163 citations · 202 across the 15 of their papers we have counts for
15 papers
RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots
Soroush Nasiriany, Abhiram Maddukuri, Lance Zhang +5
Recent advancements in Artificial Intelligence (AI) have largely been propelled by scaling. In Robotics, scaling is hindered by the lack of access to massive robot datasets. We adv…
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
Soroush Nasiriany, Fei Xia, Wenhao Yu +20
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 interactio…
MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations
Ajay Mandlekar, Soroush Nasiriany, Bowen Wen +5
Imitation learning from a large set of human demonstrations has proved to be an effective paradigm for building capable robot agents. However, the demonstrations can be extremely c…
Interactive Robot Learning from Verbal Correction
Huihan Liu, Alice Chen, Yuke Zhu +3
The ability to learn and refine behavior after deployment has become ever more important for robots as we design them to operate in unstructured environments like households. In th…
Learning Generalizable Manipulation Policies with Object-Centric 3D Representations
Yifeng Zhu, Zhenyu Jiang, Peter Stone +1
We introduce GROOT, an imitation learning method for learning robust policies with object-centric and 3D priors. GROOT builds policies that generalize beyond their initial training…
Cross-Episodic Curriculum for Transformer Agents
Lucy Xiaoyang Shi, Yunfan Jiang, Jake Grigsby +2
We present a new algorithm, Cross-Episodic Curriculum (CEC), to boost the learning efficiency and generalization of Transformer agents. Central to CEC is the placement of cross-epi…