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Register a new userComprehension Based Question Answering using Bloom's Taxonomy
استفهام على أساس الإجابة باستخدام تصنيف بلوم
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نماذج اللغة الحالية المدربة مسبقا لديها الكثير من المعرفة، ولكن القدرة المحدودة على استخدام هذه المعرفة.تساعد تصنيف Bloom في علم المربين على تعليم الأطفال كيفية استخدام المعرفة من خلال تصنيف مهارات الفهم، لذلك نحن نستخدمها لتحليل وتحسين مهارات الفهم في نماذج اللغة المدربة مسبقا مسبقا.تركز تجاربنا على الإجابة على السؤال الصفرية، باستخدام التصنيف لتقديم السياق القريب الذي يساعد على الإجابة النموذجية على الأسئلة المتعلقة بتلك الأسئلة ذات الصلة بتلك الأسئلة.نعرض سياق الاستهداف بهذه الطريقة يحسن الأداء عبر مجموعات بيانات الإجابة الشائعة على 4 أشخاص.
Current pre-trained language models have lots of knowledge, but a more limited ability to use that knowledge. Bloom's Taxonomy helps educators teach children how to use knowledge by categorizing comprehension skills, so we use it to analyze and improve the comprehension skills of large pre-trained language models. Our experiments focus on zero-shot question answering, using the taxonomy to provide proximal context that helps the model answer questions by being relevant to those questions. We show targeting context in this manner improves performance across 4 popular common sense question answer datasets.
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