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On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?

E. Bender, T. Gebru, A. McMillan-Major, and S. Shmitchell. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, page 610–623. New York, NY, USA, Association for Computing Machinery, (2021)
DOI: 10.1145/3442188.3445922

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David McMillan

Tamara Major

Péter Major

Karlheinz Major

Herbert Major

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Reusable Templates and Guides For Documenting Datasets and Models for Natural Language Processing and Generation: A Case Study of the HuggingFace and GEM Data and Model Cards.A. McMillan-Major, S. Osei, J. Rodriguez, P. Ammanamanchi, S. Gehrmann, and Y. Jernite. CoRR, (2021)GEMv2: Multilingual NLG Benchmarking in a Single Line of Code.S. Gehrmann, A. Bhattacharjee, A. Mahendiran, A. Wang, A. Papangelis, A. Madaan, A. McMillan-Major, A. Shvets, A. Upadhyay, B. Yao and 66 other author(s). CoRR, (2022)Datasets: A Community Library for Natural Language Processing.Q. Lhoest, A. del Moral, Y. Jernite, A. Thakur, P. von Platen, S. Patil, J. Chaumond, M. Drame, J. Plu, L. Tunstall and 22 other author(s). EMNLP (Demos), page 175-184. Association for Computational Linguistics, (2021)GEMv2: Multilingual NLG Benchmarking in a Single Line of Code.S. Gehrmann, A. Bhattacharjee, A. Mahendiran, A. Wang, A. Papangelis, A. Madaan, A. McMillan-Major, A. Shvets, A. Upadhyay, and B. Bohnet. EMNLP (Demos), page 266-281. Association for Computational Linguistics, (2022)On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?E. Bender, T. Gebru, A. McMillan-Major, and S. Shmitchell. FAccT, page 610-623. ACM, (2021)BLOOM: A 176B-Parameter Open-Access Multilingual Language Model.T. Scao, A. Fan, C. Akiki, E. Pavlick, S. Ilic, D. Hesslow, R. Castagné, A. Luccioni, F. Yvon, M. Gallé and 39 other author(s). CoRR, (2022)The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics.S. Gehrmann, T. Adewumi, K. Aggarwal, P. Ammanamanchi, A. Anuoluwapo, A. Bosselut, K. Chandu, M. Clinciu, D. Das, K. Dhole and 45 other author(s). CoRR, (2021)The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset.H. Laurençon, L. Saulnier, T. Wang, C. Akiki, A. del Moral, T. Scao, L. von Werra, C. Mou, E. Ponferrada, H. Nguyen and 44 other author(s). CoRR, (2023)Measuring Data.M. Mitchell, A. Luccioni, N. Lambert, M. Gerchick, A. McMillan-Major, E. Ozoani, N. Rajani, T. Thrush, Y. Jernite, and D. Kiela. CoRR, (2022)The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset.H. Laurençon, L. Saulnier, T. Wang, C. Akiki, A. del Moral, T. Scao, L. von Werra, C. Mou, E. Ponferrada, H. Nguyen and 44 other author(s). NeurIPS, (2022)

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Disambiguation of "McMillan-Major, Angelina"

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On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?

Please choose a person to relate this publication to

David McMillan

Tamara Major

Péter Major

Karlheinz Major

Herbert Major

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "McMillan-Major, Angelina"

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?

Please choose a person to relate this publication to

David McMillan

Tamara Major

Péter Major

Karlheinz Major

Herbert Major

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
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URL
DOI
BibTeX
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On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?