Multilingual LLM

Multilingual Large Language Models (MLLMs) aim to create AI systems capable of understanding and generating text across multiple languages, overcoming the limitations of English-centric models. Current research focuses on improving performance in low-resource languages through techniques like chain-of-translation prompting, balanced multilingual datasets, and optimized multilingual tokenizers, often employing transformer-based architectures. These advancements are significant because they promote inclusivity in AI, enabling broader access to language technologies and facilitating cross-cultural communication and knowledge sharing.