Jingzhi Gong

According to our database, Jingzhi Gong authored at least 24 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

How Does Chunking Affect Retrieval-Augmented Code Completion? A Controlled Empirical Study.

Xinjian Wu, Jingzhi Gong, Gunel Jahangirova, Jie Zhang

CoRR, May, 2026

SkillMOO: Multi-Objective Optimization of Agent Skills for Software Engineering.

Jingzhi Gong, Ruizhen Gu, Zhiwei Fei, Yazhuo Cao, Lukas Twist, Alina Geiger, Shuo Han, Dominik Sobania, Federica Sarro, Jie M. Zhang

CoRR, April, 2026

Benchmarking and Evaluating VLMs for Software Architecture Diagram Understanding.

Shuyin Ouyang, Jie M. Zhang, Jingzhi Gong, Gunel Jahangirova, Mohammad Reza Mousavi, Jack Johns, Beum Seuk Lee, Adam Ziolkowski, Botond Virginas, Joost Noppen

CoRR, April, 2026

Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance.

Giovanni Pinna, Jingzhi Gong, David Williams, Federica Sarro

CoRR, February, 2026

Not All Code Is Equal: A Data-Centric Study of Code Complexity and LLM Reasoning.

Lukas Twist, Shu Yang, Hanqi Yan, Jingzhi Gong, Di Wang, Helen Yannakoudakis, Jie M. Zhang

CoRR, January, 2026

Analyzing Message-Code Inconsistency in AI Coding Agent-Authored Pull Requests.

Jingzhi Gong, Giovanni Pinna, Yixin Bian, Jie M. Zhang

CoRR, January, 2026

2025

Evolving Excellence: Automated Optimization of LLM-based Agents.

Paul Brookes, Vardan Voskanyan, Rafail Giavrimis, Matthew Truscott, Mina Ilieva, Chrystalla Pavlou, Alexandru Staicu, Manal Adham, Will Evers-Hood, Jingzhi Gong, Kejia Zhang, Matvey Fedoseev, Vishal Sharma, Roman Bauer, Zheng Wang, Hema Nair, Wei Jie, Tianhua Xu, Aurora Constantin, Leslie Kanthan, Michail Basios

CoRR, December, 2025

AI Agentic Programming: A Survey of Techniques, Challenges, and Opportunities.

Huanting Wang, Jingzhi Gong, Huawei Zhang, Zheng Wang

CoRR, August, 2025

Industrial LLM-based Code Optimization under Regulation: A Mixture-of-Agents Approach.

Mari Ashiga, Vardan Voskanyan, Fateme Dinmohammadi, Jingzhi Gong, Paul Brookes, Matthew Truscott, Rafail Giavrimis, Mike Basios, Leslie Kanthan, Wei Jie

CoRR, August, 2025

Dually Hierarchical Drift Adaptation for Online Configuration Performance Learning.

Zezhen Xiang, Jingzhi Gong, Tao Chen

CoRR, July, 2025

Learning Software Bug Reports: A Systematic Literature Review.

Guoming Long, Jingzhi Gong, Hui Fang, Tao Chen

CoRR, July, 2025

Ensemble Learning for Large Language Models in Text and Code Generation: A Survey.

Mari Ashiga, Wei Jie, Fan Wu, Vardan Voskanyan, Fateme Dinmohammadi, Paul Brookes, Jingzhi Gong, Zheng Wang

CoRR, March, 2025

Accuracy Can Lie: On the Impact of Surrogate Model in Configuration Tuning.

Pengzhou Chen, Jingzhi Gong, Tao Chen

IEEE Trans. Software Eng., February, 2025

Enhancing Trust in Language Model-Based Code Optimization through RLHF: A Research Design.

Jingzhi Gong

CoRR, February, 2025

Dividable Configuration Performance Learning.

Jingzhi Gong, Tao Chen, Rami Bahsoon

IEEE Trans. Software Eng., January, 2025

Deep Configuration Performance Learning: A Systematic Survey and Taxonomy.

Jingzhi Gong, Tao Chen

ACM Trans. Softw. Eng. Methodol., January, 2025

Language Models for Code Optimization: Survey, Challenges and Future Directions.

Jingzhi Gong, Vardan Voskanyan, Paul Brookes, Fan Wu, Wei Jie, Jie Xu, Rafail Giavrimis, Mike Basios, Leslie Kanthan, Zheng Wang

CoRR, January, 2025

GA4GC: Greener Agent for Greener Code via Multi-objective Configuration Optimization.

Jingzhi Gong, Yixin Bian, Luis De La Cal, Giovanni Pinna, Anisha Uteem, David Williams, Mar Zamorano, Karine Even-Mendoza, William B. Langdon, Héctor D. Menéndez, Federica Sarro

Proceedings of the Search-Based Software Engineering, 2025

Tuning LLM-based Code Optimization via Meta-Prompting: An Industrial Perspective.

Jingzhi Gong, Rafail Giavrimis, Paul Brookes, Vardan Voskanyan, Fan Wu, Mari Ashiga, Matthew Truscott, Mike Basios, Leslie Kanthan, Jie Xu, Zheng Wang

Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering, 2025

2024

Predicting Configuration Performance in Multiple Environments with Sequential Meta-Learning.

Jingzhi Gong, Tao Chen

Proc. ACM Softw. Eng., 2024

Pushing the Boundary: Specialising Deep Configuration Performance Learning.

Jingzhi Gong

CoRR, 2024

GreenStableYolo: Optimizing Inference Time and Image Quality of Text-to-Image Generation.

Jingzhi Gong, Sisi Li, Giordano d'Aloisio, Zishuo Ding, Yulong Ye, William B. Langdon, Federica Sarro

Proceedings of the Search-Based Software Engineering - 16th International Symposium, 2024

2023

Predicting Software Performance with Divide-and-Learn.

Jingzhi Gong, Tao Chen

Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2023

2022

Does Configuration Encoding Matter in Learning Software Performance? An Empirical Study on Encoding Schemes.

Jingzhi Gong, Tao Chen

Proceedings of the 19th IEEE/ACM International Conference on Mining Software Repositories, 2022