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Register a new userThe Curious Case of Hallucinations in Neural Machine Translation
حالة الغريب من الهلوسة في الترجمة الآلية العصبية
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في هذا العمل، ندرس الهلوسة في الترجمة الآلية العصبية (NMT)، والتي تكمن في نهاية متطرفة على طيف أمراض NMT.أولا، نربط ظاهرة الهلوسة تحت اضطراب المصدر إلى النظرية الطويلة للذيل من فيلدمان، وتقديم فرضية صحيحة تجريبية تشرح الهلوسة تحت اضطرابات المصدر.ثانيا، نفكر في الهلوسة بموجب الضوضاء على مستوى Corpus (بدون أي اضطراب مصدر) وإظهار أن هناك نوعين بارزين من الهلوسة الطبيعية (النواتج المنفجرة والتذمر) يمكن أن يتم توليدها وشرحها من خلال أنماط ضوضاء ذات مستوى كوربوس معين.أخيرا، نوضح ظاهرة التضخيم الهلوسي في عمليات توليد البيانات الشعبية مثل تقطير المعارف على مستوى البيانات والتسلسل.لقد أصدرنا مجموعات البيانات والرمز لتكرار نتائجنا.
In this work, we study hallucinations in Neural Machine Translation (NMT), which lie at an extreme end on the spectrum of NMT pathologies. Firstly, we connect the phenomenon of hallucinations under source perturbation to the Long-Tail theory of Feldman, and present an empirically validated hypothesis that explains hallucinations under source perturbation. Secondly, we consider hallucinations under corpus-level noise (without any source perturbation) and demonstrate that two prominent types of natural hallucinations (detached and oscillatory outputs) could be generated and explained through specific corpus-level noise patterns. Finally, we elucidate the phenomenon of hallucination amplification in popular data-generation processes such as Backtranslation and sequence-level Knowledge Distillation. We have released the datasets and code to replicate our results.
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