Zexi Li - RankMe

44 papers A* 10A 1Journal 29Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Each Rank Could be an Expert: Single-Ranked Mixture of Experts LoRA for Multi-task Learning. KDD (1) 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
2026	A*	`conf`	Editing as Unlearning: Are Knowledge Editing Methods Strong Baselines for Large Language Model Unlearning? AAAI Zexi Li, Xiangzhu Wang, William F. Shen, Meghdad Kurmanji, Xinchi Qiu, Dongqi Cai, Chao Wu, Nicholas D. Lane
2026	J	`jnl`	Improving Model Fusion by Training-Time Neuron Alignment With Fixed Neuron Anchors. IEEE Trans. Pattern Anal. Mach. Intell. Zexi Li, Zhiqi Li, Jie Lin, Tao Shen, Jun Xiao, Yike Guo, Tao Lin, Chao Wu
2025	J	`jnl`	Editing as Unlearning: Are Knowledge Editing Methods Strong Baselines for Large Language Model Unlearning? CoRR Zexi Li, Xiangzhu Wang, William F. Shen, Meghdad Kurmanji, Xinchi Qiu, Dongqi Cai, Chao Wu, Nicholas D. Lane
2025	J	`jnl`	FedEve: On Bridging the Client Drift and Period Drift for Cross-device Federated Learning. CoRR Tao Shen, Zexi Li, Didi Zhu, Ziyu Zhao, Chao Wu, Fei Wu
2025	—	`conf`	FedGuCci: Making Local Models More Connected in Landscape for Federated Learning. KDD (2) Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Tao Shen, Tao Lin, Chao Wu, Nicholas D. Lane
2025	J	`jnl`	FedMcon: an adaptive aggregation method for federated learning via meta controller. Frontiers Inf. Technol. Electron. Eng. Tao Shen, Zexi Li, Ziyu Zhao, Didi Zhu, Zheqi Lv, Kun Kuang, Shengyu Zhang, Chao Wu, Fei Wu
2025	J	`jnl`	FediOS: decoupling orthogonal subspaces for personalization in feature-skew federated learning. Mach. Learn. Lingzhi Gao, Zexi Li, Xinyi Shang, Yang Lu, Chao Wu
2025	J	`jnl`	FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models. CoRR Yan Gao, Massimo Roberto Scamarcia, Javier Fernández-Marqués, Mohammad Naseri, Chong Shen Ng, Dimitris Stripelis, Zexi Li, Tao Shen, Jiamu Bai, Daoyuan Chen, Zikai Zhang, Rui Hu, Inseo Song, KangYoon Lee, Hong Jia, Ting Dang, Junyan Wang, Zheyuan Liu, Daniel J. Beutel, Lingjuan Lyu, Nicholas D. Lane
2025	A*	`conf`	Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering. ICLR Ziyu Zhao, Tao Shen, Didi Zhu, Zexi Li, Jing Su, Xuwu Wang, Fei Wu
2025	J	`jnl`	MobiEdit: Resource-efficient Knowledge Editing for Personalized On-device LLMs. CoRR Zhenyan Lu, Daliang Xu, Dongqi Cai, Zexi Li, Wei Liu, Fangming Liu, Shangguang Wang, Mengwei Xu
2025	—	`conf`	Photon: Federated LLM Pre-Training. MLSys Lorenzo Sani, Alex Iacob, Zeyu Cao, Royson Lee, Bill Marino, Yan Gao, Wanru Zhao, Dongqi Cai, Zexi Li, Xinchi Qiu, Nicholas D. Lane
2025	A*	`conf`	Text2Weight: Bridging Natural Language and Neural Network Weight Spaces. ACM Multimedia Bowen Tian, Wenshuo Chen, Zexi Li, Songning Lai, Jiemin Wu, Yutao Yue
2025	J	`jnl`	Text2Weight: Bridging Natural Language and Neural Network Weight Spaces. CoRR Bowen Tian, Wenshuo Chen, Zexi Li, Songning Lai, Jiemin Wu, Yutao Yue
2025	J	`jnl`	Toward Universal Personalization in Federated Learning via Collaborative Foundation Generative Models. IEEE Trans. Mob. Comput. Chenrui Wu, Zexi Li, Fangxin Wang, Hongyang Chen, Jiajun Bu, Haishuai Wang
2025	J	`jnl`	You Are Your Own Best Teacher: Achieving Centralized-level Performance in Federated Learning under Heterogeneous and Long-tailed Data. CoRR Shanshan Yan, Zexi Li, Chao Wu, Meng Pang, Yang Lu, Yan Yan, Hanzi Wang
2024	—	`conf`	An Adaptive Aggregation Method for Federated Learning via Meta Controller. MMAsia Workshops Tao Shen, Zexi Li, Ziyu Zhao, Didi Zhu, Zheqi Lv, Shengyu Zhang, Kun Kuang, Fei Wu
2024	J	`jnl`	Improving Group Connectivity for Generalization of Federated Deep Learning. CoRR Zexi Li, Jie Lin, Zhiqi Li, Didi Zhu, Chao Wu
2024	J	`jnl`	Merging LoRAs like Playing LEGO: Pushing the Modularity of LoRA to Extremes Through Rank-Wise Clustering. CoRR Ziyu Zhao, Tao Shen, Didi Zhu, Zexi Li, Jing Su, Xuwu Wang, Kun Kuang, Fei Wu
