most citedExploring Large Language Model Agents for Piloting Social Experiments

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.HC2026

AgentEconomist: An End-to-end Agentic System Translating Economic Intuitions into Executable Computational Experiments

Jiaju Chen, Jinghua Piao, Xia Xu +4

A long-standing challenge in economics lies not in the lack of intuition, but in the difficulty of translating intuitive insights into verifiable research. To address this challeng…

cs.CY2026

PaperRepro: Automated Computational Reproducibility Assessment for Social Science Papers

Linhao Zhang, Tong Xia, Jinghua Piao +2

Computational reproducibility is essential for the credibility of scientific findings, particularly in the social sciences, where findings often inform real-world decisions. Manual…

cs.AI2025

Simulating Generative Social Agents via Theory-Informed Workflow Design

Yuwei Yan, Jinghua Piao, Xiaochong Lan +3

Recent advances in large language models have demonstrated strong reasoning and role-playing capabilities, opening new opportunities for agent-based social simulations. However, mo…

cs.CY20251 cited

Exploring Large Language Model Agents for Piloting Social Experiments

Jinghua Piao, Yuwei Yan, Nian Li +2

Computational social experiments, which typically employ agent-based modeling to create testbeds for piloting social experiments, not only provide a computational solution to the m…

cs.SI2025

Debiasing International Attitudes: LLM Agents for Simulating US-China Perception Changes

Nicholas Sukiennik, Yichuan Xu, Yuqing Kan +4

Large Language Models (LLMs) offer transformative opportunities to address the longstanding challenge of modeling opinion evolution in computational social science. This study inve…