Vision systems that see and reason about the compositional nature of visual scenes are
fundamental to understanding our world. The complex relations between objects and their …

The fusion of large language models and robotic systems has introduced a transformative
paradigm in human–robot interaction, offering unparalleled capabilities in natural language …

Large language models (LLMs) have demonstrated remarkable zero-shot generalization
abilities: state-of-the-art chatbots can provide plausible answers to many common questions …

We survey applications of pretrained foundation models in robotics. Traditional deep
learning models in robotics are trained on small datasets tailored for specific tasks, which …

Recent efforts have incorporated large language models (LLMs) with external resources (eg,
the Internet) or internal control flows (eg, prompt chaining) for tasks requiring grounding or …

Building general-purpose robots that operate seamlessly in any environment, with any
object, and utilizing various skills to complete diverse tasks has been a long-standing goal in …

Recent developments in foundation models, like Large Language Models (LLMs) and Vision-
Language Models (VLMs), trained on extensive data, facilitate flexible application across …

In this study, we are interested in imbuing robots with the capability of physically-grounded
task planning. Recent advancements have shown that large language models (LLMs) …

Today's robot policies exhibit subpar performance when faced with the challenge of
generalizing to novel environments. Human corrective feedback is a crucial form of …

As robots acquire increasingly sophisticated skills and see increasingly complex and varied
environments, the threat of an edge case or anomalous failure is ever present. For example …