Abstract
The field of Deep Learning (DL) has undergone explosive growth during the last decade, with a substantial impact on Natural Language Processing (NLP) as well. Yet, compared to more established disciplines, a lack of common experimental standards remains an open challenge to the field at large. Starting from fundamental scientific principles, we distill ongoing discussions on experimental standards in NLP into a single, widely-applicable methodology. Following these best practices is crucial to strengthen experimental evidence, improve reproducibility and support scientific progress. These standards are further collected in a public repository to help them transparently adapt to future needs.
Originalsprog | Engelsk |
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Titel | Findings of 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP) |
Antal sider | 20 |
Publikationsdato | 7 dec. 2022 |
DOI | |
Status | Udgivet - 7 dec. 2022 |
Begivenhed | Empirical Methods in Natural Language Processing - Abu Dhabi National Exhibition Center (ADNEC), Abu Dhabi, United Arab Emirates Varighed: 7 dec. 2022 → 11 dec. 2022 https://2022.emnlp.org/ |
Konference
Konference | Empirical Methods in Natural Language Processing |
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Lokation | Abu Dhabi National Exhibition Center (ADNEC) |
Land/Område | United Arab Emirates |
By | Abu Dhabi |
Periode | 07/12/2022 → 11/12/2022 |
Internetadresse |
Emneord
- Deep Learning
- Natural Language Processing
- Experimental Standards
- Reproducibility
- Scientific Methodology