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cs.LG2025
FedORGP: Guiding Heterogeneous Federated Learning with Orthogonality Regularization on Global Prototypes
Fucheng Guo, Zeyu Luan, Qing Li +2
Federated Learning (FL) has emerged as an essential framework for distributed machine learning, especially with its potential for privacy-preserving data processing. However, exist…
cs.LG2024
Quantized Side Tuning: Fast and Memory-Efficient Tuning of Quantized Large Language Models
Zhengxin Zhang, Dan Zhao, Xupeng Miao +4
Finetuning large language models (LLMs) has been empirically effective on a variety of downstream tasks. Existing approaches to finetuning an LLM either focus on parameter-efficien…