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 …

Research at the intersection of machine learning, programming languages, and software
engineering has recently taken important steps in proposing learnable probabilistic models …

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 ability to generate natural language sequences from source code snippets has a variety
of applications such as code summarization, documentation, and retrieval. Sequence-to …

Automatic source code summarization is the task of generating natural language
descriptions for source code. Automatic code summarization is a rapidly expanding research …

During software maintenance, code comments help developers comprehend programs and
reduce additional time spent on reading and navigating source code. Unfortunately, these …

Source code summarization--creating natural language descriptions of source code
behavior--is a rapidly-growing research topic with applications to automatic documentation …

Source Code Summarization is the task of writing short, natural language descriptions of
source code. The main use for these descriptions is in software documentation eg the one …

Code comment has been an important part of computer programs, greatly facilitating the
understanding and maintenance of source code. However, high-quality code comments are …

Commit messages record code changes (eg, feature modifications and bug repairs) in
natural language, and are useful for program comprehension. Due to the frequent updates …