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cs.CL2025

Scaling Arabic Medical Chatbots Using Synthetic Data: Enhancing Generative AI with Synthetic Patient Records

Abdulrahman Allam, Seif Ahmed, Ali Hamdi +1

The development of medical chatbots in Arabic is significantly constrained by the scarcity of large-scale, high-quality annotated datasets. While prior efforts compiled a dataset o…

cs.CL2025

Arabic Large Language Models for Medical Text Generation

Abdulrahman Allam, Seif Ahmed, Ali Hamdi +1

Efficient hospital management systems (HMS) are critical worldwide to address challenges such as overcrowding, limited resources, and poor availability of urgent health care. Exist…

cs.CL2025

MSLEF: Multi-Segment LLM Ensemble Finetuning in Recruitment

Omar Walid, Mohamed T. Younes, Khaled Shaban +2

This paper presents MSLEF, a multi-segment ensemble framework that employs LLM fine-tuning to enhance resume parsing in recruitment automation. It integrates fine-tuned Large Langu…

cs.CL2025

Augmented Fine-Tuned LLMs for Enhanced Recruitment Automation

Mohamed T. Younes, Omar Walid, Khaled Shaban +2

This paper presents a novel approach to recruitment automation. Large Language Models (LLMs) were fine-tuned to improve accuracy and efficiency. Building upon our previous work on…

cs.CL2025

MLAR: Multi-layer Large Language Model-based Robotic Process Automation Applicant Tracking

Mohamed T. Younes, Omar Walid, Mai Hassan +1

This paper introduces an innovative Applicant Tracking System (ATS) enhanced by a novel Robotic process automation (RPA) framework or as further referred to as MLAR. Traditional re…