aiqbench analysis
This study addresses the critical need for diverse, multilingual benchmarks by localizing the MMLU dataset into 11 European languages to better evaluate Large Language Models beyond English-centric contexts. The project simultaneously serves as a practical training ground for translation professionals while documenting significant administrative and workflow hurdles in scaling evaluation datasets across borders.
Building a European Multilingual Evaluation Dataset: The MMLU Localisation Project within the EMT Network
arXiv:2607.18432v1 Announce Type: new Abstract: This paper reports on a collaboration between the Directorate-General for Translation (DGT) and the European Master's in Translation (EMT) to localise the MMLU dataset into 11 European languages. Beyond creating a more inclusive benchmark for LLM evaluation, the project offers master's students authentic, project-based professional training in translation, revision, project management, and multilingual coordination, while highlighting key methodological, administrative, and workflow challenges.
Abstract:This paper reports on a collaboration between the Directorate-General for Translation (DGT) and the European Master's in Translation (EMT) to localise the MMLU dataset into 11 European languages. Beyond creating a more inclusive benchmark for LLM evaluation, the project offers master's students authentic, project-based professional training in translation, revision, project management, and multilingual coordination, while highlighting key methodological, administrative, and workflow challenges.
Computation and Language (cs.CL)
arXiv:2607.18432 [cs.CL]
(or arXiv:2607.18432v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2607.18432 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
https://doi.org/10.26615/issn.2815-4711.2026_007 Focus to learn more DOI(s) linking to related resources
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