  We present R+X, a framework which enables robots to learn skills from long,
unlabelled, first-person videos of humans performing everyday tasks. Given a
language command from a human, R+X first retrieves short video clips containing
relevant behaviour, and then executes the skill by conditioning an in-context
imitation learning method on this behaviour. By leveraging a Vision Language
Model (VLM) for retrieval, R+X does not require any manual annotation of the
videos, and by leveraging in-context learning for execution, robots can perform
commanded skills immediately, without requiring a period of training on the
retrieved videos. Experiments studying a range of everyday household tasks show
that R+X succeeds at translating unlabelled human videos into robust robot
skills, and that R+X outperforms several recent alternative methods. Videos are
available at https://www.robot-learning.uk/r-plus-x.
