Deep Learning and its applications have cascaded impactful research and development
with a diverse range of modalities present in the real-world data. More recently, this has …

Trained with an unprecedented scale of data, large language models (LLMs) like ChatGPT
and GPT-4 exhibit the emergence of significant reasoning abilities from model scaling. Such …

Embodied AI aims to create agents that complete complex tasks by interacting with the
environment. A key problem in this field is embodied navigation which understands multi …

Abstract Vision-and-Language Navigation requires the agent to follow language instructions
to navigate through 3D environments. One main challenge in Vision-and-Language …

Accuracy of many visiolinguistic tasks has benefited significantly from the application of
vision-and-language (V&L) BERT. However, its application for the task of vision-and …

We introduce Room-Across-Room (RxR), a new Vision-and-Language Navigation (VLN)
dataset. RxR is multilingual (English, Hindi, and Telugu) and larger (more paths and …

Building a generalist agent that can interact with the world is an ultimate goal for humans
thus spurring the research for embodied navigation where an agent is required to navigate …

A long-term goal of AI research is to build intelligent agents that can communicate with
humans in natural language, perceive the environment, and perform real-world tasks. Vision …

Vision-and-language navigation (VLN) aims to enable embodied agents to navigate in
realistic environments using natural language instructions. Given the scarcity of domain …

Abstract Many Vision-and-Language Navigation (VLN) tasks have been proposed in recent
years, from room-based to object-based and indoor to outdoor. The REVERIE (Remote …