Multilingual Application

Multilingual applications leverage large language models (LLMs) to process and generate text across multiple languages, aiming to overcome limitations of English-centric models and improve cross-cultural understanding. Current research focuses on mitigating issues like data contamination and inherent biases through techniques such as low-rank adaptation and instruction tuning, while also exploring efficient model architectures like Sentence-T5 and improving the performance of direct inference over pre-translation. These advancements are significant for enhancing the accuracy and efficiency of multilingual tasks, including translation, text editing, and speech processing, impacting diverse fields from creative industries to accessibility technologies.