Multilingual Instruction Tuning With Just a Pinch of Multilinguality

As instruction-tuned large language models (LLMs) gain global adoption, their ability to follow instructions in multiple languages becomes increasingly crucial. In this work, we investigate how multilinguality during instruction tuning of a multilingual LLM affects instruction-following across languages from the pre-training corpus. We first show that many languages transfer some instruction-following capabilities to other languages from even monolingual tuning. Furthermore, we find that only 40 multilingual examples integrated in an English tuning set substantially improve multilingual instruction-following, both in seen …

adoption cs.ai cs.cl cs.lg global instruction-tuned language language models languages large language large language models llm llms multilingual multilingual llm multiple pre-training show training transfer work