Recent advances in the areas of multimodal machine learning and artificial intelligence (AI)
have led to the development of challenging tasks at the intersection of Computer Vision …

We present a large-scale study of imitating human demonstrations on tasks that require a
virtual robot to search for objects in new environments-(1) ObjectGoal Navigation (eg'find & …

Moving around in the world is naturally a multisensory experience, but today's embodied
agents are deaf—restricted to solely their visual perception of the environment. We introduce …

Abstract ObjectGoal Navigation (ObjectNav) is an embodied task wherein agents are to
navigate to an object instance in an unseen environment. Prior works have shown that end …

Experience precedes understanding. Humans constantly explore and learn about their
environment out of curiosity, gather information, and update their models of the world. On the …

Autonomous agents must learn to collaborate. It is not scalable to develop a new centralized
agent every time a task's difficulty outpaces a single agent's abilities. While multi-agent …

With the recent development of deep learning, AI models are widely used in various
domains. AI models show good performance for definite tasks such as image classification …

Text-based games provide an interactive way to study natural language processing. While
deep reinforcement learning has shown effectiveness in developing the game playing …

Unsupervised visual representation learning offers the opportunity to leverage large corpora
of unlabeled trajectories to form useful visual representations, which can benefit the training …

Large-scale generative language and vision-language models (LLMs and VLMs) excel in
few-shot in-context learning for decision making and instruction following. However, they …