Urdu Fake News Classification with Domain Adaptation

This paper addresses the critical problem of fake news detection in a low-resource language (Urdu). It highlights the limitations of directly applying multilingual models and proposes a domain adaptation approach to improve performance. The focus on a specific language and the practical application of domain adaptation are significant contributions.

• •Addresses fake news detection in a low-resource language (Urdu).
• •Employs domain adaptation to improve performance of multilingual models.
• •Demonstrates the effectiveness of domain-adapted XLM-RoBERTa.
• •Provides insights into the application of domain adaptation for low-resource NLP tasks.