中文
相关论文

相关论文: Investigating Large Language Models in Inferring P…

200 篇论文

As Large Language Models (LLMs) become integral to human-centered applications, understanding their personality-like behaviors is increasingly important for responsible development and deployment. This paper systematically evaluates six…

计算与语言 · 计算机科学 2025-11-07 Christos-Nikolaos Zacharopoulos , Revekka Kyriakoglou

The study explores whether current Large Language Models (LLMs) exhibit Theory of Mind (ToM) capabilities -- specifically, the ability to infer others' beliefs, intentions, and emotions from text. Given that LLMs are trained on language…

计算与语言 · 计算机科学 2026-03-20 Anna Babarczy , Andras Lukacs , Peter Vedres , Zeteny Bujka

Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate their emerging abilities. In this study, we show that LLMs,…

计算与语言 · 计算机科学 2023-10-10 Thilo Hagendorff , Sarah Fabi

Background: Advancements in large language models (LLMs) have opened new possibilities in psychiatric interviews, an underexplored area where LLMs could be valuable. This study focuses on enhancing psychiatric interviews by analyzing…

人工智能 · 计算机科学 2025-02-11 Jae-hee So , Joonhwan Chang , Eunji Kim , Junho Na , JiYeon Choi , Jy-yong Sohn , Byung-Hoon Kim , Sang Hui Chu

Large Language Models (LLMs) are increasingly deployed in roles requiring nuanced psychological understanding, such as emotional support agents, counselors, and decision-making assistants. However, their ability to interpret human…

计算与语言 · 计算机科学 2025-09-17 Jianfeng Zhu , Julina Maharjan , Xinyu Li , Karin G. Coifman , Ruoming Jin

Accurate assessment of personality traits is crucial for effective psycho-counseling, yet traditional methods like self-report questionnaires are time-consuming and biased. This study exams whether Large Language Models (LLMs) can predict…

计算与语言 · 计算机科学 2024-06-26 Yang Yan , Lizhi Ma , Anqi Li , Jingsong Ma , Zhenzhong Lan

Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate their emerging abilities. In this study, we show that LLMs…

计算与语言 · 计算机科学 2023-10-10 Thilo Hagendorff , Sarah Fabi , Michal Kosinski

This study explores how the Large Language Models (LLMs) adjust linguistic features to create personalized persuasive outputs. While research showed that LLMs personalize outputs, a gap remains in understanding the linguistic features of…

In this work, we tackle the challenge of embedding realistic human personality traits into LLMs. Previous approaches have primarily focused on prompt-based methods that describe the behavior associated with the desired personality traits,…

计算与语言 · 计算机科学 2025-07-30 Wenkai Li , Jiarui Liu , Andy Liu , Xuhui Zhou , Mona Diab , Maarten Sap

As educational systems evolve, ensuring that assessment items remain aligned with content standards is essential for maintaining fairness and instructional relevance. Traditional human alignment reviews are accurate but slow and…

人工智能 · 计算机科学 2025-11-26 Farzan Karimi-Malekabadi , Pooya Razavi , Sonya Powers

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 attracting the attention of healthcare professionals for their potential to assist in diagnostic assessments, which could alleviate the strain on the healthcare system caused by a high patient…

计算与语言 · 计算机科学 2025-01-03 Kaushik Roy , Harshul Surana , Darssan Eswaramoorthi , Yuxin Zi , Vedant Palit , Ritvik Garimella , Amit Sheth

Large Language Models (LLMs), which simulate human users, are frequently employed to evaluate chatbots in applications such as tutoring and customer service. Effective evaluation necessitates a high degree of human-like diversity within…

计算与语言 · 计算机科学 2024-09-04 Xiaoyu Lin , Xinkai Yu , Ankit Aich , Salvatore Giorgi , Lyle Ungar

We present Big5-Scaler, a prompt-based framework for conditioning large language models (LLMs) with controllable Big Five personality traits. By embedding numeric trait values into natural language prompts, our method enables fine-grained…

计算与语言 · 计算机科学 2025-08-11 Gunhee Cho , Yun-Gyung Cheong

Large Language Models (LLM) have recently been shown to perform well at various tasks from language understanding, reasoning, storytelling, and information search to theory of mind. In an extension of this work, we explore the ability of…

计算与语言 · 计算机科学 2023-10-31 Nutchanon Yongsatianchot , Tobias Thejll-Madsen , Stacy Marsella

This paper describes a rapid feasibility study of using GPT-4, a large language model (LLM), to (semi)automate data extraction in systematic reviews. Despite the recent surge of interest in LLMs there is still a lack of understanding of how…

We examine whether large language models (LLMs) can predict biased decision-making in conversational settings, and whether their predictions capture not only human cognitive biases but also how those effects change under cognitive load. In…

人机交互 · 计算机科学 2026-02-06 Stephen Pilli , Vivek Nallur

With large language models (LLMs) like GPT-4 appearing to behave increasingly human-like in text-based interactions, it has become popular to attempt to evaluate personality traits of LLMs using questionnaires originally developed for…

计算与语言 · 计算机科学 2024-06-06 Tom Sühr , Florian E. Dorner , Samira Samadi , Augustin Kelava

A Large Language Model (LLM) is an artificial intelligence system that has been trained on vast amounts of natural language data, enabling it to generate human-like responses to written or spoken language input. GPT-3.5 is an example of an…

人工智能 · 计算机科学 2023-05-09 Gaurav Suri , Lily R. Slater , Ali Ziaee , Morgan Nguyen

Sensitive information detection is crucial in content moderation to maintain safe online communities. Assisting in this traditionally manual process could relieve human moderators from overwhelming and tedious tasks, allowing them to focus…