1 citations · 1 across the 2 of their papers we have counts for
Showing cs.LGShow all
2 papers · 1 filter
cs.LG2024
Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
Xinyu Ma, Xu Chu, Zhibang Yang +3
With the increasingly powerful performances and enormous scales of pretrained models, promoting parameter efficiency in fine-tuning has become a crucial need for effective and effi…
cs.LG2024
LoRA Dropout as a Sparsity Regularizer for Overfitting Control
Yang Lin, Xinyu Ma, Xu Chu +4
Parameter-efficient fine-tuning methods, represented by LoRA, play an essential role in adapting large-scale pre-trained models to downstream tasks. However, fine-tuning LoRA-serie…