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

2 citations · 4 across the 2 of their papers we have counts for

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cs.SE2024★ 2 cited

NARRepair: Non-Autoregressive Code Generation Model for Automatic Program Repair

Zhenyu Yang, Zhen Yang, Zhongxing Yu

With the advancement of deep learning techniques, the performance of Automatic Program Repair(APR) techniques has reached a new level. Previous deep learning-based APR techniques e…

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…