Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

Large language models excel at a wide range of complex tasks. However, enabling general
inference in the real world, eg, for robotics problems, raises the challenge of grounding. We …

We present VISPROG, a neuro-symbolic approach to solving complex and compositional
visual tasks given natural language instructions. VISPROG avoids the need for any task …

Large language models (LLMs) are shown to possess a wealth of actionable knowledge that
can be extracted for robot manipulation in the form of reasoning and planning. Despite the …

This study focuses on using large language models (LLMs) as a planner for embodied
agents that can follow natural language instructions to complete complex tasks in a visually …

This paper presents an experimental study regarding the use of OpenAI's ChatGPT for
robotics applications. We outline a strategy that combines design principles for prompt …

For a robot to personalize physical assistance effectively, it must learn user preferences that
can be generally reapplied to future scenarios. In this work, we investigate personalization of …

We study how vision-language models trained on Internet-scale data can be incorporated
directly into end-to-end robotic control to boost generalization and enable emergent …