We present a retrospective on the state of Embodied AI research. Our analysis focuses on
13 challenges presented at the Embodied AI Workshop at CVPR. These challenges are …

Deep Learning has revolutionized our ability to solve complex problems such as Vision-and-
Language Navigation (VLN). This task requires the agent to navigate to a goal purely based …

We present a novel interactive learning protocol that enables training request-fulfilling
agents by verbally describing their activities. Unlike imitation learning (IL), our protocol …

This paper presents a novel approach for the Vision-and-Language Navigation (VLN) task in
continuous 3D environments, which requires an autonomous agent to follow natural …

Abstract We present Iterative Vision-and-Language Navigation (IVLN), a paradigm for
evaluating language-guided agents navigating in a persistent environment over time …

The speaker-follower models have proven to be effective in vision-and-language navigation,
where a speaker model is used to synthesize new instructions to augment the training data …

To be successful, Vision-and-Language Navigation (VLN) agents must be able to ground
instructions to actions based on their surroundings. In this work, we develop a methodology …

Vision-and-Language Navigation (VLN) tasks require an agent to navigate through the
environment based on language instructions. In this paper, we aim to solve two key …

Recent work studies the cognitive capabilities of language models through psychological
tests designed for humans. While these studies are helpful for understanding the general …

Understanding the geometric relationships between objects in a scene is a core capability in
enabling both humans and autonomous agents to navigate in new environments. A sparse …