Name: MFQA
Description: MQA is a Multilingual corpus of Questions and Answers (MQA) parsed from the Common Crawl. Questions are divided in two types: Frequently Asked Questions (FAQ) and Community Question Answering (CQA).
Provider: University of Antwerp
Paper Title: MFAQ: a Multilingual FAQ Dataset
Tasks: frequently asked questions, question answering
Venue Name: nan
Authors: Maxime De Bruyn, Ehsan Lotfi, Jeska Buhmann, Walter Daelemans
Abstract: 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) (Karpukhin et al., 2020) and test
  various bi-encoders on this dataset. Our experiments reveal that a multilingual model based
  on XLM-RoBERTa (Conneau et al., 2019)
  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 dataset1
  , model2
  and training
  script