Over the past decade, Open Source Software (OSS) has experienced rapid growth and
widespread adoption, attributed to its openness and editability. However, this expansion has …

The increasing use of generative Artificial Intelligence (AI) in modern software engineering,
particularly Large Language Models (LLMs) for code generation, has transformed …

Despite decades of research in vulnerability detection, vulnerabilities in source code remain
a growing problem, and more effective techniques are needed in this domain. To enhance …

The healthcare industry is currently experiencing an unprecedented wave of cybersecurity
attacks, impacting millions of individuals. With the discovery of thousands of vulnerabilities …

The rapid advancement of large language models (LLMs) such as GPT-4 has revolutionized
the landscape of software engineering, positioning these models at the core of modern …

The number of new vulnerabilities continues to rise significantly each year. Simultaneously,
vulnerability databases have challenges in promptly sharing new security events with …

The latest advancements in large language models (LLMs) have sparked interest in their
potential for software vulnerability detection. However, there is currently a lack of research …

Deep learning has demonstrated its effectiveness in software vulnerability detection, but
acquiring a large number of labeled code snippets for training deep learning models is …

Abstract Large Language Models (LLMs) have emerged as powerful tools in the domain of
software vulnerability and cybersecurity tasks, offering promising capabilities in detecting …

Large Language Models (LLMs) have emerged as powerful tools for automating various
programming tasks, including security-related ones, such as detecting and fixing …