 2026 | ACL | GlimpRouter: Efficient Collaborative Inference by Glimpsing One Token of Thoughts. | Wenhao Zeng, Xuteng Zhang, Yuling Shi, Chao Hu, Yuting Chen, Beijun Shen, Xiaodong Gu |
| 2025 | COMPSAC | ApiRAT: Integrating Multi-source API Knowledge for Enhanced Code Translation with LLMs. | Chaofan Wang, Guanjie Qiu, Xiaodong Gu, Beijun Shen |
| 2025 | COMPSAC | Empowering AI to Generate Better AI Code: Guided Generation of Deep Learning Projects with LLMs. | Chen Xie, Mingsheng Jiao, Xiaodong Gu, Beijun Shen |
| 2025 | EMNLP | Transplant Then Regenerate: A New Paradigm for Text Data Augmentation. | Guangzhan Wang, Hongyu Zhang, Beijun Shen, Xiaodong Gu |
| 2024 | APSEC | Unraveling the Potential of Large Language Models in Code Translation: How Far are We? | Qingxiao Tao, Tingrui Yu, Xiaodong Gu, Beijun Shen |
| 2023 | ICSE | Lejacon: A Lightweight and Efficient Approach to Java Confidential Computing on SGX. | Xinyuan Miao, Ziyi Lin, Shaojun Wang, Lei Yu, Sanhong Li, Zihan Wang, Pengbo Nie, Yuting Chen, Beijun Shen, He Jiang |
| 2022 | APSEC | Code Question Answering via Task-Adaptive Sequence-to-Sequence Pre-training. | Tingrui Yu, Xiaodong Gu, Beijun Shen |
| 2022 | ICSE | Cross-Domain Deep Code Search with Meta Learning. | Yitian Chai, Hongyu Zhang, Beijun Shen, Xiaodong Gu |
| 2021 | APSEC | Mining API Constraints from Library and Client to Detect API Misuses. | Hushuang Zeng, Jingxin Chen, Beijun Shen, Hao Zhong |
| 2021 | COMPSAC | Learning to Match Workers and Tasks via a Multi-View Graph Attention Network. | Nan Cui, Chunqi Chen, Beijun Shen, Yuting Chen |
| 2021 | COMPSAC | ApproxiFuzzer: Fuzzing towards Deep Code Snippets in Java Programs. | Xintian Yu, Enze Ma, Pengbo Nie, Beijun Shen, Yuting Chen, Ziyi Lin |
| 2021 | ISSRE | Tensfa: Detecting and Repairing Tensor Shape Faults in Deep Learning Systems. | Dangwei Wu, Beijun Shen, Yuting Chen, He Jiang, Lei Qiao |
| 2021 | QRS | ConLAR: Learning to Allocate Resources to Docker Containers under Time-Varying Workloads. | Diwei Chen, Beijun Shen, Yuting Chen |
| 2021 | WWW | Weakly-Supervised Question Answering with Effective Rank and Weighted Loss over Candidates. | Haozhe Qin, Jiangang Zhu, Beijun Shen |
| 2020 | ICSR | Learning to Recommend Trigger-Action Rules for End-User Development - A Knowledge Graph Based Approach. | Qinyue Wu, Beijun Shen, Yuting Chen |
| 2019 | APSEC | Reinforcement Learning of Code Search Sessions. | Wei Li, Shuhan Yan, Beijun Shen, Yuting Chen |
| 2019 | COMPSAC | An Adaptive Approach to Recommending Obfuscation Rules for Java Bytecode Obfuscators. | Yanru Peng, Yuting Chen, Beijun Shen |
| 2019 | SEKE | Constructing a Knowledge Base of Coding Conventions from Online Resources. | Junming Cao, Tianjiao Du, Beijun Shen, Wei Li, Qinyue Wu, Yuting Chen |
| 2019 | SEKE | Generating SQL Statements from Natural Language Queries: A Multitask Learning Approach (S). | Chunqi Chen, Yunxiang Xiong, Beijun Shen, Yuting Chen |
| 2019 | SEKE | Enhancing Semantic Search of Crowdsourcing IT Services using Knowledge Graph. | Duankang Fu, Shufan Zhou, Beijun Shen, Yuting Chen |
| 2019 | SEKE | CrowDevBot: A Task-Oriented Conversational Bot for Software Crowdsourcing Platform (S). | Zeyu Ni, Beijun Shen, Yuting Chen, Zhangyuan Meng, Junming Cao |
| 2018 | APSEC | SLAMPA: Recommending Code Snippets with Statistical Language Model. | Shufan Zhou, Hao Zhong, Beijun Shen |
| 2017 | APSEC | Transfer Learning for Cross-Platform Software Crowdsourcing Recommendation. | Shuhan Yan, Beijun Shen, Wenkai Mo, Ning Li |
