Too Much Information: Keeping Training Simple for BabyLMs

Lukas Edman; Lisa Bylinina

doi:10.18653/v1/2023.conll-babylm.8

Too Much Information: Keeping Training Simple for BabyLMs

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Anthology ID:: 2023.conll-babylm.8
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:: 89–97
Language:
URL:: https://aclanthology.org/2023.conll-babylm.8/
DOI:: 10.18653/v1/2023.conll-babylm.8
Bibkey:
Cite (ACL):: Lukas Edman and Lisa Bylinina. 2023. Too Much Information: Keeping Training Simple for BabyLMs. In Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning, pages 89–97, Singapore. Association for Computational Linguistics.
Cite (Informal):: Too Much Information: Keeping Training Simple for BabyLMs (Edman & Bylinina, CoNLL-BabyLM 2023)
Copy Citation:
PDF:: https://aclanthology.org/2023.conll-babylm.8.pdf

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@inproceedings{edman-bylinina-2023-much,
    title = "Too Much Information: Keeping Training Simple for {B}aby{LM}s",
    author = "Edman, Lukas  and
      Bylinina, Lisa",
    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.8/",
    doi = "10.18653/v1/2023.conll-babylm.8",
    pages = "89--97"
}

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%0 Conference Proceedings
%T Too Much Information: Keeping Training Simple for BabyLMs
%A Edman, Lukas
%A Bylinina, Lisa
%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 edman-bylinina-2023-much
%R 10.18653/v1/2023.conll-babylm.8
%U https://aclanthology.org/2023.conll-babylm.8/
%U https://doi.org/10.18653/v1/2023.conll-babylm.8
%P 89-97

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Markdown (Informal)

[Too Much Information: Keeping Training Simple for BabyLMs](https://aclanthology.org/2023.conll-babylm.8/) (Edman & Bylinina, CoNLL-BabyLM 2023)

Too Much Information: Keeping Training Simple for BabyLMs (Edman & Bylinina, CoNLL-BabyLM 2023)

ACL

Lukas Edman and Lisa Bylinina. 2023. Too Much Information: Keeping Training Simple for BabyLMs. In Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning, pages 89–97, Singapore. Association for Computational Linguistics.