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From the 2 of 11 linked papers with an AI index.

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20242026
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11 papers

cs.CL2026

A Multi-Model Metric-based Selection Framework for Abstractive Text summarization

Ahmed Alansary, Ali Hamdi

The paper proposes a framework that combines several fine‑tuned transformer summarizers and selects the best output using automatic metrics, improving abstractive summarization qua…

cs.AI2026

Severity-Aware Curriculum Learning with Multi-Model Response Selection for Medical Text Generation

Ahmed Alansary, Molham Mohamed, Ali Hamdi

The paper proposes a severity‑aware curriculum learning approach that trains multiple language models sequentially on mild, moderate, and critical medical queries and selects the b…

cs.CL2026

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…

cs.IR2026

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…

cs.CL2025

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…

cs.CL2025

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…