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.
Original language | English |
---|---|
Title of host publication | Findings of 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP) |
Number of pages | 20 |
Publication date | 7 Dec 2022 |
DOIs | |
Publication status | Published - 7 Dec 2022 |
Event | Empirical Methods in Natural Language Processing - Abu Dhabi National Exhibition Center (ADNEC), Abu Dhabi, United Arab Emirates Duration: 7 Dec 2022 → 11 Dec 2022 https://2022.emnlp.org/ |
Conference
Conference | Empirical Methods in Natural Language Processing |
---|---|
Location | Abu Dhabi National Exhibition Center (ADNEC) |
Country/Territory | United Arab Emirates |
City | Abu Dhabi |
Period | 07/12/2022 → 11/12/2022 |
Internet address |
Keywords
- Deep Learning
- Natural Language Processing
- Experimental Standards
- Reproducibility
- Scientific Methodology