Vision language models (VLMs) have shown impressive capabilities across a variety of
tasks, from logical reasoning to visual understanding. This opens the door to richer …

Vision-Language Models (VLMs) have demonstrated their widespread viability thanks to
extensive training in aligning visual instructions to answers. However, this conclusive …

Open-vocabulary generalization requires robotic systems to perform tasks involving complex
and diverse environments and task goals. While the recent advances in vision language …

Visual language tasks such as Visual Question Answering (VQA) or Visual Entailment (VE)
require AI models to comprehend and reason with both visual and textual content. Driven by …

Visually-conditioned language models (VLMs) have seen growing adoption in applications
such as visual dialogue, scene understanding, and robotic task planning; adoption that has …

Advancements in large language models (LLMs) have demonstrated their potential in
facilitating high-level reasoning, logical reasoning and robotics planning. Recently, LLMs …

Vision-Language Models (VLMs) such as GPT-4V have recently demonstrated incredible
strides on diverse vision language tasks. We dig into vision-based deductive reasoning, a …

A robot that can carry out a natural-language instruction has been a dream since before the
Jetsons cartoon series imagined a life of leisure mediated by a fleet of attentive robot …

Recent progress in vision language foundation models has shown their ability to understand
multimodal data and resolve complicated vision language tasks, including robotics …

We study how vision-language models trained on Internet-scale data can be incorporated
directly into end-to-end robotic control to boost generalization and enable emergent …