@inproceedings{clinciu-etal-2021-commonsense,
title = "It{'}s Commonsense, isn{'}t it? Demystifying Human Evaluations in Commonsense-Enhanced {NLG} Systems",
author = "Clinciu, Miruna-Adriana and
Gkatzia, Dimitra and
Mahamood, Saad",
editor = "Belz, Anya and
Agarwal, Shubham and
Graham, Yvette and
Reiter, Ehud and
Shimorina, Anastasia",
booktitle = "Proceedings of the Workshop on Human Evaluation of NLP Systems (HumEval)",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.humeval-1.1",
pages = "1--12",
abstract = "Common sense is an integral part of human cognition which allows us to make sound decisions, communicate effectively with others and interpret situations and utterances. Endowing AI systems with commonsense knowledge capabilities will help us get closer to creating systems that exhibit human intelligence. Recent efforts in Natural Language Generation (NLG) have focused on incorporating commonsense knowledge through large-scale pre-trained language models or by incorporating external knowledge bases. Such systems exhibit reasoning capabilities without common sense being explicitly encoded in the training set. These systems require careful evaluation, as they incorporate additional resources during training which adds additional sources of errors. Additionally, human evaluation of such systems can have significant variation, making it impossible to compare different systems and define baselines. This paper aims to demystify human evaluations of commonsense-enhanced NLG systems by proposing the Commonsense Evaluation Card (CEC), a set of recommendations for evaluation reporting of commonsense-enhanced NLG systems, underpinned by an extensive analysis of human evaluations reported in the recent literature.",
}
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<abstract>Common sense is an integral part of human cognition which allows us to make sound decisions, communicate effectively with others and interpret situations and utterances. Endowing AI systems with commonsense knowledge capabilities will help us get closer to creating systems that exhibit human intelligence. Recent efforts in Natural Language Generation (NLG) have focused on incorporating commonsense knowledge through large-scale pre-trained language models or by incorporating external knowledge bases. Such systems exhibit reasoning capabilities without common sense being explicitly encoded in the training set. These systems require careful evaluation, as they incorporate additional resources during training which adds additional sources of errors. Additionally, human evaluation of such systems can have significant variation, making it impossible to compare different systems and define baselines. This paper aims to demystify human evaluations of commonsense-enhanced NLG systems by proposing the Commonsense Evaluation Card (CEC), a set of recommendations for evaluation reporting of commonsense-enhanced NLG systems, underpinned by an extensive analysis of human evaluations reported in the recent literature.</abstract>
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%0 Conference Proceedings
%T It’s Commonsense, isn’t it? Demystifying Human Evaluations in Commonsense-Enhanced NLG Systems
%A Clinciu, Miruna-Adriana
%A Gkatzia, Dimitra
%A Mahamood, Saad
%Y Belz, Anya
%Y Agarwal, Shubham
%Y Graham, Yvette
%Y Reiter, Ehud
%Y Shimorina, Anastasia
%S Proceedings of the Workshop on Human Evaluation of NLP Systems (HumEval)
%D 2021
%8 April
%I Association for Computational Linguistics
%C Online
%F clinciu-etal-2021-commonsense
%X Common sense is an integral part of human cognition which allows us to make sound decisions, communicate effectively with others and interpret situations and utterances. Endowing AI systems with commonsense knowledge capabilities will help us get closer to creating systems that exhibit human intelligence. Recent efforts in Natural Language Generation (NLG) have focused on incorporating commonsense knowledge through large-scale pre-trained language models or by incorporating external knowledge bases. Such systems exhibit reasoning capabilities without common sense being explicitly encoded in the training set. These systems require careful evaluation, as they incorporate additional resources during training which adds additional sources of errors. Additionally, human evaluation of such systems can have significant variation, making it impossible to compare different systems and define baselines. This paper aims to demystify human evaluations of commonsense-enhanced NLG systems by proposing the Commonsense Evaluation Card (CEC), a set of recommendations for evaluation reporting of commonsense-enhanced NLG systems, underpinned by an extensive analysis of human evaluations reported in the recent literature.
%U https://aclanthology.org/2021.humeval-1.1
%P 1-12
Markdown (Informal)
[It’s Commonsense, isn’t it? Demystifying Human Evaluations in Commonsense-Enhanced NLG Systems](https://aclanthology.org/2021.humeval-1.1) (Clinciu et al., HumEval 2021)
ACL