The term resolution refers to the width and height of images input into neural networks.

We propose a novel approach to learning the generative neural fields represented by linear combinations of implicit basis networks.

Continual learning aims to learn a sequence of tasks from dynamic data distributions.

Learning from AI feedback (LAIF) is a popular paradigm for improving the instruction-following abilities of powerful pre-trained language models.