1 Jun 2017 Jahr - Transformer architecture, a revolution in NLP (Vaswani et al.)

Beschreibung:

Vaswani et al. introduce the groundbreaking Transformer architecture, which replaces recurrent neural networks with self-attention mechanisms to process input data in parallel. This innovative approach offers increased efficiency and scalability, leading to significant improvements in a wide range of natural language processing tasks. The Transformer architecture becomes the basis for numerous state-of-the-art models, including BERT, GPT-3, T5, and many others, driving further advancements in AI and NLP.

Zugefügt zum Band der Zeit:

Datum: