English(EN) Can Large Language Models Anticipate Behavioral Responses to Social Policies? A Case of Pension Enrollment Prediction among China's Flexible Workers

新的LLM利用政策线索预测中国养老金参保情况

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-07 04:00

研究人员开发了FlexPension-LLM，一个专门的大型语言模型，用于预测中国灵活就业人员的养老金参保情况。该模型整合了政策依据的线索，如Probit模型的边际效应和具体的养老金规则，以提高其预测准确性。FlexPension-LLM在盲测中取得了较高的复合F1分数，优于大多数基线模型，并与Claude Opus-4.6等先进模型表现相当，同时提供了可解释的决策轨迹。 AI

影响这项研究展示了LLM作为政策分析工具的潜力，为预测对社会政策的行为反应提供了比传统方法更具成本效益的替代方案。

排序理由该集群包含一篇学术论文，详细介绍了一个用于特定预测任务的新LLM。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CL TIER_1 English(EN) · Yumiao Li, Peixin Liu, Donglin Di, Chen Li, Runhuan Feng · 2026-09-07 04:00

大型语言模型能否预测对社会政策的行为反应？以中国灵活就业人员养老金参保预测为例

arXiv:2609.05189v1 Announce Type: new Abstract: Assessing the impacts of social policy changes is a widely acknowledged challenge for policymakers. Econometric methods can be unreliable when extrapolating to hypothetical scenarios, while field pilot programs are highly costly. In…

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大型语言模型能否预测对社会政策的行为反应？以中国灵活就业人员养老金参保预测为例

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