@inproceedings{van-miltenburg-etal-2021-underreporting,
title = "Underreporting of errors in {NLG} output, and what to do about it",
author = {van Miltenburg, Emiel and
Clinciu, Miruna and
Du{\v{s}}ek, Ond{\v{r}}ej and
Gkatzia, Dimitra and
Inglis, Stephanie and
Lepp{\"a}nen, Leo and
Mahamood, Saad and
Manning, Emma and
Schoch, Stephanie and
Thomson, Craig and
Wen, Luou},
editor = "Belz, Anya and
Fan, Angela and
Reiter, Ehud and
Sripada, Yaji",
booktitle = "Proceedings of the 14th International Conference on Natural Language Generation",
month = aug,
year = "2021",
address = "Aberdeen, Scotland, UK",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.inlg-1.14/",
doi = "10.18653/v1/2021.inlg-1.14",
pages = "140--153",
abstract = "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 {\textquoteleft}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."
}
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%0 Conference Proceedings
%T Underreporting of errors in NLG output, and what to do about it
%A van Miltenburg, Emiel
%A Clinciu, Miruna
%A Dušek, Ondřej
%A Gkatzia, Dimitra
%A Inglis, Stephanie
%A Leppänen, Leo
%A Mahamood, Saad
%A Manning, Emma
%A Schoch, Stephanie
%A Thomson, Craig
%A Wen, Luou
%Y Belz, Anya
%Y Fan, Angela
%Y Reiter, Ehud
%Y Sripada, Yaji
%S Proceedings of the 14th International Conference on Natural Language Generation
%D 2021
%8 August
%I Association for Computational Linguistics
%C Aberdeen, Scotland, UK
%F van-miltenburg-etal-2021-underreporting
%X 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.
%R 10.18653/v1/2021.inlg-1.14
%U https://aclanthology.org/2021.inlg-1.14/
%U https://doi.org/10.18653/v1/2021.inlg-1.14
%P 140-153
Markdown (Informal)
[Underreporting of errors in NLG output, and what to do about it](https://aclanthology.org/2021.inlg-1.14/) (van Miltenburg et al., INLG 2021)
ACL
- Emiel van Miltenburg, Miruna Clinciu, Ondřej Dušek, Dimitra Gkatzia, Stephanie Inglis, Leo Leppänen, Saad Mahamood, Emma Manning, Stephanie Schoch, Craig Thomson, and Luou Wen. 2021. Underreporting of errors in NLG output, and what to do about it. In Proceedings of the 14th International Conference on Natural Language Generation, pages 140–153, Aberdeen, Scotland, UK. Association for Computational Linguistics.