@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://aclanthology.org/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."
}<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="eleftheriou-etal-2025-kostasthesis2025">
<titleInfo>
<title>KostasThesis2025 at SemEval-2025 Task 10 Subtask 2: A Continual Learning Approach to Propaganda Analysis in Online News</title>
</titleInfo>
<name type="personal">
<namePart type="given">Konstantinos</namePart>
<namePart type="family">Eleftheriou</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Panos</namePart>
<namePart type="family">Louridas</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">John</namePart>
<namePart type="family">Pavlopoulos</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2025-07</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Sara</namePart>
<namePart type="family">Rosenthal</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Aiala</namePart>
<namePart type="family">Rosá</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Debanjan</namePart>
<namePart type="family">Ghosh</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Marcos</namePart>
<namePart type="family">Zampieri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>Association for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Vienna, Austria</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
<identifier type="isbn">979-8-89176-273-2</identifier>
</relatedItem>
<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.</abstract>
<identifier type="citekey">eleftheriou-etal-2025-kostasthesis2025</identifier>
<location>
<url>https://aclanthology.org/2025.semeval-1.122/</url>
</location>
<part>
<date>2025-07</date>
<extent unit="page">
<start>899</start>
<end>908</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T KostasThesis2025 at SemEval-2025 Task 10 Subtask 2: A Continual Learning Approach to Propaganda Analysis in Online News
%A Eleftheriou, Konstantinos
%A Louridas, Panos
%A Pavlopoulos, John
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F eleftheriou-etal-2025-kostasthesis2025
%X 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.
%U https://aclanthology.org/2025.semeval-1.122/
%P 899-908
Markdown (Informal)
[KostasThesis2025 at SemEval-2025 Task 10 Subtask 2: A Continual Learning Approach to Propaganda Analysis in Online News](https://aclanthology.org/2025.semeval-1.122/) (Eleftheriou et al., SemEval 2025)
ACL