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Register a new userDecoupling Pragmatics: Discriminative Decoding for Referring Expression Generation
الانقسام البراغماتية: فك التشفير التمييزي لإحالة توليد التعبير
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وقد مكن التحول إلى النماذج العصبية في إحالة الجيل التعبير (REG) المزيد من النماذج الطبيعية، ولكن بتكلفة الترجمة الترجمة الشفوية.نجاد بأن دمج المنطق العملي في استنتاج نماذج التوليد غير المرجعية للسياق يمكن أن يتجاوز سمات REG التقليدية والعملية، لأن هذا يوفر فصل بين المعلومات المستقلة والمعلومات الحرفية والتكيف العملي إلى السياق.مع وضع ذلك في الاعتبار، نطبق استراتيجيات فك تشفيرها الحالية من التسمية التوضيحية للصورة التمييزية إلى REG وتقييمها من حيث المعلوماتية العملية، والاحتمالية في التعليقات التوضيحية حول الحقيقة والتنوع اللغوي.تظهر نتائجنا فعالية عامة، ولكن مكاسب صغيرة نسبيا في المعلوماتية، مما أثار أسئلة مهمة ل Reg بشكل عام.
The shift to neural models in Referring Expression Generation (REG) has enabled more natural set-ups, but at the cost of interpretability. We argue that integrating pragmatic reasoning into the inference of context-agnostic generation models could reconcile traits of traditional and neural REG, as this offers a separation between context-independent, literal information and pragmatic adaptation to context. With this in mind, we apply existing decoding strategies from discriminative image captioning to REG and evaluate them in terms of pragmatic informativity, likelihood to ground-truth annotations and linguistic diversity. Our results show general effectiveness, but a relatively small gain in informativity, raising important questions for REG in general.
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