Experimental Standards for Deep Learning in Natural Language Processing Research

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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.
TitelFindings of 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Antal sider20
Publikationsdato7 dec. 2022
StatusUdgivet - 7 dec. 2022
BegivenhedEmpirical Methods in Natural Language Processing - Abu Dhabi National Exhibition Center (ADNEC), Abu Dhabi, United Arab Emirates
Varighed: 7 dec. 202211 dec. 2022


KonferenceEmpirical Methods in Natural Language Processing
LokationAbu Dhabi National Exhibition Center (ADNEC)
Land/OmrådeUnited Arab Emirates
ByAbu Dhabi


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