Publications

$^{*}$ indicates equal contribution.

Conference papers

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing
Yongxin Guo, Lin Wang, Xiaoying Tang, and Tao Lin

Camouflaged Variational Graph AutoEncoder against Attribute Inference Attacks for Cross-Domain Recommendation
Yudi Xiong, Yongxin Guo, Weike Pan, Qiang Yang, Zhong Ming, Xiaojin Zhang, Han Yu, Tao Lin, Xiaoying Tang

Personalized Federated Management and Load Balancing for Multiple Charging Stations
Jie Liu; Yongxin Guo; Xi Leng; Xiaoying Tang

Enhancing Long Video Understanding via Hierarchical Event-Based Memory
Dingxin Cheng, Mingda Li, Jingyu Liu, Yongxin Guo, Bin Jiang, Qingbin Liu, Xi Chen, Bo Zhao

TRACE: Temporal Grounding Video LLM via Casual Event Modeling
Yongxin Guo, Jingyu Liu, Mingda Li, Xiaoying Tang, Qingbin Liu, Xi Chen

Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
Yongxin Guo, Zhenglin Cheng, Xiaoying Tang, and Tao Lin

Find Your Optimal Assignments On-the-fly: A Holistic Framework for Clustered Federated Learning
Yongxin Guo, Xiaoying Tang, and Tao Lin

VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding
Yongxin Guo, Jingyu Liu, Mingda Li, Xiaoying Tang, Xi Chen, and Kevin Zhao

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering
Yongxin Guo, Xiaoying Tang, and Tao Lin

DELTA: Diverse Client Sampling for Fasting Federated Learning
Lin Wang, YongXin Guo, Tao Lin, and Xiaoying Tang

FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction
Yongxin Guo, Xiaoying Tang, and Tao Lin

PITPS: Balancing Local and Global Profits for Multiple Charging Stations Management
Jie Liu, Yongxin Guo, and Xiaoying Tang

Preprint & Under review papers

Towards Federated Learning on Time-Evolving Heterogeneous Data
Yongxin Guo, Tao Lin, and Xiaoying Tang