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Register a new userSchema-Guided Paradigm for Zero-Shot Dialog
النموذج الموجه المخطط لحوار الصفر بالرصاص
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يعد تطوير آليات تكييف أنظمة الحوار المرنة للمهام والمجالات غير المرئية تحديا كبيرا في أبحاث الحوار.تحفظ النماذج العصبية ضمنيا سياسات الحوار الخاصة بمهام المهام من بيانات التدريب.نؤخر أن هذه الحفظ الضمنية قد حظرت التعلم تحويل الصفر بالرصاص.تحقيقا لهذه الغاية، نستفيد من النموذج الموجه المخطط، حيث يتم توفير سياسة الحوار الخاصة بمهام المهام بشكل صريح للنموذج.نقدم نموذج اهتمام المخطط (SAM) وتحسين تمثيلات المخطط للحصول على ستار كوربوس.يحصل SAM على تحسين كبير في إعدادات طلقة صفرية، مع تحسن درجة +22 F1 على العمل السابق.هذه النتائج التحقق من صحة جدوى عملية التعميم الصفري في مربع الحوار.يتم أيضا تقديم تجارب الاجتثاث لإظهار فعالية SAM.
Developing mechanisms that flexibly adapt dialog systems to unseen tasks and domains is a major challenge in dialog research. Neural models implicitly memorize task-specific dialog policies from the training data. We posit that this implicit memorization has precluded zero-shot transfer learning. To this end, we leverage the schema-guided paradigm, wherein the task-specific dialog policy is explicitly provided to the model. We introduce the Schema Attention Model (SAM) and improved schema representations for the STAR corpus. SAM obtains significant improvement in zero-shot settings, with a +22 F1 score improvement over prior work. These results validate the feasibility of zero-shot generalizability in dialog. Ablation experiments are also presented to demonstrate the efficacy of SAM.
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