A learning apparatus converts documents and tags into images to train network models using visual data.
Automated scoring aligns expert evaluations with system answers, resolving feedback cycle delays that hinder training data accuracy.
Transformer models generate diverse questions from tables and text, resolving the contradiction between template efficiency and question quality.