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A Major Obstacle for NLP Research: Let’s Talk about Time Allocation!

Katharina Kann, Shiran Dudy, Arya D. McCarthy


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.
Anthology ID:
2022.emnlp-main.612
Volume:
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
Month:
December
Year:
2022
Address:
Abu Dhabi, United Arab Emirates
Editors:
Yoav Goldberg, Zornitsa Kozareva, Yue Zhang
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
8959–8969
Language:
URL:
https://aclanthology.org/2022.emnlp-main.612
DOI:
10.18653/v1/2022.emnlp-main.612
Bibkey:
Cite (ACL):
Katharina Kann, Shiran Dudy, and Arya D. McCarthy. 2022. A Major Obstacle for NLP Research: Let’s Talk about Time Allocation!. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, pages 8959–8969, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
A Major Obstacle for NLP Research: Let’s Talk about Time Allocation! (Kann et al., EMNLP 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.emnlp-main.612.pdf