mlsanityData to 7 Oct 2026

A Survey on non-English Question Answering Dataset

arXiv 2112.13634 ↗First posted 27 Dec 2021cs.CLcited by 5

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Abstract (arXiv)

Research in question answering datasets and models has gained a lot of attention in the research community. Many of them release their own question answering datasets as well as the models. There is tremendous progress that we have seen in this area of research. The aim of this survey is to recognize, summarize and analyze the existing datasets that have been released by many researchers, especially in non-English datasets as well as resources such as research code, and evaluation metrics. In this paper, we review question answering datasets that are available in common languages other than English such as French, German, Japanese, Chinese, Arabic, Russian, as well as the multilingual and cross-lingual question-answering datasets.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 38 of its 59 references that are in the map. First posted on arXiv 27 Dec 2021.

Builds on

38 of 59 references.

References · 38

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26 more
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Cited by year

Citing papers per year: 2023: 2; 2024: 3.

5 papers.

  1. 2024CaLMQA: Exploring culturally specific long-form question answering across 23 languagescited by 31
  2. 2023Resources and Few-shot Learners for In-context Learning in Slavic Languagescited by 6
  3. 2023PCoQA: Persian Conversational Question Answering Datasetcited by 5
  4. 2024Building Efficient and Effective OpenQA Systems for Low-Resource Languagescited by 0
  5. 2024EuSQuAD: Automatically Translated and Aligned SQuAD2.0 for Basquecited by 0