Underreporting of errors in NLG output, and what to do about it

التفاصيل البيبلوغرافية
العنوان: Underreporting of errors in NLG output, and what to do about it
المؤلفون: van Miltenburg, Emiel, Clinciu, Miruna-Adriana, Dušek, Ondřej, Gkatzia, Dimitra, Inglis, Stephanie, Leppänen, Leo, Mahamood, Saad, Manning, Emma, Schoch, Stephanie, Thomson, Craig, Wen, Luou
سنة النشر: 2021
المجموعة: Computer Science
مصطلحات موضوعية: Computer Science - Computation and Language
الوصف: We observe a severe under-reporting of the different kinds of errors that Natural Language Generation systems make. This is a problem, because mistakes are an important indicator of where systems should still be improved. If authors only report overall performance metrics, the research community is left in the dark about the specific weaknesses that are exhibited by `state-of-the-art' research. Next to quantifying the extent of error under-reporting, this position paper provides recommendations for error identification, analysis and reporting.
Comment: Prefinal version, accepted for publication in the Proceedings of the 14th International Conference on Natural Language Generation (INLG 2021, Aberdeen). Comments welcome
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/2108.01182
رقم الأكسشن: edsarx.2108.01182
قاعدة البيانات: arXiv