Intelligent agents stand out as a potential path toward artificial general intelligence (AGI).
Thus, researchers have dedicated significant effort to diverse implementations for them …

Autonomous robots are increasingly served in real-world unstructured human environments
with complex long-horizon tasks, such as restaurant serving and office delivery. Task and …

Large-scale task planning is a major challenge. Recent work exploits large language
models (LLMs) directly as a policy and shows surprisingly interesting results. This paper …

Abstract We propose Text2Motion, a language-based planning framework enabling robots
to solve sequential manipulation tasks that require long-horizon reasoning. Given a natural …

Recent advances in large language models (LLMs) have transformed the field of natural
language processing (NLP). From GPT-3 to PaLM, the state-of-the-art performance on …

Abstract As Large Language Models (LLMs) have shown significant intelligence, the
progress to leverage LLMs as planning modules of autonomous agents has attracted more …

While large language models (LLMs) excel in a simulated world of texts they struggle to
interact with the more realistic world without perceptions of other modalities such as visual or …

We show that large language models (LLMs) can be adapted to be generalizable policies
for embodied visual tasks. Our approach, called Large LAnguage model Reinforcement …

Intrigued by the claims of emergent reasoning capabilities in LLMs trained on general web
corpora, in this paper, we set out to investigate their planning capabilities. We aim to …

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