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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

Languages are shaped by the inductive biases of their users. Using a classical referential game, we investigate how artificial languages evolve when optimised for inductive biases in humans and large language models (LLMs) via Human-Human,…

计算与语言 · 计算机科学 2025-05-29 Tom Kouwenhoven , Max Peeperkorn , Roy de Kleijn , Tessa Verhoef

Large Language Models (LLMs) created new opportunities for generating personas, expected to streamline and accelerate the human-centered design process. Yet, AI-generated personas may not accurately represent actual user experiences, as…

When Artificial Intelligence (AI) is used to replace consumers (e.g., synthetic data), it is often assumed that AI emulates established consumers, and more generally human behaviors. Ten experiments with Large Language Models (LLMs)…

Large language models (LLMs) have been widely applied in various fields due to their excellent capability for memorizing knowledge and chain of thought (CoT). When these language models are applied in the field of psychological counseling,…

计算与语言 · 计算机科学 2023-11-02 Yirong Chen , Xiaofen Xing , Jingkai Lin , Huimin Zheng , Zhenyu Wang , Qi Liu , Xiangmin Xu

Humans no doubt use language to communicate about their emotional experiences, but does language in turn help humans understand emotions, or is language just a vehicle of communication? This study used a form of artificial intelligence (AI)…

The rapid development of Large Language Models (LLMs) opens up the possibility of using them as personal tutors. This has led to the development of several intelligent tutoring systems and learning assistants that use LLMs as back-ends with…

新兴技术 · 计算机科学 2025-06-11 Sankalan Pal Chowdhury , Terry Jingchen Zhang , Donya Rooein , Dirk Hovy , Tanja Käser , Mrinmaya Sachan

Large Language Models (LLMs) have made significant progress in reasoning, demonstrating their capability to generate human-like responses. This study analyzes the problem-solving capabilities of LLMs in the domain of thermodynamics. A…

计算工程、金融与科学 · 计算机科学 2025-12-18 Rebecca Loubet , Pascal Zittlau , Luisa Vollmer , Marco Hoffmann , Sophie Fellenz , Fabian Jirasek , Heike Leitte , Hans Hasse

The potential of artificial intelligence (AI)-based large language models (LLMs) holds considerable promise in revolutionizing education, research, and practice. However, distinguishing between human-written and AI-generated text has become…

计算与语言 · 计算机科学 2023-11-14 Kadhim Hayawi , Sakib Shahriar , Sujith Samuel Mathew

Large language models (LLMs) are used by over a billion people globally, most often to assist with writing. In this work, we demonstrate that LLMs not only alter the voice and tone of human writing, but also consistently alter the intended…

计算与语言 · 计算机科学 2026-03-20 Marwa Abdulhai , Isadora White , Yanming Wan , Ibrahim Qureshi , Joel Leibo , Max Kleiman-Weiner , Natasha Jaques

Artificial Intelligence (AI) and large language models (LLMs) are increasingly used in social and psychological research. Among potential applications, LLMs can be used to generate, customise, or adapt measurement instruments. This study…

人机交互 · 计算机科学 2026-02-16 Mario Angelelli , Morena Oliva , Serena Arima , Enrico Ciavolino

Large Language Models' (LLMs) ability to converse naturally is empowered by their ability to empathetically understand and respond to their users. However, emotional experiences are shaped by demographic and cultural contexts. This raises…

计算与语言 · 计算机科学 2025-10-28 Ananya Malik , Nazanin Sabri , Melissa Karnaze , Mai Elsherief

The integration of Large Language Models (LLMs) into the healthcare domain has the potential to significantly enhance patient care and support through the development of empathetic, patient-facing chatbots. This study investigates an…

计算与语言 · 计算机科学 2024-05-28 Man Luo , Christopher J. Warren , Lu Cheng , Haidar M. Abdul-Muhsin , Imon Banerjee

Large Language Models (LLMs) in search applications increasingly prioritize verbose, lexically complex responses that paradoxically reduce user satisfaction and engagement. Through a comprehensive study of 10.000 (est.) participants…

人机交互 · 计算机科学 2025-08-08 Carlo Esposito

Studying and building datasets for dialogue tasks is both expensive and time-consuming due to the need to recruit, train, and collect data from study participants. In response, much recent work has sought to use large language models (LLMs)…

As AI becomes fundamental in sectors like healthcare, explainable AI (XAI) tools are essential for trust and transparency. However, traditional user studies used to evaluate these tools are often costly, time consuming, and difficult to…

Large Language Models (LLMs) are increasingly expected to navigate the nuances of human emotion. While research confirms that LLMs can simulate emotional intelligence, their internal emotional mechanisms remain largely unexplored. This…

人工智能 · 计算机科学 2025-10-14 Jingxiang Zhang , Lujia Zhong

Large Language Models (LLMs) demonstrate a remarkable capacity to adopt different personas and roles; however, it remains unclear whether they can manifest behavior that adheres to a coherent, human-like value structure. In this work, we…

人工智能 · 计算机科学 2026-05-29 Asaf Yehudai , Naama Rozen , Ariel Gera

This paper explores the potential of constructing an AI spoken dialogue system that "thinks how to respond" and "thinks how to speak" simultaneously, which more closely aligns with the human speech production process compared to the current…

计算与语言 · 计算机科学 2023-09-21 Xinyu Zhou , Delong Chen , Yudong Chen

The rapid advancements in large language models (LLMs) have significantly improved their ability to generate natural language, making texts generated by LLMs increasingly indistinguishable from human-written texts. While recent research has…

计算与语言 · 计算机科学 2025-10-01 Sergio E. Zanotto , Segun Aroyehun