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arXiv · 2603.19427

Vocabulary shapes cross-lingual variation of word-order learnability in language models

Jonas Mayer Martins·Jaap Jumelet·Viola Priesemann·Lisa Beinborn
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Abstract

Why do some languages like Czech permit free word order, while others like English do not? We address this question by pretraining transformer language models on a spectrum of synthetic word-order variants of natural languages. We observe that greater word-order irregularity consistently raises model surprisal, indicating reduced learnability. Sentence reversal, however, affects learnability only weakly. A coarse distinction of free- (e.g., Czech and Finnish) and fixed-word-order languages (e.g., English and French) does not explain cross-lingual variation. Instead, the structure of the word and subword vocabulary strongly predicts the model surprisal. Overall, vocabulary structure emerges as a key driver of computational word-order learnability across languages.

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Jonas Mayer Martins, Jaap Jumelet, Viola Priesemann, Lisa Beinborn. 2026-03-19. Vocabulary shapes cross-lingual variation of word-order learnability in language models. https://arxiv.org/abs/2603.19427

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