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

In 2006, Geoffrey Hinton proposed the concept of training “Deep Neural Networks (DNNs)”
and an improved model training method to break the bottleneck of neural network …

This paper explores the limits of the current generation of large language models for
program synthesis in general purpose programming languages. We evaluate a collection of …

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

The BigCode project is an open-scientific collaboration working on the responsible
development of large language models for code. This tech report describes the progress of …

Large language models have demonstrated the ability to generate both natural language
and programming language text. Although contemporary code generation models are …

Automatic program understanding and generation techniques could significantly advance
the productivity of programmers and have been widely studied by academia and industry …

Code completion is one of the most useful features in the Integrated Development
Environments (IDEs), which can accelerate software development by suggesting the next …

The field of big code relies on mining large corpora of code to perform some learning task
towards creating better tools for software engineers. A significant threat to this approach was …

Generative models have become adept at producing artifacts such as images, videos, and
prose at human-like levels of proficiency. New generative techniques, such as unsupervised …