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Register a new userUnsupervised Multiple Choices Question Answering: Start Learning from Basic Knowledge
الخيارات متعددة غير الخاضعة للإجابة على الإجابة: البدء في التعلم من المعرفة الأساسية
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في هذه الورقة، ندرس إمكانية إجابة سؤاليات متعددة الخيارات غير المدعومة (MCQA).من المعرفة الأساسية للغاية، يعرف نموذج MCQA أن بعض الخيارات لديها احتمالات أعلى من كونها صحيحة من غيرها.المعلومات، على الرغم من صاخبة جدا، يرشد تدريب نموذج MCQA.يتم عرض الطريقة المقترحة تفوقت على النهج الأساسية في السباق وهي قابلة للمقارنة مع بعض مناهج التعلم الخاضعة للإشراف على MC500.
In this paper, we study the possibility of unsupervised Multiple Choices Question Answering (MCQA). From very basic knowledge, the MCQA model knows that some choices have higher probabilities of being correct than others. The information, though very noisy, guides the training of an MCQA model. The proposed method is shown to outperform the baseline approaches on RACE and is even comparable with some supervised learning approaches on MC500.
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