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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) have demonstrated great potential for domain-specific applications, such as the law domain. However, recent disputes over GPT-4's law evaluation raise questions concerning their performance in real-world legal…

计算与语言 · 计算机科学 2023-10-19 Ruihao Shui , Yixin Cao , Xiang Wang , Tat-Seng Chua

There is an increasing interest in leveraging Large Language Models (LLMs) for managing structured data and enhancing data science processes. Despite the potential benefits, this integration poses significant questions regarding their…

人工智能 · 计算机科学 2023-11-21 Nathalia Nascimento , Cristina Tavares , Paulo Alencar , Donald Cowan

Large Language Models (LLMs) could be a useful tool for lawyers. However, empirical research on their effectiveness in conducting legal tasks is scant. We study securities cases involving cryptocurrencies as one of numerous contexts where…

人工智能 · 计算机科学 2024-02-23 Arianna Trozze , Toby Davies , Bennett Kleinberg

In the fast-evolving domain of artificial intelligence, large language models (LLMs) such as GPT-3 and GPT-4 are revolutionizing the landscapes of finance, healthcare, and law: domains characterized by their reliance on professional…

In this paper, we explore the challenges inherent to Large Language Models (LLMs) like GPT-4, particularly their propensity for hallucinations, logic mistakes, and incorrect conclusions when tasked with answering complex questions. The…

计算与语言 · 计算机科学 2023-12-22 Xiang Li , Haoran Tang , Siyu Chen , Ziwei Wang , Anurag Maravi , Marcin Abram

Formal logic enables computers to reason in natural language by representing sentences in symbolic forms and applying rules to derive conclusions. However, in what our study characterizes as "rulebreaker" scenarios, this method can lead to…

计算与语言 · 计算机科学 2025-08-18 Jason Chan , Robert Gaizauskas , Zhixue Zhao

In this study, we investigate the capabilities and inherent biases of advanced large language models (LLMs) such as GPT-3.5 and GPT-4 in the context of debate evaluation. We discover that LLM's performance exceeds humans and surpasses the…

计算与语言 · 计算机科学 2024-06-05 Xinyi Liu , Pinxin Liu , Hangfeng He

Encoding legislative text in a formal representation is an important prerequisite to different tasks in the field of AI & Law. For example, rule-based expert systems focused on legislation can support laypeople in understanding how…

计算与语言 · 计算机科学 2023-11-10 Samyar Janatian , Hannes Westermann , Jinzhe Tan , Jaromir Savelka , Karim Benyekhlef

In this position paper, we argue that instead of morally aligning LLMs to specific set of ethical principles, we should infuse generic ethical reasoning capabilities into them so that they can handle value pluralism at a global scale. When…

计算与语言 · 计算机科学 2023-10-12 Abhinav Rao , Aditi Khandelwal , Kumar Tanmay , Utkarsh Agarwal , Monojit Choudhury

Large language models (LLMs) such as ChatGPT are increasingly integrated into high-stakes decision-making, yet little is known about their susceptibility to social influence. We conducted three preregistered conformity experiments with…

人工智能 · 计算机科学 2025-10-31 Clarissa Sabrina Arlinghaus , Tristan Kenneweg , Barbara Hammer , Günter W. Maier

Robots are increasingly common in industry and daily life, such as in nursing homes where they can assist staff. A key challenge is developing intuitive interfaces for easy communication. The use of Large Language Models (LLMs) like GPT-4…

机器人学 · 计算机科学 2024-08-01 Stanislau Stankevich , Wojciech Dudek

Interpreting the meaning of legal open-textured terms is a key task of legal professionals. An important source for this interpretation is how the term was applied in previous court cases. In this paper, we evaluate the performance of GPT-4…

计算与语言 · 计算机科学 2023-06-23 Jaromir Savelka , Kevin D. Ashley , Morgan A. Gray , Hannes Westermann , Huihui Xu

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) are increasingly used to generate user-tailored summaries, adapting outputs to specific stakeholders. In legal contexts, this raises important questions about motivated reasoning -- how models strategically…

计算与语言 · 计算机科学 2025-10-10 Eunjung Cho , Alexander Hoyle , Yoan Hermstrüwer

One open question in the study of Large Language Models (LLMs) is whether they can emulate human ethical reasoning and act as believable proxies for human judgment. To investigate this, we introduce a benchmark dataset comprising 196…

计算与语言 · 计算机科学 2025-05-14 Jiashen , Du , Jesse Yao , Allen Liu , Zhekai Zhang

Large language models (LLMs) are currently at the forefront of intertwining AI systems with human communication and everyday life. Therefore, it is of great importance to evaluate their emerging abilities. In this study, we show that LLMs,…

计算与语言 · 计算机科学 2023-10-10 Thilo Hagendorff , Sarah Fabi

Recent advances in the performance of large language models (LLMs) have sparked debate over whether, given sufficient training, high-level human abilities emerge in such generic forms of artificial intelligence (AI). Despite the exceptional…

计算与语言 · 计算机科学 2024-01-18 Nicholas Ichien , Dušan Stamenković , Keith J. Holyoak

Large Language Models (LLMs) have lately been on the spotlight of researchers, businesses, and consumers alike. While the linguistic capabilities of such models have been studied extensively, there is growing interest in investigating them…

计算与语言 · 计算机科学 2023-08-17 Sotiris Lamprinidis

Better understanding of Large Language Models' (LLMs) legal analysis abilities can contribute to improving the efficiency of legal services, governing artificial intelligence, and leveraging LLMs to identify inconsistencies in law. This…

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