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We present FRMT, a new dataset and evaluation benchmark for Few-shotRegion-aware Machine Translation, a type of style-targeted translation. Thedataset consists of professional translations from English into two regionalvariants each of Portuguese and Mandarin Chinese. Source documents are selectedto enable detailed analysis of phenomena of interest, including lexicallydistinct terms and distractor terms. We explore automatic evaluation metricsfor FRMT and validate their correlation with expert human evaluation acrossboth region-matched and mismatched rating scenarios. Finally, we present anumber of baseline models for this task, and offer guidelines for howresearchers can train, evaluate, and compare their own models. Our dataset andevaluation code are publicly available: https://bit.ly/frmt-task

FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation