181 citations · 286 across the 67 of their papers we have counts for
71 papers
Channel Gains to Captions: Task-Unified Multi-Level RF Sensing with Vision-Language Models
Tianyu Hu, Zhiren Gong, Haowei Cui +6
This letter investigates a task-unified multi-level radio-frequency (RF) sensing framework driven by vision-language models (VLMs). Existing RF sensing methods rely on task-specifi…
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…
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…
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…
RAVID: Retrieval-Augmented Visual Detection: A Knowledge-Driven Approach for AI-Generated Image Identification
Mamadou Keita, Wassim Hamidouche, Hessen Bougueffa Eutamene +2
In this paper, we introduce RAVID, the first framework for AI-generated image detection that leverages visual retrieval-augmented generation (RAG). While RAG methods have shown pro…
VIP: Visual Information Protection through Adversarial Attacks on Vision-Language Models
Hanene F. Z. Brachemi Meftah, Wassim Hamidouche, Sid Ahmed Fezza +1
Recent years have witnessed remarkable progress in developing Vision-Language Models (VLMs) capable of processing both textual and visual inputs. These models have demonstrated imp…
DeeCLIP: A Robust and Generalizable Transformer-Based Framework for Detecting AI-Generated Images
Mamadou Keita, Wassim Hamidouche, Hessen Bougueffa Eutamene +2
This paper introduces DeeCLIP, a novel framework for detecting AI-generated images using CLIP-ViT and fusion learning. Despite significant advancements in generative models capable…
Can LLMs Revolutionize the Design of Explainable and Efficient TinyML Models?
Christophe El Zeinaty, Wassim Hamidouche, Glenn Herrou +2
This paper introduces a novel framework for designing efficient neural network architectures specifically tailored to tiny machine learning (TinyML) platforms. By leveraging large…
Advancing THz Radio Map Construction and Obstacle Sensing: An Integrated Generative Framework in ISAC
Tianyu Hu, Shuai Wang, Yunhang Xie +7
Integrated sensing and communication (ISAC) in the terahertz (THz) band enables obstacle detection, which in turn facilitates efficient beam management to mitigate THz signal block…
Energy-Latency Attacks: A New Adversarial Threat to Deep Learning
Hanene F. Z. Brachemi Meftah, Wassim Hamidouche, Sid Ahmed Fezza +1
The growing computational demand for deep neural networks ( DNNs) has raised concerns about their energy consumption and carbon footprint, particularly as the size and complexity o…
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…
Energy Backdoor Attack to Deep Neural Networks
Hanene F. Z. Brachemi Meftah, Wassim Hamidouche, Sid Ahmed Fezza +2
The rise of deep learning (DL) has increased computing complexity and energy use, prompting the adoption of application specific integrated circuits (ASICs) for energy-efficient ed…
360-Degree Video Super Resolution and Quality Enhancement Challenge: Methods and Results
Ahmed Telili, Wassim Hamidouche, Ibrahim Farhat +12
Omnidirectional (360-degree) video is rapidly gaining popularity due to advancements in immersive technologies like virtual reality (VR) and extended reality (XR). However, real-ti…
FIDAVL: Fake Image Detection and Attribution using Vision-Language Model
Mamadou Keita, Wassim Hamidouche, Hessen Bougueffa Eutamene +2
We introduce FIDAVL: Fake Image Detection and Attribution using a Vision-Language Model. FIDAVL is a novel and efficient mul-titask approach inspired by the synergies between visio…
Bi-LORA: A Vision-Language Approach for Synthetic Image Detection
Mamadou Keita, Wassim Hamidouche, Hessen Bougueffa Eutamene +2
Advancements in deep image synthesis techniques, such as generative adversarial networks (GANs) and diffusion models (DMs), have ushered in an era of generating highly realistic im…
Harnessing the Power of Large Vision Language Models for Synthetic Image Detection
Mamadou Keita, Wassim Hamidouche, Hassen Bougueffa +2
In recent years, the emergence of models capable of generating images from text has attracted considerable interest, offering the possibility of creating realistic images from text…
Generative AI for Immersive Communication: The Next Frontier in Internet-of-Senses Through 6G
Nassim Sehad, Lina Bariah, Wassim Hamidouche +3
Over the past two decades, the Internet-of-Things (IoT) has become a transformative concept, and as we approach 2030, a new paradigm known as the Internet of Senses (IoS) is emergi…
ODVista: An Omnidirectional Video Dataset for super-resolution and Quality Enhancement Tasks
Ahmed Telili, Ibrahim Farhat, Wassim Hamidouche +1
Omnidirectional or 360-degree video is being increasingly deployed, largely due to the latest advancements in immersive virtual reality (VR) and extended reality (XR) technology. H…
NERV++: An Enhanced Implicit Neural Video Representation
Ahmed Ghorbel, Wassim Hamidouche, Luce Morin
Neural fields, also known as implicit neural representations (INRs), have shown a remarkable capability of representing, generating, and manipulating various data types, allowing f…
UAV Immersive Video Streaming: A Comprehensive Survey, Benchmarking, and Open Challenges
Mohit K. Sharma, Chen-Feng Liu, Ibrahim Farhat +3
Over the past decade, the utilization of UAVs has witnessed significant growth, owing to their agility, rapid deployment, and maneuverability. In particular, the use of UAV-mounted…
Video Quality Assessment and Coding Complexity of the Versatile Video Coding Standard
Thomas Amestoy, Naty Sidaty, Wassim Hamidouche +2
In recent years, the proliferation of multimedia applications and formats, such as IPTV, Virtual Reality (VR, 360-degree), and point cloud videos, has presented new challenges to t…