The federal government’s exemption for quoting religious texts in its proposed hate speech law has attracted criticism — it ...

Abstract: This review article provides a thorough assessment of modern and innovative algorithms for text classification through both observational and experimental evaluations. We propose a new ...

ABSTRACT: Since transformer-based language models were introduced in 2017, they have been shown to be extraordinarily effective across a variety of NLP tasks including but not limited to language ...

This hardback text book has a blue cloth cover with white lettering that reads "TEXT BOOK / OF THE / MADAM C. J. WALKER SCHOOLS / OF / BEAUTY CULTURE / The Mme. C. J. Walker Manufacturing Co., Inc." ...

Background: Free-text comments in patient-reported outcome measures (PROMs) data provide insights into health-related quality of life (HRQoL). However, these comments are typically analysed using ...

Large Language Models (LLMs) ushered in a technological revolution. We breakdown how the most important models work. byLanguage Models (dot tech)@languagemodels byLanguage Models (dot ...

Abstract: We propose a text classification model based on dependency graph attention convolution, which improves the model’s accurate recognition of the text category by mining the semantic features ...

A systematic review analyzing document classification methods using the 20 Newsgroups bydate dataset. This research evaluates machine learning and deep learning approaches across eight key domains, ...

Multi-label text classification (MLTC) assigns multiple relevant labels to a text. While deep learning models have achieved state-of-the-art results in this area, they require large amounts of labeled ...