The past decade has seen the rapid development of a new approach to pragmatics that
attempts to integrate insights from formal and experimental semantics and pragmatics …

Relating individual brain patterns to behaviour is fundamental in system neuroscience.
Recently, the predictive modelling approach has become increasingly popular, largely due …

Large" instruction-tuned" language models (ie, finetuned to respond to instructions) have
demonstrated a remarkable ability to generalize zero-shot to new tasks. Nevertheless, they …

This study focuses on using large language models (LLMs) as a planner for embodied
agents that can follow natural language instructions to complete complex tasks in a visually …

Grounding language to the visual observations of a navigating agent can be performed
using off-the-shelf visual-language models pretrained on Internet-scale data (eg, image …

Can world knowledge learned by large language models (LLMs) be used to act in
interactive environments? In this paper, we investigate the possibility of grounding high-level …

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 …

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 …

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