| 2026 | AAAI | Differentially Private Subspace Fine-Tuning for Large Language Models. | Lele Zheng, Xiang Wang, Tao Zhang, Yang Cao, Ke Cheng, Yulong Shen |
| 2026 | ACL | DP³: Differentially Private Prompt Perturbation for Multi-turn LLM Inference. | Lele Zheng, Chao Zhang, Feiyang Yuan, Ke Cheng, Tao Zhang, Anxiao Song, Yulong Shen |
| 2026 | KSEM | FedAMM: Mitigating Shared Parameter Drift in Personalized Federated Learning via Momentum-Guided Server Aggregation. | Tao Zhang, Yangyang Guo, Lele Zheng, Feiyang Yuan, Chao Zhang |
| 2025 | ADMA | Alternating Aggregation Low-Rank Adaptation Approach for Federated Large Models. | Tao Zhang, Chao Zhang, Feiyang Yuan, Lele Zheng, Yiyun Guo |
| 2025 | IJCAI | MMGIA: Gradient Inversion Attack Against Multimodal Federated Learning via Intermodal Correlation. | Lele Zheng, Yang Cao, Leo Yu Zhang, Wei Wang, Yulong Shen, Xiaochun Cao |
| 2025 | PAKDD | Privacy in Fine-Tuning Large Language Models: Attacks, Defenses, and Future Directions. | Hao Du, Shang Liu, Lele Zheng, Yang Cao, Atsuyoshi Nakamura, Lei Chen |
| 2024 | DASFAA | Enhancing Privacy of Spatiotemporal Federated Learning Against Gradient Inversion Attacks. | Lele Zheng, Yang Cao, Renhe Jiang, Kenjiro Taura, Yulong Shen, Sheng Li, Masatoshi Yoshikawa |
| 2022 | TrustCom | HyperMean: Effective Multidimensional Mean Estimation with Local Differential Privacy. | Tao Zhang, Bowen Deng, Lele Zheng, Ze Tong, Qi Li |
| 2020 | INFOCOM | A Lightweight Auction Framework for Spectrum Allocation with Strong Security Guarantees. | Ke Cheng, Liangmin Wang, Yulong Shen, Yangyang Liu, Yongzhi Wang, Lele Zheng |