@inproceedings{kann-etal-2022-major,
title = "A Major Obstacle for {NLP} Research: Let{'}s Talk about Time Allocation!",
author = "Kann, Katharina and
Dudy, Shiran and
McCarthy, Arya D.",
editor = "Goldberg, Yoav and
Kozareva, Zornitsa and
Zhang, Yue",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.emnlp-main.612",
doi = "10.18653/v1/2022.emnlp-main.612",
pages = "8959--8969",
abstract = "The field of natural language processing (NLP) has grown over the last few years: conferences have become larger, we have published an incredible amount of papers, and state-of-the-art research has been implemented in a large variety of customer-facing products. However, this paper argues that we have been less successful than we *should* have been and reflects on where and how the field fails to tap its full potential. Specifically, we demonstrate that, in recent years, **subpar time allocation has been a major obstacle for NLP research**. We outline multiple concrete problems together with their negative consequences and, importantly, suggest remedies to improve the status quo. We hope that this paper will be a starting point for discussions around which common practices are {--} or are *not* {--} beneficial for NLP research.",
}
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%0 Conference Proceedings
%T A Major Obstacle for NLP Research: Let’s Talk about Time Allocation!
%A Kann, Katharina
%A Dudy, Shiran
%A McCarthy, Arya D.
%Y Goldberg, Yoav
%Y Kozareva, Zornitsa
%Y Zhang, Yue
%S Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
%D 2022
%8 December
%I Association for Computational Linguistics
%C Abu Dhabi, United Arab Emirates
%F kann-etal-2022-major
%X The field of natural language processing (NLP) has grown over the last few years: conferences have become larger, we have published an incredible amount of papers, and state-of-the-art research has been implemented in a large variety of customer-facing products. However, this paper argues that we have been less successful than we *should* have been and reflects on where and how the field fails to tap its full potential. Specifically, we demonstrate that, in recent years, **subpar time allocation has been a major obstacle for NLP research**. We outline multiple concrete problems together with their negative consequences and, importantly, suggest remedies to improve the status quo. We hope that this paper will be a starting point for discussions around which common practices are – or are *not* – beneficial for NLP research.
%R 10.18653/v1/2022.emnlp-main.612
%U https://aclanthology.org/2022.emnlp-main.612
%U https://doi.org/10.18653/v1/2022.emnlp-main.612
%P 8959-8969
Markdown (Informal)
[A Major Obstacle for NLP Research: Let’s Talk about Time Allocation!](https://aclanthology.org/2022.emnlp-main.612) (Kann et al., EMNLP 2022)
ACL