26 citations · 36 across the 7 of their papers we have counts for
7 papers · 1 filter
CARDAMOM: A Micro-Dialectal Arabic Speech Dataset for ASR
Bashar Talafha, Samar M. Magdy, Aisha Alansari +36
We present Cardamom, a micro-dialectal Arabic speech dataset designed to support fine-grained evaluation and adaptation of automatic speech recognition (ASR) systems. Community-cur…
Bulbul: A Dataset for Dialectal Arabic Speech Recognition
Ahmed Ashraf, Aisha Alansari, Fadel Al Abbas +30
Arabic automatic speech recognition (ASR) faces unique challenges due to diglossia, extensive regional dialect variation, and limited speech resources. Existing speech datasets oft…
Large Language Models Hallucination: A Comprehensive Survey
Aisha Alansari, Hamzah Luqman
Large language models (LLMs) have transformed natural language processing, achieving remarkable performance across diverse tasks. However, their impressive fluency often comes at t…
AraHalluEval: A Fine-grained Hallucination Evaluation Framework for Arabic LLMs
Aisha Alansari, Hamzah Luqman
Recently, extensive research on the hallucination of the large language models (LLMs) has mainly focused on the English language. Despite the growing number of multilingual and Ara…
Multi-task Learning with Active Learning for Arabic Offensive Speech Detection
Aisha Alansari, Hamzah Luqman
The rapid growth of social media has amplified the spread of offensive, violent, and vulgar speech, which poses serious societal and cybersecurity concerns. Detecting such content…
AraReasoner: Evaluating Reasoning-Based LLMs for Arabic NLP
Ahmed Hasanaath, Aisha Alansari, Ahmed Ashraf +3
Large language models (LLMs) have shown remarkable progress in reasoning abilities and general natural language processing (NLP) tasks, yet their performance on Arabic data, charac…
Pearl: A Multimodal Culturally-Aware Arabic Instruction Dataset
Fakhraddin Alwajih, Samar M. Magdy, Abdellah El Mekki +34
Mainstream large vision-language models (LVLMs) inherently encode cultural biases, highlighting the need for diverse multimodal datasets. To address this gap, we introduce PEARL, a…