Frontiers

Comparative performance of large language models in emotional safety classification across sizes and tasks

Understanding how large language models (LLMs) process emotionally sensitive content is critical for building safe and reliable systems, particularly in mental health contexts. We compare the ...
IEEE

Refactoring Prediction using Multi-label Classification Approach

Abstract: Refactoring is the process of restructuring existing source code to improve its internal structure without altering its external behavior. Refactoring is essential to maintaining software ...
IEEE

Semantic Hierarchy-Aware Hyperbolic Representations for Multi-Label Classification With Single Positive Labels

Abstract: Single positive multi-label learning (SPML) aims to recognize multiple categories with limited supervision from one positive label in an image. With the emergence of pre-trained ...
Scientific Research Publishing

An Evaluation of Machine Learning Models for Threat Classification in IoT Devices ()

1 Center for Cyberspace Studies, Nasarawa State University, Keffi, Nigeria. 2 Department of Computer Engineering, Nile University of Nigeria, Abuja, Nigeria. 3 Department of Public and International ...
Frontiers

PMJDM: a multi-task joint detection model for plant disease identification

Shandong Province University Laboratory for Protected Horticulture, Weifang University of Science and Technology, Weifang, China Introduction: Plant disease detection is critical for ensuring ...
GitHub

sequence classification inference #4093

I fine-tuned a multi-label classification model using the following script: swift sft \ --model Qwen/Qwen2.5-0.5B \ --train_type lora \ --dataset 'training.json ...