The project is one of several community-focused initiatives demonstrating UVA’s commitment to serving the commonwealth and ...
Abstract: Hierarchical Text Classification (HTC) is a challenging task where labels are structured in a tree or Directed Acyclic Graph (DAG) format. Current approaches often struggle with data ...
Abstract: The growing volume of unstructured text data in the banking sector has created a need for advanced classification methods to manage customer inquiries efficiently, resulting in faster ...
💡 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 ...
ABSTRACT: Pregnancy presents a unique clinical scenario where the safety of pharmacological interventions is of paramount importance. The potential teratogenic risks associated with drug intake during ...
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 ...
School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China. This study aims to design and implement an efficient news text classification system based on deep learning to ...
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." ...
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 ...
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