@inproceedings{eleftheriou-etal-2025-kostasthesis2025,
    title = "{K}ostas{T}hesis2025 at {S}em{E}val-2025 Task 10 Subtask 2: A Continual Learning Approach to Propaganda Analysis in Online News",
    author = "Eleftheriou, Konstantinos  and
      Louridas, Panos  and
      Pavlopoulos, John",
    editor = "Rosenthal, Sara  and
      Ros{\'a}, Aiala  and
      Ghosh, Debanjan  and
      Zampieri, Marcos",
    booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/transition-to-people-yaml/2025.semeval-1.122/",
    pages = "899--908",
    ISBN = "979-8-89176-273-2",
    abstract = "In 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."
}