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Owing to the lack of corpora for low-resource languages, current works ondialogue generation have mainly focused on English. In this paper, we presentmDIA, the first large-scale multilingual benchmark for dialogue generationacross low- to high-resource languages. It covers real-life conversations in 46languages across 19 language families. We present baseline results obtained byfine-tuning the multilingual, non-dialogue-focused pre-trained model mT5 aswell as English-centric, dialogue-focused pre-trained chatbot DialoGPT. Theresults show that mT5-based models perform better on sacreBLEU and BertScorebut worse on diversity. Even though promising results are found in few-shot andzero-shot scenarios, there is a large gap between the generation quality inEnglish and other languages. We hope that the release of mDIA could encouragemore works on multilingual dialogue generation to promote language diversity.

MDIA: A Benchmark for Multilingual Dialogue Generation in 46 Languages