Abstract Machine learning has become the state-of-the-art technique for many tasks
including computer vision, natural language processing, speech processing tasks, etc …

Pre-trained language models have achieved striking success in natural language
processing (NLP), leading to a paradigm shift from supervised learning to pre-training …

Large language models (LLMs) have recently been applied in software engineering to
perform tasks such as translating code between programming languages, generating code …

The Generative Pre-trained Transformer (GPT) represents a notable breakthrough in the
domain of natural language processing, which is propelling us toward the development of …

With the urgent demand for generalized deep models, many pre-trained big models are
proposed, such as bidirectional encoder representations (BERT), vision transformer (ViT) …

Text Generation aims to produce plausible and readable text in human language from input
data. The resurgence of deep learning has greatly advanced this field, in particular, with the …

As practitioners increasingly deploy machine learning models in critical domains such as
health care, finance, and policy, it becomes vital to ensure that domain experts function …

Bidirectional Encoder Representations from Transformers (BERT) has gained increasing
attention from researchers and practitioners as it has proven to be an invaluable technique …

Taxonomic classification, that is, the assignment to biological clades with shared ancestry, is
a common task in genetics, mainly based on a genome similarity search of large genome …

Question answering (QA) systems provide a way of querying the information available in
various formats including, but not limited to, unstructured and structured data in natural …