Increasing linguistic diversity in NLP : Fine-tuning Multilingual Pre-trained African Language Models

Adapting Pre-trained Language Models to African Languages via Multilingual Adaptive Fine-Tuning

Multilingual pre-trained language models (PLMs) have demonstrated impressive performance on several downstream tasks for both high-resourced and low-resourced languages. However, there is still a large performance drop for languages unseen during pre-training, espe

Disfluent-to-Fluent Tunisian Dialect Speech Translation with Fine-Tuning Pre-trained Language Models

How Linguistically Fair Are Multilingual Pre-Trained Language Models?

Massively multilingual pre-trained language models, such as mBERT and XLM-RoBERTa, have received sig

Low-Resource Hate Speech Detection in English-Swahili Code-Switched Text Using Fine-Tuning of Pre-trained Language Models

The use of social media in East Africa has grown rapidly, and with it, the spread of hate speech has

African Pre-Trained Embeddings [NLP]

A first set of African Language Embeddings

• Word Embeddings

GeoMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models

Recent work has shown that Pre-trained Language Models (PLMs) store the relational knowledge learned