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 ...

Traditional machine learning algorithms for classification tasks operate under the assumption of balanced class distributions. However, this assumption only holds in some practical scenarios. In most ...

The successful application of large-scale transformer models in Natural Language Processing (NLP) is often hindered by the substantial computational cost and data requirements of full fine-tuning.

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: This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional ...

ABSTRACT: This study addresses the growing demand for news text classification driven by the rapid expansion of internet information by proposing a classification algorithm based on a Bidirectional ...

In recent decades, medical short texts, such as medical conversations and online medical inquiries, have garnered significant attention and research. The advances in the medical short text have ...