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 …

Incremental decision making in real-world environments is one of the most challenging tasks
in embodied artificial intelligence. One particularly demanding scenario is Vision and …

Abstract In Vision-and-Language Navigation (VLN), an agent needs to navigate through the
environment based on natural language instructions. Due to limited available data for agent …

Large-scale language models, like ChatGPT, have garnered significant media attention and
stunned the public with their remarkable capacity for generating coherent text from short …

People navigating in unfamiliar buildings take advantage of myriad visual, spatial and
semantic cues to efficiently achieve their navigation goals. Towards equipping …

Vision-language navigation (VLN) tasks require an agent to follow language instructions
from a human guide to navigate in previously unseen environments using visual …

Vision-and-language navigation (VLN) is a multimodal task where an agent follows natural
language instructions and navigates in visual environments. Multiple setups have been …

We investigate the Vision-and-Language Navigation (VLN) problem in the context of
autonomous driving in outdoor settings. We solve the problem by explicitly grounding the …

We present a novel method for using agent experiences gathered through an embodied
simulation to ground contextualized word vectors to object representations. We use similarity …

Vision and Language Navigation (VLN) is a challenging task that requires agents to
understand instructions and navigate to the destination in a visual environment. One of the …