Linganisha mbinu

	Mtandao wa Nyuro wa Kujirudia wa Lugha Nyingi	LSTM nyingi lugha
Nyanja	Ujifunzaji wa Kina	Ujifunzaji wa Kina
Familia	Machine learning	Machine learning
Mwaka wa asili	1990–2010s	1997 (LSTM); multilingual NLP applications from ~2016
Mwanzilishi	Elman, J. L. (RNN); multilingual extension by NLP community	Hochreiter, S. & Schmidhuber, J. (LSTM base); multilingual application by the NLP community from ~2016
Aina	Sequential model (cross-lingual)	Recurrent neural network (sequence model)
Chanzo asilia	Elman, J. L. (1990). Finding structure in time. Cognitive Science, 14(2), 179–211.	Hochreiter, S. & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735–1780.
Majina mbadala	Multilingual RNN, Cross-lingual RNN, Multi-language RNN, MRNN	Multilingual LSTM, Cross-lingual LSTM, Multi-language LSTM, Multilingual Recurrent Network
Zinazohusiana	5	5
Muhtasari	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.	A Multilingual LSTM is a Long Short-Term Memory recurrent network trained or fine-tuned to process sequences in multiple languages, typically by sharing a single model across language-specific or joint subword embeddings. It captures long-range dependencies in text and is applied to multilingual classification, named entity recognition, sentiment analysis, and sequence labeling.