LLM evaluators reward AI-positive attitudes in hiring, producing organizations prone to greater AI delegation and reduced scrutiny of AI proposals.
Gaebler, Sharad Goel, Aziz Huq, and Prasanna Tambe
2 Pith papers cite this work. Polarity classification is still indexing.
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LLMs exhibit quality-dependent order biases and name biases in pairwise comparisons that can cause selection of inferior options, demonstrated across resume and color tasks with a new classification of preferences as robust, fragile, or indifferent.
citing papers explorer
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LLM Nepotism in Organizational Governance
LLM evaluators reward AI-positive attitudes in hiring, producing organizations prone to greater AI delegation and reduced scrutiny of AI proposals.
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Fragile Preferences: A Deep Dive Into Order Effects in Large Language Models
LLMs exhibit quality-dependent order biases and name biases in pairwise comparisons that can cause selection of inferior options, demonstrated across resume and color tasks with a new classification of preferences as robust, fragile, or indifferent.