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Large Language Models (LLMs) have shown impressive potential to simulate human behavior. We identify a fundamental challenge in using them to simulate experiments: when LLM-simulated subjects are blind to the experimental design (as is…

人工智能 · 计算机科学 2025-11-25 George Gui , Olivier Toubia

Large language models (LLMs) are increasingly used to simulate human responses in behavioral research, yet it remains unclear when LLM-generated data support the same experimental inferences as human data. We evaluate this by directly…

人机交互 · 计算机科学 2026-04-20 Adnan Hoq , Tim Weninger

Large language models (LLMs) offer emerging opportunities for psychological and behavioral research, but methodological guidance is lacking. This article provides a framework for using LLMs as psychological simulators across two primary…

计算机与社会 · 计算机科学 2026-04-07 Zhicheng Lin

Behavioral simulation is increasingly used to anticipate responses to interventions. Large language models (LLMs) enable researchers to specify population characteristics and intervention context in natural language, but it remains unclear…

计算机与社会 · 计算机科学 2026-04-14 Zonghan Li , Feng Ji

In the present study, we investigate and compare reasoning in large language models (LLM) and humans using a selection of cognitive psychology tools traditionally dedicated to the study of (bounded) rationality. To do so, we presented to…

计算与语言 · 计算机科学 2023-09-25 Nicolas Yax , Hernan Anlló , Stefano Palminteri

Large Language Models (LLMs) are increasingly employed for simulating human behaviors across diverse domains. However, our position is that current LLM-based human simulations remain insufficiently reliable, as evidenced by significant…

计算与语言 · 计算机科学 2025-12-02 Qian Wang , Jiaying Wu , Zichen Jiang , Zhenheng Tang , Bingqiao Luo , Nuo Chen , Wei Chen , Bingsheng He

Large language models (LLMs) show potential as simulators of human behavior, offering a scalable way to study responses to interventions. However, because LLMs are trained largely on observational data, interventions in experiments with…

计算与语言 · 计算机科学 2026-05-21 Victoria Lin , Taedong Yun , Maja Matarić , John Canny , Arthur Gretton , Alexander D'Amour

Large language models (LLMs) are increasingly used in the social sciences to simulate human behavior, based on the assumption that they can generate realistic, human-like text. Yet this assumption remains largely untested. Existing…

计算与语言 · 计算机科学 2025-11-26 Nicolò Pagan , Petter Törnberg , Christopher A. Bail , Anikó Hannák , Christopher Barrie

Accurate and verifiable large language model (LLM) simulations of human research subjects promise an accessible data source for understanding human behavior and training new AI systems. However, results to date have been limited, and few…

Prevailing large language models (LLMs) are capable of human responses simulation through its unprecedented content generation and reasoning abilities. However, it is not clear whether and how to leverage LLMs to simulate field experiments.…

人工智能 · 计算机科学 2024-08-20 Yaoyu Chen , Yuheng Hu , Yingda Lu

State of the art large language models (LLMs) have shown impressive performance on a variety of benchmark tasks and are increasingly used as components in larger applications, where LLM-based predictions serve as proxies for human…

计算与语言 · 计算机科学 2024-06-14 Michael Franke , Polina Tsvilodub , Fausto Carcassi

There is ongoing debate about whether large language models (LLMs) can serve as substitutes for human participants in survey and experimental research. While recent work in fields such as marketing and psychology has explored the potential…

计算与语言 · 计算机科学 2025-12-30 Steven Wang , Kyle Hunt , Shaojie Tang , Kenneth Joseph

Recent studies suggest large language models (LLMs) can exhibit human-like reasoning, aligning with human behavior in economic experiments, surveys, and political discourse. This has led many to propose that LLMs can be used as surrogates…

综合经济学 · 经济学 2025-01-24 Yuan Gao , Dokyun Lee , Gordon Burtch , Sina Fazelpour

LLMs are emerging tools for simulating human behavior in business, economics, and social science, offering a lower-cost complement to laboratory experiments, field studies, and surveys. This paper evaluates how well LLMs replicate human…

机器学习 · 计算机科学 2025-10-07 Runze Zhang , Xiaowei Zhang , Mingyang Zhao

Surveys provide valuable insights into public opinion and behavior, but their execution is costly and slow. Large language models (LLMs) have been proposed as a scalable, low-cost substitute for human respondents, but their outputs are…

计算与语言 · 计算机科学 2025-10-21 Stefan Krsteski , Giuseppe Russo , Serina Chang , Robert West , Kristina Gligorić

Large language models (LLMs) are increasingly being used in human-centered social scientific tasks, such as data annotation, synthetic data creation, and engaging in dialog. However, these tasks are highly subjective and dependent on human…

The recent excitement around generative models has sparked a wave of proposals suggesting the replacement of human participation and labor in research and development--e.g., through surveys, experiments, and interviews--with synthetic…

人机交互 · 计算机科学 2024-10-01 Shivani Kapania , William Agnew , Motahhare Eslami , Hoda Heidari , Sarah Fox

Large Language Models (LLMs) have transformed artificial intelligence by excelling in complex natural language processing tasks. Their ability to generate human-like text has opened new possibilities for market research, particularly in…

人工智能 · 计算机科学 2026-04-20 Mengxin Wang , Dennis J. Zhang , Heng Zhang

Large language models (LLMs) are increasingly used in social science simulations. While their performance on reasoning and optimization tasks has been extensively evaluated, less attention has been paid to their ability to simulate human…

计算工程、金融与科学 · 计算机科学 2025-08-25 Yuanjun Feng , Vivek Choudhary , Yash Raj Shrestha

This paper explores the potential of large language models (LLMs) as reliable analytical tools in linguistic research, focusing on the emergence of affective meanings in temporal expressions involving manner-of-motion verbs. While LLMs like…

计算与语言 · 计算机科学 2025-07-15 Rosa Illan Castillo , Javier Valenzuela
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