Large Language Models (LLMs) have significantly impacted numerous domains, including
Software Engineering (SE). Many recent publications have explored LLMs applied to …

Large language models (LLMs) have dramatically enhanced the field of language
intelligence, as demonstrably evidenced by their formidable empirical performance across a …

There is considerable confusion about the role of Large Language Models (LLMs) in
planning and reasoning tasks. On one side are over-optimistic claims that LLMs can indeed …

Large Language Models (LLMs) have demonstrated exceptional coding capability.
However, as another critical component of programming proficiency, the debugging …

The computational challenges of Large Language Model (LLM) inference remain a
significant barrier to their widespread deployment, especially as prompt lengths continue to …

We study the continual pretraining recipe for scaling language models' context lengths to
128K, with a focus on data engineering. We hypothesize that long context modeling, in …

Repository-level code completion aims to generate code for unfinished code snippets within
the context of a specified repository. Existing approaches mainly rely on retrieval-augmented …

The increasing development of large language models (LLMs) in code generation has
drawn significant attention among researchers. To enhance LLM-based code generation …

Natural language to code generation is an important application area of LLMs and has
received wide attention from the community. The majority of relevant studies have …

Code generation aims to automatically generate code snippets that meet given natural
language requirements and plays an important role in software development. Although …