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What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages

Borenstein, Nadav; Svete, Anej; Chan, Robin; Valvoda, Josef; Nowak, Franz; Augenstein, Isabelle; Chodroff, Eleanor; Cotterell, Ryan (2024). What Languages are Easy to Language-Model? A Perspective from Learning Probabilistic Regular Languages. In: Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Bangkok, Thailand, 1 August 2024, 15115-15134.

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Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
06 Faculty of Arts > Zurich Center for Linguistics
Dewey Decimal Classification:410 Linguistics
000 Computer science, knowledge & systems
Scopus Subject Areas:Physical Sciences > Computer Science Applications
Social Sciences & Humanities > Linguistics and Language
Social Sciences & Humanities > Language and Linguistics
Language:English
Event End Date:1 August 2024
Deposited On:10 Jan 2025 10:42
Last Modified:29 Jan 2025 05:54
OA Status:Green
Publisher DOI:https://doi.org/10.18653/v1/2024.acl-long.807
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  • Language: English
  • Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)

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