Publications

$^{*}$ indicates equal contribution.

Conference papers

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

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

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