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Foundation Models for Natural Language Processing

Gerhard Paaß, Sven Giesselbach - Personal Name;

This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts.

Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models.


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Detail Information
Series Title
Artificial Intelligence: Foundations, Theory, and Algorithms
Call Number
XVIII, 436
Publisher
Springer Cham : Springer Cham., 2023
Collation
-
Language
English
ISBN/ISSN
978-3-031-23190-2
Classification
NONE
Content Type
text
Media Type
computer
Carrier Type
online resource
Edition
1
Subject(s)
Natural Language Processing (NLP)
Machine Learning
Specific Detail Info
-
Statement of Responsibility
Gerhard Paaß, Sven Giesselbach
Other Information
Cataloger
-
Source
https://link.springer.com/book/10.1007/978-3-031-23190-2
Validator
Suwardi
Digital Object Identifier (DOI)
https://doi.org/10.1007/978-3-031-23190-2
Journal Volume
-
Journal Issue
-
Subtitle
-
Parallel Title
-
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No other version available

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