Zobrazeno 1 - 10
of 703
pro vyhledávání: '"Large Language Models—LLMs"'
Autor:
Zhai, Xiaoming, editor, Krajcik, Joseph, editor
Externí odkaz:
https://doi.org/10.1093/oso/9780198882077.001.0001
Autor:
Harrison, Joseph S., author, Boivie, Steven, author, Hubbard, Timothy D., author, Petrenko, Oleg V., author
Publikováno v:
Delving Deep
Publikováno v:
Natural Hazards Research, Vol 4, Iss 4, Pp 669-688 (2024)
This communication presents a short review of chatbot technology and preliminary findings from comparing two recent chatbots, OpenAI’s ChatGPT and Google’s Bard, in the context of fire engineering by evaluating their responses in handling fire sa
Externí odkaz:
https://doaj.org/article/2d715d91fdc04aa6b1b6d9947dbfc0d2
Publikováno v:
Discover Artificial Intelligence, Vol 4, Iss 1, Pp 1-28 (2024)
Abstract Integrating Large Language Models (LLMs) with Knowledge Graphs (KGs) enhances the interpretability and performance of AI systems. This research comprehensively analyzes this integration, classifying approaches into three fundamental paradigm
Externí odkaz:
https://doaj.org/article/a83fc269d4354cafb92c8c8119b39a30
Publikováno v:
Journal of Informatics and Web Engineering, Vol 3, Iss 3, Pp 41-62 (2024)
This research work develops a new framework that combines patient feedback with evidence-based best practices across disease states to improve drug recommendations. It employs BERT as its free-text processing engine to deal with sentiment judgment an
Externí odkaz:
https://doaj.org/article/de3943b66bfd44ba86015d200ee87f64
Autor:
Giada Marino, Fabio Giglietto
Publikováno v:
Sociologica, Vol 18, Iss 2, Pp 87-107 (2024)
The integration of Large Language Models (LLMs) into research workflows has the potential to transform the study of political content on social media. This essay discusses a validation protocol addressing three key aspects of LLM-integrated research:
Externí odkaz:
https://doaj.org/article/8f540c7b57f74489992fdae3f9f163a8
Autor:
Ramya Tekumalla, Juan M. Banda
Publikováno v:
Genomics & Informatics, Vol 22, Iss 1, Pp 1-6 (2024)
Abstract Electronic phenotyping involves a detailed analysis of both structured and unstructured data, employing rule-based methods, machine learning, natural language processing, and hybrid approaches. Currently, the development of accurate phenotyp
Externí odkaz:
https://doaj.org/article/8b6ad65fdd3c42a7bc42282f67248cc0
Autor:
Di Zhou, Yinxian Zhang
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-13 (2024)
Abstract The growing popularity of ChatGPT and other large language models (LLMs) has led to many studies investigating their susceptibility to mistakes and biases. However, most studies have focused on models trained exclusively on English texts. Th
Externí odkaz:
https://doaj.org/article/c1f514a0dbaa44d1848e2b677b9f3772
Autor:
Ken Cheligeer, Guosong Wu, Alison Laws, May Lynn Quan, Andrea Li, Anne-Marie Brisson, Jason Xie, Yuan Xu
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 24, Iss 1, Pp 1-9 (2024)
Abstract Aims The primary goal of this study is to evaluate the capabilities of Large Language Models (LLMs) in understanding and processing complex medical documentation. We chose to focus on the identification of pathologic complete response (pCR)
Externí odkaz:
https://doaj.org/article/4e51dba5ce064e49aca9865aa0b02db1
Autor:
Joseph Millard, Alec P. Christie, Lynn V. Dicks, Justin E. Isip, Thomas F. Johnson, Grace Skinner, Rebecca Spake
Publikováno v:
Methods in Ecology and Evolution, Vol 15, Iss 10, Pp 1764-1766 (2024)
Abstract Large language models (LLM) have proved to be highly popular since the release of ChatGPT, leading many researchers to explore their potential across multiple fields of scientific research. In a recent Perspective, Cooper et al. (2024) highl
Externí odkaz:
https://doaj.org/article/363fe8fc751a40c5a08087bf566654f6