Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey
Amazon (United States) · Harvard University Press · +4 more institutions
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
- FWCI
- 185.61
- Percentile
- 100%
- References
- 169
Authors
9Topics & keywords
- Computer science
- Task (project management)
- Artificial intelligence
- Natural language processing
- Language model
- Key (lock)
- Representation (politics)
- Language understanding
- Quality Education