English(EN) Same Question, Different Answers: Auditing Persona-Dependent Variation in Six LLMs on Smoking-Cessation Advice

大型语言模型根据用户画像提供不同的戒烟建议

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-02 05:00

一篇新的arXiv论文研究了六个大型语言模型（LLMs）如何根据用户画像提供不同的健康建议，特别是在戒烟方面。研究发现，与成年用户相比，模型经常向青少年用户提供关于FDA批准的戒烟药物的较少信息。此外，与声称拥有医疗专业知识的用户相比，模型有时向这些用户提供的事实也较少。研究人员测试了一个旨在确保最低限度事实信息的系统提示，该提示减少了基于用户画像的差异，但对不同模型的影响不一致。 AI

影响强调了仔细的提示工程的必要性，以确保大型语言模型在不同用户群体中提供一致且准确的健康建议。

排序理由该集群包含一篇详细介绍大型语言模型行为研究结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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Signal score: 1 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群包含一篇详细介绍大型语言模型行为研究结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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arXiv cs.AI TIER_1 English(EN) · Artin Yousefi, Aizierjiang Aiersilan, Lorien C Abroms, David A Broniatowski · 2026-11-02 05:00

Same Question, Different Answers: Auditing Persona-Dependent Variation in Six LLMs on Smoking-Cessation Advice

arXiv:2610.42039v1 Announce Type: new Abstract: Hundreds of millions of people now ask large language model (LLM) chatbots for health advice, which raises a question that is simple to pose and hard to answer: does everyone get the same advice? We audit six widely deployed LLMs fr…

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Same Question, Different Answers: Auditing Persona-Dependent Variation in Six LLMs on Smoking-Cessation Advice

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