Resume Building Application based on LLM (Large Language Model)

Amid the highly competitive job market, creating an effective resume is vital but often difficult, particularly for students from underprivileged backgrounds with limited career development support. To mitigate this, we introduce a novel resume building application that employs the Large Language Model (LLM) to aid students in composing their first resumes. The application comprises three modules: Resume Generation, Resume Assessment, and User I/O. The Resume Generation module utilizes prompt engineering to produce resume bullet points, while the Resume Assessment module evaluates these bullet points for potential enhancements. The User I/O module simplifies user interaction by accepting free-style plain English as input and displaying the generated bullet points as suggestions. We have developed a prototype application that demonstrates the effectiveness of these functionalities while emphasizing ease-of-use. We have also confirmed that the content generated for resumes adheres to the benchmarks of high-quality standards. As future work, we aim to carry out usability testing with real students to further evaluate the application's utility in educational environments.