  We propose EXAMS -- a new benchmark dataset for cross-lingual and
multilingual question answering for high school examinations. We collected more
than 24,000 high-quality high school exam questions in 16 languages, covering 8
language families and 24 school subjects from Natural Sciences and Social
Sciences, among others.
  EXAMS offers a fine-grained evaluation framework across multiple languages
and subjects, which allows precise analysis and comparison of various models.
We perform various experiments with existing top-performing multilingual
pre-trained models and we show that EXAMS offers multiple challenges that
require multilingual knowledge and reasoning in multiple domains. We hope that
EXAMS will enable researchers to explore challenging reasoning and knowledge
transfer methods and pre-trained models for school question answering in
various languages which was not possible before. The data, code, pre-trained
models, and evaluation are available at https://github.com/mhardalov/exams-qa.
