Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora

Alex Warstadt; Aaron Mueller; Leshem Choshen; Ethan Wilcox; Chengxu Zhuang; Juan Ciro; Rafael Mosquera; Bhargavi Paranjabe; Adina Williams; Tal Linzen; Ryan Cotterell

doi:10.18653/v1/2023.conll-babylm.1

Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora

Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Wilcox, Chengxu Zhuang, Juan Ciro, Rafael Mosquera, Bhargavi Paranjabe, Adina Williams, Tal Linzen, Ryan Cotterell

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Anthology ID:: 2023.conll-babylm.1
Volume:: Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
Month:: December
Year:: 2023
Address:: Singapore
Editors:: Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Wilcox, Chengxu Zhuang, Juan Ciro, Rafael Mosquera, Bhargavi Paranjabe, Adina Williams, Tal Linzen, Ryan Cotterell
Venues:: CoNLL | BabyLM | WS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 1–34
Language:
URL:: https://aclanthology.org/2023.conll-babylm.1/
DOI:: 10.18653/v1/2023.conll-babylm.1
Bibkey:
Cite (ACL):: Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Wilcox, Chengxu Zhuang, Juan Ciro, Rafael Mosquera, Bhargavi Paranjabe, Adina Williams, Tal Linzen, and Ryan Cotterell. 2023. Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora. In Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning, pages 1–34, Singapore. Association for Computational Linguistics.
Cite (Informal):: Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora (Warstadt et al., CoNLL-BabyLM 2023)
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PDF:: https://aclanthology.org/2023.conll-babylm.1.pdf

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@inproceedings{warstadt-etal-2023-findings,
    title = "Findings of the {B}aby{LM} Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora",
    author = "Warstadt, Alex  and
      Mueller, Aaron  and
      Choshen, Leshem  and
      Wilcox, Ethan  and
      Zhuang, Chengxu  and
      Ciro, Juan  and
      Mosquera, Rafael  and
      Paranjabe, Bhargavi  and
      Williams, Adina  and
      Linzen, Tal  and
      Cotterell, Ryan",
    editor = "Warstadt, Alex  and
      Mueller, Aaron  and
      Choshen, Leshem  and
      Wilcox, Ethan  and
      Zhuang, Chengxu  and
      Ciro, Juan  and
      Mosquera, Rafael  and
      Paranjabe, Bhargavi  and
      Williams, Adina  and
      Linzen, Tal  and
      Cotterell, Ryan",
    booktitle = "Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning",
    month = dec,
    year = "2023",
    address = "Singapore",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.conll-babylm.1/",
    doi = "10.18653/v1/2023.conll-babylm.1",
    pages = "1--34"
}

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%0 Conference Proceedings
%T Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora
%A Warstadt, Alex
%A Mueller, Aaron
%A Choshen, Leshem
%A Wilcox, Ethan
%A Zhuang, Chengxu
%A Ciro, Juan
%A Mosquera, Rafael
%A Paranjabe, Bhargavi
%A Williams, Adina
%A Linzen, Tal
%A Cotterell, Ryan
%Y Warstadt, Alex
%Y Mueller, Aaron
%Y Choshen, Leshem
%Y Wilcox, Ethan
%Y Zhuang, Chengxu
%Y Ciro, Juan
%Y Mosquera, Rafael
%Y Paranjabe, Bhargavi
%Y Williams, Adina
%Y Linzen, Tal
%Y Cotterell, Ryan
%S Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F warstadt-etal-2023-findings
%R 10.18653/v1/2023.conll-babylm.1
%U https://aclanthology.org/2023.conll-babylm.1/
%U https://doi.org/10.18653/v1/2023.conll-babylm.1
%P 1-34

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Markdown (Informal)

[Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora](https://aclanthology.org/2023.conll-babylm.1/) (Warstadt et al., CoNLL-BabyLM 2023)

Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora (Warstadt et al., CoNLL-BabyLM 2023)

ACL

Alex Warstadt, Aaron Mueller, Leshem Choshen, Ethan Wilcox, Chengxu Zhuang, Juan Ciro, Rafael Mosquera, Bhargavi Paranjabe, Adina Williams, Tal Linzen, and Ryan Cotterell. 2023. Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora. In Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning, pages 1–34, Singapore. Association for Computational Linguistics.