Yebo Wu

According to our database, Yebo Wu authored at least 18 papers between 2024 and 2026.

Collaborative distances:

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

2026

Spotlight and Shadow: Attention-Guided Dual-Anchor Introspective Decoding for MLLM Hallucination Mitigation.

Yebo Wu, Han Jin, Zhijiang Guo, Li Li

CoRR, April, 2026

Beyond End-to-End: Dynamic Chain Optimization for Private LLM Adaptation on the Edge.

Yebo Wu, Jingguang Li, Chunlin Tian, Kahou Tam, Zhijiang Guo, Li Li

CoRR, April, 2026

TSEmbed: Unlocking Task Scaling in Universal Multimodal Embeddings.

Yebo Wu, Feng Liu, Ziwei Xie, Zhiyuan Liu, Changwang Zhang, Jun Wang, Li Li

CoRR, March, 2026

Floe: Federated Specialization for Real-Time LLM-SLM Inference.

Chunlin Tian, Kahou Tam, Yebo Wu, Shuaihang Zhong, Li Li, Nicholas D. Lane, Cheng-Zhong Xu

CoRR, February, 2026

A Survey on Federated Fine-Tuning of Large Language Models.

Yebo Wu, Chunlin Tian, Jingguang Li, He Sun, KaHou Tam, Zhanting Zhou, Haicheng Liao, Jing Xiong, Zhijiang Guo, Li Li, Cheng-Zhong Xu

Trans. Mach. Learn. Res., 2026

2025

Elastic Mixture of Rank-Wise Experts for Knowledge Reuse in Federated Fine-Tuning.

Yebo Wu, Jingguang Li, Zhijiang Guo, Li Li

CoRR, December, 2025

Memory-Efficient Federated Fine-Tuning of Large Language Models via Layer Pruning.

Yebo Wu, Jingguang Li, Chunlin Tian, Zhijiang Guo, Li Li

CoRR, August, 2025

Learning Like Humans: Resource-Efficient Federated Fine-Tuning through Cognitive Developmental Stages.

Yebo Wu, Jingguang Li, Zhijiang Guo, Li Li

CoRR, August, 2025

A Survey on Federated Fine-tuning of Large Language Models.

Yebo Wu, Chunlin Tian, Jingguang Li, He Sun, Kahou Tam, Li Li, Chengzhong Xu

CoRR, March, 2025

Indoor Localization Fusing Inertial Navigation With Monocular Depth Estimation in Federated Learning Framework With Data Heterogeneity.

Jie Wang, Xiaolong Wu, Jindong Tian, Erwu Liu, Yebo Wu, Rucong Lai, Yong Tian

IEEE Trans. Instrum. Meas., 2025

Breaking the Memory Wall for Heterogeneous Federated Learning via Progressive Training.

Yebo Wu, Li Li, Cheng-Zhong Xu

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

2024

Breaking the Memory Wall for Heterogeneous Federated Learning via Model Splitting.

Chunlin Tian, Li Li, Kahou Tam, Yebo Wu, Cheng-Zhong Xu

IEEE Trans. Parallel Distributed Syst., December, 2024

FedINS2: A Federated-Edge-Learning-Based Inertial Navigation System With Segment Fusion.

Jie Wang, Yebo Wu, Erwu Liu, Xiaolong Wu, Xinyu Qu, Yuanzhe Geng, Hanfu Zhang

IEEE Internet Things J., January, 2024

NeuLite: Memory-Efficient Federated Learning via Elastic Progressive Training.

Yebo Wu, Li Li, Chunlin Tian, Dubing Chen, Chengzhong Xu

CoRR, 2024

Heterogeneity-Aware Memory Efficient Federated Learning via Progressive Layer Freezing.

Yebo Wu, Li Li, Chunlin Tian, Chang Tao, Lin Chi, Wang Cong, Cheng-Zhong Xu

CoRR, 2024

Breaking the Memory Wall for Heterogeneous Federated Learning with Progressive Training.

Yebo Wu, Li Li, Chunlin Tian, Chengzhong Xu

CoRR, 2024

Heterogeneity-Aware Coordination for Federated Learning via Stitching Pre-trained blocks.

Shichen Zhan, Yebo Wu, Chunlin Tian, Yan Zhao, Li Li

Proceedings of the 32nd IEEE/ACM International Symposium on Quality of Service, 2024

Heterogeneity-Aware Memory Efficient Federated Learning via Progressive Layer Freezing.

Yebo Wu, Li Li, Chunlin Tian, Chang Tao, Chi Lin, Wang Cong, Cheng-Zhong Xu

Proceedings of the 32nd IEEE/ACM International Symposium on Quality of Service, 2024