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Register a new userAssessing Reference-Free Peer Evaluation for Machine Translation
تقييم تقييم الأقران الخالي من المرجعية للترجمة الآلية
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التقييم الخالي من المرجع لديه القدرة على جعل تقييم الترجمة الآلية أكثر قابلية للتطوير بشكل كبير، مما يتيح لنا المحور بسهولة لغات أو مجالات جديدة.لقد أظهر مؤخرا أن الاحتمالات التي قدمتها نموذج كبير متعدد اللغات يمكن أن تحقق حالة من النتائج الفنية عند استخدامها كتقسيط مجاني مرجعي.نقوم بتجربة تعديلات مختلفة لهذا النموذج، وإظهار ذلك من خلال تحجيمه، يمكننا مطابقة أداء بلو.نقوم بتحليل نقاط الضعف المحتملة المختلفة للنهج، وتجد أنه قوي بشكل مدهش ومن المرجح أن تقدم أداء معقول عبر مجموعة واسعة من المجالات وصفات النظام المختلفة.
Reference-free evaluation has the potential to make machine translation evaluation substantially more scalable, allowing us to pivot easily to new languages or domains. It has been recently shown that the probabilities given by a large, multilingual model can achieve state of the art results when used as a reference-free metric. We experiment with various modifications to this model, and demonstrate that by scaling it up we can match the performance of BLEU. We analyze various potential weaknesses of the approach, and find that it is surprisingly robust and likely to offer reasonable performance across a broad spectrum of domains and different system qualities.
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