Tag
BLOOMZ and mT0 are multilingual models finetuned on the crosslingual task mixture xP3, enabling zero-shot instruction following in dozens of languages.
This paper presents a large-scale evaluation of nine uncertainty estimation methods for LLMs across 22 languages, finding that prompting models to reason in English improves uncertainty estimation for low-resource languages and that the choice of method depends on model scale.
The paper proposes Crosslingual On-Policy Self-Distillation (COPSD), a method to transfer high-resource language reasoning capabilities to low-resource languages using a shared student-teacher architecture. Experiments across 17 African languages show significant improvements in mathematical reasoning and answer-format adherence, outperforming Group Relative Policy Optimization (GRPO).