TECHSSN at SemEval-2025 Task 10: A Comparative Analysis of Transformer Models for Dominant Narrative-Based News Summarization

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.