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相关论文: Large Language Models as Superpositions of Cultura…

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Large Language Models (LLMs) have demonstrated human-like capabilities in language comprehension and generation, becoming active participants in social and cognitive domains. This study investigates whether LLMs exhibit personality-like…

计算与语言 · 计算机科学 2025-05-22 Wang Jiaqi , Wang bo , Guo fa , Cheng cheng , Yang li

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

Large language models (LLMs) closely interact with humans, and thus need an intimate understanding of the cultural values of human society. In this paper, we explore how open-source LLMs make judgments on diverse categories of cultural…

计算与语言 · 计算机科学 2024-12-13 Minsang Kim , Seungjun Baek

Large Language Models (LLMs) are rapidly being adopted by users across the globe, who interact with them in a diverse range of languages. At the same time, there are well-documented imbalances in the training data and optimisation…

人工智能 · 计算机科学 2025-11-07 Bram Bulté , Ayla Rigouts Terryn

In subjective decision-making, where decisions are based on contextual interpretation, Large Language Models (LLMs) can be integrated to present users with additional rationales to consider. The diversity of these rationales is mediated by…

人机交互 · 计算机科学 2025-02-21 Paula Akemi Aoyagui , Kelsey Stemmler , Sharon Ferguson , Young-ho Kim , Anastasia Kuzminykh

Large language models (LLMs) are trained on vast amounts of data to generate natural language, enabling them to perform tasks like text summarization and question answering. These models have become popular in artificial intelligence (AI)…

Recent advances in Large Language Models (LLMs) highlight the need to align their behaviors with human values. A critical, yet understudied, issue is the potential divergence between an LLM's stated preferences (its reported alignment with…

人工智能 · 计算机科学 2025-06-03 Zhuojun Gu , Quan Wang , Shuchu Han

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) have revolutionized the field of natural language processing, enabling remarkable progress in various tasks. Different from objective tasks such as commonsense reasoning and arithmetic question-answering, the…

计算与语言 · 计算机科学 2025-06-19 Xiaolong Wang , Yuanchi Zhang , Ziyue Wang , Yuzhuang Xu , Fuwen Luo , Yile Wang , Peng Li , Yang Liu

Large Language Models (LLMs) have shown strong performance across many tasks, but their ability to capture culturally diverse moral values remains unclear. In this paper, we examine whether LLMs mirror variations in moral attitudes reported…

计算与语言 · 计算机科学 2026-03-31 Hadi Mohammadi , Ayoub Bagheri

Recent research has focused on examining Large Language Models' (LLMs) characteristics from a psychological standpoint, acknowledging the necessity of understanding their behavioral characteristics. The administration of personality tests…

计算与语言 · 计算机科学 2024-10-07 Jen-tse Huang , Wenxiang Jiao , Man Ho Lam , Eric John Li , Wenxuan Wang , Michael R. Lyu

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) are a transformational technology, fundamentally changing how people obtain information and interact with the world. As people become increasingly reliant on them for an enormous variety of tasks, a body of…

计算机与社会 · 计算机科学 2025-05-08 Nouar Aldahoul , Hazem Ibrahim , Matteo Varvello , Aaron Kaufman , Talal Rahwan , Yasir Zaki

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

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

Investigating value alignment in Large Language Models (LLMs) based on cultural context has become a critical area of research. However, similar biases have not been extensively explored in large vision-language models (VLMs). As the scale…

计算与语言 · 计算机科学 2025-02-24 Srishti Yadav , Zhi Zhang , Daniel Hershcovich , Ekaterina Shutova

Collecting diverse human opinions is costly and challenging. This leads to a recent trend in exploiting large language models (LLMs) for generating diverse data for potential scalable and efficient solutions. However, the extent to which…

计算与语言 · 计算机科学 2024-10-15 Shirley Anugrah Hayati , Minhwa Lee , Dheeraj Rajagopal , Dongyeop Kang

The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, enabling fully-automated, personalized, and interactive content generation at an unprecedented scale. In this paper, we…

计算与语言 · 计算机科学 2026-04-22 Sander Noels , Alexander Rogiers , Maarten Buyl , Tijl De Bie

Human problem-solving is enriched by a diversity of styles and personality traits, yet the development of Large Language Models (LLMs) has largely prioritized uniform performance benchmarks that favour specific behavioural tendencies such…

计算与语言 · 计算机科学 2026-03-09 Xi Wang , Mengdie Zhuang , Jiqun Liu

Large language models (LLMs) generate diverse, situated, persuasive texts from a plurality of potential perspectives, influenced heavily by their prompts and training data. As part of LLM adoption, we seek to characterize - and ideally,…

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