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Found 5 papers, 4 papers with code
FonMTL: Towards Multitask Learning for the Fon Language
Multitask learning is a learning paradigm that aims to improve the generalization capacity of a model by sharing knowledge across different but related tasks: this could be prevalent in very data-scarce scenarios.
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users.
A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation
We focus on two questions: 1) How can pre-trained models be used for languages not included in the initial pre-training?
GAM(L)A: An econometric model for interpretable Machine Learning
Moreover, the results also suggest that the performance of GAM(L)A is not significantly different from that of random forest and gradient boosting.
BIG-bench Machine Learning
Interpretable Machine Learning
+1
Neural Fashion Image Captioning : Accounting for Data Diversity
To address dataset diversity issues, we introduced the InFashAIv1 dataset containing almost 16. 000 African fashion item images with their titles, prices, and general descriptions.
