Yongxin Guo

According to our database, Yongxin Guo authored at least 22 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Personalized Federated Management and Load Balancing for Multiple Charging Stations.

Jie Liu, Yongxin Guo, Xi Leng, Xiaoying Tang

IEEE Trans. Ind. Informatics, August, 2025

G²RPO-A: Guided Group Relative Policy Optimization with Adaptive Guidance.

Yongxin Guo, Wenbo Deng, Zhenglin Cheng, Xiaoying Tang

CoRR, August, 2025

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

IEEE Trans. Knowl. Data Eng., July, 2025

Watch and Listen: Understanding Audio-Visual-Speech Moments with Multimodal LLM.

Zinuo Li, Xian Zhang, Yongxin Guo, Mohammed Bennamoun, Farid Boussaïd, Girish Dwivedi, Luqi Gong, Qiuhong Ke

CoRR, May, 2025

TRACE: Temporal Grounding Video LLM via Causal Event Modeling.

Yongxin Guo, Jingyu Liu, Mingda Li, Qingbin Liu, Xi Chen, Xiaoying Tang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models.

Yongxin Guo, Zhenglin Cheng, Xiaoying Tang, Zhaopeng Tu, Tao Lin

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Enhancing Clustered Federated Learning: Integration of Strategies and Improved Methodologies.

Yongxin Guo, Xiaoying Tang, Tao Lin

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding.

Yongxin Guo, Jingyu Liu, Mingda Li, Dingxin Cheng, Xiaoying Tang, Dianbo Sui, Qingbin Liu, Xi Chen, Kevin Zhao

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

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

CoRR, 2024

Smart Sampling: Helping from Friendly Neighbors for Decentralized Federated Learning.

Lin Wang, Yang Chen, Yongxin Guo, Xiaoying Tang

CoRR, 2024

Client2Vec: Improving Federated Learning by Distribution Shifts Aware Client Indexing.

Yongxin Guo, Lin Wang, Xiaoying Tang, Tao Lin

CoRR, 2024

VTG-LLM: Integrating Timestamp Knowledge into Video LLMs for Enhanced Video Temporal Grounding.

Yongxin Guo, Jingyu Liu, Mingda Li, Xiaoying Tang, Xi Chen, Bo Zhao

CoRR, 2024

FedRC: Tackling Diverse Distribution Shifts Challenge in Federated Learning by Robust Clustering.

Yongxin Guo, Xiaoying Tang, Tao Lin

Proceedings of the Forty-first International Conference on Machine Learning, 2024

FedMABA: Towards Fair Federated Learning through Multi-Armed Bandits Allocation.

Zhichao Wang, Lin Wang, Yongxin Guo, Ying-Jun Angela Zhang, Xiaoying Tang

Proceedings of the 24th IEEE International Conference on Communication Technology, 2024

2023

Find Your Optimal Assignments On-the-fly: A Holistic Framework for Clustered Federated Learning.

Yongxin Guo, Xiaoying Tang, Tao Lin

CoRR, 2023

FedConceptEM: Robust Federated Learning Under Diverse Distribution Shifts.

Yongxin Guo, Xiaoying Tang, Tao Lin

CoRR, 2023

PITPS: Balancing Local and Global Profits for Multiple Charging Stations Management.

Jie Liu, Yongxin Guo, Xiaoying Tang

Proceedings of the IEEE International Conference on Communications, 2023

DELTA: Diverse Client Sampling for Fasting Federated Learning.

Lin Wang, Yongxin Guo, Tao Lin, Xiaoying Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction.

Yongxin Guo, Xiaoying Tang, Tao Lin

Proceedings of the International Conference on Machine Learning, 2023

2022

Client Selection in Nonconvex Federated Learning: Improved Convergence Analysis for Optimal Unbiased Sampling Strategy.

Lin Wang, Yongxin Guo, Tao Lin, Xiaoying Tang

CoRR, 2022

FedAug: Reducing the Local Learning Bias Improves Federated Learning on Heterogeneous Data.

Yongxin Guo, Tao Lin, Xiaoying Tang

CoRR, 2022

2021

Towards Federated Learning on Time-Evolving Heterogeneous Data.

Yongxin Guo, Tao Lin, Xiaoying Tang

CoRR, 2021