Bigger has defined AI from day one. New data says task-specific small models beat frontier LLMs on accuracy, cost and speed — ...

Abstract: Arabic documents are massively rising due to numerous contents utilized in websites, social media, and news articles. The classification of such documents in labelled categories is a ...

This repository contains the code and pre-trained models for the paper "Zero-Shot Text Classification via Self-Supervised Tuning", which was accepted to Findings of ACL 2023. [2023/9/25] ...

Introduced in Ein-dor et al. (2020), this is a framework for experimenting with text classification tasks. The focus is on low-resource scenarios, and examining how active learning (AL) can be used in ...

Abstract: Attention mechanisms are now a mainstay architecture in neural networks and improve the performance of biomedical text classification tasks. In particular, models that perform automated ...

Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories ...

Text spam is on the rise. The latest version involves scammers sending messages to you seemingly from your own phone number. Here’s what to do. By Brian X. Chen A few weeks ago, I woke up to an early ...

Many NLP applications require manual text annotations for a variety of tasks, notably to train classifiers or evaluate the performance of unsupervised models. Depending on the size and degree of ...