Amazon’s X-Transformer tackles industrial-scale text classification

Venture Beat | Jun 29, 2020 at 7:30 PM
  • In a preprint paper published on Arxiv.org, researchers at Amazon, Carnegie Mellon, and the University of Texas at Austin describe X-Transformer, an approach to tuning language algorithms to the problem of returning labels from large data sets.
  • X-Transformer, which builds on Google’s existing Transformer architecture, consists of a semantic label indexing component, a deep neural matching component, and an ensemble ranking component.
  • Next, the deep neural matching component fine-tunes a Transformer model for each SLI-induced XMC sub-problem.