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相关论文: Diagnosing Moral Reasoning Acquisition in Language…

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Moral sensitivity is the most fundamental capability underlying human moral competence. Although many approaches aim to align large language models (LLMs) with human moral values, they primarily focus on fitting the distributions of morally…

计算与语言 · 计算机科学 2026-05-27 Bocheng Chen , Xi Chen , Han Zi , Haitao Mao , Zimo Qi , Xitong Zhang , Kristen Johnson , Guangliang Liu

While moral reasoning has emerged as a promising research direction for large language models (LLMs), achieving robust generalization remains a critical challenge. This challenge arises from the gap between what is said and what is morally…

计算与语言 · 计算机科学 2026-02-17 Guangliang Liu , Xi Chen , Bocheng Chen , Xitong Zhang , Kristen Johnson

Large language models are increasingly influencing human moral decisions, yet current approaches focus primarily on evaluating rather than actively steering their moral decisions. We formulate this as an out-of-distribution moral alignment…

人工智能 · 计算机科学 2025-11-18 Zhiyu An , Wan Du

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

Large language models (LLMs) are increasingly deployed in domains requiring moral understanding, yet their reasoning often remains shallow, and misaligned with human reasoning. Unlike humans, whose moral reasoning integrates contextual…

人机交互 · 计算机科学 2025-06-19 Mohna Chakraborty , Lu Wang , David Jurgens

In the rapidly evolving field of artificial intelligence, large language models (LLMs) have emerged as powerful tools for a myriad of applications, from natural language processing to decision-making support systems. However, as these…

计算与语言 · 计算机科学 2025-07-08 Jianchao Ji , Yutong Chen , Mingyu Jin , Wujiang Xu , Wenyue Hua , Yongfeng Zhang

Evaluating pragmatic reasoning in large language models (LLMs) remains challenging because model behavior can vary depending on evaluation methods. Previous studies suggest that prompt-based judgments may diverge from models' internal…

计算与语言 · 计算机科学 2026-05-12 Ye-eun Cho

Current Large Language Models (LLMs) are unparalleled in their ability to generate grammatically correct, fluent text. LLMs are appearing rapidly, and debates on LLM capacities have taken off, but reflection is lagging behind. Thus, in this…

计算与语言 · 计算机科学 2023-11-01 Bram M. A. van Dijk , Tom Kouwenhoven , Marco R. Spruit , Max J. van Duijn

Large Language Models (LLMs) are increasingly deployed in multilingual and multicultural environments where moral reasoning is essential for generating ethically appropriate responses. Yet, the dominant pretraining of LLMs on…

计算与语言 · 计算机科学 2025-09-29 Sualeha Farid , Jayden Lin , Zean Chen , Shivani Kumar , David Jurgens

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

This study establishes a novel framework for systematically evaluating the moral reasoning capabilities of large language models (LLMs) as they increasingly integrate into critical societal domains. Current assessment methodologies lack the…

计算机与社会 · 计算机科学 2025-05-05 Junfeng Jiao , Saleh Afroogh , Abhejay Murali , Kevin Chen , David Atkinson , Amit Dhurandhar

Reasoning is a fundamental aspect of human intelligence that plays a crucial role in activities such as problem solving, decision making, and critical thinking. In recent years, large language models (LLMs) have made significant progress in…

计算与语言 · 计算机科学 2023-05-29 Jie Huang , Kevin Chen-Chuan Chang

As large language models (LLMs) increasingly mediate ethically sensitive decisions, understanding their moral reasoning processes becomes imperative. This study presents a comprehensive empirical evaluation of 14 leading LLMs, both…

计算与语言 · 计算机科学 2025-08-12 Junchen Ding , Penghao Jiang , Zihao Xu , Ziqi Ding , Yichen Zhu , Jiaojiao Jiang , Yuekang Li

The performance of Large language models (LLMs) across a broad range of domains has been impressive but have been critiqued as not being able to reason about their process and conclusions derived. This is to explain the conclusions draw,…

计算与语言 · 计算机科学 2024-10-30 Rob Sullivan , Nelly Elsayed

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

Do large language models reason morally, or do they merely sound like they do? We investigate whether LLM responses to moral dilemmas exhibit genuine developmental progression through Kohlberg's stages of moral development, or whether…

人工智能 · 计算机科学 2026-03-24 Aryan Kasat , Smriti Singh , Aman Chadha , Vinija Jain

Large Language Models (LLMs) have succeeded remarkably in various natural language processing (NLP) tasks, yet their reasoning capabilities remain a fundamental challenge. While LLMs exhibit impressive fluency and factual recall, their…

计算与语言 · 计算机科学 2025-05-29 Avinash Patil , Aryan Jadon

The recent rise in popularity of large language models (LLMs) has prompted considerable concerns about their moral capabilities. Although considerable effort has been dedicated to aligning LLMs with human moral values, existing benchmarks…

人工智能 · 计算机科学 2025-08-19 Alessio Galatolo , Luca Alberto Rappuoli , Katie Winkle , Meriem Beloucif

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

We present an ethical decision-making framework that refines a pre-trained reinforcement learning (RL) model using a task-agnostic ethical layer. Following initial training, the RL model undergoes ethical fine-tuning, where human feedback…

计算机与社会 · 计算机科学 2026-05-05 Rohit K. Dubey , Damian Dailisan , Sachit Mahajan
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