Cross Lingual Vocabulary

Cross-lingual vocabulary research focuses on improving the efficiency and performance of large language models (LLMs) across multiple languages, particularly for those with limited resources. Current efforts concentrate on developing techniques like trans-tokenization and vocabulary expansion to adapt models trained on high-resource languages (like English) to low-resource languages, often using minimal target language data. These methods aim to increase inference speed and maintain competitive performance on downstream tasks, thereby reducing computational costs and broadening the accessibility of LLMs. This work has significant implications for multilingual natural language processing, enabling more equitable access to advanced language technologies for a wider range of languages and communities.