Chuiyang Meng, Ming Tang, Vincent W. S. Wong

Academic · 1 min

ZorBA: Zeroth-order Federated Fine-tuning of LLMs with Heterogeneous Block Activation

arXiv:2603.04436v1 Announce Type: new Abstract: Federated fine-tuning of large language models (LLMs) enables collaborative tuning across distributed clients. However, due to the large size of …

10 views Mar 7

Academic · 1 min

ASFL: An Adaptive Model Splitting and Resource Allocation Framework for Split Federated Learning

arXiv:2603.04437v1 Announce Type: new Abstract: Federated learning (FL) enables multiple clients to collaboratively train a machine learning model without sharing their raw data. However, the …

Chuiyang Meng, Ming Tang, Vincent W. S. Wong

11 views Mar 7

Academic · 1 min

FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment

arXiv:2602.17095v1 Announce Type: new Abstract: Parameter-efficient fine-tuning techniques such as low-rank adaptation (LoRA) enable large language models (LLMs) to adapt to downstream tasks efficiently. Federated …

Chuiyang Meng, Ming Tang, Vincent W. S. Wong

15 views Feb 21

Chuiyang Meng, Ming Tang, Vincent W. S. Wong

Articles by Chuiyang Meng, Ming Tang, Vincent W. S. Wong

ZorBA: Zeroth-order Federated Fine-tuning of LLMs with Heterogeneous Block Activation

ASFL: An Adaptive Model Splitting and Resource Allocation Framework for Split Federated Learning

FLoRG: Federated Fine-tuning with Low-rank Gram Matrices and Procrustes Alignment

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