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Generative AI models for virtual interviewers: applicability and performance comparison
2
Zitationen
6
Autoren
2024
Jahr
Abstract
Interviewing processes are considered crucial steps in job hunting or college admissions, and effective practice plays a significant role in successfully navigating these stages. Although various platforms have recently emerged for practicing virtual interviews, they often lack the tension and realism of actual interviews due to repetitive and formal content. This study aims to analyze and compare the performance of different generative AI models for creating a diverse set of virtual interviewers. Specifically, we examine the characteristics and applicability of each model, as well as the differences and advantages between them, and evaluate the performance of the generated virtual interviewers. Through this analysis, we aim to propose solutions for enhancing the practicality and efficiency of virtual interviews.
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