Recently human–robot collaboration (HRC) has emerged as a promising paradigm for mass
personalization in manufacturing owing to the potential to fully exploit the strength of human …

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 …

Most existing Vision-and-Language (V&L) models rely on pre-trained visual encoders, using
a relatively small set of manually-annotated data (as compared to web-crawled data), to …

Vision-and-language navigation (VLN) aims to build autonomous visual agents that follow
instructions and navigate in real scenes. To remember previously visited locations and …

Following language instructions to navigate in unseen environments is a challenging
problem for autonomous embodied agents. The agent not only needs to ground languages …

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 …

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 …

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

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 …