English Centric

Research on "English-centric" large language models (LLMs) focuses on mitigating the limitations of models primarily trained on English data when applied to other languages. Current efforts concentrate on adapting existing English-centric models through techniques like instruction tuning, knowledge distillation, and vocabulary expansion, often employing encoder-decoder architectures or low-rank adaptation methods. This research is crucial for broadening the accessibility and effectiveness of LLMs across diverse linguistic contexts, addressing issues of language bias and promoting equitable access to advanced language technologies. The ultimate goal is to develop more inclusive and robust LLMs that perform effectively across a wider range of languages.