AI and the Future of Work in Africa White Paper

Autor: O'Neill, Jacki, Marivate, Vukosi, Glover, Barbara, Karanu, Winnie, Tadesse, Girmaw Abebe, Gyekye, Akua, Makena, Anne, Rosslyn-Smith, Wesley, Grollnek, Matthew, Wayua, Charity, Baguma, Rehema, Maduke, Angel, Spencer, Sarah, Kandie, Daniel, Maari, Dennis Ndege, Mutangana, Natasha, Axmed, Maxamed, Kamau, Nyambura, Adamu, Muhammad, Swaniker, Frank, Gatuguti, Brian, Donner, Jonathan, Graham, Mark, Mumo, Janet, Mbindyo, Caroline, N'Guessan, Charlette, Githinji, Irene, Makhafola, Lesego, Kruger, Sean, Etyang, Olivia, Onando, Mulang, Sevilla, Joe, Sambuli, Nanjira, Mbaya, Martin, Breloff, Paul, Anapey, Gideon M., Mogaleemang, Tebogo L., Nghonyama, Tiyani, Wanyoike, Muthoni, Mbuli, Bhekani, Nderu, Lawrence, Nyabero, Wambui, Alam, Uzma, Olaleye, Kayode, Njenga, Caroline, Sellen, Abigail, Kairo, David, Chabikwa, Rutendo, Abdulhamid, Najeeb G., Kubasu, Ketry, Okolo, Chinasa T., Akpo, Eugenia, Budu, Joel, Karambal, Issa, Berkoh, Joseph, Wasswa, William, Njagwi, Muchai, Burnet, Rob, Ochanda, Loise, de Bod, Hanlie, Ankrah, Elizabeth, Kinyunyu, Selemani, Kariuki, Mutembei, Kiyimba, Kizito, Eleshin, Farida, Madeje, Lillian Secelela, Muraga, Catherine, Nganga, Ida, Gichoya, Judy, Maina, Tabbz, Maina, Samuel, Mercy, Muchai, Ochieng, Millicent, Nyairo, Stephanie

This white paper is the output of a multidisciplinary workshop in Nairobi (Nov 2023). Led by a cross-organisational team including Microsoft Research, NEPAD, Lelapa AI, and University of Oxford. The workshop brought together diverse thought-leaders f

Externí odkaz: http://arxiv.org/abs/2411.10091

Cross-lingual transfer of multilingual models on low resource African Languages

Autor: Thangaraj, Harish, Chenat, Ananya, Walia, Jaskaran Singh, Marivate, Vukosi

Large multilingual models have significantly advanced natural language processing (NLP) research. However, their high resource demands and potential biases from diverse data sources have raised concerns about their effectiveness across low-resource l

Externí odkaz: http://arxiv.org/abs/2409.10965

InkubaLM: A small language model for low-resource African languages

Autor: Tonja, Atnafu Lambebo, Dossou, Bonaventure F. P., Ojo, Jessica, Rajab, Jenalea, Thior, Fadel, Wairagala, Eric Peter, Aremu, Anuoluwapo, Moiloa, Pelonomi, Abbott, Jade, Marivate, Vukosi, Rosman, Benjamin

High-resource language models often fall short in the African context, where there is a critical need for models that are efficient, accessible, and locally relevant, even amidst significant computing and data constraints. This paper introduces Inkub

Externí odkaz: http://arxiv.org/abs/2408.17024

Prompting Towards Alleviating Code-Switched Data Scarcity in Under-Resourced Languages with GPT as a Pivot

Autor: Terblanche, Michelle, Olaleye, Kayode, Marivate, Vukosi

Many multilingual communities, including numerous in Africa, frequently engage in code-switching during conversations. This behaviour stresses the need for natural language processing technologies adept at processing code-switched text. However, data

Externí odkaz: http://arxiv.org/abs/2404.17216

Multimodal Misinformation Detection in a South African Social Media Environment

Autor: De Jager, Amica, Marivate, Vukosi, Modupe, Abioudun

With the constant spread of misinformation on social media networks, a need has arisen to continuously assess the veracity of digital content. This need has inspired numerous research efforts on the development of misinformation detection (MD) models

Externí odkaz: http://arxiv.org/abs/2312.04052