Experimental Standards for Deep Learning in Natural Language Processing Research

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review


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 languageEnglish
Title of host publicationFindings of 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Number of pages20
Publication date7 Dec 2022
Publication statusPublished - 7 Dec 2022
EventEmpirical Methods in Natural Language Processing - Abu Dhabi National Exhibition Center (ADNEC), Abu Dhabi, United Arab Emirates
Duration: 7 Dec 202211 Dec 2022


ConferenceEmpirical Methods in Natural Language Processing
LocationAbu Dhabi National Exhibition Center (ADNEC)
Country/TerritoryUnited Arab Emirates
CityAbu Dhabi
Internet address


  • Deep Learning
  • Natural Language Processing
  • Experimental Standards
  • Reproducibility
  • Scientific Methodology


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