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

Paper recorded by Signals 4 on 2026-09-04 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-04 on arXiv · recorded by Signals 4 on 2026-09-07

Category: cs.CL · 自然语言处理 · first seen 2026-09-07

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 this paper, we propose using large language models (LLMs) as policy-assessment tools adapted from general-purpose models. We present FlexPension-LLM, the first domain-

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#103 most recent of 186 cs.CL papers we have recorded · ↑ newer: Self-Supervised Lexical Representation Learning for Fast, Large-Scale · ↓ older: Measuring the Novelty of Biomedical Papers Using the Latent Distances
Cite this page: Can Large Language Models Anticipate Behavioral Responses to Social Policies? A Case of Pension Enrollment Prediction among China's Flexible Workers: the #103 most recent of 186 cs.CL papers we have recorded (as of 2026-09-04). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/can-large-language-models-anticipate-behavioral-responses-to-social-policies-a-c.html
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