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This study seeks to uncover evidence of a latent structure in evolved human culture as it is refracted through contemporary large language models (LLMs). Drawing on parallel responses from six leading generative models to a prompt which…

计算机与社会 · 计算机科学 2026-04-09 W. Russell Neuman

Large Language Models (LLMs) offer the potential to automate hiring by matching job descriptions with candidate resumes, streamlining recruitment processes, and reducing operational costs. However, biases inherent in these models may lead…

计算与语言 · 计算机科学 2025-03-26 Hayate Iso , Pouya Pezeshkpour , Nikita Bhutani , Estevam Hruschka

Existing behavioral alignment techniques for Large Language Models (LLMs) often neglect the discrepancy between surface compliance and internal unaligned representations, leaving LLMs vulnerable to long-tail risks. More crucially, we posit…

计算与语言 · 计算机科学 2026-03-17 Lingyu Li , Yan Teng , Yingchun Wang

Improving the alignment of Large Language Models (LLMs) with respect to the cultural values that they encode has become an increasingly important topic. In this work, we study whether we can exploit existing knowledge about cultural values…

计算与语言 · 计算机科学 2025-09-09 Rochelle Choenni , Ekaterina Shutova

The deployment of Large Language Models (LLMs) in real-world applications presents both opportunities and challenges, particularly in multilingual and code-mixed communication settings. This research evaluates the performance of seven…

Small and mid-sized generative language models have gained increasing attention. Their size and availability make them amenable to being analyzed at a behavioral as well as a representational level, allowing investigations of how these…

机器学习 · 计算机科学 2025-04-11 Lorenz Linhardt , Tom Neuhäuser , Lenka Tětková , Oliver Eberle

Large Language Models (LLMs) behave non-deterministically, and prompting has become a common method for steering their outputs. A popular strategy is to assign a persona to the model to produce more varied, context-sensitive responses,…

计算与语言 · 计算机科学 2026-04-21 Bruce W. Lee , Yeongheon Lee , Hyunsoo Cho

In day-to-day communication, people often approximate the truth - for example, rounding the time or omitting details - in order to be maximally helpful to the listener. How do large language models (LLMs) handle such nuanced trade-offs? To…

计算与语言 · 计算机科学 2024-02-14 Ryan Liu , Theodore R. Sumers , Ishita Dasgupta , Thomas L. Griffiths

This study examines the ethical reasoning of six prominent generative large language models: OpenAI GPT-4o, Meta LLaMA 3.1, Perplexity, Anthropic Claude 3.5 Sonnet, Google Gemini, and Mistral 7B. The research explores how these models…

人工智能 · 计算机科学 2025-01-16 W. Russell Neuman , Chad Coleman , Manan Shah

The success of Large Language Models (LLMs) in multicultural environments hinges on their ability to understand users' diverse cultural backgrounds. We measure this capability by having an LLM simulate human profiles representing various…

计算与语言 · 计算机科学 2024-08-14 Louis Kwok , Michal Bravansky , Lewis D. Griffin

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…

Large Language Models (LLMs) such as ChatGPT have shown remarkable abilities in producing human-like text. However, it is unclear how accurately these models internalize concepts that shape human thought and behavior. Here, we developed a…

机器学习 · 计算机科学 2025-07-01 Hiro Taiyo Hamada , Ippei Fujisawa , Genji Kawakita , Yuki Yamada

Large language models (LLMs) are increasingly being adopted in educational settings. These applications expand beyond English, though current LLMs remain primarily English-centric. In this work, we ascertain if their use in education…

计算与语言 · 计算机科学 2025-08-06 Vansh Gupta , Sankalan Pal Chowdhury , Vilém Zouhar , Donya Rooein , Mrinmaya Sachan

Human commonsense understanding of the physical and social world is organized around intuitive theories. These theories support making causal and moral judgments. When something bad happens, we naturally ask: who did what, and why? A rich…

计算与语言 · 计算机科学 2023-11-01 Allen Nie , Yuhui Zhang , Atharva Amdekar , Chris Piech , Tatsunori Hashimoto , Tobias Gerstenberg

Large Language Models (LLMs) have recently displayed their extraordinary capabilities in language understanding. However, how to comprehensively assess the sentiment capabilities of LLMs continues to be a challenge. This paper investigates…

计算与语言 · 计算机科学 2025-02-17 Yang Liu , Xichou Zhu , Zhou Shen , Yi Liu , Min Li , Yujun Chen , Benzi John , Zhenzhen Ma , Tao Hu , Zhi Li , Zhiyang Xu , Wei Luo , Junhui Wang

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

As Large Language Models (LLMs) are increasingly integrated into educational settings, understanding their potential biases is critical. This study examines sociodemographic biases in LLM-based educational counselling. We evaluate responses…

Large language models (LLMs) are increasingly used in robotics, especially for high-level action planning. Meanwhile, many robotics applications involve human supervisors or collaborators. Hence, it is crucial for LLMs to generate socially…

机器人学 · 计算机科学 2025-05-28 Lennart Wachowiak , Andrew Coles , Oya Celiktutan , Gerard Canal

Human decision-making belongs to the foundation of our society and civilization, but we are on the verge of a future where much of it will be delegated to artificial intelligence. The arrival of Large Language Models (LLMs) has transformed…

人工智能 · 计算机科学 2025-06-23 Hao Li , Gengrui Zhang , Petter Holme , Shuyue Hu , Zhen Wang

Recent advances in Large Language Models (LLMs) have enabled human-like responses across various tasks, raising questions about their ethical decision-making capabilities and potential biases. This study systematically evaluates how nine…

计算机与社会 · 计算机科学 2025-11-03 Wentao Xu , Yile Yan , Yuqi Zhu