Extending Multilingual BERT to Low-Resource Languages
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Abstract (arXiv)
Multilingual BERT (M-BERT) has been a huge success in both supervised and zero-shot cross-lingual transfer learning. However, this success has focused only on the top 104 languages in Wikipedia that it was trained on. In this paper, we propose a simple but effective approach to extend M-BERT (E-BERT) so that it can benefit any new language, and show that our approach benefits languages that are already in M-BERT as well. We perform an extensive set of experiments with Named Entity Recognition (NER) on 27 languages, only 16 of which are in M-BERT, and show an average increase of about 6% F1 on languages that are already in M-BERT and 23% F1 increase on new languages.
Key facts. Cited by 88 papers in the map (data through 14 Oct 2026). First posted on arXiv 28 Apr 2020.
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Citing papers per year: 2021: 15; 2022: 23; 2023: 15; 2024: 19; 2025: 9; 2026: 7.
88 papers.
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50 most cited of 88 All 88 (JSON)
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- 2023Translation and Fusion Improves Zero-shot Cross-lingual Information Extraction23 May 2023
- 2023Soft Prompt Decoding for Multilingual Dense Retrieval15 May 2023
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50 newest of 88 All 88 (JSON)
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- 2023Dissociating language and thought in large language models16 Jan 2023
- 2021CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representationcited by 232
- 2022Lifting the Curse of Multilinguality by Pre-training Modular Transformerscited by 146
- 2021Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLPcited by 132
- 2021AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language Processingcited by 131
- 2022A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translationcited by 98
- 2022BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Promptingcited by 90
- 2024A Survey on Multilingual Large Language Models: Corpora, Alignment, and Biascited by 84
- 2022Building Machine Translation Systems for the Next Thousand Languagescited by 69
- 2022Language Modelling with Pixelscited by 55
- 2021How to Adapt Your Pretrained Multilingual Model to 1600 Languagescited by 54
- 2021AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languagescited by 50
- 2021A Primer on Pretrained Multilingual Language Modelscited by 49
12 most cited of 85 All 85 (JSON)
- 2026Writing-System-Level Tokenizer Adaptation for Byte-Level BPE1 Aug 2026
- 2026Multilinguality of Large Language Models From a Structural Perspective1 Jun 2026
- 2026Source-Grounded Semantic Reinforcement Learning for Low-Resource Target-Language Generation28 May 2026
- 2026TokAlign++: Advancing Vocabulary Adaptation via Better Token Alignment13 May 2026
- 2026Dependency Parsing Across the Resource Spectrum: Evaluating Architectures on High and Low-Resource Languages4 May 2026
- 2026Defragmenting Language Models: An Interpretability-based Approach for Vocabulary Expansion17 Apr 2026
- 2026Effective vocabulary expansion of multilingual language models for extremely low-resource languages10 Feb 2026
- 2025Opportunities and Challenges of Natural Language Processing for Low-Resource Senegalese Languages in Social Science Research24 Dec 2025
- 2025Exploring Cross-Lingual Knowledge Transfer via Transliteration-Based MLM Fine-Tuning for Critically Low-resource Chakma Language10 Oct 2025
- 2025One Tokenizer To Rule Them All: Emergent Language Plasticity via Multilingual Tokenizers12 Jun 2025
- 2025Dictionaries to the Rescue: Cross-Lingual Vocabulary Transfer for Low-Resource Languages Using Bilingual Dictionaries2 Jun 2025
- 2025Semantic Aware Linear Transfer by Recycling Pre-trained Language Models for Cross-lingual Transfer16 May 2025
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