Jooyeon Kim

Deriving a Data-Efficient, Generalist Agent Through World Models

This research proposes mae, the transformer WM agent that thrives in both ends, i.e., operates in multiple environments using a single set of backbone world model parameters with the limited hundred thousand training samples per environment, and validate mae’s applicability in a 3D, first-person view environment with a...