LLMs have demonstrated significant potential in code generation tasks, achieving promising
results at the function or statement level in various benchmarks. However, the complexities …

Large Language Models (LLMs) have shown promise in automated code generation but
typically excel only in simpler tasks such as generating standalone code units. Real-world …

Large language models (LLMs) have demonstrated remarkable capabilities in code
generation tasks. However, repository-level code generation presents unique challenges …

Abstract Despite Large Language Models (LLMs) like GPT-4 achieving impressive results in
function-level code generation, they struggle with repository-scale code understanding (eg …

As coding challenges become more complex, recent advancements in Large Language
Models (LLMs) have led to notable successes, such as achieving a 94.6\% solve rate on the …

Generative models have demonstrated considerable potential in software engineering,
particularly in tasks such as code generation and debugging. However, their utilization in the …

Code generation tools are essential to help developers in the software development
process. Existing tools often disconnect with the working context, ie, the code repository …

Recent code large language models (LLMs) have shown promising performance in
generating standalone functions but face limitations in repository-level code generation due …

While language models (LMs) have proven remarkably adept at generating code, many
programs are challenging for LMs to generate using their parametric knowledge alone …

To evaluate the code generation capabilities of Large Language Models (LLMs) in complex
real-world software development scenarios, many evaluation approaches have been …