College - Author 1
College of Engineering
Department - Author 1
Computer Science Department
College - Author 2
College of Engineering
Department - Author 2
Computer Science Department
Advisor
Kirk Duran, College Of Engineering, Computer Science Department
Funding Source
CENG
Acknowledgements
Dr. Kirk Duran, Chris Liu, Hek Waseem, Jason Yu, Kenton Rhoden, Sam Hong Phan, Brooke Comstock, EnhanCV, OpenAI, MongoDB
Date
10-2024
Abstract/Summary
Resume generation using Large Language Models (LLMs) like ChatGPT is becoming increasingly popular for automating the creation of customized resumes, but significant user modification is often required before submission. Common issues include poor alignment with job descriptions, inflated qualifications, and lack of authenticity, which undermine the effectiveness of LLM-generated resumes. This project addresses these challenges by integrating feedback from Applicant Tracking Systems (ATS) to guide LLMs in producing resumes that accurately reflect an applicant’s qualifications and better align with job-specific requirements. By optimizing the model's output through ATS feedback, the project aims to create more authentic, tailored, and ATS-compatible resumes, reducing the need for manual edits and improving candidates' chances of passing automated filters and securing interviews.
October 1, 2024.
URL: https://digitalcommons.calpoly.edu/ceng_surp/72