| 2017 | APSEC | How Do Programmers Maintain Concurrent Code? | Feiyue Yu, Hao Zhong, Beijun Shen |
| 2017 | SEKE | A GQM-based Approach for Software Process Patterns Recommendation. | Zhangyuan Meng, Cheng Zhang, Beijun Shen, Yin Wei |
| 2017 | SEKE | Mining Developer Behavior Across GitHub and StackOverflow. | Yunxiang Xiong, Zhangyuan Meng, Beijun Shen, Wei Yin |
| 2017 | SEKE | Cold-Start Developer Recommendation in Software Crowdsourcing: A Topic Sampling Approach. | Yu Yang, Wenkai Mo, Beijun Shen, Yuting Chen |
| 2016 | APSEC | Task Recommendation with Developer Social Network in Software Crowdsourcing. | Ning Li, Wenkai Mo, Beijun Shen |
| 2016 | APSEC | EXPSOL: Recommending Online Threads for Exception-Related Bug Reports. | Xiaoning Liu, Beijun Shen, Hao Zhong, Jiangang Zhu |
| 2016 | APSEC | Heterogeneous Cross-Company Effort Estimation through Transfer Learning. | Shensi Tong, Qing He, Yuting Chen, Ye Yang, Beijun Shen |
| 2016 | COMPSAC | GRETA: Graph-Based Tag Assignment for GitHub Repositories. | Xuyang Cai, Jiangang Zhu, Beijun Shen, Yuting Chen |
| 2016 | COMPSAC | Software Defect Prediction Using Semi-Supervised Learning with Change Burst Information. | Qing He, Beijun Shen, Yuting Chen |
| 2016 | COMPSAC | SOLinker: Constructing Semantic Links between Tags and URLs on StackOverflow. | Wenkai Mo, Jiangang Zhu, Zhenzheng Qian, Beijun Shen |
| 2016 | COMPSAC | SatiIndicator: Leveraging User Reviews to Evaluate User Satisfaction of SourceForge Projects. | Zhenzheng Qian, Beijun Shen, Wenkai Mo, Yuting Chen |
| 2016 | SEKE | Building a Domain Knowledge Base from Wikipedia: a Semi-supervised Approach. | Kai Chen, Xiang Dong, Jiangang Zhu, Beijun Shen |
| 2016 | SEKE | Learning to Discover Subsumptions between Software Engineering Concepts in Wikipedia. | Xiang Dong, Kai Chen, Jiangang Zhu, Beijun Shen |
| 2016 | SEKE | CPDScorer: Modeling and Evaluating Developer Programming Ability across Software Communities. | Weizhi Huang, Wenkai Mo, Beijun Shen, Yu Yang, Ning Li |
| 2016 | SNPD | Operational pattern based code generation for management information system: An industrial case study. | Fagui Mao, Xuyang Cai, Beijun Shen, Yong Xia, Bo Jin |
| 2015 | APSEC | TBIL: A Tagging-Based Approach to Identity Linkage Across Software Communities. | Wenkai Mo, Beijun Shen, Yuting Chen, Jiangang Zhu |
| 2015 | APSEC | A Learning to Rank Framework for Developer Recommendation in Software Crowdsourcing. | Jiangang Zhu, Beijun Shen, Fanghuai Hu |
| 2015 | ESEM | Code Bad Smell Detection through Evolutionary Data Mining. | Shizhe Fu, Beijun Shen |
| 2015 | SEKE | Towards Effective Developer Recommendation in Software Crowdsourcing. | Shixiong Zhao, Beijun Shen, Yuting Chen, Hao Zhong |
| 2015 | SEKE | Building a Large-scale Software Programming Taxonomy from Stackoverflow. | Jiangang Zhu, Beijun Shen, Xuyang Cai, Haofen Wang |
| 2014 | APSEC | Mining Developer Mailing List to Predict Software Defects. | Yu Zhang, Beijun Shen, Yuting Chen |
| 2014 | COMPSAC | A Scenario-Based Approach to Predicting Software Defects Using Compressed C4.5 Model. | Biwen Li, Beijun Shen, Jun Wang, Yuting Chen, Tao Zhang, Jinshuang Wang |
| 2013 | APSEC | Mining GitHub: Why Commit Stops - Exploring the Relationship between Developer's Commit Pattern and File Version Evolution. | Weicheng Yang, Beijun Shen, Ben Xu |
| 2011 | ENASE | Measuring and Improving IT Service Support Processes: A Case Study. | Kai Zhou, Beijun Shen |
| 2011 | WiMob | A semantic unification approach for M2M applications based on ontology. | Menghan Chen, Beijun Shen |