CALaMo: a Constructionist Assessment of Language Models

Fuente: arXiv
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Autores principales: Pannitto, Ludovica, Herbelot, Aurélie
Formato: Preprint
Publicado: 2023
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author Pannitto, Ludovica
Herbelot, Aurélie
author_facet Pannitto, Ludovica
Herbelot, Aurélie
contents This paper presents a novel framework for evaluating Neural Language Models' linguistic abilities using a constructionist approach. Not only is the usage-based model in line with the underlying stochastic philosophy of neural architectures, but it also allows the linguist to keep meaning as a determinant factor in the analysis. We outline the framework and present two possible scenarios for its application.
format Preprint
id arxiv_https___arxiv_org_abs_2302_03589
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle CALaMo: a Constructionist Assessment of Language Models
Pannitto, Ludovica
Herbelot, Aurélie
Computation and Language
This paper presents a novel framework for evaluating Neural Language Models' linguistic abilities using a constructionist approach. Not only is the usage-based model in line with the underlying stochastic philosophy of neural architectures, but it also allows the linguist to keep meaning as a determinant factor in the analysis. We outline the framework and present two possible scenarios for its application.
title CALaMo: a Constructionist Assessment of Language Models
topic Computation and Language
url https://arxiv.org/abs/2302.03589