Computational intensiveness of deep learning has motivated low-precision arithmetic designs.

Motivated by our analysis results, we propose new data augmentation methods aimed at enhancing model generalization.

Educational recommendation lies in constructing a recommend system that can process the interactions between students and questions.

The focus of our work is on diagnostic tasks in personalized learning, such as cognitive diagnosis and knowledge tracing. The goal of these tasks is to assess students'

The development of foundation vision models has pushed the general visual recognition to a high level, but cannot well address the fine-grained recognition in specialized domain such as invasive species classification. Identifying and managing invasive species has strong social and ecological value.

Unlike the case for text--wherein every document written in a given language shares a basic lexicon for tokenization--there is no one-to-one correspondence between neurons in different individuals.

Deep neural networks (DNNs) are ubiquitous in computer vision and natural language processing, but suffer from high inference cost.