RealCV - An AI-Powered Resume Generator

The current job market is rapidly evolving and the recent advances in AI are making the marketplace extremely competitive. Such dynamic job market and associated complexities often obscure the matching process between qualified job seekers and suitable opportunities, particularly during the resume building and job application phases. This RealCV research and the system developed describe the use of a Large Language Model (LLM) to address these disconnects by automating and refining the customization of resumes. Unlike traditional systems that rely on keyword matching, this approach aims to effectively translate academic achievements and other nonconventional experiences into industry-relevant competencies. Using an LLM, our system automatically converts academic CVs into industrial resumes. RealCV will facilitate a deeper understanding of candidates' capabilities, potentially transforming recruitment paradigms and career transitions. The system builds upon our past work, COVID CV [1], in assisting individuals to highlight their “invisible” skills and their mappings to the “soft skills” that are significantly valued in the industry, thereby, providing appropriate matches between the job requirements and seekers' credentials.

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Publication Details

Published
2025-05-29
DOI
https://doi.org/10.1109/eit64391.2025.11103614
Primary Topic
Topic Modeling
Type
article
Field-Weighted Citation Impact
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article

RealCV - An AI-Powered Resume Generator

Aaron Ganci, Rajeev R. Raje, Md. Akhtaruzzaman Khan, Rachel Wheeler et al.
Topic Modeling
article

RealCV - An AI-Powered Resume Generator

Aaron Ganci, Rajeev R. Raje, Md. Akhtaruzzaman Khan, Rachel Wheeler, M. V. Kulkarni
article en

Abstract

The current job market is rapidly evolving and the recent advances in AI are making the marketplace extremely competitive. Such dynamic job market and associated complexities often obscure the matching process between qualified job seekers and suitable opportunities, particularly during the resume building and job application phases. This RealCV research and the system developed describe the use of a Large Language Model (LLM) to address these disconnects by automating and refining the customization of resumes. Unlike traditional systems that rely on keyword matching, this approach aims to effectively translate academic achievements and other nonconventional experiences into industry-relevant competencies. Using an LLM, our system automatically converts academic CVs into industrial resumes. RealCV will facilitate a deeper understanding of candidates' capabilities, potentially transforming recruitment paradigms and career transitions. The system builds upon our past work, COVID CV [1], in assisting individuals to highlight their “invisible” skills and their mappings to the “soft skills” that are significantly valued in the industry, thereby, providing appropriate matches between the job requirements and seekers' credentials.

Indiana University – Purdue University Indianapolis (US)
Affordable and clean energy
Openalex Percentile: Top 89%
Topic Modeling
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