16 papers
AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages
Hao Yu, Tianyi Xu, Michael A. Hedderich +3
Large language models (LLMs) are increasingly multilingual, yet open models continue to underperform relative to proprietary systems, with the gap most pronounced for African langu…
TukaBench: A Culturally Grounded Jailbreak Benchmark for African Languages
Victor Akinode, Senyu Li, Wassim Hamidouche +3
Safety evaluation of Large Language Models (LLMs) remains heavily English-centric, leaving Low-Resource Languages (LRLs), particularly African ones, critically underexplored. We in…
Can Visual Mamba Improve AI-Generated Image Detection? An In-Depth Investigation
Mamadou Keita, Wassim Hamidouche, Hessen Bougueffa Eutamene +3
In recent years, computer vision has witnessed remarkable progress, fueled by the development of innovative architectures such as Convolutional Neural Networks (CNNs), Generative A…
BYOL: Bring Your Own Language Into LLMs
Syed Waqas Zamir, Wassim Hamidouche, Boulbaba Ben Amor +3
Large Language Models (LLMs) exhibit strong multilingual capabilities, yet remain fundamentally constrained by the severe imbalance in global language resources. While over 7,000 l…
AI Diffusion in Low Resource Language Countries
Amit Misra, Syed Waqas Zamir, Wassim Hamidouche +2
Artificial intelligence (AI) is diffusing globally at unprecedented speed, but adoption remains uneven. Frontier Large Language Models (LLMs) are known to perform poorly on low-res…
Designing Object Detection Models for TinyML: Foundations, Comparative Analysis, Challenges, and Emerging Solutions
Christophe EL Zeinaty, Wassim Hamidouche, Glenn Herrou +1
Object detection (OD) has become vital for numerous computer vision applications, but deploying it on resource-constrained IoT devices presents a significant challenge. These devic…