More than one hundred benchmarks have been developed to test the commonsense
knowledge and commonsense reasoning abilities of artificial intelligence (AI) systems …

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 …

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 introduce Habitat 2.0 (H2. 0), a simulation platform for training virtual robots in
interactive 3D environments and complex physics-enabled scenarios. We make …

Massive datasets and high-capacity models have driven many recent advancements in
computer vision and natural language understanding. This work presents a platform to …

Multi-object rearrangement is a crucial skill for service robots, and commonsense reasoning
is frequently needed in this process. However, achieving commonsense arrangements …

Prompt-based learning has emerged as a successful paradigm in natural language
processing, where a single general-purpose language model can be instructed to perform …

We present BEHAVIOR-1K, a comprehensive simulation benchmark for human-centered
robotics. BEHAVIOR-1K includes two components, guided and motivated by the results of an …

Contrastive language image pretraining (CLIP) encoders have been shown to be beneficial
for a range of visual tasks from classification and detection to captioning and image …

Existing image editing tools, while powerful, typically disregard the underlying 3D geometry
from which the image is projected. As a result, edits made using these tools may become …