Semantic Scholar Open Access 2022 6 sitasi

Towards Reproducible Machine Learning Research in Natural Language Processing

Ana Lucic Maurits J. R. Bleeker Samarth Bhargav Jessica Zosa Forde Koustuv Sinha +3 lainnya

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Abstrak

While recent progress in the field of ML has been significant, the reproducibility of these cutting-edge results is often lacking, with many submissions lacking the necessary information in order to ensure subsequent reproducibility. Despite proposals such as the Reproducibility Checklist and reproducibility criteria at several major conferences, the reflex for carrying out research with reproducibility in mind is lacking in the broader ML community. We propose this tutorial as a gentle introduction to ensuring reproducible research in ML, with a specific emphasis on computational linguistics and NLP. We also provide a framework for using reproducibility as a teaching tool in university-level computer science programs.

Topik & Kata Kunci

Computer Science

Penulis (8)

Ana Lucic

Maurits J. R. Bleeker

Samarth Bhargav

Jessica Zosa Forde

Koustuv Sinha

Jesse Dodge

Sasha Luccioni

Robert Stojnic

Format Sitasi

APA MLA BibTeX

Lucic, A., Bleeker, M.J.R., Bhargav, S., Forde, J.Z., Sinha, K., Dodge, J. et al. (2022). Towards Reproducible Machine Learning Research in Natural Language Processing. https://doi.org/10.18653/v1/2022.acl-tutorials.2

Akses Cepat

Lihat di Sumber doi.org/10.18653/v1/2022.acl-tutorials.2

Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Total Sitasi: 6×
Sumber Database: Semantic Scholar
DOI: 10.18653/v1/2022.acl-tutorials.2
Akses: Open Access ✓