117 citations · 488 across the 32 of their papers we have counts for
11 papers · 1 filter
CLIP-Nav: Using CLIP for Zero-Shot Vision-and-Language Navigation
Vishnu Sashank Dorbala, Gunnar Sigurdsson, Robinson Piramuthu +2
Household environments are visually diverse. Embodied agents performing Vision-and-Language Navigation (VLN) in the wild must be able to handle this diversity, while also following…
Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems
Wang Zhu, Jesse Thomason, Robin Jia
For vision-and-language reasoning tasks, both fully connectionist, end-to-end methods and hybrid, neuro-symbolic methods have achieved high in-distribution performance. In which ou…
Retrospectives on the Embodied AI Workshop
Matt Deitke, Dhruv Batra, Yonatan Bisk +36
We present a retrospective on the state of Embodied AI research. Our analysis focuses on 13 challenges presented at the Embodied AI Workshop at CVPR. These challenges are grouped i…
Iterative Vision-and-Language Navigation
Jacob Krantz, Shurjo Banerjee, Wang Zhu +4
We present Iterative Vision-and-Language Navigation (IVLN), a paradigm for evaluating language-guided agents navigating in a persistent environment over time. Existing Vision-and-L…
ProgPrompt: Generating Situated Robot Task Plans using Large Language Models
Ishika Singh, Valts Blukis, Arsalan Mousavian +6
Task planning can require defining myriad domain knowledge about the world in which a robot needs to act. To ameliorate that effort, large language models (LLMs) can be used to sco…
VAuLT: Augmenting the Vision-and-Language Transformer for Sentiment Classification on Social Media
Georgios Chochlakis, Tejas Srinivasan, Jesse Thomason +1
We propose the Vision-and-Augmented-Language Transformer (VAuLT). VAuLT is an extension of the popular Vision-and-Language Transformer (ViLT), and improves performance on vision-an…