AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages vs MasakhaNER 2.0: Africa-centric Transfer Learning for Named Entity Recognition

AfriQA is the first cross-lingual open-retrieval question answering benchmark for African languages, with more than 12,000 XOR-QA examples across 10 African languages. The paper shows that current automatic translation and multilingual retrieval methods perform poorly for these languages, where in-language digital content is scarce.

MasakhaNER 2.0 introduces the largest human-annotated named entity recognition dataset for 20 African languages and studies Africa-centric cross-lingual transfer learning. The paper reports that choosing the best transfer language improves zero-shot F1 by an average of 14 points across the 20 languages compared with transferring from English.