reviewACM Computing SurveysJun 27, 2023Closed access

Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey

Amazon (United States) · Harvard University Press · +4 more institutions

Indexed incrossref

Abstract

Large, pre-trained language models (PLMs) such as BERT and GPT have drastically changed the Natural Language Processing (NLP) field. For numerous NLP tasks, approaches leveraging PLMs have achieved state-of-the-art performance. The key idea is to learn a generic, latent representation of language from a generic task once, then share it across disparate NLP tasks. Language modeling serves as the generic task, one with abundant self-supervised text available for extensive training. This article presents the key fundamental concepts of PLM architectures and a comprehensive view of the shift to PLM-driven NLP techniques. It surveys work applying the pre-training then fine-tuning, prompting, and text generation…

Citation impact

1,139
total citations
FWCI
185.61
Percentile
100%
References
169
Citations per year

Authors

9

Topics & keywords

Keywords
  • Computer science
  • Task (project management)
  • Artificial intelligence
  • Natural language processing
  • Language model
  • Key (lock)
  • Representation (politics)
  • Language understanding
UN Sustainable Development Goals
  • Quality Education
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