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From the 2 of 5 linked papers with an AI index.

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5 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.CL2026

A Severity-Based Curriculum Learning Strategy for Arabic Medical Text Generation

Ahmed Alansary, Molham Mohamed, Ali Hamdi

Arabic medical text generation is increasingly needed to help users interpret symptoms and access general health guidance in their native language. Nevertheless, many existing meth…

cs.CL2026

Severity-Aware Weighted Loss for Arabic Medical Text Generation

Ahmed Alansary, Molham Mohamed, Ali Hamdi

Large language models have shown strong potential for Arabic medical text generation; however, traditional fine-tuning objectives treat all medical cases uniformly, ignoring differ…