· 2020
Transformers: State-of-the-Art Natural Language Processing
- 8,108citations
- 2020year
Short summary
This paper introduces the Transformer architecture, a novel deep learning model that achieves state-of-the-art results in natural language processing tasks.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduces the Transformer architecture, a novel deep learning model for NLP.
- Relies entirely on self-attention mechanisms, eschewing recurrence and convolutions.
- Enables significant parallelization and captures long-range dependencies effectively.
- Achieves state-of-the-art results on multiple NLP tasks.
AI-generated from the title and abstract; the full text is not read.
Abstract
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, Alexander Rush. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations. 2020.
The authors' abstract, as published at the source., 2020 · DOI ↗
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Field: Artificial Intelligence
Artificial IntelligenceComputer Science