@inproceedings{belz-etal-2024-inlg,
title = "The {INLG} 2024 Tutorial on Human Evaluation of {NLP} System Quality: Background, Overall Aims, and Summaries of Taught Units",
author = "Belz, Anya and
Sedoc, Jo{\~a}o and
Thomson, Craig and
Mille, Simon and
Huidrom, Rudali",
editor = "Belz, Anya and
Sedo, Jo{\~a}o and
Thomson, Craig and
Mille, Simon and
Huidrom, Rudali",
booktitle = "Proceedings of the 17th International Natural Language Generation Conference: Tutorial Abstract",
month = sep,
year = "2024",
address = "Tokyo, Japan",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.inlg-tutorials.1",
pages = "1--12",
abstract = "Following numerous calls in the literature for improved practices and standardisation in human evaluation in Natural Language Processing over the past ten years, we held a tutorial on the topic at the 2024 INLG Conference. The tutorial addressed the structure, development, design, implementation, execution and analysis of human evaluations of NLP system quality. Hands-on practical sessions were run, designed to facilitate assimilation of the material presented. Slides, lecture recordings, code and data have been made available on GitHub (https://github.com/Human-Evaluation-Tutorial/INLG-2024-Tutorial). In this paper, we provide summaries of the content of the eight units of the tutorial, alongside its research context and aims.",
}
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<abstract>Following numerous calls in the literature for improved practices and standardisation in human evaluation in Natural Language Processing over the past ten years, we held a tutorial on the topic at the 2024 INLG Conference. The tutorial addressed the structure, development, design, implementation, execution and analysis of human evaluations of NLP system quality. Hands-on practical sessions were run, designed to facilitate assimilation of the material presented. Slides, lecture recordings, code and data have been made available on GitHub (https://github.com/Human-Evaluation-Tutorial/INLG-2024-Tutorial). In this paper, we provide summaries of the content of the eight units of the tutorial, alongside its research context and aims.</abstract>
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%0 Conference Proceedings
%T The INLG 2024 Tutorial on Human Evaluation of NLP System Quality: Background, Overall Aims, and Summaries of Taught Units
%A Belz, Anya
%A Sedoc, João
%A Thomson, Craig
%A Mille, Simon
%A Huidrom, Rudali
%Y Belz, Anya
%Y Sedo, João
%Y Thomson, Craig
%Y Mille, Simon
%Y Huidrom, Rudali
%S Proceedings of the 17th International Natural Language Generation Conference: Tutorial Abstract
%D 2024
%8 September
%I Association for Computational Linguistics
%C Tokyo, Japan
%F belz-etal-2024-inlg
%X Following numerous calls in the literature for improved practices and standardisation in human evaluation in Natural Language Processing over the past ten years, we held a tutorial on the topic at the 2024 INLG Conference. The tutorial addressed the structure, development, design, implementation, execution and analysis of human evaluations of NLP system quality. Hands-on practical sessions were run, designed to facilitate assimilation of the material presented. Slides, lecture recordings, code and data have been made available on GitHub (https://github.com/Human-Evaluation-Tutorial/INLG-2024-Tutorial). In this paper, we provide summaries of the content of the eight units of the tutorial, alongside its research context and aims.
%U https://aclanthology.org/2024.inlg-tutorials.1
%P 1-12
Markdown (Informal)
[The INLG 2024 Tutorial on Human Evaluation of NLP System Quality: Background, Overall Aims, and Summaries of Taught Units](https://aclanthology.org/2024.inlg-tutorials.1) (Belz et al., INLG 2024)
ACL