English(EN) From the Fluency Fallacy to the Micro-to-Macro Validity Gap: Opportunities and Pitfalls of LLMs in Social Simulation

论文批评LLM在社会模拟中的应用，指出有效性差距

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-10 04:00

一篇新论文批判性地审视了大型语言模型（LLM）在社会模拟中的整合，强调了重大的方法论和认识论挑战。研究确定了一个“微观到宏观有效性差距”，其中LLM的局限性，如幻觉和偏见，可能在多主体社会中传播为系统性风险。虽然LLM在严肃游戏和探索性建模等特定应用中显示出价值，但该论文警告不要将其用于精确的社会预测，并强调需要具有稳健评估框架的混合架构来进行确认性研究。 AI

影响强调了LLM在社会模拟中潜在的系统性风险和局限性，敦促在精确预测方面要谨慎。

排序理由该集群包含一篇在arXiv上发表的同行评审学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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本文如何被排名

Signal score: 13 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 该集群包含一篇在arXiv上发表的同行评审学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Patrick Taillandier, Jean Daniel Zucker, Arnaud Grignard, Benoit Gaudou, Nghi Quang Huynh, Haojia Kong, Alexis Drogoul · 2026-09-10 04:00

从流畅性谬误到微观-宏观有效性鸿沟：LLM在社会模拟中的机遇与陷阱

arXiv:2507.19364v3 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) into social simulation has generated considerable enthusiasm, but also raises substantial methodological and epistemological challenges. This critical review examines the use of LL…

本文如何被排名

报道来源 [1]

从流畅性谬误到微观-宏观有效性鸿沟：LLM在社会模拟中的机遇与陷阱

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