A Comprehensive Evaluation of Parameter-Efficient Fine-Tuning on Software Engineering Tasks

1 code implementation • 25 Dec 2023 • Wentao Zou, Qi Li, Jidong Ge, Chuanyi Li, Xiaoyu Shen, LiGuo Huang, Bin Luo

We hope that our findings can provide a deeper understanding of PEFT methods on various PTMs and SE downstream tasks.

parameter-efficient fine-tuning

Learning the Relation between Similarity Loss and Clustering Loss in Self-Supervised Learning

1 code implementation • 8 Jan 2023 • Jidong Ge, Yuxiang Liu, Jie Gui, Lanting Fang, Ming Lin, James Tin-Yau Kwok, LiGuo Huang, Bin Luo

However, the relation between these two losses is not clear.

Clustering Contrastive Learning +2

Synergy between Machine/Deep Learning and Software Engineering: How Far Are We?

no code implementations • 12 Aug 2020 • Simin Wang, LiGuo Huang, Jidong Ge, Tengfei Zhang, Haitao Feng, Ming Li, He Zhang, Vincent Ng

To improve the applicability and generalizability of research results, we analyzed what ingredients in a study would facilitate an understanding of why a ML/DL technique was selected for a specific SE problem.

Recovering Traceability Links in Requirements Documents

no code implementations • CONLL 2015 • Zeheng Li, Mingrui Chen, LiGuo Huang, Vincent Ng