Dictionaries to the Rescue: Cross-Lingual Vocabulary Transfer for Low-Resource Languages Using Bilingual Dictionaries

Haruki Sakajo, Yusuke Ide, Justin Vasselli, Yusuke Sakai, Yingtao Tian +2 more
6/2/2025
cs.CLcs.AI

No official code found. Best implementation: sj-h4/dict_trans_tokenizer (0 stars, Apache-2.0, last commit 2026-02-10).

Abstract

Cross-lingual vocabulary transfer plays a promising role in adapting pre-trained language models to new languages, including low-resource languages. Existing approaches that utilize monolingual or parallel corpora face challenges when applied to languages with limited resources. In this work, we propose a simple yet effective vocabulary transfer method that utilizes bilingual dictionaries, which are available for many languages, thanks to descriptive linguists. Our proposed method leverages a property of BPE tokenizers where removing a subword from the vocabulary causes a fallback to shorter subwords. The embeddings of target subwords are estimated iteratively by progressively removing them from the tokenizer. The experimental results show that our approach outperforms existing methods for low-resource languages, demonstrating the effectiveness of a dictionary-based approach for cross-lingual vocabulary transfer.

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Apache-2.0

Code for "Dictionaries to the Rescue: Cross-Lingual Vocabulary Transfer for Low-Resource Languages Using Bilingual Dictionaries" (Sakajo et al., 2025 ACL Findings)

00PythonMar 9, 20258 months agoApache-2.0

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Cite this paper

@article{sakajo2025dictionaries,
  title  = {Dictionaries to the Rescue: Cross-Lingual Vocabulary Transfer for Low-Resource Languages Using Bilingual Dictionaries},
  author = {Haruki Sakajo and Yusuke Ide and Justin Vasselli and Yusuke Sakai and Yingtao Tian and Hidetaka Kamigaito and Taro Watanabe},
  year   = {2025},
  eprint = {2506.01535},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2506.01535v1}
}

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