2025
SEMEVAL
SemEval 2025
KyuHyunChoi at SemEval-2025 Task 10: Narrative Extraction Using a Summarization-Specific Pretrained Model
Abstract
AbstractTask 11 of SemEval 2025 was proposed to develop supporting information for analyzing the risks of misinformation and propaganda in news articles. In this study, we selected Sub-task 3—which involves generating evidence explaining why a particular dominant narrative is labeled in an article—and fine-tuned PEGASUS for this purpose, achieving the best performance in the competition.
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Interdisciplinary Bridge
— Deep Learning and Machine 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
Authors
Topics
Deep Learning > Models > Generative Models
Natural Language Processing > Generation > Summarization
Natural Language Processing > Generation > Text Generation
Natural Language Processing > Applications > Text Classification
Natural Language Processing > Resources & Methods > Large Language Models
Natural Language Processing > Applications > Text Generation
Machine Learning > Learning Types > Fine-Tuning