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EXAMS: A Multi-Subject High School Examinations Dataset for Cross-Lingual and Multilingual Question Answering

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arxiv 2011.03080 v1 pith:FYZYOICP submitted 2020-11-05 cs.CL cs.AIcs.IRcs.LG

classification cs.CLcs.AIcs.IRcs.LG
keywords examsschoolmodelsmultilingualansweringhighlanguagesmultiple
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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