ThunderSVM: A Fast SVM Library on GPUs and CPUs. - Zeyi Wen; Jiashuai Shi; Qinbin Li; Bingsheng He; Jian Chen 011 (J. Mach. Learn. Res., 2018)

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection. - Qinbin Li; Zeyi Wen; Zhaomin Wu; Sixu Hu; Naibo Wang; Xu Liu 014; Bingsheng He (CoRR, 2019)

Exploiting GPUs for Efficient Gradient Boosting Decision Tree Training. - Zeyi Wen; Jiashuai Shi; Bingsheng He; Jian Chen 011; Kotagiri Ramamohanarao; Qinbin Li (IEEE Trans. Parallel Distributed Syst., 2019)

Practical Federated Gradient Boosting Decision Trees. - Qinbin Li; Zeyi Wen; Bingsheng He (AAAI, 2020)

Privacy-Preserving Gradient Boosting Decision Trees. - Qinbin Li; Zhaomin Wu; Zeyi Wen; Bingsheng He (AAAI, 2020)

Model-Agnostic Round-Optimal Federated Learning via Knowledge Transfer. - Qinbin Li; Bingsheng He; Dawn Song (CoRR, 2020)

ThunderGBM: Fast GBDTs and Random Forests on GPUs. - Zeyi Wen; Hanfeng Liu; Jiashuai Shi; Qinbin Li; Bingsheng He; Jian Chen 011 (J. Mach. Learn. Res., 2020)

Adaptive Kernel Value Caching for SVM Training. - Qinbin Li; Zeyi Wen; Bingsheng He (IEEE Trans. Neural Networks Learn. Syst., 2020)

Model-Contrastive Federated Learning. - Qinbin Li; Bingsheng He; Dawn Song (CVPR, 2021)

Practical One-Shot Federated Learning for Cross-Silo Setting. - Qinbin Li; Bingsheng He; Dawn Song (IJCAI, 2021)

Challenges and Opportunities of Building Fast GBDT Systems. - Zeyi Wen; Qinbin Li; Bingsheng He; Bin Cui 001 (IJCAI, 2021)

Federated Learning on Non-IID Data Silos: An Experimental Study. - Qinbin Li; Yiqun Diao; Quan Chen 002; Bingsheng He (ICDE, 2022)

A Coupled Design of Exploiting Record Similarity for Practical Vertical Federated Learning. - Zhaomin Wu; Qinbin Li; Bingsheng He (NeurIPS, 2022)

UniFed: A Benchmark for Federated Learning Frameworks. - Xiaoyuan Liu; Tianneng Shi; Chulin Xie; Qinbin Li; Kangping Hu; Haoyu Kim; Xiaojun Xu; Bo Li 026; Dawn Song (CoRR, 2022)

The OARF Benchmark Suite: Characterization and Implications for Federated Learning Systems. - Sixu Hu; Yuan Li 032; Xu Liu 014; Qinbin Li; Zhaomin Wu; Bingsheng He (ACM Trans. Intell. Syst. Technol., 2022)

Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks. - Chulin Xie; Yunhui Long; Pin-Yu Chen; Qinbin Li; Sanmi Koyejo; Bo Li 026 (CCS, 2023)

Towards Addressing Label Skews in One-Shot Federated Learning. - Yiqun Diao; Qinbin Li; Bingsheng He (ICLR, 2023)

Adversarial Collaborative Learning on Non-IID Features. - Qinbin Li; Bingsheng He; Dawn Song (ICML, 2023)

Communication-Efficient Generalized Neuron Matching for Federated Learning. - Sixu Hu; Qinbin Li; Bingsheng He (ICPP, 2023)

FedTree: A Federated Learning System For Trees. - Qinbin Li; Zhaomin Wu; Yanzheng Cai; Yuxuan Han; Ching Man Yung; Tianyuan Fu; Bingsheng He (MLSys, 2023)

DeltaBoost: Gradient Boosting Decision Trees with Efficient Machine Unlearning. - Zhaomin Wu; Junhui Zhu; Qinbin Li; Bingsheng He (Proc. ACM Manag. Data, 2023)

A Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection. - Qinbin Li; Zeyi Wen; Zhaomin Wu; Sixu Hu; Naibo Wang; Yuan Li 032; Xu Liu 014; Bingsheng He (IEEE Trans. Knowl. Data Eng., 2023)

