A Transformer-based Neural Architecture Search Method
PositiveArtificial Intelligence
A new paper introduces an innovative neural architecture search method that leverages Transformer architecture to enhance translation results. By exploring various combinations of encoder and decoder configurations and using perplexity alongside traditional BLEU scores, this approach aims to optimize neural network structures. This advancement is significant as it could lead to improved machine translation systems, making communication across languages more effective.
— Curated by the World Pulse Now AI Editorial System


