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Register a new userSAPPHIRE: Approaches for Enhanced Concept-to-Text Generation
الياقوت: نهج لتعزيز الجيل المفهوم إلى النص
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نحن نحفز واقتراح مجموعة من التحسينات البسيطة ولكنها فعالة لتوليد مفهوم إلى نص يسمى الياقوت: تعيين تعزز وبصورة ما بعد هوك تستلزم وإعادة التركيب.نوضح فعاليتها في مجال المنطق المنطقي الإنتاجية، A.K.a. مهمة Commongen، من خلال تجارب باستخدام نماذج BART و T5.من خلال التقييم التلقائي والبشري الواسع، نعرض أن الياقوت يحسن بشكل ملحوظ أداء النموذج.يوضح التحليل النوعي المتعمق أن الياقوت يتناول بفعالية العديد من القضايا من الأجيال النموذجية الأساسية، بما في ذلك قلة المنطقية وغير كافية من الخصوصية والطلاقة الفقراء.
We motivate and propose a suite of simple but effective improvements for concept-to-text generation called SAPPHIRE: Set Augmentation and Post-hoc PHrase Infilling and REcombination. We demonstrate their effectiveness on generative commonsense reasoning, a.k.a. the CommonGen task, through experiments using both BART and T5 models. Through extensive automatic and human evaluation, we show that SAPPHIRE noticeably improves model performance. An in-depth qualitative analysis illustrates that SAPPHIRE effectively addresses many issues of the baseline model generations, including lack of commonsense, insufficient specificity, and poor fluency.
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