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Large Language Models are Not Models of Natural Language: They are Corpus Models

IEEE Access, 2022
Natural Language Processing (NLP) has become one of the leading application areas in the current Artificial Intelligence boom. Transfer learning has enabled large deep learning neural networks trained on the language modeling task to vastly improve ...
Csaba Veres
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Large language models for bioinformatics

Quantitative Biology
With the rapid advancements in large language model technology and the emergence of bioinformatics‐specific language models (BioLMs), there is a growing need for a comprehensive analysis of the current landscape, computational characteristics, and ...
Wei Ruan, Yanjun Lyu, Jing Zhang, Jiazhang Cai, Peng Shu, Yang Ge, Yao Lu, Shang Gao, Yue Wang, Peilong Wang, Lin Zhao, Tao Wang, Yufang Liu, Luyang Fang, Ziyu Liu, Zhengliang Liu, Yiwei Li, Zihao Wu, Junhao Chen, Hanqi Jiang, Yi Pan, Zhenyuan Yang, Jingyuan Chen, Shizhe Liang, Wei Zhang, Terry Ma, Yuan Dou, Jianli Zhang, Xinyu Gong, Qi Gan, Yusong Zou, Zebang Chen, Yuanxin Qian, Shuo Yu, Jin Lu, Kenan Song, Xianqiao Wang, Andrea Sikora, Gang Li, Xiang Li, Quanzheng Li, Yingfeng Wang, Lu Zhang, Yohannes Abate, Lifang He, Wenxuan Zhong, Rongjie Liu, Chao Huang, Wei Liu, Ye Shen, Ping Ma, Hongtu Zhu, Yajun Yan, Dajiang Zhu, Tianming Liu   +54 more
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Large Language Models

NEJM Evidence, 2023
Large Language ModelsIn the latest edition of Stats, STAT!, Fralick and colleagues explain the statistics behind large language models - used in chat bots like ChatGPT and Bard. While these new tools may seem remarkably intelligent, at their core they just assemble sentences based on statistics from large amounts of text.
Michael, Fralick, Chana A, Sacks, Daniel, Muller, Tim, Vining, Emily, Ling, Jeffrey M, Drazen, C Corey, Hardin   +6 more
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Large Language Models in Ophthalmology: A Bibliographic Analysis [PDF]

Türk Oftalmoloji Dergisi
This study evaluated the distribution of research on the use of large language models (LLMs) in ophthalmology through a bibliographic analysis of articles retrieved from PubMed through November 2024.
Neslihan Dilruba Köseoğlu, T.Y. Alvin Liu   +1 more
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Large Language Models in Medicine [PDF]

Healthcare Informatics Research
Jinwook Choi
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Knowledge Engineering Using Large Language Models [PDF]

Transactions on Graph Data and Knowledge, 2023
Knowledge engineering is a discipline that focuses on the creation and maintenance of processes that generate and apply knowledge. Traditionally, knowledge engineering approaches have focused on knowledge expressed in formal languages.
Allen, Bradley P., Stork, Lise, Groth, Paul   +2 more
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Autoformalization with Large Language Models

Advances in Neural Information Processing Systems 35, 2022
Autoformalization is the process of automatically translating from natural language mathematics to formal specifications and proofs. A successful autoformalization system could advance the fields of formal verification, program synthesis, and artificial intelligence.
Wu, Yuhuai, Jiang, Qiaochu, Li, Wenda, Rabe, Markus, Staats, Charles, Jamnik, Mateja, Szegedy, Christian   +6 more
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Can large language models write reflectively

Computers and Education: Artificial Intelligence, 2023
Generative Large Language Models (LLMs) demonstrate impressive results in different writing tasks and have already attracted much attention from researchers and practitioners. However, there is limited research to investigate the capability of generative
Yuheng Li, Lele Sha, Lixiang Yan, Jionghao Lin, Mladen Raković, Kirsten Galbraith, Kayley Lyons, Dragan Gašević, Guanliang Chen   +8 more
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Emotional intelligence of Large Language Models

Journal of Pacific Rim Psychology, 2023
Large Language Models (LLMs) have demonstrated remarkable abilities across numerous disciplines, primarily assessed through tasks in language generation, knowledge utilization, and complex reasoning.
Xuena Wang, Xueting Li, Zi Yin, Yue Wu, Jia Liu   +4 more
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Large Language Models and Logical Reasoning

Encyclopedia, 2023
In deep learning, large language models are typically trained on data from a corpus as representative of current knowledge. However, natural language is not an ideal form for the reliable communication of concepts.
Robert Friedman
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