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相关论文: Exploring Large Language Models on Cross-Cultural …

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Ensuring that Large Language Models (LLMs) align with the diverse and evolving human values across different regions and cultures remains a critical challenge in AI ethics. Current alignment approaches often yield superficial conformity…

人工智能 · 计算机科学 2025-11-04 Jiahao Wang , Songkai Xue , Jinghui Li , Xiaozhen Wang

Large Language Models (LLMs) have shown remarkable advancements but also raise concerns about cultural bias, often reflecting dominant narratives at the expense of under-represented subcultures. In this study, we evaluate the capacity of…

计算与语言 · 计算机科学 2025-09-09 Garima Chhikara , Abhishek Kumar , Abhijnan Chakraborty

As a socio-technical activity, software development involves the close interconnection of people and technology. The integration of Large Language Models (LLMs) into this process exemplifies the socio-technical nature of software…

软件工程 · 计算机科学 2024-09-10 Stefano Lambiase , Gemma Catolino , Fabio Palomba , Filomena Ferrucci , Daniel Russo

Probing techniques for large language models (LLMs) have primarily focused on English, overlooking the vast majority of the world's languages. In this paper, we extend these probing methods to a multilingual context, investigating the…

计算与语言 · 计算机科学 2025-02-03 Daoyang Li , Haiyan Zhao , Qingcheng Zeng , Mengnan Du

Large language models (LLMs) are increasingly used across diverse cultural contexts, making accurate cultural understanding essential. Prior evaluations have mostly focused on output-level performance, obscuring the factors that drive…

计算与语言 · 计算机科学 2025-11-12 Seungho Cho , Changgeon Ko , Eui Jun Hwang , Junmyeong Lee , Huije Lee , Jong C. Park

Large Language Models (LLMs) have shown powerful performance and development prospects and are widely deployed in the real world. However, LLMs can capture social biases from unprocessed training data and propagate the biases to downstream…

计算与语言 · 计算机科学 2024-02-22 Yingji Li , Mengnan Du , Rui Song , Xin Wang , Ying Wang

Despite their global prevalence, many Large Language Models (LLMs) are aligned to a monolithic, often Western-centric set of values. This paper investigates the more challenging task of fine-grained value alignment: examining whether LLMs…

计算机与社会 · 计算机科学 2026-04-15 Bryan Chen Zhengyu Tan , Zhengyuan Liu , Xiaoyuan Yi , Jing Yao , Xing Xie , Nancy F. Chen , Roy Ka-Wei Lee

Large Language Models (LLMs) demonstrate a remarkable capacity to adopt different personas and roles; however, it remains unclear whether they can manifest behavior that adheres to a coherent, human-like value structure. In this work, we…

人工智能 · 计算机科学 2026-05-29 Asaf Yehudai , Naama Rozen , Ariel Gera

Numerous recent studies have shown that Large Language Models (LLMs) are biased towards a Western and Anglo-centric worldview, which compromises their usefulness in non-Western cultural settings. However, "culture" is a complex,…

计算机与社会 · 计算机科学 2025-02-17 Sougata Saha , Saurabh Kumar Pandey , Monojit Choudhury

Large language models (LLMs) have rapidly become indispensable tools for acquiring information and supporting human decision-making. However, ensuring that these models uphold fairness across varied contexts is critical to their safe and…

计算机与社会 · 计算机科学 2026-03-05 Xulang Zhang , Rui Mao , Erik Cambria

Although Large Language Models (LLMs) demonstrate strong capabilities across various tasks, they exhibit significant performance discrepancies across languages. While prompting LLMs in English typically yields the highest general…

计算与语言 · 计算机科学 2026-05-26 Andrew Ivan Soegeng , Patrick Sutanto , Tan Sang Nguyen

Large language models (LLMs) are often described as multilingual because they can understand and respond in many languages. However, speaking a language is not the same as reasoning within a culture. This distinction motivates a critical…

计算与语言 · 计算机科学 2026-04-07 Yuan Chang , Jiaming Qu , Zhu Li

Although the cultural (mis)alignment of Large Language Models (LLMs) has attracted increasing attention -- often framed in terms of cultural bias -- until recently there has been limited work on the design and development of datasets for…

Massively multilingual sentence representations are trained on large corpora of uncurated data, with a very imbalanced proportion of languages included in the training. This may cause the models to grasp cultural values including moral…

Large Language Models (LLMs) are advancing quickly and impacting people's lives for better or worse. In higher education, concerns have emerged such as students' misuse of LLMs and degraded education outcomes. To unpack the ethical concerns…

The growing interest in employing large language models (LLMs) for decision-making in social and economic contexts has raised questions about their potential to function as agents in these domains. A significant number of societal problems…

计算机科学与博弈论 · 计算机科学 2025-11-25 Hadi Hosseini , Samarth Khanna

Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent responses to various prompts or queries. These models far exceed the complexity of conventional neural…

机器学习 · 计算机科学 2024-12-05 Minghao Shao , Abdul Basit , Ramesh Karri , Muhammad Shafique

This paper provides a comprehensive survey of the latest research on multilingual large language models (MLLMs). MLLMs not only are able to understand and generate language across linguistic boundaries, but also represent an important…

计算与语言 · 计算机科学 2024-11-20 Shaolin Zhu , Supryadi , Shaoyang Xu , Haoran Sun , Leiyu Pan , Menglong Cui , Jiangcun Du , Renren Jin , António Branco , Deyi Xiong

As Large Language Models (LLMs) achieve remarkable breakthroughs, aligning their values with humans has become imperative for their responsible development and customized applications. However, there still lack evaluations of LLMs values…

人工智能 · 计算机科学 2025-06-03 Jing Yao , Xiaoyuan Yi , Shitong Duan , Jindong Wang , Yuzhuo Bai , Muhua Huang , Peng Zhang , Tun Lu , Zhicheng Dou , Maosong Sun , Xing Xie

Large language models (LLMs) increasingly operate in environments where they encounter social information such as other agents' answers, tool outputs, or human recommendations. In humans, such inputs influence judgments in ways that depend…

人工智能 · 计算机科学 2026-02-17 Anooshka Bajaj , Zoran Tiganj