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Large language models (LLMs) have exploded in popularity in the past few years and have achieved undeniably impressive results on benchmarks as varied as question answering and text summarization. We provide a simple new prompting strategy…

计算与语言 · 计算机科学 2022-12-14 Joshua Albrecht , Ellie Kitanidis , Abraham J. Fetterman

Large Language Models (LLMs) trained on extensive textual corpora have emerged as leading solutions for a broad array of Natural Language Processing (NLP) tasks. Despite their notable performance, these models are prone to certain…

计算与语言 · 计算机科学 2023-07-25 Yufei Wang , Wanjun Zhong , Liangyou Li , Fei Mi , Xingshan Zeng , Wenyong Huang , Lifeng Shang , Xin Jiang , Qun Liu

Large Language Models (LLMs) have demonstrated remarkable abilities in text comprehension and logical reasoning, indicating that the text representations learned by LLMs can facilitate their language processing capabilities. In…

人工智能 · 计算机科学 2025-01-16 Yuqi Ren , Renren Jin , Tongxuan Zhang , Deyi Xiong

Instruction-tuning is a widely adopted finetuning method that enables large language models (LLMs) to generate output that more closely resembles human responses. However, no studies have shown that instruction-tuning actually teaches LLMs…

计算与语言 · 计算机科学 2024-08-12 Khai Loong Aw , Syrielle Montariol , Badr AlKhamissi , Martin Schrimpf , Antoine Bosselut

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

Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona simulation and Role-Playing Language Agents (RPLAs). However, achieving authentic alignment…

计算与语言 · 计算机科学 2026-04-20 Xintao Wang , Jian Yang , Weiyuan Li , Rui Xie , Jen-tse Huang , Jun Gao , Shuai Huang , Yueping Kang , Yuanli Gou , Hongwei Feng , Yanghua Xiao

Large Language Models (LLMs),such as ChatGPT, are increasingly used in research, ranging from simple writing assistance to complex data annotation tasks. Recently, some research has suggested that LLMs may even be able to simulate human…

人工智能 · 计算机科学 2025-08-14 Sarah Schröder , Thekla Morgenroth , Ulrike Kuhl , Valerie Vaquet , Benjamin Paaßen

Large language model alignment is widely used and studied to avoid LLM producing unhelpful and harmful responses. However, the lengthy training process and predefined preference bias hinder adaptation to online diverse human preferences. To…

计算与语言 · 计算机科学 2024-05-02 Guanying Jiang , Lingyong Yan , Haibo Shi , Dawei Yin

Persona-assigned large language models (LLMs) are used in domains such as education, healthcare, and sociodemographic simulation. Yet, they are typically evaluated only in short, single-round settings that do not reflect real-world usage.…

Large language models (LLMs) are increasingly used both to make decisions in domains such as health, education and law, and to simulate human behavior. Yet how closely LLMs mirror actual human decision-making remains poorly understood. This…

人工智能 · 计算机科学 2025-11-26 Andrea Cera Palatsi , Samuel Martin-Gutierrez , Ana S. Cardenal , Max Pellert

As Large Language Models (LLMs) become widely used to model and simulate human behavior, understanding their biases becomes critical. We developed an experimental framework using Big Five personality surveys and uncovered a previously…

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

While a large body of literature suggests that large language models (LLMs) acquire rich linguistic representations, little is known about whether they adapt to linguistic biases in a human-like way. The present study probes this question…

计算与语言 · 计算机科学 2023-05-29 Suet-Ying Lam , Qingcheng Zeng , Kexun Zhang , Chenyu You , Rob Voigt

Large language models (LLMs) are transforming research on machine learning while galvanizing public debates. Understanding not only when these models work well and succeed but also why they fail and misbehave is of great societal relevance.…

计算与语言 · 计算机科学 2024-10-16 Julian Coda-Forno , Kristin Witte , Akshay K. Jagadish , Marcel Binz , Zeynep Akata , Eric Schulz

The humanlike responses of large language models (LLMs) have prompted social scientists to investigate whether LLMs can be used to simulate human participants in experiments, opinion polls and surveys. Of central interest in this line of…

计算与语言 · 计算机科学 2024-05-14 Nikolay B Petrov , Gregory Serapio-García , Jason Rentfrow

Personality traits have long been studied as predictors of human behavior. Recent advances in Large Language Models (LLMs) suggest similar patterns may emerge in artificial systems, with advanced LLMs displaying consistent behavioral…

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

What makes large language models (LLMs) impressive is also what makes them hard to evaluate: their diversity of uses. To evaluate these models, we must understand the purposes they will be used for. We consider a setting where these…

计算与语言 · 计算机科学 2024-06-04 Keyon Vafa , Ashesh Rambachan , Sendhil Mullainathan

Large language models (LLMs) are increasingly used to model human social behavior, with recent research exploring their ability to simulate social dynamics. Here, we test whether LLMs mirror human behavior in social dilemmas, where…

社会与信息网络 · 计算机科学 2024-11-18 Jin Han , Balaraju Battu , Ivan Romić , Talal Rahwan , Petter Holme

Aligning large language models (LLMs) with human intentions has become a critical task for safely deploying models in real-world systems. While existing alignment approaches have seen empirical success, theoretically understanding how these…

机器学习 · 计算机科学 2024-08-08 Shawn Im , Yixuan Li