Rafael Rafailov

MOTO enhances robot learning by combining offline training with online fine-tuning.

This study evaluates methods to enhance large language models using user preference data.

Examining over-optimization in DAAs and its impact on model performance.

A new model enables robots to learn tasks better using visual and language inputs.

A new method to assess diverse user values in language models.