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相关论文: Identifying Multiple Personalities in Large Langua…

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This study investigates the capacity of Large Language Models (LLMs) to infer the Big Five personality traits from free-form user interactions. The results demonstrate that a chatbot powered by GPT-4 can infer personality with moderate…

人机交互 · 计算机科学 2024-05-24 Heinrich Peters , Moran Cerf , Sandra C. Matz

The explainability of recommender systems has attracted significant attention in academia and industry. Many efforts have been made for explainable recommendations, yet evaluating the quality of the explanations remains a challenging and…

信息检索 · 计算机科学 2024-06-07 Xiaoyu Zhang , Yishan Li , Jiayin Wang , Bowen Sun , Weizhi Ma , Peijie Sun , Min Zhang

Large language models (LLMs) are increasingly used to support the analysis of complex financial disclosures, yet their reliability, behavioral consistency, and transparency remain insufficiently understood in high-stakes settings. This…

计算与语言 · 计算机科学 2026-01-21 Md Talha Mohsin

Large Language Models (LLMs) have become foundational in modern language-driven software applications, profoundly influencing daily life. A critical technique in leveraging their potential is role-playing, where LLMs simulate diverse roles…

计算机与社会 · 计算机科学 2026-04-23 Xinyue Li , Zhenpeng Chen , Jie M. Zhang , Ying Xiao , Tianlin Li , Weisong Sun , Yang Liu , Yiling Lou , Xuanzhe Liu

This paper explores the integration of human-like emotions and ethical considerations into Large Language Models (LLMs). We first model eight fundamental human emotions, presented as opposing pairs, and employ collaborative LLMs to…

计算与语言 · 计算机科学 2024-06-26 Edward Y. Chang

Personality traits are richly encoded in natural language, and large language models (LLMs) trained on human text can simulate personality when conditioned on persona descriptions. However, existing evaluations rely predominantly on…

计算与语言 · 计算机科学 2026-04-08 Ben Wigler , Maria Tsfasman , Tiffany Matej Hrkalovic

Evaluating Large Language Models' (LLMs) anthropomorphic capabilities has become increasingly important in contemporary discourse. Utilizing the emotion appraisal theory from psychology, we propose to evaluate the empathy ability of LLMs,…

计算与语言 · 计算机科学 2024-10-08 Jen-tse Huang , Man Ho Lam , Eric John Li , Shujie Ren , Wenxuan Wang , Wenxiang Jiao , Zhaopeng Tu , Michael R. Lyu

The rapid evolution of large language models (LLMs) and their capacity to simulate human cognition and behavior has given rise to LLM-based frameworks and tools that are evaluated and applied based on their ability to perform tasks…

计算与语言 · 计算机科学 2024-12-03 Jing Yi Wang , Nicholas Sukiennik , Tong Li , Weikang Su , Qianyue Hao , Jingbo Xu , Zihan Huang , Fengli Xu , Yong Li

Large language models (LLMs) are recognized as systems that closely mimic aspects of human intelligence. This capability has attracted attention from the social science community, who see the potential in leveraging LLMs to replace human…

计算机与社会 · 计算机科学 2025-03-04 Qiuejie Xie , Qiming Feng , Tianqi Zhang , Qingqiu Li , Linyi Yang , Yuejie Zhang , Rui Feng , Liang He , Shang Gao , Yue Zhang

Recent studies have shown that prompting can enable large language models (LLMs) to simulate specific personality traits and produce behaviors that align with those traits. However, there is limited understanding of how these simulated…

计算与语言 · 计算机科学 2026-01-06 Nuo Chen , Hanpei Fang , Piaohong Wang , Jiqun Liu , Tetsuya Sakai , Xiao-Ming Wu

Large Language Models (LLMs) offer new avenues to simulate online communities and social media. Potential applications range from testing the design of content recommendation algorithms to estimating the effects of content policies and…

Self-report questionnaires have long been used to assess LLM personality traits, yet they fail to capture behavioral nuances due to biases and meta-knowledge contamination. This paper proposes a novel multi-observer framework for…

计算与语言 · 计算机科学 2025-05-21 Yin Jou Huang , Rafik Hadfi

Large Language Models (LLMs) should answer factual questions truthfully, grounded in objective knowledge, regardless of user context such as self-disclosed personal information, or system personalization. In this paper, we present the first…

计算与语言 · 计算机科学 2025-10-16 Nil-Jana Akpinar , Chia-Jung Lee , Vanessa Murdock , Pietro Perona

Large Language Models (LLMs) have demonstrated the ability to adopt a personality and behave in a human-like manner. There is a large body of research that investigates the behavioural impacts of personality in less obvious areas such as…

统计金融 · 定量金融 2024-11-12 Harris Borman , Anna Leontjeva , Luiz Pizzato , Max Kun Jiang , Dan Jermyn

Psychometric tests are increasingly used to assess psychological constructs in large language models (LLMs). However, it remains unclear whether these tests -- originally developed for humans -- yield meaningful results when applied to…

计算与语言 · 计算机科学 2026-01-28 Jana Jung , Marlene Lutz , Indira Sen , Markus Strohmaier

Large language models (LLMs) may not equitably represent diverse global perspectives on societal issues. In this paper, we develop a quantitative framework to evaluate whose opinions model-generated responses are more similar to. We first…

This study explores the use of Large Language Models (LLMs) to analyze text comments from Reddit users, aiming to achieve two primary objectives: firstly, to pinpoint critical excerpts that support a predefined psychological assessment of…

计算与语言 · 计算机科学 2024-02-07 Sergi Blanco-Cuaresma

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

Reliable simulation of human behavior is essential for explaining, predicting, and intervening in our society. Recent advances in large language models (LLMs) have shown promise in emulating human behaviors, interactions, and…

计算与语言 · 计算机科学 2025-10-27 Ning Bian , Xianpei Han , Hongyu Lin , Baolei Wu , Jun Wang

Word-level psycholinguistic norms lend empirical support to theories of language processing. However, obtaining such human-based measures is not always feasible or straightforward. One promising approach is to augment human norming datasets…