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AfriHG: News headline generation for African Languages
December 28, 2024 ยท Declared Dead ยท ๐ arXiv.org
"No code URL or promise found in abstract"
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Authors
Toyib Ogunremi, Serah Akojenu, Anthony Soronnadi, Olubayo Adekanmbi, David Ifeoluwa Adelani
arXiv ID
2412.20223
Category
cs.CL: Computation & Language
Citations
1
Venue
arXiv.org
Last Checked
6 months ago
Abstract
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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