中文
相关论文

相关论文: Evaluating the Simulation of Human Personality-Dri…

200 篇论文

Disinformation campaigns can distort public perception and destabilize institutions. Understanding how different populations respond to information is crucial for designing effective interventions, yet real-world experimentation is…

社会与信息网络 · 计算机科学 2025-11-10 David Farr , Lynnette Hui Xian Ng , Stephen Prochaska , Iain J. Cruickshank , Jevin West

Large language models (LLMs) are increasingly used as proxies for human judgment in computational social science, yet their ability to reproduce patterns of susceptibility to misinformation remains unclear. We test whether LLM-simulated…

社会与信息网络 · 计算机科学 2026-04-13 Eun Cheol Choi , Lindsay E. Young , Emilio Ferrara

Misinformation on social media thrives on surprise, emotion, and identity-driven reasoning, often amplified through human cognitive biases. To investigate these mechanisms, we model large language model (LLM) personas as synthetic agents…

社会与信息网络 · 计算机科学 2025-12-10 Raj Gaurav Maurya , Vaibhav Shukla , Raj Abhijit Dandekar , Rajat Dandekar , Sreedath Panat

Despite the many use cases for large language models (LLMs) in creating personalized chatbots, there has been limited research on evaluating the extent to which the behaviors of personalized LLMs accurately and consistently reflect specific…

计算与语言 · 计算机科学 2024-04-03 Hang Jiang , Xiajie Zhang , Xubo Cao , Cynthia Breazeal , Deb Roy , Jad Kabbara

The proliferation of misinformation on social media platforms has highlighted the need to understand how individual personality traits influence susceptibility to and propagation of misinformation. This study employs an innovative…

计算与语言 · 计算机科学 2025-01-16 Qianmin Lou , Wentao Xu

Existing challenges in misinformation exposure and susceptibility vary across demographic groups, as some populations are more vulnerable to misinformation than others. Large language models (LLMs) introduce new dimensions to these…

计算与语言 · 计算机科学 2025-10-15 Angana Borah , Rada Mihalcea , Verónica Pérez-Rosas

The capabilities of recent large language models (LLMs) to generate high-quality content indistinguishable by humans from human-written texts raises many concerns regarding their misuse. Previous research has shown that LLMs can be…

计算与语言 · 计算机科学 2025-07-28 Aneta Zugecova , Dominik Macko , Ivan Srba , Robert Moro , Jakub Kopal , Katarina Marcincinova , Matus Mesarcik

The prevalence of unwarranted beliefs, spanning pseudoscience, logical fallacies, and conspiracy theories, presents substantial societal hurdles and the risk of disseminating misinformation. Utilizing established psychometric assessments,…

人工智能 · 计算机科学 2024-05-03 Sowmya S Sundaram , Balaji Alwar

The impressive capabilities of Large Language Models (LLMs) raise the possibility that synthetic agents can serve as substitutes for real participants in human-subject research. To evaluate this claim, prior research has largely focused on…

Large Language Models (LLMs) have garnered significant attention for their powerful ability in natural language understanding and reasoning. In this paper, we present a comprehensive empirical study to explore the performance of LLMs on…

计算与语言 · 计算机科学 2024-12-30 Mengyang Chen , Lingwei Wei , Han Cao , Wei Zhou , Songlin Hu

Psychological assessment tools have long helped humans understand behavioural patterns. While Large Language Models (LLMs) can generate content comparable to that of humans, we explore whether they exhibit personality traits. To this end,…

计算与语言 · 计算机科学 2025-02-11 Pranav Bhandari , Usman Naseem , Amitava Datta , Nicolas Fay , Mehwish Nasim

Automated disinformation generation is often listed as an important risk associated with large language models (LLMs). The theoretical ability to flood the information space with disinformation content might have dramatic consequences for…

计算与语言 · 计算机科学 2025-06-13 Ivan Vykopal , Matúš Pikuliak , Ivan Srba , Robert Moro , Dominik Macko , Maria Bielikova

This study proposes a novel methodology for generating personalized fake news debunking messages by prompting Large Language Models (LLMs) with persona-based inputs aligned to the Big Five personality traits: Extraversion, Agreeableness,…

人工智能 · 计算机科学 2026-03-11 Pietro Dell'Oglio , Alessandro Bondielli , Francesco Marcelloni , Lucia C. Passaro

While both agent interaction and personalisation are vibrant topics in research on large language models (LLMs), there has been limited focus on the effect of language interaction on the behaviour of persona-conditioned LLM agents. Such an…

计算与语言 · 计算机科学 2024-02-06 Ivar Frisch , Mario Giulianelli

We investigate and observe the behaviour and performance of Large Language Model (LLM)-backed chatbots in addressing misinformed prompts and questions with demographic information within the domains of Climate Change and Mental Health.…

Accurately simulating human opinion dynamics is crucial for understanding a variety of societal phenomena, including polarization and the spread of misinformation. However, the agent-based models (ABMs) commonly used for such simulations…

The advent of large language models (LLMs) has revolutionized natural language processing, enabling the generation of coherent and contextually relevant human-like text. As LLMs increasingly powerconversational agents used by the general…

Large Language Models (LLMs) can generate human-like disinformation, yet their ability to personalise such content across languages and demographics remains underexplored. This study presents the first large-scale, multilingual analysis of…

Large Language Models (LLMs) are becoming increasingly persuasive, demonstrating the ability to personalize arguments in conversation with humans by leveraging their personal data. This may have serious impacts on the scale and…

计算与语言 · 计算机科学 2025-01-30 Jasper Timm , Chetan Talele , Jacob Haimes

Human communication is motivated: people speak, write, and create content with a particular communicative intent in mind. As a result, information that large language models (LLMs) and AI agents process is inherently framed by humans'…

计算与语言 · 计算机科学 2026-02-03 Addison J. Wu , Ryan Liu , Kerem Oktar , Theodore R. Sumers , Thomas L. Griffiths
‹ 上一页 1 2 3 10 下一页 ›