Imitation and Large Language Models DOI
Éloïse Boisseau

Minds and Machines, Год журнала: 2024, Номер 34(4)

Опубликована: Окт. 9, 2024

Язык: Английский

Mapping the Ethics of Generative AI: A Comprehensive Scoping Review DOI Creative Commons
Thilo Hagendorff

Minds and Machines, Год журнала: 2024, Номер 34(4)

Опубликована: Сен. 17, 2024

Язык: Английский

Процитировано

13

Exploring the role of large language models in radiation emergency response DOI Creative Commons
Anirudh Chandra, Abinash Chakraborty

Journal of Radiological Protection, Год журнала: 2024, Номер 44(1), С. 011510 - 011510

Опубликована: Фев. 7, 2024

Abstract In recent times, the field of artificial intelligence (AI) has been transformed by introduction large language models (LLMs). These models, popularized OpenAI’s GPT-3, have demonstrated emergent capabilities AI in comprehending and producing text resembling human language, which helped them transform several industries. But its role yet to be explored nuclear industry, specifically managing radiation emergencies. The present work explores LLMs’ contextual awareness, natural interaction, their capacity comprehend diverse queries a emergency response setting. this study we identify different user types specific LLM use-cases Their possible interactions with ChatGPT, popular LLM, also simulated preliminary results are presented. Drawing on insights gained from exercise address concerns reliability misinformation, advocates for expert guided domain-specific LLMs trained safety protocols historical data. This aims guide management practitioners decision-makers effectively incorporating into decision support framework.

Язык: Английский

Процитировано

6

The Impact of Artificial Intelligence on Cyber Security in Digital Currency Transactions DOI

Adekunbi Justina Ajayi,

Sunday Abayomi Joseph,

Olufunke Cynthia Metibemu

и другие.

SSRN Electronic Journal, Год журнала: 2025, Номер unknown

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

0

Exploring AI Text Generation, Retrieval-Augmented Generation, and Detection Technologies: a Comprehensive Overview DOI
Fnu Neha, Deepshikha Bhati,

Deepak Kumar Shukla

и другие.

2022 IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC), Год журнала: 2025, Номер unknown, С. 00633 - 00639

Опубликована: Янв. 6, 2025

Язык: Английский

Процитировано

0

Investigating How Computer Science Researchers Design Their Co-Writing Experiences With AI DOI
Alberto Monge Roffarello, Tommaso Calò, Luca Scibetta

и другие.

Опубликована: Апрель 24, 2025

Язык: Английский

Процитировано

0

Revisión sistemática de taxonomías de riesgos asociados a la Inteligencia Artificial DOI Creative Commons

Guillem Bas Graells,

Roberto Tinoco Devia,

Claudette Salinas Leyva

и другие.

Analecta política, Год журнала: 2024, Номер 14(26)

Опубликована: Янв. 1, 2024

Este artículo realiza una revisión sistemática de treinta y seis taxonomías riesgos asociados a la Inteligencia Artificial (IA) que se han realizado desde el 2010 hasta fecha, utilizando como metodología protocolo Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). El estudio basa en importancia estas para estructurar investigación los distinguir definir amenazas. Ello permite identificar las cuestiones generan mayor preocupación y, por lo tanto, requieren mejor gobernanza. La extraer tres conclusiones. En primer lugar, observa mayoría estudios centran amenazas privacidad desinformación, posiblemente debido su concreción evidencia empírica existente. Por contrario, ciberataques desarrollo tecnologías estratégicas son menos citadas, pesar creciente relevancia. segundo encontramos artículos enfocados origen del riesgo tienden considerar más frecuentemente extremos comparación con trabajos abordan consecuencias. Esto sugiere literatura ha sabido potenciales causas catástrofe, pero no formas concretas esta puede materializar práctica. Finalmente, existe cierta división entre aquellos tratan daños tangibles presentes cubren futuros. No obstante, varias todo espectro indicando existen puntos unión clústeres.

Процитировано

3

LLMs in Automated Essay Evaluation: A Case Study DOI Open Access

Milan Kostic,

Hans Friedrich Witschel, Knut Hinkelmann

и другие.

Proceedings of the AAAI Symposium Series, Год журнала: 2024, Номер 3(1), С. 143 - 147

Опубликована: Май 20, 2024

This study delves into the application of large language models (LLMs), such as ChatGPT-4, for automated evaluation student essays, with a focus on case conducted at Swiss Institute Business Administration. It explores effectiveness LLMs in assessing German-language transfer assignments, and contrasts their performance traditional evaluations by human lecturers. The primary findings highlight challenges faced terms accurately grading complex texts according to predefined categories providing detailed feedback. research illuminates gap between capabilities nuanced requirements essay evaluation. conclusion emphasizes necessity ongoing development area LLM technology improve accuracy, reliability, consistency assessments educational contexts.

Язык: Английский

Процитировано

2

Imitation and Large Language Models DOI
Éloïse Boisseau

Minds and Machines, Год журнала: 2024, Номер 34(4)

Опубликована: Окт. 9, 2024

Язык: Английский

Процитировано

0