15 citations · 22 across the 6 of their papers we have counts for
8 papers
A Viable Paradigm of Software Automation: Iterative End-to-End Automated Software Development
Jia Li, Zhi Jin, Huangzhao Zhang +3
Software development automation is a long-term goal in software engineering. With the development of artificial intelligence (AI), more and more researchers are exploring approache…
StackTrans: From Large Language Model to Large Pushdown Automata Model
Kechi Zhang, Ge Li, Jia Li +4
The Transformer architecture has emerged as a landmark advancement within the broad field of artificial intelligence, effectively catalyzing the advent of large language models (LL…
Computational Thinking Reasoning in Large Language Models
Kechi Zhang, Ge Li, Jia Li +8
While large language models (LLMs) have demonstrated remarkable reasoning capabilities, they often struggle with complex tasks that require specific thinking paradigms, such as div…
SEAlign: Alignment Training for Software Engineering Agent
Kechi Zhang, Huangzhao Zhang, Ge Li +4
Recent advances in code generation models have demonstrated impressive capabilities in automating software development tasks, yet these models still struggle in real-world software…
HiRoPE: Length Extrapolation for Code Models Using Hierarchical Position
Kechi Zhang, Ge Li, Huangzhao Zhang +1
Addressing the limitation of context length in large language models for code-related tasks is the primary focus of this paper. Existing LLMs are constrained by their pre-trained c…
Large Language Model-Aware In-Context Learning for Code Generation
Jia Li, Ge Li, Chongyang Tao +3
Large language models (LLMs) have shown impressive in-context learning (ICL) ability in code generation. LLMs take a prompt consisting of requirement-code examples and a new requir…