From the 1 of 20 linked papers with an AI index.
20 papers
HalluTruthQA-4K: A Fine-Grained Corpus and Annotation Process for Arabic Hallucination Detection and Truth Verification
Salah Eddine Bekhouche, Abdessalam Bouchekif, Hichem Telli +2
Large language models can generate fluent Arabic answers while introducing factual errors that are difficult to identify and verify. Existing Arabic hallucination resources often a…
HalluTruthQA: A Fine-Grained Benchmark for Hallucination Detection, Localization, and Explanation in Arabic Question Answering
Abdessalam Bouchekif, Mohammed-En-Nadhir Zighem, Salah Eddine Bekhouche +9
Large language models (LLMs) can generate fluent Arabic answers, yet factual errors remain difficult to detect, localize, explain, and verify. Existing hallucination benchmarks oft…
AffectFlow-DINO: Uncertainty-Aware Multi-Task Affect Estimation via Conditional Rectified Flow
Salah Eddine Bekhouche, Abdellah Zakaria Sellam, Fadi Dornaika +1
The paper introduces AffectFlow-DINO, a multi‑task system that adds a conditional rectified‑flow head to a frozen DINOv3 ViT backbone to generate uncertainty‑aware, one‑to‑many pre…
RF-HiT: Rectified Flow Hierarchical Transformer for General Medical Image Segmentation
Ahmed Marouane Djouamaa, Abir Belaala, Abdellah Zakaria Sellam +3
Accurate medical image segmentation requires both long-range contextual reasoning and precise boundary delineation, a task where existing transformer- and diffusion-based paradigms…
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…
SPARK-IL: Spectral Retrieval-Augmented RAG for Knowledge-driven Deepfake Detection via Incremental Learning
Hessen Bougueffa Eutamene, Abdellah Zakaria Sellam, Abdelmalik Taleb-Ahmed +1
Detecting AI-generated images remains a significant challenge because detectors trained on specific generators often fail to generalize to unseen models; however, while pixel-level…