Large language models (LLMs) have been increasingly used to interact with external
environments (eg, games, compilers, APIs) as goal-driven agents. However, it remains …

Code Large Language Models (Code LLMs), such as StarCoder, have demonstrated
exceptional performance in code-related tasks. However, most existing models are solely …

Large Language Models (LLMs) applied to code-related applications have emerged as a
prominent field, attracting significant interest from both academia and industry. However, as …

The task of generating code from a natural language description, or NL2Code, is considered
a pressing and significant challenge in code intelligence. Thanks to the rapid development …

In this report, we introduce the Qwen2. 5-Coder series, a significant upgrade from its
predecessor, CodeQwen1. 5. This series includes six models: Qwen2. 5-Coder-(0.5 B/1.5 …

Code generation models based on the pre-training and fine-tuning paradigm have been
increasingly attempted by both academia and industry, resulting in well-known industrial …

Large Language Models (LLMs) have garnered remarkable advancements across diverse
code-related tasks, known as Code LLMs, particularly in code generation that generates …

Code-generating large language models map natural language to code. However, only a
small portion of the infinite space of naturalistic utterances is effective at guiding code …

Since the rise of neural natural-language-to-code models (NL-> Code) that can generate
long expressions and statements rather than a single next-token, one of the major problems …

We present CRUXEval (Code Reasoning, Understanding, and eXecution Evaluation), a
benchmark consisting of 800 Python functions (3-13 lines). Each function comes with an …