Kahou Tam

According to our database, Kahou Tam authored at least 19 papers between 2023 and 2026.

Collaborative distances:

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

2026

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

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

IEEE Trans. Parallel Distributed Syst., July, 2026

TRU: Targeted Reverse Update for Efficient Multimodal Recommendation Unlearning.

Zhanting Zhou, KaHou Tam, Ziqiang Zheng, Zeyu Ma, Yang Yang

CoRR, April, 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

FBLayout: Optimizing Memory Layout for Efficient LLM Finetuning on Mobile GPUs.

Kahou Tam, Wei Niu, Yu Bao, Xiaomin Ouyang, ChengZhong Xu, Li Li

Proceedings of the 24th Annual International Conference on Mobile Systems, 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

Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

2025

FedIA: A Plug-and-Play Importance-Aware Gradient Pruning Aggregation Method for Domain-Robust Federated Graph Learning on Node Classification.

Zhanting Zhou, KaHou Tam, Zeqin Wu, Pengzhao Sun, Jinbo Wang, Fengli Zhang

CoRR, September, 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

Federated Noisy Client Learning.

Kahou Tam, Li Li, Bo Han, Cheng-Zhong Xu, Huazhu Fu

IEEE Trans. Neural Networks Learn. Syst., January, 2025

CLONE: Customizing LLMs for Efficient Latency-Aware Inference at the Edge.

Chunlin Tian, Xinpeng Qin, Kahou Tam, Li Li, Zijian Wang, Yuanzhe Zhao, Minglei Zhang, Chengzhong Xu

Proceedings of the 2025 USENIX Annual Technical Conference, 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

When, Where, and What? A Novel Benchmark for Accident Anticipation and Localization with Large Language Models.

Haicheng Liao, Yongkang Li, Chengyue Wang, Yanchen Guan, KaHou Tam, Chunlin Tian, Li Li, Chengzhong Xu, Zhenning Li

CoRR, 2024

Towards Federated Domain Unlearning: Verification Methodologies and Challenges.

Kahou Tam, Kewei Xu, Li Li, Huazhu Fu

CoRR, 2024

Characterized Diffusion and Spatial-Temporal Interaction Network for Trajectory Prediction in Autonomous Driving.

Haicheng Liao, Xuelin Li, Yongkang Li, Hanlin Kong, Chengyue Wang, Bonan Wang, Yanchen Guan, KaHou Tam, Zhenning Li, Chengzhong Xu

CoRR, 2024

FedHybrid: Breaking the Memory Wall of Federated Learning via Hybrid Tensor Management.

Kahou Tam, Chunlin Tian, Li Li, Haikai Zhao, Chengzhong Xu

Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems, 2024

CRASH: Crash Recognition and Anticipation System Harnessing with Context-Aware and Temporal Focus Attentions.

Haicheng Liao, Haoyu Sun, Huanming Shen, Chengyue Wang, Chunlin Tian, KaHou Tam, Li Li, Chengzhong Xu, Zhenning Li

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

When, Where, and What? A Benchmark for Accident Anticipation and Localization with Large Language Models.

Haicheng Liao, Yongkang Li, Chengyue Wang, Yanchen Guan, Kahou Tam, Chunlin Tian, Li Li, Chengzhong Xu, Zhenning Li

Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

CDSTraj: Characterized Diffusion and Spatial-Temporal Interaction Network for Trajectory Prediction in Autonomous Driving.

Haicheng Liao, Xuelin Li, Yongkang Li, Hanlin Kong, Chengyue Wang, Bonan Wang, Yanchen Guan, KaHou Tam, Zhenning Li

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023

Breaking On-device Training Memory Wall: A Systematic Survey.

Shitian Li, Chunlin Tian, Kahou Tam, Rui Ma, Li Li

CoRR, 2023

FedCoop: Cooperative Federated Learning for Noisy Labels.

Kahou Tam, Li Li, Yan Zhao, Chengzhong Xu

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023