  In this paper, we present the first multilingual FAQ dataset publicly
available. We collected around 6M FAQ pairs from the web, in 21 different
languages. Although this is significantly larger than existing FAQ retrieval
datasets, it comes with its own challenges: duplication of content and uneven
distribution of topics. We adopt a similar setup as Dense Passage Retrieval
(DPR) and test various bi-encoders on this dataset. Our experiments reveal that
a multilingual model based on XLM-RoBERTa achieves the best results, except for
English. Lower resources languages seem to learn from one another as a
multilingual model achieves a higher MRR than language-specific ones. Our
qualitative analysis reveals the brittleness of the model on simple word
changes. We publicly release our dataset, model and training script.
