As a Machine Learning Researcher at Noxx, I developed a method to extract structured data from complex resume PDFs. Noxx builds AI-driven Applicant Tracking Systems that help companies hire overseas talent within budget and time zone constraints by using LLMs that understand resume meaning, not just keywords.
Resumes with their multi-column layouts and varied formatting styles present significant challenges for standard text extraction methods. Our approach preserves both text content and spatial information to maintain logical connections between resume elements.
“The key to success, as with any LLM features, is measuring performance and iterating on implementations.” — Anthropic Engineering Blog, Building Effective Agents
The evaluation framework described here has helped us create more reliable AI systems and can be applied to many LLM-based applications beyond resume parsing. Whether you’re working with documents, images, or structured data, the techniques for combining OCR with LLMs outlined in this article will provide valuable insights for your own projects.
masaishi•8mo ago
Resumes with their multi-column layouts and varied formatting styles present significant challenges for standard text extraction methods. Our approach preserves both text content and spatial information to maintain logical connections between resume elements.
“The key to success, as with any LLM features, is measuring performance and iterating on implementations.” — Anthropic Engineering Blog, Building Effective Agents
The evaluation framework described here has helped us create more reliable AI systems and can be applied to many LLM-based applications beyond resume parsing. Whether you’re working with documents, images, or structured data, the techniques for combining OCR with LLMs outlined in this article will provide valuable insights for your own projects.