Small Language Models Also Work With Small Vocabularies: Probing the Linguistic Abilities of Grapheme- and Phoneme-Based Baby Llamas

• URL: http://arxiv.org/abs/2410.01487v2
• Date: Fri, 03 Jan 2025 19:17:44 GMT
• Title: Small Language Models Also Work With Small Vocabularies: Probing the Linguistic Abilities of Grapheme- and Phoneme-Based Baby Llamas
• Authors: Bastian Bunzeck, Daniel Duran, Leonie Schade, Sina Zarrieß,
• Abstract summary: We show that tokenization-free, phoneme- and grapheme-based language models can achieve strong linguistic performance. Our findings suggest a promising direction for creating more linguistically plausible language models.
• Score: 7.585433383340306
• License:
• Abstract: Recent work investigates whether LMs learn human-like linguistic generalizations and representations from developmentally plausible amounts of data. Yet, the basic linguistic units processed in these LMs are determined by subword-based tokenization, which limits their validity as models of learning at and below the word level. In this paper, we explore the potential of tokenization-free, phoneme- and grapheme-based language models. We demonstrate that small models based on the Llama architecture can achieve strong linguistic performance on standard syntactic and novel lexical/phonetic benchmarks when trained with character-level vocabularies. We further show that phoneme-based models almost match grapheme-based models in standard tasks and novel evaluations. Our findings suggest a promising direction for creating more linguistically plausible language models that are better suited for computational studies of language acquisition and processing.

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