From Resumes (PDFs) to Clean Data: Layout-Aware Parsing with Small LLMs

Author(s): florian jun

Originally published on Towards AI.

Have you ever wondered how to parse a resume, or have you had to work with resumes at work?

This article will give you some useful information.

The article discusses the challenges of traditional OCR and LLM approaches to resume parsing, emphasizing layout and content diversity, high estimation costs, and lack of standardized datasets. It proposes a three-step pipeline for parsing resumes that includes flattening the layout, using an efficient LLM for data extraction, and applying holistic evaluation metrics. The methodology shows promising results in processing speed and accuracy, outperforming existing models while addressing common shortcomings in resume data extraction.

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Published via Towards AI