Cross Lingual Understanding

Cross-lingual understanding (CLU) focuses on enabling artificial intelligence systems to comprehend and process information across multiple languages, aiming to overcome the limitations of monolingual models. Current research emphasizes improving the performance of large multilingual language models (LLMs) and exploring techniques like prompt tuning as more efficient alternatives to traditional fine-tuning for cross-lingual transfer. This field is crucial for bridging language barriers in various applications, including multilingual information retrieval, hate speech detection, and education, and for advancing our understanding of how language models learn and transfer knowledge across different linguistic structures.