Dictionaries to the Rescue: Cross-Lingual Vocabulary Transfer for Low-Resource Languages Using Bilingual Dictionaries
Sakajo, Haruki, Ide, Yusuke, Vasselli, Justin, Sakai, Yusuke, Tian, Yingtao, Kamigaito, Hidetaka, Watanabe, Taro
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Jun-3-2025
- Country:
- Africa > Comoros
- Grande Comore > Moroni (0.04)
- Asia
- Europe
- North America
- Canada (0.04)
- Mexico > Mexico City
- Mexico City (0.04)
- United States
- Florida > Miami-Dade County
- Miami (0.04)
- Georgia > Fulton County
- Atlanta (0.04)
- Massachusetts > Middlesex County
- Cambridge (0.04)
- New Mexico > Bernalillo County
- Albuquerque (0.04)
- Washington > King County
- Seattle (0.04)
- Florida > Miami-Dade County
- South America > Colombia
- Meta Department > Villavicencio (0.04)
- Africa > Comoros
- Genre:
- Research Report > New Finding (1.00)
- Technology: