Machine learningDeep learning / NLP / CV
多语言 Transformer
多语言 Transformer 是一种基于 Transformer 架构的预训练语言模型，它联合训练了来自数十种乃至上百种语言的文本。mBERT 和 XLM-RoBERTa 等模型学习共享的跨语言表示，从而实现零样本（zero-shot）或少样本（few-shot）迁移：一个在英语数据上微调过的模型，通常可以直接应用于法语、德语、阿拉伯语或中文，而无需特定语言的标签。
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来源
- Devlin, J., Chang, M.-W., Lee, K., & Toutanova, K. (2019). BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. Proceedings of NAACL-HLT 2019, pp. 4171–4186. Association for Computational Linguistics. DOI: 10.18653/v1/N19-1423 ↗
- Conneau, A., Khandelwal, K., Goyal, N., Chaudhary, V., Wenzek, G., Guzmán, F., Grave, E., Ott, M., Zettlemoyer, L., & Stoyanov, V. (2020). Unsupervised Cross-lingual Representation Learning at Scale. Proceedings of ACL 2020, pp. 8440–8451. Association for Computational Linguistics. DOI: 10.18653/v1/2020.acl-main.747 ↗
如何引用本页
ScholarGate. (2026, June 3). Multilingual Transformer (Cross-lingual Pre-trained Language Model). ScholarGate. https://scholargate.app/zh/deep-learning/multilingual-transformer
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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