يعرض التفكير في المعلومات الجدولي تحديات فريدة من نوعها إلى نهج NLP الحديثة تعتمد إلى حد كبير على تضمينات النص المدربة مسبقا للنص.في هذه الورقة، ندرس هذه التحديات من خلال مشكلة الاستدلال اللغوي الطبيعي الجدول.نقترح تعديلات سهلة وفعالة على كيفية تقديم المعلومات إلى نموذج لهذه المهمة.نظهر عبر التجارب المنهجية التي تحسن هذه الاستراتيجيات بشكل كبير أداء الاستدلال الجزيئي.
Reasoning about tabular information presents unique challenges to modern NLP approaches which largely rely on pre-trained contextualized embeddings of text. In this paper, we study these challenges through the problem of tabular natural language inference. We propose easy and effective modifications to how information is presented to a model for this task. We show via systematic experiments that these strategies substantially improve tabular inference performance.
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