arXiv:2405.06818v2 Announce Type: replace Abstract: Natural Language Processing (NLP) for Ghana's 73 living indigenous languages remains deeply fragmented, under-resourced, and heavily skewed toward...
The paper surveys NLP research on Nigeria’s three major low‑resource languages—Hausa, Yoruba, and Igbo—covering over 500 languages spoken by 175 million people. It reviews 293 studies, finding that only 27.6% produced new linguistic resources, indicating a heavy reliance on repurposing existing data. The authors highlight under‑explored challenges such as morphological analysis and diacritic representation, and call for collaborative resource enrichment and community support to advance NaijaNLP and low‑resource NLP more broadly.
arXiv:2610.28173v1 Announce Type: cross Abstract: Large Language Models (LLMs) depend fundamentally on the diversity, depth, and factual rigor of their pre-training corpora. However, contemporary fou...
arXiv:2606. 12708v1 Announce Type: cross Abstract: Despite their linguistic diversity and global significance, African languages remain underrepresented in research and resources to support NLP.
arXiv:2610.27269v1 Announce Type: new Abstract: With the widespread adoption of large language models (LLMs) across languages and domains, AI safety has emerged as a critical global concern. However,...
The paper analyzes the distribution of artificial intelligence resources across 6,003 languages, revealing that a small number of languages dominate and that disparities are widening exponentially. It compares the diffusion of AI with earlier information technologies, noting a hype-driven spread pattern. The authors introduce the Language AI Readiness Index (EQUATE) to map technological, socio-economic, and infrastructural prerequisites for AI deployment, aiming to guide equitable diffusion of language AI.
arXiv:2609.38574v1 Announce Type: new Abstract: Large language models are frequently proposed as a route to AI-powered services for African communities, but they are least reliable exactly where the...
arXiv:2606. 30656v1 Announce Type: cross Abstract: Artificial Intelligence (AI) has the potential to be transformative for development, but Africa is currently facing a fragmented and challenging "AI divide".
arXiv:2606.30943v2 Announce Type: replace Abstract: Russian and Arabic are among the major languages of scientific communication. Language barriers impede the exchange of research results between the...
The paper audits 51 multilingual evaluation benchmarks covering 242 datasets and 219 languages, focusing on coverage, representativeness, and rigor. It finds that while coverage is broad, many languages appear in only one benchmark and entire regions are underrepresented, with low-resource languages evaluated on far fewer tasks than high-resource ones. The study also highlights that most datasets rely on English translations, creating artifacts and limiting cultural relevance, and that benchmark contamination through translation leakage and corpus overlap undermines rigor. Recommendations call for natively constructed, culturally grounded, contamination-aware evaluation frameworks that truly serve the communities they aim to assess.
The paper introduces ALTO, a corpus of 3,022 culturally and linguistically relevant instances of tech‑facilitated gender‑based violence (TFGBV) in Levantine Arabic, African French, and Swahili. It was created through a community‑led crowdsourcing partnership with civil society organizations in Jordan, Francophone West Africa, and Kenya, and annotated using active learning. Benchmarking shows that existing harmful content detection models have low TFGBV recall on ALTO and improve after fine‑tuning, with covert harms being frequently missed and Swahili exhibiting the highest error rates.
arXiv:2608.21369v1 Announce Type: cross Abstract: Nigerian Pidgin is one of Africa's most widely spoken languages, yet remains severely underrepresented in language model evaluation. Existing benchma...