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Register a new userESTIME: Estimation of Summary-to-Text Inconsistency by Mismatched Embeddings
ESTIME: تقدير عدم تناسق الملخص إلى النص عن طريق المغايات المدمجة
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نقترح إجراء تقييم جودة خاص بالرجوع إلى مرجعية، مع التركيز على الإخلاص.يعتمد الإجراء على إيجاد وعد جميع التناقضات المحتملة المحتملة في الملخص فيما يتعلق بالوثيقة المصدر.يرتبط مؤشر الإستيم المقترح ومقدر عدم تناسق الملخص من خلال المدينات غير المعطاة بدرجات الخبراء في مجموعة بيانات STOMEVAL للمستوى الملخص أقوى من تدابير التقييم المشتركة الأخرى ليس فقط في الاتساق ولكن أيضا في الطلاقة.نقدم أيضا طريقة لتوليد أخطاء واقعية خفية في ملخصات بشرية.نظهر أن ESTIME أكثر حساسية للأخطاء الدقيقة من تدابير التقييم المشتركة الأخرى.
We propose a new reference-free summary quality evaluation measure, with emphasis on the faithfulness. The measure is based on finding and counting all probable potential inconsistencies of the summary with respect to the source document. The proposed ESTIME, Estimator of Summary-to-Text Inconsistency by Mismatched Embeddings, correlates with expert scores in summary-level SummEval dataset stronger than other common evaluation measures not only in Consistency but also in Fluency. We also introduce a method of generating subtle factual errors in human summaries. We show that ESTIME is more sensitive to subtle errors than other common evaluation measures.
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