Work

Dense Retrieval for Low Resource languages - the Case of Amharic Language

Year: 2025

Type: conference-paper

Abstract: 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.

Source: International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)

DOI: 10.1145/3726302.3730274

Authors: Tilahun Yeshambel, Moncef Garouani, Serge Molina, Josiane Mothe

Institutions: Addis Ababa University, Centre National de la Recherche Scientifique, Institut de Recherche en Informatique de Toulouse, Université de Toulouse, Université Toulouse - Jean Jaurès

Language: English

Topic: Information Retrieval and Search Behavior

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Agence Nationale de la Recherche

Award: General pUrpose dIalogue-based DigitAl iNformation acCEss