3 papers
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…