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Register a new userClaim Verification Using a Multi-GAN Based Model
المطالبة بالتحقق باستخدام نموذج متعدد الجنس
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توضح هذه المقالة البحث عن التحقق من المطالبة المنفذة باستخدام نموذج متعدد القائم على GAN.يتكون النموذج المقترح من ثلاثة أزواج من المولدات والتمييز.المولد والأزواج التمييزية مسؤولة عن توليد البيانات الاصطناعية للمطالبات المدعومة والمطالبة الدوحدة وتسميات المطالبة.يتم توفير مناقشة نظرية حول النموذج المقترح للتحقق من صحة حالة التوازن للنموذج.يتم تطبيق النموذج المقترح على مجموعة بيانات الحمى، يتم استخدام نموذج لغة مدرب مسبقا لبيانات نص الإدخال.تساعد البيانات التي تم إنشاؤها بشكل شبكي على الحصول على معلومات تعمل على تحسين أداء التصنيف فوق خطوط الأساس الفنية.عشر درجات F1 المعنية بعد تطبيق الأسلوب المقترح في Fever 1.0 ومجموعات بيانات Fever 2.0 هي 0.65 + -0.018 و 0.65 + -0.051.
This article describes research on claim verification carried out using a multiple GAN-based model. The proposed model consists of three pairs of generators and discriminators. The generator and discriminator pairs are responsible for generating synthetic data for supported and refuted claims and claim labels. A theoretical discussion about the proposed model is provided to validate the equilibrium state of the model. The proposed model is applied to the FEVER dataset, and a pre-trained language model is used for the input text data. The synthetically generated data helps to gain information that improves classification performance over state of the art baselines. The respective F1 scores after applying the proposed method on FEVER 1.0 and FEVER 2.0 datasets are 0.65+-0.018 and 0.65+-0.051.
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