2025
ACL
ACL 2025
TECHSSN at SemEval-2025 Task 10: A Comparative Analysis of Transformer Models for Dominant Narrative-Based News Summarization
Abstract
AbstractThis paper presents an approach to Task 10 of SemEval 2025, which focuses on summarizing English news articles using a given dominant narrative. The dataset comprises news articles on the Russia-Ukraine war and climate change, introducing challenges related to bias, information compression, and contextual coherence. Transformer-based models, specifically BART variants, are utilized to generate concise and coherent summaries. Our team TechSSN, achieved 4th place on the official test leaderboard with a BERTScore of 0.74203, employing the DistilBART-CNN-12-6 model.
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Interdisciplinary Bridge
— Deep Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio