We study how vision-language models trained on Internet-scale data can b...
What makes generalization hard for imitation learning in visual robotic
...
Large language models (LLMs) have demonstrated exciting progress in acqu...
We describe a system for deep reinforcement learning of robotic manipula...
For robots to follow instructions from people, they must be able to conn...
Recent advances in robot learning have shown promise in enabling robots ...
By transferring knowledge from large, diverse, task-agnostic datasets, m...
In recent years, much progress has been made in learning robotic manipul...
We propose Token Turing Machines (TTM), a sequential, autoregressive
Tra...
The predictive information, the mutual information between the past and
...
Recent works have shown how the reasoning capabilities of Large Language...
Reinforcement learning (RL) provides a theoretical framework for continu...
Large language models can encode a wealth of semantic knowledge about th...
Robotic skills can be learned via imitation learning (IL) using user-pro...
Reinforcement learning can train policies that effectively perform compl...
We consider the problem of learning useful robotic skills from previousl...
We study reinforcement learning in settings where sampling an action fro...
We propose learning from teleoperated play data (LfP) as a way to scale ...