Generating Human-level Text with Contrastive Search in Transformers

This article likely discusses a new method for generating text using transformer models. The focus is on 'contrastive search,' which suggests the approach involves comparing and contrasting different text generation possibilities to improve quality. The mention of 'human-level text' implies the goal is to produce text that is indistinguishable from human-written content. The use of 'Transformers' indicates the underlying architecture is based on the popular neural network model. The article probably details the technical aspects of contrastive search, its implementation, and the results achieved in terms of text quality and fluency. It may also compare the method to other text generation techniques.

• •The article likely introduces a new text generation method.
• •The method uses contrastive search within a Transformer architecture.
• •The goal is to generate text that is comparable to human-written text.