Google AI Researchers Propose a Noise-Aware Training Method (NAT) for Layout-Aware Language Models

Researchers from Google AI have proposed a Noise-Aware Training (NAT) method for layout-aware language models. The method aims to address the challenges in training robust document extractors within strict time constraints, with the goal of improving the efficiency and scalability of document processing workflows in enterprise environments.