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autoeqa: أسئلة الترميز التلقائي لسؤال الاستخراج
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كان هناك تقدم كبير في مجال الإجابة على الأسئلة الاستخراجية (EQA) في السنوات الأخيرة.ومع ذلك، فإن معظمهم يعتمدون على التوضيحية الخاصة بالإجابة في الممرات المقابلة.في هذا العمل، نتعلم مشكلة EQA عندما لا توجد شروح موجودة للإجابة فترة الإجابة، أي، عندما تحتوي DataSet على أسئلة فقط والممرات المقابلة.تعتمد طريقتنا على الترميز التلقائي للسؤال الذي يؤدي سؤالا يرد على المهمة أثناء الترميز ومهمة توليد الأسئلة أثناء فك التشفير.نظهر أن طريقتنا تعمل بشكل جيد في إعداد صفرية ويمكن أن توفر خسارة إضافية لتعزيز الأداء ل EQA.
There has been a significant progress in the field of Extractive Question Answering (EQA) in the recent years. However, most of them are reliant on annotations of answer-spans in the corresponding passages. In this work, we address the problem of EQA when no annotations are present for the answer span, i.e., when the dataset contains only questions and corresponding passages. Our method is based on auto-encoding of the question that performs a question answering task during encoding and a question generation task during decoding. We show that our method performs well in a zero-shot setting and can provide an additional loss to boost performance for EQA.
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