Multilingual Polarization Detection Using Transformer-Based Models with Class Weighting and Threshold Tuning
arXiv:2606.30857v1 Announce Type: new Abstract: This paper describes our submission to SemEval-2026 Task 9 on detecting multilingual, multicultural, and multievent online polarization. We address all three subtasks: binary polarization detection, polarization type classification, and manifestation identification for English and Swahili. Our approach leverages transformer-based models (RoBERTa-base for English, AfroXLMR-base for Swahili) with class-weighted loss functions to address severe label ...
arXiv cs.CL
·Aaron Bundi Anampiu
·
// relacionados
Leia também
Blog
Using Lift to Turn Research PDFs into Structured JSON with Controlled, Schema-Guided Field-Level Evaluation
Blog
Anthropic Redeploys Claude Fable 5 on July 1 After US Export Controls Lift, Adds New Cybersecurity Classifier
Blog
The latest AI news we announced in June 2026
Blog