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شبكة الخصومة التوليدية متعددة اللغات (Multilingual GAN)×تضمينات الجمل متعددة اللغات×
المجالالتعلم العميقالتعلم العميق
العائلةMachine learningMachine learning
سنة النشأة2017–20192019–2022
صاحب الطريقةGoodfellow et al. (GAN); multilingual extensions by various authors from 2017 onwardReimers, N. & Gurevych, I.; Feng, F. et al. (Google)
النوعGenerative adversarial model with multilingual conditioningCross-lingual representation learning
المصدر التأسيسيGoodfellow, 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 ↗Reimers, N. & Gurevych, I. (2020). Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation. Proceedings of EMNLP 2020, 4512–4525. link ↗
الأسماء البديلةMultilingual GAN, Cross-lingual GAN, Multilingual Generative Adversarial Network, ML-GANmultilingual sentence representations, cross-lingual sentence embeddings, mSE, multilingual semantic embeddings
ذات صلة55
الملخصA 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.Multilingual sentence embeddings map sentences from many languages into a single shared vector space so that semantically equivalent sentences — regardless of language — land close together. Models such as LaBSE, multilingual Sentence-BERT, and mUSE have made it practical to compare, retrieve, and classify text across 50 to 100+ languages without translating anything first.
ScholarGateمجموعة البيانات
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  2. 2 المصادر
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  1. v1
  2. 2 المصادر
  3. PUBLISHED

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ScholarGateقارن الطرق: Multilingual GAN · Multilingual Sentence Embeddings. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare