7 citations · 10 across the 6 of their papers we have counts for
8 papers
An empirical investigation into the properties of standard word embeddings
Salomon Kabongo
The embedding of word sequences into continuous vector spaces has been one of the most important developments in Natural Language Processing in the recent past. Such embeddings hav…
IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models
David Ifeoluwa Adelani, Jessica Ojo, Israel Abebe Azime +24
Despite the widespread adoption of Large language models (LLMs), their remarkable capabilities remain limited to a few high-resource languages. Additionally, many low-resource lang…
ORKG-Leaderboards: A Systematic Workflow for Mining Leaderboards as a Knowledge Graph
Salomon Kabongo, Jennifer D'Souza, Sören Auer
The purpose of this work is to describe the Orkg-Leaderboard software designed to extract leaderboards defined as Task-Dataset-Metric tuples automatically from large collections of…
Zero-shot Entailment of Leaderboards for Empirical AI Research
Salomon Kabongo, Jennifer D'Souza, Sören Auer
We present a large-scale empirical investigation of the zero-shot learning phenomena in a specific recognizing textual entailment (RTE) task category, i.e. the automated mining of…
BibleTTS: a large, high-fidelity, multilingual, and uniquely African speech corpus
Josh Meyer, David Ifeoluwa Adelani, Edresson Casanova +16
BibleTTS is a large, high-quality, open speech dataset for ten languages spoken in Sub-Saharan Africa. The corpus contains up to 86 hours of aligned, studio quality 48kHz single sp…
Automated Mining of Leaderboards for Empirical AI Research
Salomon Kabongo, Jennifer D'Souza, Sören Auer
With the rapid growth of research publications, empowering scientists to keep oversight over the scientific progress is of paramount importance. In this regard, the Leaderboards fa…