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

This paper provides a survey of the emerging area of Large Language Models (LLMs) for
Software Engineering (SE). It also sets out open research challenges for the application of …

Over the past year (2022–2023), recently-released AI tools such as ChatGPT and GitHub
Copilot have gained significant attention from computing educators. Both researchers and …

A race is underway to embed advanced AI capabilities into products. These product copilots
enable users to ask questions in natural language and receive relevant responses that are …

Supply chain operations traditionally involve a variety of complex decision making problems.
Over the last few decades, supply chains greatly benefited from advances in computation …

The availability of large-scale datasets, advanced architectures, and powerful computational
resources have led to effective code models that automate diverse software engineering …

This paper presents CyberSecEval, a comprehensive benchmark developed to help bolster
the cybersecurity of Large Language Models (LLMs) employed as coding assistants. As …

Data analysis is challenging as analysts must navigate nuanced decisions that may yield
divergent conclusions. AI assistants have the potential to support analysts in planning their …

Over the past few years, Large Language Models of Code (Code LLMs) have started to have
a significant impact on programming practice. Code LLMs are also emerging as building …

Generative AI models, specifically large language models (LLMs), have made strides
towards the long-standing goal of text-to-code generation. This progress has invited …