Linganisha mbinu

	GANi Lugha Nyingi	Mtandao wa Nyuro wa Kujirudia wa Lugha Nyingi
Nyanja	Ujifunzaji wa Kina	Ujifunzaji wa Kina
Familia	Machine learning	Machine learning
Mwaka wa asili	2017–2019	1990–2010s
Mwanzilishi	Goodfellow et al. (GAN); multilingual extensions by various authors from 2017 onward	Elman, J. L. (RNN); multilingual extension by NLP community
Aina	Generative adversarial model with multilingual conditioning	Sequential model (cross-lingual)
Chanzo asilia	Goodfellow, 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.	Elman, J. L. (1990). Finding structure in time. Cognitive Science, 14(2), 179–211.
Majina mbadala	Multilingual GAN, Cross-lingual GAN, Multilingual Generative Adversarial Network, ML-GAN	Multilingual RNN, Cross-lingual RNN, Multi-language RNN, MRNN
Zinazohusiana	5	5
Muhtasari	A 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 Recurrent Neural Network (Multilingual RNN) applies the standard RNN architecture — which processes sequences step by step while maintaining a hidden state — to data spanning two or more languages. By training on multilingual corpora or sharing parameters across languages, the model learns cross-lingual sequence representations useful for translation, tagging, classification, and language modeling tasks.