3 citations · 3 across the 3 of their papers we have counts for
Showing cs.CLShow all
2 papers · 1 filter
cs.CL2026
Gradient Mirage: Trainable yet Label-Unidentifiable Gradients in Large Language Model Split Learning
Shiyu Miao, Yunlong Mao, Zirui Huang +5
Gradient matching attacks (GMAs) in LLM split learning (SL) rely on a critical yet underexplored assumption: the gradient exposed at the split interface is a faithful derivative of…
cs.CL2023★ 3 cited
A Split-and-Privatize Framework for Large Language Model Fine-Tuning
Xicong Shen, Yang Liu, Huiqi Liu +6
Fine-tuning is a prominent technique to adapt a pre-trained language model to downstream scenarios. In parameter-efficient fine-tuning, only a small subset of modules are trained o…