activity
20152026
most citedDo As I Can, Not As I Say: Grounding Language in Robotic Affordances

524 citations · 1.9k across the 45 of their papers we have counts for

collaborators
Showing 2023Show all

15 papers · 1 filter

cs.RO2023★ 13 cited

Foundation Models in Robotics: Applications, Challenges, and the Future

Roya Firoozi, Johnathan Tucker, Stephen Tian +12

We survey applications of pretrained foundation models in robotics. Traditional deep learning models in robotics are trained on small datasets tailored for specific tasks, which li…

cs.CL2023★ 12 cited

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Chengshu Li, Jacky Liang, Andy Zeng +7

Code provides a general syntactic structure to build complex programs and perform precise computations when paired with a code interpreter - we hypothesize that language models (LM…

cs.RO2023★ 2 cited

RoboVQA: Multimodal Long-Horizon Reasoning for Robotics

Pierre Sermanet, Tianli Ding, Jeffrey Zhao +18

We present a scalable, bottom-up and intrinsically diverse data collection scheme that can be used for high-level reasoning with long and medium horizons and that has 2.2x higher t…

cs.LG2023

Conditionally Combining Robot Skills using Large Language Models

K. R. Zentner, Ryan Julian, Brian Ichter +1

This paper combines two contributions. First, we introduce an extension of the Meta-World benchmark, which we call "Language-World," which allows a large language model to operate…

cs.CV2023★ 3 cited

Video Language Planning

Yilun Du, Mengjiao Yang, Pete Florence +10

We are interested in enabling visual planning for complex long-horizon tasks in the space of generated videos and language, leveraging recent advances in large generative models pr…

cs.RO2023★ 14 cited

Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning

Dhruv Shah, Michael Equi, Blazej Osinski +3

Navigation in unfamiliar environments presents a major challenge for robots: while mapping and planning techniques can be used to build up a representation of the world, quickly di…