أهداف المحاذاة الكامنة مثل CTC والفأس تحسن بشكل كبير نماذج الترجمة الآلية غير التلقائي.هل يمكنهم تحسين النماذج التلقائية أيضا؟نستكشف إمكانية تدريب نماذج الترجمة الآلية ذات الجهاز التلقائي بأهداف محاذاة كامنة، ومراقبة ذلك، في الممارسة العملية، ينتج هذا النهج نماذج التدهور.نحن نقدم شرحا نظريا لهذه النتائج التجريبية، وأثبت أن أهداف المحاذاة الكامنة غير متوافقة مع إجبار المعلم.
Latent alignment objectives such as CTC and AXE significantly improve non-autoregressive machine translation models. Can they improve autoregressive models as well? We explore the possibility of training autoregressive machine translation models with latent alignment objectives, and observe that, in practice, this approach results in degenerate models. We provide a theoretical explanation for these empirical results, and prove that latent alignment objectives are incompatible with teacher forcing.
References used
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