Papers with character language models

2 papers
Subword models struggle with word learning, but surprisal hides it (2025.acl-short)

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Challenge: Subword LMs struggle to discern words and non-words with high accuracy, character LM models do this easily and consistently.
Approach: They propose to model word learning in subword and character language models with the psycholinguistic lexical decision task.
Outcome: The results suggest that word learning and syntactic learning are separable in character LMs.
Better Character Language Modeling through Morphology (P19-1)

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Challenge: Inflected words benefit more from explicitly modeling morphology than uninflectes . morphological supervision is also used to augment character language models in low-resource languages .
Approach: They add morphological supervision to character language models via multitasking to improve BPC performance across 24 languages even when morphology data and language modeling data are disjointed.
Outcome: The addition improves performance even when morphology data and language modeling data are disjointed.

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