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Register a new userDifferentiable Open-Ended Commonsense Reasoning
التفكير المنطقي مفتوح العضوية
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يركز البحث في مجال المنطق الحالي على تطوير النماذج التي تستخدم معرفة المنطقية للإجابة على أسئلة متعددة الخيارات. ومع ذلك، قد لا تكون النظم المصممة للإجابة على أسئلة متعددة الخيارات مفيدة في التطبيقات التي لا توفر قائمة صغيرة من إجابات المرشحين للاختيار من بينها. كخطوة نحو جعل البحث منطق المنطقي أكثر واقعية، نقترح دراسة مسطحة المنطقية المفتوحة العضوية (OPENCSR) --- مهمة الإجابة على سؤال المنطقي دون أي اختيارات محددة مسبقا --- استخدام كموارد فقط حقائق المنطقية مكتوبة باللغة الطبيعية. OpenCSR تحديا بسبب مساحة قرارات كبيرة، ولأن العديد من الأسئلة تتطلب منطق متعدد القفز الضمني. كنعجا من OpenCSR، نقترح نماذج شديدة الفضلة للمناسبة متعددة القفز بشأن حقائق المعرفة. لتقييم أساليب OpenCSR، نقوم بتكييف العديد من معايير المنطق المنطقية الشائعة، وجمع إجابات جديدة متعددة لكل سؤال اختبار عبر مصادر الحشد. تظهر التجارب أن DrFact تفوق أساليب أساسية قوية من قبل هامش كبير.
Current commonsense reasoning research focuses on developing models that use commonsense knowledge to answer multiple-choice questions. However, systems designed to answer multiple-choice questions may not be useful in applications that do not provide a small list of candidate answers to choose from. As a step towards making commonsense reasoning research more realistic, we propose to study open-ended commonsense reasoning (OpenCSR) --- the task of answering a commonsense question without any pre-defined choices --- using as a resource only a corpus of commonsense facts written in natural language. OpenCSR is challenging due to a large decision space, and because many questions require implicit multi-hop reasoning. As an approach to OpenCSR, we propose DrFact, an efficient Differentiable model for multi-hop Reasoning over knowledge Facts. To evaluate OpenCSR methods, we adapt several popular commonsense reasoning benchmarks, and collect multiple new answers for each test question via crowd-sourcing. Experiments show that DrFact outperforms strong baseline methods by a large margin.
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