About
I am a second-year CS Ph.D. student at the University of Illinois Urbana-Champaign in the PL/FM/SE group, advised by Prof. Lingming Zhang.
My research interest lies in Software Engineering and its synergy with Machine Learning, with a focus on improving software engineering with generative models. You can find my CV here.
I obtained my bachelor’s degrees at Tsinghua University, including one in Software Engineering from the School of Software and one in Business Administration from the School of Economics and Management. I was a research assistant at Software System Security Assurance Group during my undergraduate years, advised by Prof. Yu Jiang.
Selected Publications
- ${\mathcal X}$FT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts
Yifeng Ding, Jiawei Liu, Yuxiang Wei, and Lingming Zhang
62nd Annual Meeting of the Association for Computational Linguistics
(ACL 2024), To appear, August 2024. [preprint] (published version to appear) - Magicoder: Source Code Is All You Need
Yuxiang Wei, Zhe Wang, Jiawei Liu, Yifeng Ding, and Lingming Zhang
Forty-first International Conference on Machine Learning
(ICML 2024), To appear, July 2024. [preprint] (published version to appear) - The Plastic Surgery Hypothesis in the Era of Large Language Models
Chunqiu Steven Xia, Yifeng Ding, and Lingming Zhang
38th IEEE/ACM International Conference on Automated Software Engineering
(ASE 2023), Pages 522–534, September 2023. [paper] - CoopHance: Cooperative Enhancement for Robustness of Deep Learning Systems
Quan Zhang, Yongqiang Tian, Yifeng Ding, Shanshan Li, Chengnian Sun, Yu Jiang, Jiaguang Sun
32nd ACM International Symposium on Software Testing and Analysis
(ISSTA 2023), Pages 753–765, July 2023. [paper] - AdvDoor: Adversarial Backdoor Attack of Deep Learning System
Quan Zhang, Yifeng Ding, Yongqiang Tian, Jianmin Guo, Min Yuan, Yu Jiang
30th ACM International Symposium on Software Testing and Analysis
(ISSTA 2021), Pages 127–138, July 2021. [paper]
Academic Service
- Reviewer: NAACL/ARR 2024 Jun, NeurIPS 2024, ACL/ARR 2024 Feb
- Organizing Committee: LLM4Code@ICSE’24
Talk
- AWS Comprehend - Deep NLP Reading Group: ${\mathcal X}$FT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts
- Uber Programming Systems Team: Equipping Large Language Models with Domain-Specific Knowledge for Automated Program Repair.
Contacts
- Email: yifeng6@illinois.edu
- Address: 2107 Thomas M. Siebel Center for Computer Science