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The global economy is increasingly dependent on knowledge workers to meet the needs of public and private organizations. While there is no single definition of knowledge work, organizations and industry groups still attempt to measure…

计算与语言 · 计算机科学 2023-01-12 Jillian Bommarito , Michael Bommarito , Daniel Martin Katz , Jessica Katz

The research creates a professional certification survey to test large language models and evaluate their employable skills. It compares the performance of two AI models, GPT-3 and Turbo-GPT3.5, on a benchmark dataset of 1149 professional…

人工智能 · 计算机科学 2023-05-10 David Noever , Matt Ciolino

Using a novel professional certification survey, the study focuses on assessing the vocational skills of two highly cited AI models, GPT-3 and Turbo-GPT3.5. The approach emphasizes the importance of practical readiness over academic…

机器学习 · 计算机科学 2023-12-19 David Noever , Matt Ciolino

Can targeted user training unlock the productive potential of generative artificial intelligence in professional settings? We study this question using a randomized experiment in which 164 law students completed an issue-spotting…

计算机与社会 · 计算机科学 2026-04-01 Benjamin M. Chen , Hong Bao

Following the hype around OpenAI's ChatGPT conversational agent, the last straw in the recent development of Large Language Models (LLMs) that demonstrate emergent unprecedented zero-shot capabilities, we audit the latest OpenAI's GPT-3.5…

计算与语言 · 计算机科学 2023-04-25 Ilias Chalkidis

The legal field already uses various large language models (LLMs) in actual applications, but their quantitative performance and reasons for it are underexplored. We evaluated several open-source and proprietary LLMs -- including…

计算机与社会 · 计算机科学 2025-09-12 Bhakti Khera , Rezvan Alamian , Pascal A. Scherz , Stephan M. Goetz

Large language models such as Open AI's Generative Pre-trained Transformer (GPT) models are proficient at answering questions, but their knowledge is confined to the information present in their training data. This limitation renders them…

计算与语言 · 计算机科学 2023-08-24 Saba Rahimi , Tucker Balch , Manuela Veloso

Introduction: Recently, the effectiveness of Large Language Models (LLMs) has increased rapidly, allowing them to be used in a great number of applications. However, the risks posed by the generation of false information through LLMs…

计算与语言 · 计算机科学 2024-05-10 Jakub Pokrywka , Jeremi Kaczmarek , Edward Gorzelańczyk

The Plastic Surgery In-Service Training Exam (PSITE) is an important indicator of resident proficiency and serves as a useful benchmark for evaluating OpenAI's GPT. Unlike many of the simulated tests or practice questions shown in the GPT-4…

人工智能 · 计算机科学 2023-04-05 Jonathan D. Freedman , Ian A. Nappier

This paper reports the first documented instance of a language model achieving a perfect score on an officially disclosed Law School Admission Test (LSAT). Controlled experiments on eight reasoning models show that varying the prompt,…

人工智能 · 计算机科学 2026-04-14 Bonmu Ku

This case study investigates the task of job classification in a real-world setting, where the goal is to determine whether an English-language job posting is appropriate for a graduate or entry-level position. We explore multiple…

计算与语言 · 计算机科学 2023-04-19 Benjamin Clavié , Alexandru Ciceu , Frederick Naylor , Guillaume Soulié , Thomas Brightwell

Sudden access to the rapidly improving large language model GPT by open-ai forces educational institutions worldwide to revisit their exam procedures. In the pre-GPT era, we successfully applied oral and open-book home exams for two courses…

计算机与社会 · 计算机科学 2023-05-04 Felix Dobslaw , Peter Bergh

The rapid evolution of artificial intelligence (AI), especially in the domain of Large Language Models (LLMs) and generative AI, has opened new avenues for application across various fields, yet its role in business education remains…

计算与语言 · 计算机科学 2024-01-09 Vahid Ashrafimoghari , Necdet Gürkan , Jordan W. Suchow

We propose a comprehensive study of one-stage elicitation techniques for querying a large pre-trained generative transformer (GPT-3.5-turbo) in the rhetorical role prediction task of legal cases. This task is known as requiring textual…

计算与语言 · 计算机科学 2023-10-27 Anas Belfathi , Nicolas Hernandez , Laura Monceaux

Recent progress in large language models (LLMs) like GPT-4 and PaLM-2 has brought significant advancements in addressing math reasoning problems. In particular, OpenAI's latest version of GPT-4, known as GPT-4 Code Interpreter, shows…

计算与语言 · 计算机科学 2023-08-16 Aojun Zhou , Ke Wang , Zimu Lu , Weikang Shi , Sichun Luo , Zipeng Qin , Shaoqing Lu , Anya Jia , Linqi Song , Mingjie Zhan , Hongsheng Li

Automating the classification of negative treatment in legal precedent is a critical yet nuanced NLP task where misclassification carries significant risk. To address the shortcomings of standard accuracy, this paper introduces a more…

计算与语言 · 计算机科学 2026-05-19 M. Mikail Demir , M. Abdullah Canbaz

Despite the recent advances in Large Language Models, benchmarks for evaluating legal writing remain scarce due to the inherent complexity of assessing open-ended responses in this domain. One of the key challenges in evaluating language…

计算与语言 · 计算机科学 2025-05-01 Ramon Pires , Roseval Malaquias Junior , Rodrigo Nogueira

We find that the best publicly available LLMs like GPT-4 and Claude currently perform poorly on basic legal text handling. This motivates the creation of a benchmark consisting of examples that lawyers and paralegals would expect LLMs to…

计算与语言 · 计算机科学 2024-10-18 Andrew Blair-Stanek , Nils Holzenberger , Benjamin Van Durme

Large Language Models (LLMs) have exhibited remarkable performance on various Natural Language Processing (NLP) tasks. However, there is a current hot debate regarding their reasoning capacity. In this paper, we examine the performance of…

As large language models (LLMs) advance, their role in higher education, particularly in free-response problem-solving, requires careful examination. This study assesses the performance of GPT-4o and o1-preview under realistic educational…

计算机与社会 · 计算机科学 2025-05-21 Ming Ding , Rasmus Kyng , Federico Solda , Weixuan Yuan
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