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相关论文: Moral Mimicry: Large Language Models Produce Moral…

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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)…

Large Language Models (LLMs) have become increasingly incorporated into everyday life for many internet users, taking on significant roles as advice givers in the domains of medicine, personal relationships, and even legal matters. The…

计算与语言 · 计算机科学 2025-10-17 Nicole Smith-Vaniz , Harper Lyon , Lorraine Steigner , Ben Armstrong , Nicholas Mattei

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

Recently, computer scientists have developed large language models (LLMs) by training prediction models with large-scale language corpora and human reinforcements. The LLMs have become one promising way to implement artificial intelligence…

计算机与社会 · 计算机科学 2023-08-22 Hyemin Han

Moral foundations theory (MFT) is a psychological assessment tool that decomposes human moral reasoning into five factors, including care/harm, liberty/oppression, and sanctity/degradation (Graham et al., 2009). People vary in the weight…

人工智能 · 计算机科学 2023-10-25 Marwa Abdulhai , Gregory Serapio-Garcia , Clément Crepy , Daria Valter , John Canny , Natasha Jaques

Recent advancements in large language models (LLMs) have established them as powerful tools across numerous domains. However, persistent concerns about embedded biases, such as gender, racial, and cultural biases arising from their training…

计算与语言 · 计算机科学 2025-07-30 Hadi Mohammadi , Yasmeen F. S. S. Meijer , Efthymia Papadopoulou , Ayoub Bagheri

Large language models (LLMs) have demonstrated their potential in social science research by emulating human perceptions and behaviors, a concept referred to as algorithmic fidelity. This study assesses the algorithmic fidelity and bias of…

人工智能 · 计算机科学 2024-08-09 S. Lee , T. Q. Peng , M. H. Goldberg , S. A. Rosenthal , J. E. Kotcher , E. W. Maibach , A. Leiserowitz

As large language models (LLMs) become more deeply integrated into various sectors, understanding how they make moral judgments has become crucial, particularly in the realm of autonomous driving. This study utilized the Moral Machine…

计算与语言 · 计算机科学 2024-02-08 Kazuhiro Takemoto

Large language models (LLMs) have become integral tools in diverse domains, yet their moral reasoning capabilities across cultural and linguistic contexts remain underexplored. This study investigates whether multilingual LLMs, such as…

计算与语言 · 计算机科学 2024-12-30 Meltem Aksoy

Self-correction is one of the most amazing emerging capabilities of Large Language Models (LLMs), enabling LLMs to self-modify an inappropriate output given a natural language feedback which describes the problems of that output. Moral…

计算与语言 · 计算机科学 2025-03-04 Guangliang Liu , Zhiyu Xue , Xitong Zhang , Rongrong Wang , Kristen Marie Johnson

Large language models (LLMs) have become increasingly pivotal in various domains due the recent advancements in their performance capabilities. However, concerns persist regarding biases in LLMs, including gender, racial, and cultural…

人工智能 · 计算机科学 2024-12-03 Mijntje Meijer , Hadi Mohammadi , Ayoub Bagheri

Large language models (LLMs) exhibit expert-level performance in tasks across a wide range of different domains. Ethical issues raised by LLMs and the need to align future versions makes it important to know how state of the art models…

Large Language Models (LLMs) represent a major step toward artificial general intelligence, significantly advancing our ability to interact with technology. While LLMs perform well on Natural Language Processing tasks -- such as…

计算与语言 · 计算机科学 2025-05-15 Brandon Smith , Mohamed Reda Bouadjenek , Tahsin Alamgir Kheya , Phillip Dawson , Sunil Aryal

As large language models (LLMs) increasingly participate in tasks with ethical and societal stakes, a critical question arises: do they exhibit an emergent "moral mind" - a consistent structure of moral preferences guiding their decisions -…

计算机与社会 · 计算机科学 2025-04-28 Avner Seror

We test whether Large Language Models (LLMs) can be used to simulate human participants in social-science studies. To do this, we run replications of 14 studies from the Many Labs 2 replication project with OpenAI's text-davinci-003 model,…

人机交互 · 计算机科学 2023-09-14 Peter S. Park , Philipp Schoenegger , Chongyang Zhu

As large language models (LLMs) increasingly participate in high-stakes decision-making, a central societal debate has revolved around which moral frameworks-deontological or utilitarian-should guide machine behavior. However, a largely…

计算机与社会 · 计算机科学 2026-04-14 Pengzhao Lyu , Yeun Joon Kim , Yingyue Luna Luan , Jungmin Choi

We explore how large language models (LLMs) can be influenced by prompting them to alter their initial decisions and align them with established ethical frameworks. Our study is based on two experiments designed to assess the susceptibility…

计算与语言 · 计算机科学 2024-11-19 Allison Huang , Yulu Niki Pi , Carlos Mougan

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 become central to advancing automation and decision-making across various sectors, raising significant ethical questions. This study proposes a comprehensive comparative analysis of the most advanced LLMs…

人工智能 · 计算机科学 2024-06-07 Alejandro Tlaie

Modern AI technology like Large language models (LLMs) has the potential to pollute the public information sphere with made-up content, which poses a significant threat to the cohesion of societies at large. A wide range of research has…

计算与语言 · 计算机科学 2024-07-19 Steffen Herbold , Alexander Trautsch , Zlata Kikteva , Annette Hautli-Janisz
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