六款大模型模拟人类信念更新，一对一对照实验揭示仿真失真边界，社科实验需警惕AI替身风险。
arXiv:2607.28347v1 Announce Type: new Abstract: LLMs are increasingly deployed as proxies for human study participants in social science experiments, …
Nature观点：LLM若被审慎使用，能大幅推进社会科学研究效率与创新。
Nature, Published online: 08 July 2026; doi:10.1038/d41586-026-01875-0 Large language models could advance experiments in the social sciences, but fun…
不止跑代码复现，这个新基准专测AI代理能否重演社科实验，科学验证迎来智能考官。
arXiv:2602.11354v3 Announce Type: replace Abstract: The literature has witnessed an emerging interest in AI agents for automated assessment of scienti…
AI辅助社会科学研究的可靠性关键不在于模型能力，而在于人类监督——别再迷信纯自动化了。
arXiv:2606.12848v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for tasks once reserved for trained researchers, in…
审计LLM标注者的社会期望偏差，揭示对齐误差如何扭曲计算社会科学结论。
arXiv:2606.12426v1 Announce Type: cross Abstract: LLM annotators are increasingly used in computational social science (CSS), but it is unclear whethe…
用LLM模拟社会信念演化，探索AI如何理解并预测群体认知变迁。
arXiv:2606.11482v1 Announce Type: cross Abstract: Understanding and predicting how social beliefs evolve in response to events -- from policy changes …
一篇探讨LLM智能体在社会科学分析中如何平衡方法论多样性、经验一致性与解释脆弱性的前沿学术论文
arXiv:2606.11456v1 Announce Type: cross Abstract: The deployment of LLM-based agents in scientific analysis raises opposing concerns: that agents may …
探索AI编码代理能否系统性复现社会科学发现，最新研究填补评估空白。
arXiv:2606.11447v1 Announce Type: new Abstract: Recent anecdotal evidence suggests that AI coding agents can reproduce published findings when provide…
AI正在颠覆社会科学的研究范式，是毁灭还是革新？来自《自然》的深度探讨。
Nature, Published online: 02 June 2026; doi:10.1038/d41586-026-01726-y The technology can whip up spurious findings and pollute survey responses, but …
聚焦多语言大模型在社科人文领域的责任性与认识论根基，前沿交叉研究。
arXiv:2606.00596v1 Announce Type: new Abstract: Large language models have rapidly evolved in multilingual competence and reasoning capacity, enabling…
LLM在政策评估中的反事实推理受直觉影响，40个实证案例揭示可靠性短板
arXiv:2604.10511v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used for causal and counterfactual reasoning, yet th…
从不确定性量化角度，首次系统评估LLM在替代人类调查受访者时的可靠性边界，为AI调研应用提供严谨方法论。
arXiv:2502.17773v5 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to simulate survey responses, but synthet…
社交媒体如何成为家暴受害者隐秘的求救信号？这项研究揭示了自我披露与支持寻求的动态机制。
arXiv:2509.12288v2 Announce Type: replace-cross Abstract: Domestic Violence (DV) is a pervasive public health problem characterized by patterns of coe…
OpenAI发文论证，长期AI安全研究亟需社会科学家参与，以解决人类心理、偏见与理性不确定性，促进ML与社科跨界协作。
We’ve written a paper arguing that long-term AI safety research needs social scientists to ensure AI alignment algorithms succeed when actual humans a…