1 citations · 1 across the 5 of their papers we have counts for
5 papers
Persistent Cross-Attempt State Optimization for Repository-Level Code Generation
Ruwei Pan, Jiangshuai Wang, Qisheng Zhang +6
Large language models (LLMs) have achieved substantial progress in repository-level code generation. However, solving the same repository-level task often requires multiple attempt…
Toward Executable Repository-Level Code Generation via Environment Alignment
Ruwei Pan, Junlei Shen, Linhao Wu +5
Large language models (LLMs) have achieved strong performance on code generation, but existing methods still struggle with repository-level code generation under executable validat…
Toward Functional and Non-Functional Evaluation of Application-Level Code Generation
Ruwei Pan, Yakun Zhang, Qingyuan Liang +4
Large language models (LLMs) have achieved strong performance on code generation. However, most prior evaluations focus on snippet-level outputs, such as function generation or rep…
AdaCoder: An Adaptive Planning and Multi-Agent Framework for Function-Level Code Generation
Yueheng Zhu, Chao Liu, Xuan He +4
Recently, researchers have proposed many multi-agent frameworks for function-level code generation, which aim to improve software development productivity by automatically generati…
Fixing Function-Level Code Generation Errors for Foundation Large Language Models
Hao Wen, Yueheng Zhu, Chao Liu +3
Function-level code generation leverages foundation Large Language Models (LLMs) to automatically produce source code with expected functionality. It has been widely investigated a…