2025
ACL
ACL 2025
KostasThesis2025 at SemEval-2025 Task 10 Subtask 2: A Continual Learning Approach to Propaganda Analysis in Online News
Abstract
AbstractIn response to the growing challenge of propagandistic presence through online media inonline news, the increasing need for automated systems that are able to identify and classify narrative structures in multiple languages is evident. We present our approach to the SemEval-2025 Task 10 Subtask 2, focusing on the challenge of hierarchical multi-label, multi-class classification in multilingual news articles. We present methods to handle long articles with respect to how they are naturally structured in the dataset, propose a hierarchical classification neural network model with respect to the taxonomy, and a continual learning training approach that leverages cross-lingual knowledge transfer.
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Keyword Pioneer
— propaganda analysis
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Cross-Pollinator
— Artificial Intelligence, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Speech & Audio
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Interdisciplinary Bridge
— Deep Learning and Machine Learning and Natural Language Processing
Authors
Topics
Machine Learning > Core Methods > Classification
Machine Learning > Learning Types > Continual Learning
Deep Learning > Architectures > Neural Networks
Natural Language Processing > Applications > Text Classification
Machine Learning > Learning Paradigms > Continual Learning
Deep Learning > Learning Types > Multi-Label Classification