ERPA: Efficient RPA Model Integrating OCR and LLMs for Intelligent Document Processing
Abstract
This paper presents ERPA, an innovative Robotic Process Automation (RPA) model designed to enhance ID data extraction and optimize Optical Character Recognition (OCR) tasks within immigration workflows. Traditional RPA solutions often face performance limitations when processing large volumes of documents, leading to inefficiencies. ERPA addresses these challenges by incorporating Large Language Models (LLMs) to improve the accuracy and clarity of extracted text, effectively handling ambiguous characters and complex structures. Benchmark comparisons with leading platforms like UiPath and Automation Anywhere demonstrate that ERPA significantly reduces processing times by up to 94 percent, completing ID data extraction in just 9.94 seconds. These findings highlight ERPA's potential to revolutionize document automation, offering a faster and more reliable alternative to current RPA solutions.
Keywords
Cite
@article{arxiv.2412.19840,
title = {ERPA: Efficient RPA Model Integrating OCR and LLMs for Intelligent Document Processing},
author = {Osama Abdellaif and Abdelrahman Nader and Ali Hamdi},
journal= {arXiv preprint arXiv:2412.19840},
year = {2024}
}
Comments
6 pages , 2 figures, 1 algorithm