SOURCE-LINKED INTELLIGENCE
EuroAlpaca: Task-Preserving Localisation of Instruction Data for European Languages
Machine translation (MT) offers a scalable way to extend English instruction-tuning data to multiple languages, but it can distort task-critical constraints and required outputs, creating corrupted training examples and degrading models trained on such data. We introduce EuroAlpaca, a task-preserving localisation pipeline and near-parallel resource covering 50 European languages and regional varieties, together with European-IFEval, a multilingual benchmark for verifiable instruction following. Depending on the example, our pipeline applies field-wise MT while preserving task-critical content
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-04T12:05:53.000Z
First collected: 2026-09-20T22:31:48.298Z. This is not the publication date.