Cross Lingual Fact

Cross-lingual fact verification and generation aim to build systems that can accurately assess and create factual information across multiple languages, addressing the limitations of current models which often perform poorly outside of English. Research focuses on developing robust multilingual models, often leveraging transformer-based architectures, and creating benchmark datasets to evaluate performance across diverse languages and low-resource settings. This work is crucial for bridging the information gap between languages, enabling more equitable access to knowledge and facilitating applications such as multilingual fact-checking and cross-lingual knowledge base construction.