177 citations · 392 across the 27 of their papers we have counts for
8 papers · 1 filter
Neural Machine Translation for Extremely Low-Resource African Languages: A Case Study on Bambara
Allahsera Auguste Tapo, Bakary Coulibaly, Sébastien Diarra +6
Low-resource languages present unique challenges to (neural) machine translation. We discuss the case of Bambara, a Mande language for which training data is scarce and requires si…
Participatory Research for Low-resourced Machine Translation: A Case Study in African Languages
Wilhelmina Nekoto, Vukosi Marivate, Tshinondiwa Matsila +45
Research in NLP lacks geographic diversity, and the question of how NLP can be scaled to low-resourced languages has not yet been adequately solved. "Low-resourced"-ness is a compl…
Offline Reinforcement Learning from Human Feedback in Real-World Sequence-to-Sequence Tasks
Julia Kreutzer, Stefan Riezler, Carolin Lawrence
Large volumes of interaction logs can be collected from NLP systems that are deployed in the real world. How can this wealth of information be leveraged? Using such interaction log…
KINNEWS and KIRNEWS: Benchmarking Cross-Lingual Text Classification for Kinyarwanda and Kirundi
Rubungo Andre Niyongabo, Hong Qu, Julia Kreutzer +1
Recent progress in text classification has been focused on high-resource languages such as English and Chinese. For low-resource languages, amongst them most African languages, the…
Inference Strategies for Machine Translation with Conditional Masking
Julia Kreutzer, George Foster, Colin Cherry
Conditional masked language model (CMLM) training has proven successful for non-autoregressive and semi-autoregressive sequence generation tasks, such as machine translation. Given…
Correct Me If You Can: Learning from Error Corrections and Markings
Julia Kreutzer, Nathaniel Berger, Stefan Riezler
Sequence-to-sequence learning involves a trade-off between signal strength and annotation cost of training data. For example, machine translation data range from costly expert-gene…
On Optimal Transformer Depth for Low-Resource Language Translation
Elan van Biljon, Arnu Pretorius, Julia Kreutzer
Transformers have shown great promise as an approach to Neural Machine Translation (NMT) for low-resource languages. However, at the same time, transformer models remain difficult…
Masakhane -- Machine Translation For Africa
Iroro Orife, Julia Kreutzer, Blessing Sibanda +22
Africa has over 2000 languages. Despite this, African languages account for a small portion of available resources and publications in Natural Language Processing (NLP). This is du…