most citedDelving into Parameter-Efficient Fine-Tuning in Code Change Learning: An Empirical Study

2 citations · 2 across the 1 of their papers we have counts for

collaborators

1 paper

cs.SE2024★ 2 cited

Delving into Parameter-Efficient Fine-Tuning in Code Change Learning: An Empirical Study

Shuo Liu, Jacky Keung, Zhen Yang +3

Compared to Full-Model Fine-Tuning (FMFT), Parameter Efficient Fine-Tuning (PEFT) has demonstrated superior performance and lower computational overhead in several code understandi…