2 papers
cs.LG2025
PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
Sunghyeon Woo, Sol Namkung, Sunwoo Lee +3
Prior parameter-efficient fine-tuning (PEFT) algorithms reduce memory usage and computational costs of fine-tuning large neural network models by training only a few additional ada…
cs.LG2025
DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
Sunghyeon Woo, Baeseong Park, Byeongwook Kim +4
Large language models (LLMs) have achieved significant success across various domains. However, training these LLMs typically involves substantial memory and computational costs du…