IEEE

Multi-Label Text Classification Using Prompting Techniques via LLMs in Software Effort Estimation

Abstract: Text classification (TC) has gained substantial importance across diverse domains due to the increasing proliferation of internet-based and digital technologies. Organizations worldwide ...
GitHub

NOVIC: Unconstrained Open Vocabulary Image Classification

💡 TL;DR: Given an image and nothing else (i.e. no prompts or candidate labels), NOVIC can generate an accurate fine-grained textual classification label in real-time, with coverage of the vast ...
The New York Times

Study Finds Evidence That Text-Based Therapy Eases Depression

A large-scale randomized trial of texting therapy concluded that its outcomes were as good as video sessions in treating depression. By Ellen Barry One of the most popular mental health innovations of ...
GitHub

Replication materials for Large Language Models for Text Classification: From Zero-Shot Learning to Instruction-Tuning

This repository contains replication materials for Youngjin (YJ) Chae and Thomas Davidson. 2025. "Large Language Models for Text Classification: From Zero-Shot Learning to Instruction-Tuning." ...
marktechpost

BEAL: A Bayesian Deep Active Learning Method for Efficient Deep Multi-Label Text Classification

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 ...
IEEE

Deep Learning-Based Algorithm for Classification of News Text

Abstract: As online news grows exponentially, hotspot classification is becoming increasingly important. Although traditional machine learning-based text classification methods, such as plain Bayes, ...