publications

2023

1. EMNLP

   Machine learning for healthcare: A bibliometric study of contributions from Africa

   Houcemeddine Turki, Houda Sekkal, Anastassios Pouris, and 8 more authors

   2023
2. Preprint

   A Decade of Scholarly Research on Open Knowledge Graphs

   Houcemeddine Turki, Abraham Toluwase Owodunni, Mohamed Ali Hadj Taieb, and 3 more authors

   arXiv preprint arXiv:2306.13186, 2023
3. EMNLP

   Cross-lingual Open-Retrieval Question Answering for African Languages

   Odunayo Ogundepo, Tajuddeen Gwadabe, Clara Rivera, and 41 more authors

   In Findings of the Association for Computational Linguistics: EMNLP 2023, Dec 2023

   Abs

   African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingual open-retrieval question answering (XOR QA) systems – those that retrieve answer content from other languages while serving people in their native language—offer a means of filling this gap. To this end, we create Our Dataset, the first cross-lingual QA dataset with a focus on African languages. Our Dataset includes 12,000+ XOR QA examples across 10 African languages. While previous datasets have focused primarily on languages where cross-lingual QA augments coverage from the target language, Our Dataset focuses on languages where cross-lingual answer content is the only high-coverage source of answer content. Because of this, we argue that African languages are one of the most important and realistic use cases for XOR QA. Our experiments demonstrate the poor performance of automatic translation and multilingual retrieval methods. Overall, Our Dataset proves challenging for state-of-the-art QA models. We hope that the dataset enables the development of more equitable QA technology.

4. EMNLP

   Better Quality Pre-training Data and T5 Models for African Languages

   Akintunde Oladipo, Mofetoluwa Adeyemi, Orevaoghene Ahia, and 4 more authors

   In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Dec 2023
5. ICLR: AfricaNLP

   Koya: A Recommender System for Large Language Model Selection

   Abraham Toluwase Owodunni, and Chris Chinenye Emezue

   In 4th Workshop on African Natural Language Processing, Dec 2023

2022

1. 

   Bloom Library: Multimodal Datasets in 300+ Languages for a Variety of Downstream Tasks

   Colin Leong, Joshua Nemecek, Jacob Mansdorfer, and 3 more authors

   In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Dec 2022

   Abs

   We present Bloom Library, a linguistically diverse set of multimodal and multilingual datasets for language modeling, image captioning, visual storytelling, and speech synthesis/recognition. These datasets represent either the most, or among the most, multilingual datasets for each of the included downstream tasks. In total, the initial release of the Bloom Library datasets covers 363 languages across 32 language families. We train downstream task models for various languages represented in the data, showing the viability of the data for future work in low-resource, multimodal NLP and establishing the first known baselines for these downstream tasks in certain languages (e.g., Bisu [bzi], with an estimated population of 700 users). Some of these first-of-their-kind baselines are comparable to state-of-the-art performance for higher-resourced languages. The Bloom Library datasets are released under Creative Commons licenses on the Hugging Face datasets hub to catalyze more linguistically diverse research in the included downstream tasks.