Investigating strategies for lexical complexity prediction in a multilingual setting using generative language models and supervised approaches - ACL Anthology

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Investigating strategies for lexical complexity prediction in a multilingual setting using generative language models and supervised approaches

Abdelhak Kelious, Mathieu Constant, Christophe Coeur

Anthology ID:: 2024.nlp4call-1.8
Volume:: Proceedings of the 13th Workshop on Natural Language Processing for Computer Assisted Language Learning
Month:: October
Year:: 2024
Address:: Rennes, France
Editors:: Thomas Gaillat, Cyriel Mallart, Fabienne Moreau, Jen-Yu Li, Griselda Drouet, David Alfter, Elena Volodina, Arne Jönsson
Venues:: NLP4CALL | WS
SIG:: SIGEDU
Publisher:: LiU Electronic Press
Note:
Pages:: 96–114
Language:
URL:: https://aclanthology.org/2024.nlp4call-1.8
DOI:
Bibkey:
Cite (ACL):: Abdelhak Kelious, Mathieu Constant, and Christophe Coeur. 2024. Investigating strategies for lexical complexity prediction in a multilingual setting using generative language models and supervised approaches. In Proceedings of the 13th Workshop on Natural Language Processing for Computer Assisted Language Learning, pages 96–114, Rennes, France. LiU Electronic Press.
Cite (Informal):: Investigating strategies for lexical complexity prediction in a multilingual setting using generative language models and supervised approaches (Kelious et al., NLP4CALL-WS 2024)
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PDF:: https://preview.aclanthology.org/dois-2013-emnlp/2024.nlp4call-1.8.pdf