Jiexin Wang

With the rapid advancement of large language models (LLMs), automated code generation has made remarkable progress. Recent studies explore multi-agent collaboration and adopt planning–coding–debugging workflows to enhance performance. However, these approaches are constrained by rigid, predefined...

Large Language Models (LLMs) have shown remarkable capabilities in automating code generation. Recent approaches that incorporate feedback refinement mechanisms into the generation process have further enhanced software generation quality. However, these methods can be characterized as single-pat...

Repository-level code generation has attracted growing interest, yet most benchmarks and methods remain maintainer-centric, emphasizing bug fixing and feature implementation. In contrast, a common yet underexplored scenario is repository usage: external users want to build applications by correct...