ScholarGate
Msaidizi
Machine learningDeep learning / NLP / CV

Kigeuzi Lugha Nyingi

Kigeuzi lugha nyingi ni mfumo wa lugha uliopangwa awali unaotegemea usanifu wa kigeuzi na kufunzwa kwa pamoja kwenye maandishi kutoka lugha kadhaa hadi zaidi ya lugha mia moja. Mifumo kama vile mBERT na XLM-RoBERTa hujifunza uwakilishi wa lugha mbalimbali unaoshirikiwa, kuwezesha uhamishaji wa sifuri-risasi au risasi chache: mfumo uliorekebishwa kwa data ya Kiingereza mara nyingi unaweza kutumika moja kwa moja kwa Kifaransa, Kijerumani, Kiarabu, au Kichina bila lebo maalum za lugha.

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Vyanzo

  1. 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
  2. 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

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Multilingual Transformer (Cross-lingual Pre-trained Language Model). ScholarGate. https://scholargate.app/sw/deep-learning/multilingual-transformer

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Imerejelewa na

ScholarGateMultilingual Transformer (Multilingual Transformer (Cross-lingual Pre-trained Language Model)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/multilingual-transformer · Seti ya data: https://doi.org/10.5281/zenodo.20539026