Results 1 to 10 of about 6,156,320 (380)

A Survey of Large Language Models [PDF]

arXiv.org, 2023
Language is essentially a complex, intricate system of human expressions governed by grammatical rules. It poses a significant challenge to develop capable AI algorithms for comprehending and grasping a language.
Chen, Yushuo, Chen, Zhipeng, Dong, Zican, Du, Yifan, Hou, Yupeng, Jiang, Jinhao, Li, Junyi, Li, Yifan, Liu, Peiyu, Liu, Zikang, Min, Yingqian, Nie, Jian-Yun, Ren, Ruiyang, Tang, Tianyi, Tang, Xinyu, Wang, Xiaolei, Wen, Ji-Rong, Yang, Chen, Zhang, Beichen, Zhang, Junjie, Zhao, Wayne Xin, Zhou, Kun   +21 more
core   +3 more sources

Large Language Models

NEJM Evidence, 2023
Artificial intelligence is making spectacular progress, and one of the best examples is the development of large language models (LLMs) such as OpenAI's GPT series.
Douglas, Michael R.
core   +4 more sources

Emergent Abilities of Large Language Models [PDF]

Trans. Mach. Learn. Res., 2022
Scaling up language models has been shown to predictably improve performance and sample efficiency on a wide range of downstream tasks. This paper instead discusses an unpredictable phenomenon that we refer to as emergent abilities of large language ...
Jason Lee, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H., Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus   +15 more
openalex   +3 more sources

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
doaj   +5 more sources

Large language models in medicine

Nature Medicine, 2023
Large language models (LLMs) can respond to free-text queries without being specifically trained in the task in question, causing excitement and concern about their use in healthcare settings. ChatGPT is a generative artificial intelligence (AI) chatbot produced through sophisticated fine-tuning of an LLM, and other tools are emerging through similar ...
A. J. Thirunavukarasu, D. Ting, Kabilan Elangovan, Laura Gutierrez, Ting Fang Tan, D. Ting   +5 more
semanticscholar   +3 more sources

Paraphrasing with Large Language Models [PDF]

Proceedings of the 3rd Workshop on Neural Generation and Translation, 2019
Recently, large language models such as GPT-2 have shown themselves to be extremely adept at text generation and have also been able to achieve high-quality results in many downstream NLP tasks such as text classification, sentiment analysis and question
Andrews, Martin, Witteveen, Sam
core   +3 more sources

Large Language Models Encode Clinical Knowledge [PDF]

Nature, 2022
Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, but the quality bar for medical and clinical applications is high.
Arcas, Blaise Aguera y, Azizi, Shekoofeh, Barral, Joelle, Chou, Katherine, Chowdhery, Aakanksha, Chung, Hyung Won, Cole-Lewis, Heather, Corrado, Greg S., Gamble, Paul, Gottweis, Juraj, Karthikesalingam, Alan, Kelly, Chris, Liu, Yun, Mahdavi, S. Sara, Mansfield, Philip, Matias, Yossi, Natarajan, Vivek, Payne, Perry, Pfohl, Stephen, Rajkomar, Alvin, Scales, Nathan, Scharli, Nathaneal, Semturs, Christopher, Seneviratne, Martin, Singhal, Karan, Tanwani, Ajay, Tomasev, Nenad, Tu, Tao, Webster, Dale, Wei, Jason   +29 more
core   +2 more sources

Talking About Large Language Models

Communications of the ACM, 2022
Thanks to rapid progress in artificial intelligence, we have entered an era when technology and philosophy intersect in interesting ways. Sitting squarely at the centre of this intersection are large language models (LLMs).
Shanahan, Murray
core   +3 more sources

A Watermark for Large Language Models [PDF]

International Conference on Machine Learning, 2023
Potential harms of large language models can be mitigated by watermarking model output, i.e., embedding signals into generated text that are invisible to humans but algorithmically detectable from a short span of tokens.
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, T. Goldstein   +5 more
semanticscholar   +3 more sources

Large Language Models are Biased Because They Are Large Language Models

This paper's primary goal is to provoke thoughtful discussion about the relationship between bias and fundamental properties of large language models. We do this by seeking to convince the reader that harmful biases are an inevitable consequence arising ...
Resnik, Philip
core   +2 more sources