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Register a new userSiamese Networks for Inference in Malayalam Language Texts
شبكات سيامي للاستدلال في نصوص لغة مالايالامية
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إن الاستدلال اللغوي الطبيعي هو طريقة لإيجاد الاستدلالات في نصوص اللغة.فهم معنى الجملة واستدلالها أمر ضروري في العديد من تطبيقات معالجة اللغة.في هذا السياق، نعتبر مشكلة الاستدلال بلغة Dravidian، مالايالام.تدرب شبكات سيامي أزواج فرضية النص مع Adgeddings Word و Argeddings اللازم، ويتم تقييم النتائج مقابل مقاييس التصنيف للتصنيف الثنائي في دروس الاستقصاء والتناقض.توفر XLM-R AMBEBINGS القائم على الهندسة المعمارية السيامية باستخدام الوحدات المتكررة الدائرية وشبكات الذاكرة القصيرة الأجل الثنائية لفترة طويلة نتائج واعدة لمشكلة التصنيف هذه.
Natural language inference is a method of finding inferences in language texts. Understanding the meaning of a sentence and its inference is essential in many language processing applications. In this context, we consider the inference problem for a Dravidian language, Malayalam. Siamese networks train the text hypothesis pairs with word embeddings and language agnostic embeddings, and the results are evaluated against classification metrics for binary classification into entailment and contradiction classes. XLM-R embeddings based Siamese architecture using gated recurrent units and bidirectional long short term memory networks provide promising results for this classification problem.
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