Dense Retrieval for Low Resource languages - the Case of Amharic Language
This paper presents our investigation into dense retrieval models for Amharic, a low-resource language spoken by more than 120 million people.We constructed training datasets tailored to dense retrieval models and evaluated model performance by comparing dense and sparse retrieval approaches on Amharic information retrieval.The study also highlights the challenges and efforts involved in advancing retrieval systems for low-resource languages.
Authors
- Serge Molina
- Josiane Mothe (ORCID: https://orcid.org/0000-0001-9273-2193)
- Moncef Garouani (ORCID: https://orcid.org/0000-0003-2528-441X)
- Tilahun Yeshambel (ORCID: https://orcid.org/0000-0003-0599-262X)
Institutions
- Centre National de la Recherche Scientifique (FR)
- Université Toulouse III - Paul Sabatier (FR)
- Université Fédérale de Toulouse Midi-Pyrénées (FR)
- Université Toulouse-I-Capitole (FR)
- Institut de Recherche en Informatique de Toulouse (FR)
- Université Toulouse - Jean Jaurès (FR)
- Institut Polytechnique de Bordeaux (FR)
- Addis Ababa University (ET)
Publication Details
- Published
- 2025-07-13
- DOI
- https://doi.org/10.1145/3726302.3730274
- Primary Topic
- Natural Language Processing Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00