Scaling Multilingual Safety and Reasoning Evaluation through Reasoning-Guided Translation
Large language models (LLMs) are increasingly deployed across languages, yet their safety and reasoning capabilities remain predominantly evaluated in English. Translating existing benchmarks offers a scalable approach to multilingual evaluation, but preserving task-specific meaning across languages presents significant challenges, particularly for harmful requests, mathematical reasoning, and conversational interactions. We introduce a reasoning-guided translation framework for constructing multilingual evaluations designed to preserve the structure and intended meaning of diverse benchmark tasks. Our approach separates translation strategy selection from large-scale generation, combinin...
| Authors | Zahraa Al Sahili, Ioannis Patras, Matthew Purver |
|---|---|
| Primary category | cs.CL |
| Published | 14 October 2026 |
| Last updated at source | 14 October 2026 |
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