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)

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

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

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)

VertiBench: Advancing Feature Distribution Diversity in Vertical Federated Learning Benchmarks. - Zhaomin Wu; Junyi Hou; Bingsheng He (ICLR, 2024)

Federated Transformer: Multi-Party Vertical Federated Learning on Practical Fuzzily Linked Data. - Zhaomin Wu; Junyi Hou; Yiqun Diao; Bingsheng He (NeurIPS, 2024)

Model-Based Differentially Private Knowledge Transfer for Large Language Models. - Zhaomin Wu; Jizhou Guo; Junyi Hou; Bingsheng He; Lixin Fan; Qiang Yang (CoRR, 2024)

Personalized Federated Fine-Tuning for LLMs via Data-Driven Heterogeneous Model Architectures. - Yicheng Zhang; Zhen Qin 004; Zhaomin Wu; Shuiguang Deng (CoRR, 2024)

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

Federated Data-Efficient Instruction Tuning for Large Language Models. - Zhen Qin 004; Zhaomin Wu; Bingsheng He; Shuiguang Deng (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)

Learning Relational Tabular Data without Shared Features. - Zhaomin Wu; Shida Wang; Ziyang Wang; Bingsheng He (CoRR, 2025)

Reward Inside the Model: A Lightweight Hidden-State Reward Model for LLM's Best-of-N sampling. - Jizhou Guo; Zhaomin Wu; Philip S. Yu (CoRR, 2025)

WikiDBGraph: Large-Scale Database Graph of Wikidata for Collaborative Learning. - Zhaomin Wu; Ziyang Wang; Bingsheng He (CoRR, 2025)

Beyond Prompt-Induced Lies: Investigating LLM Deception on Benign Prompts. - Zhaomin Wu; Mingzhe Du; See-Kiong Ng; Bingsheng He (CoRR, 2025)