Exploiting Label Skews in Federated Learning with Model Concatenation. - Yiqun Diao; Qinbin Li; Bingsheng He (AAAI, 2024)

Effective and Efficient Federated Tree Learning on Hybrid Data. - Qinbin Li; Chulin Xie; Xiaojun Xu; Xiaoyuan Liu; Ce Zhang 001; Bo Li 026; Bingsheng He; Dawn Song (ICLR, 2024)

Boosting Alignment for Post-Unlearning Text-to-Image Generative Models. - Myeongseob Ko; Henry Li; Zhun Wang; Jonathan Patsenker; Jiachen T. Wang; Qinbin Li; Ming Jin 002; Dawn Song; Ruoxi Jia 001 (NeurIPS, 2024)

Improving Privacy-Preserving Vertical Federated Learning by Efficient Communication with ADMM. - Chulin Xie; Pin-Yu Chen; Qinbin Li; Arash Nourian; Ce Zhang 001; Bo Li 026 (SaTML, 2024)

SoK: Privacy-Preserving Data Synthesis. - Yuzheng Hu; Fan Wu 011; Qinbin Li; Yunhui Long; Gonzalo Munilla Garrido; Chang Ge 002; Bolin Ding; David A. Forsyth; Bo Li 026; Dawn Song (SP, 2024)

ModelGo: A Practical Tool for Machine Learning License Analysis. - Moming Duan; Qinbin Li; Bingsheng He (WWW, 2024)

Federated Learning with New Knowledge: Fundamentals, Advances, and Futures. - Lixu Wang; Yang Zhao 017; Jiahua Dong 001; Ating Yin; Qinbin Li; Xiao Wang 012; Dusit Niyato; Qi Zhu 002 (CoRR, 2024)

GuardAgent: Safeguard LLM Agents by a Guard Agent via Knowledge-Enabled Reasoning. - Zhen Xiang; Linzhi Zheng; Yanjie Li; Junyuan Hong; Qinbin Li; Han Xie; Jiawei Zhang 002; Zidi Xiong; Chulin Xie; Carl Yang 001; Dawn Song; Bo Li 026 (CoRR, 2024)

MegaAgent: A Practical Framework for Autonomous Cooperation in Large-Scale LLM Agent Systems. - Qian Wang 002; Tianyu Wang; Qinbin Li; Jingsheng Liang; Bingsheng He (CoRR, 2024)

OEBench: Investigating Open Environment Challenges in Real-World Relational Data Streams. - Yiqun Diao; Yutong Yang; Qinbin Li; Bingsheng He; Mian Lu (Proc. VLDB Endow., 2024)

LLM-PBE: Assessing Data Privacy in Large Language Models. - Qinbin Li; Junyuan Hong; Chulin Xie; Jeffrey Tan; Rachel Xin; Junyi Hou; Xavier Yin; Zhun Wang; Dan Hendrycks; Zhangyang Wang; Bo Li 026; Bingsheng He; et al. (Proc. VLDB Endow., 2024)

Practical Vertical Federated Learning With Unsupervised Representation Learning. - Zhaomin Wu; Qinbin Li; Bingsheng He (IEEE Trans. Big Data, 2024)

ICM-Assistant: Instruction-tuning Multimodal Large Language Models for Rule-based Explainable Image Content Moderation. - Mengyang Wu; Yuzhi Zhao; Jialun Cao; Mingjie Xu; Zhongming Jiang; Xuehui Wang; Qinbin Li; Guangneng Hu; Shengchao Qin; Chi-Wing Fu (AAAI, 2025)

MegaAgent: A Large-Scale Autonomous LLM-based Multi-Agent System Without Predefined SOPs. - Qian Wang 002; Tianyu Wang; Zhenheng Tang; Qinbin Li; Nuo Chen 002; Jingsheng Liang; Bingsheng He (ACL (Findings), 2025)

Vertical Federated Learning in Practice: The Good, the Bad, and the Ugly. - Zhaomin Wu; Zhen Qin 004; Junyi Hou; Haodong Zhao; Qinbin Li; Bingsheng He; Lixin Fan (CoRR, 2025)