mlsanityData to 14 Oct 2026

ERPA: Efficient RPA Model Integrating OCR and LLMs for Intelligent Document Processing

arXiv 2412.19840 ↗First posted 24 Dec 2024cs.CV cs.HC cs.IRcited by 6

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Abstract (arXiv)

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.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 1 of its 9 references that are in the map. First posted on arXiv 24 Dec 2024.

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1 of 9 references.

References · 1

  1. 2024ASEM: Enhancing Empathy in Chatbot through Attention-based Sentiment and Emotion Modelingcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 4; 2026: 2.

6 papers.