Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Large language models (LLMs) have revolutionized the field of artificial intelligence,
enabling natural language processing tasks that were previously thought to be exclusive to …

Large language models (LLMs) have shown promise in proving formal theorems using proof
assistants such as Lean. However, existing methods are difficult to reproduce or build on …

Despite the remarkable ability of large language models (LMs) to comprehend and generate
language, they have a tendency to hallucinate and create factually inaccurate output …

Finetuning large language models (LLMs) on instructions leads to vast performance
improvements on natural language tasks. We apply instruction tuning using code …

During Automated Program Repair (APR), it can be challenging to synthesize correct
patches for real-world systems in general-purpose programming languages. Recent Large …

Large language models are powerful text processors and reasoners, but are still subject to
limitations including outdated knowledge and hallucinations, which necessitates connecting …

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 …

Software engineering activities such as package migration, fixing error reports from static
analysis or testing, and adding type annotations or other specifications to a codebase …