The following publications are possibly variants of this publication:
- On the Evaluation of Commit Message Generation Models: An Experimental StudyWei Tao, Yanlin Wang, Ensheng Shi, Lun Du, Shi Han, Hongyu Zhang 0002, Dongmei Zhang, Wenqiang Zhang. ICSM 2021: 126-136 [doi]
- A large-scale empirical study of commit message generation: models, datasets and evaluationWei Tao 0003, Yanlin Wang 0001, Ensheng Shi, Lun Du, Shi Han, Hongyu Zhang 0002, Dongmei Zhang 0001, Wenqiang Zhang. ese, 27(7):198, 2022. [doi]
- Revisiting Learning-based Commit Message GenerationJinhao Dong, Yiling Lou, Dan Hao 0001, Lin Tan 0001. ICSE 2023: 794-805 [doi]
- RACE: Retrieval-augmented Commit Message GenerationEnsheng Shi, Yanlin Wang, Wei Tao 0003, Lun Du, Hongyu Zhang, Shi Han, Dongmei Zhang, Hongbin Sun 0001. emnlp 2022: 5520-5530 [doi]
- Quality Assurance for Automated Commit Message GenerationBei Wang, Meng Yan, Zhongxin Liu, Ling Xu, Xin Xia 0001, Xiaohong Zhang 0002, Dan Yang 0001. WCRE 2021: 260-271 [doi]
- COME: Commit Message Generation with Modification EmbeddingYichen He, Liran Wang, Kaiyi Wang, Yupeng Zhang, Hang Zhang, Zhoujun Li 0001. ISSTA 2023: 792-803 [doi]
- Commit Message Generation for Source Code ChangesShengbin Xu, Yuan Yao 0001, Feng Xu 0007, Tianxiao Gu, Hanghang Tong, Jian Lu 0001. IJCAI 2019: 3975-3981 [doi]