53 citations · 102 across the 3 of their papers we have counts for
3 papers
cs.RO2023★ 2 cited
Evaluating Continual Learning on a Home Robot
Sam Powers, Abhinav Gupta, Chris Paxton
Robots in home environments need to be able to learn new skills continuously as data becomes available, becoming ever more capable over time while using as little real-world data a…
cs.LG2022★ 53 cited
Pre-Trained Language Models for Interactive Decision-Making
Shuang Li, Xavier Puig, Chris Paxton +11
Language model (LM) pre-training is useful in many language processing tasks. But can pre-trained LMs be further leveraged for more general machine learning problems? We propose an…
cs.RO2019★ 47 cited
"Good Robot!": Efficient Reinforcement Learning for Multi-Step Visual Tasks with Sim to Real Transfer
Andrew Hundt, Benjamin Killeen, Nicholas Greene +4
Current Reinforcement Learning (RL) algorithms struggle with long-horizon tasks where time can be wasted exploring dead ends and task progress may be easily reversed. We develop th…