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    Tibetan Question Generation Based on Sequence to Sequence Model

    Yuan Sun1,2,*, Chaofan Chen1,2, Andong Chen3, Xiaobing Zhao1,2

    CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3203-3213, 2021, DOI:10.32604/cmc.2021.016517

    Abstract As the dual task of question answering, question generation (QG) is a significant and challenging task that aims to generate valid and fluent questions from a given paragraph. The QG task is of great significance to question answering systems, conversational systems, and machine reading comprehension systems. Recent sequence to sequence neural models have achieved outstanding performance in English and Chinese QG tasks. However, the task of Tibetan QG is rarely mentioned. The key factor impeding its development is the lack of a public Tibetan QG dataset. Faced with this challenge, the present paper first collects… More >

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