What do we want from machine intelligence? We envision machines that are not just tools
for thought but partners in thought: reasonable, insightful, knowledgeable, reliable and …

Unlike previous studies on the Metaverse based on Second Life, the current Metaverse is
based on the social value of Generation Z that online and offline selves are not different …

Can world knowledge learned by large language models (LLMs) be used to act in
interactive environments? In this paper, we investigate the possibility of grounding high-level …

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 …

While large language models (LMs) have shown remarkable capabilities across numerous
tasks, they often struggle with simple reasoning and planning in physical environments …

Abstract Language model (LM) pre-training is useful in many language processing tasks.
But can pre-trained LMs be further leveraged for more general machine learning problems …

As artificial intelligence (AI) applications become more pervasive, it is critical to understand
how knowledge workers with different levels and types of experience can team with AI for …

Large Language Models (LLMs) have demonstrated impressive planning abilities in single-
agent embodied tasks across various domains. However, their capacity for planning and …

Large Language Models (LLMs) have the capacity of performing complex scheduling in a
multi-agent system and can coordinate these agents into completing sophisticated tasks that …

We present Habitat 3.0: a simulation platform for studying collaborative human-robot tasks in
home environments. Habitat 3.0 offers contributions across three dimensions:(1) Accurate …