Linganisha mbinu

	Mtandao wa CNN wa Lugha Nyingi	Kigeuzi Lugha Nyingi
Nyanja	Ujifunzaji wa Kina	Ujifunzaji wa Kina
Familia	Machine learning	Machine learning
Mwaka wa asili	2014–2016	2019–2020
Mwanzilishi	Kim, Y. (seminal NLP CNN); multilingual extension by community	Devlin et al. (mBERT); Conneau et al. (XLM-R)
Aina	Deep learning classifier	Pre-trained cross-lingual language model
Chanzo asilia	Kim, Y. (2014). Convolutional Neural Networks for Sentence Classification. Proceedings of EMNLP 2014, pp. 1746–1751.	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.
Majina mbadala	ML-CNN, cross-lingual CNN, multilingual text CNN, multilingual ConvNet	multilingual LM, cross-lingual transformer, mBERT-style model, multilingual pre-trained model
Zinazohusiana	4	4
Muhtasari	A Multilingual CNN applies convolutional filters over token embeddings drawn from two or more languages, producing shared feature representations that enable a single model to classify, tag, or extract information across language boundaries without training separate models per language. It extends the standard text-CNN architecture with multilingual or cross-lingual input embeddings.	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.