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 …

The ability to perform effective planning is crucial for building an instruction-following agent.
When navigating through a new environment, an agent is challenged with (1) connecting the …

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 challenging task that requires an agent to
navigate in real-world environments by understanding natural language instructions and …

For embodied reinforcement learning (RL) agents interacting with the environment, it is
desirable to have rapid policy adaptation to unseen visual observations, but achieving zero …

For embodied reinforcement learning (RL) agents interacting with the environment, it is
desirable to have rapid policy adaptation to unseen visual observations, but achieving zero …

When adopting a deep learning model for embodied agents it is required that the model
structure be optimized for specific tasks and operational conditions. Such optimization can …

Navigation guided by natural language instructions is particularly suitable for Domestic
Service Robots that interacts naturally with users. This task involves the prediction of a …

In recent years, vision-language research has shifted to study tasks which require more
complex reasoning, such as interactive question answering, visual common sense …

As a long-term vision in the field of artificial intelligence, the core goal of embodied
intelligence is to improve the perception, understanding, and interaction capabilities of …