| 2026 | AAAI | Editing as Unlearning: Are Knowledge Editing Methods Strong Baselines for Large Language Model Unlearning? | Zexi Li, Xiangzhu Wang, William F. Shen, Meghdad Kurmanji, Xinchi Qiu, Dongqi Cai, Chao Wu, Nicholas D. Lane |
| 2026 | KDD | Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-task Learning. | Ziyu Zhao, Yixiao Zhou, Xin Yu, Zhi Zhang, Didi Zhu, Tao Shen, Zexi Li, Jinluan Yang, Xuwu Wang, Jing Su, Kun Kuang, Zhongyu Wei, Fei Wu, Yu Cheng |
| 2025 | ICANN | ConDTab: Conditional Diffusion Transformer for Mixed-Type Tabular Synthesis with Dual Attention Latent Encoding. | Ruoxuan Wang, Shiying Li, Liuyi Fan, Wei Ma, Zexi Li, Xinbo Ai |
| 2025 | ICCV | You are Your Own Best Teacher: Achieving Centralized-level Performance in Federated Learning under Heterogeneous and Long-Tailed Data. | Shanshan Yan, Zexi Li, Chao Wu, Meng Pang, Yang Lu, Yan Yan, Hanzi Wang |
| 2025 | ICLR | Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering. | Ziyu Zhao, Tao Shen, Didi Zhu, Zexi Li, Jing Su, Xuwu Wang, Fei Wu |
| 2025 | ISNN | Degree-Aware Graph Contrastive Learning for Long-Tail Recommendations: An Empirical Analysis for Hazard Inspection. | Zexi Li, Xinbo Ai, Yanjun Guo, Wei Ma, Ruoxuan Wang, Shaoyang Cheng |
| 2025 | KDD | FedGuCci: Making Local Models More Connected in Landscape for Federated Learning. | Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Tao Shen, Tao Lin, Chao Wu, Nicholas D. Lane |
| 2024 | AAAI | Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers. | Ruiyuan Zhang, Jiaxiang Liu, Zexi Li, Hao Dong, Jie Fu, Chao Wu |
| 2024 | DATE | SCGen: A Versatile Generator Framework for Agile Design of Stochastic Circuits. | Zexi Li, Haoran Jin, Kuncai Zhong, Guojie Luo, Runsheng Wang, Weikang Qian |
| 2024 | ICML | Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models. | Didi Zhu, Zhongyi Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Chao Wu, Kun Kuang |
| 2024 | KDD | OpenFedLLM: Training Large Language Models on Decentralized Private Data via Federated Learning. | Rui Ye, Wenhao Wang, Jingyi Chai, Dihan Li, Zexi Li, Yinda Xu, Yaxin Du, Yanfeng Wang, Siheng Chen |
| 2024 | KDD | Neural Collapse Anchored Prompt Tuning for Generalizable Vision-Language Models. | Didi Zhu, Zexi Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Kun Kuang, Chao Wu |
| 2024 | WCNC | Delay-Sensitive Aggregation Coded Repair: Towards Low-Energy LEO Storage Constellation. | Zexi Li, Shushi Gu, Zhikai Zhang, Qinyu Zhang, Wei Xiang |
| 2023 | ICCV | No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier. | Zexi Li, Xinyi Shang, Rui He, Tao Lin, Chao Wu |
| 2023 | ICCV | Universal Domain Adaptation via Compressive Attention Matching. | Didi Zhu, Yinchuan Li, Junkun Yuan, Zexi Li, Kun Kuang, Chao Wu |
| 2023 | ICML | Revisiting Weighted Aggregation in Federated Learning with Neural Networks. | Zexi Li, Tao Lin, Xinyi Shang, Chao Wu |
| 2023 | SIGIR | Edge-cloud Collaborative Learning with Federated and Centralized Features. | Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu |
| 2022 | DATE | Towards Low-Cost High-Accuracy Stochastic Computing Architecture for Univariate Functions: Design and Design Space Exploration. | Kuncai Zhong, Zexi Li, Weikang Qian |
| 2022 | ICCAD | Exploiting Uniform Spatial Distribution to Design Efficient Random Number Source for Stochastic Computing. | Kuncai Zhong, Zexi Li, Haoran Jin, Weikang Qian |
| 2016 | CEC | Fireworks algorithm for the satellite link scheduling problem in the navigation constellation. | Tianjiao Zhang, Liangjun Ke, Jisheng Li, Jing Li, Zexi Li, Jingqi Huang |