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Multilingvális GAN×Multilingvis transzformátor×
TudományterületMélytanulásMélytanulás
MódszercsaládMachine learningMachine learning
Keletkezés éve2017–20192019–2020
MegalkotóGoodfellow et al. (GAN); multilingual extensions by various authors from 2017 onwardDevlin et al. (mBERT); Conneau et al. (XLM-R)
TípusGenerative adversarial model with multilingual conditioningPre-trained cross-lingual language model
AlapműGoodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative Adversarial Nets. Advances in Neural Information Processing Systems (NeurIPS), 27. link ↗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 ↗
Alternatív nevekMultilingual GAN, Cross-lingual GAN, Multilingual Generative Adversarial Network, ML-GANmultilingual LM, cross-lingual transformer, mBERT-style model, multilingual pre-trained model
Kapcsolódó54
ÖsszefoglalóA Multilingual GAN pairs the generative adversarial framework with cross-lingual components — a shared encoder, language-conditioned generator, and a language discriminator — so that a single model can generate or align representations across multiple languages simultaneously. It is applied to cross-lingual text generation, machine translation, multilingual data augmentation, and language-invariant feature learning.A multilingual transformer is a pre-trained language model built on the transformer architecture and trained jointly on text from dozens to over one hundred languages. Models such as mBERT and XLM-RoBERTa learn shared cross-lingual representations, enabling zero-shot or few-shot transfer: a model fine-tuned on English data can often be applied directly to French, German, Arabic, or Chinese without language-specific labels.
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  3. PUBLISHED

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ScholarGateMódszerek összehasonlítása: Multilingual GAN · Multilingual Transformer. Letöltve 2026-06-18, forrás: https://scholargate.app/hu/compare