Testing Cross-Lingual Text Comprehension In LLMs Using Next Sentence Prediction

A recent study published on arXiv explores the capabilities of large language models (LLMs) in understanding low-resource languages through a method called Next Sentence Prediction (NSP). The research highlights that while these models excel in English due to abundant training data, their performance in less represented languages raises questions about their true comprehension abilities. This matters because it sheds light on the limitations of LLMs and emphasizes the need for more inclusive training datasets that can enhance language understanding across diverse linguistic backgrounds.