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

Pre-trained large language models (LLMs) have recently emerged as a breakthrough
technology in natural language processing and artificial intelligence, with the ability to …

Pre-trained models have been shown effective in many code intelligence tasks. These
models are pre-trained on large-scale unlabeled corpus and then fine-tuned in downstream …

The use of learning-based techniques to achieve automated software vulnerability detection
has been of longstanding interest within the software security domain. These data-driven …

The rapid advancement of Large Language Models (LLMs) has opened up new
opportunities for leveraging artificial intelligence in various domains, including cybersecurity …

Code summarization, the task of generating useful comments given the code, has long been
of interest. Most of the existing code summarization models are trained and validated on …

Software is constantly changing, requiring developers to perform several derived tasks in a
timely manner, such as writing a description for the intention of the code change, or …

Pre-trained models have been shown effective in many code intelligence tasks, such as
automatic code summarization and defect prediction. These models are pre-trained on large …

Previous research on code intelligence usually trains a deep learning model on a fixed
dataset in an offline manner. However, in real-world scenarios, new code repositories …

Automatically fixing compilation errors can greatly raise the productivity of software
development, by guiding the novice or AI programmers to write and debug code. Recently …