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arxiv: 2412.20223 · v1 · pith:ZPOOLV5I · submitted 2024-12-28 · cs.CL

AfriHG: News headline generation for African Languages

Toyib Ogunremi , Serah Akojenu , Anthony Soronnadi , Olubayo Adekanmbi , David Ifeoluwa Adelani This is my paper

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classification cs.CL
keywords afritevaafrihgaya-101generationheadlinelanguagesmodelsmt5-base
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This paper introduces AfriHG -- a news headline generation dataset created by combining from XLSum and MasakhaNEWS datasets focusing on 16 languages widely spoken by Africa. We experimented with two seq2eq models (mT5-base and AfriTeVa V2), and Aya-101 LLM. Our results show that Africa-centric seq2seq models such as AfriTeVa V2 outperform the massively multilingual mT5-base model. Finally, we show that the performance of fine-tuning AfriTeVa V2 with 313M parameters is competitive to prompting Aya-101 LLM with more than 13B parameters.

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