Dealt with a project like this at work, these were part of my reading/reserach: https://arxiv.org/pdf/2401.08315.pdf https://arxiv.org/pdf/2401.08315.pdf http

Dealt with a project like this at work, these were part of my reading/reserach: https://arxiv.org/pdf/2401.08315.pdf https://arxiv.org/pdf/2401.08315.pdf https://www.spiceworks.com/hr/recruitment-onboarding/articles/hr-leaders-miss-key-candidates-due-to-inefficient-processes/ https://www.spiceworks.com/hr/recruitment-onboarding/article... https://hbr.org/2019/05/your-approach-to-hiring-is-all-wrong https://hbr.org/2019/05/your-approach-to-hiring-is-all-wrong https://drjohnsullivan.com/articles/ai-will-dominate-recruiting-future/ https://drjohnsullivan.com/articles/ai-will-dominate-recruit... https://drjohnsullivan.com/articles/predict-each-candidates-time-to-turnover/ https://drjohnsullivan.com/articles/predict-each-candidates-... Kaygin, Esranur. (2023). Comparative Analysis of ML (Machine Learning) and LLM (Large Language Models) in Resume Parsing: A Paradigm Shift in Talent Acquisition. ---- From what I can tell, there is potential for non trivial assistance from LLMs in this space.