2025
ACL
ACL 2025
Shouth NLP at SemEval-2025 Task 7: Multilingual Fact-Checking Retrieval Using Contrastive Learning
Abstract
AbstractWe present a multilingual fact-checking re-trieval system for the SemEval-2025 task ofmatching social media posts with relevant factchecks. Our approach utilizes a contrastivelearning framework built on the multilingual E5model architecture, fine-tuned on the provideddataset. The system achieves a Success@10score of 0.867 on the official test set, with per-formance variations between languages. Wedemonstrate that input prefixes and language-specific corpus filtering significantly improveretrieval performance. Our analysis reveals in-teresting patterns in cross-lingual transfer, withspecifically strong results on Malaysian andThai languages. We make our code public forfurther research and development.
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Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Machine Learning and Natural Language Processing
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Keyword Pioneer
— fact-checking retrieval
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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, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Learning Paradigms > Transfer Learning
Machine Learning > Core Methods > Classification
Machine Learning > Learning Types > Contrastive Learning
Deep Learning > Architectures > Transformers
Natural Language Processing > Applications > Information Retrieval
Natural Language Processing > Resources & Methods > Multilingual NLP
Deep Learning > Techniques > Contrastive Learning
Deep Learning > Learning Types > Contrastive Learning