AfriHG: News Headline Generation for African Languages
Abstract
This paper introduces AfriHG, an extended multi-lingual corpus compiled from XL-Sum and Masakhanews focusing on 16 languages widely spoken by Africans across 9 language families. We experimented with two seq-2-seq models. We also evaluated our dataset with a massively multilingual instruction-tuned LLM and benchmarked our results in the domain of abstractive summarization for News headline generation.
Cite
Text
Ogunremi et al. "AfriHG: News Headline Generation for African Languages." ICLR 2024 Workshops: AfricaNLP, 2024.Markdown
[Ogunremi et al. "AfriHG: News Headline Generation for African Languages." ICLR 2024 Workshops: AfricaNLP, 2024.](https://mlanthology.org/iclrw/2024/ogunremi2024iclrw-afrihg/)BibTeX
@inproceedings{ogunremi2024iclrw-afrihg,
title = {{AfriHG: News Headline Generation for African Languages}},
author = {Ogunremi, Toyib and Akojenu, Serah sessi and Soronnadi, Anthony and Adekanmbi, Olubayo and Adelani, David Ifeoluwa},
booktitle = {ICLR 2024 Workshops: AfricaNLP},
year = {2024},
url = {https://mlanthology.org/iclrw/2024/ogunremi2024iclrw-afrihg/}
}