11 papers
Improving Answer Extraction in Context-based Question Answering Systems Using LLMs
Hafez Abdelghaffar, Ahmed Alansary, Ali Hamdi
Question answering (QA) systems have achieved notable progress with the advent of large language models (LLMs). However, they still face challenges in accurately extracting and gen…
A Multi-Model Metric-based Selection Framework for Abstractive Text summarization
Ahmed Alansary, Ali Hamdi
Automatic text summarization has become increasingly important due to the rapid growth of digital textual information. This paper presents a Multi-Model Summarization Framework des…
Severity-Aware Curriculum Learning with Multi-Model Response Selection for Medical Text Generation
Ahmed Alansary, Molham Mohamed, Ali Hamdi
Telehealth systems have become increasingly important for delivering accessible and timely medical information. Existing large language models often struggle to provide consistent…
Hybrid Neural Retrieval with Generative Query Refinement for Quranic Passage Retrieval
Mohamed G. Salman, Mohammad E. Moftah, Ali Hamdi
Quranic Passage Retrieval (PR) could be a challenging task due to the linguistic complexity and the semantic gap between the Modern Standard Arabic (MSA) used in daily queries and…
Two-Stage Quranic QA via Ensemble Retrieval and Instruction-Tuned Answer Extraction
Mohamed Basem, Islam Oshallah, Ali Hamdi +2
Quranic Question Answering presents unique challenges due to the linguistic complexity of Classical Arabic and the semantic richness of religious texts. In this paper, we propose a…
Few-Shot Prompting for Extractive Quranic QA with Instruction-Tuned LLMs
Mohamed Basem, Islam Oshallah, Ali Hamdi +1
This paper presents two effective approaches for Extractive Question Answering (QA) on the Quran. It addresses challenges related to complex language, unique terminology, and deep…
MSA at SemEval-2025 Task 3: High Quality Weak Labeling and LLM Ensemble Verification for Multilingual Hallucination Detection
Baraa Hikal, Ahmed Nasreldin, Ali Hamdi
This paper describes our submission for SemEval-2025 Task 3: Mu-SHROOM, the Multilingual Shared-task on Hallucinations and Related Observable Overgeneration Mistakes. The task invo…
MSA at BEA 2025 Shared Task: Disagreement-Aware Instruction Tuning for Multi-Dimensional Evaluation of LLMs as Math Tutors
Baraa Hikal, Mohamed Basem, Islam Oshallah +1
We present MSA-MathEval, our submission to the BEA 2025 Shared Task on evaluating AI tutor responses across four instructional dimensions: Mistake Identification, Mistake Location,…
Cross-Language Approach for Quranic QA
Islam Oshallah, Mohamed Basem, Ali Hamdi +1
Question answering systems face critical limitations in languages with limited resources and scarce data, making the development of robust models especially challenging. The Qurani…
Few-Shot Optimized Framework for Hallucination Detection in Resource-Limited NLP Systems
Baraa Hikal, Ahmed Nasreldin, Ali Hamdi +1
Hallucination detection in text generation remains an ongoing struggle for natural language processing (NLP) systems, frequently resulting in unreliable outputs in applications suc…
Optimized Quran Passage Retrieval Using an Expanded QA Dataset and Fine-Tuned Language Models
Mohamed Basem, Islam Oshallah, Baraa Hikal +2
Understanding the deep meanings of the Qur'an and bridging the language gap between modern standard Arabic and classical Arabic is essential to improve the question-and-answer syst…