5 citations · 5 across the 9 of their papers we have counts for
16 papers
An Empirical Study of Interaction Smells in Multi-Turn Human-LLM Collaborative Code Generation
Binquan Zhang, Li Zhang, Lin Shi +6
Large Language Models (LLMs) have revolutionized code generation, evolving from static tools into dynamic conversational interfaces that facilitate complex, multi-turn collaborativ…
A Scalable Benchmark for Repository-Oriented Long-Horizon Conversational Context Management
Yang Liu, Li Zhang, Fang Liu +2
In recent years, large language models (LLMs) have advanced rapidly, substantially enhancing their code understanding and generation capabilities and giving rise to powerful code a…
CodeMEM: AST-Guided Adaptive Memory for Repository-Level Iterative Code Generation
Peiding Wang, Li Zhang, Fang Liu +2
Large language models (LLMs) substantially enhance developer productivity in repository-level code generation through interactive collaboration. However, as interactions progress,…
Aligning Academia with Industry: An Empirical Study of Industrial Needs and Academic Capabilities in AI-Driven Software Engineering
Hang Yu, Yuzhou Lai, Li Zhang +6
The rapid advancement of large language models (LLMs) is fundamentally reshaping software engineering (SE), driving a paradigm shift in both academic research and industrial practi…
Towards Realistic Project-Level Code Generation via Multi-Agent Collaboration and Semantic Architecture Modeling
Qianhui Zhao, Li Zhang, Fang Liu +8
In recent years, Large Language Models (LLMs) have achieved remarkable progress in automated code generation. In real-world software engineering, the growing demand for rapid itera…
SecureReviewer: Enhancing Large Language Models for Secure Code Review through Secure-aware Fine-tuning
Fang Liu, Simiao Liu, Yinghao Zhu +2
Identifying and addressing security issues during the early phase of the development lifecycle is critical for mitigating the long-term negative impacts on software systems. Code r…