Jingzhi Gong

29 papers A* 1A 1B 1Journal 25Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Analyzing Message-Code Inconsistency in AI Coding Agent-Authored Pull Requests.
CoRR
Jingzhi Gong, Giovanni Pinna, Yixin Bian, Jie M. Zhang
2026 J jnl
Comparing AI Coding Agents: A Task-Stratified Analysis of Pull Request Acceptance.
CoRR
Giovanni Pinna, Jingzhi Gong, David Williams, Federica Sarro
2026 J jnl
Not All Code Is Equal: A Data-Centric Study of Code Complexity and LLM Reasoning.
CoRR
Lukas Twist, Shu Yang, Hanqi Yan, Jingzhi Gong, Di Wang, Helen Yannakoudakis, Jie M. Zhang
2025 J jnl
AI Agentic Programming: A Survey of Techniques, Challenges, and Opportunities.
CoRR
Huanting Wang, Jingzhi Gong, Huawei Zhang, Zheng Wang
2025 J jnl
Accuracy Can Lie: On the Impact of Surrogate Model in Configuration Tuning.
CoRR
Pengzhou Chen, Jingzhi Gong, Tao Chen
2025 J jnl
Accuracy Can Lie: On the Impact of Surrogate Model in Configuration Tuning.
IEEE Trans. Software Eng.
Pengzhou Chen, Jingzhi Gong, Tao Chen
2025 J jnl
Deep Configuration Performance Learning: A Systematic Survey and Taxonomy.
ACM Trans. Softw. Eng. Methodol.
Jingzhi Gong, Tao Chen
2025 J jnl
Dividable Configuration Performance Learning.
IEEE Trans. Software Eng.
Jingzhi Gong, Tao Chen, Rami Bahsoon
2025 J jnl
Dually Hierarchical Drift Adaptation for Online Configuration Performance Learning.
CoRR
Zezhen Xiang, Jingzhi Gong, Tao Chen
2025 J jnl
Enhancing Trust in Language Model-Based Code Optimization through RLHF: A Research Design.
CoRR
Jingzhi Gong
2025 J jnl
Ensemble Learning for Large Language Models in Text and Code Generation: A Survey.
CoRR
Mari Ashiga, Wei Jie, Fan Wu, Vardan Voskanyan, Fateme Dinmohammadi, Paul Brookes, Jingzhi Gong, Zheng Wang
2025 J jnl
Evolving Excellence: Automated Optimization of LLM-based Agents.
CoRR
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
2025 J jnl
GA4GC: Greener Agent for Greener Code via Multi-Objective Configuration Optimization.
CoRR
Jingzhi Gong, Yixin Bian, Luis De La Cal, Giovanni Pinna, Anisha Uteem, David Williams, Mar Zamorano, Karine Even-Mendoza, William B. Langdon, Héctor Menéndez, Federica Sarro
2025 J jnl
Industrial LLM-based Code Optimization under Regulation: A Mixture-of-Agents Approach.
CoRR
Mari Ashiga, Vardan Voskanyan, Fateme Dinmohammadi, Jingzhi Gong, Paul Brookes, Matthew Truscott, Rafail Giavrimis, Mike Basios, Leslie Kanthan, Wei Jie
2025 J jnl
Language Models for Code Optimization: Survey, Challenges and Future Directions.
CoRR
Jingzhi Gong, Vardan Voskanyan, Paul Brookes, Fan Wu, Wei Jie, Jie Xu, Rafail Giavrimis, Mike Basios, Leslie Kanthan, Zheng Wang
2025 J jnl
Learning Software Bug Reports: A Systematic Literature Review.
CoRR
Guoming Long, Jingzhi Gong, Hui Fang, Tao Chen
2025 A* conf
Tuning LLM-based Code Optimization via Meta-Prompting: An Industrial Perspective.
ASE
Jingzhi Gong, Rafail Giavrimis, Paul Brookes, Vardan Voskanyan, Fan Wu, Mari Ashiga, Matthew Truscott, Mike Basios, Leslie Kanthan, Jie Xu, Zheng Wang
2025 J jnl
Tuning LLM-based Code Optimization via Meta-Prompting: An Industrial Perspective.
CoRR
Jingzhi Gong, Rafail Giavrimis, Paul Brookes, Vardan Voskanyan, Fan Wu, Mari Ashiga, Matthew Truscott, Mike Basios, Leslie Kanthan, Jie Xu, Zheng Wang
2024 J jnl
Deep Configuration Performance Learning: A Systematic Survey and Taxonomy.
CoRR
Jingzhi Gong, Tao Chen
2024 J jnl
Dividable Configuration Performance Learning.
CoRR
Jingzhi Gong, Tao Chen, Rami Bahsoon
2024 B conf
GreenStableYolo: Optimizing Inference Time and Image Quality of Text-to-Image Generation.
SSBSE
Jingzhi Gong, Sisi Li, Giordano d'Aloisio, Zishuo Ding, Yulong Ye, William B. Langdon, Federica Sarro
2024 J jnl
GreenStableYolo: Optimizing Inference Time and Image Quality of Text-to-Image Generation.
CoRR
Jingzhi Gong, Sisi Li, Giordano d'Aloisio, Zishuo Ding, Yulong Ye, William B. Langdon, Federica Sarro
2024 J jnl
Predicting Configuration Performance in Multiple Environments with Sequential Meta-Learning.
Proc. ACM Softw. Eng.
Jingzhi Gong, Tao Chen
2024 J jnl
Predicting Configuration Performance in Multiple Environments with Sequential Meta-learning.
CoRR
Jingzhi Gong, Tao Chen
2024 J jnl
Pushing the Boundary: Specialising Deep Configuration Performance Learning.
CoRR
Jingzhi Gong
2023 — conf
Predicting Software Performance with Divide-and-Learn.
ESEC/SIGSOFT FSE
Jingzhi Gong, Tao Chen
2023 J jnl
Predicting Software Performance with Divide-and-Learn.
CoRR
Jingzhi Gong, Tao Chen
2022 A conf
Does Configuration Encoding Matter in Learning Software Performance? An Empirical Study on Encoding Schemes.
MSR
Jingzhi Gong, Tao Chen
2022 J jnl
Does Configuration Encoding Matter in Learning Software Performance? An Empirical Study on Encoding Schemes.
CoRR
Jingzhi Gong, Tao Chen