NaijaRC: A Multi-choice Reading Comprehension Dataset for Nigerian Languages
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Abstract (arXiv)
In this paper, we create NaijaRC: a new multi-choice Reading Comprehension dataset for three native Nigeria languages that is based on high-school reading comprehension examination. We provide baseline results by performing cross-lingual transfer using existing English RACE and Belebele training dataset based on a pre-trained encoder-only model. Additionally, we provide results by prompting large language models (LLMs) like GPT-4.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 15 of its 21 references that are in the map. First posted on arXiv 18 Aug 2023.
Builds on
15 of 21 references.
References · 15
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- 2022A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translationcited by 97
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Citing papers per year: 2023: 1; 2024: 1; 2025: 2.
4 papers.
- 2023AfroBench: How Good are Large Language Models on African Languages?cited by 43
- 2025Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Aheadcited by 15
- 2024Y-NQ: English-Yor`ub'a Evaluation dataset for Open-Book Reading Comprehension and Text Generationcited by 1
- 2025NaijaNLP: A Survey of Nigerian Low-Resource Languagescited by 0
- 2025Charting the Landscape of African NLP: Mapping Progress and Shaping the Road Ahead27 May 2025
- 2025NaijaNLP: A Survey of Nigerian Low-Resource Languages27 Feb 2025
- 2024Y-NQ: English-Yor`ub'a Evaluation dataset for Open-Book Reading Comprehension and Text Generation11 Dec 2024
- 2023AfroBench: How Good are Large Language Models on African Languages?14 Nov 2023