Subword models struggle with word learning, but surprisal hides it

Fuente: arXiv
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Autores principales: Bunzeck, Bastian, Zarrieß, Sina
Formato: Preprint
Publicado: 2025
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author Bunzeck, Bastian
Zarrieß, Sina
author_facet Bunzeck, Bastian
Zarrieß, Sina
contents We study word learning in subword and character language models with the psycholinguistic lexical decision task. While subword LMs struggle to discern words and non-words with high accuracy, character LMs solve this task easily and consistently. Only when supplied with further contexts do subword LMs perform similarly to character models. Additionally, when looking at word-level and syntactic learning trajectories, we find that both processes are separable in character LMs. Word learning happens before syntactic learning, whereas both occur simultaneously in subword LMs. This raises questions about the adequacy of subword LMs for modeling language acquisition and positions character LMs as a viable alternative to study processes below the syntactic level.
format Preprint
id arxiv_https___arxiv_org_abs_2502_12835
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Subword models struggle with word learning, but surprisal hides it
Bunzeck, Bastian
Zarrieß, Sina
Computation and Language
We study word learning in subword and character language models with the psycholinguistic lexical decision task. While subword LMs struggle to discern words and non-words with high accuracy, character LMs solve this task easily and consistently. Only when supplied with further contexts do subword LMs perform similarly to character models. Additionally, when looking at word-level and syntactic learning trajectories, we find that both processes are separable in character LMs. Word learning happens before syntactic learning, whereas both occur simultaneously in subword LMs. This raises questions about the adequacy of subword LMs for modeling language acquisition and positions character LMs as a viable alternative to study processes below the syntactic level.
title Subword models struggle with word learning, but surprisal hides it
topic Computation and Language
url https://arxiv.org/abs/2502.12835