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<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Application of LLM Agents in Recruitment: A Novel Framework for Resume Screening · HackerPapers discussions</title><link>https://hackerpaper.kaipfister.de/p/2401.08315/</link><description>Collected HN comments and submissions linking this paper.</description><language>en</language><lastBuildDate>Mon, 02 Nov 2026 11:16:22 GMT</lastBuildDate><atom:link href="https://hackerpaper.kaipfister.de/p/2401.08315/feed.xml" rel="self" type="application/rss+xml" /><item><title>Application of LLM Agents in Recruitment: A Novel Framework for Resume Screening — mentioned by intended</title><link>https://news.ycombinator.com/item?id=40490174</link><guid isPermaLink="false">urn:hackerpapers:mention:2401.08315:40490174</guid><pubDate>Mon, 27 May 2024 12:34:07 GMT</pubDate><description>&lt;p&gt;Dealt with a project like this at work, these were part of my reading/reserach: https://arxiv.org/pdf/2401.08315.pdf https://www.spiceworks.com/hr/recruitment-onboarding/article... https://hbr.org/2019/05/your-approach-to-hiring-is-all-wrong https://drjohnsullivan.com/articles/ai-will-dominate-recruit... 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…&lt;/p&gt;&lt;p&gt;&lt;a href="https://hackerpaper.kaipfister.de/p/2401.08315/"&gt;Paper and discussion history&lt;/a&gt;. A mention is not an endorsement.&lt;/p&gt;</description><category>cs.CL</category></item></channel></rss>