2024	A*	`conf`	Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models. ICML Didi Zhu, Zhongyi Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Chao Wu, Kun Kuang
2024	J	`jnl`	Model Tailor: Mitigating Catastrophic Forgetting in Multi-modal Large Language Models. CoRR Didi Zhu, Zhongyi Sun, Zexi Li, Tao Shen, Ke Yan, Shouhong Ding, Kun Kuang, Chao Wu
2024	A*	`conf`	Neural Collapse Anchored Prompt Tuning for Generalizable Vision-Language Models. KDD Didi Zhu, Zexi Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Kun Kuang, Chao Wu
2024	J	`jnl`	Photon: Federated LLM Pre-Training. CoRR Lorenzo Sani, Alex Iacob, Zeyu Cao, Royson Lee, Bill Marino, Yan Gao, Dongqi Cai, Zexi Li, Wanru Zhao, Xinchi Qiu, Nicholas D. Lane
2024	A*	`conf`	Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers. AAAI Ruiyuan Zhang, Jiaxiang Liu, Zexi Li, Hao Dong, Jie Fu, Chao Wu
2024	J	`jnl`	Text-to-Model: Text-Conditioned Neural Network Diffusion for Train-Once-for-All Personalization. CoRR Zexi Li, Lingzhi Gao, Chao Wu
2024	J	`jnl`	Towards Effective Clustered Federated Learning: A Peer-to-Peer Framework With Adaptive Neighbor Matching. IEEE Trans. Big Data Zexi Li, Jiaxun Lu, Shuang Luo, Didi Zhu, Yunfeng Shao, Yinchuan Li, Zhimeng Zhang, Yongheng Wang, Chao Wu
2024	J	`jnl`	Training-time Neuron Alignment through Permutation Subspace for Improving Linear Mode Connectivity and Model Fusion. CoRR Zexi Li, Zhiqi Li, Jie Lin, Tao Shen, Tao Lin, Chao Wu
2023	J	`jnl`	Bridging the Gap: Neural Collapse Inspired Prompt Tuning for Generalization under Class Imbalance. CoRR Didi Zhu, Yinchuan Li, Min Zhang, Junkun Yuan, Jiashuo Liu, Zexi Li, Kun Kuang, Chao Wu
2023	A*	`conf`	Edge-cloud Collaborative Learning with Federated and Centralized Features. SIGIR Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu
2023	J	`jnl`	Edge-cloud Collaborative Learning with Federated and Centralized Features. CoRR Zexi Li, Qunwei Li, Yi Zhou, Wenliang Zhong, Guannan Zhang, Chao Wu
2023	J	`jnl`	FediOS: Decoupling Orthogonal Subspaces for Personalization in Feature-skew Federated Learning. CoRR Lingzhi Gao, Zexi Li, Yang Lu, Chao Wu
2023	A	`conf`	Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients. ICME Chenrui Wu, Zexi Li, Fangxin Wang, Chao Wu
2023	J	`jnl`	Learning Cautiously in Federated Learning with Noisy and Heterogeneous Clients. CoRR Chenrui Wu, Zexi Li, Fangxin Wang, Chao Wu
2023	A*	`conf`	No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier. ICCV Zexi Li, Xinyi Shang, Rui He, Tao Lin, Chao Wu
2023	J	`jnl`	No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier. CoRR Zexi Li, Xinyi Shang, Rui He, Tao Lin, Chao Wu
2023	A*	`conf`	Revisiting Weighted Aggregation in Federated Learning with Neural Networks. ICML Zexi Li, Tao Lin, Xinyi Shang, Chao Wu
2023	J	`jnl`	Revisiting Weighted Aggregation in Federated Learning with Neural Networks. CoRR Zexi Li, Tao Lin, Xinyi Shang, Chao Wu
2023	J	`jnl`	Scalable Geometric Fracture Assembly via Co-creation Space among Assemblers. CoRR Ruiyuan Zhang, Jiaxiang Liu, Zexi Li, Hao Dong, Jie Fu, Chao Wu
2023	A*	`conf`	Universal Domain Adaptation via Compressive Attention Matching. ICCV Didi Zhu, Yinchuan Li, Junkun Yuan, Zexi Li, Kun Kuang, Chao Wu
2023	J	`jnl`	Universal Domain Adaptation via Compressive Attention Matching. CoRR Didi Zhu, Yinchuan Li, Junkun Yuan, Zexi Li, Yunfeng Shao, Kun Kuang, Chao Wu
2022	J	`jnl`	Can we share models if sharing data is not an option? Patterns Zexi Li, Feng Mao, Chao Wu
2022	J	`jnl`	Mining Latent Relationships among Clients: Peer-to-peer Federated Learning with Adaptive Neighbor Matching. CoRR Zexi Li, Jiaxun Lu, Shuang Luo, Didi Zhu, Yunfeng Shao, Yinchuan Li, Zhimeng Zhang, Chao Wu
2021	J	`jnl`	Boosting the generalization ability of Vis-NIR-spectroscopy-based regression models through dimension reduction and transfer learning. Comput. Electron. Agric. Xiaoli Li, Zexi Li, Xufeng Yang, Yong He
2021	J	`jnl`	Ensemble Federated Adversarial Training with Non-IID data. CoRR Shuang Luo, Didi Zhu, Zexi Li, Chao Wu