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EMNLP 2025emnlpfindings

Your Mileage May Vary: How Empathy and Demographics Shape Human Preferences in LLM Responses

Yishan Wang, Amanda Cercas Curry, Flor Miriam Plaza-del-Arco

Eindhoven University of Technology · CENTAI Institute · Leiden University

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2025.findings-emnlp.935 ↗

摘要

As large language models (LLMs) increasingly assist in subjective decision-making (e.g., moral reasoning, advice), it is critical to understand whose preferences they align with—and why. While prior work uses aggregate human judgments, demographic variation and its linguistic drivers remain underexplored. We present a comprehensive analysis of how demographic background and empathy level correlate with preferences for LLM-generated dilemma responses, alongside a systematic study of predictive linguistic features (e.g., agency, emotional tone). Our findings reveal significant demographic divides and identify markers (e.g., power verbs, tentative phrasing) that predict group-level differences. These results underscore the need for demographically informed LLM evaluation.