Papers › NaijaRC: A Multi-choice Reading Comprehension Dataset for Nigerian Languages

NaijaRC: A Multi-choice Reading Comprehension Dataset for Nigerian Languages

18 Aug 2023arXiv:2308.09768archive 2025-07-28

Anuoluwapo Aremu, Jesujoba O. Alabi, Daud Abolade, Nkechinyere F. Aguobi, Shamsuddeen Hassan Muhammad, David Ifeoluwa Adelani

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.

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Tasks

Belebele Cross-Lingual Transfer Reading Comprehension

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Methods

Absolute Position Encodings Adam Attention BPE Dense Connections Dropout GPT-4 Label Smoothing Layer Normalization Linear Layer Multi-Head Attention Position-Wise Feed-Forward Layer Residual Connection Softmax Transformer

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